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welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: My mistakes on the path to impact, published by Denise_Melchin on the effective altruism forum. Doing a lot of good has been a major priority in my life for several years now. Unfortunately I made some substantial mistakes which have lowered my expected impact a lot, and I am on a less promising trajectory than I would have expected a few years ago. In the hope that other people can learn from my mistakes, I thought it made sense to write them up here! I will attempt to list the mistakes which lowered my impact most over the past several years in this post and then analyse their causes. Writing this post and previous drafts has also been very personally useful to me, and I can recommend undertaking such an analysis. Please keep in mind that my analysis of my mistakes is likely at least a bit misguided and incomprehensive. It would have been nice to condense the post a bit more and structure it better, but having already spent a lot of time on it and wanting to move on to other projects, I thought it would be best not to let the perfect be the enemy of the good! To put my mistakes into context, I will give a brief outline of what happened in my career-related life in the past several years before discussing what I consider to be my main mistakes. Background I came across the EA Community in 2012, a few months before I started university. Before that point my goal had always been to become a researcher. Until early 2017, I did a mathematics degree in Germany and received a couple of scholarships. I did a lot of ‘EA volunteering’ over the years, mostly community building and large-scale grantmaking. I also did two unpaid internships at EA orgs, one during my degree and one after graduating, in summer 2017. After completing my summer internship, I started to try to find a role at an EA org. I applied to ~7 research and grantmaking roles in 2018. I got to the last stage 4 times, but received no offers. The closest I got was receiving a 3-month-trial offer as a Research Analyst at Open Phil, but it turned out they were unable to provide visas. In 2019, I worked as a Research Assistant for a researcher at an EA aligned university institution on a grant for a few hundred hours. I stopped as there seemed to be no route to a secure position and the role did not seem like a good fit. In late 2019 I applied for jobs suitable for STEM graduates with no experience. I also stopped doing most of my EA volunteering. In January 2020 I began to work in an entry-level data analyst role in the UK Civil Service which I have been really happy with. In November, after 6.5mon full-time equivalent worked, I received a promotion to a more senior role with management responsibility and a significant pay rise. First I am going to discuss what I think I did wrong from a first-order practical perspective. Afterwards I will explain which errors in my decision making process I consider the likely culprits for these mistakes - the patterns of behaviour which need to be changed to avoid similar mistakes in the future. A lot of the following seems pretty silly to me now, and I struggle to imagine how I ever fully bought into the mistakes and systematic errors in my thinking in the first place. But here we go! What did I get wrong? I did not build broad career capital nor kept my options open. During my degree, I mostly focused on EA community building efforts as well as making good donation decisions. I made few attempts to build skills for the type of work I was most interested in doing (research) or skills that would be particularly useful for higher earning paths (e.g. programming), especially later on. My only internships were at EA organisations in research roles. I also stopped trying to do well in my degree later on, and stopped my previously-substantial involvement in political work. In my firs...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Growth and the case against randomista development, published by HaukeHillebrandt, John G. Halstead on the effective altruism forum. Update, 3/8/2021: I (Hauke) gave a talk at Effective Altruism Global on this post: Summary Randomista development (RD) is a form of development economics which evaluates and promotes interventions that can be tested by randomised controlled trials (RCTs). It is exemplified by GiveWell (which primarily works in health) and the randomista movement in economics (which primarily works in economic development). Here we argue for the following claims, which we believe to be quite weak: Prominent economists make plausible arguments which suggest that research on and advocacy for economic growth in low- and middle-income countries is more cost-effective than the things funded by proponents of randomista development. Effective altruists have devoted too little attention to these arguments. Assessing the soundness of these arguments should be a key focus for current generation-focused effective altruists over the next few years. We hope to start a conversation on these questions, and potentially to cause a major reorientation within EA. We also believe the following stronger claims: 4. Improving health is not the best way to increase growth. 5. A ~4 person-year research effort will find donation opportunities working on economic growth in LMICs which are substantially better than GiveWell’s top charities from a current generation human welfare-focused point of view. However, economic growth is not all that matters. GDP misses many crucial determinants of human welfare, including leisure time, inequality, foregone consumption from investment, public goods, social connection, life expectancy, and so on. A top priority for effective altruists should be to assess the best way to increase human welfare outside of the constraints of randomista development, i.e. allowing intervention that have not or cannot be tested by RCTs. We proceed as follows: We define randomista development and contrast it with research and advocacy for growth-friendly policies in low- and middle-income countries. We show that randomista development is overrepresented in EA, and that, in contradistinction, research on and advocacy for growth-friendly economic policy (we refer to this as growth throughout) is underrepresented We then show why some prominent economists believe that, a priori, growth is much more effective than most RD interventions. We present a quantitative model that tries to formalize these intuitions and allows us to compare global development interventions with economic growth interventions. The model suggests that under plausible assumptions a hypothetical growth intervention can be thousands of times more cost-effective than typical RD interventions such as cash-transfers. However, when these assumptions are relaxed and compared to the very good RD interventions, growth interventions are on a similar level of effectiveness as RD interventions. We consider various possible objections and qualifications to our argument. Acknowledgements Thanks to Stefan Schubert, Stephen Clare, Greg Lewis, Michael Wiebe, Sjir Hoeijmakers, Johannes Ackva, Gregory Thwaites, Will MacAskill, Aidan Goth, Sasha Cooper, and Carl Shulman for comments. Any mistakes are our own. Opinions are ours, not those of our employers. Marinella Capriati at GiveWell commented on this piece, and the piece does not represent her views or those of GiveWell. 1. Defining Randomista Development We define randomista development (RD) as an approach to development economics which investigates, evaluates and recommends only interventions which can be tested by randomised controlled trials (RCTs). RD can take low-risk or more “hits-based” forms. Effective altruists have especially focused on the low-risk for...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Announcing my retirement, published by Aaron Gertler on the effective altruism forum. A few sharp-eyed readers noticed my imminent departure from CEA in our last quarterly report. Gold stars all around! My last day as our content specialist — and thus, my last day helping to run the Forum — is December 10th. The other moderators will continue to handle the basics, and we’re in the process of hiring my replacement. (Let me know if anyone comes to mind!) Managing this place was fun. It wasn’t always fun, but — on the whole, a good time. I’ve enjoyed giving feedback to a few hundred people, organizing some interesting AMAs, running a writing contest, building up the Digest, hosting workshops for EA groups around the world, and deleting a truly staggering number of comments advertising escort services (I’ll spare you the link). More broadly, I’ve felt a continual sense of admiration for everyone who cares about the Forum and tries to make it better — by reading, voting, posting, crossposting, commenting, tagging, Wiki-editing, bug-reporting, and/or moderating. Collectively, you’ve put in tens of thousands of hours of work to develop our strange, complicated, unique website, with scant compensation besides karma. (Now that I’m leaving, it’s time to be honest — despite the rumors, our karma isn’t the kind that gets you a better afterlife.) Thank you for everything you’ve done to make this job what it was. What’s next? In January, I’ll join Open Philanthropy as their communications officer, working to help their researchers publish more of their work. I’ll also be joining Effective Giving Quest as their first partnered streamer. Wish me luck: moderating this place sometimes felt like herding cats, but it’s nothing compared to Twitch chat. My Forum comments will be less frequent, but probably spicier. thanks for listening. to help us out with the nonlinear library or to learn more, please visit nonlinear.org.
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: My current impressions on career choice for longtermists, published by Holden Karnofsky on the effective altruism forum. This post summarizes the way I currently think about career choice for longtermists. I have put much less time into thinking about this than 80,000 Hours, but I think it's valuable for there to be multiple perspectives on this topic out there. Edited to add: see below for why I chose to focus on longtermism in this post. While the jobs I list overlap heavily with the jobs 80,000 Hours lists, I organize them and conceptualize them differently. 80,000 Hours tends to emphasize "paths" to particular roles working on particular causes; by contrast, I emphasize "aptitudes" one can build in a wide variety of roles and causes (including non-effective-altruist organizations) and then apply to a wide variety of longtermist-relevant jobs (often with options working on more than one cause). Example aptitudes include: "helping organizations achieve their objectives via good business practices," "evaluating claims against each other," "communicating already-existing ideas to not-yet-sold audiences," etc. (Other frameworks for career choice include starting with causes (AI safety, biorisk, etc.) or heuristics ("Do work you can be great at," "Do work that builds your career capital and gives you more options.") I tend to feel people should consider multiple frameworks when making career choices, since any one framework can contain useful insight, but risks being too dogmatic and specific for individual cases.) For each aptitude I list, I include ideas for how to explore the aptitude and tell whether one is on track. Something I like about an aptitude-based framework is that it is often relatively straightforward to get a sense of one's promise for, and progress on, a given "aptitude" if one chooses to do so. This contrasts with cause-based and path-based approaches, where there's a lot of happenstance in whether there is a job available in a given cause or on a given path, making it hard for many people to get a clear sense of their fit for their first-choice cause/path and making it hard to know what to do next. This framework won't make it easier for people to get the jobs they want, but it might make it easier for them to start learning about what sort of work is and isn't likely to be a fit. I’ve tried to list aptitudes that seem to have relatively high potential for contributing directly to longtermist goals. I’m sure there are aptitudes I should have included and didn’t, including aptitudes that don’t seem particularly promising from a longtermist perspective now but could become more so in the future. In many cases, developing a listed aptitude is no guarantee of being able to get a job directly focused on top longtermist goals. Longtermism is a fairly young lens on the world, and there are (at least today) a relatively small number of jobs fitting that description. However, I also believe that even if one never gets such a job, there are a lot of opportunities to contribute to top longtermist goals, using whatever job and aptitudes one does have. To flesh out this view, I lay out an "aptitude-agnostic" vision for contributing to longtermism. Some longtermism-relevant aptitudes "Organization building, running, and boosting" aptitudes[1] Basic profile: helping an organization by bringing "generally useful" skills to it. By "generally useful" skills, I mean skills that could help a wide variety of organizations accomplish a wide variety of different objectives. Such skills could include: Business operations and project management (including setting objectives, metrics, etc.) People management and management coaching (some manager jobs require specialized skills, but some just require general management-associated skills) Executive leadership (setting and enfo...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: After one year of applying for EA jobs: It is really, really hard to get hired by an EA organisation, published by EA applicant on the effective altruism forum. (I am writing this post under a pseudonym because I don’t want potential future non-EA employers to find this with a quick google search. Initially my name could be found on the CV linked in the text, but after this post was shared much more widely than I had expected, I got cold feet and removed it.) In the past 12 months, I applied for 20 positions in the EA community. I didn’t get any offer. At the end of this post, I list all those positions, and how much time I spent in the application process. Before that, I write about why I think more posts like this could be useful. Please note: The positions were all related to long-termism, EA movement building, or meta-activities (e.g. grant-making). To stress this again, I did not apply for any positions in e.g. global health or animal welfare, so what I’m going to say might not apply to these fields. Costs of applications Applying has considerable time-costs. Below, I estimate that I spent 7-8 weeks of full-time work in application processes alone. I guess it would be roughly twice as much if I factored in things like searching for positions, deciding which positions to apply for, or researching visa issues. (Edit: Some organisations reimburse for time spent in work tests/trials. I got paid in 4 of the 20 application processes. I might have gotten paid in more processes if I had advanced further). At least for me, handling multiple rejections was mentally challenging. Additionally, the process may foster resentment towards the EA community. I am aware the following statement is super in-accurate and no one is literally saying that, but sometimes this is the message I felt I was getting from the EA community: “Hey you! You know, all these ideas that you had about making the world a better place, like working for Doctors without Borders? They probably aren’t that great. The long-term future is what matters. And that is not funding constrained, so earning to give is kind of off the table as well. But the good news is, we really, really need people working on these things. We are so talent constraint. (20 applications later) . Yeah, when we said that we need people, we meant capable people. Not you. You suck.” Why I think more posts like this would have been useful for me Overall, I think it would have helped me to know just how competitive jobs in the EA community (long-termism, movement building, meta-stuff) are. I think I would have been more careful in selecting the positions I applied for and I would probably have started exploring other ways to have an impactful career earlier. Or maybe I would have applied to the same positions, but with less expectations and less of a feeling of being a total loser that will never contribute anything towards making the world a better place after being rejected once again 😊 Of course, I am just one example, and others will have different experiences. For example, I could imagine that it is easier to get hired by an EA organisation if you have work experience outside of research and hospitals (although many of the positions I applied for were in research or research-related). However, I don’t think I am a very special case. I know several people who fulfil all of the following criteria: - They studied/are studying at postgraduate level at a highly competitive university (like Oxford) or in a highly competitive subject (like medical school) - They are within the top 5% of their course - They have impressive extracurricular activities (like leading a local EA chapter, having organised successful big events, peer-reviewed publications while studying, .) - They are very motivated and EA aligned - They applied for at least 5 positi...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: EAF"s ballot initiative doubled Zurich’s development aid, published by Jonas Vollmer on the effective altruism forum. Summary In 2016, the Effective Altruism Foundation (EAF), then based in Switzerland, launched a ballot initiative asking to increase the city of Zurich’s development cooperation budget and to allocate it more effectively. In 2018, we coordinated a counterproposal with the city council that preserved the main points of our original initiative and had a high chance of success. In November 2019, the counterproposal passed with a 70% majority. Zurich’s development cooperation budget will thus increase from around $3 million to around $8 million per year. The city will aim to allocate it “based on the available scientific research on effectiveness and cost-effectiveness.” This seems to be the first time that Swiss legislation on development cooperation mentions effectiveness requirements. The initiative cost around $25,000 in financial costs and around $190,000 in opportunity costs. Depending on the assumptions, it raised a present value of $20–160 million in development funding. EAs should consider launching similar initiatives in other Swiss cities and around the world. Initial proposal and signature collection In spring 2016, the Effective Altruism Foundation (EAF), then still based in Basel, Switzerland, launched a ballot initiative asking for the city of Zurich’s development cooperation budget to be increased and to be allocated more effectively. (For information on EAF’s current focus, see this article.) We chose Zurich due to its large budget and leftist/centrist majority. I published an EA Forum post introducing the initiative and a corresponding policy paper (see English translation). (Note: In the EA Forum post, I overestimated the publicity/movement-building benefits and the probability that the original proposal would pass. I overemphasized the quantitative estimates, especially the point estimates, which don’t adequately represent the uncertainty. I underestimated the success probability of a favorable counterproposal. Also, the policy paper should have had a greater focus on hits-based, policy-oriented interventions because I think these have a chance of being even more cost-effective than more “straightforward” approaches and also tend to be viewed more favorably by professionals.) We hired people and coordinated volunteers (mostly animal rights activists we had interacted with before) to collect the required 3,000 signatures (plus 20% safety margin) over six months to get a binding ballot vote. Signatures had to be collected in person in handwritten form. For city-level initiatives, people usually collect about 10 signatures per hour, and paying people to collect signatures costs about $3 per signature on average. Picture: Start of signature collection on 25 May 2016. Picture: Submission of the initiative at Zurich’s city hall on 22 November 2016. The legislation we proposed (see the appendix) focused too strongly on Randomized Controlled Trials (RCTs) and demanded too much of a budget increase (from $3 million to $87 million per year). We made these mistakes because we had internal disagreements about the proposal and did not dedicate enough time to resolving them. This led to negative initial responses from the city council and influential charities (who thought the budget increase was too extreme, were pessimistic about the odds of success, and disliked the RCT focus), implying a <1% success probability at the ballot because public opinion tends to be heavily influenced by the city council’s official vote recommendation. At that point, we planned to retract the initiative before the vote to prevent negative PR for EA, while still aiming for a favorable counterproposal. Counterproposal As is common for Swiss ballot initiatives, the city d...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Is effective altruism growing? An update on the stock of funding vs. people, published by Benjamin_Todd on the effective altruism forum. This is a cross-post from 80,000 Hours. See part 2 on the allocation across cause areas. In 2015, I argued that funding for effective altruism – especially within meta and longtermist areas – had grown faster than the number of people interested in it, and that this was likely to continue. As a result, there would be a funding ‘overhang’, creating skill bottlenecks for the roles needed to deploy this funding. A couple of years ago, I wondered if this trend was starting to reverse. There hadn’t been any new donors on the scale of Good Ventures (the main partner of Open Philanthropy), which meant that total committed funds were growing slowly, giving the number of people a chance to catch up. However, the spectacular asset returns of the last few years and the creation of FTX, seem to have shifted the balance back towards funding. Now the funding overhang seems even larger in both proportional and absolute terms than 2015. In the rest of this post, I make some rough guesses at total committed funds compared to the number of interested people, to see how the balance of funding vs. talent might have changed over time. This will also serve as an update on whether effective altruism is growing – with a focus on what I think are the two most important metrics: the stock of total committed funds, and of committed people. This analysis also made me make a small update in favour of giving now vs. investing to give later. Here’s a summary of what’s coming up: How much funding is committed to effective altruism (going forward)? Around $46 billion. How quickly have these funds grown? About 37% per year since 2015, with much of the growth concentrated in 2020–2021. How much is being donated each year? Around $420 million, which is just over 1% of committed capital, and has grown maybe about 21% per year since 2015. How many committed community members are there? About 7,400 active members and 2,600 ‘committed’ members, growing 10–20% per year 2018–2020, and growing faster than that 2015–2017. Has the funding overhang grown or shrunk? Funding seems to have grown faster than the number of people, so the overhang has grown in both proportional and absolute terms. What might be the implications for career choice? Skill bottlenecks have probably increased for people able to think of ways to spend lots of funding effectively, run big projects, and evaluate grants. To caveat, all of these figures are extremely rough, and are mainly estimated off the top of my head. I haven’t checked them with the relevant donors, so they might not endorse these estimates. However, I think they’re better than what exists currently, and thought it was important to try to give some kind of rough update on how my thinking has changed. There are likely some significant mistakes; I’d be keen to see a more thorough version of this analysis. Overall, please treat this more like notes from a podcast than a carefully researched article. Which growth metrics matter? Broadly, the future[1] impact of effective altruism depends on the total stock of: The quantity of committed funds The number of committed people (adjusted for skills and influence) The quality of our ideas (which determine how effectively funding and labour can be turned into impact) (In economic growth models, this would be capital, labour, and productivity.) You could consider other resources like political capital, reputation, or public support as well, though we can also think of these as being a special type of labour. In this post, I’m going to focus on funding and labour. (To do an equivalent analysis for ideas, which could easily matter more, we could try to estimate whether the expected return of our best way...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Announcing "Naming What We Can"!, published by GidonKadosh, EdoArad, Davidmanheim, ShayBenMoshe, sella, Guy Raveh, Asaf Ifergan on the effective altruism forum. We hereby announce a new meta-EA institution - "Naming What We Can". Vision We believe in a world where every EA organization and any project has a beautifully crafted name. We believe in a world where great minds are free from the shackles of the agonizing need to name their own projects. Goal To name and rename every EA organization, project, thing, or person. To alleviate any suffering caused by name-selection decision paralysis Mission Using our superior humor and language articulation prowess, we will come up with names for stuff. About us We are a bunch of revolutionaries who believe in the power of correct naming. We translated over a quintillion distinct words from English to Hebrew. Some of us have read all of Unsong. One of us even read the whole bible. We spent countless fortnights debating the in and outs of our own org’s title - we Name What We Can. What Do We Do? We're here for the service of the EA community. Whatever you need to rename - we can name. Although we also rename whatever we can. Even if you didn't ask. Examples As a demonstration, we will now see some examples where NWWC has a much better name than the one currently used. 80,000 Hours => 64,620 Hours. Better fits the data and more equal toward women, two important EA virtues. Charity Entrepreneurship => Charity Initiatives. (We don't know anyone who can spell entrepreneurship on their first try. Alternatively, own all of the variations: Charity Enterpeneurship, Charity Entreprenreurshrip, Charity Entrepenurship, Charity Entepenoorship, .) Global Priorities Institute => Glomar Priorities Institute. We suggest including the dimension of time, making our globe a glome. OpenPhil => Doing Right Philanthropy. Going by Dr.Phil would give a lot more clicks. EA Israel => זולתנים יעילים בארץ הקודש ProbablyGood => CrediblyGood. Because in EA we usually use credence rather than probability. EA Hotel => Centre for Enabling EA Learning & Research. Giving What We Can => Guilting Whoever We Can. Because people give more when they are feeling guilty about being rich. Cause Prioritization => Toby Ordering. Max Dalton => Max Delta. This represents the endless EA effort to maximize our ever-marginal utility. Will MacAskill => will McAskill. Evidently a more common use: Peter singer & steven pinker should be the same person, to avoid confusion. OpenAI => ProprietaryAI. Followed by ClosedAI, UnalignedAI, MisalignedAI, and MalignantAI. FHI => Bostrom's Squad. GiveWell => Don'tGivePlayPumps. We feel that the message could be stronger this way. Doing Good Better => Doing Right Right. Electronic Arts, also known as EA, should change its name to Effective Altruism. They should also change all of their activities to Effective Altruism activities. Impact estimation Overall, we think the impact of the project will be net negative on expectation (see our Guesstimate model). That is because we think that the impact is likely to be somewhat positive, but there is a really small tail risk that we will cause the termination of the EA movement. However, as we are risk-averse we can mostly ignore high tails in our impact assessment so there is no need to worry. Call to action As a first step, we offer our services freely here on this very post! This is done to test the fit of the EA community to us. All you need to do is to comment on this post and ask us to name or rename whatever you desire. Additionally, we hold a public recruitment process here on this very post! If you want to apply to NWWC as a member, comment on this post with a name suggestion of your choosing! Due to our current lack of diversity in our team, we particularly encourage women, people of color, ...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Major UN report discusses existential risk and future generations (summary), published BY finm, Avital Balwit on the effective altruism forum. Co-written with Avital Balwit. Introduction and Key Points On September 10th, the Secretary General of the United Nations released a report called “Our Common Agenda”. This report seems highly relevant for those working on longtermism and existential risk, and appears to signal unexpectedly strong interest from the UN. It explicitly uses longtermist language and concepts, and suggests concrete proposals for institutions to represent future generations and manage catastrophic and existential risks. In this post we've tried summarising the report for an EA audience. Some notable features of the report: It explicitly discusses “future generations”, “long-termism”, and “existential risk” It highlights biorisks, nuclear weapons, advanced technologies, environmental disasters/climate change as extreme or even existential risks It recommends the “regulation of artificial intelligence to ensure that this is aligned with shared global values” It proposes several instruments for protecting future generations: A Futures Lab for futures impact assessments and “regularly reporting on megatrends and catastrophic risks” A Special Envoy for Future Generations to assist on “long-term thinking and foresight” and explore various international mechanisms for representing future generations, including... Repurposing the Trusteeship Council to represent the interests of future generations (a major but long-inactive organ of the UN) A Declaration on Future Generations It proposes instruments for addressing major risks: An Emergency Platform to convene key actors in response to complex global crises A Strategic Foresight and Global Risk Report to be released every 5 years It also calls for a 2023 Summit of the Future to discuss topics including these proposals addressing major risks and future generations Other topics discussed which might be of interest: Protecting and regulating the ‘digital commons’ and an internet-enabled ‘infodemic’ The governance of outer space Lethal autonomous weapons Improving pandemic response and preparedness Developing well-being indices to complement GDP Context A year ago, on the 75th anniversary of the formation of the UN, member nations asked the Secretary General, António Guterres, to produce a report with recommendations to advance the agenda of the UN. This report is his response. The report also coincides with Guterres’ re-election for his second term as Secretary General, which will begin in January 2022 and will likely last 5 years. The report was informed by consultations, listening exercises, and input from outside experts. Toby Ord (author of The Precipice) was asked to contribute to the report as such an ‘outside expert’. Among other things he underlined that ‘future generations’ does not (just) mean ‘young people’, and that international institutions should begin to address risks even more severe than COVID-19, up to and including existential risks. All of the new instruments and institutions described in the report are proposals made to the General Assembly of member nations. It remains to be seen how many of them will ultimately be implemented, and in what eventual form. Summary of the Report The report is divided into five main sections, with sections 3 and 4 being of greatest relevance from an EA or longtermist perspective. The first section situates the report in the context of the pandemic, suggesting that now is an unusually “pivotal moment” between “breakdown” and “breakthrough”. It highlights major past successes (the Montreal Protocol, the eradication of smallpox) and notes how the UN was established in the aftermath of WWII to “save succeeding generations” from war. It then calls for a “new globa...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Don't Be Bycatch, published by AllAmericanBreakfast on the effective altruism forum. It's a common story. Someone who's passionate about EA principles, but has little in the way of resources, tries and fails to do EA things. They write blog posts, and nothing happens. They apply to jobs, and nothing happens. They do research, and don't get that grant. Reading articles no longer feels exciting, but like a chore, or worse: a reminder of their own inadequacy. Anybody who comes to this place, I heartily sympathize, and encourage them to disentangle themselves from this painful situation any way they can. Why does this happen? Well, EA has two targets. Subscribers to EA principles who the movement wants to become big donors or effective workers. Big donors and effective workers who the movement wants to subscribe to EA principles. I won't claim what weight this community and its institutions give to (1) vs. (2). But when we set out to catch big fish, we risk turning the little fish into bycatch. The technical term for this is churn. Part of the issue is the planner's fallacy. When we're setting out, we underestimate how long and costly it will be to achieve an impact, and overestimate what we'll accomplish. The higher above average you aim for, the more likely you are to fall short. And another part is expectation-setting. If the expectation right from the get-go is that EA is about quickly achieving big impact, almost everyone will fail, and think they're just not cut out for it. I wish we had a holiday that was the opposite of Petrov Day, where we honored somebody who went a little bit out of their comfort zone to try and be helpful in a small and simple way. Or whose altruistic endeavor was passionate, costly, yet ineffective, and who tried it anyway, changed their mind, and valued it as a learning experience. EA organizations and writers are doing us a favor by presenting a set of ideas that speak to us. They can't be responsible for addressing all our needs. That's something we need to figure out for ourselves. EA is often criticized for its "think global" approach. But the EA is our local, our global local. How do we help each other to help others? From one little fish in the sEA to another, this is my advice: Don't aim for instant success. Aim for 20 years of solid growth. Alice wants to maximize her chance of a 1,000% increase in her altruistic output this year. Zahara's trying to maximize her chance of a 10% increase in her altruistic output. They're likely to do very different things to achieve these goals. Don't be like Alice. Be like Zahara. Start small, temporary, and obvious. Prefer the known, concrete, solvable problem to the quest for perfection. Yes, running an EA book club or, gosh darn it, picking up trash in the park is a fine EA project to cut our teeth on. If you donate 0% of your income, donating 1% of your income is moving in the right direction. Offer an altruistic service to one person. Interview one person to find out what their needs are. Ask, don't tell. When entrepreneurs do market research, it's a good idea to avoid telling the customer about the idea. Instead, they should ask the customer about their needs and problems. How do they solve their problems right now? Then they can go back to the Batcave and consider whether their proposed solution would be an improvement. Let yourself become something, just do it a little more gradually. It's good to keep your options open, but EA can be about slowing and reducing the process of commitment, increasing the ability to turn and bend. It doesn't have to be about hard stops and hairpin turns. It's OK to take a long time to make decisions and figure things out. Build each other up. Do zoom calls. Ask each other questions. Send a message to a stranger whose blog posts you like. Form relationships, and...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Reducing long-term risks from malevolent actors, published by David_Althaus, Tobias_Baumann on the effective altruism forum. Summary Dictators who exhibited highly narcissistic, psychopathic, or sadistic traits were involved in some of the greatest catastrophes in human history. (More) Malevolent individuals in positions of power could negatively affect humanity’s long-term trajectory by, for example, exacerbating international conflict or other broad risk factors. (More) Malevolent humans with access to advanced technology—such as whole brain emulation or other forms of transformative AI—could cause serious existential risks and suffering risks. (More) We therefore consider interventions to reduce the expected influence of malevolent humans on the long-term future. The development of manipulation-proof measures of malevolence seems valuable, since they could be used to screen for malevolent humans in high-impact settings, such as heads of government or CEOs. (More) We also explore possible future technologies that may offer unprecedented leverage to mitigate against malevolent traits. (More) Selecting against psychopathic and sadistic tendencies in genetically enhanced, highly intelligent humans might be particularly important. However, risks of unintended negative consequences must be handled with extreme caution. (More) We argue that further work on reducing malevolence would be valuable from many moral perspectives and constitutes a promising focus area for longtermist EAs. (More) What do we mean by malevolence? Before we make any claims about the causal effects of malevolence, we first need to explain what we mean by the term. To this end, consider some of the arguably most evil humans in history—Hitler, Mao, and Stalin—and the distinct personality traits they seem to have shared.[1] Stalin repeatedly turned against former comrades and friends (Hershman & Lieb, 1994, ch. 15, ch. 18), gave detailed instructions on how to torture his victims, ordered their loved ones to watch (Glad, 2002, p. 13), and deliberately killed millions through various atrocities. Likewise, millions of people were tortured and murdered under Mao’s rule, often according to his detailed instructions (Dikötter, 2011; 2016; Chang & Halliday, ch. 8, ch. 23, 2007). He also took pleasure in watching acts of torture and imitating in what his victims went through (Chang & Halliday, ch. 48, 2007). Hitler was not only responsible for the death of millions, he also engaged in personal sadism. On his specific instructions, the plotters of the 1944 assassination attempt were hung by piano wires and their agonizing deaths were filmed (Glad, 2002). According to Albert Speer, “Hitler loved the film and had it shown over and over again” (Toland, 1976, p. 818). Hitler, Mao, and Stalin—and most other dictators—also poured enormous resources into the creation of personality cults, manifesting their colossal narcissism (Dikötter, 2019). (The section Malevolent traits of Hitler, Mao, Stalin, and other dictators in Appendix B provides more evidence.) Many scientific constructs of human malevolence could be used to summarize the relevant psychological traits shared by Hitler, Mao, Stalin, and other malevolent individuals in positions of power. We focus on the Dark Tetrad traits (Paulhus, 2014) because they seem especially relevant and have been studied extensively by psychologists. The Dark Tetrad comprises the following four traits—the more well-known Dark Triad (Paulhus & Williams, 2002) refers to the first three traits: Machiavellianism is characterized by manipulating and deceiving others to further one’s own interests, indifference to morality, and obsession with achieving power or wealth. Narcissism involves an inflated sense of one’s importance and abilities, an excessive need for admiration, a lack of emp...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Problem areas beyond 80,000 Hours' current priorities, published by Ardenlk on the effective altruism forum. Why we wrote this post At 80,000 Hours we've generally focused on finding the most pressing issues and the best ways to address them. But even if some issue is 'the most pressing'—in the sense of being the highest impact thing for someone to work on if they could be equally successful at anything—it might easily not be the highest impact thing for many people to work on, because people have various talents, experience, and temperaments. Moreover, the more people involved in a community, the more reason there is for them to spread out over different issues. There will eventually be diminishing returns as more people work on the same set of issues, and both the value of information and the value of capacity building from exploring more areas will be greater if more people are able to take advantage of that work. We're also pretty uncertain which problems are the highest impact things to work on—even for people who could work on anything equally successfully. For example, maybe we should be focusing much more on preventing great power conflict than we have been. After all, the first plausible existential risk to humanity was the creation of the atom bomb; it's easy to imagine that wars could incubate other, even riskier technological advancements. Or maybe there is some dark horse cause area—like research into surveillance—that will turn out to be way more important for improving the future than we thought. Perhaps for these reasons, many of our advisors guess that it would be ideal if 5-20% of the effective altruism community's resources were focused on issues that the community hasn't historically been as involved in, such as the ones listed below. We think we're currently well below this fraction, so it's plausible some of these areas might be better for some people to go into right now than our top priority problem areas. Who is best suited to work on these other issues? Pioneering a new problem area from an effective altruism perspective is challenging, and in some ways harder than working on a priority area, where there is better training and infrastructure. Working on a less-researched problem can require a lot of creativity and critical thinking about how you can best have a positive impact by working on the issue. For example, it likely means working out which career options within the area are the most promising for direct impact, career capital, and exploration value, and then pursuing them even if they differ from what most other people in the area tend to value or focus on. You might even eventually need to 'create your own job' if pre-existing positions in the area don't match your priorities. The ideal person would therefore be self-motivated, creative, and willing to chart the waters for others, as well as have a strong interest or relevant experience in one of these less-explored issues. We compiled the following lists by combining suggestions from 6 of our advisors with our own ideas, judgement, and research. We were looking for issues that might be very important, especially for improving the long-term future, and which might be currently neglected by people thinking from an effective altruism perspective. If something was suggested twice, we took that as a presumption in favor of including it. We're very uncertain about the value of working on any one of these problems, but we think it's likely that there are issues on these lists (and especially the first one) that are as pressing as our highest priority problem areas. What are the pros and cons of working in each of these areas? Which are less tractable than they appear, or more important? Which are already being covered adequately by existing groups we don't know enough about? What potentia...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: The case of the missing cause prioritisation research, published by weeatquince on the effective altruism forum. Introduction / summary In 2011 I came across Giving What We Can, which shortly blossomed into effective altruism. Call me a geek if you like but I found it exciting, like really exciting. Here were people thinking super carefully about the most effective ways to have an impact, to create change, to build a better world. Suddenly a boundless opportunity to do vast amounts of good opened up before my eyes. I had only just got involved and by giving to fund bednets and had already magnified my impact on the world 100 times. And this was just the beginning. Obviously bednets were not the most effective charitable intervention, they were just the most effective we had found to date – with just a tiny amount of research. Imagine what topic could be explored next: the long run effects of interventions, economic growth, political change, geopolitics, conflict studies, etc. We could work out how to compare charities of vastly different cause areas, or how to do good beyond donations (some people were already starting to talk about career choices). Some people said we should care about animals (or AI risk), I didn’t buy it (back then), but imagine, we could work out what different value sets lead to different causes and the best charities for each. As far as I could tell the whole field of optimising for impact seemed vastly under-explored. This wasn’t too surprising – most people don’t seem to care that much about doing charitable giving well and anyway it was only just coming to light how truly bad our intuitions were at making charitable choices (with the early 2000’s aid skepticism movement). Looking back, I was optimistic. Yet in some regards my optimism was well-placed. In terms of spreading ideas, my small group of geeky uni friends went on to create something remarkable, to shift £m if not £bn of donations to better causes, to help 1000s maybe 100,000s of people make better career decisions. I am no longer surprised if a colleague, tinder date or complete stranger has heard of effective altruism (EA) or gives money to AMF (a bednet charity). However, in terms of the research I was so excited about, of developing the field of how to do good, there has been minimal progress. After nearly a decade, bednets and AI research still seem to be at the top of everyone’s Christmas donations wish list. I think I assumed that someone had got this covered, that GPI or FHI or whoever will have answers, or at least progress on cause research sometime soon. But last month, whilst trying to review my career, I decided to look into this topic, and, oh boy, there just appears to be a massive gaping hole. I really don’t think it is happening. I don’t particularly want to shift my career to do cause prioritisation research right now. So I am writing this piece in the hope that I can either have you, my dear reader, persuade me this work is not of utmost importance, or have me persuade you to do this work (so I don’t have to). A. The importance of cause prioritisation research What is your view on the effective altruism community and what it has achieved? What is the single most important idea to come out of the community? Feel free to take a moment to reflect. (Answers on a postcard, or comment). It seems to me (predictably given the introduction) that far and away the most valuable thing EA has done is the development of and promotion of cause prioritisation as a concept. This idea seems (shockingly and unfortunately) unique to EA.[1] It underpins all EA thinking, guides where EA aligned foundations give and leads to people seriously considering novel causes such as animal welfare or longtermism. This post mostly focuses on the current progress of and neglectedness of this work ...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Lessons from my time in Effective Altruism, published by richard_ngo on the effective altruism forum. I’ll start with an overview of my personal story, and then try to extract more generalisable lessons. I got involved in EA around the end of 2014, when I arrived at Oxford to study Computer Science and Philosophy. I’d heard about EA a few years earlier via posts on Less Wrong, and so already considered myself EA-adjacent. I attended a few EAGx conferences, became friends with a number of EA student group organisers, and eventually steered towards a career in AI safety, starting with a masters in machine learning at Cambridge in 2017-2018. I think it’s reasonable to say that, throughout that time, I was confidently wrong (or at least unjustifiably confident) about a lot of things. In particular: I dismissed arguments about systemic change which I now find persuasive, although I don’t remember how - perhaps by conflating systemic change with standard political advocacy, and arguing that it’s better to pull the rope sideways. I endorsed earning to give without having considered the scenario which actually happened, of EA getting billions of dollars of funding from large donors. (I don’t know if this possibility would have changed my mind, but I think that not considering it meant my earlier belief was unjustified.) I was overly optimistic about utilitarianism, even though I was aware of a number of compelling objections; I should have been more careful to identify as "utilitarian-ish" rather than rounding off my beliefs to the most convenient label. When thinking about getting involved in AI safety, I took for granted a number of arguments which I now think are false, without actually analysing any of them well enough to raise red flags in my mind. After reading about the talent gap in AI safety, I expected that it would be very easy to get into the field - to the extent that I felt disillusioned when given (very reasonable!) advice, e.g. that it would be useful to get a PhD first. As it turned out, though, I did have a relatively easy path into working on AI safety - after my masters, I did an internship at FHI, and then worked as a research engineer on DeepMind’s safety team for two years. I learned three important lessons during that period. The first was that, although I’d assumed that the field would make much more sense once I was inside it, that didn’t really happen: it felt like there were still many unresolved questions (and some mistakes) in foundational premises of the field. The second was that the job simply wasn’t a good fit for me (for reasons I’ll discuss later on). The third was that I’d been dramatically underrating “soft skills” such as knowing how to make unusual things happen within bureaucracies. Due to a combination of these factors, I decided to switch career paths. I’m now a PhD student in philosophy of machine learning at Cambridge, working on understanding advanced AI with reference to the evolution of humans. By now I’ve written a lot about AI safety, including a report which I think is the most comprehensive and up-to-date treatment of existential risk from AGI. I expect to continue working in this broad area after finishing my PhD as well, although I may end up focusing on more general forecasting and futurism at some point. Lessons I think this has all worked out well for me, despite my mistakes, but often more because of luck (including the luck of having smart and altruistic friends) than my own decisions. So while I’m not sure how much I would change in hindsight, it’s worth asking what would have been valuable to know in worlds where I wasn’t so lucky. Here are five such things. 1. EA is trying to achieve something very difficult. A lot of my initial attraction towards EA was because it seemed like a slam-dunk case: here’s an obvious i...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: EA needs consultancies, published by lukeprog on the effective altruism forum. Problem EA organizations like Open Phil and CEA could do a lot more if we had access to more analysis and more talent, but for several reasons we can't bring on enough new staff to meet these needs ourselves, e.g. because our needs change over time, so we can't make a commitment that there's much future work of a particular sort to be done within our organizations.[1] This also contributes to there being far more talented EAs who want to do EA-motivated work than there are open roles at EA organizations.[2] A partial solution? In the public and private sectors, one common solution to this problem is consultancies. They can be think tanks like the National Academies or RAND,[3] government contractors like Booz Allen or General Dynamics, generalist consulting firms like McKinsey or Deloitte, niche consultancies like The Asia Group or Putnam Associates, or other types of service providers such as UARCs or FFRDCs. At the request of their clients, these consultancies (1) produce decision-relevant analyses, (2) run projects (including building new things), (3) provide ongoing services, and (4) temporarily "loan" their staff to their clients to help with a specific project, provide temporary surge capacity, provide specialized expertise that it doesn't make sense for the client to hire themselves, or fill the ranks of a new administration.[4] (For brevity, I'll call these "analyses," "projects," "ongoing services," and "talent loans," and I'll refer to them collectively as "services.") This system works because even though demand for these services can fluctuate rapidly at each individual client, in aggregate across many clients there is a steady demand for the consultancies' many full-time employees, and there is plenty of useful but less time-sensitive work for them to do between client requests. Current state of EA consultancies Some of these services don't require EA talent, and can thus be provided for EA organizations by non-EA firms, e.g. perhaps accounting firms. But what about analyses and services that require EA talent, e.g. because they benefit from lots of context about the EA community, or because they benefit from habits of reasoning and moral intuitions that are far more common in the EA community than elsewhere?[5] Rethink Priorities (RP) has demonstrated one consultancy model: producing useful analyses specifically requested by EA organizations like Open Philanthropy across a wide range of topics.[6] If their current typical level of analysis quality can be maintained, I would like to see RP scale as quickly as they can. I would also like to see other EAs experiment with this model.[7] BERI offers another consultancy model, providing services that are difficult or inefficient for clients to handle themselves through other channels (e.g. university administration channels). There may be a few other examples, but I think not many.[8] Current demand for these services All four models require sufficient EA client demand to be sustainable. Fortunately, my guess is that demand for ≥RP-quality analysis from Open Phil alone (but also from a few other EA organizations I spoke to) will outstrip supply for the foreseeable future, even if RP scales as quickly as they can and several RP clones capable of ≥RP-quality analysis are launched in the next couple years.[9] So, I think more EAs should try to launch RP-style "analysis" consultancies now. However, for EAs to get the other three consultancy models off the ground, they probably need clearer evidence of sufficiently large and steady aggregate demand for those models from EA organizations. At least at first, this probably means that these models will work best for services that demand relatively "generalist" talent, perhaps corresponding ...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: The Cost of Rejection, published by Daystar Eld on the effective altruism forum. For those that don't know, I've worked as a therapist for the rationality and EA community for over two years now, first part time, then full time in early 2020. I often get asked about my observations and thoughts on what sorts of issues are particularly prevalent or unique to the community, and while any short answer to that would be oversimplifying the myriad of issues I've treated, I do feel comfortable saying that "concern with impact" is a theme that runs pretty wide and deep no matter what people come to sessions to talk about. Seeing how this plays out in various different ways has motivated me to write on some aspects of it, starting with this broad generalization; rejection hurts. Specifically, rejection from a job that's considered high impact (which, for many, implicitly includes all jobs with EA organizations) hurts a lot. And I think that hurt has a negative impact that goes beyond the suffering involved. In addition to basing this post off of my own observations, I’ve written it with the help of/on behalf of clients who have been affected by this, some of whom reviewed and commented on drafts. I. Premises There are a few premises that I’m taking for granted that I want to list out in case people disagree with any specific ones: The EA population is growing, as are EA organizations in number and size. This seems overall to be a very good thing. In absolute numbers, EA organizations are growing slower or at pace with the overall EA population. Even with massive increases in funding this seems inevitable, and also probably good? There are many high impact jobs outside of EA orgs that we would want people in the community to have. (By EA orgs I specifically mean organizations headed by and largely made up of people who self-identify as Effective Altruists, not just those using evidence-and-reason-to-do-the-most-good) ((Also there’s a world in which more people self-identify as EAs and therefore more organizations are considered EA and by that metric it’s bad that EA orgs are growing slower than overall population, but that’s also not what I mean)) Even with more funding being available, there will continue to be many more people applying to EA jobs than getting them. I don’t have clear numbers for this, but asking around at a few places got me estimates between ~47-124 applications for specific positions (one of which noted that ~¾ of them were from people clearly within and familiar with the EA community), and hundreds of applications for specific grants (at least once breaking a thousand). This is good for the organizations and community as a whole, but has bad side effects, such as: Rejection hurts, and that hurt matters. For many people, rejection is easily accepted as part of trying new things, shooting for the moon, and challenging oneself to continually grow. For many others, it can be incredibly demoralizing, sometimes to the point of reducing motivation to continue even trying to do difficult things. So when I say the hurt matters, I don’t just mean that it’s suffering and we should try to reduce suffering wherever we can. I also mean that as the number of EAs grows faster than the number of positions in EA orgs, the knock-on effects of rejection will slow community and org growth, particularly since: The number of EAs who receive rejections from EA orgs will likely continue to grow, both absolutely and proportionally. Hence, this article. II. Models There are a number of models I have for all of this that could be totally wrong. I think it’s worth spelling them out a bit more so that people can point to more bits and let me know if they are important, or why they might not be as important as I think they are. Difficulty in Self Organization First, I think it’s import...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Concerns with ACE's Recent Behavior, published by Hypatia on the effective altruism forum. Epistemic Status: I feel pretty confident that the core viewpoint expressed in this post is correct, though I'm less confident in some specific claims. I have not shared a draft of this post with ACE, and so it’s possible I’ve missed important context from their perspective. EDIT: ACE board member Eric Herboso has responded with his personal take on this situation. He believes some points in this post are wrong or misleading. For example, he disputes my claim that ACE (as an organization) attempted to cancel a conference speaker. EDIT: Jakub Stencel from Anima International has posted a response. He clarifies a few points and offers some context regarding the CARE conference situation. Background In the past year, there has been some concern in EA surrounding the negative impact of “cancel culture”[1] and worsening discourse norms. Back in October, Larks wrote a post criticizing EA Munich's decision to de-platform Robin Hanson.The post was generally well-received, and there have been other posts on the forum discussing potential risks from social-justice oriented discourse norms. For example, see The Importance of Truth-Oriented Discussions in EAand EA considerations regarding increasing political polarization. I'm writing this post because I think some recent behavior from Animal Charity Evaluators (ACE) is a particularly egregious example of harmful epistemic norms in EA. This behavior includes: Making (in my view) poorly reasoned statements about anti-racism and encouraging supporters to support or donate to anti-racist causes and organizations of dubious effectiveness Attempting to cancel an animal rights conference speaker because of his views on Black Lives Matter, withdrawing from that conference because the speaker's presence allegedly made ACE staff feel unsafe, and issuing a public statement supporting its staff and criticizing the conference organizers Penalizing charities in reviews for having leadership and/or staff who are deemed to be insufficiently progressive on racial equity, and stating it won't offer movement grants funding to those who disagree with its views on diversity, equity, and inclusion[2]. Because I'm worried that this post could hurt my future ability to get a job in EAA, I'm choosing to remain anonymous. My goal here is to: a) Describe ACE's behavior in order to raise awareness and foster discussion, since this doesn't seem to have attracted much attention, and b) Give a few reasons why I think ACE's behavior has been harmful, though I’ll be brief since I think similar points have been better made elsewhere I also want to be clear that I don't think ACE is the only bad actor here, as other areas of the EAA community have also begun to embrace harmful social-justice derived discourse norms[3]. However, I'm focusing my criticism on ACE here because: It positions itself as an effective altruism organization, rather than a traditional animal advocacy organization It is well known and generally respected by the EA community It occupies a powerful position within the EAA movement, directing millions of dollars in funding each year and conducting a large fraction of the movement's research And before I get started, I'd also like to make a couple caveats: I think ACE does a lot of good work, and in spite of this recent behavior, I think its research does a lot to help animals. I'm also not trying to “cancel” ACE or any of its staff. But I do think the behavior outlined in this post is bad enough that ACE supporters should be vocal about their concerns and consider withholding future donations. I am not suggesting that racism, discrimination, inequality, etc. shouldn't be discussed, or that addressing these important problems isn't EA-worthy. The EA commu...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Introducing Probably Good: A New Career Guidance Organization, published by omernevo, sella on the effective altruism forum. We’re excited to announce the launch of Probably Good, a new organization that provides career guidance intended to help people do as much good as possible. Context For a while, we have felt that there was a need for a more generalist careers organization than 80,000 Hours — one which is more agnostic regarding different cause areas and might provide a different entry point into the community to people who aren’t a good fit for 80K’s priority areas. Following 80,000 Hours’ post about what they view as gaps in the careers space, we contacted them about how a new organization could effectively fill some of those gaps. After a few months of planning, asking questions, writing content, and interviewing experts, we’re almost ready to go live (we aim to start putting our content online in 1-2 months) and would love to hear more from the community at large. How You Can Help The most important thing we’d like from you is feedback. Please comment on this post, send us personal messages on the Forum, email us (omer at probablygood dot org, sella at probablygood dot org), or set up a conversation with us via videoconference. We would love to receive as much feedback as we can get. We’re particularly interested in hearing about things that you, personally, would actually read // use // engage with, but would appreciate absolutely any suggestions or feedback. Probably Good Overview The most updated version of the overview is here. Following is the content of the overview at the time this announcement is posted. Overview Probably Good is a new organization that provides career guidance intended to help people do as much good as possible. We will start by focusing on online content and a small number of 1:1 consultations. We will later consider other forms of career guidance such as a job board, scaling up the 1:1 consultations, more in-depth research, etc. Our approach to guidance is focused on how to help each individual maximize their career impact based on their values, personal circumstances, and motivations. This means that we will accommodate a wide range of preferences (for example, different cause areas), as long as they’re consistent with our principles, and try to give guidance in accordance with those preferences. Therefore, we’ll be looking at a wide range of impactful careers under different views on what to optimize for or under various circumstantial constraints, such as how to maximize impact within specific career paths, within specific geographic regions, through earning to give, or within more specific situations (e.g. making an impact from within a large corporation). There are other organizations in this space, the most well-known being 80,000 Hours. We think our approach is complementary to 80,000 Hours’ current approach: Their guidance mostly focuses on people aiming to work on their priority problem areas, and we would be able to guide high quality candidates who aren’t. We would direct candidates to 80,000 Hours or other specialized organizations (such as Animal Advocacy Careers) if they’re a better fit for their principles and priority paths. This characterization of our target audience is very broad; this has two main motivations. First, as part of our experimental approach: we are interested in identifying which cause areas currently have the most unserved demand. By providing preliminary value in multiple areas of expertise, we hope to more efficiently identify where our investment would be most useful, and we may specialize (in a more informed manner) in the future. The second motivation for this is that one possibility for specialization is as a “router” interface - helping individuals make preliminary decisions tailored to the...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: What Makes Outreach to Progressives Hard, published by Cullen_OKeefe on the effective altruism forum. This post summarizes some of my conclusions on things that can make EA outreach to progressives hard, as well as some tentative recommendations on techniques for making such outreach easier. To be clear, this post does not argue or assume that outreach to progressives is harder than outreach to other political ideologies.[1] Rather, the point of this post is to highlight identifiable, recurring memes/thought patterns that cause Progressives to reject or remain skeptical of EA. My Background (Or, Why I am Qualified to Talk About This) Nothing in here is based on systematic empirical analysis. It should therefore be treated as highly uncertain. My analysis here draws on two sources: Reflecting on my personal journey as someone who transitioned from a very social-justice-y worldview to a more EA-aligned one (and therefore understands the former well), who is still solidly left-of-center, and who still retains contacts in the social justice (SJ) world; and My largely failed attempts as former head of Harvard Law School Effective Altruism to get progressive law students to make very modest giving commitments to GiveWell charities. Given that the above all took place in America, this post is most relevant to American political dynamics (especially at elite universities), and may very well be inapplicable elsewhere.[2] Readers may worry that I am being a bit uncharitable here. However, I am not trying to present the best progressive objections to EA (so as to discover the truth), but rather the most common ones (so as to persuade people better). In other words, this post is about marketing and communications, not intellectual criticisms. Since I think many of the common progressive objections to EA are bad, I will attempt to explain them in (what I take to be) their modal or undifferentiated form, not steelman them. Relatedly, when I say "progressives" through the rest of this post, I am mainly referring to the type of progressive who is skeptical of EA, not all progressives. There are many amazing progressive EAs, who do not see these two ideologies to be in conflict whatsoever. And many non-EA progressives will believe few of these things. Nevertheless, I do think I am pointing to a real set of memes that are common—but definitely not universal—among the American progressive left as of 2021. This is sufficient for understanding the messaging challenges facing EAs within progressive institutions. Reasons Progressives May Not Like EA Legacy of Paternalistic International Aid Many progressives have a strong prior against international aid, especially private international aid. Progressives are steeped in—and react to—stories of paternalistic international aid,[3] much in the way that EAs are steeped in stories of ineffective aid (e.g., Playpumps). Interestingly, EAs and progressives will often (in fact, almost always) agree on what types of aid are objectionable. However, we tend to take very different lessons away from this. EAs will generally take away the lesson that we have to be super careful about which interventions to fund, because funding the wrong intervention can be ineffective or actively harmful. We put the interests of our intended beneficiaries first by demanding that charities demonstrably advance their beneficiaries' interests as cost-effectively as possible. Progressives tend to take a very different lesson from this. They tend to see this legacy as objectionable due to the very nature of the relationship between aid donors and recipients. Roughly, they may believe that the power differential between wealthy donors from the Global North and aid recipients in developing countries makes unobjectionable foreign aid either impossible or, at the very least, extr...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Snapshot of a career choice 10 years ago, published by Julia_Wise on the effective altruism forum. Here’s a little episode from EA’s history, about how much EA career advice has changed over time. Ten years ago, I wrote an angsty LessWrong post called “Career choice for a utilitarian giver.” (“Effective altruism” and “earning to give” didn’t exist as terms at that point.) At the time, there was a lot less funding in EA, and the emphasis was very much on donation rather than direct work. Donation was the main way I was hoping to have an impact. I was studying to become a social worker, but I had become really worried that I should try for some higher-earning career so I could donate more. I thought becoming a psychiatrist was my best career option, since it paid significantly more than the social work career I was on track towards, and I thought I could be good at it. I prioritized donation very highly, and I estimated that going into medicine would allow me to earn enough to save 2500 lives more than I could by staying on the same path. (That number is pretty far wrong, but it’s what I thought at the time.) The other high-earning options I could think of seemed to require quantitative skills I didn’t have, or a level of ambition and drive I didn’t have. A few people did suggest that I might work on movement building, but for some reason it didn’t seem like a realistic option to me. There weren’t existing projects that I could slot into, and I’m not much of an entrepreneurial type. The post resulted in me talking to a career advisor from a project that would eventually become 80,000 Hours. The advisor and I talked about how I might switch fields and try to get into medical school. I was trying not to be swayed by the sunk cost of the social work education I had already completed, but I also just really didn’t want to go through medical school and residency. My strongest memory of that period is lying on the grass at my grad school, feeling awful about not being willing to put the years of work into earning more money. There were lives at stake. I was going to let thousands of people die from malaria because I didn’t want to work hard and go to medical school. I felt horribly guilty. And I also thought horrible guilt was not going to be enough to motivate me through eight years of intense study and residency. After a few days of crisis, I decided to stop thinking about it all the time. I didn’t exactly make a conclusive decision, but I didn’t take any steps to get into med school, and after a few more weeks it was clear to me that I had no real intention to change paths. So I continued to study social work, with the belief that I was doing something seriously wrong. (To be clear, nobody was telling me I should feel this way, but I wasn’t living up to my own standards.) In the meantime, I started writing Giving Gladly and continued hosting dinners at my house where people could discuss this kind of thing. The Boston EA group grew out of that. It didn’t occur to me that I could work for an EA organization without moving cities. But four years later, CEA was looking for someone to do community work in EA and was willing to consider someone remote. Because of my combination of EA organizing, writing, and experience in social work, I turned out to be a good fit. I was surprised that they were willing to hire someone remote. Although I struggled at first to work out what exactly I should be doing, over time it was clear to me that I could be much more useful here than either in social work or earning to give. I don’t think there’s a clear moral of the story about what this means other people should do, but here are some reflections: I look back on this and think, wow, we had very little idea how to make good use of a person like me. I wonder how many other square pegs are ou...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Lessons from Running Stanford EA and SERI, published by kuhanj on the effective altruism forum. Introduction and summary Who knew a year of work could turn a 1-organizer EA group into one of the largest EA groups in the world? Especially considering that the person spearheading this growth had little experience running much of anything relevant, and very suboptimal organization skills (It’s me, welp). I definitely didn’t, when I started running Stanford EA in mid-2019. But I did know it was worth a shot; many universities are absolutely insane opportunities for multiplying your impact--where else can you find such dense clusters of people with the values, drive, talent, time, and career flexibility to dedicate their careers to tackling the world’s most pressing, difficult, large-scale problems? Stanford EA had effectively one real organizer (Jake McKinnon), and our only real programming was weekly discussions (which weren't very well attended) and the one-off talk for a few years. This was the case until 2019, when Jake started prioritizing succession, spending lots of time talking to a few new intrigued-but-not-yet-highly-involved members (like me!) to get more involved about the potential impact we could have doing community building and for the world more broadly. Within a year, Stanford EA grew to be one of the largest groups in EA. That first year of work turned Stanford EA into a very large group, and in the second year since, I’ve been super proud of what our team has accomplished: Getting SERI (the Stanford Existential Risks Initiative) off the ground (which wouldn’t have been possible without our faculty directors and Open Phil’s support), which has inspired other x-risk initiatives at Cambridge and (coming this year) at Harvard/MIT. Running all of CEA’s Virtual Programs for their first global iterations, introducing over 500 people to key concepts in EA Getting ~10 people to go from little knowledge of EA to being super dedicated to pursuing EA-guided careers, and boosting the networks, motivation, and knowledge of 5+ more who were already dedicated (At Stanford, and hopefully much more outside of Stanford since we ran a lot of global programming) Running a global academic conference, together with other SERI organizers. Running a large majority of all x-risk/longtermist internships in the world this year, together with other SERI organizers (though this is in part due to FHI being unable to run their internship this summer) Founding the Stanford Alt. Protein Project, which recently ran a well-received, nearly 100-person class on alternative proteins, and has also set up connections/grants between three Stanford professors and the Good Food Institute to conduct alternative protein research. Helping several other EA groups get off the ground, and running intro to EA talks and fellowships with them I say this, not to brag, but because I think it shows several important things: There’s an incredible amount of low-hanging fruit in this area. The payoffs to doing good community-building work are huge. See also these posts for additional evidence and discussion. Maybe you think EAs are over-determined? I don’t think so; perhaps half of the hardcore EAs in our group don’t seem to have been (and this proportion could be even higher with more and better community building). You (yes, you!) can do similar things. We’re not that special--we’re mostly an unorganized team of students who care a lot. We still have so much to learn, but I think we got some things right. What’s the sEAcret sauce? I try to distill it in this post, as a mix of mindsets, high-level goals, and tactics. Here’s the short version/summary: EA groups have lots of room for growth and improvement, as evidenced by the rapid growth of Stanford EA (despite it still being very suboptimally run and lots o...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: The motivated reasoning critique of effective altruism, published by Linch on the effective altruism forum. Epistemic status: Half-baked at best I have often been skeptical of the value of a) critiques against effective altruism and b) fully general arguments that seem like they can apply to almost anything. However, as I am also a staunch defender of hypocrisy, I will now hypocritically attempt to make the case for applying a fully general critique to effective altruism. In this post, I will claim that: Motivated reasoning inhibits our ability to acquire knowledge and form reasoned opinions. Selection bias in who makes which arguments significantly exacerbates the problem of motivated reasoning Effective altruism should not be assumed to be above these biases. Moreover, there are strong reasons to believe that incentive structures and institutions in effective altruism exacerbate rather than alleviate these biases. Observed data and experiences in effective altruism support this theory; they are consistent with an environment where motivated reasoning and selection biases are rampant. To the extent that these biases (related to motivated reasoning) are real, we should expect the harm done to our ability to form reasoned opinions to also seriously harm the project of doing good. I will use the example of cost-effectiveness analyses as a jumping board for this argument. (I understand that effective altruism, especially outside of global health and development, has largely moved away from explicit expected value calculations and cost-effectiveness analyses. However, I do not believe this change invalidates my argument (see Appendix B)). I also list a number of tentative ways to counteract motivated reasoning and selection bias in effective altruism: Encourage and train scientific/general skepticism in EA newcomers. Try marginally harder to accept newcomers, particularly altruistically motivated ones with extremely high epistemic standards As a community, fund and socially support external (critical) cost-effectiveness analyses and impact assessments of EA orgs Within EA orgs, encourage and reward dissent of various forms Commit to individual rationality and attempts to reduce motivated reasoning Maybe encourage a greater number of people to apply and seriously consider jobs outside of EA or EA-adjacent orgs Maintain or improve the current culture of relatively open, frequent, and vigorous debate Foster a bias towards having open, public discussions of important concepts, strategies, and intellectual advances Motivated reasoning: What it is, why it’s common, why it matters By motivated reasoning, I roughly mean what Julia Galef calls “soldier mindset” (H/T Rob Bensinger): In directionally motivated reasoning, often shortened to "motivated reasoning", we disproportionately put our effort into finding evidence/reasons that support what we wish were true. Or, from Wikipedia: emotionally biased reasoning to produce justifications or make decisions that are most desired rather than those that accurately reflect the evidence I think motivated reasoning is really common in our world. As I said in a recent comment: My impression is that my interactions with approximately every entity that perceives themself as directly doing good outside of EA is that they are not seeking truth, and this systematically corrupts them in important ways. Non-random examples that come to mind include public health (on covid, vaping, nutrition), bioethics, social psychology, developmental econ, climate change, vegan advocacy, religion, US Democratic party, and diversity/inclusion. Moreover, these problems aren't limited to particular institutions: these problems are instantiated in academia, activist groups, media, regulatory groups and "mission-oriented" companies. What does motivated reasoning loo...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: What is the likelihood that civilizational collapse would directly lead to human extinction (within decades)?, published by Luisa_Rodriguez on the effective altruism forum. Epistemic transparency: Confidence in conclusions varies throughout. I give rough indicators of my confidence at the section level by indicating the amount of time I spent researching/thinking about each particular subtopic, plus a qualitative description of the types of sources I rely on. In general, I consider it a first step toward understanding this threat from civilizational collapse — not a final or decisive one. Acknowledgements This research was funded by the Forethought Foundation. It was written by Luisa Rodriguez under the supervision of Arden Koehler and Lewis Dartnell. Thanks to Arden Koehler, Max Daniel, Michael Aird, Matthew van der Merwe, Rob Wiblin, Howie Lempel, and Kit Harris who provided valuable comments. Thanks also to William MacAskill for providing guidance and feedback on the larger project. Summary In this post, I explore the probability that if various kinds of catastrophe caused civilizational collapse, this collapse would fairly directly lead to human extinction. I don’t assess the probability of those catastrophes occurring in the first place, the probability they’d lead to indefinite technological stagnation, or the probability that they’d lead to non-extinction existential catastrophes (e.g., unrecoverable dystopias). I hope to address the latter two outcomes in separate posts (forthcoming). My analysis is organized into case studies: I take three possible catastrophes, defined in terms of the direct damage they would cause, and assess the probability that they would lead to extinction within a generation. There is a lot more someone could do to systematically assess the probability that a catastrophe of some kind would lead to human extinction, and what I’ve written up is certainly not conclusive. But I hope my discussion here can serve as a starting point as well as lay out some of the main considerations and preliminary results. Note: Throughout this document, I’ll use the following language to express my best guess at the likelihood of the outcomes discussed: TABLE1 Case 1: I think it’s exceedingly unlikely that humanity would go extinct (within ~a generation) as a direct result of a catastrophe that causes the deaths of 50% of the world’s population, but causes no major infrastructure damage (e.g. damaged roads, destroyed bridges, collapsed buildings, damaged power lines, etc.) or extreme changes in the climate (e.g. cooling). The main reasons for this are: Although civilization’s critical infrastructure systems (e.g. food, water, power) might collapse, I expect that several billions of people would survive without critical systems (e.g. industrial food, water, and energy systems) by relying on goods already in grocery stores, food stocks, and fresh water sources. After a period of hoarding and violent conflict over those supplies and other resources, I expect those basic goods would keep a smaller number of remaining survivors alive for somewhere between a year and a decade (which I call the grace period, following Lewis Dartnell’s The Knowledge). After those supplies ran out, I expect several tens of millions of people to survive indefinitely by hunting, gathering, and practicing subsistence agriculture (having learned during the grace period any necessary skills they didn’t possess already). Case 2: I think it’s very unlikely that humanity would go extinct as a direct result of a catastrophe that caused the deaths of 90% of the world’s population (leaving 800 million survivors), major infrastructure damage, and severe climate change (e.g. nuclear winter/asteroid impact). While I expect that millions would starve to death in the wake of something like a globa...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Seven things that surprised us in our first year working in policy - Lead Exposure Elimination Project, published by Jack, LuciaC on the effective altruism forum. Following the interest in our post announcing the launch of Lead Exposure Elimination Project (LEEP) eight months ago, we are now sharing an update unpacking seven findings that have surprised us in our experiences so far. We hope these will be relevant to others interested in policy change or starting a new project or charity. For those who are not familiar with LEEP, we are a Charity Entrepreneurship-incubated NGO advocating for lead paint regulation in countries with large and growing burdens of lead poisoning from paint. The reasons we focus on reducing lead exposure are outlined in our introduction post. In short, we believe the problem to be neglected and tractable, and that the intervention has the potential to improve lives with a high level of cost-effectiveness. 1. The speed of progress with government has been less of a limiting factor than expected In our first target country, Malawi, we had a number of uncertainties about how quickly progress could be made. We were unsure if we would be able to get in touch with the relevant government officials, if they would be willing to engage, and whether our advocacy would lead to action in a reasonable timeframe. We found that stakeholders were far more willing to engage than we had expected. Even without existing connections or introductions, government officials replied to our emails and agreed to meetings. Beyond getting initial meetings, the tractability of achieving change was also higher than expected. After we carried out a study demonstrating high levels of lead in paint, the Malawi Bureau of Standards agreed to begin monitoring and enforcement for lead content of paint (using pre-existing but unimplemented standards), and have since confirmed that they have begun. This change occurred within three months of beginning advocacy in Malawi - significantly faster than our expected timeframe of 1-2 years. We also found a surprising willingness to cooperate from the local paint industry. Since presenting to the paint manufacturers our findings of lead in paint and the benefits of switching to non-lead, they have engaged with us and with our support identifying non-lead alternative ingredients. We will be carrying out a repeat paint study in a few months to measure how this progress relates to levels of lead paint available on the market. There are a number of factors that we think contributed to this faster traction and high level of stakeholder engagement. One is the new country-specific data that we were able to generate through a small paint sampling study. We believe that this data provided an effective opener to communications and also convincingly demonstrated that lead paint is a problem in Malawi. Our government contacts confirmed that this Malawi-specific evidence was key for their decision to take action. Generating new country-specific data through small-scale local studies seems to be an effective advocacy strategy that may be cross-applicable to other areas of policy. Other reasons why stakeholder engagement has been greater than expected might be specific to lead paint regulation advocacy. For example, lead paint regulation is not particularly expensive for governments to implement or for paint manufacturers to comply with, reducing the barrier to action for both stakeholder groups. Also, there is a strong and established evidence-base for the harms of childhood lead poisoning, increasing consensus on the issue. As well as this, there is a growing awareness of a global movement towards lead paint regulation, including examples of neighbouring countries and the support of respected international bodies such as the WHO. This may facilitate ...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Why I'm concerned about Giving Green, published by alexrjl on the effective altruism forum. Disclosure I am a forecaster, and occasional independent researcher. I also work in a volunteer capacity for SoGive, which has included some analysis of the climate space in order to provide advice to some individual donors interested in this area. This work has involved ~20 hours of conference calls over the last year with donors and organisations, one of which was the Clean Air Task Force, although for the last few months my primary focus has been internal work on moral weights. I began the research for this piece in a personal capacity, and the opinions below are my own, not those of SoGive. I received input on some early drafts, for which I am extremely grateful, from Sanjay Joshi (SoGive’s founder), as well as Aaron Gertler and Linch Zhang, however I again want to emphasise that the opinions expressed, and especially any mistakes in the below, are mine alone. I'm also very grateful to Giving Green for taking the time to have a call with me about my thinking here. I provided a copy of the post to them in advance, and they have indicated that they'll be providing a reponse to the below. Overview Big potential I think that Giving Green has the potential to be incredibly impactful, not just on the climate but also on the EA/Effective Giving communities. Many people, especially young people, are extremely concerned about climate change, and very excited to act to prevent it. Meta-analysis of climate charities has the chance to therefore have large first-order effects, by redirecting donations to the most effective organisations within the climate space. It also, if done well, has the potential to have large second-order effects, by introducing people to the huge multiplier on their impact that cost-effectiveness research can have, and through that to the wider EA movement. I note that at least one current CEA staff member took this exact path into EA. With this said, I am concerned about some aspects of Giving Green in its current form, and having discussed these concerns with them, felt it was worth publishing the below. Concerns about research quality Giving Green’s evaluation process involves substantial evidence collection and qualitative evaluation, but eschews quantitative modelling, in favour of a combination of metrics which do not have a simple relationship to cost-effectiveness. In three cases, detailed below, I have reservations about the strength of Giving Green’s recommendations. Giving Green also currently recommends the Clean Air Task Force, which I enthusiastically endorse, but who Founders Pledge had identified as promising before Giving Green’s founding, and Tradewater, who I have not evaluated. What this boils down to is that in every case where I investigated an original recommendation made by Giving Green, I was concerned by the analysis to the point where I could not agree with the recommendation. Despite the unusual approach, especially compared to standard EA practice, the research and methodology are presented by Giving Green in a way which implies a level of concreteness comparable to major existing charity evaluators such as Givewell. As well as the quantitative aspect mentioned above, major evaluators are notable for the high degree of rigour in their modelling, with arguments being carefully connected to concrete outcomes, and explicit consideration of downside risks and ways that they could be wrong. One important part of the more usual approach is that it makes research much easier to critique, as causal reasoning is laid out explicitly, and key assumptions are identified and quantified. When research lacks this style, not only does the potential for error increase, but it becomes much more difficult and time-intensive to critique, meaning errors...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Good news on climate change, published by John G. Halstead, jackvaon the effective altruism forum. This post is about how much warming we should expect on current policy and assuming emissions stop at 2100. We argue the risk of extreme warming (>6 degrees) conditional on these assumptions now looks much lower than it once did. Crucially, the point of this post is about the direction of an update, not an absolute assessment of risk -- indeed, the two of us disagree a fair amount on the absolute risk, but strongly agree on the direction and relative magnitude of the update. The damage of climate change depends on three things: How much we emit The warming we get, conditional on emissions The impact of a given level of warming. The late and truly great economist Martin Weitzman argued for many years that the catastrophic risk from climate change was greater than commonly recognised. In 2015, Weitzman, along with Gernot Wagner, an economist now at New York University, released Climate Shock, which argued that the chance of more than 6 degrees of warming is worryingly high. Using the International Energy Agency’s estimate of the most likely level of emissions on current policy, and the IPCC’s estimate of climate sensitivity, Wagner and Weitzman estimated that the chance of more than 6 degrees is 11%, on current policy.[1] In recent years, the chance of more than 6 degrees of warming on current policy has fallen quite substantially for two reasons: Emissions now look likely to be lower The right tails of climate sensitivity have become thinner 1. Good news on emissions For a long time the climate policy and impacts community was focused on one possible ‘business as usual’ emissions scenario known as Representative Concentration Pathway 8.5 (RCP8.5), a worst case against which climate action would be compared. Each representative concentration pathway can be paired with a socioeconomic story of how the world will develop in key areas such as population, income, inequality and education. These are known as ‘shared socioeconomic pathways’ (SSPs). The latest IPCC report outlines five shared socioeconomic pathways. The only one that is compatible with RCP8.5 is a high economic growth fossil fuel-powered future called Shared Socioeconomic Pathway 5 (SSP5). In combination, SSP5 and RCP8.5 is called ‘SSP5-8.5’. On SSP5-8.5, we would emit a further 2.2 trillion tonnes of carbon by 2100, on top of the 0.65 trillion tonnes we have emitted so far.[2] For reference, we currently put about 10 billion tonnes of carbon into the atmosphere from fossil fuel burning and industry.[3] The other emissions pathways are shown below: IPCC, Climate Change 2021: The Physical Science Basis, Assessment Review 6, Summary for Policymakers: Figure SPM.4 However, for a variety of reasons, SSP5-RCP8.5 now looks increasingly unlikely as a ‘business as usual’ emissions pathway. There are several reasons for this. Firstly, the costs of renewables and batteries have declined extremely quickly. Historically, models have been too pessimistic on cost declines for solar, wind and batteries: out of nearly 3,000 Integrated Assessment Models, none projected that solar investment costs (different to the levelised costs shown below) would decline by more than 6% per year between 2010 and 2020. In fact, they declined by 15% per year.[4] This means that renewables will play an increasing role in energy supply in the future. In part for this reason, energy systems models now suggest that high fossil fuel futures are much less likely. For example, the chart below shows emissions on current policies and pledged policies, according to the International Energy Agency. Source: Hausfather and Peters, ‘Emissions – the ‘business as usual’ story is misleading’, Nature, 2020. The chart above from Hausfather and Peters (2020) relies...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Small and Vulnerable, published by deluks917 on the effective altruism forum. Anyone who is dedicating the majority of their time or money to Effective Altruism needs to ask themselves why. Why not focus on enjoying life and spending your time doing what you love most? Here is my answer: I have a twin sister but neither of us had many other friends growing up. From second to fifth grade we had none. From sixth to eighth we had one friend. As you might guess I was bullied quite badly. Multiple teachers contributed to this. Despite having no friends my parents wanted us to be normal. They pressured me to play sports with the boys in the neighborhood. I was unable to play with an acceptable level of skill and was not invited to the games anyway. But we were still forced to go 'play outside' after school. We had to find ways to kill time. Often we literally rode our bicycles in a circle in a parking lot. We were forced to 'play outside' for hours most days and even longer on weekends. I was not even allowed to bring a book outside though sometimes I would hide them outside at night and find them the next day. Until high school, I had no access to the internet. After dinner, I could watch TV, read and play video games. These were the main sources of joy in my childhood. Amazingly my mom made fun of her children for being weirdos. My sister used to face a wall and stim with her fingers when she was overwhelmed. For some reason, my mom interpreted this as 'OCD'. So she made up a song titled 'OCD! Do you mean me?' It had several verses! This is just one, especially insane, example. My dad liked to 'slap me around. He usually did not hit me very hard but he would slap me in the face all the time. He also loved to call me 'boy' instead of my name. He claims he got this idea from Tarzan. It took me years to stop flinching when people raised their hands or put them anywhere near my face. I have struggled with gender since childhood. My parents did not tolerate even minor gender nonconformity like growing my hair out. I would get hit reasonably hard if I insisted on something as 'extreme' as crossing my legs 'like a girl in public. I recently started HRT and already feel much better. My family is a lot of the reason I delayed transitioning. If you go by the checklist I have quite severe ADHD. 'Very often' seemed like an understatement for most of the questions. My ADHD was untreated until recently. I could not focus on school or homework so trying to do my homework took way too much time. I was always in trouble in school and considered a very bad student. It definitely hurts when authority figures constantly, and often explicitly, treat you like a fuck up and a failure who can't be trusted. But looking back it seems amazing I was considered such a bad student. I love most of the subjects you study in school! When I finally got access to the internet I spent hours per day reading Wikipedia articles. I still spend a lot of time listening to lectures on all sorts of subjects, especially history. Why were people so cruel to a little child who wanted to learn things? Luckily things improved in high school. Once I had more freedom and distance from my parents my social skills improved a huge amount. In high school, I finally had internet access which helped an enormous amount. My parents finally connected our computer at home to the internet because they thought my sister and I needed it for school. I also had access to the computers in the high school library. By my junior year in high school, I was not really unpopular. Ironically my parent's overbearing pressure to be a 'normal kid' probably prevented me from having a social life until I got a little independence. Sadly I was still constantly in trouble in school throughout my high school years. The abuse at home was very bad. But,...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Some quick notes on "effective altruism", published by Jonas Vollmer on the effective altruism forum. Introduction I have some concerns about the "effective altruism" branding of the community. I recently posted them as a comment, and some people encouraged me to share them as a full post instead, which I'm now doing. I think this conversation is most likely not particularly useful or important to have right now, but there's some small chance it could be pretty valuable. This post is based on my personal intuition and anecdotal evidence. I would put more trust in well-run surveys of the right kinds of people or other more reliable sources of evidence. "Effective Altruism" sounds self-congratulatory and arrogant to some people: Calling yourself an "altruist" is basically claiming moral superiority, and anecdotally, my parents and some of my friends didn't like it for that reason. People tend to dislike it if others are very public with their altruism, perhaps because they perceive them as a threat to their own status (see this article, or do-gooder derogation against vegetarians). Other communities and philosophies, e.g., environmentalism, feminism, consequentialism, atheism, neoliberalism, longtermism don't sound as arrogant in this way to me. Similarly, calling yourself "effective" also has an arrogant vibe, perhaps especially among professionals in relevant areas. E.g., during the Zurich ballot initiative, officials at the city of Zurich unpromptedly asked me why I consider them "ineffective", indicating that the EA label basically implied to them that they were doing a bad job. I've also heard other professionals in different contexts react similarly. Sometimes I also get sarcastic "aaaah, you're the effective ones, you figured it all out, I see" reactions. "Effective altruism" sounds like a strong identity: Many people want to keep their identity small, but EA sounds like a particularly strong identity: It's usually perceived as both a moral commitment, a set of ideas, and a community. By contrast, terms like "longtermism" are somewhat weaker and more about the ideas per se. Perhaps partly because of this, at the Leaders Forum 2019, around half of the participants (including key figures in EA) said that they don’t self-identify as "effective altruists", despite self-identifying, e.g., as feminists, utilitarians, or atheists. I don't think the terminology was the primary concern for everyone, but it may play a role for several individuals. In general, it feels weirdly difficult to separate agreement with EA ideas from the EA identity. The way we use the term, being an EA or not is often framed as a binary choice, and it's often unclear whether one identifies as part of the community or agrees with its ideas. Some further, less important points: "Effective altruism" sounds more like a social movement and less like a research/policy project. The community has changed a lot over the past decade, from "a few nerds discussing philosophy on the internet" with a focus on individual action to larger and respected institutions focusing on large-scale policy change, but the name still feels reminiscent of the former. A lot of people don't know what "altruism" means. "Effective altruism" often sounds pretty awkward when translated to other languages. That said, this issue also affects a lot of the alternatives. We actually care about cost-effectiveness or efficiency (i.e., impact per unit of resource input), not just about effectiveness (i.e., whether impact is non-zero). This sometimes leads to confusion among people who first hear about the term. Taking action on EA issues doesn't strictly require altruism. While I think it’s important that key decisions in EA are made by people with a strong moral motivation, involvement in EA should be open to a lot of people, even if th...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: All Possible Views About Humanity's Future Are Wild, published by Holden Karnofsky on the effective altruism forum. This is a linkpost for/ Audio version is here Summary: In a series of posts starting with this one, I'm going to argue that the 21st century could see our civilization develop technologies allowing rapid expansion throughout our currently-empty galaxy. And thus, that this century could determine the entire future of the galaxy for tens of billions of years, or more. This view seems "wild": we should be doing a double take at any view that we live in such a special time. I illustrate this with a timeline of the galaxy. (On a personal level, this "wildness" is probably the single biggest reason I was skeptical for many years of the arguments presented in this series. Such claims about the significance of the times we live in seem "wild" enough to be suspicious.) But I don't think it's really possible to hold a non-"wild" view on this topic. I discuss alternatives to my view: a "conservative" view that thinks the technologies I'm describing are possible, but will take much longer than I think, and a "skeptical" view that thinks galaxy-scale expansion will never happen. Each of these views seems "wild" in its own way. Ultimately, as hinted at by the Fermi paradox, it seems that our species is simply in a wild situation. Before I continue, I should say that I don't think humanity (or some digital descendant of humanity) expanding throughout the galaxy would necessarily be a good thing - especially if this prevents other life forms from ever emerging. I think it's quite hard to have a confident view on whether this would be good or bad. I'd like to keep the focus on the idea that our situation is "wild." I am not advocating excitement or glee at the prospect of expanding throughout the galaxy. I am advocating seriousness about the enormous potential stakes. My view This is the first in a series of pieces about the hypothesis that we live in the most important century for humanity. In this series, I'm going to argue that there's a good chance of a productivity explosion by 2100, which could quickly lead to what one might call a "technologically mature"[1] civilization. That would mean that: We'd be able to start sending spacecraft throughout the galaxy and beyond. These spacecraft could mine materials, build robots and computers, and construct very robust, long-lasting settlements on other planets, harnessing solar power from stars and supporting huge numbers of people (and/or our "digital descendants"). See Eternity in Six Hours for a fascinating and short, though technical, discussion of what this might require. I'll also argue in a future piece that there is a chance of "value lock-in" here: whoever is running the process of space expansion might be able to determine what sorts of people are in charge of the settlements and what sorts of societal values they have, in a way that is stable for many billions of years.[2] If that ends up happening, you might think of the story of our galaxy[3] like this. I've marked major milestones along the way from "no life" to "intelligent life that builds its own computers and travels through space." Thanks to Ludwig Schubert for the visualization. Many dates are highly approximate and/or judgment-prone and/or just pulled from Wikipedia (sources here), but plausible changes wouldn't change the big picture. The ~1.4 billion years to complete space expansion is based on the distance to the outer edge of the Milky Way, divided by the speed of a fast existing human-made spaceship (details in spreadsheet just linked); IMO this is likely to be a massive overestimate of how long it takes to expand throughout the whole galaxy. See footnote for why I didn't use a logarithmic axis.[4] ??? That's crazy! According to me, there's a dec...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Some personal thoughts on EA and systemic change, published by CarlShulman on the effective altruism forum. DavidNash requested that I repost my comment below, on what to make of discussions about EA neglecting systemic change, as a top-level post. These are my off-the-cuff thoughts and no one else's. In summary (to be unpacked below): Actual EA is able to do assessments of systemic change interventions including electoral politics and policy change, and has done so a number of times The great majority of critics of EA invoking systemic change fail to present the simple sort of quantitative analysis given above for the interventions they claim excel, and frequently when such analysis is done the intervention does not look competitive by EA lights Nonetheless, my view is that historical data do show that the most efficient political/advocacy spending, particularly aiming at candidates and issues selected with an eye to global poverty or the long term, does have higher returns than GiveWell top charities (even ignoring nonhumans and future generations or future technologies); one can connect the systemic change critique as a position in intramural debates among EAs about the degree to which one should focus on highly linear, giving as consumption, type interventions EAs who are willing to consider riskier and less linear interventions are mostly already pursuing fairly dramatic systemic change, in areas with budgets that are small relative to political spending (unlike foreign aid) As funding expands in focused EA priority issues, eventually diminishing returns there will equalize with returns for broader political spending, and activity in the latter area could increase enormously: since broad political impact per dollar is flatter over a large range political spending should either be a very small or very large portion of EA activity In full: Actual EA is able to do assessments of systemic change interventions including electoral politics and policy change, and has done so a number of times Empirical data on the impact of votes, the effectiveness of lobbying and campaign spending work out without any problems of fancy decision theory or increasing marginal returns E.g. Andrew Gelman's data on US Presidential elections shows that given polling and forecasting uncertainty a marginal vote in a swing state average something like a 1 in 10 million chance of swinging an election over multiple elections (and one can save to make campaign contributions 80,000 Hours has a page (there have been a number of other such posts and discussion, note that 'worth voting' and 'worth buying a vote through campaign spending or GOTV' are two quite different thresholds) discussing this data and approaches to valuing differences in political outcomes between candidates; these suggest that a swing state vote might be worth tens of thousands of dollars of income to rich country citizens But if one thinks that charities like AMF do 100x or more good per dollar by saving the lives of the global poor so cheaply, then these are compatible with a vote being worth only a few hundred dollars If one thinks that some other interventions, such as gene drives for malaria eradication, animal advocacy, or existential risk interventions are much more cost-effective than AMF, that would lower the value further except insofar as one could identify strong variation in more highly-valued effects Experimental data on the effects of campaign contributions suggest a cost of a few hundred dollars per marginal vote (see, e.g. Gerber's work on GOTV experiments) Prediction markets and polling models give a good basis for assessing the chance of billions of dollars of campaign funds swinging an election If there are increasing returns to scale from large-scale spending, small donors can convert their funds into a smal...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Reality is often underpowered, published by Gregory_Lewis on the effective altruism forum. Introduction When I worked as a doctor, we had a lecture by a paediatric haematologist, on a condition called Acute Lymphoblastic Leukaemia. I remember being impressed that very large proportions of patients were being offered trials randomising them between different treatment regimens, currently in clinical equipoise, to establish which had the edge. At the time, one of the areas of interest was, given the disease tended to have a good prognosis, whether one could reduce treatment intensity to reduce the long term side-effects of the treatment whilst not adversely affecting survival. On a later rotation I worked in adult medicine, and one of the patients admitted to my team had an extremely rare cancer,[1] with a (recognised) incidence of a handful of cases worldwide per year. It happened the world authority on this condition worked as a professor of medicine in London, and she came down to see them. She explained to me that treatment for this disease was almost entirely based on first principles, informed by a smattering of case reports. The disease unfortunately had a bleak prognosis, although she was uncertain whether this was because it was an aggressive cancer to which current medical science has no answer, or whether there was an effective treatment out there if only it could be found. I aver that many problems EA concerns itself with are closer to the second story than the first. That in many cases, sufficient data is not only absent in practice but impossible to obtain in principle. Reality is often underpowered for us to wring the answers from it we desire. Big units of analysis, small samples The main driver of this problem for ‘EA topics’ is that the outcomes of interest have units of analysis for which the whole population (leave alone any sample from it) is small-n: e.g. outcomes at the level of a whole company, or a whole state, or whole populations. For these big unit of analysis/small sample problems, RCTs face formidable in principle challenges: Even if by magic you could get (e.g.) all countries on earth to agree to randomly allocate themselves to policy X or Y, this is merely a sample size of ~200. If you’re looking at companies relevant to cage-free campaigns, or administrative regions within a given state, this can easily fall another order of magnitude. These units of analysis tend highly heterogeneous, almost certainly in ways that affect the outcome of interest. Although the key ‘selling point’ of the RCT is it implicitly controls for all confounders (even ones you don’t know about), this statistical control is a (convex) function of sample size, and isn’t hugely impressive at ~ 100 per arm: it is well within the realms of possibility for the randomisation happen to give arms with unbalanced allocation of any given confounding factor. ‘Roughly’ (in expectation) balanced intervention arms are unlikely to be good enough in cases where the intervention is expected to have much less effect on the outcome than other factors (e.g. wealth, education, size, whatever), thus an effect size that favours one arm or the other can be alternatively attributed to one of these. Supplementing this raw randomisation by explicitly controlling for confounders you suspect (cf. block randomisation, propensity matching, etc.) has limited value when don’t know all the factors which plausibly ‘swamp’ the likely intervention effect (i.e. you don’t have a good predictive model for the outcome but-for the intervention tested). In any case, they tend to trade-off against the already scarce resource of sample size. These ‘small sample’ problems aren’t peculiar to RCTs, but endemic to all other empirical approaches. The wealth of econometric and quasi-experimental methods (e.g. IVs, ...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Big List of Cause Candidates, published by NunoSempere on the effective altruism forum. Many thanks to Ozzie Gooen for suggesting this project, to Marta Krzeminska for editing help and to Michael Aird and others for various comments. In the last few years, there have been many dozens of posts about potential new EA cause areas, causes and interventions. Searching for new causes seems like a worthy endeavour, but on their own, the submissions can be quite scattered and chaotic. Collecting and categorizing these cause candidates seemed like a clear next step. We —Ozzie Gooen of the Quantified Uncertainty Research Institute and I— might later be interested in expanding this work and eventually using it for forecasting —e.g., predicting whether each candidate would still seem promising after much more rigorous research. At the same time, we feel like this list itself can be useful already. Further, as I kept adding more and more cause candidates, I realized that aiming for completeness was a fool's errand, or at least too big a task for an individual working alone. Below is my current list with a simple categorization, as well as an occasional short summary which paraphrases or quotes key points from the posts linked. See the last appendix for some notes on nomenclature. If there are any entries I missed (and there will be), please say so in the comments and I'll add them. I also created the "Cause Candidates" tag on the EA Forum and tagged all of the listed posts there. They are also available in a Google Sheet. Animal Welfare and Suffering Pointer: This cause has its various EA Forum tags (farmed animal welfare, wild animal welfare, meat alternatives), where more cause candidates can be found. Brian Tomasik et al.'s Essays on Reducing Suffering are also a gift that keeps on giving for this and other cause areas. 1.Wild Animal Suffering Caused by Fires Related categories: Politics: System change, targeted change, policy reform. Wild animal suffering caused by fires and ways to prevent it: a noncontroversial intervention (@Animal_Ethics) An Animal Ethics grantee designed a protocol aimed at helping animals during and after fires. The protocol contains specific suggestions, but the path to turning these into policy is unclear. 2. Invertebrate Welfare Invertebrate Welfare Cause Profile (@Jason Schukraft) The scale of direct human impact on invertebrates (@abrahamrowe) "In this post, we apply the standard importance-neglectedness-tractability framework to invertebrate welfare to determine, as best we can, whether this is a cause area that is worth prioritizing. We conclude that it is." Note: See also Brian Tomasik's Do Bugs Feel Pain. 3. Humane Pesticides Humane Pesticides as the Most Marginally Effective Cause (@JeffMJordan) Improving Pest Management for Wild Insect Welfare (@Wild_Animal_Initiative) The post argues that insects experience consciousness, and that there are a lot of them, so we should give them significant moral weight (comments contain a discussion on this point). The post goes on to recommend subsidization of less-painful pesticides, an idea initially suggested by Brian Tomasik, who "estimates this intervention to cost one dollar per 250,000 less-painful deaths." The second post goes into much more depth. 4. Diet Change Is promoting veganism neglected and if so what is the most effective way of promoting it? (@samuel072) Animal Equality showed that advocating for diet change works. But is it cost-effective? (@Peter_Hurford, @Marcus_A_Davis) Cost-effectiveness analysis of a program promoting a vegan diet (@nadavb, @sella, @GidonKadosh, @MorHanany) Measuring Change in Diet for Animal Advocacy (@Jacob_Peacock) The first post is a stub. The second post looks at a reasonably high-powered study on individual outreach. It concludes that, based on reasonable assum...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Killing the ants, published by Joe_Carlsmith on the effective altruism forum. (Cross-posted from Hands and Cities) I. The ants Recently, my housemates and I started seeing a lot of ants in the house. They marched in long lines along the edges of the basement and the bathrooms. A few showed up in the drawers. My girlfriend put out some red pepper, which was supposed to deter them from one of their routes, but they cut a line straight through. We thought maybe they were sheltering from the rain, which had become more frequent. We had had ants before; we’d talked, then, about whether to do something about it; but we hadn’t, and eventually they disappeared. We thought maybe this would happen again. It didn’t. Over weeks, the problem got worse. There were hundreds of ants in the upstairs bathroom. They started to show up much more in the kitchen. We threw out various things, sealed various things. They showed up in beds. Kitchen drawers were now ant territory. We talked about what to do. We were reluctant to kill them, which was part of why we had waited. But a number of people in the house felt that the situation was getting out of hand, and that we were on track for something much harder to control. I thought of a house I had stayed at, where the ants swarmed over the coffee maker every morning, and efforts (I’m not sure how extreme) to get rid of them had failed. The most effective killing method is to poison the colony as a whole. The ants are lured into a sugary liquid that also contains borax, which is poisonous for ants, but relatively safe for humans. They then track the poison back to the colony. We talked about how bad this would be for the ants — and in particular, the fact that the poison is slow-acting. Crushing them directly, we thought, might be more humane; though it would also be more time-consuming, and less likely to solve the problem. Eventually, though without resolving all disagreements amongst housemates, we put out the poison baits (my girlfriend also tried cloves, coffee grounds, and lemon juice around that time, as well as luring the ants to some peanut butter and honey outside, away from the house). The ants in the kitchen disappeared. There are still a few in the upstairs bathroom; and inside the clear plastic baits, you can see ant bodies, in the syrup. II. Owning it At one point, on the topic of the ants, I said, in passing, something like: “may we be forgiven.” My girlfriend responded seriously, saying something like: “We won’t be. There’s no forgiveness.” Something about her response made me realize that the choice to kill the ants had had, for me, a quality of unreality. I had exerted some limited advocacy, in the direction of some hazy set of norms, but with no real sense of responsibility for what I was doing. There was something performative and disengaged about it — a type of disengagement in which one, for example, “feels bad” about killing the ants — and the question of whether we were doing the “right thing” was part of that. I was looking at the concepts. I was hoping for some kind of conformity, some kind of “pass” from the moral “authorities.” But I wasn’t looking down my arm, at the world I was creating, and the ants that were dying as a result. I wasn’t owning it. Regardless of whether our choice was right or wrong (I’m still not sure), we chose for these ants to die. We killed them. What we got, when we chose, was not a “good job” or “bad job” from the universe: what we got was this world, and not another. And this world was right there, in front of me, whether we should be “forgiven” or no. Not owning the choice was made easier, I think, by the fact that the death of the ants would mostly occur offscreen; outside of my “zone”, and not, directly, by my own hand. Indeed, I had declined to crush the ants myself, and I hadn’t bee...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Cultured meat predictions were overly optimistic, published by Neil_Dullaghan on the effective altruism forum. In a 2021 MotherJones article, Sinduja Rangarajan, Tom Philpott, Allison Esperanza, and Alexis Madrigal compiled and visualized 186 publicly available predictions about timelines for cultured meat (made primarily by cultured meat companies and a handful of researchers). I added 11 additional predictions ACE had collected, and 76 other predictions I found in the course of a forthcoming Rethink Priorities project. Check out our dataset Of the 273 predictions collected, 84 have resolved - nine resolving correctly, and 75 resolving incorrectly. Additionally, another 40 predictions should resolve at the end of the year and look to be resolving incorrectly. Overall, the state of these predictions suggest very systematic overconfidence. Cultured meat seems to have been perpetually just a few years away since as early as 2010 and this track record plausibly should make us skeptical of future claims from producers that cultured meat is just a few years away. Here I am presenting the results of predictions that have resolved, keeping in mind they are probably not a representative sample of publicly available predictions, nor assembled from a systematic search. Many of these are so vaguely worded that it’s difficult to resolve them positively or negatively with high confidence. Few offer confidence ratings, so we can’t measure calibration. Below is the graphic made in the MotherJones article. It is interactive in the original article. The first sale of a ~70% cultured meat chicken nugget occurred in a restaurant in Singapore on 2020 December 19th for S$23 (~$17 USD) for two nugget dishes at the 1880 private member's club, created by Eat Just at a loss to the company (Update 2021 Oct 15:" 1880 has now stopped offering the chicken nuggets, owing to “delays in production,” but hopes to put them back on menus by the end of the year." (Aronoff, 2021). We have independently tried to acquire the products ourselves from the restaurant and via delivery but have been unsuccessful so far). 65 predictions made on cultured meat being available on the market or in supermarkets specifically can now be resolved. 56 were resolved negatively and in the same direction - overly optimistic (update: the original post said 52). None resolved negatively for being overly pessimistic. These could resolve differently depending on your exact interpretation but I don't think there is an order of magnitude difference in interpretations. The nine that plausibly resolved positively are listed below (I also listed nine randomly chosen predictions that resolved negatively). In 2010 "At least another five to 10 years will pass, scientists say, before anything like it will be available for public consumption". (A literal reading of this resolves correct, even though one might interpret the meaning as a product will be available soon after ten years) Mark Post of Maastricht University & Mosa Meat in 2014 stated he “believes a commercially viable cultured meat product is achievable within seven years." (It’s debatable if the Eat Just nugget is commercially viable as it is understood to be sold at a loss for the company). Peter Verstate of Mosa Meat in 2016 predicted that premium priced cultured products should be available in 5 years (ACE 2017) Mark Post in 2017 "says he is happy with his product, but is at least three years from selling one" (A literal reading of this resolves correct, even though one might interpret the meaning as a product will be available soon after three years) Bruce Friedrich of the Good Food Institute in March 2018 predicted “clean-meat products will be available at a high price within two to three years” Unnamed scientists in December 2018 “say that you can buy it [meat in a labor...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Make a $100 donation into $200 (or more), published by WilliamKiely on the effective altruism forum. Latest Update: On Nov 24 at 1:01pm PT, the matching fund pool was increased to $600,000. Check the realtime dashboard to see how much is still available to allocate. Of the first $250,000 in matching funds, more than 82% went to nonprofits you all donated to: Donation Match Terms This year, starting on November 1, Every.org is offering a very attractive $250,000 true counterfactual donation match. (Realtime dashboard of remaining funds.) /@william.kiely?c=gg25 Every.org will match the first donation you make to each US 501(c)(3) nonprofit you give to 1:1 up to $100 per donor per nonprofit. Currently, Every.org will contribute an extra $10 to your donation if you click to share your donation after donating. This might change (what it was originally). The Match Terms in Every.org's words: A donor can support multiple nonprofits, but only the first donation they make to each of those nonprofits will be matched. If someone makes two $50 donations to the same organization, then only the first $50 would be matched. If someone makes a $1000 donation, then only the first $100 is matched. If someone makes ten $100 donations to different organizations, then all ten donations will be matched. Steps to Participate Join with:/@william.kiely?c=gg25 (If you're a new user, this will give you and I $25 in giving credit in addition to the match described above (Update: I believe this new user incentive was removed by Nov 24), plus help me track how many EAs participate in the match so I can share the information with the community.) Check the live dashboard to see if there are remaining matching funds. If so, donate $100[1] to a nonprofit of your choice (to get your donation automatically matched 1:1) After donating, click one of the links to share your donation (to get the extra share incentive, currently +$10) Repeat steps 3 and 4 for every nonprofit you want to support! FAQ Answers Everyone can participate, regardless of country, even if you already joined last year. Fees are low, so donate by card if it's easier for you. Or if you'd prefer to eliminate all fees you can do so by connecting your bank account. Tax receipts: You can get these easily in your account on your My Giving page. If this sounds familiar... It's because 198 of you participated in a previous donation match sponsored by the same Every.org after seeing the post Make a $10 donation into $35 in December 2020. We successfully directed $4,950 in matching funds to highly effective nonprofits during that match. It was quite popular because it only took ~3 minutes for each person to direct $25 in matching funds. I'm hopeful that even more of you will participate in Every.org's current match since it's just as easy and yet the limits are much higher. thanks for listening. to help us out with the nonlinear library or to learn more, please visit nonlinear.org.
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Are we living at the most influential time in history?, published BY WilliamKiely on the effective altruism forum. Latest Update: On Nov 24 at 1:01pm PT, the matching fund pool was increased to $600,000. Check the realtime dashboard to see how much is still available to allocate. Of the first $250,000 in matching funds, more than 82% went to nonprofits you all donated to: Donation Match Terms This year, starting on November 1, Every.org is offering a very attractive $250,000 true counterfactual donation match. (Realtime dashboard of remaining funds.) /@william.kiely?c=gg25 Every.org will match the first donation you make to each US 501(c)(3) nonprofit you give to 1:1 up to $100 per donor per nonprofit. Currently, Every.org will contribute an extra $10 to your donation if you click to share your donation after donating. This might change (what it was originally). The Match Terms in Every.org's words: A donor can support multiple nonprofits, but only the first donation they make to each of those nonprofits will be matched. If someone makes two $50 donations to the same organization, then only the first $50 would be matched. If someone makes a $1000 donation, then only the first $100 is matched. If someone makes ten $100 donations to different organizations, then all ten donations will be matched. Steps to Participate Join with:/@william.kiely?c=gg25 (If you're a new user, this will give you and I $25 in giving credit in addition to the match described above (Update: I believe this new user incentive was removed by Nov 24), plus help me track how many EAs participate in the match so I can share the information with the community.) Check the live dashboard to see if there are remaining matching funds. If so, donate $100[1] to a nonprofit of your choice (to get your donation automatically matched 1:1) After donating, click one of the links to share your donation (to get the extra share incentive, currently +$10) Repeat steps 3 and 4 for every nonprofit you want to support! FAQ Answers Everyone can participate, regardless of country, even if you already joined last year. Fees are low, so donate by card if it's easier for you. Or if you'd prefer to eliminate all fees you can do so by connecting your bank account. Tax receipts: You can get these easily in your account on your My Giving page. If this sounds familiar... It's because 198 of you participated in a previous donation match sponsored by the same Every.org after seeing the post Make a $10 donation into $35 in December 2020. We successfully directed $4,950 in matching funds to highly effective nonprofits during that match. It was quite popular because it only took ~3 minutes for each person to direct $25 in matching funds. I'm hopeful that even more of you will participate in Every.org's current match since it's just as easy and yet the limits are much higher. You can donate less than $100 and still get matched, but note that you will forfeit your ability to get the full match for that nonprofit, even if you donate again. Per the terms: "If someone makes two $50 donations to the same organization, then only the first $50 would be matched." thanks for listening. to help us out with the nonlinear library or to learn more, please visit nonlinear.org.
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: 2018-2019 Long-Term Future Fund Grantees: How did they do?, published by NunoSempere on the effective altruism forum. Introduction At the suggestion of Ozzie Gooen, I looked at publicly available information around past LTF grantees. We've been investigating the potential to have more evaluations of EA projects, and the LTFF grantees seemed to represent some of the best examples, as they passed a fairly high bar and were cleanly delimited. For this project, I personally investigated each proposal without consulting many others. This work was clearly limited by not reaching out to others directly, but requesting external involvement would have increased costs significantly. We were also partially interested in finding how much we could figure out with this limitation. Background During its first two rounds (round 1, round 2) of the LTF fund, under the leadership of Nick Beckstead, grants went mostly to established organizations, and didn’t have informative write-ups. The next few rounds, under the leadership of Habryka et. al., have more informative write-ups, and a higher volume of grants, which are generally more speculative. At the time, some of the grants were scathingly criticised in the comments. The LTF at this point feels like a different, more active beast than under Nick Beckstead. I evaluated its grants from the November 2018 and April 2019 rounds, meaning that the grantees have had at least two years to produce some legible output. Commenters pointed out that the 2018 LTFF is pretty different from the 2021 LTFF, so it’s not clear how much to generalize from the projects reviewed in this post. Despite the trend towards longer writeups, the reasoning for some of these grants is sometimes opaque to me, or the grant makers sometimes have more information than I do, and choose not to publish it. Summary By outcome Flag Number of grants Funding ($) More successful than expected 6 (26%) $ 178,500 (22%) As successful as expected 5 (22%) $ 147,250 (18%) Not as successful as hoped for 3 (13%) $ 80,000 (10%) Not successful 3 (13%) $ 110,000 (13%) Very little information 6 (26%) $ 287,900 (36%) Total 23 $ 803,650 Not included in the totals or in the percentages are 5 grants worth a total of $195,000 which I tagged didn’t evaluate because of a perceived conflict of interest. Method I conducted a brief Google, LessWrong and EA forum search of each grantee, and attempted to draw conclusions from the search. However, quite a large fraction of grantees don't have much of an internet presence, so it is difficult to see whether the fact that nothing is findable under a quick search is because nothing was produced, or because nothing was posted online. Overall, one could spend a lot of time with an evaluation. I decided to not do that, and go for an “80% of value in 20% of the time”-type evaluation. Grantee evaluation examples A private version of this document goes by grantees one by one, and outlines what public or semi-public information there is about each grant, what my assessment of the grant’s success is, and why. I did not evaluate the grants where I had personal information which people gave me in a context in which the possibility of future evaluation wasn't at play. I shared it with some current LTFF fund members, and some reported finding it at least somewhat useful. However, I don’t intend to make that version public, because I imagine that some people will perceive evaluations as unwelcome, unfair, stressful, an infringement of their desire to be left alone, etc. Researchers who didn’t produce an output despite getting a grant might feel bad about it, and a public negative review might make them feel worse, or have other people treat them poorly. This seems undesirable because I imagine that most grantees were taking risky bets with a high expected value, even i...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Is EA Growing? EA Growth Metrics for 2018, published by Peter Wildeford on the effective altruism forum. Is EA growing? Rather than speculating from anecdotes, I decided to collect some data. This is a continuation of the analysis started last year. For each trend, I collected the raw data and also highlighted in green where the highest point was reached (though this may be different from the period with the largest growth depending on which derivative you are looking at). You can download the raw data behind these tables here. Implications This year, I decided to separate growth stats into a few different categories, looking at how growth changes when we talk about people learning about EA through reading; increasing their commitment through joining a newsletter, joining a Facebook group, joining the EA Forum, or subscribing to a podcast; increasing engagement by committing -- self-identifying as EA on the EA Survey and/or taking a pledge; and having an impact by doing something, like donating or changing their careers[33]. When looking at this, it appears that there has been a decline of people searching and looking for EA (at least in the ways we track), with the exception of 80,000 Hours pageviews and EA Reddit page subscriptions which continued to grow but at a much lower pace. When we look at the rate of change, we can see a fairly clear decline across all metrics: We can also see that when it comes to driving initial EA readership and engagement, 80,000 Hours is very clearly leading the pack while other sources of learning about EA are declining a bit: In fact, the two sources of learning about EA that seem to best represent natural search -- Google interest and Wikipedia pageviews -- appear somewhat correlated and are now both declining together. However, there are more people consuming EA in closer ways (what I termed “joining”) -- while growth rate in the EA Newsletter and 80K Newsletter has slowed down, the EA FB is more active, the EA Reddit and total engagement from 80K continues to grow, and new avenues like Vox's Future Perfect and 80K's podcast have opened up. However, this view of growth can change depending on which derivative you look at. Looking at the next derivative makes clear that there was a large explosion of interest in 2017 in the EA Reddit and the EA Newsletter that wasn’t repeated in 2018: Additionally, Founder's Pledge continues to grow and OFTW has had explosive growth, though GWWC has stalled out a bit. The EA Survey has also recovered from a sluggish 2017 to break records in 2018. Looking at the rate of change shows Founder's Pledge clearly increasing, GWWC decreasing, and OFTW’s having fairly rapid growth in 2018 after a slowdown in 2017. Lastly, the part we care about most seems to be doing the strongest -- while tracking the actual impact of the EA movement is really hard and very sensitive to outliers, nearly every doing/impact metric we do track was at its strongest in either 2017 or 2018, with only GiveWell and 80K seeing a slight decline in 2018 relative to 2017. However, looking at the actual rate of change shows a bleaker picture that we may be approaching a plateau. Conclusion Like last year, it still remains a bit difficult to infer broad trends given that a decline for one year might be the start of a true plateau or decline (as appears to be the case for GWWC) or may just be a one-time blip prior to a bounce back (as appears to be the case for the EA Survey[34]). Overall, the decline in people first discovering EA (reading) and the growth of donations / career changes (doing) makes sense, as it is likely the result of the intentional effort across several groups and individuals in EA over the past few years to focus on high-fidelity messaging and growing the impact of pre-existing EAs and deliberate decisions to stop mas...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Why I find longtermism hard, and what keeps me motivated, published by Michelle_Hutchinson on the effective altruism forum. [Cross-posted from the 80,000 Hours blog] I find working on longtermist causes to be — emotionally speaking — hard: There are so many terrible problems in the world right now. How can we turn away from the suffering happening all around us in order to prioritise something as abstract as helping make the long-run future go well? A lot of people who aim to put longtermist ideas into practice seem to struggle with this, including many of the people I’ve worked with over the years. And I myself am no exception — the pull of suffering happening now is hard to escape. For this reason, I wanted to share a few thoughts on how I approach this challenge, and how I maintain the motivation to work on speculative interventions despite finding that difficult in many ways. This issue is one aspect of a broader issue in EA: figuring out how to motivate ourselves to do important work even when it doesn’t feel emotionally compelling. It’s useful to have a clear understanding of our emotions in order to distinguish between feelings and beliefs we endorse and those that we wouldn’t — on reflection — want to act on. What I’ve found hard First, I don’t want to claim that everyone finds it difficult to work on longtermist causes for the same reasons that I do, or in the same ways. I’d also like to be clear that I’m not speaking for 80,000 Hours as an organisation. My struggles with the work I’m not doing tend to centre around the humans suffering from preventable diseases in poor countries. That’s largely to do with what I initially worked on when I came across effective altruism. For other people, it’s more salient that they aren’t actively working to prevent the barbarity of some factory farming practices. I’m not going to talk about all of the ways in which people might find it hard to focus on the long-run future — for the purposes of this article, I’m going to focus specifically on my own experience. I feel a strong pull to help people now A large part of the suffering in the world today simply shouldn’t exist. People are suffering and dying for want of cheap preventative measures and cures. Diseases that rich countries have managed to totally eradicate still plague millions around the world. There’s strong evidence for the efficacy of cheap interventions like insecticide-treated anti-malaria bed nets. Yet many of us in rich countries are well off financially, and spend a significant proportion of our income on non-necessity goods and services. In the face of this absurd and preventable inequity, it feels very difficult to believe that I shouldn’t be doing anything to ameliorate it. Likewise, it often feels hard to believe that I shouldn’t be helping people geographically close to me — such as homeless people in my town, or people who are being illegitimately incarcerated in my country. It’s hard to deal with there being visible and preventable suffering that I’m not doing anything to combat. For me, putting off helping people alive today in favour of helping those in the future is even harder than putting off helping those in my country in favour of those on the other side of the world. This is in part due to the sense that if we don’t take actions to improve the future, there are others coming after us who can. By contrast, if we don’t take action to help today’s global poor, those coming after us cannot step in and take our place. The lives we fail to save this year are certain to be lost and grieved for. Another reason this is challenging is that wealth seems to be sharply increasing over time. This means that we have every reason to believe that people in the future will be far richer than people today, and it would seem to follow that people in the future d...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Introducing the Legal Priorities Project, published by jonasschuett on the effective altruism forum. We’re excited to introduce a new EA organization: the Legal Priorities Project. About us The Legal Priorities Project is an independent, global research project founded by researchers from Harvard University. Our mission is to conduct legal research that tackles the world’s most pressing problems. This currently leads us to focus on the protection of future generations. The project is led by Christoph Winter (ITAM/Harvard); the other founding team members are Cullen O’Keefe (OpenAI/GovAI), Eric Martínez (MIT), and Jonas Schuett (Goethe University Frankfurt). For more information about our team, visit our website. The idea was born at the EA group at Harvard Law School in Fall 2018. Since then, we raised two rounds of funding from Ben Delo at the advice of Effective Giving, built a highly motivated and mission-aligned core team, registered as a 501(c)(3) nonprofit, hosted a seminar at Harvard Law School, and organized our first summer research fellowship. Besides that, we worked on our research agenda and a number of other research projects. We’re currently assessing the desirability and feasibility of having a formal affiliation with a university. We consider founding a center or institute at a leading law school in the US or UK within the coming 2 years. Our research We aim to establish “legal priorities research” as a new research field. At the meta-level, we determine which problems legal scholars should work on in order to tackle the world’s most pressing problems. At the object-level, we conduct legal research on the identified problems. Our approach to legal priorities research is influenced by the longtermism paradigm. Consequently, we are currently focusing on the following cause areas: (1) improving the governance of advanced artificial intelligence, (2) mitigating risks from synthetic biology, (3) mitigating extreme risks from climate change, and (4) improving institutional design and decision-making. Legal priorities research can be viewed as a subset of global priorities research. While global priorities research is located at the intersection of philosophy and economics, legal priorities research focuses primarily on legal studies, although it is still highly interdisciplinary. We are currently working on a research agenda for legal priorities research. The agenda will be divided by cause areas and will contain a list of promising research projects for legal scholars. We hope to publish the agenda in December 2020. Sign up to our newsletter, if you want to receive an email when it gets published. We are also working on a number of object-level research projects. Please get in touch, if you want to collaborate with us on future research projects. You may also want to fill out our expression of interest form. Further information Website: legalpriorities.org Email: hello@legalpriorities.org LinkedIn: linkedin.com/company/legalpriorities Twitter: twitter.com/legalpriority Facebook: facebook.com/legalpriorities thanks for listening. to help us out with the nonlinear library or to learn more, please visit nonlinear.org.
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Can I have impact if I’m average?, published by Fabienne on the effective altruism forum. A friend of mine who is into EA said a few days ago that he thinks most people cannot have an impact, because to have an impact you need to be among the 0.1%-1% best in your field. I have encountered this thought in quite a few people in/interested in EA, some of whom say that this thought has dragged them down a lot. When I led an EA career workshop for students who received the Studienstiftung scholarship, one of my participants who had just realised he could have a lot more impact if he switched career paths, said to me something along the lines of: “Oh man, what I have been doing was worthless”. I replied: “Ehm no it wasn’t? :) You seem to have improved lives noticeably. The fact that there are better opportunities than what you did does not take away that value. In fact, it’s because improving even a single life is valuable that the best opportunities are so incredibly valuable.” 80k (probably rightly so) seeks to focus on the top 1%, but that does not mean that you cannot have (a lot of) impact if you are less good at what you do. Here is what I think is going on when people despair about their impact. I think our ability to feel what “unusually high impact” means is very limited. Our head knows that there is a big difference between saving a few people and saving a multitude of people, but our heart doesn’t quite get it. So what some people in EA then seem to do is this: They assign the value level “maximally valuable” to the most impactful thing someone could do - so far, so good. But then when they encounter a lower level of impact (such as saving one life), they reduce their value judgment by however lower the impact is compared to the highest possible impact. This leaves them with an inappropriately low judgement of value for this impact, because our judgement of value for the highest impact possible was way too low to start with. It's the opposite to what people outside of EA tend to do - (correctly) give a lot of value to saving one life but not scaling this judgement up appropriately. I think it's possible to avoid both mistakes - at least, I think that I am able to avoid them both. I think underestimating the value of significant but non-maximal impact is a problem. For one thing, it’s a misconception and misconceptions are rarely helpful. Second, I think this is probably bad for the mental health and productivity of our movement, because it de-motivates and saddens people. Third, it probably affects not only people who have “average” talent, whatever that means, but also those who are in fact excellent at something but who think of themselves as average. There seem to be a lot of people like this in EA. Fourth, I think it’s bad for public relations because it can make people feel useless and can come across as arrogant. How do we fix this misconception? I hope that this post helps a bit with that - what follows are some other ideas. Perhaps the idea I’m presenting here, or related ones, could be included in the mental health workshops at EA conferences together with CBT and ACT methods for those who want more help emotionally distancing themselves from this or other unhelpful thoughts. Movement builders could watch out for this misunderstanding and correct it, like I did at the workshop I mentioned above. Maybe EA-related websites could include the idea somewhere, such as in their FAQs. I don’t know how much these things would help, but my personal experience with clarifying this misconception to people has been positive. Thanks to Rob Long for helping me improve this post! thanks for listening. to help us out with the nonlinear library or to learn more, please visit nonlinear.org.
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: A new strategy for broadening the appeal of effective giving (GivingMultiplier.org), published by Lucius_Caviola on the effective altruism forum. In this post, I introduce an ongoing research project with the aim of bringing effective giving to a wider range of altruists. The strategy combines 1) donation bundling (splitting between your favorite and an effective charity), 2) asymmetrical matching (offering higher matching rates for allocating more to an effective charity), 3) a form of donor coordination (to provide the matching). After conducting a series of experiments, we will test our strategy in the real-world using our new website GivingMultiplier.org. This project is a collaboration with Prof Joshua Greene and is supported by an EA Funds grant. Background It is difficult to motivate people to give more effectively. Presenting people with information about charity effectiveness can increase effective giving to some extent (Caviola, Schubert, et al., 2020a; 2020b). However, the effect is limited because most people prefer to give to their favorite charity even when they know that other charities are more effective (Berman et al., 2018). This is because people are motivated by ‘warm glow’ of giving (Andreoni, 1990), which isn’t a good proxy for effectiveness. Another issue is that most people aren’t motivated to proactively seek out information about the most effective charities. But making people care more about effectiveness is difficult. In multiple studies I have found that presenting people with moral arguments makes little to no difference. (Though moral arguments might work for some people and under the right circumstances, cf. Lindauer et al., 2020; Schwitzgebel et al., 2020.) Therefore, the approach we take here is to work with people’s preferences instead of trying to change them. The strategy Below is a short summary of the set of techniques our strategy relies on. In our experiments, 2,000 (Amazon MechanicalTurk) participants made probabilistically implemented decisions involving real money. If you are interested in more details about our studies and results, you can find an early working draft here. 1) Donation bundling We found that donations to effective charities can be increased by up to 75% when people are offered the option to split their donation between their favorite and a highly effective charity (Study 1). We call this technique donation bundling. Most donors find such bundle options appealing because they enjoy nearly all the warm-glow of giving exclusively to their favorite charity, but also gain the satisfaction of giving more effectively and fairly (Study 2). Likewise, we find that third-parties perceive bundle donors as both highly warm and highly competent, as compared to donors who give exclusively to an emotionally appealing charity (warm, but less competent) or exclusively to a highly effective charity (competent, but less warm) (Study 3). 2) Asymmetrical matching The bundling technique can be enhanced by offering matching funds in an asymmetrical way, i.e. the matching rate increases as more is allocated to the effective charity. In our studies, participants were offered higher matching rates, the more they would give to the effective charity as opposed to their favorite charity. For example, they might get a 10% matching rate for giving 50% to their favorite and 50% to the effective charity, but a 20% matching rate for giving 100% to the effective charity. We found that asymmetrical matching can increase donations to effective charities by an additional 55% (Study 4). A key advantage of offering donation matching is that it provides people with no prior interest in effective giving to visit the site and choose to support a highly effective charity. 3) Matching as donor coordination Where does the matching funding come from? We ...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: SHIC Will Suspend Outreach Operations, published by cafelow on the effective altruism forum. A Q1 update and 2018 in review By Baxter Bullock and Catherine Low Since launching in 2016, Students for High-Impact Charity (SHIC), a project of Rethink Charity, has focused on educational outreach for high school students (primarily ages 16-18) through our interactive content. In January 2018, we began implementing instructor-led workshops, mostly in the Greater Vancouver area. Below, we summarize our experiences of 2018 and explain why we are choosing to suspend our outreach operations. Summary 2018 saw strong uptake, but difficulty securing long-term engagement - Within a year of instructor-led workshops, we presented 106 workshops, reaching 2,580 participants at 40 (mostly high school) institutions. We experienced strong student engagement and encouraging feedback from both teachers and students. However, we struggled in getting students to opt into advanced programming, which was our behavioral proxy for further engagement. By the end of April, SHIC outreach will function in minimal form, requiring very little staff time - Over the next two months, our team will gradually wind down delivered workshops at schools. We plan on maintaining a website with resources and fielding inquiries through a contact form for those who are looking for information on how best to implement EA education. The most promising elements of SHIC may be incorporated into other high-impact projects - The SHIC curriculum could likely be repurposed for other high-impact projects within the wider Rethink Charity umbrella. For example, it could be a tool for engaging potential high-net-worth donors, or as content to provide local group leaders. We believe in the potential of educational outreach and hope to revisit this in the future - While we acknowledge the possibility that poor attendance at advanced workshops is indicative of general interest level in our program and/or EA in general, it's also possible that the methods we used to facilitate long term engagement were inadequate. We think that under the right circumstances, educational outreach could be more fruitful. SHIC will release an exhaustive evaluation of our experience with educational outreach in the coming months. 2018 in review In late 2017 we made a strategic shift towards a high-fidelity model of student engagement through instructor-led workshops. We tested this model throughout 2018, with our instructors visiting schools in Greater Vancouver, Canada[1]. Most students (56%) participated in a single-session workshop lasting approximately 80 minutes. These workshops consisted of a giving game[2], followed by an overview of the core ideas of effective altruism[3], including coverage of key cause areas. The remaining 44% of participants participated in multi-session (typically three), in-depth workshops which usually included a giving game, interactive explorations of the topics mentioned above, a cause prioritization activity, and a discussion of effective career paths. Our goal for the second half of 2018 was to identify high-potential students from our school visits, and engage them further with supplementary advanced workshops at a central location in Vancouver. To gauge interest initially, we began with an opt-in approach for all interested students who provided an email address in order to obtain more information. We ran a workshop in November which primarily consisted of an in-depth activity on cause prioritization, and a workshop in December focused on effectively creating online fundraisers for the holidays. Our results The metrics we identified to gauge our success were: Teachers and school uptake Student survey results indicating shifts of opinion and/or behavior The number of students who continue to engage with the material...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Avoiding Munich's Mistakes: Advice for CEA and Local Groups, published by Larks on the effective altruism forum. If all mankind minus one, were of one opinion, and only one person were of contrary opinion, mankind would be no more justified in silencing that one person, than he, if he had the power, would be justified in silencing mankind. John Stuart Mill, On Liberty, p23 We strive to base our actions on the best available evidence and reasoning about how the world works. We recognise how difficult it is to know how to do the most good, and therefore try to avoid overconfidence, to seek out informed critiques of our own views, to be open to unusual ideas, and to take alternative points of view seriously. ... We are a community united by our commitment to these principles, not to a specific cause. Our goal is to do as much good as we can, and we evaluate ways to do that without committing ourselves at the outset to any particular cause. We are open to focusing our efforts on any group of beneficiaries, and to using any reasonable methods to help them. If good arguments or evidence show that our current plans are not the best way of helping, we will change our beliefs and actions. Excepted from The Guiding Principles of Effective Altruism Introduction This post argues that Cancel Culture is a significant danger to the potential of EA project, discusses the mistakes that were made by EA Munich and CEA in their deplatforming of Robin Hanson, and provides advice on how to avoid such issues in the future. As ever, I encourage you to use the navigation pane to jump to the parts of the article that are most relevant to you. In particular, if you are already convinced you might skip the 'examples' and 'quotes' sections. Background The Nature of Cancel Culture In the past couple of years, there’s been much damage done to the norms around free speech and inquiry, in substantial parts due to what’s often called cancel culture. Of relevance to the EA community is that there have been an increasing number of highly public threats and attacks on scientists and public intellectuals, where researchers are harassed online, disinvited from conferences, had their papers retracted, and fired, because of mass online mobs reacting to an accusation over slight wording on topics of race, gender, and other issues of identity, or guilt-by-association with other people who have also been attacked by such mobs. This is colloquially called ‘cancelling’, after the hashtags that have formed saying #CancelX or #xisoverparty, where X is some person, company or other entity, hashtags which are commonly trending on Twitter. While such mobs cannot attack every person who speaks in public, they can attack any person who speaks in public, leading to chilling effects where nobody wants to talk about the topics that can lead to cancelling. Cancel Culture essentially involves the following steps: A victim, often a researcher, says or does something that irks someone online. This critic then harshly criticises the person using attacks that are hard to respond to in our culture - the accusation of racism is a common one. The goal of this attack is to signal to a larger mob that they should pile on, with the hope of causing massive damage to the person’s private and professional lives. Many more people then join in the attack online, including (often) contacting their employer. People who defend the victim are attacked as also being guilty of a similar crime. Seeing this dynamic, many associates of the victim prefer to sever their relationship, rather than be subject to this abuse. This may also include their employer, for whom the loss of one employee seems a relatively small cost for maintaining PR. The online crowd may swiftly move on; however, the victim now lives under a cloud of suspicion that is hard to...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Thoughts on whether we're living at the most influential time in history, published by Buck on the effective altruism forum. (thanks to Claire Zabel, Damon Binder, and Carl Shulman for suggesting some of the main arguments here, obviously all flaws are my own; thanks also to Richard Ngo, Greg Lewis, Kevin Liu, and Sidney Hough for helpful conversation and comments.) Will MacAskill has a post, Are we living at the most influential time in history?, about what he calls the “hinge of history hypothesis” (HoH), which he defines as the claim that “we are living at the most influential time ever.” Whether HoH is true matters a lot for how longtermists should allocate their effort. In his post, Will argues that we should be pretty skeptical of HoH. EDIT: Will recommends reading this revised article of his instead of his original post. I appreciate Will’s clear description of HoH and its difference from strong longtermism, but I think his main argument against HoH is deeply flawed. The comment section of Will’s post contains a number of commenters making some of the same criticisms I’m going to make. I’m writing this post because I think the rebuttals can be phrased in some different, potentially clearer ways, and because I think that the weaknesses in Will’s argument should be more widely discussed. Summary: I think Will’s arguments mostly lead to believing that you aren’t an “early human” (a human who lives on Earth before humanity colonizes the universe and flourishes for a long time) rather than believing that early humans aren’t hugely influential, so you conclude that either humanity doesn’t have a long future or that you probably live in a simulation. I sometimes elide the distinction between the concepts of “x-risk” and “human extinction”, because it doesn’t matter much here and the abbreviation is nice. (This post has a lot of very small numbers in it. I might have missed a zero or two somewhere.) EDIT: Will's new post Will recommends reading this revised article of his instead of his original post. I believe that his new article doesn't make the assumption about the probability of civilization lasting for a long time, which means that my criticism "This argument implies that the probability of extinction this century is almost certainly negligible" doesn't apply to his new post, though it still applies to the EA Forum post I linked. I think that my other complaints are still right. The outside-view argument This is the argument that I have the main disagreement with. Will describes what he calls the “outside-view argument” as follows: 1. It’s a priori extremely unlikely that we’re at the hinge of history 2. The belief that we’re at the hinge of history is fishy 3. Relative to such an extraordinary claim, the arguments that we’re at the hinge of history are not sufficiently extraordinarily powerful Given 1, I agree with 2 and 3; my disagreement is with 1, so let’s talk about that. Will phrases his argument as: The prior probability of us living in the most influential century, conditional on Earth-originating civilization lasting for n centuries, is 1/n. The unconditional prior probability over whether this is the most influential century would then depend on one's priors over how long Earth-originating civilization will last for. However, for the purpose of this discussion we can focus on just the claim that we are at the most influential century AND that we have an enormous future ahead of us. If the Value Lock-In or Time of Perils views are true, then we should assign a significant probability to that claim. (i.e. they are claiming that, if we act wisely this century, then this conjunctive claim is probably true.) So that's the claim we can focus our discussion on. I have several disagreements with this argument. This argument implies that the probability of exti...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Opinion: Digital marketing is under-utilized in EA, published by JSWinchell on the effective altruism forum. In this post I will make the case that digital marketing is under-utilized by EA orgs as well as provide some example use cases. My hope is that this post leads to EA orgs testing the below or similar strategies. A large part of what Effective Altruism is trying to do is to change people’s beliefs and behaviors. Digital advertising is one tool for achieving this goal. The fact that corporations, governments, and nonprofits repeatedly invest millions of dollars in digital marketing programs is evidence of their efficacy. A couple notes: I work at Google/YouTube helping large advertisers run Google and YouTube Ads. For that reason this post does not touch on Facebook/Instagram//Twitter/TikTok, but I am sure there are large opportunities there as well. This post is focused on paid advertising. Cost estimates are based on previous experience and industry benchmarks, but costs vary based on the geography, season, tactic etc. If you plan on running any of the strategies described below, please reach out to me so we can coordinate with other charities that are planning on running similar strategies. If your EA org would like to explore running a digital marketing campaign please don’t hesitate to reach out to me at j.s.winchell@gmail.com. Search Ads Every year, millions of people ask Google questions related to charity, poverty, animal welfare, AI safety, etc. If we can direct those people to EA websites, they will get EA answers to their questions. Google gives registered charities $10K/month in free advertising credits. Of a sample of ~10 EA charities, only one was fully using this Google Ads Grant. With a little extra knowledge, spending the Google Ads Grant becomes much easier than described in previous posts (1, 2). If you work at an EA org and would like help spending your full Google Ads Grant please fill out this survey. Image/display Ads If your organization has a target audience and you know of websites that audience visits, display ads could be a very cost-effective way for your charity to achieve its goals. Example use case: Founders Pledge wants to spread the word about their pledge. They identify three websites frequented by founders and advertise on those websites. A standard benchmark for an image/display ad is $2 per 1,000 impressions (an impression is when an ad is served). This strategy would break even at one pledge per 1,000,000,000 impressions served. (Assumes advertising cost of $2 per 1,000 impressions and an average pledge size of $2M, which is based on ~$3B pledged and ~1,500 pledgers). While the optimal number of impressions served will be much less than 1,000,000,000, it is very likely higher than 0. In addition to sending founders to the Founders Pledge website, this tactic would also increase awareness of the pledge thereby making it easier for their outreach team to sign on new members. Video Ads YouTube Ads are a powerful and inexpensive way to deliver visual and audio messages to targeted audiences. You can target users using any combination of the following: Geography (radius targeting, zip/postal code, state) Household income (top 10%, 11-20%, etc.) Search history on Google and YouTube (e.g. users that searched for “best charity” or “factory farming” in the last 30 days) Types of websites visited (e.g. users that have visited the websites of large nonprofits) YouTube channels being watched at the time the impression serves (contextual targeting) Demographics (age, gender) Example use cases: Org A wants to boost enrollment in EA University groups. They have a member student record a simple 6 second selfie video inviting students to the group. They target 18-24 year-olds within a 10 mile radius of their target universities. They could...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Collection of good 2012-2017 EA forum posts, published by saulius on the effective altruism forum. I feel that older EA forum posts are not read nearly as much as they should. Hence, I collected the ones that seemed to be the most useful and still relevant today. I recommend going through this list in the same way you would go through the frontpage of this forum: reading the titles and clicking on the ones that seem interesting and relevant to you. Note that you can hover over links to see more details about each post. Also note that many of these posts have lower karma scores than most posts posted nowadays. This is in large part because until September 2018, all votes were worth only one karma point, and before September 2014 there was no karma system at all. Furthermore, the forum readership used to be lower. Hence, I don’t advise to pay too much attention to karma when choosing which of these posts to read. Most of these posts had a significantly higher karma than other posts posted around the same time. To create this list, I skimmed through the titles (and sometimes the contents) of all posts posted between 2012 and 2017. I relied on my intuition to decide which posts to include. Undoubtedly, I missed some good ones. Please feel free to point them out in the comments. Also note that in some cases the information in these posts might be outdated, or no longer reflect the opinions of their authors. Communication Supportive Scepticism See also: Supportive scepticism in practice Some Thoughts on Public Discourse Six Ways To Get Along With People Who Are Totally Wrong If you don't have good evidence one thing is better than another, don't pretend you do You have a set amount of "weirdness points". Spend them wisely. General reasoning In defence of epistemic modesty Integrity for consequentialists Beware surprising and suspicious convergence Cause-prioritization Why I'm skeptical about unproven causes (and you should be too) Follow up: Where I've Changed My Mind on My Approach to Speculative Causes How we can make it easier to change your mind about cause areas Cause prioritization for downside-focused value systems Five Ways to Handle Flow-Through Effects Post series by Micheal Dickens Long-term Future AI Safety Literature reviews by Larks: 2016, 2017, 2018, 2019 Will we eventually be able to colonize other stars? Notes from a preliminary review The timing of labour aimed at reducing existential risk Cognitive Science/Psychology As a Neglected Approach to AI Safety Principia Qualia: blueprint for a new cause area, consciousness research with an eye toward ethics and x-risk Why might the future be good? Personal thoughts on careers in AI policy and strategy My current thoughts on MIRI's "highly reliable agent design" work Improving disaster shelters to increase the chances of recovery from a global catastrophe Why long-run focused effective altruism is more common sense Advice on how to think about altruism Effective Altruism is a Question (not an ideology) Response: Effective Altruism is an Ideology, not (just) a Question Cheerfully Effective Altruism is Not a Competition Personal consumption changes as charity (a suggestion about how to decide whether to buy more expensive but more ethical products) Aim high, even if you fall short An embarrassment of riches Parenthood and effective altruism How much does it cost to have a child? EA is the best choice I've ever made Room for Other Things: How to adjust if EA seems overwhelming On everyday altruism and the local circle Helping other altruists Effective altruism as the most exciting cause in the world For more advice on how to think about altruism, see excellent blogs Minding our way (by Nate Soares) and Giving Gladly (by Julia Wise) Movement strategy Keeping the effective altruist movement welcoming The perspectives...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Objections to Value-Alignment between Effective Altruists, published by CarlaZoeC on the effective altruism forum. With this post I want to encourage an examination of value-alignment between members of the EA community. I lay out reasons to believe strong value-alignment between EAs can be harmful in the long-run. The EA mission is to bring more value into the world. This is a rather uncertain endeavour and many questions about the nature of value remain unanswered. Errors are thus unavoidable, which means the success of EA depends on having good feedback mechanisms in place to ensure mistakes can be noticed and learned from. Strong value-alignment can weaken feedback mechanisms. EAs prefer to work with people who are value-aligned because they set out to maximse impact per resource expended. It is efficient to work with people who agree. But a value-aligned group is likely intellectually homogenous and prone to breed implicit assumptions or blind spots. I also noticed particular tendencies in the EA community (elaborated in section: homogeneity, hierarchy and intelligence), which generate additional cultural pressures towards value-alignment, make the problem worse over time and lead to a gradual deterioration of the corrigibility mechanisms around EA. Intellectual homogeneity is efficient in the short-term, but counter-productive in the long-run. Value-alignment allows for short-term efficiency, but the true goal of EA – to be effective in producing value in the long- term – might not be met. Disclaimer All of this is based on my experience of EA over the timeframe 2015-2020. Experiences differ and I share this to test how generalisable my experiences are. I used to hold my views lightly and I still give credence to other views on developments in EA. But I am getting more, not less worried over time, particularly because others members have expressed similar views and worries to me but have not spoken out about them because they fear losing respect or funding. This is precisely the erosion of critical feedback mechanism that I point out here. I have a solid but not unshakable belief about the theoretical mechanism I outline is correct but I do not know to what extent it takes effect in EA. But I’m also not sure whether those who will disagree with me will know to what extent this mechanism is at work in their own community. What I am sure of however (on the basis of feedback from people who have read this post pre-publication) is that my impressions of EA are shared by others within the community, that they are the reason why some have left EA or never quite dared to enter. This alone is reason for me to share this - in the hope that a healthy approach to critique and a willingness to change in response to feedback from the external world is still intact. I recommend the impatient reader to skip forward to the section on Feedback Loops and Consequences. Outline I will outline reasons that lead EAs to prefer value-alignment and search for definitions of value-alignment. I then describe cultural traits of the community which play a role in amplifying this preference and finally evaluate what effect value-alignment might have on EAs feedback loops and goals. Axiomaticity Movements make explicit and obscure assumptions. They make explicit assumptions: they stand for something and exist with some purpose. An explicit assumption is, by my definition, one that was examined and consciously agreed upon. EA explicitly assumes that one should maximise the expected value of one’s actions in respect to a goal. Goals differ between members but mostly do not diverge greatly. They may be a reduction of suffering, the maximisation of hedons in the universe or the fulfilment of personal preferences, and others. But irrespective of individual goals EAs mostly agree that resources sh...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: List of ways in which cost-effectiveness estimates can be misleading, published by saulius on the effective altruism forum. In my cost-effectiveness estimate of corporate campaigns, I wrote a list of all the ways in which my estimate could be misleading. I thought it could be useful to have a more broadly-applicable version of that list for cost-effectiveness estimates in general. It could maybe be used as a checklist to see if no important considerations were missed when cost-effectiveness estimates are made or interpreted. The list below is probably very incomplete. If you know of more items that should be added, please comment. I tried to optimize the list for skimming. How cost estimates can be misleading Costs of work of others. Suppose a charity purchases a vaccine. This causes the government to spend money distributing that vaccine. It's unclear whether the costs of the government should be taken into account. Similarly, it can be unclear whether to take into account the costs that patients have to spend to travel to a hospital to get vaccinated. This is closely related to concepts of leverage and perspective. More on it can be read in Byford and Raftery (1998), Karnofsky (2011), Snowden (2018), and Sethu (2018). It can be unclear whether to take into account the fixed costs from the past that will not have to be spent again. E.g., costs associated with setting up a charity that are already spent and are not directly relevant when considering whether to fund that charity going forward. However, such costs can be relevant when considering whether to found a similar charity in another country. Some guidelines suggest annualizing fixed costs. When fixed costs are taken into account, it's often unclear how far to go. E.g., when estimating the cost of distributing a vaccine, even the costs of roads that were built partly to make the distribution easier could be taken into account. Not taking future costs into account. E.g., an estimate of corporate campaigns may take into account the costs of winning corporate commitments, but not future costs of ensuring that corporations will comply with these commitments. Future costs and effects may have to be adjusted for the possibility that they don't occur. Not taking past costs into account. In the first year, a homelessness charity builds many houses. In the second year, it finds homeless people to live in those houses. In the first year, the impact of the charity could be calculated as zero. In the second year, it could be calculated to be unreasonably high. But the charity wouldn't be able to sustain the cost-effectiveness of the second year. Not adjusting past or future costs for inflation. Not taking overhead costs into account. These are costs associated with activities that support the work of a charity. It can include operational, office rental, utilities, travel, insurance, accounting, administrative, training, hiring, planning, managerial, and fundraising costs. Not taking costs that don't pay off into account. Nothing But Nets is a charity that distributes bednets that prevent mosquito-bites and consequently malaria. One of their old blog posts, Sauber (2008), used to claim that "If you give $100 of your check to Nothing But Nets, you've saved 10 lives." While it may be true that it costs around $10 or less[1] to provide a bednet, and some bednets save lives, costs of bednets that did not save lives should be taken into account as well. According to GiveWell's estimates, it currently costs roughly $3,500 for a similar charity (Against Malaria Foundation) to save one life by distributing bednets. Wiblin (2017) describes a survey in which respondents were asked "How much do you think it would cost a typical charity working in this area on average to prevent one child in a poor country from dying unnecessarily, by ...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Introducing High Impact Athletes, published by Marcus Daniell on the effective altruism forum. Hi all, A while back I posted on here asking if there were any other pro athlete aspiring EAs. The response (while not including other pro athletes) was amazing, and the conversations and contacts that manifested from this forum were myriad. Thank you deeply for being such an awesome community! Now I am very pleased to say that High Impact Athletes has launched. We are an EA aligned non-profit run by pro athletes. HIA aims to channel donations to the most effective, evidence-based charities in the world in the areas of Global Health & Poverty and Environmental Impact. We will harness the wealth, fame, and social influence of professional athletes to bring as many new people in to the effective altruism framework as possible and create the biggest possible snowball of donations to the places where they can do the most good. You can poke around on the website to learn more at/ Feedback is welcomed, and even more welcome is a follow on any of the socials. I'm terrible at social media and could use all the help I can get to build an audience. Instagram: high.impact.athletes Twitter: HIAorg Facebook: @HIAorg On that note, if anyone is interested in helping out with the social media side of things or knows anyone who would be please do get in touch either on here or at marcus@highimpactathletes.com Thank you once again, you're all awesome. Cheers, Marcus Daniell thanks for listening. to help us out with the nonlinear library or to learn more, please visit nonlinear.org.
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Parenting: Things I wish I could tell my past self, published by Michelle_Hutchinson on the effective altruism forum. I have a baby who’s nearly 10 months old. I’ve been thinking about what I’d like to be able to go back and tell myself before I embarked on this journey. I suspect that some of the differences between how I experienced it and what I had read in books correlates with ways that other effective altruists might also experience things. I also generally felt that finding decent no-nonsense information about parenting was hard, and that the signal to noise ratio when googling for answers was peculiarly bad. Probably the most useful advice I got was from EA friends with kids. So I thought it might be useful to jot down some thoughts for other EAs likely to have kids soon (or hoping to support others who are!). Note that these are just my experiences. I’ve been surprised how easy it is when it comes to mothering I hear ‘this is how I did it’ as ‘if you’re not doing the same you’re doing it wrong’. I mean no such implication! Your mileage may vary on all of the below. Things I was surprised about: Not changing much as a person: The biggest uncertainty I had starting out was how much my interests and priorities would change when I had a baby. Various people I talked to confidently expected they would substantially change once the baby came along, for example that I would find being at home looking after a baby more interesting than it sounded in the abstract. A lot of the advice I read on the internet likewise indicated that people tended to want more maternity leave than they expected, and to be more inclined to go part time after having children. For those reasons, I roughly planned to take 3 months of maternity leave, but to be prepared for actually wanting more leave. In the actual event, I was really surprised by how little my inclinations changed. Far from wanting more maternity leave than I expected, I was keen throughout to be in touch with my colleagues and hear how things were going in the office, and wanted to get back to doing bits of work really quite soon after having Leo. This seemed in marked contrast with the other mothers I was meeting at baby groups, who had expected to want to hear about what was happening in their offices, but actually weren’t at all interested once the baby came along. I think I did too much assuming that when I had a baby I’d turn into a different kind of person, and not enough simply thinking about ‘given the kind of person I am, how do I expect having a baby to interface with that?’. Also, I did too much looking at the average of how people change, rather than noticing that people react in widely differing ways, which include ‘not changing much at all’. Overall it’s rather a relief to feel I’m still the same person, but now with a cute small person to spend time with. Finding childcare was harder than I expected. When I got to it, I wanted to go back to work before three months. My husband had committed to finishing various pieces of work before starting paternity leave (3 months in). For that reason, we were keen to arrange some child care for Leo when he was younger than three months. That turned out to be more difficult than I expected. Nurseries don’t tend to take kids that young and the agency we wrote to had trouble finding us someone who would be short term (and took a while to get back to us at each step). We got a recommendation for someone on care.com, which almost worked out, except they found out their current contract precluded them from also working for us. The process also felt intimidating, at a time when we were already learning a lot of new things, which slowed down how well we did at it. I think I should have approached it more with the mindset of ‘we need to hire someone, and hiring is hard!’ than I d...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: AI Governance: Opportunity and Theory of Impact, published by Allan Dafoe on the effective altruism forum. Note: We have recently opened up roles for researchers and a project manager at the Centre for the Governance of Artificial Intelligence, part of the Future of Humanity Institute, University of Oxford AI governance concerns how humanity can best navigate the transition to a world with advanced AI systems.[1] It relates to how decisions are made about AI,[2] and what institutions and arrangements would help those decisions to be made well. I believe advances in AI are likely to be among the most impactful global developments in the coming decades, and that AI governance will become among the most important global issue areas. AI governance is a new field and is relatively neglected. I’ll explain here how I think about this as a cause area and my perspective on how best to pursue positive impact in this space. The value of investing in this field can be appreciated whether one is primarily concerned with contemporary policy challenges or long-term risks and opportunities (“longtermism”); this piece is primarily aimed at a longtermist perspective. Differing from some other longtermist work on AI, I emphasize the importance of also preparing for more conventional scenarios of AI development. Contemporary Policy Challenges AI systems are increasingly being deployed in important domains: for many kinds of surveillance; by authoritarian governments to shape online discourse; for autonomous weapons systems; for cyber tools and autonomous cyber capabilities; to aid and make consequential decisions such as for employment, loans, and criminal sentencing; in advertising; in education and testing; in self-driving cars and navigation; in social media. Society and policy makers are rapidly trying to catch up, to adapt, to create norms and policies to guide these new areas. We see this scramble in contemporary international tax law, competition/antitrust policy, innovation policy, and national security motivated controls on trade and investment. To understand and advise contemporary policymaking, one needs to develop expertise in specific policy areas (such as antitrust/competition policy or international security) as well as in the relevant technical aspects of AI. It is also important to build a community jointly working across these policy areas, as these phenomena interact, and are often driven by similar technical developments, involve similar tradeoffs, and benefit from similar insights. For example, AI-relevant antitrust/competition policy is shaping and being shaped by great power rivalry, and these fields benefit from understanding AI’s character and trajectory. Long-term Risks and Opportunities Longtermists are especially concerned with the long-term risks and opportunities from AI, and particularly existential risks, which are risks of extinction or other destruction of humanity’s long-term potential (Ord 2020, 37). Superintelligence Perspective Many longtermists come to the field of AI Governance from what we can call the superintelligence perspective, which typically focuses on the challenge of having an AI agent with cognitive capabilities vastly superior to those of humans. Given how important intelligence is---to the solving of our global problems, to the production and allocation of wealth, and to military power---this perspective makes clear that superintelligent AI would pose profound opportunities and risks. In particular, superintelligent AI could pose a threat to human control and existence that dwarfs our other natural and anthropogenic risks (for a weighing of these risks, see Toby Ord’s The Precipice).[3] Accordingly, this perspective highlights the imperative that AI be safe and aligned with human preferences/values. The field of AI Safety is in part m...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: What gives me hope, published by Michelle_Hutchinson on the effective altruism forum. Fast forward to a few months ago when I listened an interview with Peter Singer on the Lex Fridman podcast and he mentioned 80,000 Hours. Over many evenings with my new born son asleep on me on the sofa I read your key ideas pages and problem profiles and started to think about how I can change my career to maximise its long term impact. Sometimes being an effective altruist feels really tough. There is so much suffering in the world, and no guarantee that people in the future will even get to live. There’s a lot of work to be done to try to counteract these things, and the work is usually not easy - whether you’re working a high pressure job to earn money to donate, needing to make stressful judgement calls about the ways to solve big problems or applying for roles to try to figure out how you can best contribute. One of the things that I find most heartening when effective altruism feels rough is reading through the applications we get to speak with our team. Reading through so many people’s plans for their careers and journeys to effective altruism is by turns humbling, heartwarming and inspiring. It reminds me how many of us are working together on improving the world, and how dedicated and caring my fellow travellers are. It makes attacking the world’s problems feel a bit more manageable. I wanted to try to share some of the feeling I get from reading these stories. I’m not intending them as endorsements of specific actions. In particular, I think something EA does well is avoid glorifying sacrifice and making clear that the less effort you need to expend to help someone, the better. But people being willing to do what’s needed even at great personal cost does mean we’re more likely to be able to pull off difficult things. I also find it deeply moving. There are so many different ways in which people’s stories are touching. Some people have had a really tough time themselves growing up, and yet somehow got through that with a determination to use their time to help others. Others have a plethora of options that would net them riches and prestige, yet decide to spend their labour figuring out how to help others as much as possible instead. I want to share a few stories of people I've come across (with details removed for anonymity). I hope they give you a taste of the awe and feeling of connection to others I feel when I read about them. The medical student nearing the end of their training who plans on radically switching career track. Having gotten into EA, they're willing to take a role in a totally different field despite all the hard work they put into their degree and how unintelligible their choice will be to their family. The introvert willing to spend their free time fundraising door to door despite how horrible it is asking people for money The vegan who donates 10% and gave a stranger a kidney, yet (crazily!) summarises their contributions so far as if they were no big deal and just what anyone might do The student who chose their university based on being able to finish their degree as fast as possible in order to be out in the world helping others The professor, many years into their career, willing to switch research focus entirely or leave academia because they read The Precipice and realised their skills are well suited to increasing humanity’s resilience The early retiree who deliberately saved enough to retire by 40, but is willing to work a difficult corporate job in order to make money to give away The winner of one of the toughest international maths competitions with an interest in a pure maths academic career, but who is instead working on the applied problems they think will most help others The student already donating a significant proportion of the mon...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Taboo "Outside View", published by kokotajlod on the effective altruism forum. No one has ever seen an AGI takeoff, so any attempt to understand it must use these outside view considerations. [Redacted for privacy] What? That’s exactly backwards. If we had lots of experience with past AGI takeoffs, using the outside view to predict the next one would be a lot more effective. My reaction Two years ago I wrote a deep-dive summary of Superforecasting and the associated scientific literature. I learned about the “Outside view” / “Inside view” distinction, and the evidence supporting it. At the time I was excited about the concept and wrote: “...I think we should do our best to imitate these best-practices, and that means using the outside view far more than we would naturally be inclined.” Now that I have more experience, I think the concept is doing more harm than good in our community. The term is easily abused and its meaning has expanded too much. I recommend we permanently taboo “Outside view,” i.e. stop using the word and use more precise, less confused concepts instead. This post explains why. What does “Outside view” mean now? Over the past two years I’ve noticed people (including myself!) do lots of different things in the name of the Outside View. I’ve compiled the following lists based on fuzzy memory of hundreds of conversations with dozens of people: Big List O’ Things People Describe As Outside View: Reference class forecasting, the practice of computing a probability of an event by looking at the frequency with which similar events occurred in similar situations. Also called comparison class forecasting. [EDIT: Eliezer rightly points out that sometimes reasoning by analogy is undeservedly called reference class forecasting; reference classes are supposed to be held to a much higher standard, in which your sample size is larger and the analogy is especially tight.] Trend extrapolation, e.g. “AGI implies insane GWP growth; let’s forecast AGI timelines by extrapolating GWP trends.” Foxy aggregation, the practice of using multiple methods to compute an answer and then making your final forecast be some intuition-weighted average of those methods. Bias correction, in others or in oneself, e.g. “There’s a selection effect in our community for people who think AI is a big deal, and one reason to think AI is a big deal is if you have short timelines, so I’m going to bump my timelines estimate longer to correct for this.” Deference to wisdom of the many, e.g. expert surveys, or appeals to the efficient market hypothesis, or to conventional wisdom in some fairly large group of people such as the EA community or Western academia. Anti-weirdness heuristic, e.g. “How sure are we about all this AI stuff? It’s pretty wild, it sounds like science fiction or doomsday cult material.” Priors, e.g. “This sort of thing seems like a really rare, surprising sort of event; I guess I’m saying the prior is low / the outside view says it’s unlikely.” Note that I’ve heard this said even in cases where the prior is not generated by a reference class, but rather from raw intuition. Ajeya’s timelines model (transcript of interview, link to model) . and probably many more I don’t remember Big List O’ Things People Describe As Inside View: Having a gears-level model, e.g. “Language data contains enough structure to learn human-level general intelligence with the right architecture and training setup; GPT-3 + recent theory papers indicate that this should be possible with X more data and compute.” Having any model at all, e.g. “I model AI progress as a function of compute and clock time, with the probability distribution over how much compute is needed shifting 2 OOMs lower each decade.” Deference to wisdom of the few, e.g. “the people I trust most on this matter seem to think.” Intuition-...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: The psychology of population ethics, published by Lucius_Caviola on the effective altruism forum. In a new paper, David Althaus, Andreas Mogensen, Geoffrey Goodwin, and I, investigate people's population ethical intuitions. Across nine experiments (N = 5,776), we studied how lay people judge the moral value of hypothetical human populations that differ in their size and in the quality of the individual lives that comprise them. Our investigation aimed to answer three questions: Do people weigh happiness and suffering symmetrically? Do people focus more on the average or total welfare of a given population? Do people account only for currently existing lives, or also lives that could yet exist? Here is a very brief summary of the key findings (more details can be found in the linked paper): 1. People, on average, weigh suffering more than happiness Participants, on average, believed that more happy than unhappy people were needed in order for the whole population to be net positive (Studies 1a-c). Judgments about the acceptable proportion of happy and unhappy people in a population matched judgments about the acceptable proportion of happiness and unhappiness within a single individual’s lifetime. The precise trade ratio between happiness and suffering depended on the intensity levels of happiness and suffering, such that a greater proportion of happiness was required as intensity levels increased (Study 1b). Study 1c clarified that, on average, participants continued to believe that more happiness than suffering was required even when the happiness and suffering units were exactly equally intense. This suggests that people generally weigh suffering more than happiness in their moral assessments, above and beyond perceiving suffering to be more intense than happiness. However, our studies also made clear that there are individual differences and that a substantial proportion of participants weighed happiness and suffering equally strongly, in line with classical utilitarianism. In Study 1c, we asked participants what proportion of people in a population (or what proportion of all the moments in an individual life) needed to be happy vs unhappy for the whole population (or life) to be net positive. Horizontal lines represent mean value. 2. People have both an averagist and a totalist preference Participants had a preference both for populations with greater total and greater average welfare (Study 3a-d). In Study 3a, we found that participants preferred populations with better total levels (i.e., higher levels in the case of happiness and lower levels in the case of suffering) when the average levels were held constant. In Study 3b, we found that participants preferred populations with better average levels when the total levels were held constant. In Study 3c, we found that most participants’ preferences lay in between the recommendations of these two principles when they conflict, suggesting that participants applied both preferences simultaneously in such cases. Further, their focus on average welfare even led them (remarkably) to judge it preferable to add new suffering people to an already miserable world, as long as this increased average welfare (Study 3d). But, when prompted to reflect, participants’ preference for the population with the better total welfare became stronger. In Study 3d, we asked participants which out of two populations they consider better: a population consisting of 1,000 very happy (unhappy) people or a population of 2,000 people consisting of 1,000 very happy (unhappy) people and an additional 1,000 people who are also happy (unhappy) but to a weaker extent than the first 1,000—either on level ±10, ±50, ±90. Depending on the condition, participants were prompted to think reflectively or to rely on their intuition. The responses in the unh...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Information security careers for GCR reduction, published by ClaireZabel, lukeprog on the effective altruism forum. Update 2019-12-14: There is now a Facebook group for discussion of infosec careers in EA (including for GCR reduction); join here This post was written by Claire Zabel and Luke Muehlhauser, based on their experiences as Open Philanthropy Project staff members working on global catastrophic risk reduction, though this post isn't intended to represent an official position of Open Phil. Summary In this post, we summarize why we think information security (preventing unauthorized users, such as hackers, from accessing or altering information) may be an impactful career path for some people who are focused on reducing global catastrophic risks (GCRs). If you'd like to hear about job opportunities in information security and global catastrophic risk, you can fill out this form created by 80,000 Hours, and their staff will get in touch with you if something might be a good fit. In brief, we think: Information security (infosec) expertise may be crucial for addressing catastrophic risks related to AI and biosecurity. More generally, security expertise may be useful for those attempting to reduce GCRs, because such work sometimes involves engaging with information that could do harm if misused. We have thus far found it difficult to hire security professionals who aren't motivated by GCR reduction to work with us and some of our GCR-focused grantees, due to the high demand for security experts and the unconventional nature of our situation and that of some of our grantees. More broadly, we expect there to continue to be a deficit of GCR-focused security expertise in AI and biosecurity, and that this deficit will result in several GCR-specific challenges and concerns being under-addressed by default. It’s more likely than not that within 10 years, there will be dozens of GCR-focused roles in information security, and some organizations are already looking for candidates that fit their needs (and would hire them now, if they found them). It’s plausible that some people focused on high-impact careers (as many effective altruists are) would be well-suited to helping meet this need by gaining infosec expertise and experience and then moving into work at the relevant organizations. If people who try this don’t get a direct work job but gain the relevant skills, they could still end up in a highly lucrative career in which their skillset would be in high demand. We explain below. Risks from Advanced AI As AI capabilities improve, leading AI projects will likely be targets of increasingly sophisticated and well-resourced cyberattacks (by states and other actors) which seek to steal AI-related intellectual property. If these attacks are not mitigated by teams of highly skilled and experienced security professionals, then such attacks seem likely to (1) increase the odds that TAI / AGI is first deployed by malicious or incautious actors (who acquired world-leading AI technology by theft), and also seem likely to (2) exacerbate and destabilize potential AI technology races which could lead to dangerously hasty deployment of TAI / AGI, leaving insufficient time for alignment research, robustness checks, etc.[1] As far as we know, this is a common view among those who have studied questions of TAI / AGI alignment and strategy for several years, though there remains much disagreement about the details, and about the relative magnitudes of different risks. Given this, we think a member of such a security team could do a lot of good, if they are better than their replacement and/or they understand the full nature of the AI safety and security challenge better than their replacement (e.g. because they have spent many years thinking about AI from a GCR-reduction angle). Furthermo...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: COVID: How did we do? How can we know?, published by Ghost_of_Li_Wenliang on the effective altruism forum. Obviously it was a triumph: the fastest vaccine development, approval, and rollout in history (by a factor of 5). We're up to 2.5bn doses in arms, out of say 12bn. And we got several good ones! Huzzah! Obviously it was a catastrophe: through dumb inaction and a comedy of errors, we squandered the chance to suppress the virus. 4 million people are confirmed to have died of (or with) COVID - and given unbelievable underreporting that might be actually 12 million - and given Delta's momentum 20 million by the end is not unlikely. This is despite this virus being easy mode: unlike 1918, very few of the deaths were among the young frontline workers keeping the healthcare and delivery systems working; unlike SARS 1, post-viral disability is relatively rare. This is just the present pandemic and doesn't count future deaths from letting the thing become a permanent fixture. How did we do? How can we even answer that question? When I talk about whether a given country's response to COVID was a success or a failure, smart friends reply "governments had to balance the tradeoffs, so what looks like failure is really just compromise between multiple objectives (like economic activity)", "it's easy to say the optimal response in hindsight", that "it's difficult to compare different countries because of the different distances from China, wealth, state capacity". For instance, they think the UK did ok. They can think this because they choose to compare to the average actual response (never mind that the UK is top 20 in deaths per capita). But what would the best possible response look like? What did our institutions stop us from getting? Vax Any self-respecting COVID rant must foreground vaccination. It is the solution, where other policies just buy time, or else consume old or disabled people. We underinvested, and prevented market investment. The EU paid $14 per Pfizer dose. What was it really worth? The current black market price for Pfizer is about $500. But that's a gross underestimate of the shadow price, since you get almost zero quality assurance or liability from darknet dealers. (You might still get the travel passport, depending on how weak your country's infosec is.) One proper estimate of the per-vaccine social benefit is $6000. So we should have spent trillions in massive pre-purchase, on every credible vaccine. (The much-praised Operation Warp Speed and its equivalents elsewhere only pre-purchased about 2bn out of the necessary 12-14bn, and did so shockingly late, in August 2020.) $3000 x 14 bn doses pays for a lot of overtime on microlipid machine assembly (which was the bottleneck on mRNA vaccine supply last year). (That's assuming that you continue to ban vaccine markets, believing, as you apparently do, that fairness is worth the early death of millions. Another way to fund supply expansion for the global south is to just not get in our own way.) The rich world defected, duh 16% of the world bought 70% of the vaccines. What force on earth could stop them? None, so we needed the massive supply increases, which were effectively banned. This was not even good selfishness: it guaranteed the emergence of new strains in the global south. This is the real evil of the EU procurement. They want to harm their own by delaying 4 weeks, to look strong? Well, that's one thing. But had they done a pre-purchase in March 2020, then global supply could have scaled up, so that the inevitable snatch away from the global south was completely balanced out by expanded supply What did we do? Overall, about 2bn doses ordered by August 2020, i.e. 5 times too little, 5 months too late. The strange death of human challenge trials Probably the biggest mistake was not intentionally infec...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Open Philanthropy is seeking proposals for outreach projects, published by abergal, ClaireZabel on the effective altruism forum. Open Philanthropy is seeking proposals from applicants interested in growing the community of people motivated to improve the long-term future via the kinds of projects described below.[1] Apply to start a new project here; express interest in helping with a project here. We hope to draw highly capable people to this work by supporting ambitious, scalable outreach projects that run for many years. We think a world where effective altruism, longtermism, and related ideas are routine parts of conversation in intellectual spaces is within reach, and we’re excited to support projects that work towards that world. In this post, we describe the kinds of projects we’re interested in funding, explain why we think they could be very impactful, and give some more detail on our application process. Proposals we are interested in Programs that engage with promising young people We are seeking proposals for programs that engage with young people who seem particularly promising in terms of their ability to improve the long-term future (and may have interest in doing so). Here, by “particularly promising”, we mean young people who seem well-suited to building aptitudes that have high potential for improving the long-term future. Examples from the linked post include aptitudes for conducting research, advancing into top institutional roles, founding or supporting organizations, communicating ideas, and building communities of people with similar interests and goals, among others. Downstream, we hope these individuals will be fits for what we believe to be priority paths for improving the long-term future, such as AI alignment research, technical and policy work reducing risks from advances in synthetic biology, career paths involving senior roles in the national security community, and roles writing and speaking about relevant ideas, among others. We’re interested in supporting a wide range of possible programs, including summer or winter camps, scholarship or fellowship programs, seminars, conferences, workshops, and retreats. We think programs with the following characteristics are most likely to be highly impactful: They engage people ages 15 - 25 who seem particularly promising in terms of their ability to improve the long-term future, for example people who are unusually gifted in STEM, economics, philosophy, writing, speaking, or debate. They cover effective altruism (EA), rationality, longtermism, global catastrophic risks, or related topics. They involve having interested young people interact with people currently working to improve the long-term future. Examples of such programs that Open Philanthropy has supported include SPARC, ESPR, the SERI and FHI summer research programs, and the recent EA Debate Championship. However, we think there is room for many more such programs. We especially encourage program ideas which: Have the potential to engage a large number of people (hundreds to tens of thousands) per year, though we think starting out with smaller groups can be a good way to gain experience with this kind of work. Engage with groups of people who don’t have many ways to enter relevant intellectual communities (e.g. they are not in areas with high concentrations of people motivated to improve the long-term future). Include staff who have experience working with members of the groups they hope to engage with—in particular, experience talking with young people about new ideas while being respectful of their intellectual autonomy and encouraging independent intellectual development. We encourage people to have a low bar for submitting proposals to our program, but note that we view this as a sensitive area: we think programs like these have t...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: EffectiveAltruismData.com: A Website for Aggregating and Visualising EA Data, published by Hamish Huggard on the effective altruism forum. There’s lots of cool data floating around in EA: grant databases, survey results, growth metrics, etc. I’m a data scientist and enjoy data visualisation, so thought it would be a fun project to build a website which aggregates EA data into interactive plots. The website is now live at EffectiveAltruismData.com. Source code is available on Github. This project is still a work in progress: the data is pretty out of date and I’ve got lots of future work planned. But it’s far enough along that I’d like some public feedback. The website is responsive and should look good on any desktop or tablet screen. If you’re viewing on a phone it will probably look ok, but you may need to alternate between portrait and landscape. Here are a few screenshots: Implementation Details The website is mostly coded in Python. The main libraries I used were: Pandas for data handling. Plotly for creating the interactive plots. Dash for the web framework. I also wrote a bunch of vanilla CSS for the frontend styling. The web server is currently deployed with Heroku, which costs $7/month. I have vague ambitions to re-implement the frontend with D3.js or Chart.js. This should cut down the loading time and give me more control over how the visualisations work. Design Philosophy I aimed to follow the data visualisation principles laid out in Information Dashboard Design and Storytelling with Data. These include: Minimise the “ink-to-data” (or “pixel-to-data”) ratio to avoid distracting clutter. Encoding data in length or distance is much higher fidelity than area or angle. Avoid pie charts, stacked area plots, radar charts, violin plots. Stick to bar charts, scatter plots, and line graphs as much as possible. Don’t make the reader rotate their head. Use horizontal bar charts rather than vertical ones. Minimise the total length the eye has to travel to take in all the data. Avoid legends. On line graphs, put the labels directly on the ends of the lines. Why I Did This I said earlier that this project was motivated by my fancy for data visualisation. But I do think there’s a lot of scope for valuable data visualisation and data wrangling work within Effective Altruism. For example, I’ve found it difficult to get a sense of the scale of donations within EA. Are total donations basically Open Philanthropy plus a rounding error? Or do donations from all the little guys like me actually make a difference in the big picture? This isn’t just an interesting question in itself: it also informs my life decisions. If the total donations of people in my reference class is enough to make a noticeable change to AMF funding, then I’m more likely to steadily earn-to-give on a moderately affluent career path. If my reference class is totally overwhelmed by a handful of mega-donors, then I’m more likely to drop everything and spend a year figuring out if I can contribute to AI safety. This was some of the motivation behind the first panel of EffectiveAltruismData.com. Ultimately, I’d like to have a plot which puts all the major stocks and flows of EA money on a common scale and puts my personal earning-to-give into perspective. Another example: I have a vague sense that EAs are getting more diverse over time. Is this true? Currently, answering this question would require going through all the EA survey reports, reading numbers from images of plots, and typing them into a spreadsheet. It would be nice if all the data was easily accessible from some central repository and ready for analysis. Data visualisation is a great tool for getting lots of people quickly up to speed on quantitative facts. Gapminder and Our World in Data do this to great effect. If we want EA to be an efficient ...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: What we learned from a year incubating longtermist entrepreneurship, published by Rebecca Kagan, Jade Leung, imben on the effective altruism forum. This post is a retrospective on the Longtermist Entrepreneurship (LE) Project, which ran for a year and explored ways to incubate new longtermist entrepreneurship. If you’re in a hurry, we recommend reading key lessons learned, what we’d be excited about, and what it takes to work in this space. Thanks to Markus Anderljung, Aaron Gertler, Sam Hilton, Josh Jacobson and Jonas Vollmer for reviewing, as well as many others who reviewed an earlier draft of the document. All opinions and mistakes are our own. Intro The Longtermist Entrepreneurship (LE) Project ran from April 2020 through May 2021, with the aim of testing ways to support the creation of new longtermist nonprofits, companies, and projects. During that time, we did market sizing, user interviews, and ran three pilot programs on how to support longtermism entrepreneurship, including a fellowship. The LE Project was run by Jade Leung, Ben Clifford, and Rebecca Kagan, and funded by Open Philanthropy. The project shut down after a year because of staffing reasons, but also because of some uncertainty about the project’s direction and value. We never had a public internet presence, so this may be the first time that many people on the EA Forum are hearing about our work. This post describes the history of the project, our pilot programs, and our lessons learned. It also describes what we’d support seeing in the future, and what our concerns are about this space, and ways to learn more. Overall, we think that supporting longtermist entrepreneurship is important and promising work, and we expect people will continue to work in this space in the coming years. However, we aren't publishing this post because we want to encourage lots of people to start longtermist incubators. We think doing longtermist startup incubation is incredibly difficult, and requires specific backgrounds. We wanted to share what we’ve transparently and widely to help people learn from our successes and mistakes, and to think carefully about what future efforts should be made in this direction. If you’re considering starting an LE incubator[1], we’d love to hear about it so we can offer advice and coordination with others interested in working in this space. Please fill out this google form if you’re interested in founding programs in LE incubation. Key lessons learned: Overall, it’s likely that one or multiple organizations should be doing LE incubation. We need more longtermist organizations, and the current ecosystem doesn’t seem poised to fix this problem. Our fellowship and matchmaking pilots were promising, suggesting that there’s more we can do to start new organizations. There’s interest in LE programs, but a limited talent pool that has strong backgrounds in both longtermism and entrepreneurship. Talent is likely to be a significant bottleneck. Hundreds of people expressed interest in doing LE, but a very small number of these (1-3 dozen) had backgrounds in both longtermism and entrepreneurship. There were few people that we thought could pull off very ambitious projects. The idea pool is more limited and less developed than we expected. There are existing lists of ideas, but almost no ideas are fleshed out and have broad support. There are no clear “highest priority ideas'' that are obviously good to pursue and have been carefully vetted. Instead, most people we spoke to thought that the most promising ideas depended on the available talent. We found almost no longtermist ideas for traditional startup-minded people to pursue. Funders are worried about downside risks of some new projects, but often more open to funding short-runway projects with frequent checkpoints. Funders do want to see m...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Patient vs urgent longtermism has little direct bearing on giving now vs later, published by Owen_Cotton-Barratt on the effective altruism forum. This post is a response to having heard multiple people express something like "I'm persuaded by the case for patient longtermism, so I want to save money rather than give now", or otherwise implicitly assuming that patient longtermism is obviously more in favour of saving money than urgent longtermism (e.g. Ben Todd says "Even the people who are most into patient longtermism still think we should spend some on object-level things today. It’s just maybe they would only give half a percent of the portfolio as opposed to 4%." in his podcast episode on varieties of longtermism). This view is understandable to me, especially given: Trammell's paper arguing that "patient philanthropists" should invest rather than spend down their capital (note that I tentatively agree with this in the context of global poverty, to which he applies the framework in the paper); The commonsense meanings of "urgent" and "patient", and of "spend" and "invest". Nonetheless, I think it is mistaken and there is no direct implication that "patient longtermists" should be less willing to spend money now than "urgent longtermists". Rather I think it's an open question which will depend on a lot of messy empirics (about giving opportunities) which position should be more in favour of saving money now. My current guess is to recommend spending rather than saving money at current margins to both patient and urgent longtermists. Neither recommendation feels robust; however, I'm actually a little more pro-saving for "urgent" longtermists than for "patient" ones. Note that I do think that considering which timescales we want to exert influence over is an extremely fruitful lens (although I'd usually think of a natural timescale as attaching to an activity rather than an overall view), and it has a great deal of relevance for deciding what to fund and hence indirect bearing on whether to give now or later. [With apologies for a lack of careful scholarship: I suspect these points are largely written up elsewhere, and appreciated in large part already by Trammell and Todd.] So what's going on? Why doesn't the argument for patient philanthropy apply straightforwardly in the longtermist case? The argument is in favour of investing (so that you have more resources available later), rather than spending (so that you have less resources available). You might think that giving money away should naturally be considered as spending; and considered from the perspective of an individual donor it probably is. But from the perspective of the longtermist community, most "spending" of money now is actually investment. It pays for research or career development or book-writing or websites or community-building (etc.); and the hope is that resources invested in these things now will return more resources meaningfully aligned with important parts of the longtermist worldview down the line (whether more money, or more people willing to act on the principles, or more broad sympathy to and influence for the ideas). I think the best of these activities are almost certainly good investments; for instance I think that longtermism (broadly understood) has vastly outperformed the stock market over the last twenty years in terms of the resources it has amassed. I then think that individual decisions about giving now vs later should largely be driven by whether the best identifiable marginal opportunities are still good investments. There's a lot of nuance that can (and should!) modulate that statement, for instance: If an individual is still increasing their understanding of what good opportunities look like fast enough, they could be better waiting But deferring to more-informed others or ...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Shallow evaluations of longtermist organizations, published by NunoSempere on the effective altruism forum. Introduction This document reviews a number of organizations in the longtermist ecosystem, and poses and answers a number of questions which would have to be answered to arrive at a numerical estimate of their impact. My aim was to see how useful a "quantified evaluation" format in the longtermist domain would be. In the end, I did not arrive at GiveWell-style numerical estimates of the impact of each organization, which could be used to compare and rank them. To do this, one would have to resolve and quantify the remaining uncertainties for each organization, and then convert each organization's impact to a common unit [1, 2]. In the absence of fully quantified evaluations, messier kinds of reasoning have to be used and are being used to prioritize among those organizations, and among other opportunities in the longtermist space. But the hope is that reasoning and reflection built on top of quantified predictions might prove more reliable than reasoning and reflection alone. In practice, the evaluations below are at a fairly early stage, and I would caution against taking them too seriously and using them in real-world decisions as they are. By my own estimation, of two similar past posts, 2018-2019 Long Term Future Fund Grantees: How did they do? had 2 significant mistakes, as well as half a dozen minor mistakes, out of 24 grants, whereas Relative Impact of the First 10 EA Forum Prize Winners had significant errors in at least 3 of the 10 posts it evaluated. To make the scope of this post more manageable, I mostly did not evaluate organizations included in Lark's yearly AI Alignment Literature Review and Charity Comparison posts, nor meta-organizations [3]. Evaluated organizations Alliance to Feed the Earth in Disasters Epistemic status for this section: Fairly sure about the points related to ALLFED's model of its own impact. Unsure about the points related to the quality of ALLFED's work, given that I'm relying on impressions from others. Questions With respect to the principled case for an organization to be working on the area: What is the probability of a (non-AI) catastrophe which makes ALLFED's work relevant (i.e., which kills 10% or more of humanity, but not all of humanity) over the next 50 to 100 years? How much does the value of the future diminish in such a catastrophe? How does this compare to work in other areas? With respect to the execution details: Is ALLFED making progress in its "feeding everyone no matter what" agenda? Is that progress on the lobbying front, or on the research front? Is ALLFED producing high-quality research? On a Likert scale of 1-5, how strong are their papers and public writing? Is ALLFED cost-effective? Given that ALLFED has a large team, is it a positive influence on its team members? How would we expect employees and volunteers to rate their experience with the organization? Tentative answers Execution details about ALLFED in particular Starting from a quick review as a non-expert, I was inclined to defer to ALLFED's own expertise in this area, i.e., to trust their own evaluation that their own work was of high value, at least compared to other possible directions which could be pursued within their cause area. Per their ALLFED 2020 Highlights, they are researching ways to quickly scale alternative food production, at the lowest cost, in the case of large catastrophes, i.e., foods which could be produced for several years if there was a nuclear war which blotted out the sun. However, when talking with colleagues and collaborators, some had the impression that ALLFED was not particularly competent, nor its work high quality. I would thus be curious to see an assessment by independent experts about how valuable their w...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Thoughts on doing good through non-standard EA career pathways, published by Buck on the effective altruism forum. (Thanks to Beth Barnes, Asya Bergal, and especially Joshua Teperowski-Monrad for comments. A lot of the ideas in this post originated in friends of mine who didn’t want to write them up; they deserve most of the credit for good ideas, I just organized the ideas and wrote it up.) 80000 Hours writes (under the heading “Apply an unusual strength to a needed niche”): If there’s any option in which you might excel, it’s usually worth considering, both for the potential impact and especially for the career capital; excellence in one field can often give you opportunities in others. This is even more likely if you’re part of a community that’s coordinating or working in a small field. Communities tend to need a small number of experts covering each of their main bases. For instance, anthropology isn’t the field we’d most often recommend someone learn, but it turned out that during the Ebola crisis, anthropologists played a vital role, since they understood how burial practices might affect transmission and how to change them. So, the biorisk community needs at least a few people with anthropology expertise. I think that there are many people who do lots of good through pursuing a career that they were a particularly good fit for, rather than by trying to fit themselves into a top-rated EA career. But I also think it’s pretty easy to pursue such paths in a way that isn’t very useful. In this post I’m going to try to build on this advice to describe some features of how I think these nonstandard careers should be pursued in order to maximize impact. I’m going to misleadingly use the term “nonstandard EA career” to mean “a career that isn’t one of 80K’s top suggestions”. (I’m going to abbreviate 80,000 Hours as 80K.) I’m not very confident in my advice here, but even if the advice is bad, hopefully the concepts and examples are thought provoking. Doing unusual amounts of good requires unusual actions If you want to do an unusual amount of good, you probably need to take some unusual actions. (This isn’t definitionally true, but I think most EAs should agree on it–at the very least, most EAs think you can do much more good than most people do by donating an affordable but unusual share of your income to GiveWell recommended nonprofits.) One approach to this is working in a highly leveraged job on a highly leveraged problem. This is the approach suggested by the 80K career guide. They came up with a list of career options, like doing AI safety technical research, or working at the CDC on biosecurity, or working at various EA orgs, which they think are particularly impactful and which they think have room for a bunch of EAs. Another classic choice is donating to unusually effective nonprofits, which is a plan where you didn’t have to choose a particularly specific career path (though taking a specific career path is extremely helpful), the unusual effectiveness comes from the choice to donate to an unusually effective place. The nice thing about taking one of those paths is that you might not need to do anything else unusual in order to have a lot of impact. There are also some reasons to consider doing something that isn’t EtG or an 80K recommendation. For example: There might be lower hanging fruit in that field, because it doesn’t have as many EAs in it. Comparative advantage: The thing that you’re best at probably isn’t a top recommended EA career, just on priors. You can’t get a job in one of the top recommended EA careers, maybe because you’re not in 80K’s target audience of graduates aged 20-35 who have lots of career options. I care about people in this group, but I’m not going to address this situation much in the rest of this piece, because the relevant con...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: The most successful EA podcast of all time: Sam Harris and Will MacAskill (2020), published by Aaron Gertler on the effective altruism forum. Context My job is about helping people get involved in effective altruism, so I pay attention to how this happens. I'm not sure I've ever seen any piece of content not named "Doing Good Better" get as much positive as Sam Harris's two podcast episodes with Will MacAskill. After the first episode, Sam was deeply affected, and pledged to donate $3500/month in podcast proceeds to the Against Malaria Foundation. After the second episode, Sam joined Giving What We Can and pledged 10% of profits from his Waking Up app (well over $3500/month) to effective charities. Impact Both episodes seem to have caused a spike in GWWC memberships, and the second may have boosted EA engagement more generally. Some notes on that: GWWC estimates that over 600 people have taken the pledge in part because of the episodes (with another ~600 signing up for Try Giving). To break this down: ~800 people who finished the sign-up survey mentioned a podcast as one way they found GWWC (the average person chose 1.8 sources). Of the 123 people who said which podcast it was, 107 said Sam Harris (87%). Extrapolating a similar rate to the ~700 who didn't say which podcast gives another ~600 referrals on top of the original 107. The "podcast" option was only added to the form in October 2020, before the second episode but after the first; another ~500 people who filled it out before then mentioned Sam somewhere. I'd guess that most of these were coming from the first episode with Will, though he may have mentioned his giving in other episodes, and GWWC by extension. An extremely engaged community builder told me in February 2021: "I feel like most new EAs I've met in the last year came in through Sam Harris." My subjective impression in the weeks after the second episode came out was that most of the ambient "positive EA chatter" I heard on Twitter (people tweeting out random EA endorsements who normally talked about other things) included mentions of the podcast. Why was this so impactful? Some factors I think were important: Sam set an example. One of the most persuasive ways to promote something is to do it yourself. One of Sam's explicit goals on the podcast is to get listeners to make ethical decisions, and I'd imagine that many listeners seek him out for ethical advice. This isn't as much the case for podcasters like Tim Ferriss or Joe Rogan, or other sources of publicity (TED, op-eds, etc.) From the transcript below: "The question that underlies all of this, really, is: How can we live a morally beautiful life? That is more and more what I care about, and what the young Will MacAskill is certainly doing." Sam made a rare endorsement. Sam took several minutes to explain why he thinks giving is important, and gives GWWC a strong recommendation. This is a rare thing for him to do; most of his guests aren't selling anything (save maybe a book), and he doesn't advertise on his podcast. Comparatively, Tim Ferriss (another major podcaster who had Will as a guest) has ~5 minutes of long-form advertising on every episode, and generally recommends lots of things every time a guest comes on. On the writeup of Will's episode, GWWC was the 23rd item on a bullet list of "selected links". Tim's podcast referred 8 people to GWWC. This is actually a solid number, given that the "where you heard about us" question wasn't added until more than a year after that episode came out. But I think the true impact of the episode was still much lower than that of the Sam episodes, despite Tim's larger audience. The conversation is really good. I listened to the second episode soon after it came out, before I knew anything about its impact, and was almost immediately struck by how good Wi...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: A do-gooder's safari, published by Owen_Cotton-Barratt on the effective altruism forum. Doing good things is hard. We’re gonna look at some deep tensions that attach to trying to do really good stuff. To keep it relatable(?!), I’ve included badly-drawn animals. The mole pursues goals which are within comprehension and reach. At best the mole knows the immediate challenges extremely well and does a great job at dealing with them. At worst, the mole is digging in a random direction. The giraffe looks into the distance, focusing on the big picture, and perhaps on challenges that will come up later but aren’t even apparent today. At best the giraffe identifies crucial directions to steer in. At worst, the giraffe doesn’t look where they’re going and trips over, or has ideas which are dumb because they don’t engage with details. Moles have much more direct feedback loops than giraffes, so it’s harder to be a good giraffe than a good mole. When there’s a well-specified achievable goal, you can set a mole at it. Consequently many industries are structured with lots of mole-shaped roles. Idealists are often giraffes. The beaver is industriously focused on the task at hand. The beaver rejects distractions and gets s done. At best, they are extremely productive. At worst, they miss big improvements in how they could go about things, or execute on a subtly wrong version of the task that misses most of the value. The elephant is always asking how things are going, and whether the task is the right one. At their best, the elephant reorients things in better directions or finds big systemic improvements. At their worst, the elephant fails to get anything done because they can’t settle on what they’re even trying to do. The mole and beaver are cousins, as are the giraffe and elephant. But you certainly get mole-elephants (applying lots of meta but only to local goals), or giraffe-beavers (just focused on the object-level of the big-picture). The owl is a perfectionist. They have high standards for things, and want everything to meet those. At their best, they make things excellent, and perfectly crafted. If you want to produce the best X in the world, you probably need at least one owl involved. At their worst, they stall on projects because there’s something not quite right that they can’t see how to fix, and it’s unsatisfying. The hare likes to ship things. They feel urgency all the time, and hate letting the perfect be the enemy of the good. At their best, they just make things happen! The hare can also be a good learner because they charge at things — sometimes they bounce off and get things wrong, but they get loads of experience so loads of chances to learn. At their worst, the hare produces loads of stuff but it’s all junk. The dog is very socially governed / approval-seeking. They are excited to do things that people (particularly the cool people) will think are cool. At their best, they provide a social fabric which makes coordination simple (if someone else wants a thing done, they’re happy to do it without slowing everything down by making sure they understand the deep reasons why it’s desired). They also make sure gaps are filled — they jump onto projects and help out with things, or pick up balls that everyone agrees are important. At their worst, they chase after hype and status without providing any meaningful checks on whether the ideas they’re following are actually good. The cat doesn’t give tuppence for what anyone else thinks. They’re just into working out what seems good and going for it. All new ideas involve at least a bit of cat. At their best, cats head into the wilderness and bring back something amazing. At their very worst they do something stupid and damaging that proper socialisation would have stopped. The more normal cat failure modes are to wander t...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: SHOW: A framework for shaping your talent for direct work, published by RyanCarey on the effective altruism forum. By Ryan Carey, cowritten with Tegan Mccaslin (this post represents our own opinions, and not those of our current or former employers) TLDR: If your career as an EA has stalled, you’ll eventually break through if you do one (or more) of four things: gaining skills outside the EA community, assisting the work of more senior EAs, finding valuable projects that EAs aren’t willing to do, or finding projects that no one is doing yet. Let’s say you’ve applied to, and been rejected, from several jobs in high-impact areas over the past year (a situation that is becoming more common as the size of the movement grows). At first you thought you were just unlucky, but it looks increasingly likely that your current skillset just isn’t competitive for the positions you’re applying to. So what’s your next move? I propose that there are four good paths open to you now: Get Skilled: Use non-EA opportunities to level up on those abilities EA needs most. Get Humble: Amplify others’ impact from a more junior role. Get Outside: Find things to do in EA’s blind spots, or outside EA organizations. Get Weird: Find things no one is doing. I’ve used or strongly considered all of these strategies myself, so before I outline each in more depth I’ll discuss the role they’ve played in my career. (And I encourage readers who resonate with SHOW to do the same in the comments!) Currently I do AI safety research for FHI. But when I first came to the EA community 5 years ago, my training was as a doctor, not as a researcher. So when I had my first professional EA experience, as an intern for 80,000 Hours, my work was far from extraordinary. As the situation stood, I was told that I would probably be more useful as a funder than as a researcher. I figured that in the longer term, my greatest chance at having a substantial impact lay in my potential as a researcher, but that I would have to improve my maths and programming skills to realize that. I got skilled by pursuing a master’s degree in bioinformatics, thinking I might contribute to work on genomics or brain emulations. But when I graduated, I realized I still wouldn’t be able to lead research on these topics; I didn’t yet have substantial experience with the research process. So I got humble and reached out to MIRI to see if they could use a research assistant. There, I worked under Jessica Taylor for a year, until the project I was involved in wound down. After that I reached out to several places to continue doing AI safety work, and was accepted as an intern and ultimately a full-time researcher at FHI. Right now, I feel like I have plenty of good AI safety projects to work on. But will the ideas keep flowing? If not, that’s totally fine: I can get outside and work on security and policy questions that EA hasn’t yet devoted much time to, or I could dive into weird problems like brain emulation or human enhancement that few people anywhere are working on. The fact is that EA is made up in some large part by a bunch of talented generalists trying to squeeze into tiny fields, with very little supervision to go around. For most people, trying to do direct work will mean that you repeatedly hit career walls like I did, and there’s no shame in that. If anything, the personal risk you incur through this process is honorable and commendable. Hopefully, the SHOW framework will just help you go about hitting walls a little more efficaciously. 1. Get Skilled (outside of EA) This is common advice for a reason: it’s probably the safest and most accessible path for the median EA. When you consider that skills are generally learned more easily with supervision, and that most skills are transferable between EA and non-EA contexts, getting training...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Cultured meat: A comparison of techno-economic analyses, published By Linch, Neil_Dullaghan on the effective altruism forum. For cultured meat to move the needle on climate, a sequence of as-yet-unforeseen breakthroughs will still be necessary. We’ll need to train cells to behave in ways that no cells have behaved before. We’ll need to engineer bioreactors that defy widely accepted principles of chemistry and physics. We’ll need to build an entirely new nutrient supply chain using sustainable agricultural practices, inventing forms of bulk amino acid production that are cheap, precise, and safe. Investors will need to care less about money. Germs will have to more or less behave. It will be work worthy of many Nobel prizes—certainly for science, possibly for peace. And this expensive, fragile, infinitely complex puzzle will need to come together in the next 10 years. On the other hand, none of that could happen. That is the takeaway from a new article by Joe Fassler (2021) in The Counter that draws heavily on two techno-economic analyses (TEA) of cultured meat (CE Delft 2021 & Humbird 2020). For full disclosure, we at Rethink Priorities were independently reviewing these TEAs (plus a third by Risner, et al. 2020) and in the process of writing a summary and comparison of them with our main takeaways. The article addresses many of the issues we also noticed, and supplements them with interviews from industry experts. Here we want to acknowledge that they beat us to the punch somewhat, add a few relevant things we think the article left out from the comparison, and what the next steps are in our project. The main cruxes of disagreement across the TEAs are: Approach to the research question Investor payback timelines Food grade versus pharmaceutical grade bioreactors The costs of media (growth factors and amino acids) at scale The limits of cell-engineering needed to reduce media consumption needs First though, we provide our quick summaries of the three TEAs so readers have a background before diving into the comparisons. As we are investigating a scientific question that sometimes hinges on deep technical expertise (which neither Neil nor I have), we will likely have some errors in the summaries and (especially) personal takeaways. In addition, this report is less thoroughly checked than usual for Rethink Priorities reports. It should best be viewed as our current tentative understanding of the existing literature, rather than a final definitive summary of the existing literature. tl;dr: We reviewed 3 TEAs on cultured meat. Our summary is that Humbird is very high quality and suggests cultured meat cost-competitiveness is hard and needs everything to go right. CE Delft outlines some of what will need to go right, but doesn't provide much evidence that any of it is possible, has internal validity errors, and arguably has too much motivated reasoning. Risner, et al. is decent, within the narrow limits it sets itself, but too many details are underespecified for it to reflect the full costs and challenges of scaling up cultured meat. Reading the TEAs and doing surrounding research has turned Linch from a cultured meat optimist to being broadly pessimistic. Neil wants to be more agnostic until further research from Rethink Priorities and others. Our TEA Summaries As part of a project forecasting the potential for cost-competitive cultured meat to displace conventional meat, my colleague Neil and I investigated three techno-economic analyses (TEAs) estimating the economic feasibility of cost-competitive cultured meat ($2.50-$8/kg, akin to different estimates for existing wholesale meat prices). A quick note on terms. The studies we looked at (and us) are only investigating “cultured meat”, that is, animal cell based meat of target conventional meats (usually beef). They do ...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Desperation Hamster Wheels, published by Nicole_Rosson the effective altruism forum. This is a linkpost for In my first few jobs, I felt desperate to have an impact. I was often filled with anxiety that I might not be able to. My soul ached. Fear propelled me to action. I remember sitting in a coffee shop one Saturday trying to read a book that I thought would help me learn about biosafety, an impactful career path I wanted to explore. While I found the book interesting, I had to force myself to read each page because I was worn out. Yet I kept chugging along because I thought it was my lifeline, even though I was making extremely little progress. I thought: If I don’t do this excellently, I’ll be a failure. There were three critical factors that, taken together, formed a “desperation hamster wheel,” a cycle of desperation, inadequacy, and burn out that got me nowhere: Self-worth -- I often acted and felt as if my self-worth was defined wholly by my impact, even though I would give lip service to self-worth being more than that. Insecurity/inadequacy -- I constantly felt not skilled or talented enough to have an impact in the ways I thought were most valuable. Black and white thinking -- I thought of things in binary. E.g. I was either good enough or not, I was smart or not, I would have an impact or not. Together, these factors manifested as a deep, powerful, clawing desire for impact. They drove me to work as hard as possible, and fight with all I had. It backfired. This “desperation hamster wheel” led me to think too narrowly about what opportunities were available for impact and what skills I had or could learn. For example, I only thought about having an impact via the organization I was currently working at, instead of looking more broadly. I only considered the roles most lauded in my community at the time, instead of thinking outside the box about the best fit for me. I would have been much happier and much more impactful had I taken a more open, relaxed, and creative approach. Instead, I kept fighting against my weaknesses -- against reality -- rather than leaning into my strengths. (1) It led me to worse work habits and worse performance, creating a vicious cycle, as negative feedback and lack of success fueled my desperation. For example, I kept trying to do research because I thought that that work was especially valuable. But, I hadn’t yet developed the skills necessary to do it well, and my desperation made the inherent vulnerability and failure involved in learning feel like a deadly threat. Every mistake felt like a severe proclamation against my ability to have an impact. I’m doing a lot better now and don’t feel this desperation anymore. Now, I can lean into my strengths and build on my weaknesses without having my whole self-worth on the line. I can approach the questions of having an impact with my career openly and with curiosity, which has led me to a uniquely well-suited role. I can try things and make mistakes, learning from those experiences, and becoming better. I feel unsure about what helped me change. Here are some guesses, in no particular order: Taking anxiety and depression medication Changing roles to find one that played more to my strengths I’m sad that I’m not better or smarter than I grew up hoping I might be. It took time to grieve that and come to terms with it on both a personal and impact level (how many people could I have helped?) (2) Digging into the slow living movement (3) and trying to live more intentionally and with more reflection Having a partner who loves me and who doesn’t care about the impact I have, except so far as he knows I’d like to have an impact Reconnecting with my younger, child self, who felt curious and excited. In the worst moments on my desperation hamster wheel, I no longer felt those things. I foun...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: EA Funds is more flexible than you might think, published by Jonas Vollmer on the effective altruism forum. I’ve noticed that some people seem to have misconceptions about what kinds of grants EA Funds can make, so I put together a quick list of things we can fund that may be surprising to some of you. (Reminder: our funding deadline for this round is March 7, though you can apply at any time of the year.) EA Funds will consider building longer-term funding relationships, not just one-off grants. Even though we typically make one-off grant decisions and have some turnover among fund managers, we can consider commitments to provide longer-term funding. We are also happy to otherwise help with the predictability of funding, e.g. by sharing our thoughts on how easy or hard we expect it to be to get funding in the future. EA Funds can provide academic scholarships and teaching buy-outs. We haven’t received a lot of applications for scholarships in the past, but the Long-Term Future Fund (LTFF) and EA Infrastructure Fund (EAIF) would be very excited about funding more of them. Few graduate students and postdocs seem to be aware that they can be bought out of teaching duties, but sometimes this can be a great way to make more time for research. EA Funds will consider funding organizations, including medium-sized ones, not just small projects. The LTFF and EAIF are still unsure whether they will want to fund larger organizations in the longer term. Until then, they will consider funding organizations as long as they don’t have a comparative disadvantage for doing so. If Open Philanthropy has not seriously considered funding you, we will consider you, at least for now. EA Funds will consider making large grants. We have made grants larger than $250,000 in the past and will continue to consider them (potentially referring to other funders along with our evaluation). We think our comparative advantage is evaluating grants that other funders aren’t aware of or don’t have the capacity to evaluate, which typically are small grants, but we are flexible and willing to consider exceptions. The EAIF and LTFF can make grants at any time of the year and on short notice. We run funding rounds because it saves us some effort per application. But if your project needs funding within a month and the next decision deadline is three months away, we can still make it happen. If there were a project that would have a very large impact if funded within three days, and no impact otherwise, there’s a high chance that we would get it funded. The EAIF and LTFF can make anonymized grants. As announced here, we can get you funded without disclosing personal information about you in our public payout reports. EA Funds can pass on applications to other funders. In cases where we aren’t the right funder (e.g., because we don’t have sufficient funding, or it’s a for-profit start-up, or there is some other issue), we are open to passing along applications when we think it might be a good fit. We are in touch with Open Philanthropy, EA-aligned for-profit investors, and other funders, and they have expressed interest in receiving interesting applications from us. In general, we will listen to the arguments rather than rigidly following self-imposed rules. We have few constraints and are good at finding workarounds for the ones we have (except for some legal ones). We want to help great projects succeed and will do what it takes to make that happen. If you are unsure whether EA Funds can fund something, the best working hypothesis is that it can. Reminder: the current EA Funds round closes March 7th. Apply here, and see this article for more information. (Note that the Global Health and Development Fund does not accept funding applications, so this post does not apply to it.) thanks for listening. to help us...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Aligning Recommender Systems as Cause Area, published by IvanVendrov on the effective altruism forum. by Ivan Vendrov and Jeremy Nixon Disclaimer: views expressed here are solely our own and not those of our employers or any other organization. Most recent conversations about the future focus on the point where technology surpasses human capability. But they overlook a much earlier point where technology exceeds human vulnerabilities. The Problem, Center for Humane Technology. The short-term, dopamine-driven feedback loops that we have created are destroying how society works. Chamath Palihapitiya, former Vice President of user growth at Facebook. The most popular recommender systems - the Facebook news feed, the YouTube homepage, Netflix, Twitter - are optimized for metrics that are easy to measure and improve, like number of clicks, time spent, number of daily active users, which are only weakly correlated with what users care about. One of the most powerful optimization processes in the world is being applied to increase these metrics, involving thousands of engineers, the most cutting-edge machine learning technology, and a significant fraction of global computing power. The result is software that is extremely addictive, with a host of hard-to-measure side effects on users and society including harm to relationships, reduced cognitive capacity, and political radicalization. Update 2021-10-18: As Rohin points out in a comment below the evidence for concrete harms directly attributing to recommender systems is quite weak and speculative; the main argument of the post does not strongly depend on the last paragraph. In this post we argue that improving the alignment of recommender systems with user values is one of the best cause areas available to effective altruists, particularly those with computer science or product design skills. We’ll start by explaining what we mean by recommender systems and their alignment. Then we’ll detail the strongest argument in favor of working on this cause, the likelihood that working on aligned recommender system will have positive flow-through effects on the broader problem of AGI alignment. We then conduct a (very speculative) cause prioritization analysis, and conclude with key points of remaining uncertainty as well as some concrete ways to contribute to the cause. Cause Area Definition Recommender Systems By recommender systems we mean software that assists users in choosing between a large number of items, usually by narrowing the options down to a small set. Central examples include the Facebook news feed, the YouTube homepage, Netflix, Twitter, and Instagram. Less central examples are search engines, shopping sites, and personal assistant software which require more explicit user intent in the form of a query or constraints. Aligning Recommender Systems By aligning recommender systems we mean any work that leads widely used recommender systems to align better with user values. Central examples of better alignment would be recommender systems which optimize more for the user’s extrapolated volition - not what users want to do in the moment, but what they would want to do if they had more information and more time to deliberate. require less user effort to supervise for a given level of alignment. Recommender systems often have facilities for deep customization (for instance, it's possible to tell the Facebook News Feed to rank specific friends’ posts higher than others) but the cognitive overhead of creating and managing those preferences is high enough that almost nobody uses them. reduce the risk of strong undesired effects on the user, such as seeing traumatizing or extremely psychologically manipulative content. What interventions would best lead to these improvements? Prioritizing specific interventions is out of scope ...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: [Podcast] Having a successful career with anxiety, depression, and imposter syndrome, published by Aaron Gertler on the effective altruism forum. This is a linkpost for/ Note: 80,000 Hours wants to keep the interviewee's name off of Google in this context. You can use "Howie" in comments, but please don't use his surname. We'll redact the surname if any comment happens to use it. I'm linking to one of my favorite 80,000 Hours podcast episodes ever — not only because the topic seems important and broadly relevant, but because some of the interviewee's advice was directly applicable to problems I was experiencing and problems I've been working through with friends who are struggling. I'd honestly recommend the episode to basically anyone in or out of EA, with a few caveats: As 80,000 Hours notes, the conversation gets pretty intense. See the end of the quote below for advice on working around the most intense bits. The podcast goes on at length about the ways in which the EA community can be deeply supportive of people struggling with mental illness. I can imagine parts of it being a difficult listen for people who either (a) spend a lot of their time in other communities that aren't so supportive, or (b) haven't gotten the same kind of support from within the EA community. In either case, I can imagine some of the advice not being very applicable, and this being frustrating. Points that especially resonated for me: Your friends may not be available all the time, but they'll almost always want to help in some way. Consider ways that even a few minutes per day of a friend's time could be good for you. If you're struggling to get something done, and you're about to spend hours worrying about it or frantically churning out a terrible version of it before some arbitrary deadline... well, I'll quote the podcast: Sometimes you can literally just write a one sentence email that’s like, “Hey, I’m not going to get to this for a week. I’m sorry,” and that clears the whole thing. The person writes back, “That’s totally fine,” and you don’t have to feel bad about it at all anymore. And nobody was ever upset. Episode description Mental illness is one of the things that most often trips up people who could otherwise enjoy flourishing careers and have a large social impact, so we think this could plausibly be one of our more valuable episodes. We also hope that the episode will: Help people realise that they have a shot at making a difference in the future, even if they’re experiencing (or have experienced in the past) mental illness, self doubt, imposter syndrome, or other personal obstacles. Give insight into what it’s like in the head of one person with depression, anxiety, and imposter syndrome, including the specific thought patterns they experience on typical days and more extreme days. In addition to being interesting for its own sake, this might make it easier for people to understand the experiences of family members, friends, and colleagues — and know how to react more helpfully. Several early listeners have even made specific behavioral changes due to listening to the episode — including people who generally have good mental health but were convinced it’s well worth the low cost of setting up a plan in case they have problems in the future. So we think this episode will be valuable for: People who have experienced mental health problems or might in future; People who have had troubles with stress, anxiety, low mood, low self esteem, imposter syndrome and similar issues, even if their experience isn’t well described as ‘mental illness’; People who have never experienced these problems but want to learn about what it’s like, so they can better relate to and assist family, friends or colleagues who do. In other words, we think this episode could be worthwhile for almost every...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Ask Me Anything!, published by William_MacAskill on the effective altruism forum. Thanks for all the questions, all - I’m going to wrap up here! Maybe I'll do this again in the future, hopefully others will too! Hi, I thought that it would be interesting to experiment with an Ask Me Anything format on the Forum, and I’ll lead by example. (If it goes well, hopefully others will try it out too.) Below I’ve written out what I’m currently working on. Please ask any questions you like, about anything: I’ll then either respond on the Forum (probably over the weekend) or on the 80k podcast, which I’m hopefully recording soon (and maybe as early as Friday). Apologies in advance if there are any questions which, for any of many possible reasons, I’m not able to respond to. If you don't want to post your question publicly or non-anonymously (e.g. you're asking “Why are you such a jerk?” sort of thing), or if you don’t have a Forum account, you can use this Google form. What I’m up to Book My main project is a general-audience book on longtermism. It’s coming out with Basic Books in the US, Oneworld in the UK, Volante in Sweden and Gimm-Young in South Korea. The working title I’m currently using is What We Owe The Future. It’ll hopefully complement Toby Ord’s forthcoming book. His is focused on the nature and likelihood of existential risks, and especially extinction risks, arguing that reducing them should be a global priority of our time. He describes the longtermist arguments that support that view but not relying heavily on them. In contrast, mine is focused on the philosophy of longtermism. On the current plan, the book will make the core case for longtermism, and will go into issues like discounting, population ethics, the value of the future, political representation for future people, and trajectory change versus extinction risk mitigation. My goal is to make an argument for the importance and neglectedness of future generations in the same way Animal Liberation did for animal welfare. Roughly, I’m dedicating 2019 to background research and thinking (including posting on the Forum as a way of forcing me to actually get thoughts into the open), and then 2020 to actually writing the book. I’ve given the publishers a deadline of March 2021 for submission; if so, then it would come out in late 2021 or early 2022. I’m planning to speak at a small number of universities in the US and UK in late September of this year to get feedback on the core content of the book. My academic book, Moral Uncertainty, (co-authored with Toby Ord and Krister Bykvist) should come out early next year: it’s been submitted, but OUP have been exceptionally slow in processing it. It’s not radically different from my dissertation. Global Priorities Institute I continue to work with Hilary and others on the strategy for GPI. I also have some papers on the go: The case for longtermism, with Hilary Greaves. It’s making the core case for strong longtermism, arguing that it’s entailed by a wide variety of moral and decision-theoretic views. The Evidentialist’s Wager, with Aron Vallinder, Carl Shulman, Caspar Oesterheld and Johannes Treutlein arguing that if one aims to hedge under decision-theoretic uncertainty, one should generally go with evidential decision theory over causal decision theory. A paper, with Tyler John, exploring the political philosophy of age-weighted voting. I have various other draft papers, but have put them on the back burner for the time being while I work on the book. Forethought Foundation Forethought is a sister organisation to GPI, which I take responsibility for: it’s legally part of CEA and independent from the University, We had our first class of Global Priorities Fellows this year, and will continue the program into future years. Utilitarianism.net Darius Meissner and I (w...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Many Undergrads Should Take Light Courseloads , published by Mauricio on the effective altruism forum. Thanks to Kuhan Jeyapragasan for comments and relevant/motivating conversation. In the spirit of saving time, I wrote this one relatively quickly. Summary / Introduction When I started undergrad, I decided to take almost as many classes as I could that term—wouldn’t want to miss out on limited opportunities to learn, right? I spent that whole term hunched over books and stressing over how behind I was (so, not meeting people, not getting research or job experience, not figuring out what problems to prioritize, not getting others into high-impact careers), only to later realize my classes had taught me little of value. That doesn’t seem to have been a unique experience; many impact-driven undergrads fill their schedule with many classes (often, time-consuming ones). Consider not doing that—I think taking many classes each term is one of the most costly, easily avoidable mistakes that impact-driven undergrads tend to make. After all, it seems that, for most promising career goals: Extra classes are not that valuable. Some things you could be doing with that time instead are extremely valuable. If you spend much unnecessary time on classes (e.g. get more than one degree in undergrad, take almost as many classes as you’re allowed to take each term, take especially time-consuming classes, etc), please at least have it be an intentional choice—one in which you recognize the opportunity cost. The opportunity cost is too massive to accept on the basis of the high school mindset that the most important choices we make are our curricula—there are so many other ways we can pursue our goals. Caveats This is written in the context of US universities, where students tend to have substantial flexibility to choose their courseloads. It may be much less applicable to other contexts. No, I’m not saying you should let your grades plummet or drop out of college. Some people’s productivity benefits a lot from oversight/accountability/deadlines. If that’s the case for you, consider alternatives to classes which provide that structure, e.g. part-time supervised work or collaborations. Related/supporting thoughts If you want to go into research, research experience / track record and good grades (e.g. GPA of ~3.8+ for CS) on classes you took are major assets; having taken extra classes won’t be as noticed (and will burn time that, if spent differently, could better prepare you for graduate school / research). At least Dan Hendrycks (CS PhD student researching ML safety at UC Berkeley) agrees this strongly applies to AI safety technical research / CS grad school. He advises: "Avoid tough needless courses and take easy courses... [Unnecessary, tough classes are] the easiest way people burn time. [...] for CS grad school, research is what matters. [...] I can’t see much reason for a double or triple major since those will force you to take many more courses." [Edited to add details] There’s a ton of low-hanging fruit you could be taking for getting other undergrads to strategically dedicate their careers to highly pressing problems. Extra classes have very little value for going into policy or many industry jobs (from two policy professionals’ advice in conversation). Classes are very unlikely to teach you much about a bunch of very important things, like what you value and what cause prioritization / career paths will best allow you to realize those values. Taking more classes trades off against your ability to deeply understand and/or get good grades in the classes you do take. Being very stressed and sad over a packed courseload doesn’t just suck—it also probably makes you less productive and less charismatic (which, editing to clarify, seems useful for building connections and getting peo...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Please Take the 2020 EA Survey, published by Peter Wildeford on the effective altruism forum. The 2020 Effective Altruism Survey is now live at the following link: If you would like to share the EA Survey with others, please share this link: The survey will remain open through the end of the year. What is the EA Survey? The EA Survey provides valuable information about the demographics of the EA community, how people get involved, how they donate, what causes they prioritise, their experiences of EA, and more. The estimated average completion time for the main section of this year’s survey is 20 minutes. There is also an ‘Extra Credit’ section at the end of the survey, if you are happy to answer some more questions. What's new this year? There are two important changes regarding privacy and sharing permissions this year: 1) This year, all responses to the survey (including personal information such as name and e-mail address) will be shared with the Centre for Effective Altruism unless you opt out on the first page of the survey. 2) Rethink Priorities will not be making an anonymised data set available to the community this year. We will, however, consider requests for us to provide additional aggregate analyses which are not included in our main series of posts. Also the Centre for Effective Altruism has generously donated a prize of $500 USD that will be awarded to a randomly selected respondent to the EA Survey, for them to donate to any of the organizations listed on EA Funds. Please note that to be eligible, you need to provide a valid e-mail address so that we can contact you. We would like to express our gratitude to the Centre for Effective Altruism for supporting our work. thanks for listening. to help us out with the nonlinear library or to learn more, please visit nonlinear.org.
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Hinge of History Refuted (April Fools' Day), published by Thomas Kwa on the effective altruism forum. Introduction Is the present the hingiest time in history? The answer to this question is enormously important to altruists, and as such has attracted the attention of many philosophers and researchers: Nick Beckstead, Phil Trammell, Toby Ord, Aron Vallinder, Allan Dafoe, Matt Wage, Holden Karnofsky, Carl Shulman, and Will MacAskill. I attempt to answer the question through a novel method of hinginess analysis. Flawed Hinginess Measures To determine whether one era of history is hingier than another, we must have some way to measure hinginess. The naive method used by many previous researchers is to simply count the number of hinges in each time period. There are several problems with this idea. Suppose that a heavy door is held up by two hinges. Replacing these with four hinges, each half the size, would double the number of hinges. However, since the range of motion of the door is the same in each case, the hinginess has not changed. Taken to its conclusion, a naive hinge count leads to the absurd conclusion that the hinginess of the world is dominated by its insect population. It is estimated that the world contains on the order of 1 million billion ants; each ant has six legs, with each leg containing three hinges. Even disregarding the antennae and mandibles and necks of ants, we end up with an estimate of 1.81016 hinges belonging to ants, which dwarfs all of humanity's hinges by orders of magnitude.1 Despite the fact that ant joints are millions of times less hingey than some other hinges, many people believe that underground ant colonies contribute the vast majority of the world's hinginess-- the so-called "underfoot myth". In reality, the proportion is much smaller, which we will examine in the next section. Estimating the total mass or volume of hinges is not much better. While past hinges were limited to natural materials, advances in materials science have allowed us to manufacture hinges of many different metals: "copper, brass, nickel, bronze, stainless steel, chrome, and steel" (source), allowing for much better quality, more hingey, hinges of the same mass or volume. A reasonable hinginess measure should take into account the number of hinges in the universe, but also the hinginess capacity of each individual hinge. Estimating Hinginess I claim that hinginess of a given hinge depends on three factors, and can be estimated as scale tractability neglectedness: Scale: How big a door can the hinge swing, and through what distance? Tractability: When carrying this door, how low is the hinge's friction torque, compared to the torque required to twist the hinge off-axis? (In short, how good of a hinge is it?) Neglectedness: How long has the hinge functioned without maintenance?5 Some hinges rank poorly in scale and are not very neglected (e.g. ant tarsal joints), while others are large in scale and very neglected (e.g. the doors of ancient temples). Similarly, some hinges are very tractable (e.g. in a precision-engineered bank vault) while some are intractable (a living hinge, like that on a plastic ketchup bottle lid, is only a few times easier to open than to twist or break). This is summarized in the table below. Scale Tractability Neglectedness High Panama Canal gate Bank vault door Ancient temple door Low Ant leg joint Ketchup bottle Newly manufactured part Hinginess in the Past Despite the low neglectedness of animal joints, they accounted for most of the hinginess in the world between the Cambrian explosion and the rise of agriculture. The reason is that there were simply no other hinges.4 The "underfoot myth" notwithstanding, insects account for comparatively little hinginess, mostly due to their small scale and neglectedness.2 Hinginess in the Prese...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: COVID-19 brief for friends and family, published by eca on the effective altruism forum. People have been saying all kinds of wild stuff about the new coronavirus. I work in biosecurity and have been following the outbreak since the beginning. What follows is my best attempt to communicate what we know about the virus, and how to prepare, with my family and friends. I thought I would share in case others have been looking for a similar document. This is NOT intended to be a detailed, rigorous justification of the preparation measures I've outlined, nor an authoritative statement on the best current estimates for epidemiological parameters. Instead, I try to be as straightforward as possible, cite only the action-relevant details, and align with the best recommendations I've heard from the EA biosecurity community as well as experts writ large. Caveats aside, I'd be interested in feedback on this purpose, including whether I am missing sensible prep measures, have the right tone for sharing widely, or am wrong about the facts. I'm happy to provide more technical justification in comments. Here is the draft. I'll be updating it as we have more info and I have more time to include sources, so go there for the most recent version. The first draft is included below for convenience. If you'd like, please feel free to copy, modify, etc and share with your own family. Coronavirus in brief (work in progress) Bottom Line. Coronavirus is significantly worse than the flu, but not the zombie apocalypse. No need to panic, but it probably makes sense to prepare. It is going to affect day-to-day-life in western countries, including the U.S. You and your family will probably face personal risk of illness by the end of the year. You can prepare by Stocking ~1 month of nonperishable food and other necessities, and 3 months of medications. Relocating away from dense cities and/or shifting to working from home, if possible. Learning how to properly wash your hands, and practicing not touching your face. Avoiding travel after March of this year, and/or planning with cancellation option. Making plans to care for and protect the elderly from exposure to the virus. Buying and carrying hand sanitizer, and using it frequently (every 30 min outside your home, before you eat or touch your face). Wiping commonly contacted items (phone, keyboard, headphones etc) down with disinfectant regularly. Avoiding crowded places (e.g. concerts, subways, theatres, buses, airports etc) without protection. For essential travel, buying N95 respirators, if you can, and learning how to use them, including shaving facial hair. What does the virus do? The virus causes coughing, sneezing, fever, pneumonia, and in severe cases kidney failure and death. 80% of cases are relatively mild. The rest look like moderate to severe pneumonia. Approximately 1% of people who catch the virus die. After symptoms show, it takes 3 weeks - 1 month for severe cases to resolve. Risk is much higher for people over 40. Children appear to be relatively unaffected. Men may be twice as susceptible as women, although it is too early to tell with confidence. Immunity may not last long, and no-one has it to start with. Where is the virus now (Feb 28)? 80,000+ cases worldwide, most in China. 2,800+ deaths. 23 countries have more than 10 cases outside of China. Japan, Iran, Italy, and South Korea all had an exponential growth of cases from 10s to 100s in less than a week. 60 cases in the U.S. 1 case, in Northern California, is likely the first spread without link to China, suggesting the virus is spreading undetected in the United States. What do we know about the virus? It likely arose from a crossover, or “zoonosis” from animals in China, sometime in late November early december of 2019. It is most closely related to a virus called SARS which...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Finding equilibrium in a difficult time, published by Julia_Wise on the effective altruism forum. To start: I don’t want to say that self-isolation is that bad in the scheme of things. People have lost their lives, they’ve lost loved ones. Healthcare workers are working hard, at their own risk, to protect us all. Some other workers don’t have a choice about continuing to work in person. And for some immunocompromised people and their families, self-isolation is the reality much or all of the time. But I’m writing for those of us who aren’t physically ill, are doing some amount of self-isolation or social distancing because of the pandemic, and are not finding it easy. Most of this isn’t specific to EAs, but I hope it’s useful. We are all having a hard time with this I assume I’m not the only person who finished last week and realized I’d gotten very little work done. We're all anxious about the situation in different ways. This is a hard, weird time. I don’t expect to have normal work weeks for a while, and you probably shouldn’t expect that either (especially if you’re newly working from home or if you have children who are suddenly out of school). And if you're affected by job loss, of course things are even more upside-down. Focus on the basics: Sleep. Eat nourishing food. Get some exercise and sunshine. Connect with other people. These things are literally a public health measure — you’re protecting your immune system. On information: If you’re like me, you’ve found yourself reading more about this topic than is useful for any practical purpose. Think about diminishing marginal returns: what's the amount and kind of information about this that will benefit you? And when does it start to produce very little value? Here’s the advice Gregory Lewis (a medical doctor and public health specialist who works on biorisk at the Future of Humanity Institute) gave to his colleagues: I’d recommend some information hygiene. The typical person doesn’t need ‘up to the minute’ information on what is going on worldwide, and generally it takes time for instant reports to resolve into a clear picture. Further, typical media reporting will tend to be biased in the very alarming direction (e.g., the typical ‘live feed’: “New case in A!” “New Case in B!” “Event C cancelled due to coronavirus fear!”). Social media tends not to be much better regarding bias, and worse with regard to reliability. In other words, especially for those worried about this, staying glued to the screen can get a very high yield of anxiety for a very poor yield of useful action-relevant information. Here are some good sources of information (which is the bulk of my information diet): Generally: WHO Public health matters Johns Hopkins Center for Health Security newsletter For the data: JH mapping dashboard Worldometer (slightly easier to divvy out some time courses) Typically good commentary/analysis/explanation Tom Inglesby’s Twitter (both for itself, and for links to CHS’s other work) John Campbell’s Youtube Trevor Bedford’s Twitter for virology. On working remotely: When the Great Plague of London sent Isaac Newton and other Cambridge students home for a year in 1665, he did some of his best work including the famous falling-apple realization. Maybe once you settle in, you'll have a productive time in a different environment than usual. If you’re used to working from a desk and switch to working from a couch or bed, you’re risking hurting your body. (After a two-week stretch of writing from bed a lot, my husband had serious wrist pain for weeks.) Please set up a good workspace where you can use your computer without putting your neck, back, and wrists in awkward positions. More: Wirecutter on equipment for working from home (though you can make an ergonomic setup for much less - here’s mine.) Making profession...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Donating money, buying happiness: new meta-analyses comparing the cost-effectiveness of cash transfers and psychotherapy in terms of subjective well-being, published by MichaelPlant, JoelMcGuire on the effective altruism forum. This is a cross-post from the website of the Happier Lives Institute. TL;DR: We estimate that StrongMinds is 12 times (95% CI: 4, 24) more cost-effective than GiveDirectly in terms of subjective well-being. This puts it roughly on a par with the top deworming charities recommended by GiveWell. [Edit 26/10/2021: Table 4 and accompanying text added] 1. Background and summary In order to do as much good as possible, we need to compare how much good different things do in a single ‘currency’. At the Happier Lives Institute (HLI), we believe the best approach is to measure the effects of different interventions in terms of ‘units’ of subjective well-being (e.g. self-reports of happiness and life satisfaction). In this post, we discuss our new research comparing the cost-effectiveness of psychotherapy to cash transfers. Before we get to that comparison, we should first highlight the advantage of doing it in terms of subjective well-being; to illustrate that, it will help to flag some alternative methods. We could assess the effect each intervention has on wealth, but this would fail to capture the benefits of psychotherapy. It’s implausible to think that treating depression is only good insofar as it helps you to earn more. We could assess their effects using standard measures of health, such as a Disability-Adjusted Life-Year (DALY), but it’s similarly mistaken to think that alleviating extreme poverty is only good insofar as it helps you to become healthier. We could make some arbitrary assumptions about how much a given change in income and DALYs each contribute to well-being; this would allow us to ‘trade’ between them. But this would just be a guess and could be badly wrong. If we measure the effects on subjective well-being, how individuals feel and think about their lives (e.g. "Overall, how satisfied are you with your life, nowadays?" 0-10), we can provide an evidence-based comparison in units that more fully capture what we think really matters. Efforts to work out the global priorities for improving subjective well-being are relatively new. Nevertheless, the recent push to integrate well-being in public policy-making in countries such as Scotland and New Zealand, as well as the reach of publications such as the World Happiness Report (which started in 2012), indicates that this is a viable approach. Earlier work conducted by HLI’s Director, Michael Plant, suggested that using subjective well-being might reveal different priorities for individuals and organisations seeking to do the most good, with mental health standing out as one area that is crucial and potentially neglected. Plant’s (2018, 2019 ch. 7) prior back-of-the-envelope calculations indicated that StrongMinds, a mental health charity that treats women with depression in Africa, could be as cost-effective as GiveWell’s top charity recommendations. These initial findings motivated us to do a much more rigorous analysis of the same interventions in terms of subjective well-being, so we undertook meta-analyses in each case. These aimed to address three questions: Is assessing cost-effectiveness in terms of subjective well-being feasible: are there enough data that we can make these sorts of comparisons without making major assumptions to fill in the blanks? Is this approach worthwhile: does it indicate new or different priorities? Does this specific comparison between cash transfers and psychotherapy indicate that donors and decision-makers should change the way they allocate their resources, assuming they want to do the most good? Our research focused specifically on studies in low...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Careers Questions Open Thread, published Benjamin_Todd on the effective altruism forum. Hi everyone, Many people in EA aren’t able to get as much career advice as they’d like, while at the same time, hundreds of EAs are happy to provide informal advice and mentoring within their career area. Much of what we do in our one-on-one advice at 80,000 Hours is try to connect these two groups, but we’re not able to cover a significant number of people. At the same time, spaces like the EA careers discussion FB group don’t seem to have taken off as a place where people get concrete advice. As an experiment, I thought we could try having an open career questions thread on the Forum. By posting a reply here, anyone can post a question about their career, without having to make a top level post, and anyone on the forum can write an answer. If it works well, we could do it each month or so. To get things going, some of the 80,000 Hours team will be available from Monday onwards to write quick answers to topics they have views on (in an individual capacity rather than representing our official view), though our hope is that others will get involved. For those with questions, I could imagine those ranging from high-level to practical: I’m trying to choose whether to focus on global health or climate change, how should I decide? I can either accept this job offer or go to graduate school, which seems best? Which skills should I focus on learning in my spare time? Where can I learn more about how to interview for jobs in policy? I’m especially keen to see questions from people who haven’t posted much before. The answers to your questions will probably be more useful if you can share a bit of background, though feel free to skip if it'll prevent you from asking at all! You can also skip if you're asking a very general question. Here’s a short template to provide background – feel free to pick whichever parts seem most useful as context: Which 2-5 problem areas do you intend to focus on? What ideas for longer-term roles do you have? What do you see as your strengths & most valuable career capital? Some key facts on your experience / qualifications / achievements (or a link to your LinkedIn profile if you’re comfortable linking your name to the question). Any important personal constraints to keep in mind (e.g. tied to a certain location) What 2-5 next career moves are you considering? (i.e. specific jobs or educational opportunities you might take) If you want to do a longer version, you could use our worksheet. Just please bear in mind this will all be public on the internet for the long term. Don’t post things you wouldn’t want future employers to see, unless using an anonymous account. Even being frank about the pros and cons of different jobs can easily look bad. As a reminder, we have more resources to help you write out and clarify your plan here. For those responding to questions, bear in mind this thread might attract people who are newer to the forum, and careers can be a personal subject, so try to keep it friendly. I’m looking forward to your questions and seeing how the thread unfolds! Update 21 Dec: Thank you everyone for the questions and responses! The 80k team won't be able to post much more until Jan, but we'll try to respond after that. thanks for listening. to help us out with the nonlinear library or to learn more, please visit nonlinear.org.
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Introducing High Impact Professionals, published by DevonFritz, Federico Speziali on the effective altruism forum. Overview It is our pleasure to present to you our new EA organization, High Impact Professionals (HIP). Our vision is to enable EA working professionals to have the biggest positive impact possible. We imagine a community working together for the greater good, contributing not only through their money but also with their time and skills. We recently went through the 2021 Charity Entrepreneurship Incubation Program and received $100,000 in funding for our first full year of operations. The rest of this document will outline: The problem we are solving How we are solving it Our next steps How you can get involved Key Takeaways We created HIP to maximize the impact of EA working professionals and solve several identified problems within the EA ecosystem. We are going to pilot several promising interventions in year one to identify the most impactful path forward. We list them in the Pilots section of the post. We have many ways you can get involved. Our first pilot is workplace fundraising events. We have successfully run these in the past and are now helping EA working professionals (HIPs) host them at their organizations. If you are an EA working professional and want to increase your impact, become more engaged, and gain useful skills and EA career capital, register your interest to host a fundraising event. We will provide you with the resources and support needed to host a successful event. We want to talk to more HIPs to get a better understanding of the needs of our community. Through our own giving of time and money, we have a sense of what might be needed but want to validate this with others in the community. If you are an EA working professional looking to have more impact please register your interest here. We encourage you to have a low bar for doing this: if you are considering it, just do it! Please feel free to share with others you know who might be a good fit. Thanks to Cillian Crosson, Ula Zarosa, Aaron Gertler, Jack Lewars, Jan-Willem Van Putten, and Brian Tan for their invaluable feedback on this announcement. All errors are our own. Problem Impact According to the most recent EA Surveys, over half of all EAs are in the private sector and earning to give is the most common career choice amongst EAs with more than a third of votes cast. This group has resources like skills, time and money that they can contribute to high-impact organizations and through surveys have expressed a desire to do so. For example, the same survey revealed that a full 55% of EAs want to donate more, and more than one-third want to volunteer their time as a way to become more engaged. This means that the largest cohort of EAs is limited in their ultimate impact and seems to be facing a bottleneck. EA Community Issues In addition to impact problems, there have also been issues within the EA community that our organization can likely mitigate: Funding diversification - a recent survey of 29 meta organizations revealed that a majority of those polled have a strong desire for more funding diversification for their organization. Supply and demand issue with EA jobs - many EAs want to work for EA organizations but there are few positions available. This creates a lot of frustration for the many EAs that apply for an EA job but don’t get one. A recent forum post implies this could be a range of 47-124 people being rejected per role. Insularity in EA - EA is quite insular and would likely benefit from stronger connections to the private sector, both to spread the ideas of EA more widely and to establish a more solid reputation for EA in wider circles. Evidence The rigorous research and selection process performed by Charity Entrepreneurship identified this idea as one of...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: £4bn for the global poor: the UK's 0.7%, published by Sanjay on the effective altruism forum. Background The UK Chancellor of the Exchequer announced that the government will reduce the amount of spend on international development from 0.7% of GNI to 0.5%. (read more, e.g., here). This means that the government will spend £10bn on aid instead of £14bn. This post sets out an attempt to undo this decision. I'm hoping we can find more people to help with analysis and to donate to the campaign. Plan At a high level, the plan we have in mind is essentially taken straight from the tech startup playbook: Identify the highest leverage constituencies (probably those with "moderate" Tory MPs) perform google and facebook ads to identify people in those constituencies willing to write a letter or email to their MP recruit them and provide them with a template letter/email I'm currently reaching out to a bunch of NGOs in my network to ask them Are approaches like these already being used? (and if not, why not?) Do any NGOs already have the analysis on which constituencies are the best targets? Once we have recruited people, how best to look after them? Even if we find that NGOs are already targeting the most strategic constituencies, we would to do some work ourselves on analysing which the most strategic constituencies are, as this would help us to assess and potentially support the decision-making being done by the NGOs. Who's working on this, and why do we need more people The main people involved thus far are myself and a member of the EA community called Sahil. We will need more people to help with various tasks, especially analysis to work out which MPs are the most strategic ones to reach out to. There are probably other tasks that I haven't thought through -- this post is being written quickly, as we may not have much time to act. How would funds be used? Funds are needed for Facebook/Google ads to reach strategically chosen constituents of the MPs who are most interested in supporting international development. Given the considerations set out below, I would judge that this likely outperforms a donation to a GiveWell-recommended charity. (A confident/rigorous assessment of this claim would require a more detailed model than I have time for; timescales are likely short) How good is more development spend? DfID has in recent years been considered one of the top international development agencies, known for its focus on impact and its awareness of cost-effectiveness. Their Chief Economist was and still is Rachel Glennerster (early taker of the GWWC pledge). Something that's unclear is the extent to which DfID's effectiveness might change after the merger with the FCO (foreign office). Having said that, at this particular time, the need is particularly high, so at the margin, reducing spend is likely to mean that much-needed programmes are brought to an abrupt halt right at the moment when work is most needed. Reducing development spend in the short term strikes me as a clearly bad idea. How effective is this campaign likely to be? The change will require a change to the law, which means MPs will have to vote on it. I get the impression that it's not clear that the government will win on this. This suggests that it's a good campaign to apply some effort to. A guardian political correspondent had this to say about the drop in the ODA percentage: "This is a very politically tricky moment, as shown by the amount of time Sunak uses justifying it. A lot of Tory MPs are angry. The change potentially requires a Commons vote, and there is no guarantee the government will win. This one, as they say, could run and run." thanks for listening. to help us out with the nonlinear library or to learn more, please visit nonlinear.org.
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: FTX EA Fellowships, published by FTX Foundation on the effective altruism forum. Announcing a new program: FTX EA Fellowships! FTX is a cryptocurrency exchange headquartered in the Bahamas, founded with the goal of making money to give to effective causes. We’re looking to support people doing exciting work kickstart an EA community in the Bahamas To those ends, we’re looking for applications from people already working on EA jobs or projects that can be done from the Bahamas. For fellowship recipients, we’ll provide: travel to and from the Bahamas housing in the Bahamas for up to 6 months an EA coworking space a stipend of $10,000 Round 1 applications close 11/15. We’ll get back with responses by 12/1, and accommodations will start in January. This is just an initial default schedule: happy to accept off-cycle applications or people who wouldn’t be able to move until later as well. We plan to accept somewhere between 10-25 applicants in the first round, depending on interest and capacity constraints. The application is here. (If you don’t need a fellowship but might want to come hang out in the Bahamas, fill out this form.) We may follow up to do an interview over video chat after reviewing initial applications. If you have any questions feel free to email fellowships@ftx.com. thanks for listening. to help us out with the nonlinear library or to learn more, please visit nonlinear.org.
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Candy for Nets, published by Jeff_Kaufman on the effective altruism forum. Yesterday morning my five-year-old daughter was asking me about mosquitos, and we got on to talking about malaria, nets, and how Julia and I donate to the AMF to keep other kids from getting sick and potentially dying. Lily took it very seriously, and proposed that when I retire she take my programming job and donate in my place. I told her that she didn't need to wait until after I retired to start helping, and she decided she wanted to sell candy on the bike path as a fundraiser. I told her we could do this after naps if the weather was still nice, and the first thing she said when I got her up from her nap was that she wanted to go make a sign. She dictated to me, "Lily is selling candy to raise money for malaria nets, $1" and I wrote the letters. She colored them in: (It looks like she's posing with the sign here, but this is just how she happened to position herself for coloring. She has short arms.) Once Anna was up from her (longer) nap I got out the wagon and brought them over to the bike path. Lily did all the selling; I just hung out to the side, leaning against a tree. She's always been good at talking to adults, and did a good job selling the candy. She would explain that the candy was $1/each, that the money was going to buy malaria nets, and that malaria was a very bad disease that you got from mosquitoes. People were generous, and several people gave without taking candy, or put in an extra dollar. One person didn't have cash but wanted to give enough that they went home and came back with a dollar. As someone who grew up in a part of town with very little foot traffic, the idea that you can just walk a short distance from your house to somewhere where several people will pass per minute continually amazes me. After about twenty minutes all the candy was sold and Lily had collected $20.75. She played in the park for a while, and then when we came home she asked how we would use the money to buy nets. I showed her pictures of distributions on the AMF website but she wanted to see pictures of the nets in use so we spent a while on image search: I explained that we weren't going to distribute the nets ourselves, but that we would provide the money so other people could. Initially she didn't want to donate the whole amount, but wanted to set aside half to buy more candy so she could do this again. I told her that I would be happy to buy the candy. Possibly I should have let her manage this herself, but I was worried that the money wouldn't end up donated which wouldn't have been fair to the people who'd bought the candy, and explained this to her. She gave me the $20.75 and I used my credit card to pay for the nets. [1] Here's the message she dictated for the donation: I want people to be safe in the world from biting mosquitoes. I don't want them getting hurt, and especially I don't want the kids like me to die. I don't know how her relationship with altruism will change as she gets older, and I do think there are ways it will be hard for her to have parents who have strong unusual views. As we go I'm going to continue to try very hard not to pressure or manipulate her, while still giving advice and helping her explore her motivations here. I am, however, very proud of her today. [1] I haven't listed this on our donations page and it doesn't count it towards our 50% goal because the donation was Lily's and not ours. thanks for listening. to help us out with the nonlinear library or to learn more, please visit nonlinear.org.
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Listen to more EA content with The Nonlinear Library, published by Kat Woods on the effective altruism forum. Listen here: Spotify, Google Podcasts, Pocket Casts, Apple. Or, just search for "Nonlinear Library" in your preferred podcasting app. We are excited to announce the launch of The Nonlinear Library, which allows you to easily listen to top EA content on your podcast player. We use text-to-speech software to create an automatically updating repository of audio content from the EA Forum, Alignment Forum, LessWrong, and other EA blogs. In the rest of this post, we’ll explain our reasoning for the audio library, why it’s useful, why it’s potentially high impact, its limitations, and our plans. You can read it here or listen to the post in podcast form here. Goal: increase the number of people who read EA research An EA koan: if your research is high quality, but nobody reads it, does it have an impact? Generally speaking, the theory of change of research is that you investigate an area, come to better conclusions, people read those conclusions, they make better decisions, all ultimately leading to a better world. So the answer is no. Barring some edge cases (1), if nobody reads your research, you usually won’t have any impact. Research → Better conclusion → People learn about conclusion → People make better decisions → The world is better Nonlinear is working on the third step of this pipeline: increasing the number of people engaging with the research. By increasing the total number of EA articles read, we’re increasing the impact of all of that content. This is often relatively neglected because researchers typically prefer doing more research instead of promoting their existing output. Some EAs seem to think that if their article was promoted one time, in one location, such as the EA Forum, then surely most of the community saw it and read it. In reality, it is rare that more than a small percentage of the community will read even the top posts. This is an expected-value tragedy, when a researcher puts hundreds of hours of work into an important report which only a handful of people read, dramatically reducing its potential impact. Here are some purely hypothetical numbers just to illustrate this way of thinking: Imagine that you, a researcher, have spent 100 hours producing outstanding research that is relevant to 1,000 out of a total of 10,000 EAs. Each relevant EA who reads your research will generate $1,000 of positive impact. So, if all 1,000 relevant EAs read your research, you will generate $1 million of impact. You post it to the EA Forum, where posts receive 500 views on average. Let’s say, because your report is long, only 20% read the whole thing - that’s 100 readers. So you’ve created 1001,000 = $100,000 of impact. Since you spent 100 hours and created $100,000 of impact, that’s $1,000 per hour - pretty good! But if you were to spend, say 1 hour, promoting your report - for example, by posting links on EA-related Facebook groups - to generate another 100 readers, that would produce another $100,000 of impact. That’s $100,000 per marginal hour or ~$2,000 per hour taking into account the fixed cost of doing the original research. Likewise, if another 100 EAs were to listen to your report while commuting, that would generate an incremental $100,000 of impact - at virtually no cost, since it’s fully automated. In this illustrative example, you’ve nearly tripled your cost-effectiveness and impact with one extra hour spent sharing your findings and having a public system that turns it into audio for you. Another way the audio library is high expected value is that instead of acting as a multiplier on just one researcher or one organization, it acts as a multiplier on nearly the entire output of the EA research community. This allows for two benefits: long...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: 2019 AI Alignment Literature Review and Charity Comparison , published by Larks on the effective altruism forum. Cross-posted to LessWrong here. Introduction As in 2016, 2017 and 2018, I have attempted to review the research that has been produced by various organisations working on AI safety, to help potential donors gain a better understanding of the landscape. This is a similar role to that which GiveWell performs for global health charities, and somewhat similar to a securities analyst with regards to possible investments. My aim is basically to judge the output of each organisation in 2019 and compare it to their budget. This should give a sense of the organisations' average cost-effectiveness. We can also compare their financial reserves to their 2019 budgets to get a sense of urgency. I’d like to apologize in advance to everyone doing useful AI Safety work whose contributions I may have overlooked or misconstrued. As ever I am painfully aware of the various corners I have had to cut due to time constraints from my job, as well as being distracted by 1) another existential risk capital allocation project, 2) the miracle of life and 3) computer games. How to read this document This document is fairly extensive, and some parts (particularly the methodology section) are the same as last year, so I don’t recommend reading from start to finish. Instead, I recommend navigating to the sections of most interest to you. If you are interested in a specific research organisation, you can use the table of contents to navigate to the appropriate section. You might then also want to Ctrl+F for the organisation acronym in case they are mentioned elsewhere as well. If you are interested in a specific topic, I have added a tag to each paper, so you can Ctrl+F for a tag to find associated work. The tags were chosen somewhat informally so you might want to search more than one, especially as a piece might seem to fit in multiple categories. Here are the un-scientifically-chosen hashtags: Agent Foundations AI_Theory Amplification Careers CIRL Decision_Theory Ethical_Theory Forecasting Introduction Misc ML_safety Other_Xrisk Overview Philosophy Politics RL Security Shortterm Strategy New to Artificial Intelligence as an existential risk? If you are new to the idea of General Artificial Intelligence as presenting a major risk to the survival of human value, I recommend this Vox piece by Kelsey Piper. If you are already convinced and are interested in contributing technically, I recommend this piece by Jacob Steinheart, as unlike this document Jacob covers pre-2019 research and organises by topic, not organisation. Research Organisations FHI: The Future of Humanity Institute FHI is an Oxford-based Existential Risk Research organisation founded in 2005 by Nick Bostrom. They are affiliated with Oxford University. They cover a wide variety of existential risks, including artificial intelligence, and do political outreach. Their research can be found here. Their research is more varied than MIRI's, including strategic work, work directly addressing the value-learning problem, and corrigibility work. In the past I have been very impressed with their work. Research Drexler's Reframing Superintelligence: Comprehensive AI Services as General Intelligence is a massive document arguing that superintelligent AI will be developed for individual discrete services for specific finite tasks, rather than as general-purpose agents. Basically the idea is that it makes more sense for people to develop specialised AIs, so these will happen first, and if/when we build AGI these services can help control it. To some extent this seems to match what is happening - we do have many specialised AIs - but on the other hand there are teams working directly on AGI, and often in ML 'build an ML system that does it...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: What will 80,000 Hours provide (and not provide) within the effective altruism community?, published by Benjamin_Todd on the effective altruism forum. There are many career services that would be useful to the effective altruism community, and unfortunately 80,000 Hours is not able to provide them all. In this post, I aim to sum up what we intend to provide and what we can’t, to make it easier for other groups to fill these gaps. 80,000 Hours’ online content is also serving as one of the most common ways that people get introduced to the effective altruism community, but we’re not the ideal introduction for many types of people, which I also list in the section on online articles. You can see our full plans in our annual review . Target audience Our aim is to do the most we can to fill the key skill gaps in the world’s most pressing problems. We think that is the best way we can help to improve the lives of others over the long term. We think that the best way to do this is – given our small team – to initially specialise on a single target audience, and gradually expand the audience over time. Given this, most of our effort (say 50%+) is on advice and support for English-speaking people age 20-35 who might be able to enter one of our current priority paths (say a 5%+ chance of success). We also aim to put ~30% of our effort into other ways of addressing our priority problems (AI, biorisk, global priorities research, building EA, nuclear security, improving institutional decision-making, extreme climate risks) or potential priority problems , some of which we might class as priority paths in the future. 20% of our effort goes into a wider range of roles and problem areas. (Edit: note that this allocation is in line with the views of EA Forum members and other proxies for 'core' EA community members.) We think a wider range of people could consider our priority paths than is often assumed. For instance, some people have worried that this is aimed at too narrow an audience, say, people who attended one of the best 20 universities in the world. But one of our top paths is ‘AI policy’; we take this to include some junior roles in government and politics, and many people take these roles who haven’t attended a top 20 university. Another priority path is working at EA organisations, and the latest EA survey found that about half of the staff at those organisations did not attend a top 20 university. We also aim to be useful to a broader range of readers than those who might pursue a priority path – as I’ll explain later – and we think much of our content is indeed relevant to them. Still, this audience is clearly much narrower than everyone we’d like to get involved in effective altruism, and everyone already within effective altruism who could benefit from help with their career. We also intend to expand the scope of this audience over time as our team grows (especially by extending the age range we focus on), though this will proceed gradually over a matter of years. This means we need other groups to focus on other audiences. Some of the bigger gaps include: People interested in problem areas pursued by those focused on near-term impacts, such as global health and factory farming; we don’t include career paths in these areas within our priority paths. People who would prefer materials written in a language that’s not English, and those who want career advice specific to non-English speaking countries, especially outside the US and UK. People older than 35, and especially over 40. People younger than 20, and especially under 18. People who are looking for advice on where to donate, or want to do part-time advocacy, but don't want to significantly change their careers. People who could make an impactful career change but not within our priority paths or nearby options. Ri...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Things I Learned at the EA Student Summit, published by Akash on the effective altruism forum. This weekend, I attended the EA Student Summit. Below, I’m summarizing some of my “key takeaways”—ideas that I found interesting, helpful, or thought-provoking. I’m dividing them into a few key themes and questions: How to Learn About EA How can we effectively learn about EA? Will Payne had some helpful suggestions, summarized below: We don’t need to reinvent the wheel—there are already a lot of resources (and curated libraries of resources) out there. Oxford’s EA Introductory Fellowship reading list seems like a great place to start. We should be explicit about updating our beliefs. If we change our mind about something, it’s useful for us to document it and share it with others. We should strive to learn more effortfully. Will pointed out that it’s usually not enough to passively read an article or listen to a podcast—we’re more likely to remember information and benefit from it if we learn in more effortful ways. Some examples include summarizing an article in your own words, asking yourself reflection questions (and then answering them), or explaining an idea to others. This forum post is another example :) Will’s talk also had one of my favorite suggestions from the summit. Instead of saying “I found this article interesting because it was about X”, Will suggests that we say “I found this article interesting because it suggests that we should do Y.” I think this is extremely clever, for at least two reasons. First, I think it makes the person that we’re talking to more motivated and energized about the topic. There are thousands of interesting articles about interesting topics, but there are very few that directly try to make me think or act differently. Second, I think it helps us recognize when things aren’t actually helpful. It’s easy to get lost thinking about interesting ideas that don’t actually have any impact on the choices we make. By asking “does this suggest that I should do something different or think about something differently?”, we might save ourselves a lot of time. EA Resources that I Didn't Know About I learned about a few useful EA resources: The Center for Effective Altruism has a media specialist and a licensed social worker who serves as the EA community liaison. Anyone can contact them. Yes, that means you. Or me. Part of their job is literally to help us think, feel, and communicate better. Aaron Gertler, who runs the EA forum, is willing to read/edit any potential forum posts. Giving What We Can has a list of content ideas for blog posts. These are just a few that I’ve learned about recently— I’m sure there are many more. This post from a few weeks ago has a more thorough list of EA-related organizations. How often should you reach out to EAs and EA-related organizations? I have an immense amount of respect for other EAs. These are literally people who are devoting their lives toward solving the world’s biggest problems and finding the most effective ways to spend their time and money. So naturally, I thought that these people—especially the “big name” people—would have far better things to do with their time than talk to me. I need to wait until I have a really impressive idea before I request the time of other EAs—I could distract them from discovering the next highly effective charity or the solution to AI safety! Nearly all of my experiences at the summit went against this idea. People wanted to talk to me, and others, about raw, unpolished ideas. Almost every EA I spoke to—including the “big names”—seemed authentically and intrinsically motivated to talk to students about their interests and ideas. I honestly think this was my biggest surprise of the conference—there are so many EAs who would genuinely like to talk to you. Now, there’s al...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Why I am probably not a longtermist, published by Denise_Melchin on the effective altruism forum. tl;dr: I am much more interested in making the future good, as opposed to long or big, as I neither think the world is great now nor am convinced it will be in the future. I am uncertain whether there are any scenarios which lock us into a world at least as bad as now that we can avoid or shape in the near future. If there are none, I think it is better to focus on “traditional neartermist” ways to improve the world. I thought it might be interesting to other EAs why I do not feel very on board with longtermism, as longtermism is important to a lot of people in the community. This post is about the worldview called longtermism. It does not describe a position on cause prioritisation. It is very possible for causes commonly associated with longtermism to be relevant under non-longtermist considerations. I structured this post by crux and highlighted what kind of evidence or arguments would convince me that I am wrong, though I am keen to hear about others which I might have missed! I usually did not investigate my cruxes thoroughly. Hence, only ‘probably’ not a longtermist. The quality of the long-term future 1. I find many aspects of utilitarianism uncompelling. You do not need to be a utilitarian to be a longtermist. But I think depending on how and where you differ from total utiliarianism, you will probably not go ‘all the way’ to longtermism. I very much care about handing the world off in a good state to future generations. I also care about people’s wellbeing regardless of when it happens. What I value less than a total utilitarian is bringing happy people into existence who would not have existed otherwise. This means I am not too fussed about humanity’s failure to become much bigger and spread to the stars. While creating happy people is valuable, I view it as much less valuable than making sure people are not in misery. Therefore I am not extremely concerned about the lost potential from extinction risks (but I very much care about its short-term impact), although that depends on how good and long I expect the future to be (see below). What would convince me otherwise: I not only care about pursuing my own values, but I would like to ensure that other people’s reflected values are implemented. For example, if it turned out that most people in the world really care about increasing the human population in the long term, I would prioritise it much more. However I am a bit less interested in the sum of individual preferences, but more the preferences of a wide variety of groups. This is to give more weight to rarer worldviews as well as not rewarding one group outbreeding the other or spreading their values in an imperialist fashion. I also want to give the values of people who are suffering the most more weight. If they think the long-term future is worth prioritising over their current pain, I would take this very seriously. Alternatively, convincing me of moral realism and the correctness of utilitarianism within that framework would also work. So far I have not seen a plain language explanation of why moral realism makes any sense, but it would probably be a good start. If the world suddenly drastically improved and everyone had as good a quality of life as my current self, I would be happy to focus on making the future big and long instead of improving people’s lives. 2. I do not think humanity is inherently super awesome. A recurring theme in a lot of longtermist worldviews seems to be that humanity is wonderful and should therefore exist for a long time. I do not consider myself a misanthrope, I expect my views to be average for Europeans. Humanity has many great aspects which I like to see thrive. But I find the overt enthusiasm for humanity most longtermis...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: We need alternatives to Intro EA Fellowships, published by Ashley Lin on the effective altruism forum. Thanks to Kuhan Jeyapragasan, Akash Wasil, Olivia Jimenez, and Lizka Vaintrob for helpful comments / conversations. TLDR: I think group organizers have become anchored on the idea of Intro EA Fellowships as 8-week small-group things, which might actually be a sub-optimal way to introduce promising students to the EA world. We need new alternatives that are exciting, immersive, and enable EA-interested students to move as quickly as they’d like through the EA funnel. The Intro EA Fellowship (also known as the Arete Fellowship) is a program where a small group of fellows and a facilitator meet multiple times to learn about some aspect of effective altruism. Stanford EA’s virtual Intro EA Fellowship was the first structured EA program I was part of and when I realized EA was a thriving community with real humans in it. I don’t think my experience is unique. In uni EA groups around the world, the Intro EA Fellowship is one of the core programs offered to students. Some context on Intro EA Fellowships: Fellowships are usually structured in cohorts of 2-5 fellows and a facilitator who meets weekly for 6-10 weeks. Each week, fellows do some amount of readings and participate in a discussion with their cohort. There are often also social activities that allow fellows to get to know each other better and cultivate friendships. Uni group organizers often use Intro EA Fellowships as an early/mid part of the funnel for highly-engaged EA students. Intro EA Fellowships exist in so many places because they have some upsides, some of which I list below. That said, I also think there are some strong downsides to the Intro EA Fellowship model as it currently exists. As a participant, I wasn’t particularly impressed by my Intro EA Fellowship experience -- I’m not sure if my fellowship cohort actually finished (people got busy) and think there’s a chance I would’ve bounced off the EA community had I not attended a summer EA retreat for high school students a couple months later. Now, as I help organize Penn EA’s Intro Fellowship cohort, I’m noticing how my frustrations as an Intro Fellowship participant weren’t unique to me. In this post, I share some of those frustrations (downsides to the Intro Fellowship as I see them). I try to steelman the argument for why Intro EA fellowships should exist. Finally, I introduce some Intro EA Fellowship alternatives that I'd be excited to see uni group organizers prototype. I’m personally planning to try some of these -- if you’d like to coordinate, please reach out ashley11@wharton.upenn.edu! Downsides of Intro Fellowships Much of this is observed through my own experience being part of / facilitating fellowships. I also think Intro Fellowship experiences are highly variable depending on one’s cohort and facilitator, and I think there’s a good chance I’ve had a relatively worse Intro EA Fellowship experience than others: The standard 8-week fellowship timeline is too slow for people who are really excited early on and want to move faster. In these scenarios, the fellowship might actually slow people down and cause their excitement to fade (an hour-long conversation and some readings each week is a pretty sluggish pace) -- worse case scenario, it might cause some promising people to lose interest. I want to cultivate a fast-paced vibe among fellows, instead of a discussion-group like vibe. (To me “fast-paced,” when applied to something that seems interesting, cultivates genuine excitement and deep curiosity). For example, when I first found 80,000 Hours, I pulled an all-nighter reading it and was absolutely ecstatic that people had spent so much time thinking about triaging problems and how one can do the most good in the world. In my early EA days...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: 500 Million, But Not A Single One More, published by jai on the effective altruism forum. This is a linkpost for http://blog.jaibot.com/?p=413 We will never know their names. The first victim could not have been recorded, for there was no written language to record it. They were someone’s daughter, or son, and someone’s friend, and they were loved by those around them. And they were in pain, covered in rashes, confused, scared, not knowing why this was happening to them or what they could do about it — victims of a mad, inhuman god. There was nothing to be done — humanity was not strong enough, not aware enough, not knowledgeable enough, to fight back against a monster that could not be seen. It was in Ancient Egypt, where it attacked slave and pharaoh alike. In Rome, it effortlessly decimated armies. It killed in Syria. It killed in Moscow. In India, five million dead. It killed a thousand Europeans every day in the 18th century. It killed more than fifty million Native Americans. From the Peloponnesian War to the Civil War, it slew more soldiers and civilians than any weapon, any soldier, any army. (Not that this stopped the most foolish and empty souls from attempting to harness the demon as a weapon against their enemies.) Cultures grew and faltered, and it remained. Empires rose and fell, and it thrived. Ideologies waxed and waned, but it did not care. Kill. Maim. Spread. An ancient, mad god, hidden from view, that could not be fought, could not be confronted, could not even be comprehended. Not the only one of its kind, but the most devastating. For a long time, there was no hope — only the bitter, hollow endurance of survivors. In China, in the 10th century, humanity began to fight back. It was observed that survivors of the mad god’s curse would never be touched again: They had taken a portion of that power into themselves, and were so protected from it. Not only that, but this power could be shared by consuming a remnant of the wounds. There was a price, for you could not take the god’s power without first defeating it — but a smaller battle, on humanity’s terms. By the 16th century, the technique spread to India, then across Asia, the Ottoman Empire and, in the 18th century, Europe. In 1796, a more powerful technique was discovered by Edward Jenner. An idea began to take hold: Perhaps the ancient god could be killed. A whisper became a voice; a voice became a call; a call became a battle cry, sweeping across villages, cities, nations. Humanity began to cooperate, spreading the protective power across the globe, dispatching masters of the craft to protect whole populations. People who had once been sworn enemies joined in a common cause for this one battle. Governments mandated that all citizens protect themselves, for giving the ancient enemy a single life would put millions in danger. And, inch by inch, humanity drove its enemy back. Fewer friends wept; fewer neighbors were crippled; fewer parents had to bury their children. At the dawn of the 20th century, for the first time, humanity banished the enemy from entire regions of the world. Humanity faltered many times in its efforts, but there were individuals who never gave up, who fought for the dream of a world where no child or loved one would ever fear the demon ever again. Viktor Zhdanov, who called for humanity to unite in a final push against the demon; the great tactician Karel Raška, who conceived of a strategy to annihilate the enemy; Donald Henderson, who led the efforts in those final days. The enemy grew weaker. Millions became thousands, thousands became dozens. And then, when the enemy did strike, scores of humans came forth to defy it, protecting all those whom it might endanger. The enemy’s last attack in the wild was on Ali Maow Maalin, in 1977. For months afterwards, dedicated humans swep...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Yale EA’s Fellowship Application Scores were not Predictive of Eventual Engagement, published by ThomasWoodside, jessica_mccurdy on the effective altruism forum. Written by Jessica McCurdy and Thomas Woodside Overview Yale has been one of the only groups in the past advocating for a selective fellowship. However, after we noticed a couple instances of people who had barely been accepted to the fellowship becoming extremely engaged with the group, we decided to do an analysis of our scoring of applications and eventual engagement. We found no correlation. We think this shows the possibility that some of the people we have rejected in the past could have become extremely engaged members, which seems like a lot of missed value. We are still doing more analysis using different metrics and methods. For now we are tentatively recommending that groups do not follow our previous advice about being selective if they have the capacity to take on more fellows. We recommend either guaranteeing future acceptance to those over a baseline or encouraging applicants to apply to EA virtual programs if limited by capacity. This is not to say that there is no good way of selecting fellows but rather that ours in particular was not effective. Rationale for Being Selective & Relevant Updates These have been our reasons for being selective in the past and our updated thoughts Only the most excited applicants participate (less engaged fellows who have poor attendance or involvement can set unwanted norms) By emphasizing the time commitment in the interviews and making it easy for applicants to postpone doing the fellowship hopefully we will self select for this. Fellows are incentivized show up and be actively engaged (since they know they are occupying a spot another person did not receive) The application and interview process alone should create the feeling of selectiveness even if we don’t end up being that selective. We only need a few moderators that we are confident will be friendly, welcoming, and knowledgeable about EA We were lucky enough to have several previous fellows who fit this description. Now that there is training available for facilitators we hope to skill up new ones quickly. We made it a lot easier to become and be a facilitator by separating that role from the organizers role. We create a stronger sense of community amongst Fellows This is still a concern Each Fellow can receive an appropriate amount of attention since organizers get to know each one individually This is still a concern though in the past Fellowship organizers were also taking on many different roles and now we have one person now whose only role is to manage the fellowship. We don’t strain our organizing capacity and can run the Fellowship more smoothly This is still a concern but the previous point also applies here Overall, we still think these are good and important reasons for keeping the fellowship smaller. However, we are currently thinking that the possibility of rejecting an applicant who would have become really involved outweighs these concerns. Although, there is an argument to be made that these people would have found a way to be involved anyways. How we Measured Engagement and Why we Chose it How we measured it We brainstormed ways of being engaged with the group and estimated a general ranking for them. We ended up with: Became YEA President > Joined YEA Exec > Joined the Board OR Became a regular attendee of events and discussion groups OR Became a mentor (after graduating) > Became a Fellowship Facilitator (who is not also on the board) OR Did the In-Depth Fellowship > Became a top recruiter for the Fellowship OR Had multiple 1-1 outside of the fellowship OR Asked to be connected to the EA community in their post- graduation location OR Attended the Student Summit > Came to at least ...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Long-Term Future Fund: April 2019 grant recommendations, published by Habryka on the effective altruism forum. Please note that the following grants are only recommendations, as all grants are still pending an internal due diligence process by CEA. This post contains our allocation and some explanatory reasoning for our Q1 2019 grant round. We opened up an application for grant requests earlier this year which was open for about one month, after which we received an unanticipated large donation of about $715k. This caused us to reopen the application for another two weeks. We then used a mixture of independent voting and consensus discussion to arrive at our current grant allocation. What is listed below is only a set of grant recommendations to CEA, who will run these by a set of due-diligence tests to ensure that they are compatible with their charitable objectives and that making these grants will be logistically feasible. Grant Recipients Each grant recipient is followed by the size of the grant and their one-sentence description of their project. Anthony Aguirre ($70,000): A major expansion of the Metaculus prediction platform and its community Tessa Alexanian ($26,250): A biorisk summit for the Bay Area biotech industry, DIY biologists, and biosecurity researchers Shahar Avin ($40,000): Scaling up scenario role-play for AI strategy research and training; improving the pipeline for new researchers Lucius Caviola ($50,000): Conducting postdoctoral research at Harvard on the psychology of EA/long-termism Connor Flexman ($20,000): Performing independent research in collaboration with John Salvatier Ozzie Gooen ($70,000): Building infrastructure for the future of effective forecasting efforts Johannes Heidecke ($25,000): Supporting aspiring researchers of AI alignment to boost themselves into productivity David Girardo ($30,000): A research agenda rigorously connecting the internal and external views of value synthesis Nikhil Kunapuli ($30,000): A study of safe exploration and robustness to distributional shift in biological complex systems Jacob Lagerros ($27,000): Building infrastructure to give X-risk researchers superforecasting ability with minimal overhead Lauren Lee ($20,000): Working to prevent burnout and boost productivity within the EA and X-risk communities Alex Lintz ($17,900): A two-day, career-focused workshop to inform and connect European EAs interested in AI governance Orpheus Lummis ($10,000): Upskilling in contemporary AI techniques, deep RL, and AI safety, before pursuing a ML PhD Vyacheslav Matyuhin ($50,000): An offline community hub for rationalists and EAs Tegan McCaslin ($30,000): Conducting independent research into AI forecasting and strategy questions Robert Miles ($39,000): Producing video content on AI alignment Anand Srinivasan ($30,000): Formalizing perceptual complexity with application to safe intelligence amplification Alex Turner ($30,000): Building towards a “Limited Agent Foundations” thesis on mild optimization and corrigibility Eli Tyre ($30,000): Broad project support for rationality and community building interventions Mikhail Yagudin ($28,000): Giving copies of Harry Potter and the Methods of Rationality to the winners of EGMO 2019 and IMO 2020 CFAR ($150,000): Unrestricted donation MIRI ($50,000): Unrestricted donation Ought ($50,000): Unrestricted donation Total distributed: $923,150 Grant Rationale Here we explain the purpose for each grant and summarize our reasoning behind their recommendation. Each summary is written by the fund member who was most excited about recommending the relevant grant (plus some constraints on who had time available to write up their reasoning). These differ a lot in length, based on how much available time the different fund members had to explain their reasoning. Writeups by Helen Toner Al...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: When can I eat meat again?, published by clairey on the effective altruism forum. By Claire Yip, co-founder of Cellular Agriculture UK. These views are my own. Summary Timeline: When we can expect highly similar cost-competitive alternatives to animal products Timeline There is a lot of uncertainty around when we will be able to eat meat grown from cells, and how we should divide our efforts between that, plant-based alternatives, and other forms of animal advocacy. This post seeks to give sensible, unbiased views on the future of alternative proteins. However, these views are uncertain too: I have c.40-60% confidence. These estimates are not set in stone. Factors like investment and activity would quicken progress, but things will also probably take longer than we expect, for unexpected reasons, and we don’t know everything that we don’t know. These are estimates for cost-competitive alternatives. We will be able to buy these products earlier than this. In the next 5-10 years, expect to see plant-based versions of processed meats become more widespread and delicious. Yay, chicken nuggets! You’re also in luck if you want plant-based or animal-free scrambled eggs, omelettes, milk, cream, yoghurt, or whey protein powder. These plant-based products will get even better in the next 10-20 years, especially as they’re blended e.g. with collagen (produced without animals), or real meat cultivated from cells. Decent animal-free butter, cheese, and whole egg products might become a reality! Pet food produced from animal and microorganism cells will also be more easily available. If you want to eat unprocessed whole meat like bacon or sashimi without hurting too many animals or blowing your grocery budget, it looks like you’ll have to wait a few decades (30-50 years). My time estimates are mostly based on private conversations with plant-based and cellular agriculture companies, at conferences and through writing a report on low-cost cell culture media for the Good Food Institute, as well as my understanding of the technical progress needed for each technology. However, my views do not represent those of GFI. Actions you can take Donors: If you want to donate to this space, promising recipients are the Good Food Institute and New Harvest (for open access research into cellular and acellular agriculture specifically). Farmed Animal Funders has highly tentative suggestions on how philanthropists might allocate donations/funding to plant-based alternatives. If you want to work in this space: Most companies are hungry for scientific and engineering talent and will continue to hire. Relevant disciplines/skills for plant-based meat include: biochemistry, food science, plant biology, chemical engineering. Relevant disciplines/skills for a/cellular agriculture include: biochemistry, food science, plant biology, chemical engineering, tissue engineering, synthetic biology, bioreactor engineering, cell culture. Software engineering will probably become more useful in automation and computational modelling. Experience required varies: some ask for a few years of experience in a lab while others may only hire PhDs. There are more job openings at plant-based companies, although public interest is peaking, so competition is also high (so replaceability might be a concern). These are hugely varied, from working on production lines to operations, HR, data science, etc. Non-scientific roles at acellular and cellular agriculture companies will be more widely available as they approach commercialisation, in 3-5 years. CellAgri, GFI, and 80,000 Hours maintain lists of job opportunities. Students: GFI has a guide for students which contains career profiles. They also have quarterly career calls. Researchers/scientists: Academic research seems valuable, partly because it is often open access while s...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Introducing LEEP: Lead Exposure Elimination Project, published by Jack, LuciaC on the effective altruism forum. We are excited to announce the launch of Lead Exposure Elimination Project (LEEP), a new EA organisation incubated by Charity Entrepreneurship. Our mission is to reduce lead poisoning, which causes significant disease burden worldwide. We aim to achieve this by advocating for lead paint regulation in countries with large and growing burdens of lead poisoning from paint. In this post, we make the case for lead exposure reduction as a priority, and outline our plan to address this problem. The Problem Others in the effective altruism community have already identified that working on lead poisoning could be a high-impact opportunity (see here, here, and here). Through the Importance, Tractability, Neglectedness framework, we unpack the reasoning for prioritising lead exposure interventions, and for our approach of advocating for the introduction of lead paint laws. Importance Lead poisoning has substantial health and economic costs, and lead paint is a primary contributor [1]. In terms of individual impacts, lead exposure has a number of effects. Even a low level of lead exposure can lead to mental disability and IQ loss, as well as increased rates of mental illness and psychopathology and significantly reduced lifetime earnings capacity [2, 3, 4]. Lead also has effects on behaviour and criminal tendencies; in particular having a large impact on the prevalence of violent crime [5]. In adults, lifetime lead exposure is an important risk factor for renal disease and cardiovascular disease, including hypertension and coronary artery disease [6, 7]. Higher levels of exposure can affect all organ systems, and even result in respiratory difficulties, seizure, coma, and death [5]. Lead poisoning primarily affects children, and does so at a massive scale. UNICEF reports that 815 million children have blood lead levels above 5 µg/dL - a sufficient level for neurodevelopmental effects and reduced IQ [8]. The vast majority live in low and middle-income countries. Put another way, one in three children are currently affected by lead poisoning to some degree. In addition to disability, it also causes 1 million deaths per year. In total, lead poisoning accounts for 22 million DALYs every year, which means that lead poisoning is responsible for approximately 1% of the global disease burden [9]. In terms of lost earnings, lead poisoning impacts the world economy to the level of approximately $1 trillion per year [4]. This amounts to a loss of 1.2% of world GDP. These losses are concentrated in low and middle-income countries, where they can amount to as much as 5-8% of GDP, suggesting that lead exposure can be a significant barrier to economic development and poverty reduction. In short, the problem of lead poisoning is a significant one. Neglectedness At present, while all countries except for one have banned leaded petrol, 61% of countries have no lead paint regulations whatsoever [1]. In many of these primarily low and middle-income countries the burden of disease from lead poisoning is still significant. In high-income countries, this is a less severely neglected area, as most countries have introduced regulations banning leaded petrol and lead paint. While there are some organisations working to address this issue in low and middle-income countries, including IPEN, ToxicsLink, and Pure Earth, many countries with significant lead burdens remain neglected by other actors. LEEP aims to fill this gap, and target these neglected countries. Tractability This is the most uncertain aspect of working on lead poisoning, given the uncertainty around the success of policy change interventions. However, there are several reasons in favour of the tractability of policy change to ban t...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: 2020 AI Alignment Literature Review and Charity Comparison, published by Larks on the effective altruism forum. Write a Review cross-posted to LW here. Introduction As in 2016, 2017, 2018, and 2019, I have attempted to review the research that has been produced by various organisations working on AI safety, to help potential donors gain a better understanding of the landscape. This is a similar role to that which GiveWell performs for global health charities, and somewhat similar to a securities analyst with regards to possible investments. My aim is basically to judge the output of each organisation in 2020 and compare it to their budget. This should give a sense of the organisations' average cost-effectiveness. We can also compare their financial reserves to their 2021 budgets to get a sense of urgency. I’d like to apologize in advance to everyone doing useful AI Safety work whose contributions I have overlooked or misconstrued. As ever I am painfully aware of the various corners I have had to cut due to time constraints from my job, as well as being distracted by 1) other projects, 2) the miracle of life and 3) computer games. This article focuses on AI risk work. If you think other causes are important too, your priorities might differ. This particularly affects GCRI, FHI and CSER, who both do a lot of work on other issues which I attempt to cover but only very cursorily. How to read this document This document is fairly extensive, and some parts (particularly the methodology section) are largely the same as last year, so I don’t recommend reading from start to finish. Instead, I recommend navigating to the sections of most interest to you. If you are interested in a specific research organisation, you can use the table of contents to navigate to the appropriate section. You might then also want to Ctrl+F for the organisation acronym in case they are mentioned elsewhere as well. Papers listed as ‘X researchers contributed to the following research lead by other organisations’ are included in the section corresponding to their first author and you can Cntrl+F to find them. If you are interested in a specific topic, I have added a tag to each paper, so you can Ctrl+F for a tag to find associated work. The tags were chosen somewhat informally so you might want to search more than one, especially as a piece might seem to fit in multiple categories. Here are the un-scientifically-chosen hashtags: AgentFoundations Amplification Capabilities Corrigibility DecisionTheory Ethics Forecasting GPT-3 IRL Misc NearAI OtherXrisk Overview Politics RL Strategy Textbook Transparency ValueLearning New to Artificial Intelligence as an existential risk? If you are new to the idea of General Artificial Intelligence as presenting a major risk to the survival of human value, I recommend this Vox piece by Kelsey Piper, or for a more technical version this by Richard Ngo. If you are already convinced and are interested in contributing technically, I recommend this piece by Jacob Steinheart, as unlike this document Jacob covers pre-2019 research and organises by topic, not organisation, or this from Critch & Krueger, or this from Everitt et al, though it is a few years old now Research Organisations FHI: The Future of Humanity Institute FHI is an Oxford-based Existential Risk Research organisation founded in 2005 by Nick Bostrom. They are affiliated with Oxford University. They cover a wide variety of existential risks, including artificial intelligence, and do political outreach. Their research can be found here. Their research is more varied than MIRI's, including strategic work, work directly addressing the value-learning problem, and corrigibility work - as well as work on other Xrisks. They run a Research Scholars Program, where people can join them to do research at FHI. There is a f...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: EA Forum Creative Writing Contest: $22,000 in prizes for good stories, published by Aaron Gertler on the effective altruism forum. Update: The contest is now closed! All submissions made by 11:59 PST on Friday, October 29 will be considered. This includes a few posts whose authors had trouble submitting, but contacted me about before the deadline. Stories are a key part of how EA has grown since its beginning. Some examples: The Drowning Child and the Expanding Circle, which probably did more to launch the EA movement than any other piece of writing Harry Potter and the Methods of Rationality, which introduced many readers to important ideas about good epistemics and AI risk 500 Million, But Not A Single One More, which has been read aloud in conference halls for hundreds of people and is one of the first essays in the EA Handbook The Fable of the Dragon-Tyrant, which seems to have been extremely influential for one of the world’s most prominent entrepreneurs (who has since given tens of millions of dollars to various EA-adjacent causes) There’s a lot of “rational fiction” out there — stories about people thinking clearly to solve problems. Many of those stories also incorporate EA themes. But they tend to reveal their ideas over dozens of chapters, making it hard for someone to pick up on those themes unless they’re willing to dedicate many hours of time. We’d like to see creative work that “gets to the point” quickly — stories that, in a single sitting, might inspire someone to find out more about effective altruism, whether that means the whole movement or a single idea/cause area/intervention. So we’re running a contest! We want to see you write or share stories and creative nonfiction with EA themes. And we’ve added prizes to sweeten the deal.[1] Notably, your work doesn’t have to use EA jargon or cover a popular cause area, as long as it gets across the core idea of "using evidence and reason to help others effectively". That said, it doesn't hurt if the work references popular EA topics in some way, or tries to directly inspire readers to find out more about EA. For example, HPMOR includes a note along the lines of “to learn what Harry knows, read the LessWrong Sequences”. We’d be happy to see stories that would justify the note “to learn what X knows, join a Virtual Program”.[2] What kinds of content can I submit? We’ll have two categories: Fictional stories, like “The Fable of the Dragon-Tyrant” Creative nonfiction, like “500 Million, But Not A Single One More” No need to include the category in your submission. What are the prizes? Update: CEA initially funded $10,000 in prizes. However, a generous donor (Owen Cotton-Barratt) added another $12,000. We’re now offering $22,000 in total prize money, with the following structure: First prize (among all entries): $10,000 Two second prizes: $3,000 each If first prize goes to a fiction entry, at least one second prize will go to a nonfiction entry, and vice-versa Four third prizes: $1,000 each Eight honorable mentions: $250 each What’s the deadline? Entries must be published on the EA Forum no later than 11:59 pm PST on Friday, October 29 (initial deadline extended by two weeks after a few people said it seemed short). If you’d like to be kind to the judges and let us space out our reading over time, you can publish earlier :-) How do I submit content? We recommend publishing your entry on the EA Forum and tagging it with Creative Writing Contest. We want lots of people to read and discuss your submissions — we think the Forum will be a really fun place if good stories start showing up. However, we won’t use upvotes or comments as part of our process for choosing a winner. If you'd strongly prefer not to publish the work for any reason (including the desire to submit it elsewhere), you can submit it through this f...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Survey on AI existential risk scenarios, published by SamClarke, Alexis Carlier, jonasschuett on the effective altruism forum. Cross-posted to LessWrong. Summary In August 2020, we conducted an online survey of prominent AI safety and governance researchers. You can see a copy of the survey at this link.[1] We sent the survey to 135 researchers at leading AI safety/governance research organisations (including AI Impacts, CHAI, CLR, CSER, CSET, FHI, FLI, GCRI, MILA, MIRI, Open Philanthropy and PAI) and a number of independent researchers. We received 75 responses, a response rate of 56%. The survey aimed to identify which AI existential risk scenarios[2] (which we will refer to simply as “risk scenarios”) those researchers find most likely, in order to (1) help with prioritising future work on exploring AI risk scenarios, and (2) facilitate discourse and understanding within the AI safety and governance community, including between researchers who have different views. In our view, the key result is that there was considerable disagreement among researchers about which risk scenarios are the most likely, and high uncertainty expressed by most individual researchers about their estimates. This suggests that there is a lot of value in exploring the likelihood of different AI risk scenarios in more detail, especially given the limited scrutiny that most scenarios have received. This could look like: Fleshing out and analysing the scenarios mentioned in this post which have received less scrutiny. Doing more horizon scanning or trying to come up with other risk scenarios, and analysing them. At this time, we are only publishing this abbreviated version of the results. We have a version of the full results that we may publish at a later date. Please contact one of us if you would like access to this, and include a sentence on why the results would be helpful or what you intend to use them for. We welcome feedback on any aspects of the survey. Motivation It has been argued that AI could pose an existential risk. The original risk scenarios were described by Nick Bostrom and Eliezer Yudkowsky. More recently, these have been criticised, and a number of alternative scenarios have been proposed. There has been some useful work exploring these alternative scenarios, but much of this is informal. Most pieces are only presented as blog posts, with neither the detail of a book, nor the rigour of a peer-reviewed publication. For further discussion of this dynamic, see work by Ben Garfinkel, Richard Ngo and Tom Adamczewski. The result is that it is no longer clear which AI risk scenarios experts find most plausible. We think this state of affairs is unsatisfactory for at least two reasons. First, since many of the proposed scenarios seem underdeveloped, there is room for further work analyzing them in more detail. But this is time-consuming and there are a wide range of scenarios that could be analysed, so knowing which scenarios leading experts find most plausible is useful for prioritising this work. Second, since the views of top researchers will influence the views of the broader AI safety and governance community, it is important to make the full spectrum of views more widely available. The survey is intended to be a first step in this direction. The survey We asked researchers to estimate the probability of five AI risk scenarios, conditional on an existential catastrophe due to AI having occurred. There was also a catch-all “other scenarios” option. These were the five scenarios we asked about, and the descriptions we gave in the survey: "Superintelligence" A single AI system with goals that are hostile to humanity quickly becomes sufficiently capable for complete world domination, and causes the future to contain very little of what we value, as described in “Superintelligenc...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: How can we make Our World in Data more useful to the EA community?, published by EdMathieu on the effective altruism forum. I work at Our World in Data, where we try to make research and data on the world's largest problems more accessible and understandable. I attended EA Global this past weekend, where I received very interesting input from many lovely people on potential improvements. But I thought it'd also be worth asking here to get wider feedback. I'm interested in all the following: Low-hanging 'data fruits': simple datasets or charts that you know to be readily available somewhere and that would add significant value, but that aren't already listed here. High-hanging fruits: things we could add to the website in the medium term with a lot more work (new subjects, larger datasets, data that needs a lot of cleaning, etc.) Imaginary fruits: what you'd like to see on OWID in your wildest dreams (e.g. global population projections to the year 10,000 under various scenarios). Thank you! thanks for listening. to help us out with the nonlinear library or to learn more, please visit nonlinear.org.
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Toby Ord’s ‘The Precipice’ is published!, published by matthew.vandermerwe on the effective altruism forum. Write a Review The Precipice: Existential Risk and the Future of Humanity is out today. I’ve been working on the book with Toby for the past 18 months, and I’m excited for everyone to read it. I think it has the potential to make a profound difference to the way the world thinks about existential risk. How to get it It's out in the UK on March 5 and US March 24 An audiobook, narrated by Toby himself, is out March 24 You can buy it on Amazon now, or at theprecipice.com/purchase You can download the opening chapters for free by signing up to the newsletter at www.theprecipice.com What you can do Read the book Talk about it with your friends and family, or share quotes you like on social media If you enjoy it, consider writing a review on Amazon or Goodreads Summary of the book Part One: The Stakes Toby places our time within the broad sweep of human history: showing how far humanity has come in 2,000 centuries, and where we might go if we survive long enough. He outlines the major transitions in our past—the Agricultural, Scientific, and Industrial Revolutions. Each is characterised by dramatic increases in our power over the natural world, and together they have yielded massive improvements in living standards. During the twentieth century, with the detonation of the atomic bomb, humanity entered a new era. We gained the power to destroy itself, without the wisdom to ensure that we don’t. This is the Precipice, and how we navigate this period will determine whether humanity has a long and flourishing future, or no future at all. Toby introduces the concept of existential risk—risks that threaten to destroy humanity’s longterm potential. He shows how the case for safeguarding humanity from these risks draws support from a range of moral perspectives. Yet it remains grossly neglected—humanity spends more each year on ice cream than we do on protecting our future. Part Two: The Risks Toby explores the science behind the risks we face. In Natural Risks, he considers threats from asteroids & comets, supervolcanic eruptions, and stellar explosions. He shows how we can use humanity’s 200,000 year history to place strict bounds on how high the natural risk could be. In Anthropogenic Risks, he looks at risks we have imposed on ourselves in the last century, from nuclear war, extreme climate change, and environmental damage. In Future Risks, he turns to threats that are on the horizon from emerging technologies, focusing in detail on engineered pandemics, unaligned artificial intelligence, and dystopian scenarios. Part Three: The Path Forward Toby surveys the risk landscape and gives his own estimates for each risk. He also provides tools for thinking about how they compare and combine, and for how to prioritise between risks. He estimates that nuclear war and climate change each pose more risk than all the natural risks combined, and that risks from emerging technologies are higher still. Altogether, Toby believes humanity faces a 1 in 6 change of existential catastrophe in the next century. He argues that it is in our power to end these risks today, and to reach a place of safety. He outlines a grand strategy for humanity, provides actionable policy and research recommendations, and shows what each of us can do. The book ends with an inspiring vision of humanity’s potential, and what we might hope to achieve if we navigate the risks of the next century. thanks for listening. to help us out with the nonlinear library or to learn more, please visit nonlinear.org.
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Everyday Longtermism, published by Owen_Cotton-Barratt on the effective altruism forum. This post is about a question: What does longtermism recommend doing in all sorts of everyday situations? I've been thinking (on and off) about versions of this question over the last year or two. Properly I don't want sharp answers which try to give the absolute best actions in various situations (which are likely to be extremely context dependent and perhaps also weird or hard to find), but good blueprints for longtermist decision-making in everyday situations: pragmatic guidance which will tend to produce good outcomes if followed. The first part of the post explains why I think this is an important question to look into. The second part talks about my current thinking and some guess answers: that everyday longtermism might involve seeking to improve decision-making all around us (skewing to more important decision-making processes), while abiding by commonsense morality. A lot of people provided some helpful thoughts in conversation or on old drafts; interactions that I remember as particularly helpful came from: Nick Beckstead, Anna Salamon, Rose Hadshar, Ben Todd, Eliana Lorch, Will MacAskill, Toby Ord. They may not endorse my conclusions, and in any case all errors, large and small, remain my own. Motivations for the question There are several different reasons for wanting an answer to this. The most central two are: Strong longtermism says that the morally right thing to do is to make all decisions according to long-term effects. But for many many decisions it's very unclear what that means. At first glance the strong longtermist stance seems like it might recommend throwing away all of our regular moral intuitions (since they're not grounded in long-term effects). This could leave some dangerous gaps; we should look into whether they get rederived from different foundations, or if something else should replace them. More generally it just seems like if longtermism is important we should seek a deep understanding of it, and for that it's good to look at it from many angles (and everyday decisions are a natural and somewhat important class). Having good answers to the question of everyday longtermism might be very important for the memetics / social dynamics of longtermism. People encountering and evaluating an idea that seems like it's claiming broad scope of applicability will naturally examine it from lots of angles. Two obvious angles are "what does this mean for my day-to-day life?" and "what would it look like if everyone was on board with this?". Having good and compelling answers to these could be helpful for getting buy-in to the ideas. I think an action-guiding philosophy is at an advantage in spreading if there are lots of opportunities for people to practice it, to observe when others are/aren’t following it, and to habituate themselves to a self-conception as someone who adheres to it. For longtermism to get this advantage, it needs an everyday version. That shouldn't just provide a fake/token activity, but meaningful practice that is substantively continuous with the type of longtermist decision-making which might have particularly large/important long-term impacts. If longtermism got to millions or tens of millions of supporters -- as seems plausible on timescales of a decade or three -- it could be importantly bottlenecked on what kind of action-guiding advice to give people. A third more speculative motivation is that the highest-leverage opportunities may be available only at the scale of individual decisions, so having better heuristics to help identify them might be important. The logic is outlined in the diagram below. Suppose opportunities naturally arise at many different levels of leverage (value out per unit of effort in) and scales (how much effort...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Empirical data on value drift, published by Joey on the effective altruism forum. Write a Review Why It’s Important to Know the Risk of Value Drift The concept of value drift is that over time, people will become less motivated to do altruistic things. This is not to be confused with changing cause areas or methods of doing good. Value drift has a strong precedent of happening for other related concepts, both ethical things (such as being vegetarian) and things that generally take willpower (such as staying a healthy weight). Value drift seems very likely to be a concern for many EAs, and if it were a major concern, it would substantially affect career and donation plans. For example, if value drift rarely happens, putting money into a savings account with the intent of donating it might be basically as good as putting it into a donor-advised fund. However, if the risk of value drift is higher, a dollar in a savings account is more likely to later be used for non-altruistic reasons and thus not nearly as good as a dollar put into a donor advised fund, where it’s very hard not to donate it to a registered charity. In a career context, a plan such as building career capital for 8 years and then moving into an altruistic job would be considered a much better plan if value drift were rare than if it were common. The more common value drift is, the stronger near-term focused impact plans are relative to longer-term focused impact plans. For example, you might get an entry-level position at a charity and build up capacity by getting work experience. This has the potential, though not always, to be slower at building your CV than getting a degree or working in a low-impact but high-prestige field. However, it has impact right away, which matters more if the risk of value drift is high. The Data Despite the importance of value drift to important questions, it's rarely been talked about or studied. One of the reasons it is so under-studied is that it would take a long time to get good data. I have been in the EA movement for ~5 years. I decided to pool some data from contacts who I met in my first year of EA. I only included people who would have called themselves EAs for 6 months or longer (I would not include someone who was only into EA for a month and then disappeared), and who and took some sort of EA action (working for an EA org, taking the GWWC pledge, running an EA group). I also only included people who I knew and kept in touch with well enough to know what happened to them (even if they left the EA movement). It is ultimately a convenience sample, but it was based on working for 4 current EA orgs and living in 4 different countries over that time, so it’s not focused on a single location or organization. I also broke the groups down into ~10% donors and ~50% donors, because many times I have heard people being more or less concerned about one of these groups vs the other. These broad groups are not just focused on people doing earning to give. Someone who is working heavy hours for an EA organization and making most of their life decisions with EA as their number one priority would be considered in the 50% group. Someone running an EA chapter who makes decisions with EA as a factor, but prioritizes other factors above it, would be put in the 10% group. The percentages are aimed at rough proxies of how important EA is in these people's lives, not strictly financial donations. I did not count changing cause areas as value drift (e.g. changing from donating 10% to MIRI to AMF) -- only different levels of overall altruistic involvement. The results over 5 years are as follows: 16 people were ~50% donors → 9/16 stayed around 50% 22 people were ~10% donors → 8/22 stayed around 10% No one moved from the 10% category to the 50% category, and I only counted fairly noticeabl...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Ingredients for creating disruptive research teams, published by stefan.torges on the effective altruism forum. Write a Review Introduction This post tries to answer the question of what qualities make some research teams more effective than others. I was particularly interested in learning more about “disruptive” research teams, i.e. research teams that have an outsized impact on (1) the research landscape itself (e.g. by paving the way for new fields or establishing a new paradigm), and/or (2) society at large (e.g. by shaping technology or policy).[1] However, I expect the conclusions to be somewhat relevant for all research teams. Research seems to have become increasingly important within the effective altruism community. In the past few years, GPI was founded, FHI started growing significantly, and Open Phil is expanding its research capacity. Will MacAskill even called effective altruism a “research program”. From this perspective, we should be both interested in creating new fields of research, or at least substantially influencing existing ones, as well as impacting society. Acknowledgments: I did some of the research presented here as part of my work at the Berlin-based Effective Altruism Foundation (EAF), a research group and grantmaker dedicated to preventing suffering in the long-term future. Thanks to Jonas Vollmer, Jan Dirk Capelle, Max Daniel, and Alfredo Parra for valuable comments on an early draft of this post. Summary I looked at the two most comprehensive and rigorous academic studies on productive research teams I could find after a shallow review of the available literature (one literature review, Bland & Ruffin (1992), and one meta-analysis, Hülseger, Anderson & Salgado (2009)). Unfortunately, I could not find similarly comprehensive studies of disruptive research teams in particular. I complemented this with seven case studies of research teams I picked based on my own non-systematic judgment that they have been particularly disruptive. These are the RAND Corporation, the Sante Fe Institute, the Palo Alto Research Center (PARC), Bell Labs, Skunk Works, the Los Alamos Laboratory, and the partnership of Kahneman & Tversky. The following are my key findings based on this research: Particularly disruptive research teams always seem to contain a significant number of excellent researchers and even those who are not brilliant are very capable. Teams seem to benefit from cognitive diversity but not demographic diversity. Disruptive research teams seem to benefit from a purposeful vision that describes the kind of change they want to affect in the world. While more concrete goals are probably helpful, they seem difficult to set in this context. Leaders likely have an outsized impact on how productive and disruptive a research group is. In almost all cases, relevant research expertise seems to required for such a role. For some teams, a second administrative leadership role seems to be helpful for securing resources and managing external relationships. Research teams seem more likely to realize their full disruptive potential if the researchers do not have to do anything but research and have easy access to all the resources they need. Individual researchers in disruptive teams seem to thrive when given a large degree of autonomy, i.e., when they’re allowed to pursue projects and collaborations as they see fit. Instead of imposing metrics or incentives, it seems to work best to give them considerable freedom to work outside of usual incentive structures. To facilitate internal communications outside of formal structures, teams seem to benefit from shared spaces that allow for these exchanges to occur. Establishing a shared physical space that encourages interaction seems to be most important. Psychological safety, i.e., the feeling that voicing contro...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Long-term investment fund at Founders Pledge, published by SjirH on the effective altruism forum. Write a Review Edit 27/10/21: See these posts 1 2 3 for the next steps in this project. The post below was originally published on 09/01/20. At Founders Pledge, we are considering launching a long-term investment fund for our members. Contributions to this fund would by default be invested, potentially over centuries or millennia to come. Grants would only be made when there’s a strong case that a donation opportunity beats investment from a longtermist perspective. This idea was prompted in large part by recent research in the EA community, most notably Phil Trammell’s initial work on patient philanthropy and Will MacAskill’s forum post and the ensuing discussion on outside-view longtermism. We have just started this investigation, and don’t hold the views expressed below strongly. This post is mainly a call for input: we’d like to make the best possible use of the expertise and connections available in the larger EA community. Why a long-term investment fund In brief, we currently see three main potential ways in which investing to give later may be better than giving now: By exploiting the pure time preference in the market, i.e. that non-patient people are willing to sell the future (and especially the long-term future) cheaply By exploiting the risk premium in the market, to the extent that longtermist altruists should price risks differently to the market By giving us more time to learn and get better at identifying high-impact giving opportunities to benefit the long term There are also considerations that may counter (partially or in full) these three benefits: We may be living at one of the most influential times in history There are risks of expropriation, e.g. existential catastrophes or legal changes There are risks of value or competency change in the wrong direction, e.g. governance ends up in the wrong hands or new moral and nonmoral insights are not incorporated We have major uncertainty about all six factors, and intend to look into them further as part of this investigation. Assuming legal feasibility, we think it likely (>50%) that a well-governed long-term investment fund is among the highest-impact giving opportunities we currently know of from a longtermist perspective. What the fund would (ideally) entail Donations would be invested with the idea of growing the fund, potentially over centuries or even millennia to come. Money would only be deployed when there is a strong case that allocating to a funding opportunity is higher-impact from a longtermist perspective than keeping the money invested. This could happen, for instance, if our estimate of the expropriation rate rises greatly, legal and/or market changes make investing much less attractive, or we identify a truly extraordinary funding opportunity that we don’t expect to be filled by others. We might decide to create a separate legal entity for the fund, to make it less dependent on what happens to Founders Pledge in the long term. If so, we’ll have to define a legally fixed objective. We think we should define this in pure moral terms to allow for strategic flexibility, e.g. it should not include anything about investing. It should also balance protection against value drift with flexibility to incorporate new moral insights. Our starting idea is “to provide maximum benefit to all sentient beings, regardless of where or when they exist”. In addition to this fixed legal objective, we are thinking about the best way to structure the fund’s year-to-year governance. For instance, we could carefully select a board of trustees to guard the objective of the fund and update its strategy. They should embody the values of the fund and be strategically knowledgeable. This would allow a lot of the gover...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Improving Institutional Decision-Making: a new working group, published by IanDavidMoss, lauragreen, Vicky Clayton on the effective altruism forum. Write a Review By Ian David Moss, Vicky Clayton and Laura Green Summary This post describes recent and planned efforts to develop improving institutional decision-making (IIDM) as a cause area within and beyond the effective altruism movement. Despite increasing interest in the topic over the past several years, IIDM remains underexplored compared to “classic” EA cause areas such as AI safety and animal welfare. To help address some questions that have come up in our community-building work, we provide a working definition of IIDM, emphasizing its interdisciplinary nature and potential to bring together insights across professional, industry, and geographic boundaries. We also describe a new meta initiative aiming to disentangle and make intellectual progress on IIDM over the next year. The initiative includes several research and community development projects intended to enable more confident funding recommendations and career guidance going forward. You can get involved by volunteering to work on our projects, helping us secure funding, or giving us feedback on our plans. Introduction In 2017, 80,000 Hours published Jess Whittlestone’s problem profile on the topic of improving institutional decision-making (IIDM), which deemed the cause area “among the most pressing problems to work on” and suggested that “improving the quality of decision-making in important institutions could improve our ability to solve almost all other problems.” In the years since, we’ve seen signs of steadily increasing interest in IIDM within the EA community: IIDM-related talks, meetups and discussion channels have been included at most recent EA Global conferences, and a Facebook group founded to centralize discussion on the topic now has nearly 900 members. Today, 80,000 Hours continues to list IIDM among its priority problem areas and names “Building capacity to explore and solve problems,” a broad category that includes IIDM, as one of its top two overall priorities for career paths. Still, IIDM remains underexplored compared to “classic” EA cause areas such as AI safety and animal welfare. Up until now, there has not been a formal, globally focused umbrella organization dedicated to IIDM within the effective altruism ecosystem, leaving a gap of coordination in the field. There are legitimate questions about the effectiveness and tractability of interventions in the space that need to be resolved in order to be able to direct donations or career tracks with confidence. And we know from conversations with others in the EA community that IIDM’s interdisciplinary nature can make the cause area feel fuzzy or overly broad to some. For these reasons, the three of us are stepping up to act as a focal point for people interested in “disentangling” and making intellectual progress on IIDM in 2021. This work grows out of a year’s worth of informal exploration that has taken place since the first official IIDM meetup at EAG London 2019. In this article, we’ll share our working definition of IIDM and some key points from our recently developed operational plan. What is improving institutional decision-making? Decision-making at major institutions is shaped by a complex web of individual judgments, value systems, organizational structures and routines, leadership behaviors, incentives, social influences, and external conditions. As such, it’s worth taking a moment to define and explain what we mean by “improving institutional decision-making” a little more clearly. Let’s focus first on the “decision-making” part. The classic decision problems taught in economics textbooks describe fairly straightforward analytical problems: given two or more mutually ex...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: AMA: Tim Ferriss, Michael Pollan, and Dr. Matthew W. Johnson on psychedelics research and philanthropy, published by Aaron Gertler on the effective altruism forum. We're excited to bring you an AMA with three people who have done a lot to increase the profile and prospects of psychedelic research. Effective altruism has a history of engaging with psychedelics (see these posts, for example) as a promising intervention for mental health issues — one which could sharply reduce the suffering of tens or hundreds of millions of people. Between Tim, Michael, and Matt, we have many kinds of expertise here — nonprofit investing, journalism, medicine, and more. We hope the discussion is interesting, and useful for anyone who's thought about working or giving within this area. We'll gather questions for a couple of days. Michael and Matt will answer questions on Sunday, May 16th. Tim will answer questions on Tuesday, May 18th (we've pushed his original date back by one day). Author introductions Tim Ferriss Hi, everyone! I’m Tim Ferriss, and I’ll be doing an AMA here. More on me: I’m an author (The 4-Hour Workweek, Tools of Titans, etc.) and early-stage investor (Uber, Shopify, Duolingo, Alibaba, etc.). Through my foundation and since circa 2015, I have committed at least $4-6 million to non-profit scientific research and clinical treatments of “intractable” psychiatric conditions such as treatment-resistant depression, opioid/opiate addiction, post-traumatic stress disorder (PTSD), and others. I believe (A) this research has the potential to revolutionize the treatment of mental health and addiction, which the data from studies thus far seem to support, and (B) I’m a case study. Psychedelics have saved my life several times over, including helping me to heal from childhood abuse. Projects and institutions include the Centre for Psychedelic Research at Imperial College London (the first such center in the world); the Center for Psychedelic and Consciousness Research at Johns Hopkins University School of Medicine (the first such center in the US); MAPS (Phase 3 studies for MDMA-assisted psychotherapy); divisions and studies at UCSF (e.g., The Neuroscape Psychedelic Division); The University of Auckland (LSD microdosing); and others (e.g., pro bono launch of Trip of Compassion documentary on MDMA-assisted psychotherapy). I evaluate non-profit and scientific initiatives in the same way I evaluate for-profit startups, and I believe some bets in this nascent field represent high-leverage, low-cost opportunities to bend the arc of history, much as Katharine McCormick did for the first birth control pill. Here is one blog post with more elaboration. I am happy to answer any questions through the AMA. Dr. Matthew Johnson is no doubt better qualified to answer the scientific (and more), and Michael Pollan is no doubt more qualified to answer the journalistic (and more), but I will do my best to be helpful! Michael Pollan I'm a journalist and author who focuses on ways that the human and natural worlds intersect — including within our minds. In 2015, I wrote a New Yorker article on psychotherapy, "The Trip Treatment", which profiled a number of cancer patients whose experiences with psilocybin had reduced or entirely banished their fear of death. This led me to embark on a two-year journey into the history of psychedelic policy and its potential for modern medicine, and to write a book: How to Change Your Mind: The New Science of Psychedelics. My forthcoming book, This is Your Mind on Plants, covers the strange contrast between the human experience with several plant drugs — opium, caffeine, and mescaline — and how we choose to define and regulate them. I'd be glad to answer questions about anything I've written on the subject. Particular topics of interest: The history of drug regulatio...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: How to succeed as an early-stage researcher: the "lean startup" approach, published by tobyshevlane on the effective altruism forum. I am approaching the end of my AI governance PhD, and I’ve spent about 2.5 years as a researcher at FHI. During that time, I’ve learnt a lot about the formula for successful early-career research. This post summarises my advice for people in the first couple of years. Research is really hard, and I want people to avoid the mistakes I’ve made. My argument: At the early stage of your research career, you should think of yourself as an entrepreneur trying to build products (i.e. research outputs) that customers (i.e. the broader community) want to consume. You might be thinking: but I thought I was trying to maximise my impact? Sure, but at this stage in your career, you don’t know what’s impactful. You should be epistemically humble and responsive to feedback from people you respect. You should be opportunistic, willing to pivot quickly. I am calling this the “lean startup” approach to research. By now, everyone knows that most startup ideas are bad, and that founders should embrace this: testing minimal versions of the product, getting feedback from customers, iterating, and making dramatic changes where necessary. When you’re starting out in research, it’s the same. Early-stage researchers have two big problems. Number one, all your project ideas are bad. Number two, once you’ve written something, nobody is going to read it. It’s like an app that nobody downloads. It is possible to avoid these pitfalls, but that requires active effort. I will list many strategies that I’ve found helpful. At the end of the post, I’ll give a few examples from my own career. A lot of this advice is stolen from people who have helped me over the years. I encourage you to try it out. EDIT: I am most familiar with AI governance. I'm not sure how well my views generalise to other fields. (Thanks to the commenters who raised this issue.) Problem 1: your project ideas are bad In the early stage of your research career, 80-100% of your project ideas are bad. You’ll feel like your favourite project idea is great, but then years later, you’ll ask yourself: “what was I thinking?” Executing an idea requires a large time investment. You don’t want to waste that time on a bad idea. By “project idea” I mean not just a topic, but some initial framing of the problem, and some promising ideas for what kind of arguments or results you might produce. So, how do you find a good one of those? Solutions: Ideally, someone senior tells you what to work on. But this is time-expensive for them, and they don’t want to give away their best ideas to somebody who might execute them badly. So more realistically. Write out at least 10 project ideas, and ask somebody more senior to rank the best few. Always keep this list and add to it over time. This is a tried-and-tested method and it works very well. If you are pushing just one, single project idea, you might be able to arouse some minor, polite interest from other people, but this is a much less meaningful feedback process. Notice when people are genuinely interested. Sometimes you will get a cue that a person is actually interested in a puzzle or argument that you’ve formulated. You notice that they’ve been nerd sniped. That’s a very valuable feedback signal. It is also a reason to recentre the project around the exact question that nerd sniped them. Because you don’t yet have a well-developed sense of what issues are most interesting, you should update heavily on this kind of feedback. (As you get more experienced, you can allow yourself to get nerd sniped by your own ideas.) Fit into an established paradigm. While at FHI I have gradually absorbed a sense of the implicit worldviews of senior people, and what kinds of problems they t...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: What areas are the most promising to start new EA meta charities - A survey of 40 EAs, published by Joey on the effective altruism forum. Write a Review Charity Entrepreneurship (CE) is researching EA meta as one of four cause areas in which we plan to launch charities in 2021. EA meta has always been an area we have been excited about and think holds promise (after all, CE is a meta charity). Historically we have not focused on meta areas for a few reasons. One of the most important is that we wanted to confirm the impact of the CE model in more measurable areas such as global health and animal advocacy. After two formal programs we are now sufficiently confident in the model to expand to more meta charities. We were also impressed by the progress and traction that Animal Advocacy Careers made in their first year. Founded based on our research into animal interventions, this organization works at a more meta level than other charities we have incubated. In this document, I summarize the results of 40 interviews conducted with EA experts. These interviews constitute part of CE’s research into potentially effective new charities that could be founded in 2021 to improve the EA movement as a whole. Methodology In discussing meta charities, we are using a pretty broad definition. We include both charities that are one step removed from impact but in a single cause area (such as Animal Advocacy Careers), and more cross-cutting meta charities within the effective altruist movement. Generally our first step when approaching an area would involve broad research and literature reviews. However, given the more limited resources focused on meta EA and our stronger baseline understanding of the area, we wanted to supplement this information with a broad range of interviews. We ended up speaking to about 40 effective altruists (EAs) across 16 different organizations and 8 current or former chapter leaders. We tried to pick people who had spent considerable time thinking about meta issues and could be considered EA experts, and overall aimed for a diverse range of perspectives. The duration of the interviews ranged from 30 minutes to 2 hours, running about an hour on average. Not everyone answered every question but the majority of questions were answered by the majority of people. The average question got ~35 responses and none got fewer than 30. Interviewees were informed that an EA Forum post would be written containing the aggregated data but not individual responses. The background notes ended up being ~100 pages. We broke down the questions asked into three sections: Open questions What meta ideas might be uniquely impactful? What ideas might be uniquely unimpactful? Crucial considerations Expand vs improve Time vs money vs information Broad vs narrow What do you think of the current EA community trajectory? What do you think are the biggest flaws of the EA movement? Specific sub areas We took ideas that people had historically suggested on the EA Forum and organized them into around a dozen categories, providing examples for each. For each category, we were interested in whether it was seen as above or below average, as well as if any specific ideas stood out as promising. The descriptions below aim to reflect the aggregate responses I got, not what CE thinks or my impression after speaking to everyone (that will be a different post). The results constitute one (but not the only) piece of data CE will use when coming to recommendations for a new organization. Results 1. Open questions This was the hardest area to synchronize. It was surprising how much overall divergence there was between different people in terms of what ideas and concepts were seen as the most important. Lots of ideas that came up in the open questions were covered in the category areas, but open question...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Apply to the ML for Alignment Bootcamp (MLAB) in Berkeley [Jan 3 - Jan 22], published by Habryka, Buck on the Effective Altruism Forum. We (Redwood Research and Lightcone Infrastructure) are organizing a bootcamp to bring people interested in AI Alignment up-to-speed with the state of modern ML engineering. We expect to invite about 20 technically talented effective altruists for three weeks of intense learning to Berkeley, taught by engineers working at AI Alignment organizations. The curriculum is designed by Buck Shlegeris (Redwood) and Ned Ruggeri (App Academy Co-founder). We will cover all expenses. We aim to have a mixture of students, young professionals, and people who already have a professional track record in AI Alignment or EA, but want to brush up on their Machine Learning skills. Dates are Jan 3 2022 - Jan 22 2022. Application deadline is November 15th. We will make application decisions on a rolling basis, but will aim to get back to everyone by November 22nd. Apply here AI-Generated image (VQGAN+CLIP) for prompt: "Machine Learning Engineering by Alex Hillkurtz", "aquarelle", "Tools", "Graphic Cards", "trending on artstation", "green on white color palette" The curriculum is still in flux, but this list might give you a sense of the kinds of things we expect to cover (it’s fine if you don’t know all these terms): Week 1: PyTorch — learn the primitives of one of the most popular ML frameworks, use them to reimplement common neural net architecture primitives, optimization algorithms, and data parallelism Week 2: Implementing transformers — reconstruct GPT2, BERT from scratch, play around with the sub-components and associated algorithms (eg nucleus sampling) to better understand them Week 3: Training transformers — set up a scalable training environment for running experiments, train transformers on various downstream tasks, implement diagnostics, analyze your experiments (Optional) Week 4: Capstone projects We’re aware that people start school/other commitments at various points in January, and so are flexible about you attending whatever prefix of the bootcamp works for you. Logistics The bootcamp takes place at Constellation, a shared office space in Berkeley for people working on long-termist projects. People from the following organizations often work from the space: MIRI, Redwood Research, Open Philanthropy, Lightcone Infrastructure, Paul Christiano’s Alignment Research Center and more. As a participant, you’d attend communal lunches and events at Constellation and have a great opportunity to make friends and connections. If you join the bootcamp, we’ll provide: Free travel to Berkeley, for both US and international applications Free housing Food Plug-and-play, pre-configured desktop computer with an ML environment for use throughout the bootcamp You can find a full FAQ and more details in this Google Doc. Apply here Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: A Qualitative Analysis of Value Drift in EA, published by MarisaJurczyk on the Effective Altruism Forum. Write a Review About a year ago, after working with the Effective Thesis Project, I started my undergraduate thesis on value drift in the effective altruism movement. I interviewed eighteen EAs about their experiences with value drift and used a grounded theory approach to identify common themes. This post is a condensed report of my results. The full, official version of the thesis can be found here. Note that I’ve changed some of the terms used in my thesis in response to feedback, specifically “moral drift”, “internal value drift”, and “external value drift”. This post uses the most up-to-date terminology at time of posting, though these terms still a work-in-progress. Summary Value drift is a term EAs and rationalists use to refer to changes in our values over time, especially changes away from EA and other altruistic values. We want to promote morally good value changes and avoid morally bad value changes, but distinguishing between the two can be difficult since we tend to be poor judges of our own morality. EAs seem to think that value drift is most likely to affect the human population as a whole, less likely to affect the EA community, and even less likely to affect themselves. This discrepancy might be due to an overconfidence bias, so perhaps EAs ought to assume that we’re more likely to value drift than we intuitively think we are. Being connected with the EA community, getting involved in EA causes, being open to new ideas, prioritizing a sustainable lifestyle, and certain personality traits seem associated with less value drift from EA values. The study of EAs’ experiences with value drift is rather neglected, so further research is likely to be highly impactful and beneficial for the community. Background What is Value Drift? As far as I can tell, “value drift” is an expression that was first used by the rationalist community, in reference to AI safety. It has not been discussed nor studied outside of the rationalist and EA communities - at least, not using the term “value drift.” Value drift has been defined as broadly as changes in values and as narrowly as losing motivation to do altruistic things. People seem to see the former as the technical definition and the latter as what the term implies, as value drift away from EA values is often seen as the most concerning value drift to an EA who wants to remain an EA, or altruistic more generally. However, we can certainly experience value drift towards EA values or experience value drift that keeps us just as aligned with EA. NB: Throughout this post, I use value drift to refer to a shift away from EA values, unless I specify otherwise. I discuss a few different types of value drift throughout this post: Hierarchical value drift: a change in one’s hierarchy of values in which a value is not lost or gained, but rather its priority is changed. Transformative value drift: losing a previously-held value or gaining a new value. Abstract value drift: changes in abstract values, such as happiness or non-suffering. Concrete value drift: changes in concrete vales, such as effective altruism, animal welfare, global health, or existential risk-prevention. Value drift can lead us to act less morally than we otherwise would. However, it’s possible that our behaviors can change without our values changing. Darius Meissner’s forum post, “Concrete Ways to Reduce Value Drift and Lifestyle Drift”, makes the important distinction between value drift and lifestyle drift, where value drift refers to changes in values and lifestyle drift refers to changes in behaviors, often as a result of circumstances. Some academic research highlights a similar phenomenon called ethical drift, which refers specifically to behavior chan...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Geographic diversity in EA, published by AmAristizábal on the Effective Altruism Forum. Write a Review Hi, I´m from Colombia (first post) and I want to share my thoughts on lack of geographic diversity in EA. I suspect that due to lack of diversity, questions that could be relevant to EA have not been considered enough and here I share some of the ones that I deal with the most (although I don't have a strong position about most of these things and probably I just have not been aware if they DO HAVE been considered, in that case I would appreciate a lot if you could send links or recommendations): -Whether giving locally could be better (or not) for donors in low and middle income countries: Countries with weak currencies such as mine face high exchange rates (especially in hard times such as this pandemic). I have the intuition that with a volatile dollar price it doesn't always make sense to donate to EA recommended charities and perhaps donors could allocate better their donations by donating locally. In my case I just switch to save and donate later (because I'm young ) but what if I still want to donate a little bit to keep motivation? Or what if I want to convince my friend's uncle to donate?I still want to have an informed opinion. -Spot regional differences within countries when answering different types of questions: Even if my country's GDP is higher than many countries where effective donations according to EA are allocated, there are many regions within my country where poverty is extremely high, even higher than in richer cities from poorer countries. Those differences are hard to spot if EA spots “poverty” as a whole without zooming in geographical zones. -Addressing the real potential of going into policy in LMICs: EA recommends policy careers but I suspect that it's an even more important path in LMICs, where policies are weaker, policymakers are even less evidence based and where institutions have a lot more potential to improve. -Whether there is a chance to adapt EA to other cultural values: Individualism vs collectivism: I feel that EA was born in cultures that value individualistic goals (even if the focus is on the world as a whole). For example, I see EA deeply linked to “western”´s understanding of freedom, independence of thought, skepticism, mistrust for authority and social norms, etc. However, other cultures with more collectivist mindsets can struggle to link altruism to those specific values. In many cultures altruism is deeply linked to religion or family bonds and giving is prioritized when you help those that surround you. Even if there is no rational argument to value more a life in my country vs a life in sub-saharan Africa, what if EA is losing an opportunity to take advantage of these cultural drives towards giving by, for example, strengthening local networks of charities. Nationalism: Even if I'm not fond of nationalism I do recognize it as a huge drive for altruism in my country (probably in many others as well). I won't convince my friend's uncle to donate to Against Malaria but I could convince him to donate to a colombian charity. Could we use those emotional bonds to promote doing good in an effective way at the same time? -I wonder if there is a bias when EA talks about problems not being “neglected” enough when dismissing some cause areas or focus topics: an example that comes to my mind is gender inequality in governments or in the workplace. In EA there is a whole focus area on improving institutional decision making, which is great (actually there is where I want to focus); but what if there are easier and more urgent steps to be taken towards IIDM in LMICs such as focusing on women's access to governments (something that in high income countries is not that neglected and has been widely addressed, or at least a lot mo...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Why EA groups should not use “Effective Altruism” in their name, published by KoenSchoen on LessWrong. Starting a conversation about the name “Effective Altruism” for local and university groups. Abstract: most EA groups’ names follow the recipe “Effective Altruism + [location/university]”. In 2020 we founded a university EA group who’s name does not include the words “Effective Altruism”. We have grown rapidly, and it now seems more and more likely that our organization will stick around in years to come. We think our name played a non-negligible part in that. In fact, we believe that choosing an alternative name is one of the most cost-effective things you can do to make your group grow. In this article we argue that more (potential) groups should consider an alternative name. We propose a method for coming up with that name. Lastly, we propose that “part of the EA network” could serve as a common subtitle to unite all EA groups despite their various names. Scroll down to ‘summary’ for a quick overview of our arguments. One of my teachers, a social entrepreneur, once told me: “when you are doing any kind of project, first make sure to give it a good name.” These words ran through my mind when I, together with five others, started a new EA student association at Erasmus University Rotterdam in the Netherlands. At our second collective meeting we decided against the name “Effective Altruism Erasmus” and opted for “Positive Impact Society Erasmus” (PISE) instead. Now, 6 months in, we still believe this was a great decision. Our association is doing well, and we believe that our name has had some part in that. As we speak, more Dutch EA groups are considering changing their name. Maastricht University’s chapter is already called “LEAP” (Local Effective Altruism Project) and the group at Wageningen University is also considering a name change. We think we should have a movement wide conversation about “Effective Altruism” as the name for local and university groups. Below we have written down our thoughts on two questions: firstly, should local and university groups have a name other than “Effective Altruism X”? Secondly, if so, what should that name be? Lastly, we propose a common subtitle for all EA groups with an alternative name. Our thoughts are far from complete and we are uncertain on many accounts. We invite anyone to add to the discussion! Before we start: how important is a name anyways? How important is the name of your group? On the one hand a name is just a name. If you are delaying founding an EA chapter because you are fervently debating your groups name, you need to reconsider your priorities. However, you only get one chance at a first impression and sometimes your first impression makes a difference. How much of a difference does it make? In the last 6 month our group grew from 6 active members to 24, all of which are now spending time every week on organizing events and workshops, working on projects etc. Many of them had never heard of EA before this year but have now taken a fellowship, or read an EA book. If we had to make a conservative guess we would say about 2-3 people would not have found us if we would have had the traditional name (later we will give some examples of this). In total, coming up with the name took us about 3,5 hours (which was about an hour longer than it should have cost). 2,5 hours of work for growing your organization by 2-3 extra active members (every 6 months) is a return on investment we haven’t often seen elsewhere. Therefore we think more local and university groups should consider an alternative name. Should local and university groups have a name other than “Effective Altruism + [location/university]”? The name “Effective Altruism” was never meant to take off as a popular term. The marketing implications of the name ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: EA Debate Championship & Lecture Series, published by Dan Lahav, sella on the Effective Altruism Forum. Executive Summary On October 23-25 2020, we hosted the inaugural online EA Debate Championship - a three-day debate championship with EA-themed topics. The championship had 150+ participants, from roughly 25 countries, that span 6 continents. The championship was supported by the World Universities Debating Championship, aka WUDC - one of the largest international student-driven events in the world. There were a total of 7 debate rounds - 5 preliminary rounds and 2 knockout rounds. The knockout rounds were held in 2 different language proficiency categories to promote inclusivity. In total over the course of that weekend over 500 EA-related speeches were delivered. The championship featured a Distinguished Lecture Series as non-mandatory preparation material - 9 lectures, 3 debate exercises and 1 Q&A session containing introductory EA materials (totalling ~10 hours), with top EA speakers including Ishaan Guptasarma, Joey Savoie, Karolina Sarek, Kat Woods, Lewis Bollard, Olivia Larsen, Nick Beckstead, and Will MacAskill. The debate exercises were filmed by world-renowned debate teams. The championship included a research component to examine if debating on EA topics changes the stance of debaters towards EA values. Most of the participants were not familiar with EA prior to the competition, or had limited exposure to core EA ideas. However, when asked after the tournament many were highly positive on the prospect of attending a future EA debating championship, and reported a strong willingness to continue their engagement with the EA community. During the tournament, over $2,000 were donated to effective charities by the participants (with most of the funds going to the Against Malaria Foundation). The funds were doubled via donation matching provided by Open Philanthropy. The competition was initiated and organized by members of EA Israel who are also debaters; with the support of several highly influential international debaters and the World Championship. This collaboration was possible due to the strong ties that exist between the debating community and the EA community in Israel. We think that there is room to building similar ties on a more global scale. In the rest of the post we will explain our motivation to run the event, describe the program and its outcomes in detail, share what we have learned from the process, and discuss our next steps. Organizing the tournament was an effort of a great many. We thank them all, and would like to stress that any mistakes or inaccuracies in the description are our own. In particular we would like to thank Adel Ahmed, Ameera Moore, Barbara Batycka, Bosung Baik, Chaerin Lee, Connor O’Brien, Dana Green, Emily Frizell, Enting Lee, Harish Natarajan, Ishaan Guptasarma, Jaeyoung Choi, Jessica Musulin, Joey Savoie, Kallina Basli, Karolina Sarek, Kat Woods, Lewis Bollard, Milos Marajanovic, Mubarrat Wassey, Nick Beckstead, Olivia Larsen, Omer Nevo, Sally Kwon, Salwaa Khan, Seoyoun, Seungyoun Lee, Sharmila Parmanand, Tricia Park, Will MacAskill and Yeaeun Shin for their contributions in running the tournament, filming lectures or creating exercises; to David Moss, David Reinstein and Stefan Schubert for their advice on running the tournament survey; and to the many incredibly qualified debate adjudicators & speakers that made the event possible Motivation We initiated this effort due to the impression that themed debating tournaments (along with matching preparation materials) can be a relatively broad yet high-fidelity outreach opportunity. We believe this is the case for several reasons: The international debating community mostly consists of undergraduate students from around 50 countries (elite universities are represented ac...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Despite billions of extra funding, small donors can still have a significant impact, published by Benjamin_Todd on the Effective Altruism Forum. I’ve written about how there’s now a lot more funding committed to effective altruism– about $50bn. It’s natural to think this means small donors can no longer have much impact, and I’ve seen several cases of people saying they’re not sure whether their donations will do any good, because all the opportunities are being taken by large donors. However, I think this isn’t right: more donations from small donors still have a significant impact. This means raising additional funding is still of value to the community, and I think earning to give and donating to e.g. the Long Term Future Fund, is a highly impactful thing to do – probably more impactful than the vast majority of careers. I also think the increase in funding means there’s an opportunity to do even more good than earning to give, and that people earning to give currently should seriously consider switching to the kinds of opportunities flagged in my talk at EAG. But that doesn’t mean that small donations have no impact. Instead: What matters is not the total amount of available funding, but the current level of cost-effectiveness at the margin. This has likely declined, but is still high. Small donors should be able to roughly match large donors in terms of cost-effectiveness by ‘funging’ with them. Small donors can sometimes beat large donors in terms of cost-effectiveness, and I provide a list of some common ways to do this. At the end, I’ll make some comments on where I think people should donate. 1. What matters is not total funding available but marginal cost-effectiveness It’s true that as more funding becomes available, all else equal, we should expect more of the best opportunities to be taken, and for cost-effectiveness to decrease. However, there is a force which limits the size of this effect: how quickly we’re able to discover new opportunities. Because effective altruism is still small and building capacity, it’s not obvious that cost-effectiveness will decline quickly. While I think the very best opportunities involve taking a more hits based, longterm focused approach than GiveWell, their recommendations serve as a good starting point to examine these dynamics. GiveWell’s top recommendations probably constitute the ‘bar’ for neartermist work. In a recent post, Open Philanthropy’s Global Health and Wellbeing team expect to find many opportunities above this bar, but for marginal dollars to go to GiveWell. Overall, GiveWell now seems to be targeting a cost-effectiveness of 8x GiveDirectly or higher for most donations, though about 20% funds will go towards opportunities that are 5-8x as cost-effective as GiveDirectly, and so additional donations should be about this cost-effective. GiveWell is unsure whether the margin will be closer to 5x than 8x. In the same post, Open Philanthropy says “we currently expect GiveWell’s marginal cost-effectiveness to end up around 7-8x GiveDirectly”. They also say they believe that GiveWell’s margin has been around 10x GiveDirectly in recent years, so if it declines to 7x, that will be a 30% fall – this is only a modest decline and still very high. To illustrate, they estimate that donating $4,250 to a charity that’s 8x GiveDirectly is as good as saving the life of a child under five. With a lognormal distribution of cost-effectiveness, there should be many more opportunities at the 5x level than the 10x level, so it should be possible to deploy a lot more funds as the bar lowers. (Even setting aside the possibility of discovering new highly cost-effective interventions.) In a worst case scenario, billions could be spent on cash transfers at a level of cost-effectiveness similar to or only a little below GiveDirectly. T...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Presenting: 2021 Incubated Charities (Charity Entrepreneurship), published by Joey on the Effective Altruism Forum. 2021 was the third year that we at Charity Entrepreneurship held our annual Incubation Program. Interest in the program was very high, with over 2000 applications submitted. 27 participants representing 16 countries graduated from the 2-month intensive training program, including teams that will start new organizations, individuals that are being hired by high-impact organizations, regional groups that will conduct research under our mentorship, and a foundation that will focus on providing grants to high-impact interventions. We are delighted to announce the launch of five new charities and want to thank our funders: EA Funds, Open Philanthropy, and the CE Seed Network (a group of high-impact professionals) for their generous donations, which totaled to $537,000 in grants offered to the charities this year. The 2021 incubated charities are: Training For Good - delivering a range of training programs to fill important EA capability gaps and raise the utilization rate of EA talent High Impact Professionals - enabling working professionals to have the biggest positive impact possible Shrimp Welfare Project - improving the lives of hundreds of millions of farmed shrimp in Southeast Asia Healthier Hens - improving the welfare of farmed egg-laying hens via a cost-effective intervention focused on feed fortification Center for Alcohol Policy Solutions - saving lives and promoting well-being through alcohol taxation TRAINING FOR GOOD Co-founders: Cillian Crosson, Jan-Willem van Putten, Steve Thompson Website: trainingforgood.com Contact: contact@trainingforgood.com CE Incubation Grant: $175,000 Description of the intervention: Training for Good (TFG) will upskill people to tackle the most pressing global problems. TFG will deliver a range of training programs to help solve skill bottlenecks in EA cause areas and raise the rate of talent utilization within the EA movement. Background of the intervention: Talent utilization: There are over 6,000 committed EAs, the majority of whom want to pursue impactful careers. Yet many are struggling to find concrete opportunities to implement EA in their lives. TFG aims to raise the rate of talent utilization within the EA movement by creating training programs that enable large numbers of people to enter impactful careers. Skill bottlenecks: Funding for many EA cause areas has grown faster than the number of people interested in them. This has led to a “funding overhang” and an increase in certain skill bottlenecks. TFG aims to solve these skill bottlenecks in EA cause areas by developing targeted programs that fill current skill gaps and advance the capabilities needed to deploy funds effectively in the future. Near-term plans: TFG intends to experiment with different approaches to training before choosing where to narrow their focus. They will pilot the following four training programs within year one: Salary Negotiation for Earning-to-Givers: In November 2021, TFG is launching a training program to help E2Gers maximize their donation potential. If you are interested in participating, please complete this application form by midnight on 7th November. Effective Careers in the Civil Service: In January 2022, TFG will launch a training program for aspiring policymakers. If you are a current or aspiring policymaker within Europe (including UK and other non-EU countries), please complete this needs survey to help us identify the most important skill gaps. EA for Experienced Professionals: Around May 2022, TFG will host a week-long retreat, training corporate executives with 10+ years experience in basic EA concepts and connecting them to the EA movement to fill management skill gaps in key EA organizations. Grantmaking for Im...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Introducing Training for Good (TFG), published by Cillian Crosson, Jan-WillemvanPutten, SteveThompson on the Effective Altruism Forum. We are excited to announce the launch of a new effective altruism training organisation, Training for Good (TFG). trainingforgood.com TFG aims to upskill people to tackle the most pressing global problems. TFG will identify the most critical skill gaps in the EA movement and address them through training. TFG was incubated by Charity Entrepreneurship in 2021. This post introduces TFG, provides an overview of the problems we seek to tackle and presents our immediate plans for addressing them. The following is structured into: Overview of TFG TFG’s short term plans Decisions and underlying assumptions How you can help Ask us anything We thank Brian Tan, Charles He, Devon Fritz, Isaac Dunn, James Ozden, and Sam Hilton for their invaluable feedback on this announcement. All errors and shortcomings are our own. Overview of TFG Why training? Track record Some EA organisations have experienced moderate success running training programmes and online courses. Animal Advocacy Careers ran a ~9 week online course, teaching core content about effective animal advocacy, effective altruism, and impact-focused career strategy. They recently published the results of two longitudinal studies they ran comparing and testing the cost-effectiveness of this online course and their one-to-one advising calls. Their results weakly suggested that while one-to-one calls are slightly more effective per participant, online courses are a slightly more cost-effective service Charity Entrepreneurship’s two-month incubation programme aims to equip participants with the skills needed to found an effective non-profit. Through this programme, they have helped launch 16 effective organisations to date. The Centre for Effective Altruism uses online courses as a high fidelity method of spreading EA ideas and growing the movement. They run an Introductory EA Programme which introduces the core ideas of effective altruism through 1-hour discussions over the course of eight weeks. Other programmes offered by Peter Singer, the Centre for Applied Rationality, the Good Food Institute, and 80,000 Hours have also proved popular, suggesting that there is further demand for such courses. Movement demographics Movement demographics suggest that EAs are a promising audience for training. 80% are aged under 35 and a large proportion are still deciding what career to pursue or building up career capital. Over 50% of EAs also place career capital as a focus above direct impact. These demographic factors suggest a strong interest in gaining skills and participating in training programmes. Cause neutral and flexible Training is a cause neutral intervention. Cross-cutting programmes can be run which benefit several cause areas simultaneously or multiple targeted programmes can be run for different cause areas. Flexibility is particularly important when we consider that EA is a relatively young movement and that there may be cause areas which deserve our attention that we are currently neglecting. If information arises to suggest that we should switch our attention to another cause area (even temporarily), TFG could easily do so. Moreover, we believe that such organisational flexibility could help enable movement flexibility, as it creates the space for intellectual exploration to take place. Comparative advantage Our co-founding team has a relative amount of expertise designing and delivering training programmes. In particular, Steve has extensive experience in both the design and facilitation of large scale training and development programmes. He has spent over ten years in the corporate sector training and coaching across multinational firms. Cillian and Jan-Willem also have experience fac...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Notes on Managing to Change the World", published by Peter Wildeford on the effective altruism forum. The book “Managing to Change the World: The Nonprofit Manager's Guide to Getting Results” by Alison Green and Jerry Hauser comes highly recommended from a wide variety of top executive directors of non-profits, and after reading it, I can say these positive recommendations are entirely justified. Don’t let the title fool you - while talk of “changing the world” may sound pie-in-the-sky or even hippyish, this book was relentlessly practical. The principles also matter more than just for non-profits. I think anyone managing others should read this book, regardless of whether they are working in non-profits or not. So far this is my favorite management book that I have ever read.[1] The density of information is amazing and it will be difficult for me to do the book justice with a summary, and the book is short enough that I encourage everyone to read the actual book cover-to-cover rather than just my summary here. Nevertheless, I will persist with summarizing. Note there may be some things in this book that I disagree with, or at least don’t fully agree with. I’d be careful to read the book critically. There is also a lot of good advice that is not in this book. In these notes I mainly aim to summarize what I find as the key takeaways of the book, from my understanding and as applied to my personal context, rather than try to present my all-things-considered view on how best to run a non-profit organization. Also note that this post is a personal post and does not necessarily represent the views or practices at Rethink Priorities. Summary of the Summary Management is about getting things done through other people and your job as a manager is to get results. Good managers set goals, are clear about what those goals are, hold people to those goals, help people meet those goals, are clear with people about when they aren’t meeting goals, and are not afraid to tell some employees they aren’t right for the job. Good managers ensure people are in roles where they will excel and get everyone aligned around a common purpose. Good managers delegate, but don’t disappear after - they don’t do the work themselves but do ensure implementation happens and help employees do their work. Most managers should spend less time actually doing work than they probably spend, but more time guiding other people through their work than they probably spend. The best way to ensure delegation goes successfully is to (1) be clear from the start about what you expect, (2) stay engaged enough along the way to make sure you and the employees are on the same page and to ensure the ongoing quality of the work, and (3) hold people accountable for what they deliver. The most common way managers fail at delegation is by not staying involved throughout to check on progress. You should have a regular (typically weekly) 1-on-1 meeting with each employee you manage to connect personally, review progress against the plan, ask probing questions, provide feedback, help the employees adjust priorities, and create connections between employees. When giving feedback, be specific. When asking questions, be specific. Delegation usually starts by handing off specific tasks and projects, but the true power of delegation emerges when you can hand off broad responsibilities. When interacting with your own boss (managing up), have empathy and remember they are a person. Guide them toward doing the right thing and make managing easy. When asking for input from your manager, apply the one hand rule - keep questions to yes/no or multiple choice, make an initial recommendation / default, and make everything clear upfront but provide background at the end as necessary. What is management? The point of management is to get more ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: A Red-Team Against the Impact of Small Donations, published by AppliedDivinityStudies on the Effective Altruism Forum. In a comment on Benjamin Todd's article in favor of small donors, : This article is kind of too "feel good" for my tastes. I'd also like to see a more angsty post that tries to come to grips with the fact that most of the impact is most likely not going to come from the individual people, and tries to see if this has any new implications, rather than justifying that all is good. I am naturally an angsty person, and I don't carry much reputational risk, so this seemed like a natural fit. I agree with NunoSempere that Benjamin's epistemics might be suffering from the nobility of his message. It's a feel-good encouragement to give, complete with a sympathetic photo of a very poor person who might benefit from your generosity. Because that message is so good and important, it requires a different style of writing and thinking than "let's try very hard to figure out what's true." Additionally, I see Benjamin's post as a reaction to some popular myths. This is great, but we shouldn't mistake "some arguments against X are wrong" for "X is correct". As to not bury the lede: I think there are better uses of your time than earning-to-give. Specifically, you ought to do more entrepreneurial, risky, and hyper-ambitious direct work, while simultaneously considering weirder and more speculative small donations. Funny enough, although this is framed as a "red-team" post, I think that Benjamin mostly agrees with that advice. You can choose to take this as evidence that the advice is robust to worldview diversification, or as evidence that I'm really bad at red-teaming and falling prey to justification drift. In terms of epistemic status: I take my own arguments here seriously, but I don't see them as definitive. Specifically, this post is meant to counterbalance , so you should read his first, or at least read it later as a counterbalance against this one. 1. Our default view should be that high-impact funding capacity is already filled. Consider Benjamin's explanation for why donating to LTFF is so valuable: I would donate to the Long Term Future Fund over the global health fund, and would expect it to be perhaps 10-100x more cost-effective (and donating to global health is already very good). This is mainly because I think issues like AI safety and global catastrophic biorisks are bigger in scale and more neglected than global health. I absolutely agree that those issues are very neglected, but only among the general population. They're not at all neglected within EA. Specifically, the question we should be asking isn't "do people care enough about this", but "how far will my marginal dollar go?" To answer that latter question, it's not enough to highlight the importance of the issue, you would have to argue that: There are longtermist organizations that are currently funding-constrained, Such that more funding would enable them to do more or better work, And this funding can't be met by existing large EA philanthropists. It's not clear to me that any of these points are true. They might be, but Benjamin doesn't take the time to argue for them very rigorously. Lacking strong evidence, my default assumptions are that funding capacity for extremely high-impact organizations well aligned with EA ideology will be filled by donors. Benjamin does admirably clarify that there are specific programs he has in mind: there are ways that longtermists could deploy billions of dollars and still do a significant amount of good. For instance, CEPI is a $3.5bn programme to develop vaccines to fight the next pandemic. At face value, CEPI seems great. But at the meta-level, I still have to ask, if CEPI is a good use of funds, why doesn't OpenPhil just fund it? In general, my default...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: You have more than one goal, and that's fine, published by Julia_Wise on the Effective Altruism Forum. Write a Review This version of the essay has been lightly edited. You can find the original here. When people come to an effective altruism event for the first time, the conversation often turns to projects they’re pursuing or charities they donate to. They often have a sense of nervousness around this, a feeling that the harsh light of cost-effectiveness is about to be turned on everything they do. To be fair, this is a reasonable thing to be apprehensive about, because many youngish people in EA do in fact have this idea that everything in life should be governed by cost-effectiveness. I've been there. Cost-effectiveness analysis is a very useful tool. I wish more people and institutions applied it to more problems. But like any tool, this tool will not be applicable to all parts of your life. Not everything you do is in the “effectiveness” bucket. I don't even know what that would look like. I have lots of goals. I have a goal of improving the world. I have a goal of enjoying time with my children. I have a goal of being a good spouse. I have a goal of feeling connected in my friendships and community. Those are all fine goals, but they’re not the same. I have a rough plan for allocating time and money between them: Sunday morning is for making pancakes for my kids. Monday morning is for work. It doesn’t make sense to mix these activities, to spend time with my kids in a way that contributes to my work or to do my job in a way that my kids enjoy. If I donate to my friend’s fundraiser for her sick uncle, I’m pursuing a goal. But it’s the goal of “support my friend and our friendship,” not my goal of “make the world as good as possible.” When I make a decision, it’s better if I’m clear about which goal I’m pursuing. I don’t have to beat myself up about this money not being used for optimizing the world — that was never the point of that donation. That money is coming from my "personal satisfaction" budget, along with money I use for things like getting coffee with friends. I have another pot of money set aside for donating as effectively as I can. When I'm deciding what to do with that money, I turn on that bright light of cost-effectiveness and try to make as much progress as I can on the world’s problems. That involves looking at the research on different interventions and choosing what I think will do the most to bring humanity forward in our struggle against pointless suffering, illness, and death. The best cause I can find usually ends up being one that I didn’t previously have any personal connection to, and that doesn’t nicely connect with my personal life. And that’s fine, because personal meaning-making is not my goal here. I can look for personal meaning in the decision afterward, but that's not what drives the decision. When you make a decision, be clear with yourself about which goals you’re pursuing. You don’t have to argue that your choice is the best way of improving the world if that isn’t actually the goal. It’s fine to support your local arts organization because their work gives you joy, because you want to be active in your community, or because they helped you and you want to reciprocate. If you also have a goal of improving the world as much as you can, decide how much time and money you want to allocate to that goal, and try to use those resources as effectively as you can. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Is Democracy a Fad?, published by Ben Garfinkel on the Effective Altruism Forum. This cross-post from my personal blog explains why I think democracy will probably recede within the next several centuries, supposing people are still around. The key points are that: (1) Up until the past couple centuries, nearly all states have been dictatorships. (2) There are many examples of system-wide social trends, including the rise of democracy in Ancient Greece, that have lasted for a couple centuries and then been reversed. (3) If certain popular theories about democratization are right, then widespread automation would negate recent economic changes that have allowed democracy to flourish. This prediction might have some implications for what people who are trying to improve the future should do today (although I'm not sure what these implications are). It might also have some implications for how we should imagine the future more broadly. For example, it might give us stronger reasons to doubt that future generations will take inclusive approaches to any consequential decisions they face.[1] Introduction There’s a strange new trend that’s been sweeping the world. In recent centuries, you may have noticed, it has become more and more common for people to choose their own leaders. Five thousand years after states first emerged, democracy has been taking off in a big way. The average state’s level of democracy over the past two hundred years. States with sub-zero scores are more autocratic than democratic.[2] If you follow politics, then you’ve probably already heard a lot about democracy. Still, though, a quick definition might be useful. In a proper democracy, the state’s most important figures are at least indirectly chosen through elections. A large portion of the people ruled by the state are allowed to vote, these votes are counted more-or-less accurately and more-or-less equally, and there’s no truly serious funny business.[3] Proper democracies are something new. For most of the past five thousand years, dictatorship has been the standard model for states. We don’t know much about the first state, Uruk, but the most common theory is that it was a theocracy ruled by a small priestly class. Monarchy emerged a bit later, spread across the broader Near East, and then stuck around in one form or another for thousands of years. Many archeologists suspect these little bowls were used to ration out grain to people doing forced labor. They are also by far the most common artifact found around Uruk, which is often taken as an ominous sign. In other parts of the world, small states with noteworthy democratic elements have emerged from time to time. Certain small states in Greece, as the most famous example, were borderline-proper democracies for a couple hundred years. However, if there was any trend at all, then the trend was toward more consistent and complete dictatorship. States with noteworthy democratic elements tended to lose these elements over time, as they either expanded or fell under the influence of larger states.[4] No sensible person living one thousand years ago would have predicted the recent democratic surge. It’s natural to wonder: Will this rise in democracy last? Or will democracy turn out to be only a passing fad—something like the Ice Bucket Challenge of regime types?[5] Let’s suppose, to be more specific, that one thousand years from now people and states still at least kind of exist. How surprised should we be if democracy is no more common then than it was in the year 1000AD? An Outside View One way to approach this question is to think hard about history, political science, economics, the future of technology, and all that. Another way to approach the question is just to look at the long-run trend. The trend, again, is roughly this: Democracy was very ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: I scraped all public "Effective Altruists" Goodreads reading lists, published by MaxRa on the Effective Altruism Forum. A couple of weeks ago I mentioned the idea of scraping the reading lists of the members of the Effective Altruists Goodreads group. The initial motivation was around the idea that EAs might be reading too much of the same books, and we might improve this by finding out which books are read relatively little compared to how many EAs proclaim that they want to read them. I got some positive feedback and got to work. Besides helping a little with improving our exploration of literature, I think the results also serve as an interesting survey of the reading behavior of EAs. Though we might want to keep in mind a possible selection bias for EAs and EA-adjacent people that share their reading behavior on Goodreads. For those who don’t know Goodreads, it’s a social network where you can share ratings and reviews of the books you’ve read, and organize books in shelves like I have read this! or I want to read this!. It’s quite fun, many EAs are on there and I wholeheartedly recommend joining. In total, there were 333 349 people in the Effective Altruists Goodreads group, and 257 275 of them had their privacy settings set to completely public, allowing anyone to inspect their reading lists even without being logged in. I checked the Goodreads scraping rules and was good to go. Before you continue, I invite you to predict the following: 3 from the 10 most read books, except Doing Good Better a book that relatively many EAs want to read, but few have actually read Finally, if you have any further ideas for analysis, leave a comment and I’ll be happy to see what I can do. If you want access to the csv file or the Python script I used, I uploaded them here. In this screenshot you see the types of data I have. Most read books Here the books that our community already explored a bunch. I would not have expected 1984 and Superintelligence to make it to the Top 5. HPMOR being the least read Harry Potter novel is a slight disappointment. Most planned to read Many classics on people’s I want to read this! lists, maybe overall slightly lengthier & more difficult books? Though Superforecasting is not too long and very readable and very excellent in my opinion, so feel free to read this one. Highest planned to read / have read ratio These are the books that might be more useful to be read by more EAs, as many say they want to read them, but in proportion the fewest people have actually read them. Of course, there are good reasons why some of those books are read less, e.g. some of them, like The Rise and Fall of American Growth, Probability Theory or The Feynman Lectures on Physics would take me enormously more time to read compared to, say, 1984 (which still took me, a relatively slow reader, something on the order of 10 to 20 hours). Also, the vast majority of the books in this list have only been read by one person, so a score of 11 can be interpreted as one person having read the book and 11 people wanting to read it. Additionally, as of now this list excludes books that have never been read by any EA, as the ratio would be infinite. For those books, see the next section. If we only allow books with at least 2 reads, we get this list: Most commonly planned to read books that have not been read by anyone yet I’ll consider it a big success of this project if some people will have read Julia Galef's The Scout Mindset Energy and Civilization next time I check. Highest rated books Here the highest rated of all books that were read at least 10 times. Not too many surprises here, EAs know what's good! Lowest rated books Here the same with the highest rated books. Before any fandom feels too ostracized (speaking as somebody who absolutely loved the Eragon saga), I should info...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Five New EA Charities with High Potential for Impact, published by by Joey on the Effective Altruism Forum. Write a Review Cross-posted from Charity Entrepreneurship blog. Hundreds of ideas researched, thousands of applications considered, and a two-month intensive Incubation Program culminated in five new charities being founded. Each of these charities has the potential to have a large impact on the world and to become one of the most cost-effective in their field. We’re delighted to announce the five new charities who have just launched through our 2020 Incubation Program: Lead Exposure Elimination Project (LEEP) - advocating for lead paint regulation to reduce lead poisoning and improve the health, well-being, and potential of children worldwide. Animal Ask - maximizing farmed animal asks through dedicated research. Family Empowerment Media (FEM) - enabling informed family planning and birth spacing decisions through clear, compelling, and accurate radio-based communication. Giving Green - directing dollars towards evidence-backed projects that combat the climate crisis. Canopie - bridging the mental health care gap for pre- and postpartum women through cost-effective, scalable, and evidence-based solutions. LEAD EXPOSURE ELIMINATION PROJECT (LEEP) Co-founders: Lucia Coulter, Jack Rafferty Website: leadelimination.org Contact: contact@leadelimination.org CE Incubation Grant: $60,000 Room for more funding: $25,000 Donation page: leadelimination.org/donate/ Description of the intervention: LEEP advocates for lead paint regulation to reduce lead poisoning and improve the health, well-being, and potential of children worldwide. Background of the intervention: One in three children has dangerous levels of lead in their bloodstream. This lead acts as a powerful toxin that causes irreversible harm to their brains and vital organs. It results in reduced intelligence, lower educational attainment, behavioral disorders, increased tendencies for violent crime, cardiovascular disease, and reduced lifetime earnings. The impact on cognitive development is responsible for an estimated $1 trillion of income loss per year in LMICs alone, while the health effects cause 1 million deaths and 22.4 million DALYs per year, accounting for 1% of the global burden of disease. A primary cause of lead exposure is lead paint, which is widespread and unregulated in over 100 countries. LEEP advocates for regulation of lead paint in countries with large and growing burdens of lead poisoning from paint, where no-one else is working on the issue. Their approach is to identify these countries, create incentives through awareness, and support governments to develop and introduce lead paint laws. For more details on LEEP, read their introductory post on the EA forum. To hear about their progress, sign up for their newsletter. Near-term plans: LEEP’s first priority is country selection to ensure they target tractable, high-burden, and neglected countries. They have so far identified Malawi as their most promising country on this basis. Over the next two months, LEEP will be testing the levels of lead in new paints on the market in Malawi and building relationships with stakeholders and decision-makers. Depending on findings and progress from this stage, they will either pilot their advocacy campaign in Malawi to introduce lead paint regulation, or pivot to another promising country. ANIMAL ASK Co-founders: George Bridgwater, Amy Odene Website: www.animalask.org Contact: info@animalask.org CE Incubation Grant: $100,000 Room for more funding: In early 2021 when we have evaluated our organizational worth to the movement, we may seek additional funding. Description of the intervention: Animal Ask was founded with the express aim to assist animal advocacy organizations in their efforts to reduce farmed an...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Can EA leverage an Elon-vs-world-hunger news cycle?, published by Jackson Wagner on the Effective Altruism Forum. Summary: Elon Musk promises to donate six billion dollars if the UN can explain how this would truly solve world hunger (it would probably be much more expensive). Regardless of whether the donation happens or not, a major news cycle about the cost-effectiveness of international charitable donations seems like a great opportunity to raise the public profile of effective altruism. Details of The Billionare-Bashing Drama US senators are currently debating a large bill that will probably include some form of tax increase on the rich. Elon Musk, now the world's richest man, voiced his opposition to a proposed tax on unrealized capital gains. He framed his oppositon specifically in terms of government inefficiency, saying: "Who is best at capital allocation -- government or entrepeneurs -- is indeed what it comes down to." More recently, a recent CNN headline asserted that just 2% of Elon Musk's ~$300B net worth could "solve world hunger" by feeding the 42 million people who suffer from malnutrition -- people who are otherwise "literally going to die". Inevitably, this claim turns out to be somewhat hyperbolic/innumerate -- 6 billion dollars divided by 42 million people is around $140 per person, which would be a lot lower than givewell's most effective interventions (around ~$5000 per life saved). Maybe this billionare-bashing CNN interview is revealing an astounding, hithero unknown charitable opportunity. But more likely, most of the people are not literally going to die and/or the effort to alleviate the problem would cost much more than $6 billion (at the very least, if we need to keep giving people food each year, the real cost would be $6 billion repeating annually). I haven't yet looked into the details of the situation too closely. Now, Elon has offered to indeed donate $6 billion, on the (presumably impossible) condition that the UN provide a realistic plan for how the problem of world hunger could legitimately be solved on that budget. For scale, six billion dollars devoted to EA cause areas would represent more than a 10% increase on the ~$42B total funds currently committed to the movement. Right now, EA organizations are spending spend about $0.2 billion on GiveWell-style global health charities each year. This Seems Like A Good Time For EA To Shine This conversation is already distinct from most billionare-related discorse for its focus on cost-effectiveness and international aid for the world's poorest, rather than the usual arguing over the fairness of allowing rich people to exist at all and the desire to increase taxes in order to fund more social services in the developed world. In short, for a brief moment in time, a major news cycle is focused on how one can do the most good to save the most lives per dollar. This obviously seems like a great time to introduce the ideas of effective altruism to more people. I can only imagine that Kelsey Piper is already busily drafting up an article about this for Future Perfect. But what else can EA do to capitalize on this news cycle? Should Givewell try to outline how they would attempt to spend six billion dollars? Surely their current top charities would run out of room-for-more-funding? Would it be wiser to stay on-message with a relatively simple theme, like promoting Givewell's expertise in cost-effective global health and development spending? Or should we try to fire off a bunch of thinkpieces climbing the counterintuitiveness ladder from typical disaster aid to growth economics, and from there onwards to longtermism, x-risk reduction, etc? What should EA's general strategy be around these news cycles -- the movement generally tries to avoid political polarization, but surely some events are go...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: If you like a post, tell the author!, published by Aaron Gertler on the Effective Altruism Forum. Write a Review I wonder whether I should write more comments pointing out what I liked in a post even if I don't have anything to criticise instead of just silently upvoting. - Denise Melchin I've heard this question quite a few times, and the answer is: Yes! Absolutely yes! Tell authors when you like something they've written! Imaginary case study Consider the experience of a Forum author who writes a post most readers like, in a world where people only comment if they have a critique. They go to the Forum and see a string of comments: "You're wrong about A." "You're wrong about B." "Why didn't you mention C?" The post could have dozens of upvotes, but if it looks like anyone who closely engaged with it found something to criticize, the author may not feel great about their work. (This doesn't mean that criticism isn't valuable: If you find something to criticize, you should also probably tell the author.) In a world where people share what they like about posts, the comments might be: "You're wrong about A." "I see what the above poster means about point A1, but I thought point A2 was actually an interesting take, and could be correct under assumption Q." "I hadn't read this post you linked to — thanks for the reference!" "You're wrong about B." "I really liked your discussion of B!" "Why didn't you mention C?" "Your points about D and E were really helpful for a project I'm working on." The criticism still exists, but I'd expect the author to feel better about responding if they know the post was valuable to some readers. Also, positive reactions are useful feedback in their own right! Frequently asked questions What if my positive comment is just "thanks, I enjoyed this?" Still good! Even a generic nice comment will be much more salient to most authors than a silent upvote. What if my positive comment just takes up space in a way that distracts from more important critical discussion and intellectual progress and whatnot? This is paraphrased from things I've actually heard when talking to Forum users. While I understand the concern, I must emphasize that the Forum exists on the Internet, a system of interconnected computer networks where space is effectively unlimited. We also offer the "scrollbar," a feature people can use to skip over comments they don't want to read or discuss. If someone finds your positive comment distracting, they can scroll past it. But there's at least one person who probably won't find it distracting — the author. Conclusion If you like a post, tell the author! If you don't like a post, it's also fine to tell the author! But at the very least, let's try to make sure authors don't get a negatively-skewed view of how people think about their posts. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Matt Levine on the Archegos failure, published by Kelsey Piper on the Effective Altruism Forum. Matt Levine is a finance writer with a very entertaining free newsletter, also available on Bloomberg to subscribers. Today's newsletter struck me as a fairly remarkable failure analysis of a very expensive failure, in which Credit Suisse lost $5.5billion dollars when the hedge fund Archegos collapsed. That doesn't usually happen, and banks are, of course, very incentivized to avoid it. When it happened, Credit Suisse commissioned a very thorough investigation into what went wrong. Some background: Archegos was a hedge fund, founded in 2013, that defaulted spectacularly this spring. The Wall Street Journal estimates that they lost $8billion in 10 days. Levine wrote at the time: The basic story of Archegos is that it extracted as much leverage as possible from a half dozen Wall Street banks to buy a concentrated portfolio of tech and media stocks (apparently partially hedged with short index positions[2]), and those stocks went up a lot, before going down a lot. If you merely own some stocks, and they go way up and then way down, you'll end with approximately the money you started with and everything will be fine. But if you have taken out loans to buy stocks, then when they go up your wealth has increased. And if you then use your increased wealth to borrow lots more money and buy more stocks, then when they go down you will lose $8billion in ten days. None of this is unknown to bankers, so it's confusing that the bankers let Archegos do this. In the immediate aftermath, there was a lot of theorizing about how the banks might have had inaccurate or incomplete information about how heavily leveraged Archegos was. Levine: When the Archegos story came out this spring, there was a sense, from the outside, that the banks had missed something, that there was some structural component of Archegos’s trades that caused the banks to underestimate the risks they were taking. For instance, there was a widespread theory that, because Archegos did most of its trades in the form of total return swaps (rather than owning stocks directly), it didn’t have to disclose its positions publicly, and because it did those swaps with multiple banks, none of the banks knew how big and concentrated Archegos’s total positions were, so they didn’t know how bad it would be if Archegos defaulted. But, nope, absolutely not, Credit Suisse was entirely plugged in to Archegos’s strategy and how much trading it was doing with other banks, and focused clearly on this risk. So what went wrong? According to the report Credit Suisse commissioned from a law firm on the whole mess, what went wrong is that Credit Suisse determined that Archegos was overleveraged, and that they needed more collateral, and they called Archegos to that effect, and Archegos responded "hey sorry I've been swamped this week, can we talk later?" and that was that. No, really, that's pretty much it. The report: On February 23, 2021, the PSR analyst covering Archegos reached out to Archegos’s Accounting Manager and asked to speak about dynamic margining. Archegos’s Accounting Manager said he would not have time that day, but could speak the next day. The following day, he again put off the discussion, but agreed to review the proposed framework, which PSR sent over that day. Archegos did not respond to the proposal and, a week-and-a-half later, on March 4, 2021, the PSR analyst followed up to ask whether Archegos “had any thoughts on the proposal.” His contact at Archegos said he “hadn’t had a chance to take a look yet,” but was hoping to look “today or tomorrow.” Of course, when your counterparty is refusing to give you more collateral, you can pull all their loans. But Credit Suisse was kind of reluctant to pull that lever given that it wa...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Movement Collapse Scenarios, published by rebecca_baronon the Effective Altruism Forum. Epistemic status: I mostly want to provide a starting point for discussion, not make any claims with high confidence. Introduction and summary It’s 2024. The effective altruism movement no longer exists, or is no longer doing productive work, for reasons our current selves wouldn’t endorse. What happened, and what could we have done about it in 2019? I’m concerned not to hear this question discussed more often (though CEA briefly speculates on it here). It’s a prudent topic for a movement to be thinking about at any stage of its life cycle, but our small, young, rapidly changing community should be taking it especially seriously—it’s very hard to say right now where we’ll be in five years. I want to spur thinking on this issue by describing four plausible ways the movement could collapse or lose much of its potential for impact. This is not meant to be an exhaustive list of scenarios, nor is it an attempt to predict the future with any sort of confidence—it’s just an exploration of some of the possibilities, and what could logically lead to what. Sequestration: The EAs closest to leadership become isolated from the rest of the community. They lose a source of outside feedback and a check on their epistemics, putting them at a higher risk of forming an echo chamber. Meanwhile, the rest of the movement largely dissolves. Attrition: Value drift, burnout, and lifestyle changes cause EAs to drift away from the movement one by one, faster than they can be replaced. The impact of EA tapers, though some aspects of it may be preserved. Dilution: The movement becomes flooded with newcomers who don’t understand EA’s core concepts and misapply or politicize the movement’s ideas. Discussion quality degrades and “effective altruism” becomes a meaningless term, making the original ideas impossible to communicate. Distraction: The community becomes engrossed in concerns tangential to impact, loses sight of the object level, and veers off track of its goals. Resources are misdirected and the best talent goes elsewhere. Below, I explore each scenario in greater detail. Sequestration To quote CEA’s three-factor model of community building, Some people are likely to have a much greater impact than others. We certainly don’t think individuals with more resources matter any more as people, but we do think that helping direct their resources well has a higher expected value in terms of moving towards CEA’s ultimate goals. However, good community building is about inclusion, whereas good prioritization is about exclusion and It might be difficult in practice for us to be elitist about the value someone provides whilst being egalitarian about the value they have, even if the theoretical distinction is clear. I don’t want to be seen as arguing for any position in the debate about whether and how much to prioritize those who appear most talented—a sufficiently nuanced writeup of my thoughts would distract from my main point here. However, I do want to highlight a possible risk of too much elitism that I haven’t really seen talked about. The terms “core” and “middle” are commonly used here, but I generally find their use conflates level of involvement or commitment with level of prominence or authority. In this post I’ll be using the following definitions: Group 1 EAs are interested in effective altruism and may give effectively or attend the occasional meetup, but don’t spend much time thinking about EA or consider it a crucial part of their identities and their lives. Group 2 EAs are highly dedicated to the community and its project of making the world a better place; they devour EA content online and/or regularly attend meetups. However, they are not in frequent contact with EA decision-makers. Group 3 EA...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is:Some promising career ideas beyond 80,000 Hours' priority paths, published by Ardenlk on the Effective Altruism Forum. Write a Review This is a sister post to "Problem areas beyond 80,000 Hours' current priorities". Introduction In this post, we list some more career options beyond our priority paths that seem promising to us for positively influencing the long-term future. Some of these are likely to be written up as priority paths in the future, or wrapped into existing ones, but we haven't written full profiles for them yet—for example policy careers outside AI and biosecurity policy that seem promising from a longtermist perspective. Others, like information security, we think might be as promising for many people as our priority paths, but because we haven't investigated them much we're still unsure. Still others seem like they'll typically be less impactful than our priority paths for people who can succeed equally in either, but still seem high-impact to us and like they could be top options for a substantial number of people, depending on personal fit—for example research management. Finally some—like becoming a public intellectual—clearly have the potential for a lot of impact, but we can't recommend them widely because they don't have the capacity to absorb a large number of people, are particularly risky, or both. We compiled this list by asking 6 advisers about paths they think more people in the effective altruism community should explore, and which career ideas they think are currently undervalued—including by 80,000 Hours. In particular, we were looking for paths that seem like they may be promising from the perspective of positively shaping the long-term future, but which aren't already captured by aspects of our priority paths. If something was suggested twice and also met those criteria, we took that as a presumption in favor of including it. We then spent a little time looking into each one and put together a few thoughts and resources for those that seemed most promising. The result is the list below. We'd be excited to see more of our readers explore these options, and plan on looking into them more ourselves. Who is best suited to pursue these paths? Of course the answer is different for each one, but in general pursuing a career where less research has been done on how to have a large impact within it—especially if few of your colleagues will share your perspective on how to think about impact—may require you to think especially critically and creatively about how you can do an unusual amount of good in that career. Ideal candidates, then, would be self-motivated, creative, and inclined to think rigorously and often about how they can steer toward the highest impact options for them—in addition to having strong personal fit for the work. What are the pros and cons of each of these paths? Which are less promising than they might at first appear? What particular routes within each one are the most promising and which are the least? What especially promising high-impact career ideas is this list missing? We're excited to read people's reactions in the comments. And we hope that for people who want to pursue paths outside those we talk most about, this list can give them some fruitful ideas to explore. Career ideas we're particularly excited about beyond our priority paths Become a historian focusing on large societal trends, inflection points, progress, or collapse We think it could be high-impact to study subjects relevant to the long-term arc of history—e.g, economic, intellectual, or moral progress from a long-term perspective, the history of social movements or philanthropy, or the history of wellbeing. Better understanding long trends and key inflection points, such as the industrial revolution, may help us understand what could cause other im...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Estimates of global captive vertebrate numbers, published by saulius on the Effective Altruism Forum. Write a Review In this article, I list all the estimates I could find for numbers of vertebrates that are farmed or kept in captivity for various purposes. I also describe some groups of captive vertebrates for which I found no estimates. For some bigger groups of animals that are less well-known amongst animal activists, I also describe trends and main welfare concerns. The purpose of the article is to make it easier to find and compare estimates. Hopefully, this can also help animal advocates decide which issues to focus on. Note that I chose to focus on captive vertebrates simply to limit the scope of the article. Summary tables Estimates are summarized in the tables below. Numbers can also be explored in this spreadsheet. The rest of the article provides sources and explanations for these numbers. All figures are for the whole world unless otherwise specified. For brevity, I use M for a million (10^6) and B for a billion (10^9). Reptiles and amphibians table Fish table Note that all the numbers above exclude shellfish. I’ve found no estimates for : fish used as live bait in commercial fishing, fish trapped in nets and traps, fish hooked on hooks in commercial and recreational fisheries, food fish transported alive, other species of wild-caught fish suffocating in the air after landing. Chickens table Most of the 68.8B slaughtered chickens were raised specifically for meat, but the figure seems to include at least some slaughtered chickens from the egg-laying industry (see the appendix in Šimčikas (2019a)). According to FAOSTAT, in total there were 23.7B chickens alive in 2018. Other birds table I haven’t found estimates for the number of: ducks and geese live-plucked for their feathers and down, swiftlets farmed for their nests, ostriches farmed for meat Mammals table I haven’t tried finding the number of: animals raised in other pet mills (kitten mills, rabbit mills, etc.), animals raised in more humane pet breeding facilities, household rodent pests caught in traps, civets used to make civet coffee, elk farmed for food. Mixed species table I haven’t estimated the number of animals who are: kept alive in food markets, captured or captive-bred to be released into the wild as a Buddhist ritual to earn good karma (fangsheng), raised to be hunted in countries other than the UK, used in circuses outside of Europe, used for racing, fighting, and other forms of entertainment, kept in wildlife rehabilitation clinics, land animals bred in captivity to be released into the wild for species reintroduction programs. various species of animals kept in wildlife farms (see Standaert (2020)) Pets The table below presents Euromonitor International data, which has estimates of the number of pets in 53 countries,[1] which account for about 70% of the world’s human population. table If estimates in tables above seem difficult to compare and comprehend, it may be useful to look at the appendix where I convert estimates into units of time. Estimates can also be explored in this spreadsheet. Explanation of uncertainty levels In the ‘Uncertainty’ columns in the tables above, I describe the uncertainty for each estimate as low, moderate, high, or very high. Here is roughly what I mean by these words: Low - the estimate comes from a trustworthy source that explains how it arrived at the estimate. I’d be surprised if the estimate was off by a factor of 1.5 or more. In cases I provide a point estimate (e.g., “1M”), this means that I’d be surprised if the actual number was more than 1.5 times smaller or larger than the estimate. In cases where I provide a range (e.g., “1M–2M”), this means that I’d be surprised if the real number was more than 1.5 times larger than the upper bound or more th...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Does Economic History Point Toward a Singularity?, published by Ben Garfinkel on the Effective Altruism Forum. Write a Review I’ve ended up spending quite a lot of time researching premodern economic growth, as part of a hobby project that got out of hand. I’m sharing an informal but long write-up of my findings here, since I think they may be relevant to other longtermist researchers and I am unlikely to write anything more polished in the near future. Click here for the Google document.[1] Summary Over the next several centuries, is the economic growth rate likely to remain steady, radically increase, or decline back toward zero? This question has some bearing on almost every long-run challenge facing the world, from climate change to great power competition to risks from AI. One way to approach the question is to consider the long-run history of economic growth. I decided to investigate the Hyperbolic Growth Hypothesis: the claim that, from at least the start of the Neolithic Revolution up until the 20th century, the economic growth rate has tended to rise in proportion with the size of the global economy.[2] This claim is made in a classic 1993 paper by Michael Kremer. Beyond influencing other work in economic growth theory, it has also recently attracted significant attention within the longtermist community, where it is typically regarded as evidence in favor of further acceleration.[3] An especially notable property of the hypothesized growth trend is that, if it had continued without pause, it would have produced infinite growth rates in the early twenty-first century. I spent time exploring several different datasets that can be used to estimate pre-modern growth rates. This included a number of recent archeological datasets that, I believe, have not previously been analyzed by economists. I wanted to evaluate both: (a) how empirically well-grounded these estimates are and (b) how clearly these estimates display the hypothesized pattern of growth. Ultimately, I found very little empirical support for the Hyperbolic Growth Hypothesis. While we can confidently say that the economic growth rate did increase over the centuries surrounding the Industrial Revolution, there is approximately nothing to suggest that this increase was the continuation of a long-standing hyperbolic trend. The alternative hypothesis that the modern increase in growth rates constituted a one-off transition event is at least as consistent with the evidence. The premodern growth data we have is mostly extremely unreliable: For example, so far as I can tell, Kremer’s estimates for the period between 10,000BC and 400BC ultimately derive from a single speculative paragraph in a book published decades earlier. Putting aside issues of reliability, the various estimates I considered also, for the most part, do not clearly indicate that pre-modern growth was hyperbolic. The most empirically well-grounded datasets we have are at least weakly in tension with the hypothesis. Overall, though, I think we are in a state of significant ignorance about pre-modern growth rates. Beyond evaluating these datasets, I also spent some time considering the growth model that Kremer uses to explain and support the Hyperbolic Growth Hypothesis. One finding is that if we use more recent data to estimate a key model parameter, the model may no longer predict hyperbolic growth: the estimation method that we use matters. Another finding, based on some shallow reading on the history of agriculture, is that the model likely overstates the role of innovation in driving pre-modern growth. Ultimately, I think we have less reason to anticipate a future explosion in the growth rate than might otherwise be supposed.[4][5] EDIT: See also this addendum comment for an explanation of why I think the alternative "phase transition" ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: List of EA funding opportunities, published by MichaelA on the Effective Altruism Forum. This is a quickly written post listing opportunities for people to apply for funding from funders that are part of the EA community. I'm probably forgetting some opportunities relevant to longtermist and EA movement building work, and many opportunities relevant to other cause areas. Please comment if you know of things I’m missing! Maybe a list like this already exists; if so, please comment to mention it! Two somewhat similar things are the 80,000 Hours job board and Effective Thesis’s list of funding opportunities. I strongly encourage people to consider applying for one or more of these things. Given how quick applying often is and how impactful funded projects often are, applying is often worthwhile in expectation even if your odds of getting funding aren’t very high. (I think the same basic logic applies to job applications.) It'd probably be useful for someone to make a separate collection of non-EA funding opportunities that would be well-suited to EA-aligned projects. But such things are included in this post. I follow the name of each funding opportunity with some text from the linked page. I wrote this post in a personal capacity, not as a representative of any of the orgs mentioned. See also Things I often tell people about applying to EA Funds. EDIT: JJ Hepburn has now created an Airtable with similar info, which you can view the outputs of here. That currently complements this post, and could supersede this post if someone takes ownership of adding things there, updating the info, and ironing out potential glitches. Please contact me if you're interested in doing that. Currently open Open Phil funding opportunities Request for proposals for growing the community of people motivated to improve the long-term future “We are seeking proposals from applicants interested in growing the community of people motivated to improve the long-term future via the kinds of projects described below. Apply to start a new project here; express interest in helping with a project here. Applications are open until further notice and will be assessed on a rolling basis. If we plan to stop accepting applications, we will indicate it on this page at least a month ahead of time. See this post for additional details about our thinking on these projects.” Open Philanthropy Undergraduate Scholarship “Apply here (see below for details regarding application deadlines). This program aims to provide support for highly promising and altruistically-minded students who are hoping to start an undergraduate degree at one of the top universities in the USA or UK (see below for details) and who do not qualify as domestic students at these institutions for the purposes of admission and financial aid.” Open Philanthropy Course Development Grants “This program aims to provide grant support to academics for the development of new university courses (including online courses). At present, we are looking to fund the development of courses on a range of topics that are relevant to certain areas of Open Philanthropy’s grantmaking that form part of our work to improve the long-term future (potential risks from advanced AI, biosecurity and pandemic preparedness, other global catastrophic risks), or to issues that are of cross-cutting relevance to our work. We are primarily looking to fund the development of new courses, but we are also accepting proposals from applicants who are looking for funding to turn courses they have already taught in an in-person setting into freely-available online courses. Applications are open until further notice and will be assessed on a rolling basis. APPLY HERE” Early-career funding for individuals interested in improving the long-term future “This program aims to provide support - p...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Effective Altruism is a Question (not an ideology), published by Helen on the Effective Altruism Forum. Write a Review What is the definition of Effective Altruism? What claims does it make? What do you have to believe or do, to be an Effective Altruist? I don’t think that any of these questions make sense. It’s not surprising that we ask them: if you asked those questions about feminism or secularism, Islamism or libertarianism, the answers you would get would be relevant and illuminating. Different proponents of the same movement might give you slightly different answers, but synthesising the answers of several people would give you a pretty good feeling for the core of the movement. But each of these movements is answering a question. Should men and women be equal? (Yes.) What role should the church play in governance? (None.) What kind of government should we have? (One based on Islamic law.) How big a role should government play in people’s private lives? (A small one.) Effective Altruism isn’t like this. Effective Altruism is asking a question, something like: “How can I do the most good, with the resources available to me?” There are some excellent introductions to Effective Altruism out there. They often outline common conclusions that Effective-Altruism-style thinking leads to: things like earning to give, or favouring interventions in poorer countries over those in richer countries. This makes sense - Effective Altruism does seem to imply that those things are a good idea - but it doesn't make the conclusions part of the core of the movement. What does this mean for how we think and talk about Effective Altruism? Reframing Effective Altruism as a question has some pretty significant implications. These aren’t necessarily new – some people already act on the points below. But I think they are worth thinking about explicitly. 1. We should try to avoid calling ourselves “effective altruists” Feminist, secularist, Islamist, environmentalist... it’s not surprising that people who think Effective Altruism is interesting and important want to switch the “-ism” into an “-ist”, and use it to refer to themselves. The linguistic part of our brain does it automatically. But there’s a big problem with this. “Effective Altruism” is a carefully and cleverly chosen name, and it describes its own core question succinctly. But it does this by combining a common adjective with a common noun, which means that changing the last syllable gives you not an identifier, but a truth claim. “I am an effective altruist” may sound to the speaker like “I think Effective Altruism is really important”, but to the listener, it sounds like “I perform selfless acts in a manner that is successful, efficient, fruitful or efficacious.” (Thesauruses are fun!) Effective Altruism is already a slightly impudent name, since its claim to be a ground-breaking idea rests on the premise that other altruism is ineffective. Calling oneself an effective altruist is much worse. As well as provoking scepticism or hostility, it automatically leads into questions like “Can I [x] and still be an effective altruist?” “How much do I have to donate to be an effective altruist?” “How does an effective altruist justify spending money on anything beyond bare survival?” These questions feel like they should have meaningful answers, but trying to answer them probably won't get us very far. Alternative descriptors include “aspiring effective altruist”, “interested in Effective Altruism”, “member of the Effective Altruism movement”. What do you think of those options? Do you have others? When could it still be appropriate to use “effective altruist”? 2. Our suggested actions and causes are best guesses, not core ideas It’s extremely important that Effective Altruism does get translated into actions in the real world. To d...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: My personal cruxes for working on AI safety, published by Buck on the Effective Altruism Forum. Write a Review The following is a heavily edited transcript of a talk I gave for the Stanford Effective Altruism club on 19 Jan 2020. I had rev.com transcribe it, and then Linchuan Zhang, Rob Bensinger and I edited it for style and clarity, and also to occasionally have me say smarter things than I actually said. Linch and I both added a few notes throughout. Thanks also to Bill Zito, Ben Weinstein-Raun, and Howie Lempel for comments. I feel slightly weird about posting something so long, but this is the natural place to put it. Over the last year my beliefs about AI risk have shifted moderately; I expect that in a year I'll think that many of the things I said here were dumb. Also, very few of the ideas here are original to me. After all those caveats, here's the talk: Introduction It's great to be here. I used to hang out at Stanford a lot, fun fact. I moved to America six years ago, and then in 2015, I came to Stanford EA every Sunday, and there was, obviously, a totally different crop of people there. It was really fun. I think we were a lot less successful than the current Stanford EA iteration at attracting new people. We just liked having weird conversations about weird stuff every week. It was really fun, but it's really great to come back and see a Stanford EA which is shaped differently. Today I'm going to be talking about the argument for working on AI safety that compels me to work on AI safety, rather than the argument that should compel you or anyone else. I'm going to try to spell out how the arguments are actually shaped in my head. Logistically, we're going to try to talk for about an hour with a bunch of back and forth and you guys arguing with me as we go. And at the end, I'm going to do miscellaneous Q and A for questions you might have. And I'll probably make everyone stand up and sit down again because it's unreasonable to sit in the same place for 90 minutes. Meta level thoughts I want to first very briefly talk about some concepts I have that are about how you want to think about questions like AI risk, before we actually talk about AI risk. Heuristic arguments When I was a confused 15 year old browsing the internet around 10 years ago, I ran across arguments about AI risk, and I thought they were pretty compelling. The arguments went something like, "Well, sure seems like if you had these powerful AI systems, that would make the world be really different. And we don't know how to align them, and it sure seems like almost all goals they could have would lead them to kill everyone, so I guess some people should probably research how to align these things." This argument was about as sophisticated as my understanding went until a few years ago, when I was pretty involved with the AI safety community. I in fact think this kind of argument leaves a lot of questions unanswered. It's not the kind of argument that is solid enough that you'd want to use it for mechanical engineering and then build a car. It's suggestive and heuristic, but it's not trying to cross all the T's and dot all the I's. And it's not even telling you all the places where there's a hole in that argument. Ways heuristic arguments are insufficient The thing which I think is good to do sometimes, is instead of just thinking really loosely and heuristically, you should try to have end-to-end stories of what you believe about a particular topic. And then if there are parts that you don't have answers to, you should write them down explicitly with question marks. I guess I'm basically arguing to do that instead of just saying, "Oh, well, an AI would be dangerous here." And if there's all these other steps as well, then you should write them down, even if you're just going to have your just...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: List of EA-related organisations, published by JamieGittins on the Effective Altruism Forum. Write a Review Update: After some suggestions in the comments I made a wiki, which anyone can add to. Hopefully this will enable us to keep the list up to date. I’ve constantly been discovering new, exciting organisations in the years since I got involved in EA. Recently, I came across WANBAM (Women and Non-Binary Altruism Mentors) and wished that I’d known about it sooner, so I could’ve started recommending it to people who I thought would be interested. It then occurred to me that people probably have similar experiences all the time in EA. I couldn’t find a comprehensive list of EA-related organisations that already existed, so I decided to make one. By collecting as many EA-related organisations as I can into one place, I hope I can help some people to discover some exciting orgs that they wouldn’t have otherwise! What this is: A list of organisations that are aligned with some of EA’s key principles. The organisations I have included tend to meet a least one of these criteria: Have explicitly aligned themselves with EA Are currently recommended by GiveWell or Animal Charity Evaluators Were incubated by Charity Entrepreneurship Have engaged with the EA community (e.g. by posting on the EA Forum or attending EA Global) What this is not: A comprehensive list of every organisation which should be considered ‘EA-aligned’. I don’t think this is a useful or even possible distinction to make, since many organisations lie on a continuum of commitment to EA values. As is obvious from scrolling the 80,000 Hours job board, there are many thousands of organisations out there which do effective work in EA cause areas. I have not included EA projects which don’t hire staff, or which are national/local EA groups (some of which hire paid staff) to keep the list more straightforward. Despite my best efforts, I imagine I’ve accidentally left off some organisations which should be on here (or potentially added some which shouldn’t be), so I welcome any comments with suggestions of changes! Infrastructure 80,000 Hours – Does research into how people can have greater impact with their careers. Also maintains a high impact jobs board and produces a podcast. Animal Advocacy Careers – Seeks to address the career and talent bottlenecks in the animal advocacy movement, especially the farmed animal movement, by providing career services and advice. Incubated by Charity Entrepreneurship. Animal Charity Evaluators (ACE) – Evaluates and recommends the most effective animal charities. Ayuda Efectiva - Promotes effective giving in Spain. Their Global Health Fund routes donations to a selection of GiveWell's recommended charities, providing tax deductibility for Spanish donors. They plan to launch similar funds for other cause areas in the near future. Centre for Effective Altruism (CEA) – Helps to grow and support the EA community. Charity Entrepreneurship – Does research into the most effective interventions and incubates charities to implement these interventions. Doebem - A Brazilian-based donation platform which recommends effective charities according to EA principles. Donational - A donation platform which recommends effective charities to users, and helps them to pledge and allocate a proportion of their income to those charities. Effective Altruism Foundation (EAF) – Implements projects aimed at doing the most good in terms of reducing suffering. Once initiated, projects are carried forward by EAF with differing degrees of independence and in some cases become autonomous organisations. Projects have included Raising for Effective Giving (REG) and the Centre on Long-Term Risk (CLR). Effective Giving UK/Netherlands – Helps major donors to find and fund the most promising solutions to the world’s m...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Humanities Research Ideas for Longtermists, published by Lizka on the Effective Altruism Forum. Summary This post lists 10 longtermism-relevant project ideas for people with humanities interests or backgrounds. Most of these ideas are for research projects, but some are for summaries, new outreach content, etc. (See below for what I mean by “humanities.”) The ideas, in brief: Study future-oriented beliefs in certain religions or groups Study the ways in which incidental qualities become essential to institutions Explore fiction as a tool for moral circle expansion Study how longtermists use different forms of media and how this might be improved Study how non-EAs actually view AI safety issues, and how we got here Produce anthropological/ethnographic studies of unusually relevant groups Apply insights from education, history, and development studies to creating a post-societal-collapse recovery plan Study notions of utopias Analyze social media (and online forums) in the context of longtermism Use tools from non-history humanities fields to aid history-oriented projects relevant for longtermism Why it might be helpful to produce lists of projects for people with humanities backgrounds (or interests) to work on Deliberately looking for and studying topics that are humanities-oriented could be a way to discover longtermist interventions that are hard to notice or tackle from other angles (e.g., a STEM angle), improve our views on known causes and interventions, and find topics that are better fits for some people than existing (non-humanities) project ideas would be. If it is relatively easy to produce such lists, it suggests that we are systematically missing humanities ideas and tools from our reasoning, and that this gap is not explainable by a natural disconnect between longtermist values or concerns and non-STEM areas.[1] (If we had exhausted humanities approaches to longtermism, it would probably be hard to find previously unnoticed topics that seem reasonable.) It seems valuable to have diversity in backgrounds and perspectives, and the existence of this gap suggests that supporting humanities projects might be a way to improve on that front. Collections like this can consolidate existing ideas and resources in one place, making it easier to find projects and collaborate as a community. I am aware of talented people who have been put off EA (and longtermism) due to their general sense that the humanities are considered worthless. My sense is that EAs do see value in the humanities, and it might be worth making this clearer. (Personal note) this project was helpful for me as a way to explore longtermist research. Scope and disclaimers The focus of the post is on the humanities disciplines most neglected in EA and longtermism, so I excluded history, philosophy, and psychology. (Those might also be neglected in the community, but there has been at least some mention of how they could be relevant for longtermism in places like the Forum.)[2] My use of the word “humanities'' is loose—for this project, I accepted some fields that might be considered social sciences instead. In practice, I think the ideas listed here are most related to anthropology, archival studies, area studies, art history, (comparative) literature, (comparative) religion studies/theology, education, and media studies. The list is not meant to be exhaustive by any means; in particular, the selection of topics here is heavily influenced by my own academic background (literature, sort-of-history, art, math). Some of the ideas are ideas for bringing existing research into EA rather than ideas for producing totally new research. It is also important to note that I have very little background in most of the areas involved in this list, and I wouldn't be surprised if deeper research discovered that some ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: A personal take on longtermist AI governance, published by lukeprog on the Effective Altruism Forum. Several months ago, I summarized Open Philanthropy's work on AI governance (which I lead) for a general audience here. In this post, I elaborate my thinking on AI governance in more detail for people who are familiar with effective altruism, longtermism, existential risk, and related topics. Without that context, much of what I say below may be hard to understand, and easy to misunderstand. These are my personal views, and don't necessarily reflect Open Phil's views, or the views of other individuals at Open Phil. In this post, I briefly recap the key points of my previous post, explain what I see as the key bottlenecks in the space, and share my current opinions about how people sympathetic to longtermism and/or AI existential risk mitigation can best contribute today. Open Phil's AI governance work so far (a recap) First, some key points from my previous post: In practice, Open Phil's grantmaking in Potential Risks from Advanced Artificial Intelligence is split in two: One part is our grantmaking in "AI alignment," defined here as "the problem of creating AI systems that will reliably do what their designers want them to do even when AI systems become much more capable than their designers across a broad range of tasks."[1] The second part, which I lead, is our grantmaking in "AI governance," defined here as "local and global norms, policies, laws, processes, politics, and institutions (not just governments) that will affect social outcomes from the development and deployment of AI systems." Our AI focus area is part of our longtermism-motivated portfolio of grants,[2] and we focus on AI alignment and AI governance grantmaking that seems especially helpful from a longtermist perspective. On the governance side, I sometimes refer to this longtermism-motivated subset of work as "transformative AI governance" for relative concreteness, but a more precise concept for this subset of work is "longtermist AI governance."[3] It's difficult to know which “intermediate goals” we could pursue that, if achieved, would clearly increase the odds of eventual good outcomes from transformative AI (from a longtermist perspective). As such, our grantmaking so far tends to focus on: .research that can help clarify how AI technologies may develop over time, and which intermediate goals are worth pursuing. .research and advocacy aimed at the few intermediate goals we've come to think are clearly worth pursuing, such as particular lines of AI alignment research, and creating greater awareness of the difficulty of achieving high assurance in the safety and security of increasingly complex and capable AI systems. .broad field-building activities, for example scholarships, career advice for people interested in the space, professional networks, etc.[4] .training, advice, and other support for actors with plausible future impact on transformative AI outcomes, as always with a focus on work that seems most helpful from a longtermist perspective. Key bottlenecks Since our AI governance grantmaking began in ~2015,[5] we have struggled to find high-ROI grantmaking opportunities that would allow us to move grant money into this space as quickly as we'd like to.[6] As I see it, there are three key bottlenecks to our AI governance grantmaking. Bottleneck #1: There are very few longtermism-sympathetic people in the world,[7] and even fewer with the specific interests, skills, and experience to contribute to longtermist AI governance issues. As a result, the vast majority of our AI governance grantmaking has supported work by people who are (as far as I know) not sympathetic to longtermism (and may have never heard of it). However, it's been difficult to find high-ROI grantmaking opportunities of this...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: A cause can be too neglected, published by saulius on the Effective Altruism Forum. Write a Review Effective Altruism movement often uses a scale-neglectedness-tractability framework. As a result of that framework, when I discovered issues like baitfish, fish stocking, and rodents fed to pet snakes, I thought that it is an advantage that they are almost maximally neglected (seemingly no one is working on them). Now I think that it’s also a disadvantage because there are set-up costs associated with starting work on a new cause. For example: You first have to bridge the knowledge gap. There are no shoulders of giants you can stand on, you have to build up knowledge from scratch. Then you probably need to start a new organization where all employees will be beginners. No one will know what they are doing because no one has worked on this issue before. It takes a while to build expertise, especially when there are no mentors. If you need support, you usually have to somehow make people care about a problem they’ve never heard before. And it could be a problem which only a few types of minds are passionate about because it was neglected all this time (e.g. insect suffering). graph Now let’s imagine that someone did a cost-effectiveness estimate and concluded that some well-known intervention (e.g. suicide hotline) was very cost-effective. We wouldn’t have any of the problems outlined above: Many people already know how to effectively do the intervention and can teach others. We could simply fund existing organizations that do the intervention. If we found new organizations, it might be easier to fundraise from non-EA sources. If you talk about a widely known cause or intervention, it’s easier to make people understand what you are doing and probably easier to get funding. Note that we can still use EA-style thinking to make interventions more cost-effective. E.g. fund suicide hotlines in developing countries because they have lower operating costs. Conclusions We don’t want to create too many new causes with high set-up costs. We should consider finding and filling gaps within existing causes instead. However, I’m not writing this to discourage people from working on new causes and interventions. This is only a minor argument against doing it, and it can be outweighed by the value of information gained about how promising the new cause is. Furthermore, this post shows that if we don’t see any way to immediately make a direct impact when tackling a new issue (e.g. baitfish), it doesn’t follow that the cause is not promising. We should consider how much impact could be made after set-up costs are paid and more resources are invested. Opinions are my own and not the views of my employer. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Our plans for hosting an EA wiki on the Forum, published by Aaron Gertler on the Effective Altruism Forum. We are in the process of implementing a major project on the Forum — turning our current system of tags into a full-fledged “EA wiki”. Under this system, many of the tags used for posts will also serve as articles in the wiki. Many articles in the Wiki will also serve as tags that can be applied to articles. However, there are exceptions in both directions. Some tags don’t make sense as wiki articles (for example, “EA London Update”). And some articles are too narrow to be useful tags (for example, Abhijit Banerjee). These will be marked as “wiki only” — they can be found with the Forum’s search engine, but can’t be used to tag posts. The project is made possible by the work of Pablo Stafforini, who received an EA Infrastructure Fund grant to create an initial set of articles. Why is an EA wiki useful? EA content mostly takes the form of essays, videos, research papers, and other long-form content. If you want to find a simple definition of a term, or a brief summary of a cause area, you often have to find a particular blog post from 2012 or ask someone in the community. A wiki can serve as a collection of definitions and brief explanations that help people efficiently develop their understanding of EA’s ideas and community. It can also host more detailed articles that wouldn’t have a reason to exist elsewhere. Even if no one person wants to e.g. summarize all the major arguments to give now vs. later, ten people can each contribute a small portion of an article and get the same result. CEA tried to do some of this with EA Concepts, a proto-wiki with well-written articles on a range of topics. But the project was deprioritized at one point and never picked back up — mostly because it takes a lot of time and energy to create and maintain anything close to a complete list of important concepts in effective altruism. The EA Forum seems like a better way to do this, for a few reasons. Why host this on the EA Forum? There have been multiple attempts to create an EA wiki before, including EA Concepts, but none have really taken off. It’s hard to get the necessary volume of volunteer work to compile a strong encyclopedia on a topic as broad and complex as effective altruism. Building a new wiki on the EA Forum has a few advantages over using a separate website: Constant attention: Hundreds of people visit the Forum every day. While tag pages don’t get many edits now, we’ll be doing a lot of work to promote them over the next few months. Anyone who visits the Forum will be prompted to contribute; if even a small number decide to help, I think we’ll have a larger collection of volunteers than any past EA wiki project. Strong SEO: The effectivealtruism.org domain gets a lot of traffic, which means it tends to show up in search engines for relevant terms. Once we’ve set up a collection of heavily cross-linked wiki articles, I expect that the articles will begin to draw a lot of new visitors to the site. Automatic updates through tagging: While the whole “articles are tags” thing can feel weird at times, it also means that many articles will be attached to an ever-growing list of relevant posts. Professional support: The Forum is run by CEA and draws from the technical work of developers from both CEA and LessWrong. We constantly add new features, and if something breaks, we have the resources to fix it. CEA’s resources also allow us to provide incentives for Wiki editing (more news on that soon, but not in this post). What are the next steps? Pablo’s approach involves setting up as many relatively short articles as possible, to give editors something to work from. He started by creating ~150 “stubs”, or one-sentence articles, that he expects to develop in the coming months...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: The Long-Term Future Fund has room for more funding, right now , published by abergal on the Effective Altruism Forum. The Long-Term Future Fund is on track to approve $1.5M - $2M of grants this round. This is 3 - 4x what we’ve spent in any of our last five grant rounds and most of our current fund balance. We received 129 applications this round, desk rejected 33 of them, and are evaluating the remaining 96. Looking at our preliminary evaluations, I’d guess we’ll fund 20 - 30 of these. In our last comparable grant round, April 2019, we received 91 applications and funded 13, for a total of $875,150. Compared to that round: We’ve received more applications. (42% more than in April.) We’re likely to distribute more money per applicant, because several applications are for larger grants, and requested salaries have gone up. (The average grant request is ~$80K this round vs. ~$50K in April, and the median is ~$50K vs. ~$25K in April.) We’re likely to fund a slightly greater percentage of applications. (16% - 23% vs. 14% in April.) We’ve recently changed parts of the fund’s infrastructure and composition, and it’s possible that these changes have caused us to unintentionally lower our standards for funding. My personal sense is that this isn’t the case; I think the increased spending reflects an increase in the number of quality applications submitted to us, as well as changing applicant salaries. If you were considering donating to the fund in the past but were unsure about its room for more funding, now could be a particularly impactful time to give. I don’t know if my perceived increase in quality applications will persist, but I no longer think it’s implausible for the fund to spend $4M - $8M this year while maintaining our previous bar for funding. This is up from my previous guess of $2M. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: More EAs should consider “non-EA” jobs, published by abergal on the Effective Altruism Forum. The Long-Term Future Fund is on track to approve $1.5M - $2M of grants this round. This is 3 - 4x what we’ve spent in any of our last five grant rounds and most of our current fund balance. We received 129 applications this round, desk rejected 33 of them, and are evaluating the remaining 96. Looking at our preliminary evaluations, I’d guess we’ll fund 20 - 30 of these. In our last comparable grant round, April 2019, we received 91 applications and funded 13, for a total of $875,150. Compared to that round: We’ve received more applications. (42% more than in April.) We’re likely to distribute more money per applicant, because several applications are for larger grants, and requested salaries have gone up. (The average grant request is ~$80K this round vs. ~$50K in April, and the median is ~$50K vs. ~$25K in April.) We’re likely to fund a slightly greater percentage of applications. (16% - 23% vs. 14% in April.) We’ve recently changed parts of the fund’s infrastructure and composition, and it’s possible that these changes have caused us to unintentionally lower our standards for funding. My personal sense is that this isn’t the case; I think the increased spending reflects an increase in the number of quality applications submitted to us, as well as changing applicant salaries. If you were considering donating to the fund in the past but were unsure about its room for more funding, now could be a particularly impactful time to give. I don’t know if my perceived increase in quality applications will persist, but I no longer think it’s implausible for the fund to spend $4M - $8M this year while maintaining our previous bar for funding. This is up from my previous guess of $2M. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Announcing the Patient Philanthropy Fund, published by SjirH on the Effective Altruism Forum. Today, after nearly two years of preparations, Founders Pledge is launching the Patient Philanthropy Fund (PPF): a grantmaking vehicle that invests to give to safeguard and improve the long-term future. The PPF is incubated as a special trust within Founders For Good - the Founders Pledge UK entity. It is managed by a Management Committee consisting of purpose-aligned experts on timing of giving. Our aim is to further develop and grow it over the coming 10 years and eventually spin it out as a separate charitable entity. The Fund is open for contributions by non-FP-members via EA Funds. We are launching the PPF with $1m in pre-seed funding contributed by a list of Founding Partners and Supporters, including many EA community members. Please refer to the Fund's website for more information on its plans, governance structure, Management Committee, grant-making policy etc. And please share any feedback or questions you have on the PPF in the comments on this post, or reach out to sjir@founderspledge.com! Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: EA is vetting-constrained, published by toonalfrink on the Effective Altruism Forum. Write a Review Re: What to do with people? and After one year of applying for EA jobs: It is really, really hard to get hired by an EA organisation Epistemic status: just my personal impression. Please prove me wrong. So we know that: 1) In aggregate, there are billions of dollars in EA 2) There are lots of surplus talented people looking for EA work, that can't get it and I would like to add: 3) I estimate that there are at least 10-20 budding organisations that would love to use this money to get these people to work, and scale beyond their current size, and properly tackle the problem they aim to solve. I know at least 5 founders like that personally. So with all the ingredients in place for amazing movement growth, why isn't the magic happening? Knowing who to delegate to I agree with the idea that if you want to solve problems, you need to organise your system in a hierarchy, with some kind of divide-and-conquer strategy where a principal figures out the subproblems of a problem and delegates them to some agents, and recurse. One problem here is that, even if the agent is aligned, the principal needs some way to tell that the agent is capable of carrying out a problem to a certain standard. Different systems solve this problem in different ways. A company might have some standards for hiring and structurally review the performance of their employees. Academia relies on prestige and some metrics that are proxies of quality. The market gives the most money to those that sell the most popular products. Communities kick out members that cross boundaries, and deprive uninteresting people of attention. EA, by which I mean the established organisations of EA, does this kind of thing in two ways: by hiring directly, and by vetting projects. For the latter there are grantmakers. As professionals that have thought a lot about what projects need to happen, they take a long hard look at an application by a startup founder, and if they expect it to work out well, they fund it. Simple enough. The state of vetting in EA I want to clarify that none of the following is meant to be accusatory. Grantmaking sounds like one of the hardest jobs in the world, and projects are by no means entitled to EA money just because they call themselves EA. I hope that this post keeps a spirit of high trust, which I think is very important. So why aren't we seeing more new EA organisations getting funding? Two hypotheses come to mind: The “high standards” hypothesis. Grantmakers think that these new organisations just aren't up to standard, and they would therefore cause damage. Perhaps their model is that EA should retain a very high standard to make sure that the prestige of the movement stays intact. After all that's what the movement might need to influence big institutions like academia and government. The "vetting bottleneck" hypothesis. Grantmaking organisations are just way understaffed. It's not that they're sure that these organisations don't meet the bar, it's just that they can't verify that in time, so the safest option is to hold off on funding, or fund a more established organisation instead. In reality, it is probably a combination of both of these. Some anecdotal evidence: When one startup got rejected by a grantmaking organisation, and they pressed for feedback, there were told that "We do not possess the domain expertise to evaluate scalable existential risk reduction projects in the way that [other org] would be better placed to do." And "as such, we rely more on the strength and quality of references when modeling out the potential impact of projects." This was after they were invited to the interview stage. It suggests that grantmakers fall back on prestige because they don’t always have the...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: There's Lots More To Do, published by Jeff_Kaufman on the Effective Altruism Forum. Write a Review Benjamin Hoffman recently wrote a post arguing that "drowning children are rare": Stories such as Peter Singer's "drowning child" hypothetical frequently imply that there is a major funding gap for health interventions in poor countries, such that there is a moral imperative for people in rich-countries to give a large portion of their income to charity. There are simply not enough excess deaths for these claims to be plausible. As far as I can see, this pretty much destroys the generic utilitarian imperative to live like a monk and give all your excess money to the global poor or something even more urgent. Insofar as there's a way to fix these problems as a low-info donor, there's already enough money. Claims to the contrary are either obvious nonsense, or marketing copy by the same people who brought you the obvious nonsense. Spend money on taking care of yourself and your friends and the people around you and your community and trying specific concrete things that might have specific concrete benefits. Imagine that the best intervention out there was direct cash transfers to globally poor people. The amount of money that could be productively used here is very large: it would cost at least $1T to give $1k to each of the 1B poorest people in the world. This is very far from foundations already having more than enough money. That there are extremely poor people who can do far more with my money than I can is enough for me to give. While I also think there are other ways to spend money altruistically that have more benefit per dollar than cash transfers, this only strengthens the argument for helping. How does Ben reach the opposite conclusion? Reading his post several times it looks to me like two things: He's looking at "saving lives via preventing communicable, maternal, neonatal, and nutritional diseases" as the only goal. While it's a category of intervention that people in the effective altruism movement have talked about a lot, it's definitely not the only way to help people. If you were to completely eliminate deaths in this category it would be amazing and hugely beneficial, but there would still be people dying from other diseases, suffering in many non-fatal ways, and generally having poverty limit their options and potential. And that's without considering more speculative options like trying to keep us from killing ourselves off or generally trying to make the long-term future go as well as possible. He's setting a threshold of $5k for how much we'd be willing to pay to avert a death, which is much too low. I do agree there is some threshold at which you'd be very reasonable to stop trying to help others and just do what makes you happy. Where this threshold is depends on many things, especially how well-off you are, but I would expect it to be more in the $100k range than the $5k range for rich-country effective altruists. By comparison, the US Government uses ~$9M. I do think the "drowning children" framing isn't great, primarily because it puts you in a frame of mind where you expect that things will be much cheaper than they actually are (familiar), but also because it depends on being in a situation where only you can help and where you must act immediately. There's enough actual harm in the world that we don't need thought experiments to show why we should help. So while there aren't that many "drowning children", there is definitely a lot of work to do. (Crossposted from jefftk.com) Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Announcing the launch of the Happier Lives Institute, published by MichaelPlant on the Effective Altruism Forum. Write a Review Following months of work by a dedicated team of volunteers, I am pleased to announce the launch of the Happier Lives Institute, a new EA organisation which seeks to answer the question: ‘What are the most effective ways we can use our resources to make others happier?’ Summary The Happier Lives Institute is pioneering a new way of thinking about the central question of effective altruism - how can we benefit others as much as possible? We are approaching this through a ‘happiness lens’, using individuals’ reports of their subjective well-being as the measure of benefit. Adopting this approach indicates potential new priorities, notably that mental health emerges as a large and neglected problem. Our vision is a world where everyone lives their happiest life. Our mission is to guide the decision-making of those who want to use their resources to most effectively make lives happier. We aim to fulfill our mission by: 1. Searching for the most effective giving opportunities in the world for improving happiness. We are starting by investigating mental health interventions in low-income countries. 2. Assessing which careers allow individuals to have the greatest counterfactual impact in terms of promoting happier lives. Our approach Our work is driven by three beliefs. 1) We should do the most good we can We should use evidence and reason to determine how we can use our resources to benefit others the most. We follow the guiding principles of effective altruism: commitment to others, scientific mindset, openness, integrity, and collaborative spirit. 2) Happiness is what ultimately matters Philosophers use the word ‘well-being’ to refer to what is ultimately good for someone. We think well-being consists in happiness, defined as a positive balance of enjoyment over suffering. Understood this way, this means that when we reduce misery, we increase happiness. Further, we believe well-being is the only thing which is intrinsically good, that is, that matters in and of itself. Other goods, such as wealth, health, justice, and equality are instrumentally valuable: they are not valuable in themselves, but because and to the extent that they increase happiness. 3) Happiness can be measured The last few decades have seen an explosion of research into ‘subjective well-being’ (SWB), with about 170,000 books and articles published in the last 15 years. SWB is measured using self-reports of people’s emotional states and global evaluations of life satisfaction; these measures have been shown to be valid and reliable. We believe SWB scores are the best available measure of happiness; therefore, we should use these scores, rather than anything else (income, health, education, etc.) to determine what makes people happier. Specifically, we expect to rely on life satisfaction as the primary metric. This is typically measured by asking “Overall, how satisfied are you with your life nowadays?” (0 - 10). While we think measures of emotional states are closer to an ideal measure of happiness, far fewer data of this type is available. A longer explanation of our approach to measuring happiness can be found here. When we take these three beliefs together, the question: “How can we do the most good?” becomes, more specifically: “What are the most cost-effective ways to increase self-reported subjective well-being?” Our strategy Social scientists have collected a wealth of data on the causes and correlates of happiness. While there are now growing efforts to determine how best to increase happiness through public policy, no EA organisation has yet attempted to translate this information into recommendations about what the most effective ways are for private actors to make l...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: In praise of unhistoric heroism, published by rosehadshar on the Effective Altruism Forum. Write a Review Dorothea Brooke as an example to follow I once read a post by an effective altruist about how Dorothea Brooke, one of the characters in George Eliot’s Middlemarch, was an EA. There’s definitely something interesting about looking at the story like this, but for me this reading really missed the point when it concluded that Dorothea’s life had been “a tragic failure”.[1] I think that Dorothea’s life was in many ways a triumph of light over darkness, and that her success and not her failure is the thing we should take as a pattern. Dorothea dreamed big: she wanted to alleviate rural poverty and right the injustice she saw around her. In the end, those schemes came to nothing. She married a Radical MP, and in the process forfeited the wealth she could have given to the poor. She spent her life in small ways, “feeling that there was always something better which she might have done, if she had only been better and known better.” But she made the lives of those around her better, and she did good in the ways which were open to her. I think that the way in which Dorothea’s life is an example to us is best captured in the final lines of Middlemarch: “Her finely touched spirit had still its fine issues, though they were not widely visible. Her full nature, like that river of which Cyrus broke the strength, spent itself in channels which had no great name on the earth. But the effect of her being on those around her was incalculably diffusive: for the growing good of the world is partly dependent on unhistoric acts; and that things are not so ill with you and me as they might have been, is half owing to the number who lived faithfully a hidden life, and rest in unvisited tombs.” If this was said of me after I’d die, I’d think I’d done a pretty great job of things. A related critique of EA I think many EAs would not be particularly pleased if that was ‘all’ that could be said for them after they died, and I think that there is something worrying about this. One of the very admirable things about EAs is their commitment to how things actually go. There’s a recognition that big talk isn’t enough, that good intentions aren’t enough, that what really counts is what ultimately ends up happening. I think this is important and that it helps make EA a worthwhile project. But I think that when people apply this to themselves, things often get weird. I don’t spend that much time with my ear to the grapevine, but from my anecdotal experience it seems not uncommon for EAs to: obsess about their own personal impact and how big it is neglect comparative advantage and chase after the most impactful whatever conclude that they are a failure because their project is a failure or lower status than some other project generally feel miserable about themselves because they’re not helping the world more, regardless of whether they’re already doing as much as they can An example of a kind of thing I’ve heard several people say is ‘aw man, it sucks to realise that I’ll only ever have a tiny fraction of the impact Carl Shulman has’. There are many things I dislike about this, but in this context the thing that seems most off is that being Carl Shulman isn’t the game. Being you is the game, doing the good you can do is the game, and for this it really doesn’t matter at all how much impact Carl has. Sure, there’s a question of whether you’d prefer to be Carl or Dorothea, if you could choose to be either one.[2] But you are way more likely to end up being Dorothea.[3] You should expect to live and die in obscurity, you should expect to undertake no historic acts, you should expect most of your work to come to nothing in particular. The heroism of your life isn’t that you single-handedly press the wor...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Rethink Priorities - 2021 Impact and 2022 Strategy, published by Peter Wildeford on the Effective Altruism Forum. Summary Our purpose and people Rethink Priorities is a research organization that conducts research to inform policymakers and major foundations about how to best help people and nonhuman animals in both the present and the long-term future. Our work informs key stakeholders of the effective altruism community regarding decisions around funding, interventions, and research time allocation worth millions of dollars every year. This year we hired 14 new people. We now have a staff of 28 people, corresponding to 24.75 full-time equivalents (with 19.75 FTE focused on research and 5 FTE on operations). We’ll have spent about $2.1M USD in 2021. Our 2021 impact In 2021, we achieved some tangible impact from our work, such as: Improving animal welfare strategies in the European Union (moving several million dollars to what we believe are more effective approaches). Setting up an ambitious project to study the capacity for welfare of different species. Starting to staff up a team to address AI Governance and Strategy. Investigating lead reduction as a possible intervention competitive with GiveWell’s top charities. Running an intern program that successfully got new researchers involved in effective altruism and led to some interns getting permanent jobs in organizations like the Centre for Effective Altruism, Founders Pledge, and here at Rethink Priorities. Our plans for 2022 Among other projects in 2022, we’re especially excited to: Begin work with our newly expanded AI Governance and Strategy team and Global Health and Development team, both of which are directly focused on identifying high-impact giving opportunities. Build a larger longtermist research team to explore longtermist work and interventions more broadly. Tentatively conclude our intensive work on interspecies comparisons of moral weight, which could help us better prioritize across many cause areas. Help solve the funding overhang in EA and unlock tons of impact by identifying interventions across cause areas that can take lots of money while still meeting a high bar for cost-effectiveness. Our funding goals If better funded, we would be able to do more high-quality work and employ more talented researchers than we otherwise would. Currently, our goal is to raise $5,435,000 by the end of 2022. This consists of gaps of: $2,230,000 for animal-focused research $1,410,000 for longtermism research $1,275,000 for EA movement research and surveying $520,000 for global health and development research However, we believe that if we were maximally ambitious and expanded as much as is feasible, we could effectively spend the funds if we raised up to $12,900,000 in 2022. If you’d like to support our work, you can donate to us as part of Facebook’s donation matching on Giving Tuesday on November 30, or donate directly to us here. We do accept and track restricted funds by cause area if that is of interest. If you have questions about tax-deductibility in your country or are interested in making a major gift, please contact our Director of Development Janique Behman. Ask us more We’re running an AMA on the EA Forum this Friday, November 19. Ask us any questions you may have! Our path to impact Rethink Priorities achieves impact by improving the decisions made by grantmakers and on-the-ground organizations, multiplying the impact of their work. The effective altruism movement currently allocates hundreds of millions of dollars and millions of hours of work every year — we aim to improve that allocation. We work independently to uncover new insights while also collaborating with existing groups and funders to ensure the most effective actions are taken based on rigorous research. Our organization can be understoo...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Update on CEA's EA Grants Program, published by Nicole_Ross, Centre for Effective Altruism on the Effective Altruism Forum. Write a Review In December, I (Nicole Ross) joined CEA to run the EA Grants program, which gives relatively small grants (usually under $60,000 per grant) to individuals and start-up projects within EA cause areas. Before joining CEA, I worked at the Open Philanthropy Project and GiveWell doing both research and grants operations. When I joined CEA, the EA Grants program had been running since 2017. Upon my initial review, it had a mixed track record. Some grants seemed quite exciting, some seemed promising, others lacked the information I needed to make an impact judgment, and others raised some concerns. Additionally, the program had a history of operational and strategic challenges. I've spent the majority of the last nine months working to improve the overall functioning of the program. I'm now planning the future of EA Grants, and trying to determine whether some version of the program ought to exist moving forward. In this brief update, I’ll describe some of the program’s past challenges, a few things I’ve worked on, and some preliminary thoughts about the future of the program. I’ll also request feedback on the current EA funding landscape, and what value EA Grants might be able to add if we decide to maintain the program going forward. Note on early 2019 EA Grants round Last year, we publicly stated that we “expect the next round after this one to be early next year [2019] but we want to review lessons from this round before committing to a date.” When it became clear that we would not hold a round in early 2019, we did not update the previous statement. We regret any confusion we may have caused by failing to provide a clear update on our plans. Issues with the program EA Grants began in 2017. From June 2017 to December 2018 (when I joined CEA), grant management was a part-time responsibility of various staff members who also had other roles. As a result, the program did not get as much strategic and evaluative attention as it needed. Additionally, CEA did not appropriately anticipate the operational systems and capacity needed to run a grantmaking operation, and we did not have the full infrastructure and capacity in place to run the program. Because everyone involved recognized the importance of the program, CEA eventually began to take steps to resolve broader issues related to this lack of attention, including establishing the full-time Grants role for which I was hired and hiring an operations contractor to process grants. We believe it was a mistake that we didn’t act more quickly to improve the program, and that we weren’t more transparent during this process. My first responsibility in my new role was to investigate these issues, with support from staff who had worked on the EA Grants program in the past. I am grateful for the many hours current and former staff have spent helping me get up to speed and build a consolidated picture of the EA Grants program. Below are what I view as the most important historical challenges with the EA Grants program: 1) Lack of consolidated records and communications We did not maintain well-organized records of individuals applying for grants, grant applications under evaluation, and records of approved or rejected applications. We sometimes verbally promised grants without full documentation in our system. As a result, it was difficult for us to keep track of outstanding commitments, and of which individuals were waiting to hear back from CEA. This resulted in us spending much longer preparing for our independent audit than would have been ideal. 2) Lack of clarification about the role EA Grants played in the funding ecosystem While we gave information about the types of projects EA Grants woul...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: The case for building more and better epistemic institutions in the effective altruism community, published by stefan.torges on the Effective Altruism Forum. Write a Review As a community, we should think more about how to create and improve our collective epistemic institutions. With that, I mean the formalized ways of creating and organizing knowledge in the community beyond individual blogs and organizations. Examples are online platforms like the EA Forum and Metaculus, events like EA Global and the Leaders Forum, surveys like the EA survey and the survey at the Leaders Forum. This strikes me as a neglected form of community-building that might be particularly high-leverage. The case for building more and better epistemic institutions Epistemic progress is crucial for the success of this community. Effective altruism is about finding out how to do the most good and then doing it. For that, epistemic progress is important. Will MacAskill has even referred to effective altruism as a “research project.” Since people in this community have changed their views about how to do the most good substantially over the last ten years, we should expect that we’re still wrong about many things. Some institutions facilitate or significantly accelerate epistemic progress. People in this community are probably more aware of the research showing this than many other people. Ironically, we even recommend working on improving the decision-making of other organizations or communities. Aggregative forecasting is talked about most often and it seems to have solid evidence behind it. Still, it has limitations. For instance, it cannot help us with conceptual work, improving our reasoning and arguments directly, and inherently vague concepts. There is some evidence on other instruments like certain forms of expert elicitation or structured analytic techniques (e.g., devil’s advocate), but the evidence base seems less sound. It might still be worth experimenting with them. Peer review seems to be another valuable institution facilitating epistemic progress. I’m not sure if this has ever been investigated properly but it has a lot of prima facie plausibility to it. I don’t want to argue that we already know all the institutions that facilitate epistemic progress but there are at least some that do. If we think this is sufficiently important and there are more such institutions to be designed, experimenting and expanding the research base might be among the most important things we could do. We are not close to the perfect institutional setup. I don’t want to overstate the case. We have already built a number of great institutions in this regard, probably much better than other communities. Again, forecasting has probably seen the most attention (e.g., Metaculus, Foretold). The other examples I mentioned at the top, however, are also important and many have improved over the last few years. Still, I’m confident we can do better. Starting from the evidence base I sketched out above, we might start experimenting with the following institutions: Institutionalizing devil’s advocates: So far, we have had to rely on the initiative and courage of individuals to come forward with criticism of cause areas or certain paradigms within them (e.g., here, here). Perhaps there are ways to incentivize or institutionalize such work even more or even earlier. For instance, we could set up prizes for the best critique of apparently common assumptions or priorities. Expert surveys/elicitation: Grace et al. (2017) did one for AI timelines. The Leaders Forum survey is focused on EA-related questions. If possible, we could experiment with validating the participants or systematizing participant selection in other ways. We could also just explore many more questions this way in order to get a sense of what the most...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Effective Altruism is an Ideology, not (just) a Question, published by Fods12 on the Effective Altruism Forum. Write a Review This is a linkpost for/ Introduction In a widely-cited article on the EA forum, Helen Toner argues that effective altruism is a question, not an ideology. Here is her core argument: What is the definition of Effective Altruism? What claims does it make? What do you have to believe or do, to be an Effective Altruist? I don’t think that any of these questions make sense. It’s not surprising that we ask them: if you asked those questions about feminism or secularism, Islamism or libertarianism, the answers you would get would be relevant and illuminating. Different proponents of the same movement might give you slightly different answers, but synthesising the answers of several people would give you a pretty good feeling for the core of the movement. But each of these movements is answering a question. Should men and women be equal? (Yes.) What role should the church play in governance? (None.) What kind of government should we have? (One based on Islamic law.) How big a role should government play in people’s private lives? (A small one.) Effective Altruism isn’t like this. Effective Altruism is asking a question, something like: “How can I do the most good, with the resources available to me?” In this essay I will argue that his view of effective altruism being a question and not an ideology is incorrect. In particular, I will argue that effective altruism is an ideology, meaning that it has particular (if somewhat vaguely defined) set of core principles and beliefs, and associated ways of viewing the world and interpreting evidence. After first explaining what I mean by ideology, I proceed to discuss the ways in which effective altruists typically express their ideology, including by privileging certain questions over others, applying particular theoretical frameworks to answer these questions, and privileging particular answers and viewpoints over others. I should emphasise at the outset that my purpose in this article is not to disparage effective altruism, but to try to strengthen the movement by helping EAs to better understand the intellectual actual intellectual underpinnings of the movement. What is an ideology? The first point I want to explain is what I mean when I talk about an ‘ideology’. Basically, an ideology is a constellation of beliefs and perspectives that shape the way adherents of that ideology view the world. To flesh this out a bit, I will present two examples of ideologies: feminism and libertarianism. Obviously these will be simplified since there is considerable heterogeneity within any ideology, and there are always disputes about who counts as a ‘true’ adherent of any ideology. Nevertheless, I think these quick sketches are broadly accurate and helpful for illustrating what I am talking about when I use the word ‘ideology’. First consider feminism. Feminists typically begin with the premise that the social world is structured in such a manner that men as a group systematically oppress women as a group. There is a richly structured theory about how this works and how this interacts with different social institutions, including the family, the economy, the justice system, education, health care, and so on. In investigating any area, feminists typically focus on gendered power structures and how they shape social outcomes. When something happens, feminists ask ‘what affect does this have on the status and place of women in society?’ Given these perspectives, feminists typically are uninterested in and highly sceptical of any accounts of social differences between men and women based on biological differences, or attempts to rationalist differences on the basis of social stability or cohesion. This way of looking at thing...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is:Review of FHI's Summer Research Fellowship 2020, published by rosehadshar on the Effective Altruism Forum. Write a Review This post reviews the Future of Humanity Institute’s Summer Research Fellowship 2020 in detail. If you’re in a hurry, we recommend reading the summary of activities, lessons learned, and comparing costs and benefits sections for a quicker take. Thanks to Owen Cotton-Barratt, Max Daniel, Eliana Lorch, Tanya Singh and the summer fellows for reviewing and improving this post. Summary of activities 27 fellows spent 6 weeks on a remote fellowship programme. We got ~300 applications and interviewed ~50 people. Backgrounds ranged from undergraduate students to postdocs. By default, each fellow had a mentor and worked on a research project (though there were some exceptions, and many fellows also spent significant time exploring). The mentors were researchers and research managers at FHI, CSER, OpenPhil, OpenAI, GPI, and MIRI. Approximately, the projects related to AI governance (13 fellows), technical AI safety (3 fellows), biosecurity (4 fellows), macrostrategy broadly construed (5 fellows), and policy (2 fellows). This fellowship grew out of the CEA summer fellowship (which CEA wanted to stop running), though was significantly different in that a) it was remote, and b) we took more fellows (in 2019, the CEA fellowship took 11 fellows). Lessons learned Meta: we’re stating these confidently to make clear which direction the summer fellowship has updated us in. Obviously this was just one summer programme, and in many cases there might be important differences which mean that these takeaways wouldn’t generalise. The takeaways are in rough order of importance according to us. Remote fellowships can provide substantial value to fellows and organizers, and are worth considering where in person options are not available, or are especially costly. Initially we put some probability on the whole fellowship being awkward and unproductive, but in fact fellows had good experiences and some good things seem to have come from the programme. Remoteness also allowed us to take more fellows, and in the particular case of Covid-19, also came with lower opportunity costs for many fellows and organisers. In spite of remoteness, it was possible to create a positive, friendly and open culture. Many fellows remarked on this and appreciated it, and we guess that it helped to increase engagement, support those experiencing difficulties, and deepen fellows’ experiences. Modelling open and authentic communication on the part of the organisers seems to have been a major contributing factor to this culture. That said, we still think that there are many ways in which an in person fellowship would have been better, particularly in terms of culture, networking and some kinds of logistics. There is more interest than we expected in mentoring people amongst researchers in a range of different EA organisations. We successfully found 18 mentors for 24 fellows (3 fellows didn’t have formal mentors for various reasons), and we contacted at least a further 10 people who we think would have mentored if there had been a fellow working on the right topic. We also didn’t do a comprehensive search for mentors, and instead reached out ad hoc to people in our network, so we expect we would have found more interest if we had searched a bit harder. There were more promising applicants for this programme than we expected. In 2019 the CEA fellowship received ~90 applications, and this fellowship received ~300. We think that the number of strong applicants was correspondingly larger. Minor difficulties with mental health were common, and more serious ones not extremely rare (although this is confounded by remoteness and Covid-19). 1-1s and other conversations seemed to help support people with this. We t...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Does climate change deserve more attention within EA?, published by Louis_Dixon on the Effective Altruism Forum. Write a Review I have been an 80,000 Hours Podcast listener and active in EA for about eighteen months, and I have shifted from a focus on climate change, to animal welfare, and now to x-risk and s-risk, which seem to be highly promising from an EA perspective. Along the way, I wonder if some parts of EA might have underplayed climate change, and if more engagement and content on the topic could be valuable. While I was thinking about sustainability and ethics, I was frustrated by how limited the coverage of the topic was in the 80,000 Hours Podcast episodes, so I emailed the team. Rob Wiblin responded and suggested that I write up an EA forum post. Thanks to Alexrjl, John Bachelor, and David Nash for their suggestions and edits. Edited 29/10/2019 to remove a misquotation of 80,000 Hours, and a few other cases where I want to rectify some over-simplifications. Summary While it is true that EA and 80,000 Hours is effective in drawing attention to highly neglected areas, my view is it has unjustly neglected coverage of climate change. There are several reasons why I believe climate change deserves more attention within EA. Firstly, some key opinion-shapers in EA appear to have recently updated towards higher weightings on the severity of climate change. Secondly, though climate change is probably not an existential risk itself, it could be treated as an existential risk factor or multiplier. Thirdly, there are limitations to a crude application of the ITN framework and a short-termist approach to altruism. Fourthly, climate change mitigation and resilience may be more tractable than previously argued. Finally, by failing to show a sufficient appreciation of the severity of climate change, EA may risk losing credibility and alienating potential effective altruists. Changing perceptions of climate change among key individuals in EA 1. Assessment of climate change in Doing Good Better, 2015 The view taken in this book, foundational to EA, mostly equates climate change to a year of lost growth, and assigns a 'small but significant risk' that temperature rises are above 4C. Will Macaskill: Economists tended to assess climate change as not all that bad. Most estimate that climate change will cost only around 2% of global GDP. The thought that climate change would do the equivalent of putting us back one year economically isn’t all that scary- 2013 didn’t seem that much worse than 2014. So the social cost of one tonne of American’s greenhouse gas emissions is about $670 every year. Again, that’s not a significant cost, but it’s also not the end of the world. However, this standard economic analysis fails to faithfully use expected value reasoning. The standard analysis looks only at the effects from the most likely scenario: a 2-4C rise in temperature. there is a small but significant risk of a temperature increase that’s much greater than 2-4C. The IPCC gives more than 5% probability to temperature rises greater than 6C and even acknowledges a small risk of catastrophic climate change of 10C or more. To be clear, I’m not saying that this is at all likely, in fact it’s very unlikely. But it is possible, and if it were to happen, the consequences would be disastrous, potentially resulting in a civilisational collapse. It’s difficult to give a meaningful answer of how bad that would be, but if we think it’s potentially catastrophic, then we need to revise our evaluation of the importance of mitigating climate change. In that case, the true expected social cost of carbon could be much higher than $32 per metric ton, justifying much more extensive efforts to reduce emissions than the estimates the economists first suggested. The main text, and the later table of cause ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Why and how to start a for-profit company serving emerging markets, published by Ben_Kuhn on the Effective Altruism Forum. Write a Review This is a linkpost for Wave (1) is a for-profit, venture backed startup building cheap, instant money transfer to and within Africa. Since launching in 2015, we’ve become by far the biggest remitter to Kenya and Ghana, saving our users and recipients over $100 million so far. Our biggest source of expected future impact is building mobile money systems within Africa, which will have an orders-of-magnitude bigger impact if it succeeds. Wave’s mission is to improve the world, not to make money. Despite that, we operate more like a tech company than a social enterprise. Our investors are venture capitalists trying to make a high return, and they hold us to the same standards of growth rate and unit economics as any developed-world startup. This might seem like a downside (surely it would be easier to directly optimize for impact rather than have pressure from investors to make money?), but for us it’s actually increased our impact in two ways. First, the pressure to grow quickly forces us to make our product better and scale faster, so we help more people by a larger amount. Second, since we’ve done really well by for-profit investors’ standards, we can raise much more money than a nonprofit or social enterprise. In my opinion, Wave’s path—importing the US startup playbook to developing countries—was predictably high-expected-impact ex ante. First, starting a company generally has high expected impact: the social benefit of innovation is usually a large multiple of the private return. Serving an emerging market adds another multiplier, because the problems you could work on are much worse. (Providing someone $5 of value means a lot more when $5 is their day’s wages!) Finally, there’s more low-hanging fruit for companies to work on in developing countries, because the supply of skilled entrepreneurs is smaller. On the margin, then, more altruists with experience working in the developed world should try this approach. I feel safe saying this because very few people (altruistic or not) currently seem to. This is surprising, since lots of developing countries now have the infrastructure to support tech companies. In big cities like Dakar, Nairobi, Addis or Lagos, there’s mostly-reliable electricity, decent internet, high smartphone penetration, driveable roads and so on. But there aren’t many great startups taking advantage of them. (According to our investors who pay the most attention to Africa, Wave is by far the most promising.) Why isn’t the space more crowded? I’d guess it’s because creating a great product requires two things: being maniacally perfectionist, and deeply understanding your users. To be maniacally perfectionist, you need to be immersed in a culture with really high product standards (for instance, Silicon Valley). To understand your users in Africa, you need to live in Africa. The intersection of these two groups is practically no one, because most people who could live in Silicon Valley would much rather not move to, say, a former tank base in the middle of the desert (where many of my coworkers lived for years). One way to think of Wave is as an importer of high standards. For instance, in most mobile money systems in Africa, if you try to make a large withdrawal, your local agent may not have enough cash—it could take them hours or days to come up with the money. At Wave, we realized this made users sad, so we started predicting how much cash our agents would need and working with them to make sure they never ran out. This was a lot of extra work and risk for us, but led to massive adoption from traders—with funds available instantly from Wave, they could often turn over inventory literally twice as fast. Every wa...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Minimal-trust investigations, published by Holden Karnofsky on the Effective Altruism Forum. This piece is about the single activity ("minimal-trust investigations") that seems to have been most formative for the way I think. Most of what I believe is mostly based on trusting other people. For example: I brush my teeth twice a day, even though I've never read a study on the effects of brushing one's teeth, never tried to see what happens when I don't brush my teeth, and have no idea what's in toothpaste. It seems like most reasonable-seeming people think it's worth brushing your teeth, and that's about the only reason I do it. I believe climate change is real and important, and that official forecasts of it are probably reasonably close to the best one can do. I have read a bunch of arguments and counterarguments about this, but ultimately I couldn't tell you much about how the climatologists' models actually work, or specifically what is wrong with the various skeptical points people raise.1 Most of my belief in climate change comes from noticing who is on each side of the argument and how they argue, not what they say. So it comes mostly from deciding whom to trust. I think it's completely reasonable to form the vast majority of one's beliefs based on trust like this. I don't really think there's any alternative. But I also think it's a good idea to occasionally do a minimal-trust investigation: to suspend my trust in others and dig as deeply into a question as I can. This is not the same as taking a class, or even reading and thinking about both sides of a debate; it is always enormously more work than that. I think the vast majority of people (even within communities that have rationality and critical inquiry as central parts of their identity) have never done one. Minimal-trust investigation is probably the single activity that's been most formative for the way I think. I think its value is twofold: It helps me develop intuitions for what/whom/when/why to trust, in order to approximate the views I would hold if I could understand things myself. It is a demonstration and reminder of just how much work minimal-trust investigations take, and just how much I have to rely on trust to get by in the world. Without this kind of reminder, it's easy to casually feel as though I "understand" things based on a few memes or talking points. But the occasional minimal-trust investigation reminds me that memes and talking points are never enough to understand an issue, so my views are necessarily either based on a huge amount of work, or on trusting someone. In this piece, I will: Give an example of a minimal-trust investigation I've done, and list some other types of minimal-trust investigations one could do. Discuss a bit how I try to get by in a world where nearly all my beliefs ultimately need to come down to trusting someone. Example minimal-trust investigations The basic idea of a minimal-trust investigation is suspending one's trust in others' judgments and trying to understand the case for and against some claim oneself, ideally to the point where one can (within the narrow slice one has investigated) keep up with experts.2 It's hard to describe it much more than this other than by example, so next I will give a detailed example. Detailed example from GiveWell I'll start with the case that long-lasting insecticide-treated nets (LLINs) are a cheap and effective way of preventing malaria. I helped investigate this case in the early years of GiveWell. My discussion will be pretty detailed (but hopefully skimmable), in order to give a tangible sense of the process and twists/turns of a minimal-trust investigation. Here's how I'd summarize the broad outline of the case that most moderately-familiar-with-this-topic people would give:3 People sleep under LLINs, which are mosqu...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Opinion: Estimating Invertebrate Sentience, published by Jason Schukraft on the Effective Altruism Forum. Write a Review Introduction Between May 2018 and June 2019 Rethink Priorities completed a large project on the subject of invertebrate sentience.[1] We investigated the best methodology to approach the question, outlined some philosophical difficulties inherent in the project, described the features most relevant to invertebrate sentience, compiled the extant scientific literature on the topic, summarized our results, and ultimately produced an invertebrate welfare cause profile. We are currently in the process of identifying concrete interventions to improve invertebrate wellbeing, with a report on the welfare of managed honey bees due out in mid-November and a report on the welfare of farmed snails nearing completion. One thing we did not do was publish explicit numerical estimates of the probability that various groups of invertebrates are sentient. Our team discussed publishing such estimates many times, but these discussions generated considerable internal disagreement. Two members of the (four person) team believed that publishing explicit sentience estimates was a bad idea. The other two members felt that it was a good idea. In the end, we settled on the following compromise: several months after the completion of the invertebrate sentience project, we would publish an unofficial opinion piece in which each of us could share her/his own reasoning on the subject and, if so desired, her/his own estimates.[2] This post fulfills that compromise. In it, the four members of Rethink Priorities’ invertebrates team—Daniela R. Waldhorn, Marcus A. Davis, Peter Hurford, and Jason Schukraft—outline their views on the value, feasibility, and danger of quantitative estimates of invertebrate sentience. Marcus and Peter provide numerical estimates of sentience for each of the taxa we investigated for our invertebrate sentience project, Daniela offers a qualitative ranking of the same taxa, and Jason argues that we are not yet in a position to deliver estimates that are actionable and robust enough to outweigh the (slight but non-negligible) harm that publishing such estimates prematurely might engender. What follows are the personal opinions of individual researchers. Officially, Rethink Priorities does not have a position on the explicit probability that various invertebrates are sentient. Daniela R. Waldhorn 1. Vertebrates There is an ample and detailed body of empirical data which justifies believing that non-human vertebrates are sentient. In particular, there is solid neuro-anatomical, physiological and behavioral evidence that vertebrates like cows and chickens are conscious. There is also a growing trend to recognize that these animals do not only experience physical suffering (and pleasure) but also have emotional lives (see e.g. Marino, 2017; Proctor et al., 2013). Based on existing evidence and the generalized acceptance of the Cambridge Declaration on Consciousness (2012)[3], my overall conclusions regarding the probabilities of consciousness for these animals are presented as follows: 2. Invertebrates When we consider invertebrates, the debate about whether they are conscious becomes much more complex. First, it must be conceded that the numerous invertebrate species and their diversity impose severe constraints to justifiable generalizations about the presence of consciousness in this group of animals. Second, the scientific literature about sentience in invertebrates is not only scarce but fragmentary–that is to say, the extent to which invertebrates have been investigated varies. Thus, there are some particular species about which there is a comparatively great deal of knowledge (e.g., fruit flies), whereas much less research has focused on individuals of ot...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Donor Lottery Debrief, published by TimothyTelleenLawton on the Effective Altruism Forum. Write a Review Good news, I've finally allocated the rest of the donor lottery funds from the 2016-2017 Donor Lottery (the first one in our community)! It took over 3 years but I'm excited about the two projects I funded. It probably goes without saying, but this post is about an independent project and does not represent CFAR (where I work). This post contains several updates related to the donor lottery: My first donation: $25k to The Czech Association for Effective Altruism (CZEA) in 2017 My second (and final) donation: $23.5k to Epidemic Forecasting (EpiFor) in 2020 Looking back on the Donor Lottery Call for more projects like these to fund CZEA My previous comments on the original donor lottery post share the basics of how the first $25k was used for CZEA (this was $5k more than I was originally planning to donate due to transfer efficiency considerations). Looking back now, I believe that donation likely had a strong impact on EA community building. My donation was the largest that CZEA had received (I think they previously had received one other large donation—about half the size) and it was enough for CZEA to transition from a purely volunteer organization into a partially-professional organization (1 FTE, plus volunteers). Based on conversations with Jan Kulveit, I believe it would have taken at least 8 more months for CZEA to professionalize otherwise. I believe that in the time they bought with the donation, they were able to more easily secure substantial funding from CEA and other funders, as well as scale up several compelling initiatives: co-organizing Human-aligned AI Summer School, AI Safety Research Program, and a Community Building Retreat (with CEA). I also have been glad to see a handful of people get involved with EA and Rationality through CZEA, and I think the movement is stronger with them. To pick an example familiar to me, several CZEA leaders were recently part of CFAR's Instructor Training Program: Daniel Hynk (Co-founder of CZEA), Jan Kulveit (Senior Research Scholar at FHI), Tomáš Gavenčiak (Independent Researcher who has been funded by EA Grants), and Irena Kotíková (President of CZEA). For more detail on CZEA's early history and the impact of the donor lottery funds (and other influences), see this detailed account. EpiFor In late April 2020, I heard about Epidemic Forecasting—a project launched by people in the EA/Rationality community to inform decision makers by combining epidemic modeling with forecasting. I learned of the funding opportunity through my colleague and friend, Elizabeth Garrett. The pitch was immediately compelling to me as a 5-figure donor: A group of people I already believed to be impressive and trustworthy were launching a project to use forecasting to help powerful people make better decisions about the pandemic. Even though it seemed likely that nothing would come of it, it seemed like an excellent gamble to make, based on the following possible outcomes: Prevent illness, death, and economic damage by helping governments and other decision makers handle the pandemic better, especially governments that couldn't otherwise afford high-quality forecasting services Highlight the power of—and test novel applications of—an underutilized tool: forecasting (see the book Superforecasting for background on this) Test and demonstrate the opportunity for individuals and institutions to do more good for important causes by thinking carefully (Rationality/EA) rather than relying on standard experts and authorities alone Engage members of our community in an effort to change the world for the better, in a way that will give them some quick feedback—thus leading to deeper/faster learning Cross-pollinate our community with professional fie...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: EA Birthday Posts: An Alternative to Fundraisers, published by kuhanj on the Effective Altruism Forum. Write a Review For my birthday earlier this year, I spent a fair amount of time writing an EA-themed birthday post (reproduced at the bottom of this write-up). I think that this post did fairly well - 5 messages and subsequent calls about career plan changes (!), and 170 reactions on Facebook. As such, I'd be excited for more EAs to make similar posts, especially other highly involved university organizers with experience communicating about EA. In this post I share my thought-process for making this birthday post, what I could’ve done differently, some considerations for other EAs interested in doing the same, and the post itself. I’d love to hear feedback on the post and the ideas in this writeup, and similar successful examples of leveraging birthdays and other occasions for EA purposes. Choosing the content of the post: I initially decided to make an EA-themed birthday fundraiser, thinking it might be a uniquely strong meta-EA opportunity. At first I spent a lot of time trying to figure out what cause area I wanted to raise awareness for. However in the end, I ended up going down a different route than typical birthday fundraisers. Rather than picking a particular charity and asking for donations, I decided to instead make a different ask - to consider high impact careers (in particular, by highlighting 80,000 Hours and its Key Ideas page). I did this for three main reasons: A change in career choice is far more impactful than making a donation (and will probably lead to donations later on anyway). Even one person counterfactually making a career pivot towards addressing the most pressing problems as a result of reading my post could be worth upwards of hundreds of thousands of dollars in donations - several orders of magnitude more successful than I would expect for a regular birthday fundraiser. Birthdays are a good opportunity to ask people to do costly things that would make me happy, like donating to a charity I care about, or in my case, reading a lengthy FB post and website). I wanted to counter common misconceptions about EA. Many people I meet at Stanford who have heard of it already think EA = EArning (sorry) to give, or that it only focuses on donations to evidence-backed short-term well-being focused interventions. I thought my birthday post provided a good opportunity to address these misconceptions. Ideas I wanted to convey through the post: What we choose to do with our careers is likely the highest impact decision we’ll make. 80000hours.org is a really great resource for (especially young) people trying to figure out what problems are most pressing, and how we can use our career to tackle them. Addressing common misconceptions about EA: That it is not just about donations or earning to give, or solely about global health interventions, or any single cause area for that matter. Short descriptions of the current cause areas prioritized in EA and why they’re prioritized. I wasn’t thrilled with the wording I ended up with for each of the cause area descriptions, but it’s a start. I’d be excited to hear others’ thoughts on how to best communicate about these causes to non-EA audiences. Impact of the post: Most excitingly, five people so far have taken me up on my offer to talk to them about changing careers/career plans. I’ve had calls and planned follow up with each of them to discuss their thoughts on the 80,000 Hours Key Ideas page and applying the content to their careers. A few others messaged me saying they’d read the 80,000 Hours Key Ideas page and really liked it. The post has received 170 likes and 5 shares, which is my most well-received Facebook post so far by quite some margin (nearly twice as much engagement as my second most popular post...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Introducing Metaforecast: A Forecast Aggregator and Search Tool, published by NunoSempere, Ozzie Gooen on the Effective Altruism Forum. Introduction The last few years have seen a proliferation of forecasting platforms. These platforms differ in many ways, and provide different experiences, filters, and incentives for forecasters. Some platforms like Metaculus and Hypermind use volunteers with prizes, others, like PredictIt and Smarkets are formal betting markets. Forecasting is a public good, providing information to the public. While the diversity among platforms has been great for experimentation, it also fragments information, making the outputs of forecasting far less useful. For instance, different platforms ask similar questions using different wordings. The questions may or may not be organized, and the outputs may be distributions, odds, or probabilities. Fortunately, most of these platforms either have APIs or can be scraped. We’ve experimented with pulling their data to put together a listing of most of the active forecasting questions and most of their current estimates in a coherent and more easily accessible platform. Metaforecast Metaforecast is a free & simple app that shows predictions and summaries from 10+ forecasting platforms. It shows simple summaries of the key information; just the immediate forecasts, no history. Data is fetched daily. There’s a simple string search, and you can open the advanced options for some configurability. Currently between all of the indexed platforms we track ~2100 active forecasting questions, ~1200 (~55%) of which are on Metaculus. There are also 17,000 public models from Guesstimate. One obvious issue that arose was the challenge of comparing questions among platforms. Some questions have results that seem more reputable than others. Obviously a Metaculus question with 2000 predictions seems more robust than one with 3 predictions, but less obvious is how a Metaculus question with 3 predictions compares to one from Good Judgement Superforecasters where the number of forecasters is not clear, or to estimates from a Smarkets question with £1,000 traded. We believe that this is an area that deserves substantial research and design experimentation. In the meantime we use a star rating system. We created a function that estimates reputability as “stars” on a 1-5 system using the forecasting platform, forecast count, and liquidity for prediction markets. The estimation came from volunteers acquainted with the various forecasting platforms. We’re very curious for feedback here, both on what the function should be, and how to best explain and show the results. Metaforecast is being treated as an experimental endeavor of QURI. We spent a few weeks on it so far, after developing technologies and skill sets that made it fairly straightforward. We're currently expecting to support it for at least a year and provide minor updates. We’re curious to see what interest is like and respond accordingly. Metaforecast is being led by Nuño Sempere, with support from Ozzie Gooen, who also wrote much of this post. Select Search Screenshots Charity GiveWell Data Sources Platform Url Information used in Metaforecast Robustness Metaculus Active questions only. The current aggregate is shown for binary questions, but not for continuous questions. 2 stars if it has fewer than 100 forecasts, 3 stars when between 101 and 300, 4 stars if over 300 Foretell (CSET)/ All active questions 1 star if a question has fewer than 100 forecasts, 2 stars if it has more Hypermind Questions on various dashboards 3 stars Good Judgement/ We use various superforecaster dashboards. You can see them here and here 4 stars Good Judgement Open/ All active questions 2 stars if a question has fewer than 100 forecasts, 3 stars if it has more Smarkets/ Only take the polit...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: [New org] Canning What We Give, published by Louis_Dixon on the Effective Altruism Forum. Epistemic status: 30% (plus or minus 50%). Further details at the bottom. In the 2019 EA Cause Prioritisation survey, Global Poverty remains the most popular single cause across the sample as a whole. But after more engagement with EA, around 42% of people change their cause area, and of that, a majority (54%) moved towards the Long Term Future/Catastrophic and Existential Risk Reduction. While many people find that donations help them stay engaged (and continue to be a great thing to do), there has been much discussion of other ways people can contribute positively. In thinking about the long-run future, one area of research has been improving human's resilience to disasters. A 2014 paper looked at global refuges, and more recently ALLFED, among others, have studied ways to feed humanity in disaster scenarios. There is much work done, and even much more needed, to directly reduce risks such as through pandemic preparedness, improving nuclear treaties, and improving the functioning of international institutions. But we believe that there are still opportunities to increase resilience in disaster scenarios. Wouldn't it be great if there was a way to directly link the simplicity of donations with effective methods for the recovery of civilisation? Photo credit to Facebook and Wikipedia - cans shown are illustrative only Canning what we give In The Knowledge by Lewis Dartnell (p. 40), an estimate is given of how long a supermarket would be able to feed a single person: So if you were a survivor with an entire supermarket to yourself, how long could you subsist on its contents? Your best strategy would be to consumable perishable goods for the first few weeks, and then turn to dried pasta and nice... A single average-sized supermarket should be able to sustain you for around 55 years - 63 if you eat the canned cat and dog food as well. But in thinking about an population, there would be fewer resources to go around per person. The UK Department for Environment, Food and Rural Affairs (DEFRA) estimated in 2010 that there was a national stock reserve of 11.8 days of 'ambient slow-moving groceries'. (ibid, p.40) It seems clear that there aren't enough canned goods. Our proposal We propose that: We try to expand both the range of things that are canned, and find ways to bury them deep in the earth (ideally beyond of the reach of the mole people) Donors to GWWC instead consider CWWG Donors put valuable items in cans which they would want in a disaster scenario, e.g. fruit salads, Worcester sauce, marmelade EA funds provides a donation infrastructure to support sending cans A mock-up of the CWWG dashboard Risks We are concerned that: Cluelessness could lead to uncertain outcomes The production of too many cans could make things too shiny and there could be a shortage of sunglasses There might not be enough can openers Focusing industrial production on making can could lead to a global arms race to make more cans Further information Partial credit to this goes to Harri Besceli - we came up with the idea together. This was a joke. Happy April fools. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: My Q1 2019 EA Hotel donation, published by vipulnaik on the Effective Altruism Forum. Write a Review On March 31, 2019, I donated 3200 GBP to the EA Hotel fundraiser via GoFundMe. The donation cost me $4,306.14 USD. My decision was based mainly on the information in the EA Hotel page and the documents linked from the donations list website page on EA Hotel, which include the recent Effective Altruism Forum posts. In this post, I describe the reasons that influenced my decision to donate. I didn't draft the post before donating, so some of the elaboration includes aspects that didn't (at least consciously) influence my donation decision. I limited the time I spent writing the post, and will most likely not be able to respond to comments. But please feel free to comment with your thoughts in response to my post or other comments! NOTE: I have no affiliation with the EA Hotel. I have never visited it, nor have I closely collaborated with anybody living there. I did not show this post to anybody affiliated with the EA Hotel before posting. Nothing here should be taken as an official statement about the EA Hotel. The sections of the post: I like the idea of the EA Hotel I like the skin-in-the-game of the key players I like the execution so far I see institutional risk reasons for lack of institutional funding: These reasons don't apply to individual donors, so I don't see the lack of institutional funding as a reason to dissuade me from donating I have not been dissuaded by the reasons against donating that I have seen so far I find the value of marginal donations high and easy to grasp How I decided to donate and determined the donation amount I like the idea of the EA Hotel My interpretation of the fundamental problem the EA Hotel is trying to solve: provide low-cost and optimized transient living arrangements to people engaged in self-study or early stages of projects. The hotel's low-cost living arrangements are further subsidized so that long-term residents don't have to pay anything at all, and in fact, get a stipend to cover some living expenses. This means that residents can pursue projects with single-minded focus without burning through savings or having to do additional jobs just to keep themselves financially afloat. The backdrop of the problem, as I understand: EA communities have congregated in some of the most expensive places in the world, such as the San Francisco Bay Area, Boston/Cambridge, New York City, and London. Even outside of these, most places with significant numbers of EAs tend to be cities, and these tend to have higher costs of living. Most EA projects have trouble raising enough money to cover costs of living in these places, even after they get funding. Moreover, most EA organizations, which are also based in these areas, do not pay enough of a premium for people to build savings that would allow them to comfortably spend months working on such projects in these expensive locations. Tendencies within EA to donate large fractions of one's personal wealth may have further exacerbated people's lack of adequate savings to pursue EA projects. These problems, specially the first one, have been widely acknowledged. Attempts to figure out a new, lower-cost city for EAs and build group housing in that city started since as far back as 2014, when the Coordination of Rationality/EA/SSC Housing Project group was created. Browsing through the archives of that Facebook group is interesting because it shows the amount of effort that has gone in over the years in identifying lower-cost living places for EAs. This is the group where EA Hotel founder Greg Colbourn first announced his intention to buy a hotel in Blackpool. Side note: Peter McCluskey's comment suggests that complaining about the high rent in major hubs is a signal of low status, because the mo...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Why Nations Fail and the long-termist view of global poverty, published by Ben_Kuhn on the Effective Altruism Forum. Write a Review This is a linkpost for Within the effective altruism community, people often talk about “long-termist” vs “short-termist” worldviews. The official distinction between the two is that short-termists prioritize problems by how they affect people alive today, while long-termists prioritize problems by how they could affect humanity’s entire future trajectory. In practice, people usually treat this as synonymous with prioritizing either existential risk reduction (if long-termist), or scaling up proven global health interventions (if short-termist). It’s a bit surprising that each worldview should have exactly one favorite cause area, though. Couldn’t you have short-termist work on existential risk, or long-termist work on global poverty? In reality, these supposedly discrete worldviews seem more like correlated clusters of various different beliefs: "Short-termist" High time discount rate Prefers highly robust “outside view” type arguments Extrapolates existing effects or trends Skeptical of prima facie bizarre claims Focuses on fixing known, concrete problems Fast feedback loops are critical to making progress "Long-termist" Low or no discount rate More open to “inside view” that this case might be different Reasons about the future from first principles Takes weird-sounding ideas more seriously Focuses on preventing hypothetical, nebulous risks Fast feedback is helpful, but not the most important thing It’s understandable why some of these are correlated, but there must be a lot of people who fall through the cracks between the clusters. What if you share short-termists’ skepticism of weird claims and hypothetical risks, but you’re willing to focus on first-principles reasoning and work on a long time scale? You’d still want to focus on something that’s a problem today, so you’d probably want to work on global poverty. But you’d dismiss GiveWell’s top charities as treating a symptom and not a cause. Why do these countries need charity in the first place? South Korea used to be just as poor as anywhere in Africa, but today it’s incredibly prosperous, while sub-Saharan Africa has made way less progress. If we could move the lowest-growth countries from their current trajectory onto South Korea’s, we’d have done much more than any single malaria-eradication campaign could. If that were your worldview, you’d really enjoy Why Nations Fail, one of the best attempts I’ve seen at getting a first-principles understanding of what affects countries’ long-term economic growth. First of all, what is economic growth? It’s when people produce more (or more valuable) stuff with the same effort[1]. The first and least controversial point in Why Nations Fail is that for a nation to keep on doing more with less, its individual citizens need to be incentivized to become more productive. In particular, the state should not set up systems where, whenever someone gets more productive, other people come and take away the extra stuff they produced. Those systems are what the authors call extractive economic institutions, and they include things like slavery, serfdom, indentured servitude, roving bandits, guilds, collectivized agriculture, nationalization of private assets, officials requiring bribes, kangaroo courts, banana republics, and other [animal or vegetable] [civic institution]. You might think you could grow your economy under extractive institutions by forcing people to become more productive even if they won’t get to keep the surplus. This does often work in the short term (and the short term can last a surprisingly long time)–for instance, Soviet Russia grew at about 5% annually from 1930-1970,[2] despite having extremely extractive institutions. But ...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: How are resources in EA allocated across issues?, published by Benjamin_Todd on the effective altruism forum. This is a cross-post from 80,000 Hours. How are the resources in effective altruism allocated across cause areas? Knowing these figures, for both funding and labour, can help us spot gaps in the current allocation. In particular, I’ll suggest that broad longtermism seems like the most pressing gap right now. This is a follow on from my first post, where I estimated the total amount of committed funding and people, and briefly discussed how many resources are being deployed now vs. invested for later. These estimates are for how the situation stood in 2019. I made them in early 2020, and made a few more adjustments when I wrote this post. As with the previous post, I recommend that readers take these figures as extremely rough estimates, and I haven’t checked them with the people involved. I’d be keen to see additional and more thorough estimates. Update Oct 2021: I mistakenly said the number of people reporting 5 for engagement was ~2300, but actually this was the figure for people reporting 4 or 5. Allocation of funding Here are my estimates: Cause Area $ millions per year in 2019 % Global health 185 44% Farm animal welfare 55 13% Biosecurity 41 10% Potential risks from AI 40 10% Near-term U.S. policy 32 8% Effective altruism/rationality/cause prioritisation 26 6% Scientific research 22 5% Other global catastrophic risk (incl. climate tail risks) 11 3% Other long term 1.8 0% Other near-term work (near-term climate change, mental health) 2 0% Total 416 100% What it’s based on: Using Open Philanthropy’s grants database, I averaged the allocation to each area 2017–2019 and made some minor adjustments. (Open Phil often makes 3yr+ grants, and the grants are lumpy, so it’s important to average.) At a total of ~$260 million, this accounts for the majority of the funding. (Note that I didn’t include the money spent on Open Phil’s own expenses, which might increase the meta line by around $5 million.) I added $80 million to global health for GiveWell using the figure in their metrics report for donations to GiveWell-recommended charities excluding Open Philanthropy. (Note that this figure seems like it’ll be significantly higher in 2020, perhaps $120 million, but I’m using the 2019 figure.) GiveWell says their best guess is that the figures underestimate the money they influence by around $20 million, so I added $20 million. These figures also ignore what’s spent on GiveWell’s own expenses, which could be another $5 million to meta. For longtermist and meta donations that aren’t Open Philanthropy, I guessed $30 million per year. This was based on roughly tallying up the medium-sized donors I know about and rounding up a bit. I then roughly allocated them across cause areas based on my impressions. This figure is especially uncertain, but seems small compared to Open Philanthropy, so I didn’t spend too long on it. Neartermist donations outside of Open Phil and GiveWell are the most uncertain. I decided to exclude donors who don’t explicitly donate under the banner of effective altruism, or else we might have to include billions of dollars spent on cost-effective global health interventions, pandemic prevention, climate change etc. I excluded the Gates Foundation too, though they have said some nice things about EA. This is a very vague boundary. For animal welfare, about $9 million has been donated to the EA Animal Welfare Fund, compared to $11.6 million to the Long Term Future Fund and the Meta Fund (now called the Infrastructure Fund). If the total amount to longtermist and meta causes is $30 million per year, and this ratio holds more broadly, it would imply $23 million per year to EA animal welfare (excluding OP) in total. This seems plausible considering that Ani...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Frank Feedback Given To Very Junior Researchers, published by NunoSempere on the effective altruism forum. Over the last year, I have found myself giving feedback on various drafts, something that I'm generally quite happy to do. Recently, I got to give two variations of this same feedback in quick succession, so I noticed the commonalities, and then realized that these commonalities were also present on past pieces of feedback. I thought I'd write the general template up, in case others might find it valuable. High level comments You are working at the wrong level of abstraction and depth / you are biting more than you can chew / being too ambitious. In particular, the questions that you analyze are likely to have many cruxes, i.e, factors that might change the conclusion completely. But you only identify a few such cruxes, and thus your analysis doesn't seem likely to be that robust. I guess that the opposite error is possible—focus too much on one specific scenario which isn't that likely to happen. I just haven't seen it as much, and it doesn't seem as crippling when it happens. Because you're being too ambitious, you don't have the tools necessary to analyze what you want to analyze, and to some extent those tools may not exist. Compare with: Forecasting transformative AI timelines using biological anchors, Report on Semi-informative Priors on Transformative AI or Invertebrate Sentience: Summary of findings, which are much more constrained and have specific technical/semi-technical intellectual tool suited to the job (comparison with biological systems, variations on Laplace's law and other priors, markers of consciousness like reaction to harmful stimuli). You don't have an equivalent technical tool. There is a missing link between the individual facts you outline, and the conclusions you reach (e.g., about [redacted] and [redacted]). I think that the correct thing to do here is to sit with the uncertainty, or to consider a range of scenarios, rather than to reach one specific conclusion. Alternatively, you could highlight that different dynamics could still be possible, but that on the balance of probabilities, you personally think that your favored hypothesis is more likely. But in that case, it's be great if you more clearly defined your concepts and then expressed your certainty in terms of probabilities, because those are easier to criticize or put to the test, or even notice that there is a disagreement to be had. Judgment calls I get the impression that you rely too much on secondary sources, rather than on deeply understanding what you're talking about. You are making the wrong tradeoff between formality and ¿clarity of thought? Your report was difficult to read because of the trappings of scholarship—formal tone, long sentences and paragraphs, etc.) An index would have helped. Your classification scheme is not exhaustive, and thus less useful. This seems particularly important when considering intelligent adversaries. I get the impression that you are not deeply familiar with the topic you are talking about. For example, when giving your overview, you don't consider [redacted], which is really the company working on this space. In particular, I expect that the funders or decision-makers (for instance, Open Philanthropy) whom you might be attempting to influence or inform will be more familiar with the topic than you, and would thus not outsource their intellectual labor to your report. I don't really know whether you are characterizing the literature faithfully, whether you're just citing the top few most salient experts that you found, or whether there are other factors at play. For instance, maybe the people who [redacted] don't want to be talking about it. Even if you are representing the academic consensus fairly, I don't know how much to trust it....
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Cause profile: mental health, published by MichaelPlant on the effective altruism forum. Write a Review Introduction In this piece, I argue that mental illness may be one of the world’s most pressing problems. Here is a summary of the key points: Not only does mental illness seem to cause as much, if not more, total worldwide unhappiness than global poverty, it also seems far more neglected. Effective mental health interventions exist currently. These have been improving over time and we can expect further improvements. I estimate the cost-effectiveness of a particular mental health organisation, StrongMinds, and claim it is (at least) four times more effective per dollar than GiveDirectly, a GiveWell recommended top charity. This assumes we understand cost-effectiveness in terms of happiness, as measured by self-reported life satisfaction. I explain why it’s unclear if StrongMinds is better than all the other GiveWell recommended life-improving charities (due to inconsistent evidence regarding negative spillovers from wealth increases) and life-saving charities (due to methodological issues about where on a 0-10 life satisfaction scale is the ‘neutral point’ equivalent to being dead). I make some initial suggestions for the highest-impact careers, as well as alternative donation opportunities. No thorough analysis has yet been done to compare these. While mental health has the most obvious appeal for those who believe we ought to be maximising the happiness of people alive today, I explain that belief isn’t necessary to conclude it is of the highest priority: someone could, in principle, value what happens to all possible sentient life and still reasonably decide this cause is where they’ll do the most good. I raise, but do not seek to resolve, the many crucial considerations here. In order to get a sense of how important work on this area is, I examine (i) the scale, (ii) neglectedness, and (iii) tractability of the problem in turn. Ultimately, tractability - which I understand as cost-effectiveness - is what really matters and the preceding two sections should be seen as providing helpful background. I then set out why someone might - and might not - think this cause is their top priority and what they could do next if they decided it is. Scale (how many suffer and by how much?) Section summary: mental illness causes more suffering than poverty in developed countries, seems to cause roughly as much suffering worldwide as poverty does and, unlike poverty, is not shrinking. The 2013 Global Burden of Disease (GBD) report estimated that depression affects approximately 350m people annually, while anxiety afflicts another 250 million.[1] By comparison, the report estimated that malaria affects 146 million people, while a 2015 World Bank report estimated 702 million people living on less than $1.25 a day.[2] While poverty affects many more people than mental health, the share of the world population living in absolute poverty is falling rapidly: there were 1.76 billion in absolute poverty in 1999, a drop of about 1 billion people.[3] By contrast, severe mental illnesses are on the rise.[4] As one example, in the UK the proportion of those reporting severe symptoms of common mental disorders has risen 34.7% between 1993 and 2014 (from 6.9% to 9.3% of the population).[5] It’s unlikely this is solely due to increased reporting: an American birth cohort analysis running from 1938 to 2010 found large increases in all psychopathologies after using standard methods to control for possible increases in reporting.[6] To properly assess scale we also need to know how much suffering each causes: if poverty makes people miserable but mental illnesses are only mildly bad, poverty will be larger in scale. In a recent analysis of self-reported happiness scores, the World Happiness Rep...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Existential Risk and Economic Growth, published by leopold on the effective altruism forum. Write a Review As a summer research fellow at FHI, I’ve been working on using economic theory to better understand the relationship between economic growth and existential risk. I’ve finished a preliminary draft; see below. I would be very interesting in hearing your thoughts and feedback! Draft: leopoldaschenbrenner.com/xriskandgrowth Abstract: Technological innovation can create or mitigate risks of catastrophes—such as nuclear war, extreme climate change, or powerful artificial intelligence run amok—that could imperil human civilization. What is the relationship between economic growth and these existential risks? In a model of endogenous and directed technical change, with moderate parameters, existential risk follows a Kuznets-style inverted U-shape. This suggests we could be living in a unique “time of perils,” having developed technologies advanced enough to threaten our permanent destruction, but not having grown wealthy enough yet to be willing to spend much on safety. Accelerating growth during this “time of perils” initially increases risk, but improves the chances of humanity's survival in the long run. Conversely, even short-term stagnation could substantially curtail the future of humanity. Nevertheless, if the scale effect of existential risk is large and the returns to research diminish rapidly, it may be impossible to avert an eventual existential catastrophe. thanks for listening. to help us out with the nonlinear library or to learn more, please visit nonlinear.org.
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Some thoughts on deference and inside-view models, published by Buck on the effective altruism forum. Write a Review TL;DR: It's sometimes reasonable to believe things based on heuristic arguments, but it's useful to be clear with yourself about when you believe things for heuristic reasons as opposed to having strong arguments that take you all the way to your conclusion. A lot of the time, I think that when you hear a heuristic argument for something, you should be interested in converting this into the form of an argument which would take you all the way to the conclusion except that you haven't done a bunch of the steps--I think it's healthy to have a map of all the argumentative steps which you haven't done, or which you're taking on faith. I think that all the above can be combined to form a set of attitudes which are healthy on both an individual and community level. For example, one way that our community could be unhealthy would be if people felt inhibited to say when they don't feel persuaded by arguments. But another unhealthy culture would be if we acted like you're a chump if you believe things just because people who you trust and respect believe them. We should have a culture where it's okay to act on arguments without having verified every step for yourself, and you can express confusion about individual steps without that being an act of rebellion against the conclusion of those arguments. I wrote this post to describe the philosophy behind the schedule of a workshop that I ran in February. The workshop is kind of like AIRCS, but aimed at people who are more hardcore EAs, less focused on CS people, and with a culture which is a bit less like MIRI and more like the culture of other longtermist EAs. Thanks to the dozens of people who I've talked to about these concepts for their useful comments; thanks also to various people who read this doc for their criticism. Many of these ideas came from conversations with a variety of EAs, in particular Claire Zabel, Anna Salamon, other staff of AIRCS workshops, and the staff of the workshop I’m going to run. I think this post isn't really insightful enough or well-argued enough to justify how expansive it is. I posted it anyway because it seemed better than not doing so, and because I thought it would be useful to articulate these claims even if I don't do a very good job of arguing for them. I tried to write the following without caveating every sentence with "I think" or "It seems", even though I wanted to. I am pretty confident that the ideas I describe here are a healthy way for me to relate to thinking about EA stuff; I think that these ideas are fairly likely to be a useful lens for other people to take; I am less confident but think it's plausible that I'm describing ways that the EA community could be different that would be very helpful. Part 1: ways of thinking Proofs vs proof sketches When I first heard about AI safety, I was convinced that AI safety technical research was useful by an argument that was something like "superintelligence would be a big deal; it's not clear how to pick a good goal for a superintelligence to maximize, so maybe it's valuable to try to figure that out." In hindsight this argument was making a bunch of hidden assumptions. For example, here are three objections: It's less clear that superintelligence can lead to extinction if you think that AI systems will increase in power gradually, and before we have AI systems which are as capable of the whole of humanity we have AI systems which are as capable as dozens of humans. Maybe some other crazy thing (whole brain emulation, nanotech, technology-enabled totalitarianism) is likely to happen before superintelligence, which would make working on AI safety seem worse in a bunch of ways Maybe it's really hard to work on technical AI ...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Are there any other pro athlete aspiring EAs?, published by Marcus Daniell on the effective altruism forum. Write a Review I'm starting an EA aligned non-profit called High Impact Athletes that is aiming to funnel donations from current and retired pro athletes and their fans towards the most effective orgs in the world. It's still early stage but I wondered if there were any pro or ex athletes hiding in the EA Forum who might be interested in supporting the idea? I believe pro sport is a relatively untapped space for EA and potentially has huge pulling power if the athletes get their fans on board. Many thanks, Marcus Daniell thanks for listening. to help us out with the nonlinear library or to learn more, please visit nonlinear.org.
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Rethink Priorities 2020 Impact and 2021 Strategy, published by Marcus_A_Davis on the effective altruism forum. Write a Review Summary Rethink Priorities is an EA research organization focused on influencing funders and key decision-makers to improve decisions within EA and EA-aligned organizations. This year we expanded our operations team and hired multiple researchers across multiple causes, allowing us to expand and improve our animal welfare and EA movement building work, and build a dedicated longtermism team. Rethink Priorities currently has a staff of 16 people, corresponding to 13 full-time equivalents (including 3 FTE operations staff). This year we spent 72% of our time working on research relevant to farmed and wild animal welfare, 9% on movement building, 8% on longtermism, and 11% on other research projects. By the end of the year, we’ll have spent about $833K in 2020. We track our impact in multiple ways. This year we found qualitative interviews with key decision makers and leaders at EA organizations particularly helpful in understanding how to improve. Given the feedback we’ve received, we think two areas for improvement are more focus on communication with key funders and groups and also improving the visual communication of our work. Over the next few years we plan to expand our work in animal welfare, relaunch our work in longtermism, and continue our work in movement building. We continue to be constrained by a lack of funding to hire talented researchers and execute promising projects, having to turn down or delay very high-value projects. In particular, our non-animal growth is constrained by depending too heavily on EA Funds. We would strongly benefit from new individual donors to support our work and diversify our funder base. If funded we would hire 1-2 additional researchers to tackle our ambitious research agenda and the opportunities we have to work with more groups. We would also create an intern program. In addition to resulting in additional directly valuable research, this program would also benefit both our future growth and the growth of other EA-aligned research efforts, by helping us identify new talented researchers, helping them build their skills, and helping our existing staff develop their management skills. Currently, our goal is to raise $1.57M by the end of 2021. This consists of gaps of $757K for animal research, $503K for longtermism research, $261K for meta and movement building, and $46K for other research. We do accept and track restricted funds by cause area if that is of interest. If you’d like to support our work, you can donate to us as part of Facebook’s donation matching on Giving Tuesday or donate directly to us here. If you’re interested in supporting our work with a major gift, contact Director of Development Janique Behman. Our Mission Our mission is to help funders make better grants and help organizations do higher impact work. We accomplish this by doing and communicating research that analyzes existing interventions, broadens and refines the scope of possible consideration, and deepens our understanding of what interventions are possible and effective. Rethink Priorities Theory of Change Organizational Structure Staff Over the course of 2020, we made a number of hires to improve our team. Thanks to support in 2019, Peter Hurford, Co-Executive Director, became full-time in March 2020, and in May we hired a Director of Operations, Abraham Rowe. Janique Behman joined as our Director of Development in November 2020. We also expanded our research team, hiring five researchers (~3.75 FTE) to continue and expand our work across animal welfare, movement building, and longtermism.[1] Michael Aird - Associate Researcher - Previously did longtermist and macrostrategy research for Convergence Analysis and the Center...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: 2017 Donor Lottery Report, published by AdamGleave on the effective altruism forum. Write a Review I am the winner of the 2017 donor lottery. This write-up documents my decision process. The primary intended audience are other donors: several of the organisations I decided to donate to still have substantial funding gaps. I also expect this to be of interest to individuals considering working for one of the organisations reviewed. To recap, in a donor lottery many individuals make small contributions. The accumulated sum is then distributed to a randomly selected participant. Your probability of winning is proportional to the amount donated, such that the expected amount of donations you control is the same as the amount you contribute. This is advantageous since the winner (given the extra work, arguably the "loser") of the lottery can justify spending substantially more time evaluating organisations than if he or she were controlling only their smaller personal donations. In 2017, the Centre for Effective Altruism ran a donor lottery, and I won one of the two blocks of $100,000. After careful deliberation, I recommended that CEA make the following regrants: $70,000 to ALLFED. $20,000 to the Global Catastrophic Risk Institute (GCRI). $5,000 to AI Impacts. $5,000 to Wild Animal Suffering Research. In the remainder of this document, I describe the selection process I used, and then provide detailed evaluations of each of these organisations. Selection Process I am a CS PhD student at UC Berkeley, working to develop reliable artificial intelligence. Prior to starting my PhD, I worked in quantitative finance. This document is independent work and is not endorsed by CEA, the organisations evaluated, or by my current or previous employers. I assign comparable value to future and present lives, place significant weight on animal welfare (with high uncertainty) and am risk neutral. I have some moral uncertainty but would endorse these statements with >90% probability. Moreover, I largely endorse the standard arguments regarding the overwhelming importance of the far future. Since I am mostly in agreement with major donors, notably Open Philanthropy, I tried to focus on areas that are the comparative advantage of smaller donors. In particular, I focused my investigation on small organisations with a significant funding gap. To generate an initial list of possible organisations, I (a) wrote down organisations that immediately came to mind, (b) solicited recommendations from trusted individuals in my network, and (c) reviewed the list of 2017 EA grant recipients. I shortlisted four organisations from a superficial review of the longlist. Ultimately all the organisations on my shortlist were also organisations that immediately came to my mind in (a). This either indicates I already had a good understanding of the space, or that I am poor at updating my opinion. I then conducted a detailed review of each of the shortlisted organisations. This included reading a representative sample of their published work, soliciting comments from individuals working in related areas, and discussion with staff at the organisation until I felt I had a good understanding of their strategy. In the next section, I summarise my current views on the shortlisted organisations. The organisations evaluated were provided with a draft of this document and given 14 days to respond prior to publication. I have corrected any mistakes brought to my attention, and have also included a statement from ALLFED; other organisations were provided with the option to include a statement but chose not to do so. Some confidential details have been withheld, either at the request of the organisation or the individual who provided the information. Summary of conclusions I ranked ALLFED above GCRI as I view their research ...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: How to generate research proposals, published by Jsevillamol on the effective altruism forum. Write a Review Epistemic status: The advice I give is based on anecdotic experience, and what works well for me might not transfer well to others, but my past self would have found this article quite useful As part of the application to FHI’s Summer Fellows Program I had to submit a research proposal, and once I finished my original proposal I had to engage again with the process to select my next research project. In this article I will explain the particular approach I chose for this task, and provide some commentary on what worked well and what did not. I expect you will get a lot of mileage out of this article if you are an early career researcher struggling to generate research ideas or if you are considering pursuing a career in research and would like to peek into how an important chunk of a researcher’s time is spent. In short, my top advice for early career researchers is: Create a pipeline that allows you to note down interesting research questions without committing to them and share them with others to receive feedback When explicitly generating research questions, read research agendas and talk to other people to find disagreements. Think about what makes a good research project to develop taste. My personal take is that what matters most is having concrete research questions, that you can devise a good methodology to answer those questions, that the output you intend to produce has a clear audience and goals and that your environment and background are a good fit to the question. When selecting between ideas, try to fail fast, and don’t be afraid to discard ideas. To do this, try writing up outlines of the projects and schedule conversations with other researchers with overlapping interests. To avoid spending too much time on the meta level, preallocate time to making the decision. If you have trouble deciding between concrete projects, just pick the one you are most excited about and work on it until you find a roadblock. Generating and prioritizing research proposals seems to be a critical part of strategic research, and my informal impression is that systematic approaches are quite underexplored. The overall process I used is split up in three chunks: generating research ideas, curating the ideas and operationalizing the ideas. We will cover each of these parts in separate sections of this article. The outcome of this process is a detailed outline of a research project, which clearly explains the methodology and value of a project and that can be reused as an introduction to a potential publication. The whole process took ~2 weeks. Progress was uneven, on some days I progressed a lot on the research proposal generation and others I just focused on other projects. Brainstorming ideas For the brainstorming phase I set up a brainstorming document where I collected questions that had drawn my attention, together with useful context and notes on what inspired the idea in a bullet point format. To fill the list I resorted to the following strategies: Reading research agendas Talking to other people and finding disagreements Creating taxonomies of areas of interest Reading research agendas proved to be quite fruitful. With research agendas I mostly refer to collections of open questions compiled by other researchers. If you already have a topic of interest you can search research agendas focused precisely on that; if not they can provide an excellent introduction to new areas of research. Some examples of research agendas are Allan Dafoe’s AI Governance Research Agenda [REF], Luke Muehlhauser’s How to study superintelligence strategy [REF] or OPP’s Important unresolved research questions in macroeconomic policy [REF]. Talking to people and finding disagreements was...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: The ITN framework, cost-effectiveness, and cause prioritisation, published by John G. Halstead on the effective altruism forum. Write a Review From reading EA material, one might get the impression that the Importance, Tractability and Neglectedness (ITN) framework is the (1) only, or (2) best way to prioritise causes. For example, in EA concepts’ two entries on cause prioritisation, the ITN framework is put forward as the only or leading way to prioritise causes. Will MacAskill’s recent TedTalk leaned heavily on the ITN framework as the way to make cause prioritisation decisions. Open Philanthropy Project explicitly prioritises causes using an informal version of the ITN framework. In this post, I argue that: Extant versions of the ITN framework are subject to conceptual problems. A new version of the ITN framework, developed here, is preferable to extant versions. Non-ITN cost-effectiveness analysis is, when workable, superior to ITN analysis for the purposes of cause prioritisation. This is because: Marginal cost-effectiveness is what we ultimately care about. If we can estimate the marginal cost-effectiveness of work on a cause without estimating the total scale of a problem or its neglectedness, then we should do that, in order to save time. Marginal cost-effectiveness analysis does not require the assumption of diminishing marginal returns, which may not characterise all problems. ITN analysis may be useful when it is difficult to produce intuitions about the marginal cost-effectiveness of work on a problem. In that case, we can make progress by zooming out and carrying out an ITN analysis. In difficult high stakes cause prioritisation decisions, we have to get into the weeds and consider in-depth the arguments for and against different problems being cost-effective to work on. We cannot bypass this process through simple mechanistic scoring and aggregation of the three ITN factors. For this reason, the EA movement has thus far significantly over-relied on the ITN framework as a way to prioritise causes. For high stakes cause prioritisation decisions, we should move towards in-depth analysis of marginal cost-effectiveness. [update - my footnotes didn't transfer from the googledoc, so I am adding them now] 1. Outlining the ITN framework Importance, tractability and neglectedness are three factors which are widely held to be correlated with cost-effectiveness; if one cause is more important, tractable and neglected than another, then it is likely to be more cost-effective to work on, on the margin. ITN analyses are meant to be useful when it is difficult to estimate directly the cost-effectiveness of work on different causes. Informal and formal versions of the ITN framework tend to define importance and neglectedness in the same way. As we will see below, they differ on how to define tractability. Importance or scale = the overall badness of a problem, or correspondingly, how good it would be to solve it. So for example, the importance of malaria is given by the total health burden it imposes, which you could measure in terms of a health or welfare metric like DALYs. Neglectedness = the total amount of resources or attention a problem currently receives. So for example, a good proxy for the neglectedness of malaria is the total amount of money that currently goes towards dealing with the disease.[^1] Extant informal definitions of tractability Tractability is harder to define and harder to quantify than importance and neglectedness. In informal versions of the framework, tractability is sometimes defined in terms of cost-effectiveness. However, this does not make that much sense because, as mentioned, the ITN framework is meant to be most useful when it is difficult to estimate the marginal cost-effectiveness of work on a particular cause. There would be no reas...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Coronavirus Research Ideas for EAs, published by Peter Wildeford on the effective altruism forum. write a Review COVID-19 is a tragedy with more everyday social implications in the developed world than anything since World War II. Many EAs are wondering what, if anything, to do about COVID to help the world. To try to investigate further, I am helping articulate possible research ideas for further discussion and consideration. The kind of research we need to do in this situation is very different from the kind of research EA is used to doing well. We normally spend several months carefully researching a single topic that doesn’t change very much. With COVID, everything about this is reversed—the situation currently requires us to rapidly get up to speed and produce research in a matter of days in a situation that is rapidly changing. There is an exponentially growing “speed premium”—much more than we’ve ever seen. As such, please note that we have waived our normal review and quality check standards to get this out ASAP and there may be considerable mistakes in this article. On the other hand, I do urge some degree of caution and humility. Let’s not all collectively lose our minds. We should worry at least some about armchair epidemiology from non-experts (though also see this) and properly recognize what our skills are and aren’t, where we can contribute and where we shouldn’t. We should also be careful that research done at breakneck speed is more likely to be wrong. I'm a bit worried that many people will want to work on this topic just so they don't feel helpless in the face of the pandemic, or because there’s a lot of attention being paid to it now, or that it feels high-status and urgent, or many other reasons unconnected from EA-related impact. It can be really tough to see your community, friends, family, and self hurting and not feel like there’s much you can do. However, the work EA was doing before this pandemic still remains of importance now. If you can contribute to the anti-COVID effort that is great, but it is also fine (sometimes even preferable!) to continue to research what you were researching before. Naturally, these research questions were put together rapidly and may continue to evolve rapidly. I numbered the questions to make them easier to reference and discuss. They’re grouped by topic. Note that the numbering system may get a bit weird as I add new questions without wanting to renumber all the other questions. I am trying to keep numbers stable so they can be referred to as shorthand. Questions vary a lot in their urgency, importance, tractability, and neglectedness. If you’re already up to speed, I think questions 1, 3, 4, 14, 15, 19, 21, 22 and 33 are particularly important and urgent to look into right now. I’m not sure how best to coordinate around these and other questions... the question of coordination itself should be the subject of active research (see question 3). For now, feel free to comment here, or centralize on LessWrong and the “Effective Altruism Coronavirus Discussion” FB group. If you intend to dedicate significant effort to any of these questions, it might also be worth you joining our cross-org Slack group—comment here or email me (peter@rethinkpriorities.org) to be added. I do think we should try to communicate early and often about our progress and aim to produce results quickly and share with others. Note that this isn’t the only compilation of coronavirus research questions. I also know of LessWrong’s agenda and this list of questions. I will try to keep this all up to date as rapidly as I can. Meta-Research 1.) Just how bad are things right now? How bad might we expect it to get? What is the current state of play and what are various plausible scenarios forward? [PRIORITY] The COVID-19 pandemic is a rapidly escalat...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Introducing Animal Advocacy Africa , published by AnimalAdvocacyAfrica on the effective altruism forum. Write a Review We’re excited to introduce a new EA project: Animal Advocacy Africa! Animal Advocacy Africa (AAA) aims to develop a collaborative and effective animal advocacy movement in Africa. We plan to do this by engaging organisations and individual advocates within farmed animal advocacy in Africa and using this engagement to seek cost-effective opportunities to help animals. We aim to achieve this via a two-stage process: Six-month research phase: Identifying which barriers are holding the animal advocacy movement back in Africa, and which interventions can most effectively address these barriers. We have contacted organisations in South Africa, Kenya, Tanzania, Nigeria, Ghana, Zimbabwe, Lesotho and Swaziland. Six-month pilot phase: Implementing a pilot program based on our findings, which we can later scale up in African countries that seem promising to work in (e.g. because there are existing organisations working there that we could support). If we can’t find a strong pilot candidate that we can scale, we plan to pivot to an alternative approach. AAA is a program of Credence Institute, a South African non-profit dedicated to advancing the interests of animals. The team at Credence has over a decade’s worth of experience in animal advocacy and the meat alternatives space in Africa, developing relationships with people from the EA community, industry, academia, and the animal sciences along the way. We can draw upon these relationships, and those of its associates’, board, and volunteers, to engage key stakeholders in the animal advocacy movement, both in Africa as well as abroad. This idea was refined during Charity Entrepreneurship’s incubation program and is led by Lynn Tan (Director of Research) and Cameron King (Director of Operations), who were in the program along with Brett Thompson (Advisor). Our other founding team member is Jenna Hiscock (Director of Partnerships Development). Since then, we have received a grant of $40,000 from the Effective Altruism Animal Welfare Fund to begin and maintain the research phase of our initiative for six months. Why Africa? Below, we examine working on animal advocacy in Africa through the ITN framework: Importance: Africa is currently home to approximately 3.2 billion land-based farm animals and given its rising population and urbanisation — significant factors driving demand for livestock products — a shift toward intensive animal farming practices looks inevitable. According to the FAO, global annual meat production in Africa will reach 35 million tonnes by 2030, which would be an increase of 22 million since 2015. Given the negative impact of intensive animal agriculture on the lives of animals — restricted movement, mutilation without pain relief, death from dehydration, and more horror — finding ways to improve, displace, and prevent this practice should be a global concern. Yet, when it comes to animal advocacy, Africa is being left behind — both in terms of research and funding relative to the number of farmed animals. We want to prevent future animals from coming into a life of suffering. Ensuring that African countries do not commit to the same path of animal cruelty is part of our mission. To accomplish this, we believe the African animal advocacy space will have to attract more funding and become more effectiveness-minded — two mutually reinforcing elements. Tractability: We think interventions that have optimal timing should be prioritised over those that do not or those that could be more effectively implemented at a different time. This would mean targeting countries with low but growing animal production rates such as those in Africa. Acting preemptively, in this case banning intensive animal farmi...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: GCRs mitigation: the missing Sustainable Development Goal, published by AmAristizábal on the effective altruism forum. Thanks to Luca Righetti, Elise Bohan, Fin Moorhouse, Max Daniel, Konrad Seifert and Maxime Stauffer for their valuable comments and thoughts on the draft and future steps. Thanks to Owen for telling me to turn this idea into a post! Summary and introduction Throughout this post, I will explore some overlaps between sustainability (focusing on Sustainable Development Goals) and longtermism (focusing on Global Catastrophic Risks mitigation). I wrote this over a two-week period to get some tentative thoughts out. My goal with posting this is to find other people interested in thinking about the intersection of sustainable development and GCRs mitigation as well as to invite feedback for how/if to proceed with research or practical projects in this area. The write-up doesn't represent any strongly held and stable views, but is meant to explore if there is a policy opportunity for longtermists to work with sustainable development policies. More specifically, I want to see if it is worth pushing the next SDGs agenda with a bigger focus on GCRs mitigation. Roughly, I want to explore if this is a bridge worth building: In the first section, I will briefly overview the Sustainable Development Goals (SDGs) and Global Catastrophic Risks (GCRs), explaining why it could make sense to start building a link between these. In section 2, I will explore how GCRs mitigation fits into the SDGs, using COVID-19 as an example of how risk mitigation is foundational to sustainable development. In section 3, I will quickly point out some potential overlaps between longtermism and sustainability and mention the idea of a risk budget as the ultimate non-renewable resource. In section 4, I will portray a way of understanding SDGs in terms of longtermist grand strategies, followed by a final section exploring the pros and cons of building this bridge and possible future steps if it is worth pursuing. 1. Overview of SDGs and GCRs SDGs I am broadly interested in the overlap between sustainability –with its many definitions– and longtermism, but first I want to explore the SDGs primarily for their policy opportunities (other sustainability frameworks could be explored in future posts). In 2015 the United Nations General assembly set up the Sustainable Development Goals, which are 17 goals meant to be accomplished by 2030. They were adopted by all UN members and are a “call for action” for member states to eradicate poverty and improve different quality of life indicators whilst also tackling climate change and environmental damage. Here is a summarized timeline of sustainability and sustainable development: The concept of sustainability can be traced back at least to 1700, and was applied to forestry in Saxony. It emerged in a time of scarcity when the mining industry had consumed whole forests and trees had been cut out at unsustainable rates for decades, threatening the livelihood of thousands. 20th century: environmental movements started to point out that there were environmental costs associated with the many material benefits that were now being enjoyed due to the industrial revolution from the 18th and 19th century. In 1973 and 1979 there were energy crises that demonstrated the extent to which the global community had become dependent on non-renewable energy resources. 1970s: The concept of "degrowth" (somewhat related to sustainability) properly appeared during the 1970s. It was a political, economic, and social movement that critiqued “productivism”, the paradigm of economic growth, pointing out the social and ecological harm caused by the pursuit of infinite growth and Western "development" imperatives. 1987: Modern concept of sustainable development derived from the Brun...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Feedback available for EA Forum drafts, published by Aaron Gertler on the effective altruism forum. Write a Review Update, 12/7/21: Given my departure from CEA, I'm no longer sharing feedback. I recommend the EA Editing and Review group as another option! If providing feedback to random Forum users sounds fun to you, and you want to take over for me, contact content@centreforeffectivealtruism.org to express your interest. Please include a description of your past writing/editing experience. This was a widely-demanded service, so CEA might be interested in hiring someone to continue it (though I'm not certain about this). Hello, Forum! This is Aaron, your friendly neighborhood moderator (and a content writer/editor at CEA). I’m writing this to let you know that I offer a free service as part of my work for CEA: If you want someone to read your Forum post before you publish it, I will gladly do that. My goal is to help people who are uncertain about an idea or draft by getting them to a point where they feel comfortable publishing a post. That said, you’re always welcome to run things by me even if you’re already sure you want to publish them. Also, I'm not the only person doing this: the EA Editing and Review Facebook group has a community of volunteer editors, who will often be faster or have more relevant experience than me. (Though you can also just share with both of us!) Services I offer Commenting on an idea that hasn’t yet been written up, to suggest directions you could take or material you might want to read before you write a draft. Making broad suggestions about major changes you could make, or pieces on related topics that I’d be excited to see. Making minor suggestions about points or sentences that I found unclear. I rarely have time for a full copyedit, but I may note typos I happen to see. Sending your draft to other people who know more about the topic than I do, or otherwise seem like they’d give useful feedback. I’ll ask for permission before I do this. How to get help Email me a shared document with a draft of your post. Not a shared draft on the Forum or a Word Doc, please — either a Google Doc or another online document that I can make comments on without having to save a separate draft. This makes the process much easier from my side. Let me know when you need to hear back by. Even if there’s no rush, it helps me to have a fake deadline I can add to my task-tracking system, so something like “two weeks from today, but you can extend that if you need to” is better than “whenever”. If I doubt the deadline will work with my schedule, I may say something like “it’s more likely than not that I won’t get to this”. Tell me what kind of feedback you want. For example: “I’m new to effective altruism, and I’m worried that I’m saying something obvious that will bore or annoy people who have more experience. Do you know of other posts that cover the same points?” “I’m not sure this belongs on the Forum at all. What do you think?” “I think this post is almost perfect, and I’m not looking to make major changes, but I’d still like feedback on paragraphs #4 and #5.” I’ve already done this for many Forum users, including people who’d never posted before and people who have thousands of karma. I’m not the world’s greatest editor, but I’ve written and edited a lot of things for money over the years, and I spend a lot of time thinking about how to communicate EA ideas. Feedback on my feedback In November 2020, I reached out to the 70 people I'd worked with so far, to ask whether they'd been satisfied with the feedback I gave. From 39 responses, the average score was 8.3/10, and comments included: "I think some of the most important traits to have for giving feedback on the EA Forum are friendliness and non-judgmentalness, and you definitely nail that." "I appreciat...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Effective Altruism and Free Riding, published by sbehmer on the effective altruism forum. Write a Review I'd like to thank Parker Whitfill, Andrew Kao, Stefan Schubert, and Phil Trammell for very helpful comments. Errors are my own. Many people have argued that those involved in effective altruism should “be nice”, meaning that they should cooperate when facing prisoner’s dilemma type situations ([1] [2] [3]). While I believe that some of these are convincing arguments, it seems to be underappreciated just how often someone attempting to do good will face prisoner’s dilemmas. Previous authors seem to highlight mostly zero-sum conflict between opposing value systems [3] [4] or common-sense social norms like lying [1]. However, the problem faced by a group of people trying to do good is effectively a public goods problem [10]; this means that, except in rare cases (like where people 100% agree on moral values), someone looking to do good will be playing a prisoner’s dilemma against others looking to do good. In this post I first give some simple examples to illustrate how collective action problems almost surely arise between a group of people looking to do good. I then argue that the standard cause-prioritization methodology used within EA recommends to defect (“free-ride”) in these prisoner’s dilemma settings. Finally, I discuss some potential implications of this, including that there may be harms from popularizing EA thinking and that there may be large gains from improving cooperation. Main Points: 1. A group of people trying to do good are playing a form of a public goods game. Except in rare circumstances, this will lead to inefficiencies due to free-riding (defecting), and thus gains from cooperation. 2. Free-riding comes from individuals putting resources toward causes which they personally view as neglected (being under-valued by other people’s value systems) at the expense of causes for which there is more consensus. 3. Standard EA cause prioritization recommends that people free-ride on others' efforts to do good (at least when interacting with people not in the EA community). 4. If existing societal norms are to cooperate when trying to do good, EA may cause harm by encouraging people to free-ride. 5. There may be large gains from improving cooperation. Collective Action Problems Among People Trying to do Good Note that the main argument in this section is not original to me. Others within EA have written about this, some in more general settings than what I look at here [10]. The standard collective action problem is in a setting where people are selfish (each individual cares about their own consumption) but there’s some public good, say clean air, that they all value. The main issue is that when deciding whether to pollute the air or not, an individual doesn’t consider the negative impacts that pollution will have on everyone else. This creates a prisoner’s dilemma, where they would all be better off if they didn’t pollute, but any individual is better off by polluting (defecting). These problems are often solved through governments or through informal norms of cooperation. Here I argue that this collective action problem is almost surely present among a group of people trying to do good, even if every member of the group is completely unselfish. All that is needed is that people’s value systems place some weight on how good the world is (they are not simply warm-glow givers) and that they have some disagreement about what counts as good (there’s some difference in values). The key intuition is that in an uncooperative setting each altruist will donate to causes based on their own value system without considering how much other altruists value those causes. This leads to underinvestment in causes which many different value systems place positive weight ...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: 3 suggestions about jargon in EA, published by MichaelA on the effective altruism forum. Write a Review Summary and purpose I suggest that effective altruists should: Be careful to avoid using jargon to convey something that isn’t what the jargon is actually meant to convey, and that could be conveyed well without any jargon. As examples, I’ll discuss misuses I’ve seen of the terms existential risk and the unilateralist’s curse, and the jargon-free statements that could’ve been used instead. Provide explanations and/or hyperlinks to explanations the first time they use jargon. Be careful to avoid implying jargon or concepts originated in EA when they did not. I’m sure similar suggestions have been made before, both within and outside of EA. This post’s purpose is to collect the suggestions together in one post that (a) can be linked to, and (b) has this as its sole focus (rather than touching on these suggestions in passing). This post is intended to provide friendly suggestions rather than criticisms. I’ve sometimes failed to follow these suggestions myself. 1. Avoid misuse The upside of jargon is that it can efficiently convey a precise and sometimes complex idea. The downside is that jargon will be unfamiliar to most people. I’ve seen instances where EAs or EA-aligned people have used jargon to convey something other than what the jargon is meant to convey. This erodes the upside of that jargon, while also unnecessarily having that downside of unfamiliarity. In these instances, it would be better to say what one is trying to say without jargon (or with the different, appropriate jargon). Of course, “avoid misuse” is a hard principle to disagree with - but how do you implement it, in this case? I have two concrete suggestions (though I’m sure other suggestions could be made as well): Before using jargon, think about whether you’ve actually read the source that introduced that jargon, and/or the most prominent source that used the jargon (i.e., the “go-to” reference). If you haven’t, perhaps read that before using the jargon. If you read that a long time ago, perhaps double-check it. I suggest this in part because I suspect people often encounter jargon second-hand, leading to a “telephone game” effect. See whether you can say the same idea without the jargon, at least in your own head. This may help you realise that you’re unsure what the jargon means. Or it may help you realise that the idea is easy to convey without the jargon. I’ll now give two examples I’ve come across of the sort of misuse I’m talking about. Existential risk For details, see Clarifying existential risks and existential catastrophes. What the term is meant to refer to: The most prominent definitions of existential risk are the following: An existential risk is one that threatens the premature extinction of Earth-originating intelligent life or the permanent and drastic destruction of its potential for desirable future development (Bostrom, 2012) And: An existential risk is a risk that threatens the destruction of humanity’s longterm potential (Ord, 2020) Both authors make it clear that this refers to more than just extinction risk. For example, Ord breaks existential catastrophes down into three main types: extinction, unrecoverable collapse, and unrecoverable dystopia. What the term is sometimes mistakenly used for: The term existential risk is sometimes used when the writer or speaker is actually referring only to extinction risk (e.g., in this post, this podcast, and this post). This is a problem because: This makes the statements unnecessarily hard to understand for non-EAs. We could suffer an existential catastrophe even if we do not suffer extinction, and it’s important to remain aware of this. It would be better for these speakers and writers to just say “extinction risk”, as that term i...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Global lead exposure report, published by DavidBernard, Jason Schukraft on the effective altruism forum. Rethink Priorities has been piloting expanding into human-focused neartermist global priorities research. This post is one of three outputs from the pilot program. Open Philanthropy provided funding for this project and we use their general frameworks for evaluating cause areas, but they do not necessarily endorse its conclusions. We don’t intend this report to be Rethink Priorities’ final word on lead exposure. We hope the report galvanizes a productive conversation about lead exposure within the EA community. We are open to revising our views as more information is uncovered. If you are interested in doing similar research, please apply to Rethink Priorities’ Global Health and Development Staff Researcher position (deadline 13th June 2021). Key Takeaways Lead exposure is a large problem with social costs on the order of $5-10 trillion annually, most of which come through neurological damages and losses in IQ causing lost income later in life. Lead exposure is diverse both in terms of sources and geography, with there being many different pathways for environmental lead to enter the human body and exposure being common across nearly all low- and middle-income countries. Although the proportion of the lead burden attributable to different sources is unclear, important exposure pathways include informal recycling of lead acid batteries, residential use of lead-based paint, consumption of lead-adulterated foodstuffs, and cookware manufactured with scrap lead. Strategies for reducing lead exposure are mostly context- and source-dependent, but generally preventing new lead entering the environment seems more tractable than removing existing lead. We estimate that $6-10 million globally is currently spent by NGOs focused on reducing lead exposure in low- and middle-income countries. We are confident that existing and potential new NGOs in the area currently have the capacity to productively absorb $5-10 million annually in additional money, and it’s possible though unlikely that this capacity would expand to $25 million annually over the next 5 years. Rough initial cost-effectiveness estimates suggest that some strategies for dealing with lead exposure could be as or more cost-effective than GiveWell top charities. Executive Summary We believe that the problem of lead exposure deserves more attention than it currently receives in the neartermist effective altruism community. Exposure to lead causes many problems. High levels of lead exposure can be fatal. Even at low levels of exposure, lead exposure causes neurological damage, especially in children. Lead exposure is associated with many cognitive and behavioral problems and is a significant risk factor for cardiovascular diseases, mental disorders, and kidney disease. Worldwide, lead exposure is estimated to impose a 21.7 million DALY burden (for comparison, malaria causes a 46.4 million DALY burden) and we think the true value is likely 30-100% larger. The economic costs of lead exposure, primarily lost earnings due to reductions in IQ, are estimated to total around a trillion dollars annually but we think the true value is 30-50% of this size. If one adopts a logarithmic income utility model[1], the utility value of this dollar burden is an order of magnitude higher, since 94% of the loss occurs in low- and middle-income countries (LMICs) which have on average 10x lower incomes than the USA. Lead exposure is common across LMICs. Important exposure pathways include the informal recycling of lead acid batteries,[2] the residential use of lead-based paint, the consumption of lead-adulterated foodstuffs (especially spices), and the use of improperly sealed aluminum-lead alloy cookware. Unfortunately, the proportion of ...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Canva CEO commits at least $6 billion “to do the most good”, published by 22tom on the effective altruism forum. Melanie Perkins, the CEO of Canva, recently announced that they intend to donate the “vast majority of their equity to do good in the world”. This comes out to at least $6 billion. I think this is awesome news and a potentially exciting opportunity for the EA community. As reported in several media outlets, Canva has recently been valued at $40 billion USD. Following this, Melanie Perkins (Canva’s CEO) outlined in a blog post their vision, through a simple Two-Step plan: With a $40 billion valuation, Canva has made a lot of progress on step 1. To achieve step 2, Melanie and her husband and co-founder, Cliff, have “committed the vast majority of their equity (30% of Canva) to do good in the world”, through the Canva Foundation.[1] This works out to be the equivalent of at least $6 billion USD, and potentially more.[2] To put this into perspective, that would be more than 10 times that of all Giving What We Can pledges (using Ben Todd’s estimates). Canva have already taken the 1% pledge,[3] but are now looking to expand their philanthropy further. Excitingly for EAs, this starts with a $10 million pilot program with GiveDirectly in South Africa. They then “hope to rapidly scale this more broadly and to contribute to the lives of as many people across the globe as we can.” [emphasis added] This strikes me as both awesome news and an exciting opportunity. What could/should EAs do about this? I have some very tentative suggestions: Find out more. I heard about this today, and have only spent ~1 hour Googling. Investigating more about this news and the Canva Foundation seems potentially worthwhile, to get a better grip on what this could mean for EAs. Maybe nothing. There are potential backfire risks when doing outreach, the CEO may have their own priorities, or perhaps the money is already committed to EA causes, so action is less valuable. Something else? I have spent very little time looking into this, but would be interested in other people's thoughts. Disclaimer: I have no associations or affiliations with Canva. From some Googling, it seems that the Canva Foundation was registered with the Australian government in May 2020. Their stated objective is “providing benevolent relief to people and communities in need in Australia and around the world, by and without limitation: (a) improving access to quality education for disadvantaged youth; (b) providing benevolent support to people in need when a crisis strikes; (c) establishing collaborative partnerships with other benevolent institutions to promote, support and amplify their activities; (d) doing such other things or activities which are necessary, incidental or conducive to the attainment of these objects.” ↩︎ $40 billion x 30% x 50%. However, “vast majority” could mean much more than 50%, potentially reaching double-digit billions. ↩︎ Pledge 1% encourages firms to give 1% of their equity, profits, time or product away. However, they don’t seem to focus on that money being spent effectively (as far as I can tell). ↩︎ thanks for listening. to help us out with the nonlinear library or to learn more, please visit nonlinear.org.
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: 2018 AI Alignment Literature Review and Charity Comparison, published by Larks on the effective altruism forum. Write a Review Cross-posted to LessWrong. Introduction Like last year and the year before, I’ve attempted to review the research that has been produced by various organisations working on AI safety, to help potential donors gain a better understanding of the landscape. This is a similar role to that which GiveWell performs for global health charities, and somewhat similar to an securities analyst with regards to possible investments. It appears that once again no-one else has attempted to do this, to my knowledge, so I've once again undertaken the task. This year I have included several groups not covered in previous years, and read more widely in the literature. My aim is basically to judge the output of each organisation in 2018 and compare it to their budget. This should give a sense for the organisations' average cost-effectiveness. We can also compare their financial reserves to their 2019 budgets to get a sense of urgency. Note that this document is quite long, so I encourage you to just read the sections that seem most relevant to your interests, probably the sections about the individual organisations. I do not recommend you skip to the conclusions! I’d like to apologize in advance to everyone doing useful AI Safety work whose contributions I may have overlooked or misconstrued. Methodological Considerations Track Records Judging organisations on their historical output is naturally going to favour more mature organisations. A new startup, whose value all lies in the future, will be disadvantaged. However, I think that this is correct. The newer the organisation, the more funding should come from people with close knowledge. As organisations mature, and have more easily verifiable signals of quality, their funding sources can transition to larger pools of less expert money. This is how it works for startups turning into public companies and I think the same model applies here. This judgement involves analysing a large number papers relating to Xrisk that were produced during 2018. Hopefully the year-to-year volatility of output is sufficiently low that this is a reasonable metric. I also attempted to include papers during December 2017, to take into account the fact that I'm missing the last month's worth of output from 2017, but I can't be sure I did this successfully. This article focuses on AI risk work. If you think other causes are important too, your priorities might differ. This particularly affects GCRI, FHI and CSER, who both do a lot of work on other issues. We focus on papers, rather than outreach or other activities. This is partly because they are much easier to measure; while there has been a large increase in interest in AI safety over the last year, it’s hard to work out who to credit for this, and partly because I think progress has to come by persuading AI researchers, which I think comes through technical outreach and publishing good work, not popular/political work. Politics My impression is that policy on technical subjects (as opposed to issues that attract strong views from the general population) is generally made by the government and civil servants in consultation with, and being lobbied by, outside experts and interests. Without expert (e.g. top ML researchers at Google, CMU & Baidu) consensus, no useful policy will be enacted. Pushing directly for policy seems if anything likely to hinder expert consensus. Attempts to directly influence the government to regulate AI research seem very adversarial, and risk being pattern-matched to ignorant opposition to GM foods or nuclear power. We don't want the 'us-vs-them' situation, that has occurred with climate change, to happen here. AI researchers who are dismissive of safety law...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Corporate campaigns affect 9 to 120 years of chicken life per dollar spent, published by saulius on the effective altruism forum. Write a Review Summary In this article, I estimate how many chickens will be affected by corporate cage-free[1] and broiler welfare[2] commitments won by all charities, in all countries, during all the years between 2005 and the end of 2018. According to my estimate, for every dollar spent, 9 to 120 years of chicken life will be affected. However, the estimate doesn't take into account indirect effects which could be more important. The estimate is summarized in the table below.[3] In the table, everything is expressed in my subjective 90% confidence intervals. Numbers in parentheses are means. M stands for million, and B stands for billion. The full estimation can be seen in the Guesstimate model. Numbers in the table may not add up because of the way Guesstimate works. Table1 In addition to direct costs on corporate campaigns, the cost estimate includes the costs of undercover investigations about the living conditions of chickens, relevant research, and all administrative expenses associated with these activities. It doesn’t include the costs of legislative campaigns and future costs of ensuring compliance to commitments that are already made. Consequently, predictions of follow-through rates assume that the spending on ensuring compliance will not be substantial. There are many ways this cost-effectiveness could be misleading. For example: I only estimate direct short term effects. Indirect effects on chicken and egg consumption, wild animal welfare, public opinion on farm animal issues, and long-term future could be more important. This is cost-effectiveness of past campaigns. Cost-effectiveness in the future might be different because companies could learn how to deal with animal advocates, it might be done in different countries, or for different asks. This is not an estimate of what an additional donated dollar would achieve, as I do not discuss room for more funding and there is a high variance in cost-effectiveness within the spending associated with corporate campaigns. In the first appendix, I show that even under very pessimistic assumptions, fighting for welfare reforms has affected more than one chicken-year per dollar spent In the second appendix, I discuss how the involvement of volunteers slightly skews this cost-effectiveness estimate. In short, volunteer time is a cost that is not accounted for. In the third appendix, I review previous cost-effectiveness estimates of corporate campaigns by Capriati (2018), Bollard (2016), Dickens (2016), and Animal Charity Evaluators. In the fourth appendix, I explain why I chose to estimate the cost-effectiveness of campaigns in all countries, during all the years between 2005 and the end of 2018, rather than focusing on a specific charity or year, despite the fact that very few commitments were won before 2013. In short, all efforts are interrelated. Efforts in one year can lead to victories in later years, and a single commitment can be influenced by multiple charities working in multiple countries. This article is a project of Rethink Priorities. It contains a lot of details but I tried to make it easy to skim. The section I recommend reading the most is Ways this estimate could be misleading. The number of chickens that should be affected According to unpublished estimates by Lewis Bollard from the Open Philanthropy Project (OpenPhil), commitments that were made before the end of 2018 should affect at least: ~243 million egg-laying hens in the U.S. ~135.6 million hens in other countries[4] ~512 million broilers (meat chickens) in the U.S. He arrived at these figures by estimating numbers of animals used by many of the companies that made commitments. Estimates are very approximate ...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: What to know before talking with journalists about EA, published by sky on the effective altruism forum. Write a Review Journalists regularly contact individuals, groups, and organizations who are involved in the effective altruism space. At first glance, opportunities to speak with journalists may seem like a good way to spread information about important work and ideas. However, we have found that they can also be a good way to create misunderstandings or negative impressions of EA or of particular projects. Because evaluating and engaging in successful media engagements requires specialized skills and knowledge, it’s important to seek advice or resources, proceed carefully, and be prepared. Quick takeaway: when you are contacted by the media, we think it’s important that you connect with resources and advisors so you can make informed decisions. Many large organizations have full-time staff who do media advising, but we know most community members won’t have access to such resources. CEA does not have full-time media staff but we do have some experience assisting people with media questions. We would like to offer you information and resources for deciding if or how to participate in media opportunities. If you receive media inquiries, feel free to email your questions to media@centreea.org. You can also refer others to this post or to our full guide: Advice for responding to journalists. EA and journalism CEA regularly hears about journalists who are interested in interviewing people about EA. So far this year, we’ve heard from ten groups or individuals who were considering whether or how to participate in a media piece. Here are some examples: A producer of a popular podcast emails someone with questions about EA for an upcoming story and states that they have a pressing deadline. The community member wants to respond professionally and feels pressured to do so quickly. They’re not sure what best practices to follow to make the decision about participating or not. A journalist attends a local EA group event, perhaps without the group knowing in advance. Now attendees need to decide on the spot if they want to participate in a story, when they likely arrived expecting a casual social event. Some attendees at the event may be people who work in government or other sensitive fields where they are expected to maintain a neutral public image. They may not know their employer’s policies around media, or their employer may have an expectation that employees not participate in media engagements related to their work without pre-approval. They may wonder if they need to leave the event. Attendees may speak casually without realizing they could be quoted, and may misunderstand what it means to speak “off the record.” If the journalist is unfamiliar with EA, they may come away with misunderstandings, depending on the direction the conversation happens to take. A journalist approaches several EA organizations, local groups, and individuals with invitations to be interviewed for a story or documentary they’re working on. Now each of these people and groups must make a decision about whether to participate, often without having much time to research important considerations: What is the journalist’s understanding of EA? Have they covered it before? What approach did they take in the past? Who else is being interviewed or who else might be a good resource for this particular kind of story? Is the potential interview related to one’s area of expertise or outside of it? What will happen if the request for an interview is declined? Will the piece go forward in a less informed way, or will it not be produced at all? Many large organizations have media professionals who specialize in preparing and training staff or researching questions like the ones above. CEA thinks that kind of ...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Intervention Profile: Ballot Initiatives, published by Jason Schukraft on the effective altruism forum. Write a Review Executive summary Ballot initiatives are a form of direct democracy in which citizens can gather signatures to qualify a proposed piece of legislation for the ballot, which is then subject to a binding up-or-down vote by the general electorate. Ballot initiatives are possible in Switzerland, Taiwan, many U.S. states and cities, and elsewhere. Ballot initiatives appear to maintain several advantages over more traditional policy lobbying, including lower barriers to entry and more direct control over the final legislation. However, the ultimate cost-effectiveness of a ballot initiative campaign depends on several factors, many of which are difficult to specify precisely. Although ballot initiatives hold enough promise to warrant additional investigation, it is not yet possible to say to what extent ballot initiative campaigns ought to be pursued by the effective altruism community. Introduction and context This post is the first[1] in Rethink Priorities’ planned series on using ballot initiatives to advance effective altruist (EA) causes.[2] In this post we explain what a ballot initiative is, what might feasibly be accomplished with ballot initiatives, and why ballot initiatives deserve attention as a potentially effective intervention across a number of different cause areas. We offer some basic details on the ballot initiative process as well as some limitations that any organization considering a ballot initiative ought to be aware of. Finally we outline some areas of future research that we and some like-minded groups intend to explore. To be clear, this post does not attempt to argue that ballot initiatives are a cost-effective intervention, either in general or for any particular cause area. Such an argument would require a more detailed analysis than we have as yet undertaken. Although we discuss many past and potential initiative campaigns, this discussion should not be construed as an endorsement of the effectiveness or even the positive value of the initiative campaigns.[3] The goal of this post is to bring ballot initiatives to the collective attention of the EA community to help promote future research into the effectiveness of ballot initiative campaigns for EA-aligned policies and movement-building. What is a ballot initiative? Ballot initiatives are a way for ordinary citizens to directly suggest and then vote on proposed legislation. A ballot initiative is a vehicle for enacting policy proposals that originate outside elected legislative bodies. Generally speaking, in jurisdictions that allow ballot initiatives, any citizen can submit an initiative, which, if it attracts the requisite popular support and meets certain legal requirements, is then placed on the ballot of an upcoming election. In broad terms, the process begins with the drafting of a petition. If the petition garners the required number of voter signatures during some specified time period, it is then put up for a direct and binding[4] vote. If the measure passes, it automatically becomes law.[5] In this way ballot initiatives bypass elected legislative bodies and are thus a form of direct democracy. Terminology sometimes varies by jurisdiction and is often confusing. A ballot initiative should be distinguished from a referendum, which is the process by which some piece of government policy (either already enacted or merely proposed) is put to the electorate for a general vote.[6] The key difference is that referenda concern policies originally crafted by the government whereas initiatives concern policies crafted by the citizens themselves.[7] Both initiatives and referenda result in ballot measures, which is the general term for policy proposals that are put to an elect...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Illegible impact is still impact, published by G Gordon Worley III on the effective altruism forum. Write a Review In EA we focus a lot on legible impact. At a tactical level, it's the thing that often separates EA from other altruistic efforts. Unfortunately I think this focus on impact legibility, when taken to extremes and applied in situations where it doesn't adequately account for value, leads to bad outcomes for EA and the world as a whole. Legibility is the idea that only what can easily be explained and measured within a model matters. Anything that doesn't fit neatly in the model is therefore illegible. In the case of impact, legible impact is that which can be measured easily in ways that a model predicts is correlated with outcomes. Examples of legible impact measures for altruistic efforts include counterfactual lives saved, QALYs, DALYs, and money donated; examples of legible impact measures for altruistic individuals include the preceding plus things like academic citations and degrees, jobs at EA organizations, and EA Forum karma. Some impact is semi-legible, like social status among EAs, claims of research progress, and social media engagement. Semi-legible impact either involves fuzzy measurement procedures or low confidence models of how the measure correlates with real world outcomes. Illegible impact is, by comparison, invisible, like helping a friend who, without your help, might have been too depressed to get a better job and donate more money to effective charities or filling a seat in the room at an EA Global talk such that the speaker feels marginally more rewarded for having done the work they are talking about and marginally incentives them to do more. Illegible impact is either hard or impossible to measure or there's no agreed upon model suggesting the action is correlated with impact. And the examples I gave are not maximally illegible because they had to be legible enough for me to explain them to you; the really invisible stuff is like dark matter—we can see signs of its existence (good stuff happens in the world) but we can't tell you much about what it is (no model of how the good stuff happened). The alluring trap is thinking that illegible impact is not impact and that legible impact is the only thing that matters. If that doesn't resonate, I recommend checking out the links above on legibility to see when and how focusing on the legible to the exclusion of the illegible can lead to failure. One place we risk failing to adequately appreciate illegible impact is in work on far future concerns and existential risk. This comes with the territory: it's hard to validate our models of what will happen in the far future, and the feedback cycle is so long that it may be thousands or millions of lifetimes before we get data back that lets us know if an intervention, organization, or person had positive impact, let alone if that impact was effectively generated. Another place we risk impact illegible is in dealing with non-humans since there remains great uncertainty in many people's minds about how to value the experiences of animals, plants, and non-living dynamic systems like AI. Yes, people who care about non-humans are often legible to each other because they share enough assumptions that they can share models and can believe measures in terms of those models, but outside these groups interventions to help non-humans can seem broadly illegible, up to interpreting these the interventions, like those addressing wild animal suffering, as being silly or incoherent rather than potentially positively impactful. Beyond these two examples, there's one place where I think the problems of illegible impact are especially neglected and that is easily tractable if we bother to acknowledge it. It's one EAs are already familiar with, though likely no...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: A central directory for open research questions, published by MichaelA on the effective altruism forum. Write a Review Quite wonderfully, there has been a proliferation of research questions EAs have identified as potentially worth pursuing, and now even a proliferation of collections of such questions. So like a good little EA, I’ve gone meta: this post is a collection of all such collections I’m aware of. I hope this can serve as a central directory to all of those other useful resources, and thereby help interested EAs find questions they can investigate to help inform our whole community’s efforts to do good better. Some things to note: It may be best to just engage with one set of questions that are relevant to your skills, interests, or plans, and ignore the rest of this post. It’s possible that some of these questions are no longer “open”. I’ve included some things that aren’t explicitly written as collections of research questions, as long as research questions could very easily be inferred from them (e.g., from the problems people identify, or the posts people want written). Various EA-related topics List of EA-related thesis topics - Effective Thesis, no date You can also contact them for discussion, help, or coaching. A collection of researchy projects for Aspiring EAs - EdoArad, 2019 What questions could COVID-19 provide evidence on that would help guide future EA decisions? - Michael Aird (i.e., me) and others, 2020 Technical and Philosophical Questions That Might Affect Our Grantmaking - Open Philanthropy Project, 2017 What are the key ongoing debates in EA? - various, 2020 What posts do you want someone to write? - various, 2020 2018 list of half-baked volunteer research ideas and its comments - Jacy Reese and others, 2018 EA Summit Project Ideas (specifically the “Research Projects”) - various, no date What are some lists of open questions in effective altruism? - Aaron Gertler and others, 2019 This and the following list are roughly the same sort of “meta collection” as this post, and I think I took everything relevant from them already. The most important questions and problems - Pablo Stafforini Some history topics it might be very valuable to investigate - Michael Aird, 2020 On the longtermist case for working on farmed animals [Uncertainties & research ideas] - Michael Aird, 2021 What are the highest impact questions in the behavioral sciences? - Abby Hoskin, 2021 Mostly focused on longtermism, existential risks, or GCRs The Precipice, Appendix F: Policy and research recommendations - Toby Ord, 2020 Research questions that could have a big social impact, organised by discipline - Arden Koehler & Howie Lempel (80,000 Hours), 2020 Crucial questions for longtermists - Michael Aird for Convergence Analysis, 2020 Legal Priorities Research: A Research Agenda - Legal Priorities Project, 2021 Project Ideas in Biosecurity for EAs - David Manheim ("In conjunction with a group of other EA biosecurity folk"), 2021 Politics, Policy, and Security from a Broad Longtermist Perspective: A Preliminary Research Agenda - Michael Aird for Rethink Priorities, 2021 Humanities Research Ideas for Longtermists - Lizka for Rethink Priorities, 2021 80 Questions for UK Biological Security - Luke Kemp et al., 2021 Open Research Questions - Center on Long-Term Risk, no date ALLFED’s research priorities and Effective Theses topic ideas - 2019 Open Research Questions - Center for Reducing Suffering, no date Some history topics it might be very valuable to investigate - Michael Aird, 2020 Questions related to moral circles that are listed at the end of this post and in this comment - Michael Aird, 2020 Cause prioritisation / macrostrategy topics Denis Drescher collected and may investigate - 2020 Michael Aird_Research statement [FHI RSP] - Michael Aird, 2020 Mostly focused on AI ...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Concern, and hope, published by willbradshaw on the effective altruism forum. Write a Review I am worried. The last month or so has been very emotional for a lot of people in the community, culminating in the Slate Star Codex controversy of the past two weeks. On one side, we've had multiple posts talking about the risks of an incipient new Cultural Revolution; on the other, we've had someone accuse a widely-admired writer associated with the movement of abetting some pretty abhorrent worldviews. At least one prominent member of an EA org I know, someone I deeply respect, deleted their Forum account this week. I expect there are more I don't know about. Both groups feel like they and their sacred values are under attack. Both groups are increasingly commenting anonymously or from throwaway accounts, and seeing their comments mass-downvoted and attacked. It's hard not to believe we're at risk of moving in a much more unpleasant direction. I'm not going to pretend I don't have my own sympathies here. I've definitely been feeling a lot more tribal than usual lately, and it's impaired my judgement at a couple of points. But I think it's important to remember that we are all EAs here. We're here because we endorse, in one form or another, radical goodwill towards the rest of the world. I have never been among a group of people at once more dedicated to the wellbeing of others and the pursuit of the true. I admire you all so much. Many people here feel their membership in EA is a natural outgrowth of their other beliefs. Those other beliefs can differ quite a lot from person to person. But I implore all of you to see the common good in each other. There are many people in EA who hold beliefs and political opinions significantly different from mine. But with very few exceptions they have proven among the most open, honest and charitable proponents of those views I've ever encountered. We can have the conversations we need to have to get through this. The Forum is probably not the place to have those conversations. Too many people are too worried about their words being used against them to speak too openly under their own names – an indictment of our broader culture if ever there was one. But you can reach out to each other! Schedule calls! Now is a bad time to not be able to have in-person conferences, but it's not impossible to make up the difference if we try. (And on the Forum, please try to be charitable, even if your conversation partner is falling short of the standards you would set yourself. Strive to raise the tone of the conversation, not just to match it. I have sometimes failed in this recently.) I'll start. If I say something on the Forum you disagree with, and you don't think it's productive to discuss it in comments, please feel free to reach out to me by private message, or schedule a call with me here. Our epistemic norms are precious. So are our norms of compassion, justice, and universal goodwill. We need both to achieve the lofty goals we've set ourselves, and we need each other. thanks for listening. to help us out with the nonlinear library or to learn more, please visit nonlinear.org.
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Make a $10 donation into $35, published by WilliamKiely on the effective altruism forum. Write a Review Update March 2021: This donation match appears to be available indefinitely. Facebook's Giving Tuesday donation match ran out quickly this morning, but here's one that's still available: Every.org will donate $25 to any 501(c)(3) nonprofit up to $250,000 in total for each new referred user who donates $10 or more. This works out to a 250% counterfactual match on $10 in donations--higher than Facebook's, just with a lower limit. Steps: Join with:/@william.kiely/ Donate $10 to a nonprofit of your choice. Receive $25 in credit immediately. Donate the $25 you received to a nonprofit of your choice. I'd recommend just donating via card to save on time, rather than connect your bank account which would save on fees. The whole process can be completed in less than ~5 minutes and appears to be available to everyone regardless of what country you're in, so I'd suggest taking 5 minutes to make a $10 donation now. Happy Giving Tuesday! Update Two Weeks In: As of December 16th, $3,800 in matching referral funds has been given to 152 people who joined using my referral link. These 152 people have made 327 donations ("Joins") on the platform so far totaling $6,075 given to nonprofits (including the matching referral funds). The breakdown of which nonprofits these donations were made to is shown below. Thank you to everyone who shared this opportunity to get it in front of more people! The $250,000 in matching referral funds offered by Every.org are nowhere close to being exhausted and will therefore very likely continue to exist until at least December 25th. So please feel free to continue to share this post with your friends and ask them to consider donating to an effective charity! thanks for listening. to help us out with the nonlinear library or to learn more, please visit nonlinear.org.
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Early Alpha Version of the Probably Good Website, published by omernevo, sella on the effective altruism forum. TL;DR We have launched a preliminary (alpha) website for Probably Good. The long-term goal of this effort is to provide EA-aligned career advice in a way that’s engaging, relevant and useful to people with a diverse range of views, backgrounds and circumstances. For more details see our original announcement. As can be clearly seen in the site - this is an early version, which we are sharing here mainly to receive feedback, which you can give here in the comments or through the website's feedback page. Any feedback - including on content, style, prioritization or typos - would be greatly appreciated. Details Three months ago, we announced Probably Good - a new career guidance organization aimed at filling existing gaps in career advice in the EA community, and providing tools and advice relevant to a wide range of empirical, epistemic and moral views. It was heartening to see the support, offers to help, requests for advice, and significant amount of feedback we received - much of which we have already incorporated into our plans and content. Today we’re excited to announce we have launched a first version of our website on ProbablyGood.org. This first version is what could be called a minimal viable product (and, really, this version is not even viable yet) - it’s the most minimal version we could produce that we believe helps us test whether this direction can provide value. As should be pretty clear from the site itself - it is not yet comprehensive or even fully fleshed out. We are sharing it here mainly for feedback. We hope (and believe) this preliminary version can help clarify what we hope to offer, allow members of the community to provide us with more specific and meaningful feedback, and allow us to start testing out different strategies and directions. However, the site already showcases some of the content we’ve been working on for the last few months. This includes the beginning of our general career guide, a profile on Nonprofit Entrepreneurship, and a profile on Development Economics. We’re particularly interested in feedback about the content included and whether it’s useful, what additional content you’d most be interested in, and any other considerations you think are important for the goal of significantly and positively influencing people’s career trajectories. That being said, we’d appreciate feedback you have on any topic. Note that you can leave feedback here as a comment, or send it directly to us through the website. We’re really excited to share this with you and truly appreciate your support and help in making this project a success! Omer and Sella. thanks for listening. to help us out with the nonlinear library or to learn more, please visit nonlinear.org.
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Avoiding the Repugnant Conclusion is not necessary for population ethics: new many-author collaboration, published by deanspears on the effective altruism forum. This is a linkpost for 29 economists and philosophers, including leading researchers published today in Utilitas: “avoiding the Repugnant Conclusion is not a necessary condition for a minimally adequate... approach to population ethics.” The link at the top of this post is to my own summary of the article and how we reached it, posted at Medium. Population ethics asks how to evaluate policies and social trends that change the size of the global population. For decades, research has focused on whether to accept “the Repugnant Conclusion.” The Repugnant Conclusion is a hypothetical claim about how to compare populations of well-off people against imaginable, enormous populations of worse-off people. The Stanford Encyclopedia of Philosophy explains the Repugnant Conclusion and calls it “one of the cardinal challenges of modern ethics”. In a new publication in the journal Utilitas (link to open access paper), 29 philosophers, economists, and demographers agree: “avoiding the Repugnant Conclusion should no longer be the central goal driving population ethics research.” The collaborators come from different institutes, continents, and academic disciplines. They also come from different perspectives. Their statement emphasizes that they came to their agreement for different reasons. Some think the Repugnant Conclusion is true. Others are unsure, but think it would be no big deal if true, or just one among many factors to consider. Others coauthors argue that the Repugnant Conclusion makes no sense to begin with. Population ethics “is not simply an academic exercise, and we should not let it be governed by undue attention to one consideration.” The collaborators conclude with a hope that population ethics will one day make progress beyond the debates and questions of today: “Perhaps someday the correct approach to axiology, social welfare, or population ethics will be agreed upon among experts. If so, we do not know whether the approach used will entail the Repugnant Conclusion. We should keep our minds open.” Contact: Dean Spears. dspears@utexas.edu Citation: Zuber, et al. (2021) Utilitas (link) thanks for listening. to help us out with the nonlinear library or to learn more, please visit nonlinear.org.
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: What EA projects could grow to become megaprojects, eventually spending $100m per year?, published by by Nathan Youngon the effective altruism forum. Ben Todd (CEO of 80,000 Hours) says "Effective altruism needs more 'megaprojects'. Most projects in the community are designed to use up to ~$10m per year effectively, but the increasing funding overhang means we need more projects that could deploy ~$100m per year." What are some $100m projects that you think might be worth consideration? By megaproject, I'm referring to any project that could eventually be scaled up to $100 million, not ones that are planned from the start to cost $100 million. In many cases, this could include very small efforts that would have to achieve multiple levels of success to eventually get $100Million+ per year. thanks for listening. to help us out with the nonlinear library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: The Explanatory Obstacle of EA, published by GidonKadosh on the Effective Altruism Forum. This post discusses multiple issues relating to the way the EA movement is perceived (ranging from common misconceptions to unjustified strong opinions against EA) and suggests alternatives to the ways we describe EA. Since I don’t have the resources to quantify this problem, I rely on my personal experience as a community builder and that of many other community builders and explain the rationale behind my suggestions. Around 2013, a couple of mass media articles about EA (1,2,3) - specifically about Earning To Give - were published. These articles clearly missed most of the nuances behind the idea of Earning To Give, and heavily misrepresented the idea. In light of such events, the EA movement at that time faced a critical question: Should we stay away from mass media? The answer the EA community arrived at was yes, and CEA formalized this as a part of its strategy: Historically, spreading EA via the mass media was a key focus of CEA. Over time it became clear that the mass media is not particularly well suited to spreading ideas with high fidelity. Therefore, we have pivoted away from this focus and towards higher-fidelity methods like books and podcasts. I think this was a good decision, but I think the movement should have asked itself another critical question to prevent future broad misunderstandings of EA: Are we explaining what EA is well enough? From my experience, the answer is no, even today. EA Israel used and experimented with the common pitches and explanations from several EA pitch guides (1,2,3), but we’ve kept noticing how almost every new member needs additional explanations on the basics of EA. We’ve kept encountering newcomers who are highly excited about EA while thinking it’s something else (e.g. it’s about making people more altruistic, or specifically making charities more efficient), and then lose excitement through the onboarding process. We also find ourselves struggling with common misconceptions, as does the rest of the community (1,2). If individuals who look into EA perceive it as something that is not sufficiently close to its meaning, we both attract individuals who are not a good fit for EA, and miss individuals who could have been a good fit. Clarifying our explanation of EA is also a great way to recognize disagreements among the community about what EA is. For instance, does EA call individuals to spend more resources on doing good, or to do more good with the same amount of resources? What is a good explanation? For the purposes of this post, let’s make a distinction between three approaches to describing a concept, each with a different focus: A definition: Should be as accurate as possible. An explanation: Should be as clear as possible. A pitch: Should be as convincing as possible. While not true in all contexts, a pitch in our case should include a clear explanation of EA: Regardless of how convincing our pitch is, we still want newcomers to have a good understanding of what EA is, so they can later make better decisions. Therefore, crafting better explanations of EA is beneficial both for pitching and for explanations. The EA community discussed the definition of EA many times before (1,2,3), and has many convincing and clever pitches (linked above). But I haven’t seen as many discussions on explanations, and accordingly, I think what’s most missing for newcomers is clarity. Sidenote: It can be challenging to discuss what “convincing” is. I find it useful using the theory of motivational salience, and I’ll try to explain how certain phrases create reasons for being involved with EA (incentive salience) versus creating reasons against being involved in EA (aversive salience). For the purpose of this post, this mostly means that we want ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: On fringe ideas, published by Kelsey Piper on the Effective Altruism Forum. Write a Review This is a linkpost for The Forum team published this with Kelsey's permission. We've slightly edited the original content, which you can find here. Question to the blog What do you think about the more fringe parts of EA? I get really angry seeing people call themselves EAs but then spending all of their time writing speculative essays on, say (to quote those I came across most recently), how actually wildlife conservation is bad because animals in the wild suffer. Like, it's fun to think about that, but my goals as an EA are very different than those of someone who thinks stuff like that is even comparable with global development or long-term sustainability. But I do wonder what your opinion is, since you do have a record of being sensible in evaluating ideas regardless of how fringe they are, which I really appreciate. Kelsey’s response One big formative influence on how I think about this is imagining that effective altruism had existed at various other moments in history. Would we have been doing any good, or would we have been too stuck in the assumptions of the time period? Would an effective altruist movement in the 1840s U.S. have been abolitionist? If we think we would have failed to stand up against slavery, what do we need to change, now, as a movement, to make sure we’re not getting similarly big things wrong? Would an effective altruist movement in the 1920s U.S. have been eugenicist? If we think we would have embraced a pseudoscientific and deeply harmful movement like the sterilization campaigns of the Progressive era, what habits of mind and thought would have prevented us from doing that, and are we actively employing them? I think that for effective altruism to be robustly good — to be a movement that would have done good even when embedded in societies that were doing great evil, or societies that were oriented around entirely the wrong questions, or a society that had a “do-gooder” consensus that was actually terrible — there are a bunch of things that have to be in place. Firstly, we have to actually be doing things that benefit the people who need it most. Last year, donations moved through GiveWell to top charities (not counting donations from Good Ventures) increased to $65 million. If that number wasn’t impressive, and wasn’t increasing, I would be worried that we were failing as a community. We need the reality check of being accountable for actual results. We need to actually do things. Next, we need to be continually monitoring for signs that the things we’re doing are actually doing harm, under lots of possible worldviews. That includes worldviews that aren’t intuitive, or that aren’t the way most people think about charity. If recipients aren’t happy, that’s an enormous potential warning sign. If our efforts increase suffering, even if it’s in some weird way that’s hard to take seriously, that’s a warning sign. If there are forces systematically ensuring we don’t hear from recipients, that’s a warning sign. Basically, we need to cast a really, really wide net for possible ways we’re screwing up, so that the right answer is at least available to us. Next, imagine someone walked into that 1840s EA group and said, ‘I think black people are exactly as valuable as white people and it should be illegal to discriminate against them at all,” or someone walked into the 1920s EA group and said, “I think gay rights are really important.” I want us to be a community that wouldn’t have kicked them out. I think the principle I want us to abide by is something like ‘if something is an argument for caring more about entities who are widely regarded as not worthy of such care, then even if the argument sounds pretty absurd, I am supportive of some people doing rese...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: How I got an entry-level role in Congress, published new_staffer on the Effective Altruism Forum. A few months ago I was hired for an entry-level role in a Congressional office. In this post I will share my job search and application process. I hope this will be helpful to people who are considering Congressional work as a career option. Because I am early in my career, I imagine this will be most helpful/applicable for people who are in undergrad or earlier. Note: I’m intentionally keeping this post anonymous. If you have any questions, please comment them here and I will do my best to answer them. If you’d like to connect further, feel free to send me a private message through the EA Forum. My Specific Experience Context about myself as an applicant: I earned an undergraduate social science major at a relatively prestigious university and was an unremarkable student academically. While there, I was involved with party politics + local elections, held leadership positions in student activist campaigns, spent two summers working for local politicians, and worked in ‘government affairs’ for public interest groups for two semesters. During one semester I lived in Washington DC and interned in Congress. My application process: I started my job search in earnest the summer after graduating college. I recommend making time to network and begin your job hunt in your last semester, but I was too busy with coursework to do so. I spent about 20 hours a week for 3 months applying for Congressional entry level roles almost exclusively. Though it took me 3 months, it could have easily been a few months longer than that (I got lucky to land my position early but was prepared to job hunt longer). I spent the majority of my time ‘networking.’ For me, this meant sending emails to people, requesting that we meet briefly (this was during pandemic, so it was all virtual). I contacted (nearly) everyone I knew from the time I spent in DC, asked to catch up via phone or video call, let them know I was job searching, and asked them to connect me with people who work in Congress. Especially important were the people who I’d worked with as an intern on the Hill, because they could flag my resume with other offices and could vouch for my work experience. I also emailed strangers who I knew worked on the Hill, whose names I found by searching on LinkedIn. I tried to find people who I had one or more things in common with (graduates of the same university, from my home state, working on a policy issue that I have a demonstrated interest in, worked at the same non-profit I used to work for, etc). After I found someone who worked on the Hill, I would contact them by using the standard email format for Congressional staffers, which is Jane_Doe@lastnameofSenator.senate.gov for the Senate or Jane.Doe@mail.house.gov for the House of Representatives. Most people did not reply to these emails, but some people did! In these conversations, I asked them about their job experience in general and their tips on job searching. Example ‘cold’ networking email: Hello [name], Hope you're having a restful recess. I graduated from [your alma mater] in [recent month] and just moved to D.C. I’m heading into my last month working with [government advocacy group] and am interested in exploring Congressional work as my next step. I really admire that you work for [name of Congressperson], who [list 2-3 things you admire about their boss]. I'd love to hear about your journey to becoming a [position/title name], how you're liking your work, and whether you have any advice on navigating the Hill [during this unique moment / pandemic / etc]. Do you have availability for a short call in the next two weeks? Thank you and I hope we can talk soon, [Your name] Other than networking and asking people to send me any internal post...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Will companies meet their animal welfare commitments? , published by saulius on the Effective Altruism Forum. Write a Review Summary Multiple animal organisations are now focusing on securing corporate commitments to improve animal welfare. And they have been very successful: Chicken Watch lists 1672 such commitments, 1007 of which are set to be fulfilled between 2020 and 2026. However, there is some reason to worry that some of these commitments may be broken: Some industry sources doubt whether U.S. cage-free commitments will be fully met. Insufficient consumer demand and lack of funds led to producers slowing down or even shutting down their cage-free conversion plans. What is more, only 27% of U.S. companies included in CIWF’s EggTrack report disclosed their progress towards cage-free commitments. So far, most animal welfare commitments were met. However: Sainsbury’s broke their broiler commitment. Marriott, Burger King, Smithfield Foods and Woolworths pushed back the date of their commitments. Bennet, Dussman, Au Bon Pain, Hilton Hotels & Resorts, and The Walt Disney Company did not report progress to CIWF for cage-free commitments that have already passed their due date. In the past, some companies gave themselves some wiggle room in the phrasing of their commitments, which they could later use to get out of their commitments with less damage to their reputation. Based on this, I suggest that it would be valuable to put more effort in ensuring that companies keep their promises, and I list some ways in which it could be done. Broken and postponed commitments Sainsbury’s In 2010, following a corporate campaign, UK supermarket chain Sainsbury’s committed to introduce higher welfare standards for all of their own brand fresh chicken, within five years. They publicized their high welfare credentials widely in the UK press and received an award from Compassion in World Farming (CIWF). Eight years later, less than 20% of the chicken sold by Sainsbury’s is higher welfare, and now they have decided to abandon their welfare promise (source). There was a shaming campaign against Sainsbury’s, and they did receive some negative publicity. However, it seems that the shaming campaign died down without any new promise received from Sainsbury’s. I’m afraid that this sets a bad precedent. If the animal welfare movement does not react to broken promises with more resistance, all the corporate commitments that we achieved may not mean much. I think that we should campaign against Sainsbury’s until they agree to a new broiler commitment. It would be best to all do this as a united front, to make it clear that a demise of any one organisation would not mean that commitments achieved by that organisation are no longer important. Then all animal organisations could use this situation as an example of what happens when corporations break their promises. I also believe that now is the best time to act on this. If many commitments fail at the same time in 2020 or 2025 (which are the respective deadlines for many of the commitments), each individual brand will probably receive less bad publicity due to saturation of similar stories. It may be seen as a failure of the corporate world as a whole, or even as a failure of the animal welfare movement. Smithfield Foods In 2007, Smithfield Foods (the world’s largest pork producer) announced that “it is beginning the process of phasing out individual gestation stalls at all of its company-owned sow farms and replacing them with pens—or group housing—over the next 10 years.” In 2009, Smithfield delayed their plans blaming the recession. According to HSUS article, “Such backpedalling led to a serious HSUS campaign, including an undercover investigation at one of its factory farms, complaints about false advertising, significant negative media cove...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Why AI alignment could be hard with modern deep learning, published by Ajeya on the Effective Altruism Forum. This is a linkpost for/ (This is a guest post on Holden Karnofsky's Cold Takes blog, written by Ajeya Cotra.) Holden previously mentioned the idea that advanced AI systems (e.g. PASTA) may develop dangerous goals that cause them to deceive or disempower humans. This might sound like a pretty out-there concern. Why would we program AI that wants to harm us? But I think it could actually be a difficult problem to avoid, especially if advanced AI is developed using deep learning (often used to develop state-of-the-art AI today). In deep learning, we don’t program a computer by hand to do a task. Loosely speaking, we instead search for a computer program (called a model) that does the task well. We usually know very little about the inner workings of the model we end up with, just that it seems to be doing a good job. It’s less like building a machine and more like hiring and training an employee. And just like human employees can have many different motivations for doing their job (from believing in the company’s mission to enjoying the day-to-day work to just wanting money), deep learning models could also have many different “motivations” that all lead to getting good performance on a task. And since they’re not human, their motivations could be very strange and hard to anticipate -- as if they were alien employees. We’re already starting to see preliminary evidence that models sometimes pursue goals their designers didn’t intend (here and here). Right now, this isn’t dangerous. But if it continues to happen with very powerful models, we may end up in a situation where most of the important decisions -- including what sort of galaxy-scale civilization to aim for -- are made by models without much regard for what humans value. The deep learning alignment problem is the problem of ensuring that advanced deep learning models don’t pursue dangerous goals. In the rest of this post, I will: Build on the “hiring” analogy to illustrate how alignment could be difficult if deep learning models are more capable than humans (more). Explain what the deep learning alignment problem is with a bit more technical detail (more). Discuss how difficult the alignment problem may be, and how much risk there is from failing to solve it (more). Analogy: the young CEO This section describes an analogy to try to intuitively illustrate why avoiding misalignment in a very powerful model feels hard. It’s not a perfect analogy; it’s just trying to convey some intuitions. Imagine you are an eight-year-old whose parents left you a $1 trillion company and no trusted adult to serve as your guide to the world. You must hire a smart adult to run your company as CEO, handle your life the way that a parent would (e.g. decide your school, where you’ll live, when you need to go to the dentist), and administer your vast wealth (e.g. decide where you’ll invest your money). You have to hire these grownups based on a work trial or interview you come up with -- you don't get to see any resumes, don't get to do reference checks, etc. Because you're so rich, tons of people apply for all sorts of reasons. Your candidate pool includes: Saints -- people who genuinely just want to help you manage your estate well and look out for your long-term interests. Sycophants -- people who just want to do whatever it takes to make you short-term happy or satisfy the letter of your instructions regardless of long-term consequences. Schemers -- people with their own agendas who want to get access to your company and all its wealth and power so they can use it however they want. Because you're eight, you'll probably be terrible at designing the right kind of work tests, so you could easily end up with a Sycophant or Scheme...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: The academic contribution to AI safety seems large, published by technicalities on the Effective Altruism Forum. Summary: I model the contribution to AI safety by academics working in adjacent areas. I argue that this contribution is at least on the same order as the EA bet, and seek a lower bound. Guesstimates here and here. I focus on present levels of academic work, but the trend is even more important. Confidence: High in a notable contribution, low in the particular estimates. Lots of Fermi estimates. A big reason for the EA focus on AI safety is its neglectedness: ...less than $50 million per year is devoted to the field of AI safety or work specifically targeting global catastrophic biorisks. 80,000 Hours (2019) ...we estimate fewer than 100 people in the world are working on how to make AI safe. 80,000 Hours (2017) Grand total: $9.09m. [Footnote: this] doesn’t include anyone generally working on verification/control, auditing, transparency, etc. for other reasons. Seb Farquhar (2018) ...what we are doing is less than a pittance. You go to some random city... Along the highway you see all these huge buildings for companies... Maybe they are designing a new publicity campaign for a razor blade. You drive past hundreds of these... Any one of those has more resources than the total that humanity is spending on [AI safety]. Nick Bostrom (2016) Numbers like these helped convince me that AI safety is the best thing to work on. I now think that these are underestimates, because of non-EA lines of research which weren't counted. Use "EA safety" for the whole umbrella of work done at organisations like FHI, MIRI, DeepMind and OpenAI’s safety teams, and by independent researchers. A lot of this - maybe a third - is conducted at universities; to avoid double counting I count it as EA and not academia. The argument: EA safety is small, even relative to a single academic subfield. There is overlap between capabilities and short-term safety work. There is overlap between short-term safety work and long-term safety work. So AI safety is less neglected than the opening quotes imply. Also, on present trends, there’s a good chance that academia will do more safety over time, eventually dwarfing the contribution of EA. What’s ‘safety’? EA safety is best read as about “AGI alignment”: work on assuring that the actions of an extremely advanced system are sufficiently close to human-friendly goals. EA focusses on AGI because weaker AI systems aren’t thought to be directly tied to existential risk. However, Critch and Krueger note that “prepotent” - unstoppably advanced, but not necessarily human-level - AI could still pose x-risks. The potential for this latter type is key to the argument that short-term work is relevant to us, since the scaling curves for some systems seem to be holding up, and so might reach prepotence. “ML safety” could mean just making existing systems safe, or using existing systems as a proxy for aligning an AGI. The latter is sometimes called “mid-term safety”, and this is the key class of work for my purposes. In the following “AI safety” means anything which helps us solve the AGI control problem. De facto AI safety work The line between safety work and capabilities work is sometimes blurred. A classic example is ‘robustness’: it is both a safety problem and a capabilities problem if your system can be reliably broken by noise. Transparency (increasing direct human access to the goals and properties of learned systems) is the most obvious case of work relevant to capabilities, short-term safety, and AGI alignment. As well as being a huge academic fad, it's a core mechanism in 6 out of the 11 live AGI alignment proposals recently summarised by Hubinger. More controversial is whether there’s significant overlap between short-term safety and AGI alignment. Al...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Some thoughts on EA outreach to high schoolers , published by Buck on the Effective Altruism Forum. [A bunch of these points came from Claire Zabel. Thanks to various people who provided feedback.] TL;DR: I think that lots of EAs have updated against outreach to high school students based on evidence that isn’t actually entirely relevant. I also think that there are some reasons to think that outreach to high school students could be competitive with outreach to undergraduates. There are a variety of downsides to outreach targeting younger people, none of which seem decisive to me. EAs seem to be too pessimistic about high school outreach There have been several posts about unsuccessful (according to the authors) attempts to get high schoolers into EA. E.g. see here and here. When I’ve talked to people about different recruiting possibilities (in which these posts were often mentioned if I brought up the possibility of trying to recruit high schoolers), I’ve gotten the sense that many EAs are pessimistic about trying to engage high school students. But I think these past interventions were ineffective for reasons unrelated to their target audience, and that other interventions aimed at high school students seem comparably promising to working with university students. These posts document attempts to engage high schoolers that were relatively short and untargeted (they didn’t strongly select their audience, other than by age, and didn’t get to select from a very big group). If you imagine the analogous kind of intervention for other age groups where EA recruitment has had notable successes, we predict the results would be (and has been) similarly disappointing. E.g. if you took a random group of a few hundred university students or recent graduates, selected within that group for EA-ness, then showed them a few videos or had them listen to a few hours of talks about EA, we predict the results would usually be similarly lackluster (and, it’s my impression that they have been, when that kind of thing has been tried). In contrast, many of the biggest EA groups are at top universities, where they can select from thousands of students, and where the students have been somewhat pre-selected for traits that seem correlated with EA-ness, like intellectual curiosity and openness. The only somewhat-similarly-targeted analogues I know of for high schoolers are SPARC and ESPR (which recruit from people with evidence of talent in STEM fields, e.g. by looking for high school students that have done well in STEM Olympiad competitions). I know a decent number of SPARC and ESPR alum have gone on to do direct work in top cause areas, some of which seems really promising. It doesn’t seem easy to compare the hit rate of SPARC to e.g. the Yale EA group, and establishing causality is always hard, but the story of SPARC seems totally different from the lack of traction SHIC seemed to get. Basically, I think we should treat engaging with high school EAs more similarly to how we treat engaging with older EAs: we should look for places with particularly high density of people who have a chance of contributing to high priority causes and engage them over the course of weeks or months rather than using relatively short means of engagement, and also do structured types of engagement where they can build up connections with other people interested in this. If we do that, I don’t think there’s a good reason to be more pessimistic about interventions to engage high schoolers than university students. Benefits to engaging with younger people I see a few big upsides to working with younger people: It seems harder to recruit people the older they are, at least after people get into their thirties, and so maybe it gets even easier if you go younger than the point at which most recruiting efforts start....
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Introducing the Simon Institute for Longterm Governance (SI), published by maxime, konrad on the Effective Altruism Forum. (Konrad Seifert & Maxime Stauffer) have the pleasure to announce the Simon[1] Institute for Longterm Governance (SI): simoninstitute.ch The website caters to our initial target audience of international policymakers. This post introduces our theory of change and provides additional information relevant to the EA community and potential funders. The following is structured into: An overview of SI Key decisions we made in founding SI and underlying assumptions An overview of the value SI provides to the EA community Call for support How to get in touch Ask us anything We thank Nora Ammann, Haydn Belfield, Ollie Base, Michael Aird, Devon Fritz, Rumtin Sepasspour, Christine Peterson, Julia Wise and Helen Toner for their invaluable feedback on this announcement. All errors and shortcomings are ours. 1. Overview of SI Our theory of change SI aims to contribute to the long-term flourishing of civilization. For 1., humanity needs to anticipate and mitigate global catastrophic risks (GCRs) and build resilient systems so that civilization can survive and flourish. Policymaking in national governments and international organizations is the most influential form of explicit value-driven coordination and can, therefore, be used to achieve 2. To build long-term governance there are at least four improvements we can make to 3.: a. The dominant societal narratives require the inclusion of future generations and an understanding of human progress on long timeframes b. Institutions must be reformed to take the interests of future generations into account (e.g. see Tyler John’s EAGxVirtual talk (2020) and Gonzalez-Ricoy & Gosseries (2016)). c. Policy agendas must account for tail risks and their interaction effects (e.g. Avin et al. (2018)). For example, the post-2030 UN agenda should include GCRs beyond climate change. d. Decision-making needs to (i) be more anchored in ethics, (ii) use more scientific evidence and sound reasoning, (iii) navigate complex systems and understand tail risks, (iv) make better decisions in the face of uncertainty and urgency, and (v) deal more productively with diverging preferences and groupthink. SI focuses on 4.d. to build the capacity for achieving 4.a.-c. and contribute to 2. and 1. Our first working paper will outline this theory of change in more detail. A first draft will be published on our website in April 2021. Our approach SI aims to embed concern for future generations within the incentive structures and decision-making processes of the international public policy ecosystem, leveraging our personal connections to the United Nations[2] and European Union systems. We are building organizational capacity via three focus areas: Policy support: We develop training programs aiming to improve the collective capacity of policy networks[3] to make sense of tail risks, the abundance of information, competing objectives, complexity and uncertainty in a timely manner. Field-building: We strengthen research coordination and policy decisions by building a Geneva-based community of longtermist international civil servants and researchers to share knowledge and exchange strategic insights. Research: We seek to understand and improve long-term policymaking by synthesising research, formalizing system dynamics and empirically testing tools and hypotheses in policy contexts. Current projects include a table-top exercise on pandemic preparedness for the ecosystem of the UN Biological Weapons Convention; building a Geneva-based network of long-term focused international civil servants & GCR governance researchers; and writing working papers operationalizing what it might take for public policymaking to benefit the long-term future. See here fo...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Thoughts on being overqualified for EA positions, published by Ben_West on the Effective Altruism Forum. I sometimes hear of people not wanting to work for EA organizations out of a fear that they are "overqualified". I believe the reasoning is something like: In the for-profit sector, projects with some characteristics (e.g. building a website with less than 100k pageviews/day) are usually done by more junior people. This is presumably because it's not cost-effective to hire more senior staff (i.e. the value senior staff add to the project is less than the extra cost of hiring them). Projects in EA organizations have these characteristics. Therefore, there is not enough benefit for it to be worth having senior people do these tasks in EA organizations over having junior people do them. I think (3) is not justified for a few reasons. The most important is that it equivocates between "an analogous profit maximizing entity might not hire a senior person" and "senior people don't provide much benefit". It's basically always possible to do things faster/cheaper/with fewer errors/with a better user experience/etc. I don't think it's possible for any mortal to be "overqualified" in the sense of "could not perform the task better than someone who was less skilled," for all but the most trivial of tasks. Often, the reason it's not profitable to hire more senior people is more about leverage than about their ability to perform better. E.g. maybe a senior software engineer makes any website they work on 10% better than a junior engineer would – they can make a small website 10% better just as easily as they can make a large website 10% better. But they will still only get hired to work on the large website because a 10% increase in a large website is a greater absolute return than a 10% increase in a small website. Startups often have their early success boosted by "overqualified" founders doing all the work – customers are impressed that they get to speak to the brilliant founders instead of normal salespeople so they are more likely to purchase the product, bugs get fixed more quickly because there are extremely talented engineers working on fixing them, etc. It's common for startups to hit problems once they grow and have "correctly qualified" people in their positions, because they no longer benefit from those advantages. Smaller EA organizations are somewhat like these startups whose success can be boosted by "overqualified" employees. A secondary reason is that the intuition that EA organizations are "small" seems to often be based on comparing inputs rather than outputs. It's true that this forum is read by many fewer people than, say, view the home and garden section on Amazon.com, but I suspect that global welfare is more easily increased by improving this site than Amazon (both because there is lower hanging fruit, and because the value generated per viewer is higher). Finally, something I underestimated before working at an EA organization is the extent to which the novelty of EA work meant that similar tasks are more challenging. I've created a software product used by most hospitals in the US, started a successful company, and am now managing one of the smallest teams I've ever managed, but am not at all finding it easy. Things like impact analysis have received ~0% as much focus from experts as for-profit analogs like fiscal accounting have, making it much more challenging to answer basic questions like "was our project successful?" A better argument for believing that one is overqualified Often when employers speak of someone as being "overqualified", what they mean is "this person might get bored with the work or dissatisfied with the low pay and quit to work somewhere else." Expecting to be bored with a job is a very good reason to not take it, but I would enc...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: English as a dominant language in the movement: challenges and solutions, published by Dobroslawa_Gogloza on the Effective Altruism Forum. Many of the problems we are facing are global, so the social movements that we have to create in response to them must also be global. To facilitate cooperation within any movement, we also need a common language. It is very good that we have a language that makes it easy for activists from different parts of the world to share information, learn from each other and plan strategies together. However, we must also be aware that the use of a single language of communication has certain consequences for the dynamics and power structures of our social movement. There are many studies that analyze differences in the perception of native-speakers of a language compared to a second language or foreign language speakers. The results are very worrying. One observation is that people for whom a common language is their mother tongue, especially those whose pronunciation has the most prestigious accent, “are automatically in a position of strength compared to those who need to learn it as a second or foreign language”. A standard accent — like the ones normally shown in the media — is automatically associated with higher education and higher economic status. It is also worth noting that it’s practically impossible to lose an accent completely when speaking a foreign language. Some other observations from scientists studying the evaluation of people speaking with a non-standard accent: Non-standard speakers are usually perceived as less competent, less intelligent and less trustworthy. If you are not very proficient in English as a foreign language, you will feel anxious and inhibited when you need to communicate in English. Non-native speakers avoid expressing their opinions at meetings for fear of being perceived as incompetent. Some experiments suggest that a non-standard accent contributes to discrimination or being perceived negatively, even more than having a different skin color. The same arguments put forward by a person with a standard accent are assessed as being of better quality. In one study, most of the non-standard speakers were convinced that they would be more respected if they spoke a standard accent and one-third of them reported experiencing discrimination based on their accent. The accents are not equal. While most people who speak with a foreign accent are assessed negatively, some experiments have shown that people with a Western European accent are perceived rather positively. Especially German-accented speakers are sometimes seen as more organized and intelligent. People who speak English as a foreign language feel more comfortable speaking English with other people who speak it as a foreign language since they do not feel constantly assessed. Communication with other non-standard speakers can be more important in creating a platform for understanding each other than cultural differences between the interlocutors. When native speakers are difficult to understand, it does not affect their status. When a non-native speaker is hard to understand, it affects the perception of them as less professional. To quote a meta-analysis of various studies on the perception of people who are not native speakers: Across rating dimensions, speakers who use a standard accent are rated more positively than those using a non-standard accent, almost a full standard deviation higher. This effect may have considerable consequences for those speakers being evaluated. For the standard speaker, it represents a huge advantage, and for the non-standard speaker, it represents nothing less than a considerable handicap. The reader should consider the fact that evaluations have been shown to be shaped by single words, such as the speaker saying “hel...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: EA Survey 2019 Series: How EAs Get Involved in EA, published by David_Moss on the Effective Altruism Forum. Summary Personal Contacts (14%), LessWrong (9.6%) and 80,000 Hours (9.6%) are still the main ways most people have heard of EA over time. In recent years (2018-2019), 80,000 Hours (17%) is the single largest source for people first hearing about EA, followed by Personal Contacts (15%). 80,000 Hours (47.8%), GiveWell (42.7%) and Personal Contact (34.8%) had the highest percentages of EAs saying they were important for getting them involved in EA. We find few differences in the proportion of highly engaged EAs first hearing of EA from different sources, except for significantly higher proportions of engaged EAs first hearing of EA from a personal contact or a local group. Additionally, for the first time, we provide data about which specific books, podcasts, TED Talks etc. people most commonly heard about EA from. Peter Singer was the most commonly mentioned factor, appearing in 17.6% of these comments. We find some differences in which things get men and women involved in EA: personal contacts and 80,000 Hours seem to recruit more women. We also find that significantly more non-white individuals first heard about EA from 80,000 Hours, with few differences across any of the other sources. Where do people first hear about EA? Where have most people first heard of EA overall? 2137 (85%) respondents answered the “Where did you first hear about Effective Altruism?” question.[1] ‘Personal Contact’ is quite far ahead of all other options (14%), followed by LessWrong and 80,000 Hours (each 9.6%). There are now substantially fewer responses in the broad ‘Other’ category (8.6%) than in 2018, but is still the fourth largest category. Due to changes to the categories, this year’s results are not directly comparable to the previous years. However, we can see that the results are quite similar. Personal Contact was the most selected option in both 2018 and 2019 (notwithstanding the ‘Other’ category in 2018), with 16% and 14% respectively. LessWrong (12% vs 9.6%) and 80,000 Hours (8% vs 9.6%) were the next most popular categories. Local EA Group (5% vs 5.2%) and Slate Star Codex (5% vs 6.8%) follow next, with Book (6%) and Podcast (5.6%), TED Talks (4.6%) and Article/Blog (4.5%) also receiving similar numbers of responses. New additions, Future Perfect and One For the World, received <1% of responses each. alt_text ‘Other’ Responses: open comment data We also analysed open comment data for the 8.6% of respondents who selected ‘Other’. Out of the 183 respondents who selected “Other”, 50.8% were categorised as fitting into existing categories. Many of these wrote something like “I’m not sure, either LessWrong or 80,000 Hours”, so they cannot be unambiguously coded as any single category. Of those responses that seemed to fit single existing categories, 31 mentioned a Blog or Article, 24 mentioned a Personal Contact, 14 mentioned an Educational Course, 8 mentioned a Local Group, 6 mentioned LessWrong, 6 a Podcast, 4 80,000 Hours, 2 a Book and 1 Slate Star Codex. Of those responses which did not fit a pre-existing category, the most mentioned was Peter Singer (38). 21 mentioned an other EA org (including FHI (4), CFAR (3), SPARC (2), MIRI (2) Effective Giving (1), SHIC (1), CEA (1), OpenAI (1), REG (1), MFA (1), GBS Schweiz (1), and Leverage Research (1)), 10 mentioned YouTube, 3 mentioned Radio, and 20 were uncategorised others including Felicifia (an old forum for discussing utilitarianism) (3), a rap (1) and a coffee shop (1). Changes across time As we noted last year, where people first hear about EA has changed significantly over time.[2] alt_text Link to full size image: Full table: Categories are displayed in reverse order (i.e. options at the top of the graph are at the bo...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: A new, cause-general career planning process , published by Benjamin_Todd on the AI Alignment Forum. We just released a new resource, which may become an important part of our site, and which might help reduce some cultural issues in the EA community. As a little background, 80,000 Hours has always aimed to provide two types of advice: Information about specific problems and career paths and their impact General strategies & decision-making tips for high-impact careers, such as steps for how to compare two jobs, or whether to focus on career capital or immediate impact. The key ideas page we released in April 2019 emphasised specific problems & paths over general advice, but it was always our intention to fill in our coverage of both (similarly to how the 2017 career guide covered both). I think we’ve taken a big step towards filling this gap with our new, in-depth ‘career planning process’. It’s a set of prompts that take you through how to make a career plan, checking you’ve asked yourself the most important questions, are aware of the best resources, and have taken the most useful steps to investigate. It starts with high-level questions and then works from there to concrete next actions. Specifically, it covers: Clarifying your ultimate goals and what a high-impact career looks like Prompts for choosing a global problem to focus on Exploring ideas for longer-term career paths you might pursue Clarifying our career strategy, based on your answers to the above Ideas for your next career move based on the above Your alternatives and back-up options How to investigate your key uncertainties Putting your plan into action To get started on the process, you can either dive into the article that discusses each step above, or start filling out the associated worksheet: An in-depth article with a section covering each step above A Google Doc worksheet you can copy and fill in Later, we hope to release a ‘just the key messages’ version that aims to quickly communicate the key concepts, without as much detail on why or how to apply them. We realise the current article is very long – it’s not aimed at new readers but rather at people who might want to spend days or more making a career plan. Longer-term, I could imagine it becoming a book with chapters for each stage above, which contain advice, real-life examples and exercises. (Added: we'll also consider making a 'tool' version like we had in the 2017 career guide.) I hope this process will be useful to anyone within (and outside) the community with the good fortune to be able to consider making a big career change, since the prompts don’t depend on which causes you support or career paths you’re able to work on. We’ve had good feedback from some local groups already, and EA Student Career Mentoring have adapted it for their advising process. I also hope it clarifies a lot of our positions. In Key Ideas, we throw out a lot of options and concepts, but there’s a long way to go from those ideas to an individual's career plan, which takes account of their values, skills, personal constraints, and so on. To oversimplify the problem, people often get the impression we think everyone should try to work on AI safety as quickly as possible. This is wrong first because we’d like to see people work on many problems besides AI safety. But just as importantly, we also think there are many other considerations to take into account in career planning: we want people to think about their greatest strengths, how to build valuable skills over time, how to ‘work forward’ from idiosyncratic opportunities, and to consider exploration, personal growth, and many other rules of thumb. All this could easily mean someone's best option isn't pursuing one of our priority paths or working on one of our highest-priority problems. Finally, I hope this c...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Ending The War on Drugs - A New Cause For Effective Altruists?, published by MichaelPlant on the Effective Altruism Forum This is a linkpost for Peter Singer and I argue for drug legalisation in an article that was published in the New Statesman earlier this week (link to my tweet). In short, we argue 'War on Drugs' has failed and it's time that governments, not gangsters, run the drug market. I posted what follows below in the EA facebook group and was encouraged to do so here too (as the discussion is often better). The aim of the article wasn't to make an argument in 'EA terms': we merely claimed that moving from drug prohibition to drug legalisation would be a good thing, not that putting money or time put towards this would be (for someone) the most good they could do. However, I would like to elaborate on the article and say why effective altruists might be interested in this cause area - not least because it's not really been discussed before, conversations about psychedelics and my 2017 EA forum posts on the topic aside, and it seems important to 'keep EA weird' and continue to keep the proverbial eyes peeled for ways to, well, do good better! The thrust of the article is that drug legalisation would do quite a bit of good. I suspect the largest part of this is that those in drug-producing and trafficking countries would no longer be affected by the corruption and violence that drug cartels, and the War of Drugs, bring. One well-known example is the Mexican Drug War where over 100,000 are estimated to have died since 2006. Such conflict is destabilising and hinders the economic development of many of the world's poorer citizens. Hence, it might look good solely as a poverty alleviation policy. It would also benefit those people who are currently criminalised for drug offenses - in the US, 1/5th of the prison population - as well as reduce harms to users, raise money states could spend elsewhere, and some other things besides. Determining the scale of the problem isn't straightforward and I haven't yet really tried, but my hot take is that, on a global scale, it's not trivial. Certainly, it's not so trivial it should be dismissed out of hand. As one indication, the UN estimates the illicit drug trade is worth 1.5% of world GDP. The natural EA question is "okay, but how cost-effective is it vs other things?" If you're thinking as a citizen, this question isn't so relevant: it doesn't really cost you anything to support this policy change, talk to your friends about it, etc., and it's not as if supporting this would take public money from anything else you might value - indeed, it's a revenue raiser. I leave it open how valuable it is to spend extra 'citizen time' on this vs some other policy. Drug policy reform could be one item in a potential basket of 'no-cost' policies an effective altruist might support alongside, say, improved animal welfare. (I previously posted about a policy platform back in 2019, but nothing much happened.) If you're thinking as a donor, then you really would wonder how drug policy reform efforts, e.g. advocacy organisations, compare to other things. This is pretty complicated as both the scale of the problem is unclear (as noted) and it's really tricky to model the effectiveness of systemic change interventions anyway. I don't have the capacity to look at this anytime soon, nor will it be a priority for the Happier Lives Institute, but I would be really enthusiastic for someone else to take a stab at this and would be happy to chat to them about it. If you're wondering what to do with your career, I think it's very possible, given the importance of personal fit, that this could be a priority path for someone with suitable skills and interests. At least, it's worth considering. Finally, it's worth noting that, if someone objects to the...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Long-Term Future Fund: May 2021 grant recommendations, published by abergal on the AI Alignment Forum. Introduction Since November, we’ve made 27 grants worth a total of $1,650,795 (with the expectation that we will get up to $220,000 back), reserved $26,500 for possible later spending, and referred two grants worth a total of $120,000 to private funders. We anticipate being able to spend $3–8 million this year (up from $1.4 million spent in all of 2020). To fill our funding gap, we’ve applied for a $1–1.5 million grant from the Survival and Flourishing Fund, and we hope to receive more funding from small and large longtermist donors. The composition of the fund has changed since our last grant round. The new regular fund team consists of Asya Bergal (chair), Adam Gleave, and Oliver Habryka, though we may take on additional regular fund managers over the next several months. Notably, we’re experimenting with a “guest manager” system where we invite people to act as temporary fund managers under close supervision. Our guest managers this round were Daniel Eth, Evan Hubinger, and Ozzie Gooen. Highlights Our grants include: $35,000 to support John Wentworth’s independent AI safety research, specifically testing an empirical claim relevant to AI alignment called the natural abstraction hypothesis. John Wentworth has produced a huge amount of high-quality work that has influenced top AI safety researchers and pushed the field of AI safety forward; this grant will enable him to produce more work of this kind. This grant was given the maximum possible score by four of our six fund managers (one manager gave a non-maximal score; the other didn’t score this grant). Up to $200,000 to fund PhD students and computing resources at David Krueger’s new AI safety lab at the University of Cambridge. David Krueger has done excellent safety work and was recently appointed to a faculty position in Cambridge’s Computational and Biological Learning Lab. Having a new academic lab focused on AI safety is likely to have highly positive field-building effects by attracting promising junior AI researchers to safety work and shifting the thinking of more senior researchers. $6,917 to support a research assistant for Jess Whittlestone and Shahar Avin’s work at the Centre for the Study of Existential Risk (CSER), wherein they hope to ensure that the lessons learnt from COVID-19 improve global catastrophic risk (GCR) prevention and mitigation in the future. This is a timely grant for an ambitious project which, if successful, could shift global attitudes towards GCRs. Grant recipients See below for a list of grantees’ names, grant amounts, and project descriptions. Most of the grants have been accepted, but in some cases, the final grant amount is still uncertain. Grants made during the last grant application round: Adam Shimi ($60,000): Independent research in AI alignment for a year, to help transition from theoretical CS to AI research. AI Safety Camp ($85,000): Running a virtual and physical camp where selected applicants test their fit for AI safety research. Alexander Turner ($30,000): Formalizing the side effect avoidance problem. Amon Elders ($250,000): Doing a PhD in computer science with a focus on AI safety. Anton Korinek ($71,500): Developing a free online course to prepare students for cutting-edge research on the economics of transformative AI. Anonymous ($33,000): Working on AI safety research, emphasizing AI learning from human preferences. Center for Human-Compatible AI ($48,000): Hiring research engineers to support CHAI’s technical research projects. Daniel Filan ($5,280): Technical support for a podcast about research aimed at reducing x-risk from AI. David Krueger ($200,000, with an expected reimbursement of up to $120,000): Computing resources and researcher salaries at a new...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. This is: This Can't Go On, published by Holden Karnofsky on the effective altruism forum. Audio version available at Cold Takes (or search Stitcher, Spotify, Google Podcasts, etc. for "Cold Takes Audio") This piece starts to make the case that we live in a remarkable century, not just a remarkable era. Previous pieces in the series talked about the strange future that could be ahead of us eventually (maybe 100 years, maybe 100,000). Summary of this piece: We're used to the world economy growing a few percent per year. This has been the case for many generations. However, this is a very unusual situation. Zooming out to all of history, we see that growth has been accelerating; that it's near its historical high point; and that it's faster than it can be for all that much longer (there aren't enough atoms in the galaxy to sustain this rate of growth for even another 10,000 years). The world can't just keep growing at this rate indefinitely. We should be ready for other possibilities: stagnation (growth slows or ends), explosion (growth accelerates even more, before hitting its limits), and collapse (some disaster levels the economy). The times we live in are unusual and unstable. We shouldn't be surprised if something wacky happens, like an explosion in economic and scientific progress, leading to technological maturity. In fact, such an explosion would arguably be right on trend. For as long as any of us can remember, the world economy has grown1 a few percent per year, on average. Some years see more or less growth than other years, but growth is pretty steady overall.2 I'll call this the Business As Usual world. In Business As Usual, the world is constantly changing, and the change is noticeable, but it's not overwhelming or impossible to keep up with. There is a constant stream of new opportunities and new challenges, but if you want to take a few extra years to adapt to them while you mostly do things the way you were doing them before, you can usually (personally) get away with that. In terms of day-to-day life, 2019 was pretty similar to 2018, noticeably but not hugely different from 2010, and hugely but not crazily different from 1980.4 If this sounds right to you, and you're used to it, and you picture the future being like this as well, then you live in the Business As Usual headspace. When you think about the past and the future, you're probably thinking about something kind of like this: Business As Usual I live in a different headspace, one with a more turbulent past and a more uncertain future. I'll call it the This Can't Go On headspace. Here's my version of the chart: This Can't Go On Which chart is the right one? Well, they're using exactly the same historical data - it's just that the Business As Usual chart starts in 1950, whereas This Can't Go On starts all the way back in 5000 BC. "This Can't Go On" is the whole story; "Business As Usual" is a tiny slice of it. Growing at a few percent a year is what we're all used to. But in full historical context, growing at a few percent a year is crazy. (It's the part where the blue line goes near-vertical.) This growth has gone on for longer than any of us can remember, but that isn't very long in the scheme of things - just a couple hundred years, out of thousands of years of human civilization. It's a huge acceleration, and it can't go on all that much longer. (I'll flesh out "it can't go on all that much longer" below.) The first chart suggests regularity and predictability. The second suggests volatility and dramatically different possible futures. One possible future is stagnation: we'll reach the economy's "maximum size" and growth will essentially stop. We'll all be concerned with how to divide up the resources we have, and the days of a growing pie and a dynamic economy will be over forever. Another is explosi...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. This is: Independent impressions, published by MichaelA on the effective altruism forum. Your independent impression about something is essentially what you'd believe about that thing if you weren't updating your beliefs in light of peer disagreement - i.e., if you weren't taking into account your knowledge about what other people believe and how trustworthy their judgement seems on this topic. Your independent impression can take into account the reasons those people have for their beliefs (inasmuch as you know those reasons), but not the mere fact that they believe what they believe. Meanwhile, your all-things-considered belief can (and probably should!) also take into account peer disagreement. Armed with this concept, I try to stick to the following epistemic/discussion norms, and I think it's good for other people to do so as well: I try to keep track of my own independent impressions separately from my all-things-considered beliefs I try to feel comfortable reporting my own independent impression, even when I know it differs from the impressions of people with more expertise in a topic I try to be clear about whether, in a given moment, I'm reporting my independent impression or my all-things-considered belief One rationale for that bundle of norms is to avoid information cascades. In contrast, when I actually make decisions, I try to always make them based on my all-things-considered beliefs. For example: My independent impression is that it's plausible that an unrecoverable dystopia is more likely than extinction and that we should prioritise such risks more than we currently do. But this opinion seems relatively uncommon among people who've thought a lot about existential risks. That observation pushes my all-things-considered belief somewhat away from my independent impression and towards what most of those people seem to think. And this all-things-considered belief is what guides my research and career decisions. But I think it's still useful for me to keep track of my independent impression and report it sometimes, or else communities I'm part of might end up with overly certain and homogenous beliefs. This term, this concept, and these suggested norms aren't at all original to me - see in particular Naming beliefs, this comment, and several of the posts tagged Epistemic humility (especially this one). But I wanted a clear, concise description of this specific set of terms and norms so that I could link to it whenever I say I'm reporting my independent impression, ask someone for theirs, or ask someone whether an opinion they've given is their independent impression or their all-things-considered belief. My thanks to Lukas Finnveden for suggesting I make this a top-level post (it was originally a shortform). thanks for listening. to help us out with the nonlinear library or to learn more, please visit nonlinear.org.
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. This is: How we promoted EA at a large tech company, published by ParthThaya on the effective altruism forum. This is a linkpost for/@parth.thaya/how-we-promoted-effective-altruism-at-a-large-tech-company-e8cb8c2149ba tl;dr Large tech companies employ hundreds of thousands of people, many of whom are financially well-off and want to help the world, but who are not aware of the effective altruism movement. Because there are already many EA folks working at these companies, and because many of these companies already have the culture and infrastructure to encourage/promote giving (ex. events, donation matching), this presents a huge opportunity to promote and build an EA mindset at these companies. Introduction GiveWell believes their best approach to finding more donors is to reach more people who are demographically similar to their current donors, but have not yet heard of them or effective altruism, namely young professionals in the tech or finance professions — people “with a quantitative mindset.” I work at Microsoft, a company where employees donate over $150 million dollars a year to support nonprofits and schools. Microsoft provides 100% donation and volunteer time matching up to $15k per employee in the US, effectively doubling every donation’s impact. The company also has the entire month of October officially dedicated to charitable giving, called the Give Campaign. During the Give Campaign, teams host lots of fun and interesting events (Poker tournaments, 5ks, cat calendars, etc). Employees are highly encouraged to attend these events, with execs chiming in and mails sent out on participation rates. A few employees are even given a 6-month break from their regular tasks to focus almost exclusively on organizing events for their team. But while the company proudly declares itself to be data driven (and it is in many ways), this has not translated to its giving program. Employees are highly encouraged to give, but are not encouraged to give effectively. Most employees attend events based on interest in the activity, and are often unaware of what cause the event even benefits. This seemed to present an opportunity. How we came together Evan Sandhoefner started a Microsoft Effective Altruism Facebook group and added random Microsoft employees to it. Though the group was minimally active, it was enough for a few EAs to find each other. A couple weeks before the 2018 Give Campaign officially started, I made a post asking what we could do to encourage effective giving at the company. Amy Huang reached out to me and we started bouncing around ideas. Over time, we met others who expressed enthusiasm and interest in what we were trying to do, and joined our team: Alex Bitiukov, Ayo Olubeko, Jessica Yang, and Sonia Jaffe. What we did Year 1: 2018 The first year, we launched an internal campaign during the main Give Campaign to raise awareness of the ideas of effective altruism within the company. We started off by creating an internal site that talked about effective altruism and made the case for why it was important. The site took a lot of text from the main/ website, but looked to appeal specifically to Microsoft employees. alt text alt text We also had links to take site visitors to the company’s internal donations page for various EA-recommended top charities. The next thing we did was put up posters for EA all around campus. This was not trivial for a two-person team, as the Microsoft main campus alone has over 100 buildings, and a typical building had 4–5 floors. On each floor, we put our posters on any available poster-boards we saw, but also by elevators and by bathroom doors (basically, anywhere there was a precedent for putting up posters). We got to postering up ~20 buildings. alt text We also sent out promotional emails to various internal mailing lists (Hack for...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. This is: Health and happiness research topics—Part 1: Background on QALYs and DALYs, published by Derek on the effective altruism forum. Sequence contents Background on QALYs and DALYs The HALY+: Improving preference-based health metrics The sHALY: Developing subjective wellbeing-based health metrics The WELBY (i): Measuring states worse than dead The WELBY (ii): Establishing cardinality The WELBY (iii): Capturing spillover effects The WELBY (iv): Other measurement challenges Applications in effective altruism Applications outside effective altruism Conclusions Sequence summary Note: As many of the posts have not yet been completed, I may edit this summary to reflect the final content. This series of posts describes some of the metrics commonly used to evaluate health interventions and estimate the burden of disease, explains some problems with them, presents some alternatives, and suggests some potentially fruitful areas for further research.[1] It is primarily aimed at members of the effective altruism (EA) community who may wish to carry out one of the projects. Many of the topics would be suitable for student dissertations (especially in health economics, public health, psychology, and perhaps philosophy), but some of the most promising ideas would require major financial investment. Parts of the sequence—particularly the first and last posts—may also be worth reading for EAs with a general interest in evaluation methodology, global health, mental health, social care, and related fields. I begin by looking at health-adjusted life-years (HALYs), particularly the quality-adjusted life-year (QALY) and the disability-adjusted life-year (DALY). By combining length of life and level of health in one metric, these enable direct comparison across a wide variety of health conditions, making them popular both for evaluating healthcare programmes and for quantifying the burden of diseases, injuries, and risk factors in a population. I’ve also heard EAs using these concepts informally as a generic unit of value. However, HALYs have a number of major shortcomings in their current form. In particular, they: neglect non-health consequences of health interventions rely on poorly-informed judgements of the general public fail to acknowledge extreme suffering (and happiness) are difficult to interpret, capturing some but not all spillover effects are of little use in prioritising across sectors or cause areas This can lead to inefficient allocation of resources, in healthcare and beyond. Broadly, three alternative measures[2] could be developed in order to address these limitations: The HALY+: a tweaked version of the original QALY or DALY that captures some non-health outcomes and/or relies on more informed preferences. The sHALY: a “subjective wellbeing-based HALY” that retains the health-focused descriptive system but assigns weights to health states using experienced wellbeing rather than preferences. The WELBY: a wellbeing-adjusted life-year that can, in principle, capture the benefits of all kinds of intervention. A variation, the pWELBY, uses preferences to assign weights to each level of wellbeing. After introducing these metrics, this sequence of posts considers the additional research required to create them, and potential applications both within and outside EA. The importance, tractability, and neglectedness of each major project is briefly considered, though I do not attempt a formal priority ranking.[3] For individual researchers, my extremely tentative view is that work to establish the “dead point” (below which are states worse than dead) and lower bound on wellbeing scales is likely to have the greatest payoff—but, as with careers in general, the best choice of project is likely to depend heavily on personal fit. For well-funded research teams, including some large EA orga...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. This is: 2-week summer course in economic theory and global prioritization: LMK if interested!, published by trammell on the effective altruism forum. Background: I'm an economics DPhil student at Oxford and research associate at GPI. I thought some people might find it valuable if I organized a 2-week course, at the beginning or end of next summer (to avoid overlap with internships/etc), on methods and topics in economic theory that seem especially useful for "global priorities research" purposes, aren't necessarily covered by a standard undergrad or grad economics curriculum, and I happen to know about. It would take 10-25 students, primarily late-stage undergrads or early-stage grad students in economics. It would be in person, with lectures and problem sets and all the rest of it. If it goes well, it might serve as a basis for developing more polished and scalable educational materials. The exact syllabus isn't finalized, but we would try to spend a few days each on what to my understanding are particularly relevant and not-generically-covered topics in growth theory, such as AI and growth (esp. [1]), considerations bearing on the relationship between growth and x-risk (e.g. [2]), and long-term implications of population growth or decline (e.g. [3]); philanthropic strategy, such as my patient philanthropy nonsense ([4]) and the game theory of replaceability / crowding out more generally; finance, such as impact investing and mission hedging ([6]); and mechanism design, such as quadratic funding ([7]) and the mechanisms behind international climate agreements, and how they might apply to other global public goods. I would also try to squeeze in a few words about dead-ends that EA-minded econ theory students often seem to wander down (like why trying to understand and make something x-risk-relevant out of these papers is a waste of time!). The course would probably be funded and sponsored by Forethought. It would probably be in Oxford, but I could look into doing it in the Bahamas, if people prefer (what with FTX being there now and keen to sponsor EA activity there). Transportation and accommodation would be provided. If something like this sounds like it could be appealing to you, please fill out an expression of interest, so I can gauge how much demand there would be and reach out to those interested if it goes ahead. And comment below or reach out to me with any questions or suggestions. Thanks! thanks for listening. to help us out with the nonlinear library or to learn more, please visit nonlinear.org.
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. This is: A practical guide to long-term planning – and suggestions for longtermism, published by weeatquince on the effective altruism forum. Over the last two years I have been researching and advising numerous government officials on how to do long-term thinking well. Now you are probably not going to be shocked to hear me say it but: making long-term decisions is difficult. Most institutions don’t do it very well and the feedback loops to tell us what works are, as you would expect, long. Yet, that said, it is neither a new challenge nor an uncommon challenge. Many groups of people have faced this problem before and developed tools, strategies and approaches that seem to be working. I have been trying to pull all of this together to paint a rough picture of what best practice in long-term thinking looks like, and advise governments accordingly. To do that work well I did of course engage in some depth with relevant academic work, including the research on longtermism both from within academia and on this forum. And lo and behold it seemed to me like the space was divided into two distinct camps: longtermist theorists and long-term practitioners. The theorists wonder why policy makers do not listen to them and the policy practitioners wonder why academics are not producing work relevant to them. As a practitioner, it seemed that on some days I would say something that was obvious to me and a researcher would be excited by how novel and useful it is, yet on other days I just could not understand the things longtermist researchers were doing and why it mattered. This post is an attempt to bridge this divide. The post is in three parts: Section A is descriptive. I invite you to look around my world, at the politicians, policy makers and risk planners who think long-term. I draw examples from fields as diverse as defence, forestry, tech policy and global development looking for common threads and patterns that give us some idea of how we should be making our long-term plans and decisions. My hope is to both be informative about current best practice in long-term planning but also to give a sense of where I am coming from as a practitioner thinking about the long-term. Section B is applied. There are of course differences between how a UK government policy official will think about the long-term, and how longtermists might think about the long-term. I take some of the ideas described in Section A and try applying them to some longtermist questions. I don’t have all the answers but I hope to suggest areas for future research and exploration. Section C is constructive. I reflect on how my experience as a practitioner of longtermism shapes my view of the academic longtermist community. I then make some recommendations about how longtermists can better produce useful practical research. Section A: Welcome to my world, let me show you around Imagine that you are a politician or policy maker. You believe that the future matters a lot and that preventing existential risk is important, but you are uncertain about how best to achieve long-term goals. So for a starting point you look for existing examples of good long-term planning and long-term decision making. At first good examples of long-term policy thinking can be hard to spot. Political incentives that push policy-makers towards short-term plans [1] or towards making long-term decisions primarily based on ideology [2]. There are however places where there is seemingly good long-term policy making to learn from, especially a step away from the most politicised topics. And if we look across enough institutions we start to get a picture of a best practice approach to long-term thinking. Now I don’t want to claim that current best practice represents the only way to do long term thinking. But I do think it makes sense to set common sen...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. This is: Can the EA community copy Teach for America? (Looking for Task Y) , published by alexrjl on the effective altruism forum. Summary (edited in) Below, I make the case for the importance of thinking about "Task Y", a way in which people who are interested in EA ideas can usefully help, without moving full time into an EA career. The most useful way in which I am now thinking about "Task Y" is as an answer to the question "What can I do to help?". Motivation & introduction to Task Y Episode 10 of the 80000hours podcast was recently re-aired, and one part of the conversation really stayed with me as I listened, and prompted me to ask a question. I've bolded the part I'm referring to for emphasis, but included a much longer quote for context. Robert Wiblin: A question that often comes up is whether Effective Altruism should aim to be a very broad movement that appeals to potentially hundreds of millions of people, and it helps them each to make a somewhat larger contribution, or whether it should be more, say, like an academic research group or an academic research community that has only perhaps thousands or tens of thousands of people involved, but then tries to get a lot of value out of each one of them, really get them to make intellectual advances that are very valuable for the world. What’s your thought on that, on the two options there? Nick Beckstead: I guess, if I have to pick one, maybe I would pick the second option, but I might frame it a little bit differently, and I might say, “Let’s leave the first option open in the long run as well.” I guess, the way I see it right now is this community doesn’t have currently a scalable use of a lot of people. There’s some groups that have found efficient scalable uses of a lot of people, and they’re using them in different ways. For example, if you look at something like Teach for America, they identified an area where, “Man, we could really use tons and tons of talented people. We’ll train them up in a specific problem, improving the US education system. Then, we’ll get tons of them to do that. Various of them will keep working on that. Some of them will understand the problems the US education system faces, and fix some of its policy aspects.” That’s very much a scalable use of people. It’s a very clear instruction, and a way that there’s an obvious role for everyone. I think, the Effective Altruist Community doesn’t have a scalable use of a lot of its highest value . There’s not really a scalable way to accomplish a lot of these highest valued objectives that’s standardised like that. The closest thing we have to that right now is you can earn to give and you can donate to any of the causes that are most favored by the Effective Altruist Community. I would feel like the mass movement version of it would be more compelling if we’d have in mind a really efficient and valuable scalable use of people, which I think is something we’ve figured out less. I guess what I would say is right now, I think we should figure out how to productively use all of the people who are interested in doing as much good as they can, and focus on filling a lot of higher value roles that we can think of that aren’t always so standardised or something. We don’t need 2000 people to be working on AI strategy, or should be working on technical AI safety exactly. I would focus more on figuring out how we can best use the people that we have right now. Nick's conclusion, that we should focus on making best use of the people who are currently part of the EA community is a sensible one, but his statement, and in particular the bolded part, I believe hints at another, potentially exciting question: What if there were a scaleable way to effectively use the effort and time of people who agree with broad EA principles, but who for for some reason aren't abl...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. This is: [updated] Global development interventions are generally more effective than climate change interventions, published by HaukeHillebrandt on the effective altruism forum. Previously titled “Climate change interventions are generally more effective than global development interventions”. Because of an error the conclusions have significantly changed. [old version]. I have extended the analysis and now provide a more detailed spreadsheet model below. In the comments below, Benjamin_Todd uses a different guesstimate model and found the climate change came out ~80x better than global health (even though the point estimate found that global health is better). Word count: ~1800 Reading time: ~9 mins Keywords: Climate change, climate policy, global development, global health, cause prioritization, prioritization research, comparing diverse benefits Epistemic status: Uncertain and speculative. I don’t excessively hedge my claims throughout for clarity’s sake (#‘better wrong than vague’, #“say wrong things”, #"correct me if I'm wrong", #"All models are wrong, but some are useful"). Acknowledgments: Thanks to John Halstead, Danny Bressler, Sahil Shah, and members on the Effective Altruism forum, especially AGB, for helpful comments. Any errors are mine. Comparative cost-effectiveness of climate change and global development Summary Does climate change deserve more attention within the effective altruism community?[1] What is more effective: climate change interventions to avert emissions per tonne or single recipient global development interventions such as cash transfers? Are targeted interventions to more fundamentally transform the lives of the poorest more effective than supplying broad global public goods such as a stable climate with comparatively small benefits to everyone on the planet? To answer these questions, the following question is crucial: “What value should we use for the social cost of carbon to adequately reflect the greater marginal utility of consumption for low-income people?”[2] Here, I tried to answer this question. Surprisingly, I find that global development interventions are generally more effective than climate change interventions. My spreadsheet model below shows that climate change interventions are only more effective than global development interventions, if and only if: Money is worth only 100 times as much to the global poor than people in high-income countries (i.e. if utility to consumption is logarithmic) and not more AND climate change interventions are very effective (less than $1 per tonne of carbon averted) AND/OR under quite pessimistic assumptions about climate change (if the social cost of carbon is higher than $1000 per tonne of carbon). Key claims I base the above conclusion on the following three empirical claims: 1. New research on the income-adjusted country-level social cost of carbon allows us to compare global development interventions to climate change interventions. The new research is the first to use climate model projections, empirical climate-driven economic damage estimations, and also socio-economic projections which take into account greater marginal utility of consumption for every country individually.[3] In other words, this takes into account “your dollar does (>)100x or more good if you give to the poorest rather than people in high-income countries”). More on income weighting in Appendix 2. Other more canonical Integrated Assessment Models (IAM) such as DICE have only have one value for the whole world, and, while the RICE IAM has 12 regions,[4] this still understates the heterogeneous geography of climate damage. The new research first estimated the social cost of carbon for every country in the world. Then, the authors summed up all the country-level costs of carbon to arrive at the global cost of carbon: US$...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. This is: Summary of Core Feedback Collected by CEA in Spring/Summer 2019, published by Ben_West, Centre for Effective Altruism on the effective altruism forum. Introduction The Centre for Effective Altruism (CEA) aims to grow and maintain the Effective Altruism (EA) movement. As part of that work, it is important for us to understand the needs, values, and concerns of members of the EA community. CEA collects feedback from community members in a variety of ways (see “CEA’s Feedback Process” below). In the spring and summer of 2019, we reached out to about a dozen people who work in senior positions in EA-aligned organizations to solicit their feedback. We were particularly interested to get their take on execution, communication, and branding issues in EA. Despite this focus, the interviews were open-ended and tended to cover the areas each person felt was important. This document is a summary of their feedback. The feedback is presented “as is,” without any endorsement by CEA. This feedback represents a small (albeit influential) portion of the EA community, and should be considered in context with other sources of feedback. This post is the first in a series of upcoming posts where we aim to share summaries of the feedback we have received. The second is here. CEA’s Feedback Process CEA has, historically, been much better at collecting feedback than at publishing the results of what we collect. This post is part of our attempt to address that shortcoming and publish more feedback, but, until more can be published, we want to share more details about the types of feedback we collect. As some examples of other sources of feedback CEA has collected this year: We have received about 2,000 questions, comments and suggestions via Intercom (a chat widget on many of CEA’s websites) so far this year We hosted a group leaders retreat (27 attendees), a community builders retreat (33 attendees), and had calls with organizers from 20 EA groups asking about what’s currently going on in their groups and how CEA can be helpful Calls with 18 of our most prolific EA Forum users, to ask how the Forum can be made better. A “medium-term events” survey, where we asked everyone who had attended an Individual Outreach retreat how the retreat impacted them 6-12 months later. (53 responses) EA Global has an advisory board of ~25 people who are asked for opinions about content, conference size, format, etc., and we receive 200-400 responses to the EA Global survey from attendees each time. The feedback summarized in this document sometimes agrees with other feedback we have received, and sometimes disagrees. This document generally presents feedback “as is” in an attempt to give an accurate summary of people’s responses, even if the feedback here disagreed with opinions we have gotten from other data sources. Solutions Mentioned in this Document In addition to examples of concerns respondents raised, this document contains efforts CEA has implemented which may address the concern. Efforts are ongoing, so these ideas are not intended to be final solutions, and we will continue to iterate as we gather more information about how things are working. Additionally, the solutions were not necessarily triggered by this feedback – many of these projects were started before the feedback round was run, were inspired by other feedback, etc. Executive Summary Things Which Are Going Well CEA’s Community Health and Events Projects. Respondents felt that the Community Health team does important work to keep the community safe, and there is a strong argument for a central entity like CEA to oversee community health. EA Global is the “flagship” event of the community, and smaller events run by CEA were also positively regarded. EA Community Members are Smart, Talented, and Thoughtful. Respondents frequently mentioned ...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. This is: Institutions for Future Generations, published by tylermjohn on the effective altruism forum. Given the plausibility of longtermism, many effective altruists are interested in identifying tractable ways to shape the very long-term future for the better. One neglected and potentially tractable way to vastly improve the value of the long-term future is by identifying future-beneficial political and economic institutions and policies and acting to increase the probability of their implementation at various levels of political organization. Will MacAskill recently advocated age-weighted voting as one such strategy for better-aligning the interests of governments with the interests of future generations to improve the value of the future. We can in principle imagine many more, and potentially more promising design and policy proposals for aligning institutional incentives with the interests of future generations so that States will be more likely to use their massive resources and influence to reduce the likelihood of catastrophic risks and put the world on a more positive long-term trajectory. To that end, I've recently undertaken the project—funded by the Forethought Foundation—of identifying and taxonomizing as many future-beneficial political and economic institutions and policies as possible and evaluating them along at least the following dimensions: How effectively could this design promote value in the very long-run? How politically feasible is this proposal? How likely is it to be co-opted by other (esp. shorttermist) interests? How well could it function as a symbol for a wider longtermist movement? To date, I've identified 33 distinct institutions and policies, ranging from the very incremental/realist to the relatively utopian. I'm writing to solicit your help identifying more potentially future-beneficial institutions and policies. Anything that comes to mind off the top of your head would probably be useful, as this topic is very under-theorized and if I don't list the idea here it's relatively likely that it hasn't been considered at any length anywhere else. I'd also be interested in general feedback on anything relevant to the project, especially suggested amendments to the evaluation criteria and any useful empirical research that would be relevant to making these evaluations. I list all 33 designs below along with a brief and general description. Once the project is finished, it'll be publicly available as a report and I will be happy to share it back here. Note that very few of these ideas originate with me; some of them are in existing literature, and others come from people who I've spoken to, who I acknowledge at the bottom of this post. Note also that not all of these proposals are expected to be good proposals. In the final report, less promising proposals will receive a more shallow review and more promising proposals will receive a more thorough review. Many might turn out to be quite unpromising. Thanks in advance for your feedback! Proposals Voting by Guardianship Future people are granted suffrage which is exercised through ballots cast by a formal body of existing people selected to represent future people and who vote with the express purpose and function of voting on behalf of future people. Demeny Voting Some (possibly all) voters are given an additional vote which they are told to cast on behalf of future generations. Special Voting Rules Specific voting rules for matters concerning future generations, especially in the legislature. One model is a sub-majority rule model: if a pre-determined numerical sub-majority of the legislature determines that a bill is in contempt of future generations, the bill can be stalled or vetoed (subject to overturn by the Courts). Ombudsperson for Future Generations Receives and investigates public complai...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. This is: EA Leaders Forum: Survey on EA priorities (data and analysis), published by Aaron Gertler on the effective altruism forum. Thanks to Alexander Gordon-Brown, Amy Labenz, Ben Todd, Jenna Peters, Joan Gass, Julia Wise, Rob Wiblin, Sky Mayhew, and Will MacAskill for assisting in various parts of this project, from finalizing survey questions to providing feedback on the final post. Clarification on pronouns: “We” refers to the group of people who worked on the survey and helped with the writeup. “I” refers to me; I use it to note some specific decisions I made about presenting the data and my observations from attending the event. This post is the second in a series of posts where we aim to share summaries of the feedback we have received about our own work and about the effective altruism community more generally. The first can be found here. Overview Each year, the EA Leaders Forum, organized by CEA, brings together executives, researchers, and other experienced staffers from a variety of EA-aligned organizations. At the event, they share ideas and discuss the present state (and possible futures) of effective altruism. This year (during a date range centered around ~1 July), invitees were asked to complete a “Priorities for Effective Altruism” survey, compiled by CEA and 80,000 Hours, which covered the following broad topics: The resources and talents most needed by the community How EA’s resources should be allocated between different cause areas Bottlenecks on the community’s progress and impact Problems the community is facing, and mistakes we could be making now This post is a summary of the survey’s findings (N = 33; 56 people received the survey). Here’s a list of organizations respondents worked for, with the number of respondents from each organization in parentheses. Respondents included both leadership and other staff (an organization appearing on this list doesn’t mean that the org’s leader responded). 80,000 Hours (3) Animal Charity Evaluators (1) Center for Applied Rationality (1) Centre for Effective Altruism (3) Centre for the Study of Existential Risk (1) DeepMind (1) Effective Altruism Foundation (2) Effective Giving (1) Future of Humanity Institute (4) Global Priorities Institute (2) Good Food Institute (1) Machine Intelligence Research Institute (1) Open Philanthropy Project (6) Three respondents work at organizations small enough that naming the organizations would be likely to de-anonymize the respondents. Three respondents don’t work at an EA-aligned organization, but are large donors and/or advisors to one or more such organizations. What this data does and does not represent This is a snapshot of some views held by a small group of people (albeit people with broad networks and a lot of experience with EA) as of July 2019. We’re sharing it as a conversation-starter, and because we felt that some people might be interested in seeing the data. These results shouldn’t be taken as an authoritative or consensus view of effective altruism as a whole. They don’t represent everyone in EA, or even every leader of an EA organization. If you’re interested in seeing data that comes closer to this kind of representativeness, consider the 2018 EA Survey Series, which compiles responses from thousands of people. Talent Needs What types of talent do you currently think [your organization // EA as a whole] will need more of over the next 5 years? (Pick up to 6) This question was the same as a question asked to Leaders Forum participants in 2018 (see 80,000 Hours’ summary of the 2018 Talent Gaps survey for more). Here’s a graph showing how the most common responses from 2019 compare to the same categories in the 2018 talent needs survey from 80,000 Hours, for EA as a whole: And for the respondent’s organization: The following table contains data on every category ...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. This is: Community vs Network, published by DavidNash on the effective altruism forum. Intro In this post I’m looking at how much focus we should place on the wider network of people interested in effective altruism versus highly engaged members. The Centre for Effective Altruism has a funnel model describing their focus on contributors and core members as well as people moving down the funnel. I think this has often been interpreted by group organisers as the idea that engagement is key although that is seen as an open question in CEA’s three-factor model of community building. This means people often link engagement to impact, thinking that those who are more involved in the community, go to lots of events or work at EA related organisations are having more impact and so put on events and tailor content towards those activities. It might be that impact is better represented by the diagram below with the percentage of people along the bottom and it is supposed to represent a range of increasing involvement rather than binary in or out. Although the percentages aren’t accurate I think the rough image is true, that the vast majority of people who know about effective altruism aren’t involved in the community. Looking at the larger network of people who are interested in EA, this includes people in a wider variety of careers, potentially busy lives with work, family and other communities, potentially even high up in government, academia and business. They may have 0 or 1 connections to people who are also interested in EA and look for EA related advice when making donations or thinking about career changes once every few years. I’ve made the diagram assuming equal average impact whether someone is in the ‘community’ or ‘network’ but even if you doubled or tripled the average amount of impact you think someone in the community has there would still be more overall impact in the network. Rather than trying to get this 90% to attend lots of events or get involved in a tangential ‘make work’ project, it may be more worthwhile to provide them with value that they are looking for, whether that’s donation advice, career ideas or connections to people in similar fields. Anecdotally I have had quite a few meetings with less engaged members of the wider EA network in London. People who maybe haven’t been to an event or don’t read the forum but have 10-20 years experience and have gone on to work in higher impact organisations or connect to the relevant people involved in EA so that they can help each other. I think the advice to get involved in the EA community still makes sense, but we should focus on the wider network of people getting 1-3 extra connections rather than making a more tight knit community. What does this mean for movement building? If people agree with this analysis, what would it mean for wider EA movement building and for individuals? Less focus on groups based around their location More focus on groups based around a shared career, cause or interest area For example in careers that could be lawyers, info security, consulting For cause areas that could be animal welfare, beneficial AI, new causes For interest areas, some current examples are EA for Christians, Project 4 Awesome and the Giving What We Can community When people want to get more involved in movement building, there are more resources for them to consider a global career or cause network/community as a possible option Less focus on EA aligned organisations for career options (much more discussion here, here and here) More support on helping new cause areas become their own fields More reference to advice that isn’t EA specific, there doesn’t need to be an EA version of each self improvement book that already exists (although sometimes bespoke advice is useful) Effective Altruism as Coordination It may be b...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. This is: How to run a high-energy reading group, published by tessa on the effective altruism forum. Why are reading groups and journal clubs bad so often? I think there are two reasons: boring readings and low-energy discussions. This post is about how to avoid those pitfalls. The problem I have participated in (and organized) some really bad reading groups. This is a shame, because I love a good reading group. They cause me to read more things and read them more carefully. A great group discussion will give me way more than I’d get just by taking notes on a reading. This is what a bad reading group looks like: six people gather around a table. Two kind of skimmed the reading, and two didn’t read it at all. No one knows quite what to talk about. Someone ventures a, “so, what surprised you about the paper?” Another person flips through their notes, scanning for a possible answer. Most people stay quiet. No one leaves the table feeling excited about the reading or about being a part of the group. This is avoidable, but you need to find interesting and valuable readings and you need to structure your group to encourage high-energy discussions. How to find good readings If you’re lucky, someone in your group will propose a reading that they’re excited to re-read and discuss in depth. However, at our East Bay Biosecurity meetups, we often wanted to learn about a topic (say, "regulation of gene drives" or "basic immunology") that no one in the group knew much about. A Google search for “basic immunology biosecurity” will not reliably find interesting readings. What are better ways to find good readings? 1. Follow a syllabus or reading list People may have already compiled good readings on the topic you’re interested in. Take advantage of their work! Some examples: Annotated Bibliography of Recommended Materials from the Center for Human-Compatible AI at UC Berkeley My Most of the 80,000 Hours podcasts include links to recommended further reading 2. Ask an expert for recommendations Find someone who is working on the problem you’re interested in and ask them for advice. It’s okay to cold-email people, and to send them a follow-up or two if they don’t respond (see It Is Your Responsibility to Follow Up). You’ll get better responses if you give some (brief) details on your interests and level of background knowledge; I’ve received random LinkedIn messages asking “how to learn about biosecurity” and that’s not enough information for me to give useful recommendations. A (hypothetical) better example would be something like, “I’m running a reading group of undergrads (a mix of life sciences and computer science) and we’re currently trying to understand how to improve vaccine availability in future pandemics. I reached out because I saw you were involved in [thing]. Are there any papers or readings you’d recommend for the group? Thanks so much for your time!” 3. Browse back catalogs If you can identify a few organizations, researchers, or journalists whose writing you enjoy, just read their work for a while. For example, in East Bay Biosecurity we read a lot of reports from the Johns Hopkins Center for Health Security and the US National Academies Press. 4. Ask one group member to identify good readings by giving a talk If you want to learn about a topic, but you can’t find anything useful from a syllabus, expert, or back catalog, someone is going to have to wade through messy search results until they find something good. To encourage productive Google-wading, I suggest you nominate one of your group members to give a talk on the topic of interest. Preparing the talk will force them to read many things about the topic, and they’re likely to find useful standalone readings along the way. This will require quite a lot of time on that one group member’s part (I recall East Bay Biosecurity ...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. This is: Hiring engineers and researchers to help align GPT-3, published by Paul_Christiano on the effective altruism forum. My team at OpenAI, which works on aligning GPT-3, is hiring ML engineers and researchers. Apply here for the ML engineer role and here for the ML researcher role. GPT-3 is similar enough to "prosaic" AGI that we can work on key alignment problems without relying on conjecture or speculative analogies. And because GPT-3 is already being deployed in the OpenAI API, its misalignment matters to OpenAI’s bottom line — it would be much better if we had an API that was trying to help the user instead of trying to predict the next word of text from the internet. I think this puts our team in a great place to have an impact: If our research succeeds I think it will directly reduce existential risk from AI. This is not meant to be a warm-up problem, I think it’s the real thing. We are working with state of the art systems that could pose an existential risk if scaled up, and our team’s success actually matters to the people deploying those systems. We are working on the whole pipeline from “interesting idea” to “production-ready system,” building critical skills and getting empirical feedback on whether our ideas actually work. We have the real-world problems to motivate alignment research, the financial support to hire more people, and a research vision to execute on. We are bottlenecked by excellent researchers and engineers who are excited to work on alignment. What the team does In the past Reflection focused on fine-tuning GPT-3 using a reward function learned from human feedback. Our most recent results are here, and had the unusual virtue of simultaneously being exciting enough to ML researchers to be accepted at NeurIPS while being described by Eliezer as “directly, straight-up relevant to real alignment problems.” We’re currently working on three things: [20%] Applying basic alignment approaches to the API, aiming to close the gap between theory and practice. [60%] Extending existing approaches to tasks that are too hard for humans to evaluate; in particular, we are training models that summarize more text than human trainers have time to read. Our approach is to use weaker ML systems operating over shorter contexts to help oversee stronger ones over longer contexts. This is conceptually straightforward but still poses significant engineering and ML challenges. [20%] Conceptual research on domains that no one knows how to oversee and empirical work on debates between humans (see our 2019 writeup). I think the biggest open problem is figuring out how and if human overseers can leverage “knowledge” the model acquired during training (see an example here). If successful, ideas will eventually move up this list, from the conceptual stage to ML prototypes to real deployments. We’re viewing this as practice for integrating alignment into transformative AI deployed by OpenAI or another organization. What you’d do Most people on the team do a subset of these core tasks: Design+build+maintain code for experimenting with novel training strategies for large language models. This infrastructure needs to support a diversity of experimental changes that are hard to anticipate in advance, work as a solid base to build on for 6-12 months, and handle the complexity of working with large language models. Most of our code is maintained by 1-3 people and consumed by 2-4 people (all on the team). Oversee ML training. Evaluate how well models are learning, figure out why they are learning badly, and identify+prioritize+implement changes to make them learn better. Tune hyperparameters and manage computing resources. Process datasets for machine consumption; understand datasets and how they affect the model’s behavior. Design and conduct experiments to answer questions about ou...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. This is: Problem area report: Pain, published by Sid Sharma on the effective altruism forum. Write a Review Authors: Sid Sharma, Clare Donaldson, Michael Plant[1] [2] This is a cross-post from the Happier Lives Institute Executive summary We all expect to experience some pain in our lives. For most of us, especially those in high-income countries, these experiences will be mild, bearable, and short. Others are not so fortunate. Millions suffer excruciating pain. Millions more suffer moderate or severe pain. They suffer despite the fact that cheap and effective treatments exist. This report briefly discusses the measurement of pain then explores three major causes of pain and what might be done to relieve them. The findings are relevant for individuals and organisations considering if and how to put their resources (i.e. their money and/or time) towards this global problem. Problem 1: Terminal conditions requiring access to opioids First, we consider pain from terminal conditions such as advanced cancer and HIV.[3] These cause intense suffering if untreated. If carefully treated with opioids[4], 95% of those with severe or moderate-pain report mild or no pain and quality of life greatly improves. In high-income countries (HICs), some 98% of this need for opioids is met; this figure falls to 5% in low and middle-income countries (LMICs). Cost is not the main barrier, however; a course of 90 days’ opioids is as little as $8. This ‘access abyss’ stems from an overestimate of the risks from opioids and a focus on life extending treatment (Knaul et al., 2017a). The specific issues include: restrictive regulation designed to stop the misuse of opioids; a lack of training and awareness among health professionals; and fragile supply chains. We discuss how organisations taking a multipronged approach have succeeded in improving access in India and Uganda. Problem 2: Headache disorders Second, we examine two headache disorders: migraines and cluster headaches. The former are common, affecting around one in six people, and sometimes debilitating. They impose a burden of disease roughly comparable with malaria or depression.[5] The latter are agonising and experienced by 0.1-0.2% of the global population. Inexpensive relief exists for migraines, such as aspirin, triptans, and propranolol. The main barriers appear to be: patients do not seek help; and if they do, they are often misdiagnosed by doctors who generally receive little training about these conditions. Education campaigns for physicians, patients, and policymakers seem to be the order of the day. Temporary relief exists for cluster headaches in oxygen and triptans, while preventative agents can be used to reduce the frequency of headaches. Like migraines, patients are often misdiagnosed and receive the wrong treatment. Yet, even with access to the right treatments, many people with cluster headaches endure a great deal of suffering. In addition to education campaigns, possible solutions include increasing access to proven treatments for people in low-resource settings or expediting the development of, and access to, novel therapies, such as psychedelics. Problem 3: Low back pain The third and final issue assessed is low back pain. This is the leading cause of years lived with disability globally. Little is known about what causes low back pain or how to treat it. Efforts to increase access to existing treatments are therefore unpromising. However, there may be a high value of information in medical research into the nature of and intervention for this problem. Conclusions and limitations Our report closes with suggestions for further research and identifies some promising career and donation opportunities. We have not been able to thoroughly evaluate the best ways to make progress within this problem area; so these suggestions sh...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. This is: Which World Gets Saved, published by trammell on the effective altruism forum. It is common to argue for the importance of x-risk reduction by emphasizing the immense value that may exist over the course of the future, if the future comes. Famously, for instance, Nick Bostrom calculates that, even under relatively sober estimates of the number and size of future human generations, "the expected value of reducing existential risk by a mere one millionth of one percentage point is at least a hundred times the value of a million human lives". [Note: People sometimes use the term "x-risk" to refer to slightly different things. Here, I use the term to refer to an event that would bring the value of future human civilization to roughly zero—an extinction event, a war in which we bomb ourselves back to the Stone Age and get stuck there forever, or something along those lines.] Among those who take such arguments for x-risk reduction seriously, there seem to be two counterarguments commonly (e.g. here) raised in response. First, the future may contain more pain than pleasure. If we think that this is likely, then, at least from the utilitarian perspective, x-risk reduction stops looking so great. Second, we may have opportunities to improve the trajectory of the future, such as by improving the quality of global institutions or by speeding economic growth, and such efforts may have even higher expected value than (immediate) x-risk reduction. "Mundane" institution-building efforts may also have the benefit of reducing future catastrophic risks, should they arise. It seems to me that there is another important consideration which complicates the case for x-risk reduction efforts, which people currently neglect. The consideration is that, even if we think the value of the future is positive and large, the value of the future conditional on the fact that we marginally averted a given x-risk may not be. And in any event, these values are bound to depend on the x-risk in question. For example: There are things we currently do not know about human psychology, some of which bear on how inclined we are toward peace and cooperation. Perhaps Steven Pinker is right, and violence will continue its steady decline, until one evening sees the world's last bar fight and humanity is at peace forever after. Or perhaps he's wrong—perhaps a certain measure of impulsiveness and anger will always remain, however favorable the environment, and these impulses are bound to crop up periodically in fights and mass tortures and world wars. In the extreme case, if we think that the expected value of the future (if it comes) is large and positive under the former hypothesis but large and negative under the latter, then the possibility that human rage may end the world is a source of consolation, not worry. It means that the existential risk posed by world war is serving as a sort of "fuse", turning off the lights rather than letting the family burn. As an application: if we think the peaceful-psychology hypothesis is more likely than the violent-psychology hypothesis, we might think that the future has high expected value. We might thus consider it important to avert extinction events like asteroid impacts, which would knock out worlds "on average". But we might oppose efforts like the Nuclear Threat Initiative, which disproportionately save violent-psychology worlds. Or we might think that the sign of the value of the future is positive in either scenario, but judge that one x-risk is worth devoting more effort to than another, all else equal. Once we start thinking along these lines, we open various cans of worms. If our x-risk reduction effort starts far "upstream", e.g. with an effort to make people more cooperative and peace-loving in general, to what extent should we take the success of the interme...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. This is: Longtermism', published William_MacAskill on the effective altruism forum. This post discusses the introduction and definition of the term ‘longtermism’. Thanks to Toby Ord, Matthew van der Merwe and Hilary Greaves for discussion. [Edit, Nov 2021: After many discussions, I've settled on the following informal definition: Longtermism is the view that positively influencing the longterm future is a key moral priority of our time. This is what I'm going with for What We Owe The Future. With this in hand, I call strong longtermism is the view that positively influencing the longterm future is the key moral priority of our time. It turns out to be suprisingly difficult to define this precisely, but Hilary and I give it our best shot in our paper.] Up until recently, there was no name for the cluster of views that involved concern about ensuring the long-run future goes as well as possible. The most common language to refer to this cluster of views was just to say something like ‘people interested in x-risk reduction’. There are a few reasons why this terminology isn’t ideal: It’s cumbersome and somewhat jargony It’s a double negative; whereas focusing on the positive (‘ensuring the long-run future goes well’) is more inspiring and captures more accurately what we ultimately care about People tend to understand ‘existential risk’ as referring only to extinction risk, which is a strictly narrower concept You could care a lot about reducing existential risk even though you don’t care particularly about the long term if, for example, you think that extinction risk is high this century and there’s a lot we can do to reduce it, such that it’s a very effective thing even by the lights of the present generation’s interests. Similarly, you can care a lot about the long-run future without focusing on existential risk reduction, because existential risk is just about drastic reductions in the value of the future. (‘Existential risk’ is defined as a risk where an adverse outcome would either annihilate Earth-originating intelligent life or permanently and drastically curtail its potential.) But, conceptually at least (and I think in practice, too) smaller improvements in the expected value of the long-run future could be among the things we want to focus on, such as changing people’s values, or changing political institutions (like the design of a world government) before some lock-in event occurs. You might also think (as Tyler Cowen does) that speeding up economic and technological progress is one of the best ways of improving the long-run future. For these reasons, and with Toby Ord’s in-progress book on existential risk providing urgency, Toby and Joe Carlsmith started leading discussions about whether there were better terms to use. In October 2017, I proposed the term ‘longtermism’, with the following definition: “Longtermism =df the view that the most important determinant of the value of our actions today is how those actions affect the very long-run future.” Since then, the term ‘longtermism’ seems to have taken off organically. I think it’s here to stay. Unlike ‘existential risk reduction’, the idea behind ‘longtermism’ is that it is compatible with any empirical view about the best way of improving the long-run future and, I hope, helps immediately convey the sentiment behind the philosophical position, in the same way that ‘environmentalism’ or ‘liberalism’ or ‘cosmopolitanism’ does. But getting a good definition of the term is important. As Ben Kuhn notes, the term could currently be understood to refer to a mishmash of different views. I think that’s not good, and we should try to develop some standardisation before the term is locked in to something suboptimal. I think that there are three natural concepts in this area, which we should distinguish. My proposal is that ...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. This is: Concerning the Recent 2019-Novel Coronavirus Outbreak, published by Matthew_Barnett on the effective altruism forum. Update: Most information presented here is out of date. See the 80,000 hours page for more up-to-date information. I have been researching the Wuhan Coronavirus for several hours today, and I have come to the tentative conclusion that the situation is worse than I initially thought. Given my current understanding, it now seems reasonable to assign a non-negligible probability (>2%) to the proposition that the current outbreak will result in a global disaster (>50 million deaths resulting from the pathogen within 1 year). I understand this prediction will sound alarmist, but in this post I will outline some of the reasons why I have come to this conclusion. I now believe that it is warranted for effective altruists to take particular actions to prepare for a resulting pandemic. The most effective action is likely to research preparation in order to limit exposure to sources of the virus. Sending out evidence-based warning signals to at-risk communities may also be effective at limiting the spread of the pathogen. Summary of my reasons for believing that this outbreak could result in a global disaster The current outbreak matches the criteria that scientists have identified as being particularly likely characteristics of a pandemic-induced global disaster. That is, it’s a disease that’s contagious during a long incubation period, has a high infection rate, has no known treatment, few people are immune, and it has a low but significant mortality rate. See this article for a summary of likely characteristics of a pandemic-induced global disaster. Based on my research, I wasn't able to identify any historically recent pathogen with these characteristics, giving me reason to believe that using an outside view to argue against alarmism may not be warranted. For reference, the 2003 SARS outbreak, the 2009 Swine Flu, and the several Ebola outbreaks do not match the profiles of a global disaster as completely as the current outbreak. Estimates of the mortality rate vary, but one media source says, "While the single figures of deaths in early January seemed reassuring, the death toll has now climbed to above 3 percent." This would put it roughly on par with the mortality rate of the 1918 flu pandemic, and over 10 times more deadly than a normal seasonal flu. It’s worth noting, however, that the 1918 flu pandemic killed mostly young adults, whereas the pattern for this pathogen appears to be the opposite (which is normal for pathogens). The incubation period (the period during which symptoms are not present but those infected can still infect others) could be as long as 14 days, according to many sources. An Imperial College London report stated, "Self-sustaining human-to-human transmission of the novel coronavirus (2019-nCov) is the only plausible explanation of the scale of the outbreak in Wuhan. We estimate that, on average, each case infected 2.6 (uncertainty range: 1.5-3.5) other people up to 18th January 2020, based on an analysis combining our past estimates of the size of the outbreak in Wuhan with computational modelling of potential epidemic trajectories. This implies that control measures need to block well over 60% of transmission to be effective in controlling the outbreak." Compare the above infection rate to the H1N1 virus, which some estimate to have infected 10-20% of the world population in 2009. The World Health Organization has said, "The pandemic (H1N1) 2009 influenza virus has a R0 of 1.2 to 1.6 (Fraser, 2009) which makes controlling its spread easier than viruses with higher transmissibility." A simple regression model indicates that the growth rate of the pathogen is predictable and extremely rapid. The number of cases as reported by the Na...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. This is: What FHI’s Research Scholars Programme is like: views from scholars, published by rosehadshar on the effective altruism forum. Write a Review FHI’s Research Scholars Programme (RSP) has now been running for just under two years, and we’re excited to have launched applications for a third cohort of research scholars. In this post, I (RSP’s project manager) want to share some scholars’ responses to a series of prompts about RSP, in their own words. I’ve removed some prompts where there weren’t many responses or I didn’t think they’d be very helpful, and sometimes lightly edited the responses for clarity. Each scholar’s experience of RSP is different, and this sample (~11 out of 19 scholars) probably isn’t representative; but I hope it will give an illustrative idea of what RSP can be like to those who are interested in the programme or considering applying. Note that RSP is still a young programme, and we continue to make changes (that we hope are on-average improvements), so future experiences may differ. Why did you want to do RSP in the first place? “I wanted to figure out my career plans, work on my health, and see what kinds of research I was good at.” “After having led the research wing of an EA organization, I wanted to transition to doing research myself, but wasn’t sure which area to focus on. I was hoping to explore different directions to make a more informed decision.” “I had a fairly specific vision of what I wanted to work on, and thought I could teach myself the important necessary things from online resources and books. I liked that RSP seemed to provide a good environment for independent research and study.” “I really liked the program description, and a large amount of research freedom and space to explore." What are you working on at the moment? “I’m trying to clarify and evaluate claims that distributions of opportunities for altruistic impact are often heavy-tailed – i.e. roughly that the total impact from many different activities will be dominated by the few highest-impact ones.” “I’m working on a few projects at the moment. One is on investigating potential effects from transformative narrow AI, one is on investigating atomically precise manufacturing, and one is on mapping out potential paths to transformative AI.” “I’m working on several projects at the moment, one of which is on the effects current and advanced AI systems might have on human autonomy. In another project, I analyse the opportunities and challenges that might arise from introducing broader impact statement requirements for ML conference submissions.” How do you spend most of your time? “Most of my time is spent on the research projects that I am working on. In practice, this means that I spend a fair bit of time doing solo research and writing either at Oxford’s libraries or in the FHI office. I also spend time meeting with collaborators, other researchers, or people doing work that is relevant to my research. There is an active community of researchers willing to engage on new projects, so I find there is no shortage of people interested in workshopping ideas or collaborating.” “It depends on the time of the academic year. I spend the majority of my time on research but there are times where other things, such as teaching, presenting, or consulting take up a whole bunch of my time.” “This was actually quite varied during the program, where in some quarters I was every few weeks in the US, attending conferences and workshops and meeting many others working in the field, other times I was mainly walking in Christchurch meadows, thinking, drawing at whiteboards, and not talking to too many people" What problems have you faced on RSP? “[T]he freedom to largely do what you like is a strength, but the relative lack of structure can also be a challenge. Although the RSP leadership pr...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. T his is: Can my self-worth compare to my instrumental value?, published by C Tilli on the effective altruism forum. A personal reflection on how my experience of EA is similar to my experience of religious faith in that it provides a sense of purpose and belonging, but that I miss the assurance of my own intrinsic value and how that can make it difficult to maintain a stable sense of self-worth. Note: I realize that my experience of religion and faith is probably different from that of a lot of other people. My aim is not to get into a discussion of what religion does right or wrong, especially since I am no longer religious. I grew up with a close connection to my local church and was rather religious until my mid-late teenage years. I am now in my thirties and have been involved with the EA movement for a couple of years. To me, there are similarities between how I remember relating to faith and church and how I now relate to the EA philosophy and movement. For me, both provide (provided) a strong sense of purpose and belonging. There is a feeling that I matter as an individual and that I can have an important mission in life, that I can even be some kind of heroine. For both, there is also a supportive community (of course not always for everyone, but my experience has been mainly positive in both cases) that shares my values and understands and supports how this sense of mission affects many of my important life decisions. This is something that I find very valuable. However, in comparison to what my faith and church used to offer me, there is something lacking in the case of EA. I miss the assurance that I as a person have an intrinsic value, in addition to my instrumental value as a potential world-saviour. With faith, you are constantly reminded that God loves you, that God created you just as you are and that you are therefore, in a sense, flawless. There is a path for everyone, and you are always seen and loved in the most important way. This can be a very comforting message, and I feel it has a function to cushion the tough demands that come with the world-saving mission. The instrumental value you have through your mission to do good is in a way balanced by the assurance that no matter what, you also have infinite intrinsic value. With EA, I don’t find any corresponding comforting thought or philosophy to rest in. If I am a well-off, capable person in the rich world, the QALYs I could create or save for others are likely to be much more than the QALYs I can live through myself. This seems to say that my value is mostly made up of my instrumental value, and that my individual wellbeing is less important compared to what I could achieve for others. I believe that if community members perceive that their value is primarily instrumental, this might damage their (our) mental well-being, specifically risking that many people might suffer burnouts. The idea that most of the impact is achieved by a few, very impactful people could also make the people who perceive themselves as having potential for high impact particularly vulnerable, since the gap between their intrinsic value or self-worth and their instrumental value would seem even wider. If the value of our work (the QALYs we can save) is orders of magnitude greater than the value of ourselves (the QALYs we can live), what does that mean? Can we justify self-care, other than as a means to improve ourselves to perform better? Is it possible then to build a stable sense of self-worth that is not contingent on performance? I have read several previous posts on EA’s struggling with feelings of not achieving enough (In praise of unhistoric heroism, Doing good is as good as it ever was, Burnout and self-care), and to me this seems closely related to what I’m trying to address here. I’m not sure what can be done about this ...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. This is: Response to Phil Torres’ ‘The Case Against Longtermism’, published by HaydnBelfield on the effective altruism forum. This short post responds to some of the criticisms of longtermism in Torres’ minibook: Were the Great Tragedies of History “Mere Ripples”? The Case Against Longtermism, which I came across in this syllabus. I argue that while many of the criticisms of Bostrom strike true, newer formulations of longtermism and existential risk – most prominently Ord’s The Precipice (but also Greaves, MacAskill, etc) – do not face the same challenges. I split the criticisms into two sections: the first on problematic ethical assumptions or commitments, the second on problematic policy proposals. Note that I both respect and disagree with all three authors. Torres piece is insightful and thought-provoking, as well as polemical; Ord’s book is a great restatement of the ethical case, though I disagree with his prioritisation of climate change, nuclear weapons and collapse; and Bostrom is a groundbreaking visionary, though one can dispute many of his views. Problematic ethical assumptions or commitments Torres argues that longtermism rests on assumptions and makes commitments that are problematic and unusual/niche. He is correct that Bostrom has a number of unusual ethical views, and in his early writing he was perhaps overly fond of a contrarian ‘even given these incredibly conservative assumptions the argument goes through’ framing. But Torres does not sufficiently appreciate that these limitations and constraints have largely been acknowledged by longtermist philosophers, who have (re)formulated longtermism so as to not require these assumptions and commitments. Total utilitarianism Torres suggests that longtermism is based on an ethical assumption of total utilitarianism, a view in which we should maximise wellbeing based on adding together the wellbeing of all the individuals in a group. Such a ‘more is better’ ethical view accords significant weight to trillions of future individuals. He points out that total utilitarianism is not a majority opinion amongst moral philosophers. However, although total utilitarianism strongly supports longtermism, longtermism doesn’t need to be based on total utilitarianism. One of the achievements of The Precipice is Ord’s arguments pointing out the affinities between longtermism with other ethical traditions, such as conservatism, obligations to the past, virtue ethics. One can be committed to a range of ethical views and endorse longtermism. Trillions of simulations on computronium Torres suggests that the scales are tilted towards longtermism by including in the calculation quadrillions of simulations of individuals living flourishing lives. The view that such simulations would be moral agents, or that this future is desirable, is certainly unusual. But one doesn’t have to be committed to this view for the argument to work. The argument goes through if we assume that humanity never leaves Earth, and simply survives until the Earth is uninhabitable – or even more conservatively, survives the duration of an average mammalian species. There are still trillions of future individuals, whose interests and dignity matter. ‘Reducing risk from 0.001% to 0.0001% is not the same as saving thousands of lives’ Torres implies that longtermism is committed to a view of the form that reducing risk from 0.001% to 0.0001% is morally equivalent to saving e.g. thousands of present day lives. This a clear example of early Bostrom stating his argument in a philosophically robust, but very counterintuitive way. Worries about this framing have been common for over a decade, in the debate over ‘Pascal’s Mugging’. However, longtermism does not have to be stated in such a way. The probabilities are unfortunately likely higher – for example Ord gives a 1/6 (~16...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. This is: Virtues for Real-World Utilitarians, published by Stefan_Schubert, Lucius_Caviola on the effective altruism forum. This is a linkpost for In this paper, we argue that utilitarians who try to act on utilitarianism in the real world face many psychological obstacles, ranging from selfishness to moral biases to limits to epistemic and instrumental rationality. To overcome the most important of these obstacles, utilitarians need to cultivate a number of virtues. We argue that utilitarians should prioritize six virtues. Moderate altruism - to set aside some of their resources for others. Moral expansiveness - to care about distant beneficiaries. Effectiveness-focus - to prioritize the most effective interventions. Truth-seeking - to overcome epistemic biases to find those effective interventions. Collaborativeness - to engage in fruitful collaboration with other utilitarians, as well as non-utilitarians. Determination - to consistently act on utilitarian principles with persistence and deliberation In addition, we argue that utilitarians should normally not engage in harm for the greater good, but should stick to common sense norms such as norms against lying and stealing. So in our view, real-world utilitarianism converges with common sense morality in some respects. Utilitarians should follow common sense norms and should not feel that they have to sacrifice almost all of their resources for others, in contrast to what it might seem at first glance. But in other ways, real-world utilitarianism diverges from common sense morality. Because some opportunities to do good are so much more effective than others, utilitarians should cultivate virtues that allow them to take those opportunities, such as effectiveness-focus and moral expansiveness. Those virtues are not emphasized by common sense morality. Some of our suggested virtues are commonly associated with utilitarianism. Moral expansiveness is maybe the clearest example. By contrast, virtues such as truth-seeking, collaborativeness, and determination do not tend to be associated with utilitarianism, and are not conceptually tied to it. But empirically, it just turns out that they are very important in order to maximize utilitarian impact in the real world. thanks for listening. to help us out with the nonlinear library or to learn more, please visit nonlinear.org.
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. This is: EA Global Tips: Networking with others in mind, published by kuhanj on the effective altruism forum. Summary/Context: EAs tend to be pretty good at thinking about people other than themselves. One situation in which I don’t see this as much is when networking, where I've seen people largely focus on their careers/questions+uncertainties/projects/funding opportunities/etc. EA Global London 2021 is a day away, and many attendees are searching for attendees to schedule meetings with (which I, and many others, usually strongly recommend over attending recorded sessions, and most other sessions too). I thought now (or more accurately a few days ago, oops) might be a good time to write down some thoughts on: the importance and benefits of coordination in communities with shared goals like the EA community. the implications of this for networking in EA and specifically at EA Global (the default time for many members of the community to set aside a weekend to meet with other members of the community). how I’ve approached networking at EA Global. Some concrete tips I’d encourage for EAs when networking (especially for EA Global): Think about who you can help and how you can help them, along with who can help you when deciding who to reach out to. Default to thinking about your network (EA group, friends, etc) along with yourself when deciding who to network with. In the spirit of the above point, consider how your network can help others along with how others can help your network. When having conversations, get into the habit of regularly thinking about how you can provide value to your conversation partner, and actually following up. I’ve listed some concrete ways I’ve applied these principles at previous EA conferences in the post, and how doing so has helped generate impact (and more specifically, Stanford EA and SERI succeed). The Importance of Coordination: My favourite article on the importance of coordination in EA is “Doing good together—how to coordinate effectively, and avoid single-player thinking” by Ben Todd. In it, he writes: The historian, Yuval Harari, claims in his book Sapiens that better coordination has been the key driver of human progress. He highlights innovations like language, religion, human rights, nation states and money as valuable because they improve cooperation among strangers. If we work together, we can do far more good. This is part of why we started the effective altruism community in the first place: we realised that by working with others who want to do good in a similar way — based on evidence and careful reasoning — we could achieve much more. But unfortunately we, like other communities, often don’t coordinate as well as we could. Instead, especially in effective altruism, people engage in “single-player” thinking. They work out what would be the best course of action if others weren’t responding to what they do. But once you’re part of a community that does respond to your actions, this assumption breaks down. We need to develop new rules of thumb for doing good — the strategies and approaches that work well in a single-player situation often don’t work once you’re collaborating with a community. Tips for Networking with Others in Mind Given the above, here are a few recommendations for networking in EA (which apply in general, but especially for EA Global given its status as the schelling/default networking event for the community): When considering whom to reach out to, think not only about who might be able to provide value, advice, connections, job/internship/research/funding opportunities to yourself, but how you might offer these things to others. If you’re a group organizer, or if you know other EAs/people interested in EA (so probably most people reading this post), consider doing the above for all your group members, or all ...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. This is: Defining Effective Altruism, published by William_MacAskillon the effective altruism forum. Hilary Greaves and Theron Pummer have put together an excellent collection of essays on effective altruism, which will be coming out soon. Effective altruism is still widely misunderstood in academia, so I took the opportunity to write up my thoughts on how effective altruism should be defined and why, and to respond to some of the most common misconceptions about effective altruism. I hope that having a precise definition will also help guard against future dilution or drift of the concept, or confusion regarding what effective altruism is about. You can find the essay (with some typos that will be corrected) here. Below I’ve put together an abridged version, highlighting the points that I’d expect to be most interesting for the Forum audience and trying to cut out some philosophical jargon; for a full discussion, though, the essay is better. The definition of effective altruism I suggest two principal desiderata for the definition. The first is to match the actual practice of those who would currently describe themselves as engaging in effective altruism. The second is to ensure that the concept has as much public value as possible. This means, for example, we want the concept to be broad enough to be endorsable by or useful to many different moral views, but still determinate enough to enable users of the concept to do more to improve the world than they otherwise would have done. This, of course, is a tricky balancing act. My proposal for a definition (which is making CEA’s definition a little more rigorous) is as follows: Effective altruism is: (i) the use of evidence and careful reasoning to work out how to maximize the good with a given unit of resources, tentatively understanding ‘the good’ in impartial welfarist terms, and (ii) the use of the findings from (i) to try to improve the world. (i) refers to effective altruism as an intellectual project (or ‘research field’); (ii) refers to effective altruism as a practical project (or ‘social movement’). The definition is: Non-normative. Effective altruism consists of two projects, rather than a set of normative claims. Maximising. The point of these projects is to do as much good as possible with the resources that are dedicated towards it. Science-aligned. The best means to figuring out how to do the most good is the scientific method, broadly construed to include reliance on careful rigorous argument and theoretical models as well as data. Tentatively impartial and welfarist. As a tentative hypothesis or a first approximation, doing good is about promoting wellbeing, with everyone’s wellbeing counting equally. More precisely: for any two worlds A and B with all and only the same individuals, of finite number, if there is a one to one mapping of individuals from A to B such that every individual in A has the same wellbeing as their counterpart in B, then A and B are equally good.[1] The ideas that EA is about maximising and about being science-aligned (understood broadly) are uncontroversial. The two more controversial aspects of the definition are that it is non-normative, and that it is tentatively impartial and welfarist. Effective Altruism as non-normative The definition could have been normative by making claims about how much one is required to sacrifice: for example, it could have stated that everyone is required to use as much of their resources as possible in whatever way will do the most good; or it could have stated some more limited obligation to sacrifice, such as that everyone is required to use at least 10% of their time or money in whatever way will do the most good. There are four reasons why I think the definition shouldn’t be normative: (i) a normative definition was unpopular among leaders of the comm...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. This is: Logarithmic Scales of Pleasure and Pain: Rating, Ranking, and Comparing Peak Experiences Suggest the Existence of Long Tails for Bliss and Suffering, published by algekalipso on the effective altruism forum. TL;DR Based on: the characteristic distribution of neural activity, personal accounts of intense pleasure and pain, the way various pain scales have been described by their creators, and the results of a pilot study we conducted which ranks, rates, and compares the hedonic quality of extreme experiences, we suggest that the best way to interpret pleasure and pain scales is by thinking of them as logarithmic compressions of what is truly a long-tail. The most intense pains are orders of magnitude more awful than mild pains (and symmetrically for pleasure). This should inform the way we prioritize altruistic interventions and plan for a better future. Since the bulk of suffering is concentrated in a small percentage of experiences, focusing our efforts on preventing cases of intense suffering likely dominates most utilitarian calculations. An important pragmatic takeaway from this article is that if one is trying to select an effective career path, as a heuristic it would be good to take into account how one’s efforts would cash out in the prevention of extreme suffering (see: Hell-Index), rather than just QALYs and wellness indices that ignore the long-tail. Of particular note as promising Effective Altruist careers, we would highlight working directly to develop remedies for specific, extremely painful experiences. Finding scalable treatments for migraines, kidney stones, childbirth, cluster headaches, CRPS, and fibromyalgia may be extremely high-impact (cf. Treating Cluster Headaches and Migraines Using N,N-DMT and Other Tryptamines, Using Ibogaine to Create Friendlier Opioids, and Frequency Specific Microcurrent for Kidney-Stone Pain). More research efforts into identifying and quantifying intense suffering currently unaddressed would also be extremely helpful. Finally, if the positive valence scale also has a long-tail, focusing one’s career in developing bliss technologies may pay-off in surprisingly good ways (whereby you may stumble on methods to generate high-valence healing experiences which are orders of magnitude better than you thought were possible). Introduction Weber’s Law Weber’s Law describes the relationship between the physical intensity of a stimulus and the reported subjective intensity of perceiving it. For example, it describes the relationship between how loud a sound is and how loud it is perceived as. In the general case, Weber’s Law indicates that one needs to vary the stimulus intensity by a multiplicative fraction (called “Weber’s fraction”) in order to detect a just noticeable difference. For example, if you cannot detect the differences between objects weighing 100 grams to 105 grams, then you will also not be able to detect the differences between objects weighing 200 grams to 210 grams (implying the Weber fraction for weight perception is at least 5%). In the general case, the senses detect differences logarithmically. There are two compelling stories for interpreting this law: In the first story, it is the low-level processing of the senses which do the logarithmic mapping. The senses “compress” the intensity of the stimulation and send a “linearized” packet of information to one’s brain, which is then rendered linearly in one’s experience. In the second story, the senses, within the window of adaptation, do a fine job of translating (somewhat) faithfully the actual intensity of the stimulus, which then gets rendered in our experience. Our inability to detect small absolute differences between intense stimuli is not because we are not rendering such differences, but because Weber’s law applies to the very intensity of experience. ...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. This is: Announcing the EA Virtual Group, published by SamiM on the effective altruism forum. Edit: Sep 30, 2020. We changed our name to EA Anywhere. 1. Background Hello, I’m Sami and I currently live in Saudi Arabia. I’ve known about EA for about a year or so, but I never had anyone to discuss it with in person. All of my interactions with EA’s have been online. During the pandemic, I have been lucky to be “adopted” by two EA groups. I joined their online meetings and participated in the book clubs, I finally had someplace where I can engage with EA’s face to face and even make friends with them. I would see familiar faces every week and feel like a part of a community. Unfortunately, this is coming to an end. Since the restrictions are loosening, local groups will return to hosting in-person meetings and I, along with others in my situation, will lose our EA family. 2. Pitch Given the lack of access to local groups that many EA’s face (e.g. Not living close to local groups, disabilities that make it hard to travel to events, responsibilities during meeting time) I think creating a virtual place for those EA’s would be a good idea, to take the role of a local group. The plan is to have regular online meetings to discuss a wide range of effective altruism related ideas, enjoy each other's company, and support each other with our goals to make a positive impact. Potential benefits include: 1. Increasing the geographical diversity of the EA community. 2. Members will learn more about EA and related fields. 3. Personal connections that reduce value drift. 4. Increasing motivation to take action (e.g. work in EA-related projects, apply for EA jobs, donate, post on the forum, etc). 3. Plan On the 1st of July, I will release a poll to decide the most popular meeting times and create a group that gets together at those times. If other time slots are also popular, we could split into multiple groups based on availability. Our meetups are every other Sunday at 6 PM GMT. If you are or know potential members please direct them here/ Thanks for listening. to help us out with the nonlinear library or to learn more, please visit nonlinear.org.
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. This is: More empirical data on 'value drift' , published by SamiM on the effective altruism forum. Edit: Sep 30, 2020. We changed our name to EA Anywhere. 1. Background Hello, I’m Sami and I currently live in Saudi Arabia. I’ve known about EA for about a year or so, but I never had anyone to discuss it with in person. All of my interactions with EA’s have been online. During the pandemic, I have been lucky to be “adopted” by two EA groups. I joined their online meetings and participated in the book clubs, I finally had someplace where I can engage with EA’s face to face and even make friends with them. I would see familiar faces every week and feel like a part of a community. Unfortunately, this is coming to an end. Since the restrictions are loosening, local groups will return to hosting in-person meetings and I, along with others in my situation, will lose our EA family. 2. Pitch Given the lack of access to local groups that many EA’s face (e.g. Not living close to local groups, disabilities that make it hard to travel to events, responsibilities during meeting time) I think creating a virtual place for those EA’s would be a good idea, to take the role of a local group. The plan is to have regular online meetings to discuss a wide range of effective altruism related ideas, enjoy each other's company, and support each other with our goals to make a positive impact. Potential benefits include: 1. Increasing the geographical diversity of the EA community. 2. Members will learn more about EA and related fields. 3. Personal connections that reduce value drift. 4. Increasing motivation to take action (e.g. work in EA-related projects, apply for EA jobs, donate, post on the forum, etc). 3. Plan On the 1st of July, I will release a poll to decide the most popular meeting times and create a group that gets together at those times. If other time slots are also popular, we could split into multiple groups based on availability. Our meetups are every other Sunday at 6 PM GMT. If you are or know potential members please direct them here/ Thanks for listening. to help us out with the nonlinear library or to learn more, please visit nonlinear.org.
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. This is: How much does performance differ between people?, published by Max_Daniel, Benjamin_Todd on the effective altruism forum. by Max Daniel & Benjamin Todd [ETA: See also this summary of our findings + potential lessons by Ben for the 80k blog.] Some people seem to achieve orders of magnitudes more than others in the same job. For instance, among companies funded by Y Combinator the top 0.5% account for more than ⅔ of the total market value; and among successful bestseller authors, the top 1% stay on the New York Times bestseller list more than 25 times longer than the median author in that group. This is a striking and often unappreciated fact, but raises many questions. How many jobs have these huge differences in achievements? More importantly, why can achievements differ so much, and can we identify future top performers in advance? Are some people much more talented? Have they spent more time practicing key skills? Did they have more supportive environments, or start with more resources? Or did the top performers just get lucky? More precisely, when recruiting, for instance, we’d want to know the following: when predicting the future performance of different people in a given job, what does the distribution of predicted (‘ex-ante’) performance look like? This is an important question for EA community building and hiring. For instance, if it’s possible to identify people who will be able to have a particularly large positive impact on the world ahead of time, we’d likely want to take a more targeted approach to outreach. More concretely, we may be interested in two different ways in which we could encounter large performance differences : If we look at a random person, by how much should we expect their performance to differ from the average? What share of total output should we expect to come from the small fraction of people we’re most optimistic about (say, the top 1% or top 0.1%) – that is, how heavy-tailed is the distribution of ex-ante performance? (See this appendix for how these two notions differ from each other.) Depending on the decision we’re facing we might be more interested in one or the other. Here we mostly focused on the second question, i.e., on how heavy the tails are. This post contains our findings from a shallow literature review and theoretical arguments. Max was the lead author, building on some initial work by Ben, who also provided several rounds of comments. You can see a short summary of our findings below. We expect this post to be useful for: (Primarily:) Junior EA researchers who want to do further research in this area. See in particular the section on Further research. (Secondarily:) EA decision-makers who want to get a rough sense of what we do and don’t know about predicting performance. See in particular this summary and the bolded parts in our section on Findings. We weren’t maximally diligent with double-checking our spreadsheets etc.; if you wanted to rely heavily on a specific number we give, you might want to do additional vetting. To determine the distribution of predicted performance, we proceed in two steps: We start with how ex-post performance is distributed. That is, how much did the performance of different people vary when we look back at completed tasks? On these questions, we’ll review empirical evidence on both typical jobs and expert performance (e.g. research). Then we ask how ex-ante performance is distributed. That is, when we employ our best methods to predict future performance by different people, how will these predictions vary? On these questions, we review empirical evidence on measurable factors correlating with performance as well as the implications of theoretical considerations on which kinds of processes will generate different types of distributions. Here we adopt a very loose conception of performa...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. This is: Key Lessons From Social Movement History, published by Jamie_Harris on the effective altruism forum. This is a linkpost for In this post I summarize key strategic implications from Sentience Institute's five completed social movement case studies and several additional case studies by other researchers, looking for correlations and convergent findings across the different movements and contexts. From this evidence, I argue that the farmed animal movement should take steps to avoid unintended consequences from incremental tactics; use a more diverse range of institutional tactics; use fewer individual diet change tactics, primarily as a complement to institutional tactics; explore opportunities to bypass public opinion; and focus less on issue salience. I also argue that the nascent movements to protect the interests of future sentient beings (e.g. artificial sentience) should focus first on building a credible, professional movement but subsequently invest in a broader range of social movement tactics when promising opportunities arise. INTRODUCTION Sentience Institute has now published five social movement case studies. This post provides a summary of the strategic implications from this work so far. The main goal of these case studies is to glean strategic insights for social movements encouraging moral circle expansion (MCE), especially the farmed animal movement and the nascent movements to protect the interests of future sentient beings (e.g. artificial sentience). Other social movements, including the broader effective altruism movement, may also benefit. We have argued: Individual historical cases can therefore provide inspiration for potential tactics and perhaps build our intuition, but we should not place much weight on strategic knowledge gained from a single case, because causal relationships may not replicate in different contexts and may seem to work in contradictory ways. Note, however, that weak evidence can still be useful and should not be disregarded as it is often all we have available. Even if we are not very confident about individual hypothesized causal relationships, we may be able to place significant weight on the strategic knowledge gleaned from history if we see that certain correlations reliably replicate across different movements and across different contexts. In this post, I identify correlations and convergent findings across the different movements and contexts that SI has studied so far. METHODOLOGY The movements we have studied so far are: The British antislavery movement The US anti-abortion movement The US anti-death penalty movement (including brief discussion of Europe) The US prisoners' rights movement The international Fair Trade movement We have a separate post discussing methodological considerations such as why we have chosen to focus on these particular case studies. Our research on this topic is incomplete, so I also draw on similar reports by other researchers associated with the effective altruism community: Animal Charity Evaluators’ case studies of childrens’ rights (UK, Sweden, and New Zealand) and environmentalism (US and Europe). Mauricio Baker’s case studies of and , both with a broad international focus. Włodzimierz Gogłoza’s case study of the US antislavery movement. To identify big-picture trends, I assigned scores to each movement[1] for a number of different variables: Success — whether the movement encouraged institutional changes, change to individuals’ behavior, change in public opinion, or acceptance by targeted institutions. Where I refer to “successful social change,” I am referring to the average of these four submetrics. My rough impression of the proportion of resources spent by each movement on various tactics. The position taken by each movement on other strategic tradeoffs, e.g. confrontation vs....
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. This is: Takeaways from EAF's Hiring Round , published by Jamie_Harris on the effective altruism forum. This is a linkpost for In this post I summarize key strategic implications from Sentience Institute's five completed social movement case studies and several additional case studies by other researchers, looking for correlations and convergent findings across the different movements and contexts. From this evidence, I argue that the farmed animal movement should take steps to avoid unintended consequences from incremental tactics; use a more diverse range of institutional tactics; use fewer individual diet change tactics, primarily as a complement to institutional tactics; explore opportunities to bypass public opinion; and focus less on issue salience. I also argue that the nascent movements to protect the interests of future sentient beings (e.g. artificial sentience) should focus first on building a credible, professional movement but subsequently invest in a broader range of social movement tactics when promising opportunities arise. INTRODUCTION Sentience Institute has now published five social movement case studies. This post provides a summary of the strategic implications from this work so far. The main goal of these case studies is to glean strategic insights for social movements encouraging moral circle expansion (MCE), especially the farmed animal movement and the nascent movements to protect the interests of future sentient beings (e.g. artificial sentience). Other social movements, including the broader effective altruism movement, may also benefit. We have argued: Individual historical cases can therefore provide inspiration for potential tactics and perhaps build our intuition, but we should not place much weight on strategic knowledge gained from a single case, because causal relationships may not replicate in different contexts and may seem to work in contradictory ways. Note, however, that weak evidence can still be useful and should not be disregarded as it is often all we have available. Even if we are not very confident about individual hypothesized causal relationships, we may be able to place significant weight on the strategic knowledge gleaned from history if we see that certain correlations reliably replicate across different movements and across different contexts. In this post, I identify correlations and convergent findings across the different movements and contexts that SI has studied so far. METHODOLOGY The movements we have studied so far are: The British antislavery movement The US anti-abortion movement The US anti-death penalty movement (including brief discussion of Europe) The US prisoners' rights movement The international Fair Trade movement We have a separate post discussing methodological considerations such as why we have chosen to focus on these particular case studies. Our research on this topic is incomplete, so I also draw on similar reports by other researchers associated with the effective altruism community: Animal Charity Evaluators’ case studies of childrens’ rights (UK, Sweden, and New Zealand) and environmentalism (US and Europe). Mauricio Baker’s case studies of and , both with a broad international focus. Włodzimierz Gogłoza’s case study of the US antislavery movement. To identify big-picture trends, I assigned scores to each movement[1] for a number of different variables: Success — whether the movement encouraged institutional changes, change to individuals’ behavior, change in public opinion, or acceptance by targeted institutions. Where I refer to “successful social change,” I am referring to the average of these four submetrics. My rough impression of the proportion of resources spent by each movement on various tactics. The position taken by each movement on other strategic tradeoffs, e.g. confrontation vs. nonco...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. This is: Hiring Process and Takeaways from Fish Welfare Initiative , published by haven on the effective altruism forum. Who should read this: This post will likely only be useful to those employers who will be directly involved in a hiring process, although the Recommendations for Applicants section should be useful for most job applicants. Job applicants may also find it interesting to learn about the employer side of the process. We (the co-founders of Fish Welfare Initiative) recently completed our hiring process for our first new full-time employees: a Research Analyst and an Animal Welfare Specialist (more on that distinction later). As neither of us had previous hiring experience, we set out to build a process based on the best available evidence on how to hire effectively, objectively, and kindly. The following is what we found and learned. We hope that this process and the linked templates will be useful to your organization and will save you some of the large time investment required to create a new process. If you have any questions or comments, feel free to comment below or contact us. Big Takeaways Probably the best hiring advice we received came from the CEO of a GiveWell-recommended charity. He looks for candidates who are “smart, nice, and really want the job.” Your hiring process is a reflection of your organization. To reflect FWI, we aimed to make our hiring process evidence-based, compassionate, unconventional/innovative, and requiring some dedication. If you’re not already, you should use Calendly or another scheduling software to schedule all interviews. We found EA Facebook pages, our website, and personal recommendations to be the best places to find talented applicants. Score everything with a template, where applicant materials and questions are all scored quantitatively. This will help you increase objectivity. You should input these scores for each round into one master spreadsheet. With interviews, we updated away from asking the same somewhat shallow questions. Rather, asking fewer and more probing semi-structured questions provided more valuable information. Don’t be afraid to gather more information about a candidate: additional calls, emails, and interviews can all be helpful. Don’t be a jerk to your applicants. Too many employers are. Your applicants will appreciate you for how you treat them and leave with a good impression of your organization. Resources We Used We relied heavily on the following resources and highly recommend looking them over. We agree with most of the recommendations they make, and have tried to restrict this post to primarily our own original takeaways so as not to duplicate work. Charity Entrepreneurship’s Application Process Takeaways from EAF’s Hiring Round (which heavily inspired the creation and structure of this post) Hiring Ethically & Rationally - Aaron Hamlin Hire with Your Head Effective Strategies for Equity and Inclusion - Sentience Institute Additionally, although it was published towards the end of our hiring process, Notes on hiring a copyeditor for CEA is also a good resource. We are very grateful to the organizations and individuals who created these resources. The Role We Hired For We were originally looking for a researcher who had prior knowledge and (ideally) credentials with fish and animal welfare. As this was the first hire FWI was going to make, we also wanted someone who would be able to take a leadership role in shaping the organization. We ended up advertising for two separate roles: a Research Analyst and an Animal Welfare Specialist. Advertising for Two Separate Jobs Initially, we were unsure whether we wanted someone who was an early-career generalist (flexible and value-aligned), or someone who was later-career and had more domain knowledge and credentials (although possibly less flexibil...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. This is: Should EA Buy Distribution Rights for Foundational Books?, published by Cullen_OKeefe on the effective altruism forum. [Idle speculation; not a systematic analysis] A number of books are foundational to the EA Movement. I am thinking of such books as Reasons and Persons; Doing Good Better; The Life You Can Save; Animal Liberation; and Superintelligence. Ideas introduced or summarized in those books serve as both the intellectual basis of EA and as a common inspiration for EA-aligned actions. Yet, for most people, there are nontrivial costs to accessing these books. True, many people could get them at no monetary cost from a library, though the ease of this probably varies with life stage (i.e., student or not) and geography. As a former EA student group leader, I know CEA was happy to reimburse the expense of getting some physical copies of our own, and that was excellent. However, there have been many times when I would have liked to cite these books and have not been immediately able to because this would require a trip to the library (probably preceded by a waiting period) or paying money to download the books from Amazon or a similar service. I imagine others are in a similar situation. These costs may well inhibit people from first exploring these ideas to begin with. This situation seems suboptimal to me. EAs value the contents of these books a lot, and their contents are free to copy on the margin. This suggests that the efficient ex post cost of accessing the content of these books should be zero. Unnecessary barriers to access could also deter potential readers and thus reduce the number of people who could be exposed to and convinced of EA ideas. There are certain ways in which it makes economic sense to give some EA organization the right to distribute these books, too. There is currently a principal-agent problem wherein the rightsholders of the books (publishers, I assume?) have only pecuniary interests in promoting and selling the books, yet we as a movement have high, nonpecuniary interest in having those books widely distributed. Our longer time horizons than publishers may also lead us to continue promoting them long after publishers normally would. I also imagine that for most publishers, profits are concentrated after release, whereas the value EA as a movement derives from the availability of these books is more constant over time. This suggests the possibility of exploiting different time preferences by buying distribution rights after the books have been on the market for a few years and therefore produced most of their expected revenue. The main downside I can foresee is cost, and I have no idea how much such rights would cost. A cheaper way to acquire such rights might be to acquire digital-only distribution rights, especially since EA is hardly in a position to actually print and ship books (though this can in principle be contracted out). A digital distribution model also overcomes the barriers for people who are primarily interested in citing the books. Note that none of this is a criticism of how the authors of the aforementioned books have chosen to publish them. I assume they have good reason for the arrangements they chose, and I know that some of them donate proceeds. This is simply an inquiry into whether such post-publication acquisition is desirable, as I have not seen this idea discussed before in EA. However, I would not be surprised if either the authors of the above books, nor would I be surprised if an EA charity considered this before and determined that it was not worthwhile. Thanks for listening. to help us out with the nonlinear library or to learn more, please visit nonlinear.org.
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: EA considerations regarding increasing political polarization, published by Alfred Dreyfus on the effective altruism forum. Write a Review American politics has become increasingly polarized in recent years. During the ongoing George Floyd protests, observers have pointed out that polarization has hit highs not yet seen in modern American history. Whether this trend of increasing polarization will continue is unclear. However, it is at least plausible that the trend is far from over, and therefore, broad picture implications are worth closer attention. In this post, I will explore my preliminary predictions under a scenario where polarization continues to increase. While I think that full-scale war -- on the level of the civil war -- is unlikely to happen in the United States, for reasons I will go into below, I find that the most relevant comparison might be the Chinese cultural revolution. Although the comparison may seem exaggerated, it is still important to explore key similarities to the Chinese cultural revolution, and what is happening in the United States. If the United States were to experience a cultural revolution-like event, it would likely affect nearly all areas of impact that effective altruists care about, and would have profound effects on our ability to produce free open-ended research on controversial issues. Given that many of the ideas that effective altruists discuss -- such as genetic enhancement, factory farming abolition, and wild animal suffering -- are controversial, it is important to understand how our movement could be undermined in the aftermath of such an event. Furthermore, conformity pressures of the type exhibited in the Chinese cultural revolution could push important threads of research, such as AI alignment research, into undesirable directions. When discussing topics as explosive as the one in this post, it is important to stay grounded in solid reasoning and evidence, and to avoid the tendency of waging the war rather than understanding the war. Understanding Julia Galef’s scout versus soldier mindset is helpful here. While in this post I am forced to engage in speculation, it is my hope that readers will judge my argument based on its merits alone, rather than assuming that I’m trying to single out or attack a particular “side” of the current political debate. Background Political polarization, as measured by political scientists, has clearly gone up in the last 20 years. It is unclear whether this recent trend is unprecedented, however. For example, some political scientists believe that current levels are higher than at any point after the civil war. Others are more skeptical. For my purposes, it is not too important for my thesis that current rates are unprecedented. As an assumption for this post, I will only analyze scenarios where the rates of polarization continue to rise, until they reach extreme levels. I believe there are currently no good reasons to think that there’s less than, say, a 10% chance that polarization will get much worse. Given even a 10% chance, the effects of extreme polarization deserve scrutiny and analysis. While effective altruists could just wait to find out whether polarization will get worse, I believe it is important to conduct this research early for two reasons. The first is that it may be possible to install norms in our communities that effectively guard against the most negative effects of polarization, and therefore, the earlier we detect these trends, the more likely we are to install such norms. Secondly, the very nature of increased polarization makes it more likely that future analysis will be affected by political pressures, and therefore early research will be more level-headed. Academics have already explored the implications of increased polarization for eroding democratic norms ...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Why scientific research is less effective in producing value than it could be: a mapping, published by C Tilli on the effective altruism forum. Contributors: David Janků, David Reinstein, Edo Arad, Georgios Kaklamanos, Sophie Schauman Introduction Research has produced, and is producing, a lot of value for society. Research also takes up a lot of resources: Global spending on R&D is almost US$ 1.7 trillion annually (approx 2 % of global GDP). This is an attempt to map challenges and inefficiencies in the research system. If we addressed these challenges and inefficiencies, research could produce a lot more value for the same amount of resources. The main takeaways of this post are: There are a lot of different issues that cause waste of resources in the research system In this post, these issues are categorized as related to (1) choice of research questions, (2) the quality of research and (3) the use of the results produced Though solutions and reform initiatives are outside the scope of this post, there does seem to be a lot of room for improvement The terms “value” and “impact” are used very broadly here: it could be lives saved, technological progress, or a better understanding of the universe. The question of what types of value or impact we should expect research to produce is a big one, and not the one I want to focus on here. Instead, I will just assume that when we dedicate resources to research we are expecting some form of valuable outcome or impact. I will attempt to map up inefficiencies in how that is produced. This post is a result of a collaboration that came out of the EA Global Reconnect conference. After the conference, a group of EA’s interested in improving science started recurring coworking sessions to discuss ideas for related projects and forum posts. I have received invaluable support and feedback from many people in this group, particularly those mentioned as contributors above. The plan is that contributors to this post and perhaps others in the group will follow up with additional forum posts on metascience that focus more on specific issues, initiatives or solutions. David Reinstein is working on a post titled “Slaying the journals”, a proposal for peer review/rating, archiving, and open science aimed at avoiding rent-extracting publishers, reducing careerist gamesmanship, and making research more effective. There are many previous initiatives that I am not aiming to cover here: just as examples, Open Philanthropy has previously published several pieces related to metascience, and Center for Open Science is working to improve scientific research with a focus on improving transparency and reproducibility. My hope is that this mapping could be of use to people who want to get an overview of issues in the research system, and to initiate a discussion about potential valuable projects or interventions. 1. Overview The causes of inefficiencies in the research system can be roughly categorized in three areas: (1) the choice and design of research questions can be flawed, (2) the research that is carried out can suffer from poor methodological quality and/or low reproducibility, and (3) even when research successfully leads to valuable results, they are not adequately incorporated into real-world solutions and decision-making. Each of these three areas can be broken up into underlying drivers, many of which fit into the broad categories of i. publishing, ii. funding and iii. culture. Figure 1 shows the three main problem categories described in this post in the structure that builds on the idea of a problem tree. The main problem that is in focus (“Research is less effective in producing value than it could be”) is placed at the top and “root causes” of that problem are written out below, with arrows indicating causal relationships. Figure 1. I...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: What would you do if you had half a million dollars?, published by Patrick on the effective altruism forum. I won the 2020/2021 $500,000 donor lottery. I’m interested in maximizing my positive impact on the long-term future, and I thought it would be helpful to elicit thoughts from the effective altruism community about how best to do this. In this post I outline the high-level options I’m considering. (I wrote more about the options that readers may be less familiar with.) If you’d like to share your opinion, please fill out this short survey. I’m most interested in whether I failed to mention any considerations that would make one option much worse or much better, and your subjective opinion about how good each option is. Donate directly to charities Previous donor-lottery winners who have written about their donation decisions have given directly to charities rather than to re-granting organizations (see here, here, and here[1]). But my impression is that I don’t have sufficient local knowledge or relevant expertise that would give me an advantage over existing longtermist grantmakers. This could change if I were to invest a lot of time into discovering donation opportunities. Having more effort put into discovery and evaluation of EA funding opportunities would be valuable. But grant evaluation that’s sufficiently well-informed would require both getting up to speed as a grant evaluator and evaluating the grants themselves, and this would be a lot of work. Long-Term Future Fund (LTFF) The Long-Term Future Fund gives out small grants (typically less than $100k), usually to individuals. Its managers also consider making larger grants to organizations, though these account for a minority of their grantmaking. In the last funding round, six people worked part-time on evaluating grant applications, with the Centre for Effective Altruism providing additional support. They say they have room for more funding: We anticipate being able to spend $3–8 million this year (up from $1.4 million spent in all of 2020). To fill our funding gap, we’ve applied for a $1–1.5 million grant from the Survival and Flourishing Fund, and we hope to receive more funding from small and large longtermist donors. [source] They plan to add more fund managers so that they can evaluate more grants. Longview Philanthropy Longview Philanthropy advises large donors (primarily those who give $1 million or more per year). Though the LTFF and Longview each give both to organizations and to individuals, Longview tends to give relatively more grants to organizations and fewer to individuals. Another difference is that the LTFF has a high volume of grant applications that it evaluates quickly, whereas Longview does fewer, more in-depth grant investigations. Finally, the LTFF publishes its grant evaluations publicly, but Longview shares information about its grant decisions with only its donors and other grantmakers. (Because of its focus on large donors, communicating this information publicly is less valuable.) If I were to give to Longview, the donation would go to their recently created general-purpose fund. This fund has some advantages over Longview’s other grantmaking: Longview can better take advantage of time-sensitive giving opportunities, such as funding that would affect hiring decisions. (Job candidates may not be willing to wait for weeks or months for funding to come through.) Grantees would have increased certainty about funding, which would help with planning. Longview currently has one full-time staff member, Kit Harris, whose primary focus is grantmaking (there are plans to hire more full-time grantmakers); four other staff members are also involved in the grantmaking process, and Longview has recently hired four part-time research assistants. Longview is in regular contact with people wo...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: A bunch of new GPI papers, published by Pablo on the effective altruism forum. Write a Review Earlier today I posted a link to Andreas Mogensen's paper on "Maximal Cluelessness". But later I realized that this was just one among several important papers published yesterday on the Global Priorities Institute website. Rather than posting separate links to each, I'm linking to all of them below (abstract included when available). Cotton-Barratt & Greaves, A bargaining-theoretic approach to moral uncertainty This paper explores a new approach to the problem of decision under relevant moral uncertainty. We treat the case of an agent making decisions in the face of moral uncertainty on the model of bargaining theory, as if the decision-making process were one of bargaining among different internal parts of the agent, with different parts committed to different moral theories. The resulting approach contrasts interestingly with the extant “maximise expected choiceworthiness” and “my favourite theory” approaches, in several key respects. In particular, it seems somewhat less prone than the MEC approach to ‘fanaticism’: allowing decisions to be dictated by a theory in which the agent has extremely low credence, if the relative stakes are high enough. Overall, however, we tentatively conclude that the MEC approach is superior to a bargaining-theoretic approach. Greaves & MacAskill, The case for strong longtermism We believe that this neglect of the very long-term future is a grave moral error. An alternative perspective is given by a burgeoning view called longtermism, on which we should be particularly concerned with ensuring that the long-run future goes well. In this article we accept this view but go further, arguing that impacts on the long run are the most important feature of our actions. More precisely, we argue for two claims. Axiological strong longtermism (AL): In a wide class of decision situations, the option that is ex ante best is contained in a fairly small subset of options whose ex ante effects on the very long-run future are best. Deontic strong longtermism (DL): In a wide class of decision situations, the option one ought, ex ante, to choose is contained in a fairly small subset of options whose ex ante effects on the very long-run future are best. MacAskill & Mogensen, The paralysis argument Given plausible assumptions about the long-run impact of our everyday actions, we show that standard non-consequentialist constraints on doing harm entail that we should try to do as little as possible in our lives. We call this the Paralysis Argument. After laying out the argument, we consider and respond to a number of objections. We then suggest what we believe is the most promising response: to accept, in practice, a highly demanding morality of beneficence with a long-term focus. Mogensen, Meaning, medicine and merit Given the inevitability of scarcity, should public institutions ration healthcare resources so as to prioritize those who contribute more to society? Intuitively, we may feel that this would be somehow inegalitarian. I argue that the egalitarian objection to prioritizing treatment on the basis of patients’ usefulness to others is best thought of as semiotic: i.e. as having to do with what this practice would mean, convey, or express about a person’s standing. I explore the implications of this conclusion when taken in conjunction with the observation that semiotic objections are generally flimsy, failing to identify anything wrong with a practice as such and having limited capacity to generalize beyond particular contexts. Mogensen, ‘The only ethical argument for positive 𝛿 ’? I consider whether a positive rate of pure intergenerational time preference is justifiable in terms of agent-relative moral reasons relating to partiality between generations, ...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: New data suggests the ‘leaders’’ priorities represent the core of the community, published by Benjamin_Todd on the effective altruism forum. Write a Review There have been several surveys of attendees of what was previously called the ‘EA Leaders Forum’ about what they believe the community’s cause priorities should be (2017, 2018, 2019). The relevance of these results have been criticised each year for not representing the views of the wider community (e.g. in 2019). You can see some hypotheses about why there might be differences in views between the Leaders Forum group and others here. In particular, the former group is selected to be more into longtermism than the average, potentially skewing the results. Similarly, CEA and 80,000 Hours have been criticised for not having their priorities line up with the community (e.g. this post summarises criticisms about representativeness, and 80k was recently criticised here). Critics of the Leaders Forum survey often appeal to the EA Survey as a reflection of the community’s priorities. This is a much broader survey with about 2,500 respondents, and when we compare the ideal portfolio chosen in the Leaders Forum Survey to the top cause preferences of the EA Survey respondents (as explained in more depth later), we see significant differences: The problem with this is the EA Survey is open to anyone to take, and without knowing more about who’s taking it, it’s unclear why this should be used to set community priorities. Fortunately, the 2019 EA Survey lets us make progress on this question. It asked many more questions about people’s level of engagement, which means we can further subdivide the responses. In this post, I do a quick analysis of these new results to show that based on this data, the Leaders Forum survey priorities seem to reflect the most engaged half of the community – around 1,000-2,000 people – pretty well. This suggests the issue we actually face is not a difference between the leaders and the core of the community, but rather between the core and those who are new or moderately engaged. The data In the 2019 EA Survey, one question asked about how engaged people feel they are on a scale of 1 to 5, where 5 was defined as “I am heavily involved in the effective altruism community, perhaps helping to lead an EA group or working at an EA-aligned organization. I make heavy use of the principles of effective altruism when I make decisions about my career or charitable donations.”[1] About 450 out of 2,100 respondents to this question reported a “5”. My estimate is that only about 40% of engaged EAs filled out the survey in 2019,[2] which would suggest there are around ~1,000 people with this level of engagement, so it’s a much wider group than the ~30 or so people at the leaders forum. If we look at what different members of this group said they think is the ‘top cause’, and compare that to the ‘ideal portfolio’ chosen by the mean attendee of the Leaders Forum,[3] (making some assumptions about how the categories line up) we find: As you can see, these line up pretty well, except that the EA Survey group actually has a greater collective preference for ‘meta’ cause prioritisation work. (Note that ‘other near term’ wasn’t offered as a category on the leaders forum survey so may be undercounted – I hope this will be fixed this year.) Using broader buckets, among the leaders survey we get 54% longtermist, 20% meta, and 24% near term and 2% other. Among the survey respondents we find 48% longtermist, 28% meta, and 24% near term. (The 2020 Leaders Forum results are also not published, but at a glance they line up even better, with more agreement on AI and other near term causes.) I should be very clear: these questions are asking about different things. The Leaders Forum one is about the ideal portfolio of resources...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: Asking for advice, published by Michelle_Hutchinson on the effective altruism forum. Write a Review Recently I’ve been working on team strategy, and have been finding it really useful to get advice and input not just from the rest of 80,000 Hours, but also from others. I find it challenging to get advice on complex strategic questions from people with little context of the work I’m doing in a way which is minimally time consuming for them. I think it’s something I’ve gotten better at over the years, but I don’t remember having read much about it. Since it’s so useful to get feedback on projects, I wanted to write down some of the things which I try to do when soliciting feedback, and ask others to share what’s worked for them. Why think about this? How you go about asking for advice on a project can make a huge difference to the people you’re asking. The experience of giving input can vary from costly and annoying to incredibly rewarding. A lot of that depends on factors like how much someone feels their time is being valued, and there are some straightforward ways to affect that. I find putting time and thought into getting feedback can be frustrating, because it feels so far from the object level of getting useful work done. In my recent case (how to structure 80,000 Hours advising), the project itself is already one step removed from actually talking to people about their careers. And then thinking about how to get feedback on the plans feels even further from the part where I’m actually helping people! But I find it useful to remember that not only will it make it a nicer experience for the person whose time I’m asking for, it’s also going to make it more viable for them to give advice both this time and in future. One of the things I love most about the effective altruism community is how collaborative it is. People support each other not just within their specific organisations, but across the whole community. I really appreciate the feeling that we’re all part of a global team. I want to assist that by allowing people to give advice in a way that’s quick and easy (and pleasant!) for them. Specifics Before seeking feedback Think carefully about who I’m reaching out to and why: There are a lot of smart, knowledgeable people out there. So sometimes it feels tempting to ask lots of people for advice at once. But that’s typically a worse use of their time than asking the one or two best placed people. I often find it hard to explain what I’m doing and what advice I’m after to people with less context, so their comments are less useful yet it takes them more time and effort to give them (since they have to put in more time to understand the project). It’s also useful to convey to the person why they’re the one being asked for advice. For example, maybe they’ve done similarly risky projects in the past and you want to know how they mitigated the risk - if you tell them that they’ll know where to focus their advice, so you’ll hear more about the specific thing you wanted. It will also help them feel you value their time. Figure out what I most need help on: What are the key assumptions I’m making I most want to check with others? What are my biggest uncertainties with the project, or the parts where I most think people might disagree with me? I have a tendency to want to check everything, and to ask for advice before I’ve gotten clear in my own mind what the crucial uncertainties are. But that makes it very difficult for people to give constructive comments. It also means when they do comment, sometimes the comments are about a part of the project which isn’t that important anyway, whereas maybe a crucial part ends up overlooked because they spent their time on the other part. Write a concise document summarising my key uncertainties and what I’m looking for feedback ...
welcome to the nonlinear library, where we use text-to-speech software to convert the best writing from the rationalist and ea communities into audio. this is: 5,000 people have pledged to give at least 10% of their lifetime incomes to effective charities, published by lukefreeman on the effective altruism forum. Write a Review This is a linkpost for/ Today we reached a major milestone. More than 5,000 people have pledged to give at least ten percent of their lifetime earnings to effective charities . [Video: A message to our 5,000 members] Since its founding in December 2009, Giving What We Can has attracted members from 87 countries. Together, we have donated at least $195 million to highly effective charities across many different cause areas. This money has a tangible impact on the lives of many individuals now, and will help many others in the future. Thank you for your generosity, your support, and your commitment to helping others. To celebrate, our members are hosting events all around the world (in-person and virtually) for you to meet other people who have made effective giving a meaningful part of their lives. We encourage you to attend one of these events! Several of our members have submitted some words to share with our community – we’ve collated them all below for you to watch and read. If you’d like to share something please do so in the comments or email us at community@givingwhatwecan.org. Read our official press release about this milestone Video Quotes Toby Ord (Co-founder, researcher at Future of Humanity Institute) “I’m so excited that Giving What We Can is over 200 times larger than when we launched 10 years ago. It’s overwhelming to be part of such a large and friendly community of people, all striving to make the world a much better place.” Will MacAskill (Co-founder, researcher at Forethought Foundation) “Getting to 5,000 members absolutely blows my mind. That’s a full 217 times as many members as we had at launch 11 years ago. I remember when I first took the pledge, it felt really quite scary. I was a graduate student at the time and I had a scholarship for my accommodation paid for but I was living on about £4,500 per year and I was trying to give £900 of that away over the year. It was tough. I remember I refused to get a haircut because it seemed like an unnecessary expense... One of the things I worried about back then was whether I’d be a social outcast, always having to explain to people why I’ve chosen this weird life for myself. The answer turned out to be “no”, quite the opposite in fact. The pledge functioned like this bat signal, attracting people all around the world with a similar set of values and it’s been such a joy to see so many people come together and make a commitment to use a significant proportion of their income for the common good. So thank you, for taking the pledge and for showing what it means to take giving seriously.” Julia Wise (Member #179 and former President of GWWC, community health at CEA) "When I first learned about Giving What We Can, I remember feeling so relieved that there were all these other people out there who were not just thinking about what we can do for others, but were taking concrete action on that." Derek Ball (Member #57, Lecturer in the philosophy departments at the University of St Andrews) "I first read about Giving What We Can in a newspaper article almost 10 years ago. At the time, I strongly felt that I needed to do more to help others, but I wasn’t sure what to do. Giving What We Can provided guidance and inspiration that I needed — an easy-to-follow recipe for doing some good. I can honestly say that it has changed my life. Congratulations on 5000 members!" Michelle Hutchinson (Member #153 and former ED of GWWC, Head of Advising at 80,000 Hours) "It’s been really incredible watching GWWC grow from a few members early on to a 5,000 strong community. It’s really incredible how much people in our community donate and how much they think ab...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: A full syllabus on longtermism, published by jtm on the effective altruism forum. What this is A syllabus of readings relating to ‘longtermist’ philosophy. I’m posting it here because I hope it might inform syllabi for university courses, reading groups or EA fellowships, and because I would love to see people share suggestions for other works to include. As this list was designed to include roughly a semester’s worth of material it is, needless to say, not an exhaustive resource. Indeed, each of the dozen topics could have a syllabus of their own and I am not myself very familiar with the relevant literature – suggestions are very welcome! Some background Like many other student groups, my previous university EA community would often invite faculty speakers to join dinner discussions and fellowship meetings. In our group, the ethics professor Shelly Kagan has been generous enough to regularly attend group discussions. While he initially joined for conversations on Peter Singer’s arguments on charity, we started a few years ago to instead focus on questions regarding intergenerational ethics. After a few very successful group discussions, I suggested that Kagan could teach a course on the topic and, a few years later, that course is now being taught as an undergraduate seminar. While Kagan was preparing the course, I offered to make a draft syllabus for it, and although I believe Kagan’s actual syllabus looks quite different from the list I produced, I figured that it might nevertheless be worthwhile to share here on the forum. I should stress that this syllabus is independent of the course and professor and that any errors thus are entirely my own. Why I think this might be valuable I think we got quite lucky to find a university professor who was sufficiently interested in – and sympathetic to – longtermism that they would teach a course on it, and I’m not sure that this is something that could happen at every school with an EA group. But conditional on finding such a professor, I hope this syllabus could increase the likelihood of them teaching a course like this, which seems really valuable. Of course, I also hope that this could prove useful for reading groups, fellowships, and the like! Crucially, I do not see this as a resource for “convincing people that longtermism is true.” (Edit: For some compelling arguments as to why our community should be careful about seeking 'value-alignment', see this great post by CarlaZoeC.) Rather, I hope that the readings can inspire and inform robust conversations about the strengths and weaknesses of longtermism – a philosophy that, in the scheme of things, remains very new and unexplored. Indeed, several of the readings included here pose serious challenges to various aspects of longtermism that are worth carefully considering. Some considerations that went into making this syllabus Intergenerational ethics ≠ longtermism The course this syllabus was made for is called “Ethics and the Future,” which underscores the fact that, as I see it, ‘intergenerational ethics’ (a philosophical topic or field) is not equivalent to ‘longtermism’ (a philosophical position and research agenda within that field). So while longtermism is heavily featured, it’s not the only thing you’ll find on the syllabus. Formalism and accessibility In addition to the usual dose of jargon, many of the papers on this subject – especially on the topics of discounting and population ethics – include a lot of mathematical expressions that may pose a barrier to some readers. I tried to keep accessibility in mind when making the syllabus and excluded a few potential readings on those grounds, but I still suspect that some of the readings might be challenging to many students without a lot of formal training (myself included). Ultimately, however, this is just a dra...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Strategic considerations for upcoming EU farmed animal legislation, published by Neil_Dullaghan on the effective altruism forum. Preamble The European Commission is planning to revise and expand the scope of European Union (EU) animal protection policies with new legislative proposals in late 2023, likely followed by another ~12-24 months of negotiations before being passed into law. The effective animal advocacy movement should attempt to have the most impact during the policy formation stage and to prioritise which countries need to be targeted to ensure proposals are not significantly weakened before passing into law. I’ve recently written two reports to contribute to strategic discussions, here and here. The two reports total more than 57,000 words. Below is an overview of the project, the main recommendations, and a summary of the main arguments (or see PDF version here). For readers unfamiliar with the EU it will help to have first read the introductory post in Rethink Priorities’ EU animal policy series, read Lewis Bollard’s Open Philanthropy newsletters on EU topics (2021,2020, 2017) or watched these time stamped videos on decision-making structures in the EU (CNBC 2019, Kurzgesagt 2019). Who is this for & what might they gain from reading this research? Farmed animal funders: Information on what countries one would want to see progress in to have the best chance of successful EU legislation. European animal advocacy organisations: Ideas on how your work can fit into a larger EU strategy, legislative texts to model your political asks on, and suggestions on why joining associations, like Eurogroup for Animals or the Open Wing Alliance, could improve your EU impact. What did I do? I collected and synthesised historical case studies of six animal welfare issues (battery cages, tail docking, tethers, veal crates, sow stalls and broiler stocking density) addressed by seven EU species-specific directives[1] and progress so far towards fish welfare standards. I also offer a brief overview of animal welfare issues not yet legislated on. I summarised evidence from the wider political science literature on the main factors in EU decision-making, especially those highlighted by the case studies. This was to counter some of the problems of having only deeply researched cases of successful farmed animal reform. I also outline some strategic considerations for EU legislation on cage-free hens on fish welfare. I compiled information in Google Sheets on previous legislation, country-level statistics such as the percentage of cage-free hens, a list of animal welfare reports from the agency of the EU that provides independent scientific advice, a timeline of when countries will hold the Rotating Council Presidency, and some data from Votewatch.eu on how countries have voted on key policy areas. I hope this information can feed into an EU strategy. I created probability distributions of what share of egg laying hens will be cage-free by 2025, and partnered with an EU academic to generate simulations of countries voting on a hypothetical EU cage-free policy for egg-laying hens. I also posted a number of questions on the forecasting platform Metaculus as an example of one tool animal advocates can use for multi-year planning. Why is this a worthwhile area to pursue? Government/policy/lobbying experience is seen as a talent bottleneck in effective animal advocacy (Harris 2021) and legislative/policy change has been less of a focus within the space relative to public opinion and industry change (Animal Charity Evaluators 2018). Relative to corporate commitments, legislative changes are likely to be much more difficult to reverse and may have higher levels of implementation due to enforcement mechanisms (though see my report on enforcement for caveats). As noted above, the European...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. this is: Help me find the crux between EA/XR and Progress Studies, published by jasoncrawford on the effective altruism forum. I'm trying to get to the crux of the differences between the progress studies (PS) and the EA / existential risk (XR) communities. I'd love input from you all on my questions below. The road trip metaphor Let me set up a metaphor to frame the issue: Picture all of humanity in a car, traveling down the highway of progress. Both PS and EA/XR agree that the trip is good, and that as long as we don't crash, faster would be better. But: XR thinks that the car is out of control and that we need a better grip on the steering wheel. We should not accelerate until we can steer better, and maybe we should even slow down in order to avoid crashing. PS thinks we're already slowing down, and so wants to put significant attention into re-accelerating. Sure, we probably need better steering too, but that's secondary. (See also @Max_Daniel's recent post) My questions Here are some things I don't really understand about the XR position (granted that I haven't read the literature on it extensively yet, but I have read a number of the foundational papers). (Edit for clarity: these questions are not proposed as cruxes. They are just questions I am unclear on, related to my attempt to find the crux) How does XR weigh costs and benefits? Is there any cost that is too high to pay, for any level of XR reduction? Are they willing to significantly increase global catastrophic risk—one notch down from XR in Bostrom's hierarchy—in order to decrease XR? I do get that impression. They seem to talk about any catastrophe less than full human extinction as, well, not that big a deal. For instance, suppose that if we accelerate progress, we can end poverty (by whatever standard) one century earlier than otherwise. In that case, failing to do so, in itself, should be considered a global catastrophic risk, or close to it. If you're willing to accept GCR in order to slightly reduce XR, then OK—but it feels to me that you've fallen for a Pascal's Mugging. Eliezer has specifically said that he doesn't accept Pascal's Mugging arguments in the x-risk context, and Holden Karnofsky has indicated the same. The only counterarguments I've seen conclude “so AI safety (or other specific x-risk) is still a worthy cause”—which I'm fine with. I don't see how you get to “so we shouldn't try to speed up technological progress.” Does XR consider tech progress default-good or default-bad? My take is that tech progress is default good, but we should be watchful for bad consequences and address specific risks. I think it makes sense to pursue specific projects that might increase AI safety, gene safety, etc. I even think there are times when it makes sense to put a short-term moratorium on progress in an area in order to work out some safety issues—this has been done once or twice already in gene safety. When I talk to XR folks, I sometimes get the impression that they want to flip it around, and consider all tech progress to be bad unless we can make an XR-based case that it should go forward. That takes me back to point (1). What would moral/social progress actually look like? This idea that it's more important to make progress in non-tech areas: epistemics, morality, coordination, insight, governance, whatever. I actually sort of agree with that, but I'm not sure at all that what I have in mind there corresponds to what EA/XR folks are thinking. Maybe this has been written up somewhere, and I haven't found it yet? Without understanding this, it comes across as if tech progress is on indefinite hold until we somehow become better people and thus have sufficiently reduced XR—although it's unclear how we could ever reduce it enough, because of (1). What does XR think about the large numbers of people who do...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Funds are available to fund non-EA-branded groups, published by Buck, ClaireZabel on the effective altruism forum. This post was written by Buck and Claire Zabel but it’s written in Buck’s voice, and “I” here refers to Buck, because it’s about grantmaking that he might do. (Claire contributed in her personal capacity, not as an Open Phil grantmaker). In addition to accepting applications for EA groups in some locations as part of my EAIF grantmaking, I am interested in evaluating applications from people who run groups (in-person or online, full-time or part-time) on a variety of related topics, including: Reading groups, eg for The Precipice or Scout Mindset Groups at companies, online-only groups, and other groups not based in particular geographic locations or universities. Groups discussing blogs or forums that are popular with EAs, such as Slate Star Codex / Astral Codex Ten or LessWrong. Longtermist-only, AI-centric or biosafety-centric groups, animal welfare groups, or other groups that address only a single EA cause area. (I might refer these applications to the Long-Term Future Fund or the Animal Welfare Fund as appropriate; both of these funds have confirmed to me that they’re interested in making grants of this type.) I also welcome applications from people who do or want to do work for existing groups, or group organizers who want funding to hire someone else to work with them. Eg: Maintaining or overhauling group websites, if you think this is worthwhile for your particular group Working 10hrs/week on a student group Running group mailing lists In cases where the project/expense isn’t a good fit for the EA Funds, but I think it’s worth supporting, I am likely able to offer alternative sources of funds. I might stop doing this if someone appears who’s able to commit more time and thought to funding and supporting these kinds of groups, but for the time being I want to offer folks who want to work on these kinds of things a chance to request support. I think that people who put serious time into creating high-quality groups deserve compensation for the time they put in, so please don’t let thoughts like “I only work on this for 10 hours a week” or “I’m happy to do this in a volunteer capacity” discourage you from applying. If you’re unsure if something is a reasonable fit, feel free to email me (bshlegeris@gmail.com) and ask before applying. Depending on your cost of living, ask for a rate of $20-50 per hour (this includes employer's payroll tax and would correspond to ~$15-40/h gross salary). The EAIF application form is here; you should also feel free to email me any questions you have about this. thanks for listening. to help us out with the nonlinear library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: [Creative Writing Contest] The Reset Button, published by Joshua Ingle on the effective altruism forum. You never thought you’d use the reset button until the day you did. The button, an old family heirloom gifted by your parents on your eighteenth birthday, sat at the bottom of a box in your closet for most of your twenties. While you were laser-focused on maxing out your college grades and interning at company after company until you finally landed a good job, then sating a bit of your lifelong wanderlust with well-deserved world travels, the reset button lingered, half forgotten. Yes, you made youthful mistakes. From time to time, you considered digging the button out and using it. But whenever the temptation struck, your reasoning always came back to this: What could possibly be important enough to justify the button’s use? Your parents had stressed it could only be used once, and no bungled speech or embarrassing date or wasted funds ever seemed worth it. Their parents and even their grandparents had stewarded the button so they could pass it down the family line, so how astonishingly selfish would you be to use it on yourself? No, you’ll pass it down to your kids, and they to their kids, until it can be used for something truly important. Or so you tell yourself. Later in life, you’re comfortable enough that you haven’t thought about the reset button in years. You’re mid-career, in a secure position at a prestigious company, with a new house and only a little debt. Due to some guest posts you’ve written on a popular blog, your name is known and respected in your field. Once or twice each year, you and your partner hop over to a resort town for a week of romance and adventure. You donate a bit to some favorite charities as well. You have the usual worries, but overall, life is good. At breakfast today, your partner reminds you to make a digital copy of the kids’ birth certificates so you can submit their passport applications, and when you open your small safe to grab the certificates, you notice the reset button in the far corner, encased in its simple steel container beneath some insurance documents. You’d forgotten you moved it there when you cleaned out your college boxes last winter. How does that damn button work? You’ve wondered this before, but you never had the resources to figure it out. If Frieda and Colin in the R&D Department open it up and look inside, you bet they’ll be able to tell you, and maybe even get some inspiration for company products. On a whim, you pocket the reset button and take it to work. You spend an hour at the gym, then curse a traffic jam on the freeway that’ll make you twenty minutes late. Worries gnaw at you while you wait. Are your kids getting a good education? Will the deal you’re negotiating at work go through? Can you find enough time to rest and fend off exhaustion? You try to distract yourself with the radio, but half the channels have hosts chattering about world news. Some new crisis in international politics. Such intrigue used to interest you, but you’re not in the mood for it now, so you keep switching channels until you find calming music. Your boss passes you in the hallway and asks if you’ve finished writing the big contract yet. You tell her you’ll get it to her by noon. You exchange pointers with Malik on your workout routines over coffee in the break room. He mentions he heard a rumor you’re being eyed for a position that just opened in upper-level management but says you didn’t hear it from him. Beaming, you walk to your office, open your desktop, and notice you only have five minutes until today’s operations meeting. So you stride past cubicles to Kendal’s desk and ask her to generate six of the relevant reports. You check the time as you wait for them to print, then offer her generous thanks as she hands t...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: We're Redwood Research, we do applied alignment research, AMA, published by Buck on the effective altruism forum. Redwood Research is a longtermist organization working on AI alignment based in Berkeley, California. We're going to do an AMA this week; we'll answer questions mostly on Wednesday and Thursday this week (6th and 7th of October). I expect to answer a bunch of questions myself; Nate Thomas and Bill Zito and perhaps other people will also be answering questions. Here's an edited excerpt from this doc that describes our basic setup, plan, and goals. Redwood Research is a longtermist research lab focusing on applied AI alignment. We’re led by Nate Thomas (CEO), Buck Shlegeris (CTO), and Bill Zito (COO/software engineer); our board is Nate, Paul Christiano and Holden Karnofsky. We currently have ten people on staff. Our goal is to grow into a lab that does lots of alignment work that we think is particularly valuable and wouldn’t have happened elsewhere. Our current approach to alignment research: We’re generally focused on prosaic alignment approaches. We expect to mostly produce value by doing applied alignment research. I think of applied alignment research as research that takes ideas for how to align systems, such as amplification or transparency, and then tries to figure out how to make them work out in practice. I expect that this kind of practical research will be a big part of making alignment succeed. See this post for a bit more about how I think about the distinction between theoretical and applied alignment work. We are interested in thinking about our research from an explicit perspective of wanting to align superhuman systems. When choosing between projects, we’ll be thinking about questions like “to what extent is this class of techniques fundamentally limited? Is this class of techniques likely to be a useful tool to have in our toolkit when we’re trying to align highly capable systems, or is it a dead end?” I expect us to be quite interested in doing research of the form “fix alignment problems in current models” because it seems generally healthy to engage with concrete problems, but we’ll want to carefully think through exactly which problems along these lines are worth working on and which techniques we want to improve by solving them. We're hiring for research, engineering, and an office operations manager. You can see our website here. Other things we've written that might be interesting: A description of our current project Some docs/posts that describe aspects of how I'm thinking about the alignment problem at the moment: The theory-practice gap. The alignment problem in different capability regimes. We're up for answering questions about anything people are interested in. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Burnout: What is it and how to Treat it. , published by Elizabeth on theeffective altruism forum. Introduction Lately there has been considerable concern among effective altruists about burnout. People are worried about themselves or others being less productive or just plain miserable. The goal of this report is to bring people up to speed on the scientific research about burnout and, when possible, make recommendations about alleviation and prevention. Unfortunately, the scientific literature has few specific recommendations to make, so I would like to use this as an opportunity to foster discussion about what has worked and not worked for people personally. Look for those comments below. The goal is for this to be useful to individual workers in treating their own burnout, and to organizational decision makers in preventing burnout organization-wide. [Studies are actually mixed on if burnout reduces productivity, with some even showing burnout associated with higher productivity. My interpretation here is that high standards for yourself lead to both high performance and burnout.] Tl;dr Social support == Good. Sleep == Good. Ambiguity == Bad. Vacations == Meh. What is Burnout? The official definition of burnout is “physical or mental collapse caused by overwork or stress”. That kind of implies that a person can’t work when burnt out, but that’s not my experience- ceasing work when you’re burnt out is a privilege. But working when you’re burnt out is miserable, and makes burnout worse, so even if circumstances improve you’re in a hole. Burnout was originally conceived of in the caring professions (e.g. nursing and social work), which are emotionally demanding in several different ways. This has by and large not been born out scientifically; other professions burn out just as hard, with perhaps slightly different patterns on the Maslach Burnout Inventory, the most popular measure of burnout. Based mostly on personal observation I strongly suspect there are multiple types of burnout, which can co-occur, and which current instruments are not sensitive enough to differentiate. Of particular interest to this crowd is the difference between burnout caused by hating your job or not having the resources it demands, vs. loving your job too much and being sucked into giving more than you should. I suspect that the latter is more heavily represented among effective altruists than in the literature. The Maslach Burnout Inventory (used in >90% of studies) divides burnout into three parts: exhaustion, cynicism, and (perceived) personal efficacy. The MBI has been shown to be internally consistent and cross-culturally valid. On the other hand, it has mixed results in distinguishing burnout from traditional depression or anxiety, and I could find no studies demonstrating any predictive value of the inventory — the closest was two studies showing MBI predicted an increase in thoughts of suicide and dropping out of school among med students. In contrast, the Copenhagen Burnout Inventory has one whole study showing a that a high score predicts future sickness absence, sleep problems, and use of painkillers. The CBI measures only exhaustion, and separately tracks personal burnout, work burnout, and client burnout. I would have liked to give preference to studies using the CBI because it has more empirical validation, but there simply weren’t enough to rely on, so most of the studies referred to in this post use the MBI. By far the most popular model of burnout in the literature is “Job Demands - Resources”, or “JD-R”, which posits that high job demands lead to exhaustion, and low resources lead to cynicism and feelings of low personal efficacy. “Demands” and “Resources” are defined fairly broadly here. Demands includes things like “coping with conflicting goals” and resources includes ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: What to do with people?, published by Jan_Kulveit> on the effective altruism forum. I would like to offer one possible answer to the ongoing discussion in the effective altruism community, centered around the question about scaleable use of the people (“Task Y”). The following part of the 80000h podcast with Nick Beckstead is a succinct introduction of the problem (as emphasized by alxjrl) Nick Beckstead: (. ) I guess, the way I see it right now is this community doesn’t have currently a scalable use of a lot of people. There’s some groups that have found efficient scalable uses of a lot of people, and they’re using them in different ways. For example, if you look at something like Teach for America, they identified an area where, “Man, we could really use tons and tons of talented people. We’ll train them up in a specific problem, improving the US education system. Then, we’ll get tons of them to do that. Various of them will keep working on that. Some of them will understand the problems the US education system faces, and fix some of its policy aspects.” That’s very much a scalable use of people. It’s a very clear instruction, and a way that there’s an obvious role for everyone. I think, the Effective Altruist Community doesn’t have a scalable use of a lot of its highest value . There’s not really a scalable way to accomplish a lot of these highest valued objectives that’s standardised like that. The closest thing we have to that right now is you can earn to give and you can donate to any of the causes that are most favored by the Effective Altruist Community. I would feel like the mass movement version of it would be more compelling if we’d have in mind a really efficient and valuable scalable use of people, which I think is something we’ve figured out less. I guess what I would say is right now, I think we should figure out how to productively use all of the people who are interested in doing as much good as they can, and focus on filling a lot of higher value roles that we can think of that aren’t always so standardised or something. We don’t need 2000 people to be working on AI strategy, or should be working on technical AI safety exactly. I would focus more on figuring out how we can best use the people that we have right now. Relevant posts and discussions on the topic are under several posts on the forum: Can the EA community copy Teach for America? (Looking for Task Y) After one year of applying for EA jobs: It is really, really hard to get hired by an EA organisation Hierarchical networked structure The answer I’d like to offer is abstract, but general and scalable. The answer is: “build a hierarchical networked structure”, for lack of better name. It is best understood as a mild shift of attitude. A concept on a similar level of generality as “prioritization” or “crucial considerations”. The hierarchical structure can be in physical space, functional space or research space. An example of a hierarchy in physical space could be the structure of local effective altruism groups: it is hard to coordinate an unstructured group of 10 thousands people. It is less hard, but still difficult to coordinate a structure of 200 “local groups” with widely different sizes, cultures and memberships. The optimal solution likely is to coordinate something like 5-25 “regional” coordinators/ hub leaders, who then coordinate with the local groups. The underlying theoretical reasons for such a structure are simple considerations like “network distance” or “bandwidth constraints”. A hierarchy in functional space could be for example a hierarchy of organizations and projects providing people career advice. It is difficult to give personalized career advice to tens of thousands of people as a small and lean organization. Scalable hierarchical version of career advice may look like...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Concrete Ways to Reduce Risks of Value Drift and Lifestyle Drift, published by Darius_M on the effective altruism forum. Write a Review This post is motivated by Joey’s post on ‘Empirical data on value drift’ and some of the comments. Introduction “And Harry remembered what Professor Quirrell had said beneath the starlight: Sometimes, when this flawed world seems unusually hateful, I wonder whether there might be some other place, far away, where I should have been. And Harry couldn’t understand Professor Quirrell’s words, it might have been an alien that had spoken, (...) something built along such different lines from Harry that his brain couldn’t be forced to operate in that mode. You couldn’t leave your home planet while it still contained a place like Azkaban. You had to stay and fight.” Harry Potter and the Methods of Rationality I use the terms value drift and lifestyle drift in a broad sense to mean internal or external changes leading you to lose most of the expected altruistic value of your life. Value drift is internal; it describes changes to your value system or motivation. Lifestyle drift is external; the term captures changes in your life circumstances leading to difficulties implementing your values. Internally, value drift could occur by ceasing to see helping others as one of your life’s priorities (losing the ‘A’ in EA), or loosing the motivation to work on the highest-priority cause areas or interventions (losing the ‘E’ in EA). Externally, lifestyle drift could occur (as described in Joey's post) by giving up a substantial fraction of your effectively altruistic resources for non-effectively altruistic purposes, thus reducing your capacity to do good. Concretely, this could involve deciding to spend a lot of money on buying a (larger) house, having a (fancier) wedding, traveling around the world (more frequently or expensively), etc. Of course, changing your cause area or intervention to something that is equally or more effective within the EA framework does not count as value drift. Note that even if your future self were to decide to leave the EA community, as long as you still see ‘helping others effectively’ as one of your top-priorities in life it might not constitute value drift. You don’t need to call yourself an EA to have a large impact. But I am convinced that EA as a community helps many members uphold their motivation for doing the most good. Why this is important for altruists There is a difference between the potential altruistic value and the expected altruistic value you may achieve over the course of your lifetime. Risks of value or lifestyle drift may make you lose most of the expected altruistic value of your life, thus preventing you from realizing a large fraction of your potential altruistic value. Most of the potential altruistic value of EAs lies in the medium- to long-term, when more and more people in the community take up highly effective career paths and build their professional expertise to reach their ‘peak productivity’ (likely in their 40s). However, if value and lifestyle drift are common, most of an EA's expected altruistic value lies in the short- to medium-term; the reason being, that many of the people currently active in the community will cease to be interested in doing the most good long before they reach their peak productivity. This is why, speaking for myself, losing my altruistic motivation or giving up a large fraction of my altruistic resources in the future would equal a small moral tragedy to my present self. I think that as EAs we can reasonably have a preference for our future selves not to abandon our fundamental commitment to altruism or effectiveness. What you can do to reduce risks of value drift and lifestyle drift: Caveat: the following suggestions are all very tentative and largely based o...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: EA Hotel Fundraiser 8: Life at the EA Hotel, and Testimonials, published by CEEALAR on the effective altruism forum. The EA Hotel has been open for 20 months. Here we showcase, in 100 pictures and 1000 words, what life is like in and around the hotel. We then follow with some testimonials. The aim is to give people more of an idea of what the project is like on a human level. This post is part of our fundraiser series, and complements other posts focused on outputs and the case for the project. [We are all here, on the Pale Blue Dot. Living in interesting times.] The EA Hotel (often under cloud cover) is situated in the UK. In Blackpool. Near the beach (this picture was taken from the top of Blackpool Tower). The building - the Athena Hotel - is a guest house that dates back to c.1850. It has a mixture of single rooms and double rooms, 12 of which have en suites. We also have a couple of dorm rooms, which are used for short-term visitors and events. Obviously the main activity that occupies our guests is working on their EA projects. Checking in with the Community & Projects Manager to discuss progress. Co-working in the bar is popular. Sometimes even late into the night. Although for most, the workday ends at 19:00, when dinner is served. Our nightly communal meals give people the chance to get to know each other better, and of course, discuss the many philosophical issues relating to EA! (Derek eating his favourite - vegan mac and cheese) We do of course talk about other things too (like AI Safety - pictured here: participants of TAISU). Here are some examples of dinners: curry and rice is popular. And rarer but well enjoyed: le vegan Big Mac. Sometimes we put on special meals - like our Christmas dinner last month (lots of vegan pies! And crackers - the Brits amongst us didn’t realise how much of a localised tradition this is). Or celebrating a birthday. For breakfasts, lunches, and snacks, we have a self-service buffet. A regular after-dinner activity is talks (here: Markus talking about Hormesis). Lately we have had weekly Lightning Talk sessions, and “Theme of the Week”, where a pre-shared article is discussed. We have also held a few events, which have been popular, with many outside visitors attending, packing out the place. Group photo of TAISU participants. When not working, exercise is a popular activity. We used to have gym sessions in the bar, but most enthusiasts ended up getting memberships at the gym round the corner. A popular weekend activity is games, ranging from the simple.. ..to the very complex (Terraforming Mars); and the traditional (Texas Hold ‘Em Poker).. ..to the not so traditional (Bughouse Chess). Social activities also sometimes involve leaving the hotel. A walk on the beach, or a pint in a beer garden. Playing pool, singing karaoke, or raving it up in Walkabout. Walking back along the beach. The main area in town for nightlife (on a quiet night). Blackpool is famous for its tower. It also has 3 piers. This is the North Pier (opened 1863, when people paid 2d to walk over the sea). This is the Central Pier (level with the hotel). Despite a recent decline in visitor numbers, Blackpool is still a popular seaside resort in the summer. For the tourist on a budget, there are free events like the St Annes International Kite Festival down the coast, or the World Fireworks Championship. For the not-quite-so-budget-conscious EA, for a few pounds you can take a ride along the coast on an old tram, or have a go on the penny arcades. Wandering through town you can see some interesting street architecture. The Promenade, early in the holiday season. A street with colourful guest houses near us. Our street, with its illuminations on. Tower and backstreets from the window of room 16. The beach is 3km long and up to 500m wide at low tide (here: a sunny ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Ask Rethink Priorities Anything (AMA), published by Marcus_A_Davis on the effective altruism forum. Hi, all. We're the staff at Rethink Priorities and we would like you to Ask Us Anything! We'll be answering all questions starting Tuesday, 15 December. About the Org Rethink Priorities is an EA research organization focused on influencing funders and key decision-makers to improve decisions within EA and EA-aligned organizations. You might know of our work on quantifying the amount of farmed vertebrates and invertebrates, interspecies comparisons of moral weight, ballot initiatives as a tool for EAs, the risk of nuclear winter, or running the EA Survey, among other projects. You can see all our work to date here and some of our ongoing projects here. Over the next few years we plan to expand our work in animal welfare, relaunch our work in longtermism, and continue our work in movement building, and much more. About the Team Leadership Marcus A. Davis - Co-Executive Director Marcus is a co-founder and co-Executive Director at Rethink Priorities, where he leads research and strategy. He's also a co-founder of Charity Entrepreneurship and Charity Science Health, where he previously systematically analyzed global poverty interventions, helped manage partnerships, and implemented the technical aspects of the project. Peter Hurford - Co-Executive Director Peter is the other co-founder and co-Executive Director of Rethink Priorities. Prior to running Rethink Priorities, he was a data scientist in industry for five years at DataRobot, Avant, Clearcover, and other companies. He also has a Triple Master Rank on Kaggle (an international data science competition) and have achieved top 1% performance in five different Kaggle competitions. He was a previous long-time board member at Animal Charity Evaluators and he continues to serve on the board at Charity Science. Research David Moss - Principal Research Manager David Moss is the Principal Research Manager at Rethink Priorities. He previously worked for Charity Science and has worked on the EA Survey for several years. David studied Philosophy at Cambridge and is an academic researcher of moral psychology. Kim Cuddington - Distinguished Researcher Kim Cuddington is a Distinguished Researcher at Rethink Priorities and is an Associate Professor at the University of Waterloo. She has a PhD in Zoology, a Masters in Biology, and a Masters in Philosophy. She also has a background in ecology and mathematical modeling. David Reinstein - Distinguished Researcher Senior lecturer in economics at the University of Exeter. His research has covered a number of topics including charitable giving and social influences on giving. He originally received his PhD at the University of California, Berkeley under Emmanuel Saez. Jason Schukraft - Senior Research Manager Jason is a Senior Research Manager at Rethink Priorities. Before joining the RP team, Jason earned his doctorate in philosophy from the University of Texas at Austin. Jason specializes in questions at the intersection of epistemology and applied ethics. David Rhys Bernard - Senior Staff Researcher David is a PhD candidate at the Paris School of Economics and has a Masters in Public Policy and Development. He has a background in causal inference and econometrics and has previously worked at Giving What We Can and the United Nations Development Programme. Saulius Šimčikas - Senior Staff Researcher Saulius is a Senior Staff Researcher at Rethink Priorities. Previously, he was a research intern at Animal Charity Evaluators, organized Effective Altruism events in the UK and Lithuania, and worked as a programmer. Neil Dullaghan - Staff Researcher Neil is a Staff Researcher at Rethink Priorities. He also volunteers for Charity Entrepreneurship and Animal Charity Evaluators. Before joining RP, ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: What is going on in the world?, published by Katja_Grace on the effective altruism forum. This is a linkpost for/ Here’s a list of alternative high level narratives about what is importantly going on in the world—the central plot, as it were—for the purpose of thinking about what role in a plot to take: The US is falling apart rapidly (on the scale of years), as evident in US politics departing from sanity and honor, sharp polarization, violent civil unrest, hopeless pandemic responses, ensuing economic catastrophe, one in a thousand Americans dying by infectious disease in 2020, and the abiding popularity of Trump in spite of it all. Western civilization is declining on the scale of half a century, as evidenced by its inability to build things it used to be able to build, and the ceasing of apparent economic acceleration toward a singularity. AI agents will control the future, and which ones we create is the only thing about our time that will matter in the long run. Major subplots: ‘Aligned’ AI is necessary for a non-doom outcome, and hard. Arms races worsen things a lot. The order of technologies matters a lot / who gets things first matters a lot, and many groups will develop or do things as a matter of local incentives, with no regard for the larger consequences. Seeing more clearly what’s going on ahead of time helps all efforts, especially in the very unclear and speculative circumstances (e.g. this has a decent chance of replacing subplots here with truer ones, moving large sections of AI-risk effort to better endeavors). The main task is finding levers that can be pulled at all. Bringing in people with energy to pull levers is where it’s at. Institutions could be way better across the board, and these are key to large numbers of people positively interacting, which is critical to the bounty of our times. Improvement could make a big difference to swathes of endeavors, and well-picked improvements would make a difference to endeavors that matter. Most people are suffering or drastically undershooting their potential, for tractable reasons. Most human effort is being wasted on endeavors with no abiding value. If we take anthropic reasoning and our observations about space seriously, we appear very likely to be in a ‘Great Filter’, which appears likely to kill us (and unlikely to be AI). Everyone is going to die, the way things stand. Most of the resources ever available are in space, not subject to property rights, and in danger of being ultimately had by the most effective stuff-grabbers. This could begin fairly soon in historical terms. Nothing we do matters for any of several reasons (moral non-realism, infinite ethics, living in a simulation, being a Boltzmann brain, ..?) There are vast quantum worlds that we are not considering in any of our dealings. There is a strong chance that we live in a simulation, making the relevance of each of our actions different from that which we assume. There is reason to think that acausal trade should be a major factor in what we do, long term, and we are not focusing on it much and ill prepared. Expected utility theory is the basis of our best understanding of how best to behave, and there is reason to think that it does not represent what we want. Namely, Pascal’s mugging, or the option of destroying the world with all but one in a trillion chance for a proportionately greater utopia, etc. Consciousness is a substantial component of what we care about, and we not only don’t understand it, but are frequently convinced that it is impossible to understand satisfactorily. At the same time, we are on the verge of creating things that are very likely conscious, and so being able to affect the set of conscious experiences in the world tremendously. Very little attention is being given to doing this well. We have weapons that c...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Some global catastrophic risk estimates, published by Tamay on the effective altruism forum. In October of 2018, I developed a question series on Metaculus related to extinction events spanning risks from nuclear war, bio-risk, risks from climate change and geo-engineering, Artificial Intelligence risk, and risks from nanotechnology failure modes. Since then, these questions have accrued nearly 2,000 predictions. Catastrophes were defined as a reduction in the human population of at least 10% in any period of 5 years or less. (Near) extinction is defined as an event that reduces the human population by at least 10% within 5 years, and by at least 95% within 25 years. Here's a summary of the results as they stand today. Global catastrophic risk Chance of catastrophe by 2100 Chance of (near) extinction by 2100 Nuclear war 4.18% 0.29% Biotechnology or bioengineered pathogens 4.18% 0.17% Artificial Intelligence failure modes 3.99% 1.88% Climate change or geo-engineering 1.71% 0.02% Nanotechnology failure modes 0.57% n/a These predictions are generated by aggregating forecasters' individual predictions based on their track records. Specifically, the predictions are weighted by a function of the forecasters' level of 'skill', where 'skill' is estimated with data on relative performance on a number (typically many hundreds) of resolved forecasts. If we assume that these events are independent, the predictions suggest that there's at least a 13.85% chance of catastrophe, and a 2.34% chance of (near) extinction by the end of the century. Admittedly, independence is likely to be an inappropriate assumption, since, for example, some catastrophes could exacerbate other global catastrophic risks. Moreover, the risks might higher be higher than these numbers suggest, given that there are other sources of global catastrophic risk besides the ones in the list. Interestingly, the predictions indicate that although nuclear risk and bioengineered pathogens are most likely to result in a major catastrophe, an AI failure mode is by far the biggest source of extinction-level risk—it is at least 6-times more likely to cause near extinction than the second most likely event to do so (namely, nuclear war). Links to all the questions on which these predictions are based may be found here. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: How well did EA-funded biorisk organisations do on Covid?, published by John G. Halstead on the effective altruism forum. EA funders have funded various organisations working on biosecurity and pandemic preparedness, including: John Hopkins Center for Health Security Georgetown Center for Global Health Science and Security Center for International Security and Cooperation Biosecurity Initiative Nuclear Threat Initiative Blue Ribbon Study Panel on Biodefense It seems to be widely accepted that many mainstream institutions got important things about COVID wrong, such as masks, travel bans, and lockdowns. Have there been any reviews of how these and other EA-funded things performed on COVID-related matters, with the benefit of hindsight? New Answer Ask Related Question New Comment Write here. Select text for formatting options. We support LaTeX: Cmd-4 for inline, Cmd-M for block-level (Ctrl on Windows). You can switch between rich text and markdown in your user settings. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Economic policy in poor countries, published by John G. Halstead on the effective altruism forum. When funding policy advocacy in the rich world, Open Philanthropy Project aims to only fund projects that at least meet the '100x bar', which means that the things they fund need to increase incomes for average Americans by $100 for every $1 spent to get as much benefit as giving $1 to GiveDirectly recipients in Africa. The reason for this is that (1) there is roughly a 100:1 ratio between the consumption of Americans to GiveDirectly cash transfer recipients, and (2) the returns of money to welfare are logarithmic. A logarithmic utility function implies that $1 for someone with 100x less consumption is worth 100x as much. Since GiveWell's top charities are 10x better than GiveDirectly, the standard set by GiveWell's top charities is a '1,000x bar'. Since 2015, Open Phil has made roughly 300 grants totalling almost $200 million in their near-termist, human-centric focus areas of criminal justice reform, immigration policy, land use reform, macroeconomic stabilisation policy, and scientific research. In 'GiveWell’s Top Charities Are (Increasingly) Hard to Beat', Alex Berger argues that much of Open Phil's US policy work probably passes the 100x bar, but relatively little passes the 1,000x bar. The reason that Open Phil's policy work is able to meet the 100x bar is that it is leveraged. Although trying to change planning law in California has a low chance of success, the economic payoffs are so large that the expected value of these grants is high. So, even though it is a lot harder to increase welfare in the US, because the policy work has so much leverage, the expected benefits are high enough to 100x the $ benefits. This raises the question: if all of this true, wouldn't advocating for improved economic policy in poor countries be much better than GiveWell's top charities? If policy in the US has high expected benefits because it is leveraged, then policy in Kenya must also have high expected benefits because it is leveraged. We should expect many projects improving economic policy in Kenya to produce 100x the welfare benefits of GiveDirectly, and we should expect a handful to produce 1,000x the welfare benefits of GiveDirectly. This is an argument for funding work to improve economic policy in the world's poorest countries. Lant Pritchett has been arguing for this position for at least 7 years without any published response from the EA community. Hauke Hillebrandt and I summarise his arguments here. My former colleagues from Founders Pledge, Stephen Clare and Aidan Goth, discuss the arguments in more depth here. Updated addendum: At present, according to GiveWell, the best way to improve the economic outcomes of very poor people is to deworm them. This is on the basis of one very controversial RCT conducted in 2004. I don't think this is a tenable position. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: We’re Rethink Priorities. Ask us anything! , published by Peter Wildeford on the effective altruism forum. Hi all, We're the staff at Rethink Priorities and we would like you to Ask Us Anything! We'll be answering all questions starting Friday, November 19. About the Org Rethink Priorities is an EA research organization focused on helping improve decisions among funders and key decision-makers within EA and EA-aligned organizations. You might know of our work on quantifying the number of farmed vertebrates and invertebrates, interspecies comparisons of moral weight, ballot initiatives as a tool for EAs, the risk of nuclear winter, or running the EA Survey, among other projects. You can see all of our work to date here. Over the next few years, we’re expanding our farmed animal welfare and moral weight research programs, launching an AI governance and strategy research program, and continuing to grow our new global health and development wing (including evaluating climate change interventions). Team You can find bios of our team members here. Links on names below go to RP publications by the author (if any are publicly available at this point). Leadership Marcus Davis — Co-CEO — Focus on animal welfare and operations Peter Wildeford — Co-CEO — Focus on longtermism, global health and development, surveys, and EA movement research Animal Welfare Dr. Kim Cuddington — Senior Ecologist — Wild animal welfare Dr. William McAuliffe — Senior Research Manager — Wild animal welfare, farmed animal welfare Jacob Peacock — Senior Research Manager — Farmed animal welfare Dr. Jason Schukraft — Senior Research Manager — Moral weight, global health and development Daniela Waldhorn — Senior Research Manager — Invertebrate welfare, farmed animal welfare Dr. Neil Dullaghan — Senior Researcher — Farmed animal welfare Dr. Samara Mendez — Senior Researcher — Farmed animal welfare Saulius Šimčikas — Senior Researcher — Farmed animal welfare Meghan Barrett — Entomology Specialist — Invertebrate welfare Dr. Holly Elmore — Researcher — Wild animal welfare Michael St. Jules — Associate Researcher — Farmed animal welfare Longtermism Michael Aird — Researcher — Nuclear war, AI governance and strategy Linch Zhang — Researcher — Forecasting, AI governance and strategy Surveys and EA movement research David Moss — Principal Research Director — Surveys and EA movement research Dr. David Reinstein — Senior Economist — EA Survey, effective giving research Dr. Jamie Elsey — Senior Behavioral Scientist — Surveys Dr. Willem Sleegers — Senior Behavioral Scientist — Surveys Global Health and Development Dr. Greer Gosnell — Senior Environmental Economist — Climate change, global health interventions Ruby Dickson — Researcher — Global health interventions Jenny Kudymowa — Researcher — Global health interventions Bruce Tsai — Researcher — Climate change, global health interventions Operations Abraham Rowe — COO — Operations, finance, HR, development, communications Janique Behman — Director of Development — Development, communications Dr. Dominika Krupocin — Senior People and Culture Coordinator — HR Carolina Salazar — Project and Hiring Manager — HR, project management Romina Giel — Operations Associate — Operations, finance Ask Us Anything Please ask us anything — about the org and how we operate, about the staff, about our research. anything! You can read more about us in our 2021 Impact and 2022 Strategy update or visit our website: rethinkpriorities.org. If you're interested in hearing more, please subscribe to our newsletter. Also, we’re currently raising funds to continue growing in 2022. We consider ourselves funding constrained — we continue to get far more qualified applicants to our roles than we are able to hire, and have scalable infrastructure to support far more research. We accept and track restr...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Effective Altruism and Meaning in Life, published by extra_ordinary on the effective altruism forum. Suppose I fail to make a major altruistic breakthrough with my life. Can my life still be meaningful? Do I still have value as a person? We know in our heads we're supposed to answer 'yes' to these questions. But in our guts, these days—these days of great loathing over the difficulty of getting jobs in EA—it can feel to many of us like we're stuck living lives that are utterly ordinary, marginal, minuscule, impactless, insignificant, replaceable, unoriginal, unimportant, uninspiring, or uninspired. The minds of EAs are, admirably, more scope-sensitive regarding impact than average, untrained intuitions. The great saints of EA—heroes like Stanislov Petrov, Norman Borlaug, or various philanthropists and nonprofit founders—truly do save or improve many, many orders of magnitude more lives than a typical person. This can tempt our guts, if not our heads, to feel we are many, many orders of magnitude less important than we could or should be. What follows is an allegorical, caricatured chronology of how I got to the point of coveting elusive EA talent-gaps, but then realized I was staking too much of my self-worth on success as an EA. It mentions "saints" and "angels" that altered my trajectory and seesawed my optimism. Why on earth would I use these metaphors? Well, it's not only because it's more fun (though it is). The hope is that others will find the story familiar, amusing, or reassuring, and will gain some perspective on meaning in life and how EA does and does not contribute to it. "Build a Movement": The Gospel according to St. Peter The vivid yellow cover of St. Peter's gospel shone persuasively, almost blindingly, into my eyes. Its empowering title, The Life You Can Save, was as luring as the precious, sad-looking child whose picture helped spell out the title. I held it in my very hands as I gazed amazed around the university lawn, excitedly in dialog with some of the most intelligent, ambitious young altruists I had ever met. Boldly, we brainstormed the myriad ways we could promote effective giving to our community. And unto us St. Peter spake: I think we should advocate the level of giving that will raise the largest possible total, and so have the best consequences. . . . [R]oughly 5 percent of annual income for those who are financially comfortable, and rather more for the very rich. My hope is that people will be convinced that they can and should give at this level. I believe that doing so would be a first step toward restoring the ethical importance of giving as an essential component of a well-lived life. And if it is widely adopted, we'll have more than enough to end extreme poverty. (p. 152) Soon we faithful would go on to start a Giving What We Can chapter which would meet near that very lawn. Sacraments developed in short order: we Lived Below the Line once a year; we took the Giving What We Can Pledge or at least Tried Giving; we promoted effective altruism across campus; we debated whether to give now or give later. Finally we had found our great calling and purpose; at last we were part of something larger than ourselves. And much unlike superstitious apostasies, we were able to to defend every detail with sound logic, even equations, some fit for the back of an envelope. Trials: a slow-igniting revolution Alas, temptation soon surrounded us, and we wavered in our walks. We grew weary of harping on the same message, despite our yearnings to persevere. Conversions were slow: for every hundred people exposed to our holy refrain, 'your dollar goes further overseas', barely one or two were transformed by our gospel. Even for the converts we scarcely had enough rousing rituals: signing the Pledge was one-time; Live Below the Line was once a year; deb...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Effective Animal Advocacy Resources, published by saulius on the effective altruism forum. This article contains a list of research organizations, newsletters, research libraries, personal blogs, conferences, podcasts, funds, notable written works and other links associated with Effective Animal Advocacy (EAA) movement. The list is biased because I only included resources that I know of. If you think something is missing, please comment. Introductory materials Animal Welfare (article from effectivealtruism.org) Plant and cell based meat (6 min TED talk) Farm Animal Funders briefings (targeted at big funders) Research organizations Here is a list of organizations and departments that publish animal advocacy strategy research: Animal Advocacy Careers - “researching career trajectories and addressing talent constraints in the animal movement”. Animal Ask - founded with the express aim to optimise and prioritise future asks to assist animal advocacy organisations in their efforts to reduce farmed animal suffering. We provide organisations with in-depth research, narrowly targeted at key decisions between different animal asks, supporting organisations, individual activists, policymakers and donors so that they may do more good in the long term. Animal Charity Evaluators (ACE) - charity reviews, intervention reviews, general research, advocacy advice, interviews, and more. Animal Ethics - resources on ethics, sentience, animal exploitation and wild animal suffering. Charity Entrepreneurship - a research and training program aimed at creating multiple high-impact charities. A lot of their 2019 research was about what new animal-focused charities would be the most impactful. CIWF research, CIWF USA research Faunalytics - original research focusing on farmed animal and movement-building topics, a library of lay-friendly summaries of academic research, and one-on-one support for advocates who want help finding data or designing or understanding research. fishcount - estimates of wild-caught and farmed fish numbers, discussion of fish welfare issues. Fish Welfare Initiative - will do research about welfare reforms for fish in the next 5 months. MFA research - evaluations to optimize various advocacy strategies. OpenPhil - the largest funder in farm animal advocacy (~$35 million per year), shares some of its internal research. Rethink Priorities - animal-related research so far focused on neglected groups of animals, corporate campaigns, and wild animal welfare. Sentience Institute - meta-level research for the EAA community. THL Labs - “informing advocacy strategies through actionable research on their effectiveness”. Wild Animal Initiative - “working to understand and improve the lives of animals in the wild.” Previously, it was two organizations: Utility Farm and Wild-Animal Suffering Research. Some of the texts are only available on the websites of these defunct organizations. They merged in 2019. In total, there seem to be about 35 full time researcher equivalents in animal advocacy research space. Note that I excluded organizations like Asia Research and Engagement (ARE), Farm Animal Investment Risk & Return (FAIRR), Centre for Animal Welfare Science Excellence and Animal Welfare Foundation that do or fund animal welfare related research that is not directly about advocacy strategy. I also excluded clean meat research. For incomplete lists of animal advocacy organizations in general see all ACE’s charity reviews and a list of OWA organizations. Newsletters Main newsletters: But Can They Suffer - monthly summaries of the most relevant new EAA research. The last three newsletters can be seen here. OpenPhil Farm Animal Welfare Newsletter - original content by OpePhil. All previous newsletters are available in the archive. THL Labs newsletter - updates include monthly summari...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Genetic Enhancement as a Cause Area , published by Galton on the effective altruism forum. Originally posted on the EA subreddit. First, I will present a rough sketch for why genetic enhancement could be a plausible cause X. Then I will list some specific proposals for genetic interventions. I will conclude by responding to objections. If there is interest, I may write more posts on this topic. Basic argument There are two main ways to think about genetic enhancement as a potential EA cause area. One perspective is focused on improving short-term human welfare. While reducing “defects” (disabilities, depression, etc.) would be a major focus, this perspective could additionally encompass increasing the frequency of beneficial traits, such as longevity-promoting alleles of the FOXO3 gene. The key idea is that enhancement is performed to increase individual well-being. The other way of thinking about genetic enhancement, and the one I prefer, takes a long-term view. Changes are made with the far-future of our society in mind. For instance, by drastically increasing IQs, we could put our civilization in a better position to solve complex challenges that exist today or will arise down the line. Other interventions such as increasing empathy and decreasing Dark Triad personality traits could be used to influence the values of our descendents and avert future moral catastrophes. The short-term case for genetic enhancement If we want to improve short-term human well-being, we can group most possible interventions into two broad categories: Improve the quality and duration of life for presently-existing humans. Change which (and how many) humans will be born in the first place. The first method is far less philosophically controversial. Everyone agrees that once you’re born, it’s better to live a happy life than a miserable one. On the other hand, when it comes to changing the number and identity of people in existence, we enter the muddy waters of population ethics, fraught with paradoxes and impossibility theorems. For the most basic version of my argument to work, it suffices to assume that when selecting among a fixed number of “potential children” who could be born, we should choose the ones with the highest expected well-being. I have not yet said anything about genes specifically! Of course, both environment and genetics could be factors when evaluating the expected well-being of potential future humans. However, living environment in general is already subject to more optimization (see next paragraph). It also appears that many traits that contribute to a happy, successful life are highly heritable, including psychological traits (see appendix 1). Further, taking a slightly longer-term view, genetic information is directly passed on for multiple successive generations, while environment is ephemeral. I think a focus on genes is justified. Going back to the dichotomy of altruistic interventions, the first option is the tack that most effective altruists interested in short-term human welfare have taken. It is also the strategy most popular among do-gooders in general. In comparison, little philanthropic effort is devoted to efforts to (e.g.) decrease the number of children born with severe congenital diseases or to increase the frequency of welfare-promoting alleles in the population. Aside from philanthropy, people in general seek out the best living environment for themselves and their children. On the other hand, although sexual selection does exist, people generally do not explicitly optimize the genetics of their progeny. So it’s clear that improving population genetics is comparatively neglected. Further, I would argue that genetic enhancement is quite important. A meta-analysis of twin studies found that genetic factors explain 36% of variation in subjective wel...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Creepy Crawlies (an EA poem), published by MHarris on the effective altruism forum. Does an incy wincy spider Have an incy wincy brain, With incy wincy feelings, And incy wincy pain? Do all the creepy crawlies Climbing up the water spout Count for nothing, or for everything? What a crazy thing to doubt! If I can't know for certain What it's like to be a bat, How can I hope to understand The troubles of a gnat? If, though I know, I think, I am, I guess at what you are, Then I must know my limits Empathy can't go so far. Some day we'll have the answers, Or at least we'll know much more, And, in the meantime, muddle on. We'll do our best, I'm sure. We'll be wild geese, and better yet, We'll grow in what we can. But, in the mean time, barely know Enough to help our fellow man. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: What are some key numbers that (almost) every EA should know?, published by Linch on the Effective Altruism Forum. I think it might be interesting and valuable to create a "list of numbers every EA should know", in a similar vein to Latency Numbers Every Programmer Should Know and Key Numbers for Cell Biologists. I was originally thinking of either a) making the whole list myself, or b) convincing someone else (eg, an RP intern) to do it, but on AaronGertler's advice I decided to turn to the Forum to help with crowdsourcing this problem. We can use upvotes/downvotes and comments to debate which numbers should be worth including/excluding. So what are some key numbers that (almost) every EA should know? Feel free to answer with either important numbers that you think are cause-specific (eg, numbers of chickens currently alive in factory farms, Toby Ord's x-risk estimates, extreme poverty rates in 1950 vs 2018) or relatively cause agnostic (eg, $billions that Open Phil has, expected lifespan of social movements, number of atoms in the observable universe). Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is:Towards a Weaker Longtermism, published by Davidmanheim on the Effective Altruism Forum. A key (new-ish) proposition in EA discussions is "Strong Longtermism," that the vast majority of the value in the universe is in the far future, and that we need to focus on it. This far future is often understood to be so valuable that almost any amount of preference for the long term is justifiable. In this brief post, I want to argue that this strong claim is unnecessary compared to a weaker argument, creates new problems that are easily avoided otherwise, and should be replaced with the weaker claim. (I am far from the first to propose this.) The 'regular longtermism' claim, as I present it, is that we should assign approximately similar value to the long term future as we do to the short-term. This is a philosophically difficult position which nonetheless, I argue, is superior to either status quo, or strong longtermism. Philosophical grounding The typical presentation of longtermism is that if we do not discount future lives exponentially, almost any weight placed on the future, which almost certainly can be massively larger than the present, will overwhelm the value of the present. This is hard to justify intuitively - it implies that we should ignore the near-term costs, and (taken to the extreme) could justify almost any atrocity in the pursuit of a miniscule reduction of long-term risks 1 The typical alternative is presented by naïve economic discounting, which assumes that we should exponentially discount the far future at some finite rate. This leads to claims that a candy bar today is worth more than the entire future of humanity starting in, say, 10,000 years. This is also hard to justify intuitively. A third perspective roughly justifies the current position; we should discount the future at the rate current humans think is appropriate, but also separately place significant value on having a positive long term future. This preserves both the value of the long-term future of humanity if positive, and the preference for the present. Lacking any strong justification for setting the balance, I will very tentatively claim they should be weighted approximately equally, but this is not critical - almost any non trivial weight on the far future would be a large shift from the status quo towards longer-term thinking. This may be non-rigorous, but has many attractive features. The key question, it seems, is whether the new view is different, and/or whether the exact weights for the near and long term will matter in practice. Does 'regular longtermism' say anything? Do the different positions lead to different conclusions in the short term? If they do not, there is clearly no reason to prefer strong longtermism. If they do, it seems that almost all of these differences are intuitively worrying. Strong longtermism implies we should engage in much larger near term sacrifices, and justifies ignoring near-term problems like global poverty, unless they have large impacts on the far future 2 . Strong neartermism, AKA strict exponential discounting, implies that we should do approximately nothing about the long term future. So, does regular longtermism suggest less focus on reducing existential risks, compared to the status quo? Clearly not. In fact, it suggests overwhelmingly more effort should be spent on avoiding existential risk than is currently available for the task. It may suggest less effort than strong longtermism, but only to the extent that we have very strong epistemic reasons for thinking that very large short term sacrifices are effective. What now? I am unsure that there is anything new in this post. At the same time, it seems that the debate has crystallized into two camps which I strongly disagree with - the "anti-longtermist" camp, typified by Phil Torres, who is h...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: A list of EA-related podcasts, published by M_Allcock on the Effective Altruism Forum. Podcasts are a great way to learn about EA. Here’s a list of the EA-related podcasts I’ve come across over the last few years of my podcast obsession. I’ve split them up into two categories: Strongly EA-related podcasts: Podcasts run by EA organisations or otherwise explicitly EA-related. Podcasts featuring EA-related episodes: Podcasts which are usually not EA-related but have some episodes which are about an EA idea or interviewing an EA-aligned guest. Please add to the comments any podcasts that I have missed. I am always excited to find out about more interesting podcasts! Strongly EA-related podcasts Doing Good Better Podcast- Five short episodes about EA concepts. Produced by the Centre for Effective Altruism. No new content since 2017. The Life You Can Save Podcast- Episodes from Peter Singer’s organisation that focus on alleviating global poverty. The latest episodes are interviews with EA organisation staff. The Turing Test - The newly restarted EA podcast from the Harvard University EA group. Interviews with EA thinkers including Brian Tomasik on ethics, animal welfare, and a focus on suffering, and Scott Weathers on Charity Science Health. 80,000 Hours Podcast - Robert Wiblin leads long-form interviews (up to 4 hours) with individuals in high impact careers. This podcast really gets into the weeds of the most important cause areas. Global Optimum - An informal podcast by professional psychology researcher, Daniel Gambacorta. Discussing psychology results that can help you become a more effective altruist. There is usually no extra padding in this podcast, it's straight to the point. Future Perfect Podcast - The podcast part of Vox Media’s Future Perfect project. Dylan Matthews leads scripted discussions about interesting and hopefully effective ways to improve the world. Morality is hard - Michael Dello Iacovo interviews guests about topics related to effective animal advocacy. Future of Life Podcast - Interviews with researchers and thought leaders who the Future of Life Institute believe are helping to “safeguard life and build optimistic visions of the future”. They include a series on AI alignment and a recent series on climate change. Wildness - A new podcast of Wild Animal Initiative. Narrative episodes based around a theme relevant to wild animal welfare research, typically including multiple interviews with animal welfare researchers. EARadio - hundreds of audio recordings from EA Global talks. Some episodes are hard to follow due to the missing visual information that is used in presentations. Sentience Institute Podcast - New podcast on effective animal advocacy. Podcasts featuring EA-related episodes Our Hen House - Jacy Reese on the end of animal farming; Joey Savoie on using charity entrepreneurship to help animals. The Joe Rogan Experience - Nick Bostrom on the simulation argument; Will Macaskill on EA. The Most Interesting People I Know - Chloe Cockburn on US justice system reform; Lewis Bollard on ending factory farming; Spencer Greenberg on lots of things related to EA; Andres Gomez Emilsson of Qualia Research Institute on solving consciousness. Autocracy and Transhumanist Podcast - Phil Torres, Seth Baum, and Anders Sandberg on the long-term future; Jeff Sebo on the moral value of other minds. The Future Thinkers - Phil Torres on the long-term future and existential risks; Daniel Schmachtenberger on generator functions for existential risks, global phase shift, and mitigating existential risks. Making Sense with Sam Harris - Lots of episodes about consciousness, meaning, and ethics. In particular: Will Macaskill on EA; Nick Bostrom on existential risks; Eliezer Yudkowsky on AI. Philosophise This - A brilliant episode on Peter Singer and effective altrui...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Giving What We Can & EA Funds now operate independently of CEA, published by MaxDalton, Jonas Vollmer, lukefreeman on the Effective Altruism Forum. This is a linkpost for/ In 2020, the Centre for Effective Altruism hired Luke Freeman to run Giving What We Can (GWWC), and Jonas Vollmer to lead EA Funds. We think that they have both made strong progress in the past year. For instance, Luke revamped GWWC’s website and saw the number of new pledges triple compared to the same period in 2019. Meanwhile Jonas improved EA Funds’ capacity to make more effective grants and addressed some issues affecting donor satisfaction.[1] In addition to the above, we closed EA Grants, redirecting applicants to EA Funds. As planned, both EA Funds and GWWC now operate independently of my supervision as Executive Director of CEA, while continuing to receive operational support from CEA and oversight from our board. This is similar to 80,000 Hours’ position relative to CEA: they make decisions independently and have their own leadership, but CEA provides operational support and they are legally part of the same entity. We are delighted that these projects now have the freedom to grow independently, while CEA is able to focus on nurturing the community’s discussion spaces. Our 2020 plans As mentioned in our public plans for 2020: In 2019, Giving What We Can members logged over $20m in donations to the charities that they believe to be most effective, and 528 people took a 10% lifetime pledge, bringing the year-end total to 4,454 members. EA Funds facilitated grantmaking of $8.5m through the four main funds, as well as $3.4m to other effective charities. I think that both of these programs are important for EA because: They direct a significant amount of money to effective charities. They provide an opportunity for individuals to take important, concrete actions based on EA principles. However, these projects have a fairly different focus from CEA’s other projects (which focus on community engagement rather than charitable donations), and we think that with more focus and staff time they could achieve more. We'd like to move towards a state where these projects have the latitude and resources to accomplish more, and where CEA can focus on a narrower range of projects. Over the last few months, I’ve been working with trustees and staff to plan for the future of these projects, using surveys of users and members to inform our thinking. We’ll initially search for someone who can lead an independent Giving What We Can [...] If we find a leader for Giving What We Can, we’ll help to onboard and advise them, and we will continue to provide operational support to both EA Funds and Giving What We Can for the foreseeable future. Once we’ve completed our hiring round for the Giving What We Can director, we will consider focusing more on plans for hiring an executive for and/or spinning out EA Funds. Giving What We Can Giving What We Can (GWWC) aims to create a culture where people are inspired to give more, and to give more effectively. This year: We hired Luke Freeman to run the program. In Luke’s first three months, the rate of new pledges tripled compared with the same period last year; we also reached 5,000 members. Website content is now more accurate, cause neutral, and compelling. 2020 Cost: $61,000 FTEs: 1.0 (from Q3 2020) 2021 Budget: $246,000[2] Hiring Luke Freeman We hired Luke Freeman in July 2020. We have been impressed with his results, as well as with the energy, nuance, and experience he brings to the role. In October, he passed probation and began to report to CEA’s board, thus spinning GWWC out of core CEA. Growth From January to October, we: Reached over 5,000 total members 623 new pledges (increased by 77% over the same period in the previous year) with an estimated value of $45.5M[3]...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Announcing the Open Philanthropy Undergraduate Scholarship, published by Bastian_Stern on the Effective Altruism Forum. We are pleased to announce the new Open Philanthropy Undergraduate Scholarship. From the program page: This program aims to provide support for highly promising and altruistically-minded students who are hoping to start an undergraduate degree at one of the top universities in the USA or UK (see below for details) and who do not qualify as domestic students at these institutions for the purposes of admission and financial aid. Funding criteria We are looking to fund candidates who: have demonstrated exceptional academic merit; are interested in using their careers to do as much good as possible. We plan to offer both full and partial scholarships, depending on candidates’ financial need and the strength of their applications. Note that the application timeline will differ depending on whether candidates are applying for funding to attend university in the USA or the UK (or both) - see the sections immediately below. Scholarships to attend university in the USA Candidates are eligible to apply if: they are planning to apply to one or more of the following universities for an undergraduate degree starting in 2022: California Institute of Technology, Stanford University, University of Chicago, University of Pennsylvania, Columbia University, Brown University, University of California - Berkeley; and they qualify as international students for the purposes of admission and financial aid at these institutions. Candidates who are applying to Harvard, Massachusetts Institute of Technology, Princeton, and Yale in addition to (one or more) of the universities listed above are also eligible to apply. However, we generally don’t expect to offer scholarships to attend one of the former universities (Harvard, MIT, Princeton, Yale), given that these universities both meet full financial need of admitted undergraduates and select applicants - including international applicants - in a need-blind manner (i.e. financial need does not affect the chances of admission), which means that we see less room for our scholarship to benefit recipients.[1] The application timelines for applicants seeking funding to attend one or more of the above-listed universities in the USA are as follows: If you plan on applying to one of the above-listed universities in the USA through early decision/early action and would like us to consider your application for a scholarship to attend that university, you should apply here by October 1st, 11.59 p.m. Pacific Time. We plan to inform successful candidates by mid- to late October, in order to allow them to include information about the scholarship they have been awarded in their early decision/early action applications. Otherwise, you should apply here by November 12th 2021, 11.59 p.m. Pacific Time. We plan to inform successful candidates by early to mid-December, again in order to allow them to include information about the scholarships they have been awarded in their university applications. Our impression is that for both early decision/early action and regular decision applicants, having already secured an outside scholarship (like ours) at the time of applying to the universities in question can in many cases meaningfully improve their chances of admission. If you have already applied to one of the universities on our list through early decision/early action, you can still apply for a scholarship to attend one of the other relevant universities (by applying before the November 12th deadline). Scholarships will be conditional on admission to one of the relevant universities. In some cases, we may offer scholarships conditional on admission to a specific subset of the universities listed above. Note that for these universities, early decis...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is:You can talk to EA Funds before applying , published by evhub on the Effective Altruism Forum. Cross-posted to LessWrong. One thing I have realized as a fund manager for the EA Long-Term Future Fund is that there are a lot of grants that I would like to make that never cross our desk, just because potential applicants are too intimidated by us or don’t realize that their idea is one we’d be willing to fund if only they applied. To try to remedy that problem, I’m going to start offering the following service: if you have any idea of any way in which you think you could use money to help the long-term future, but aren’t currently planning on applying for a grant from any grant-making organization, I want to hear about it. Feel free to send me a private message on the EA Forum or LessWrong. I promise I’m not that intimidating :) Not only that, but having talked about this with some of the other EA Funds managers, many of them were willing to extend the same offer as well: For the Animal Welfare Fund, just send an email to Kieran Greig. For the EA Infrastructure Fund, both Michelle Hutchinson (via EA Forum or email) and Michael Aird (currently a guest manager; can be contacted via EA Forum, LessWrong, or email) would be happy to chat. For example, here are some of the sorts of grants I’m often excited about but that I rarely see anyone apply for: “I want to transition to a career in something longtermist, but that transition would be difficult for me financially and I’d like to have some extra financial reserves to make it easier.” “I think I would be more productive in my longtermist job if I had more money to spend on things that would save me time.” “I have an idea for a longtermist project I want to work on, but I don’t want to commit to definitely working on that project for the duration of a long grant and want freedom to change my mind and switch to a different project if I want.” “I have an ambitious idea for a project that I think would benefit the long-term future, but I think it would take a lot of money, more than what I normally see LTFF grants being given out for.” Really, though, I don’t want to anchor anybody too much on these specific ideas—if you have any idea of any way in which you think you could use money to help the long-term future, I want to hear about it. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: EA Hotel Fundraiser 5: Out of runway!, published by CEEALAR on the Effective Altruism Forum. UPDATE 5th Nov 2019: since this post went up, we have received ~£9,500 in donations and a further ~£4000 in backdated payments from residents. Following the latter, and adjusting costs for last 6 months downward to ~£5,100/month, our runway now extends ~3 months, to the beginning of Feb. Thanks for all the support, this is a great start to our latest fundraiser. We are working on more posts in the series listed below (will link to them in the list as they are completed). This is a quick post to say that our financial situation is looking pretty dire right now. We were going to wait until “Giving Season” starts in December to start a fresh fundraiser, but now can’t afford to do that. We have several things in the pipeline to bolster our case (charity registration, compiling more outputs, more fundraising posts detailing the case for the hotel, hiring round for the Community & Projects Manager, refining internal systems), but they may not reach fruition in time unfortunately. If you are interested in donating, now is the perfect timing for you to have a large impact on the project! Happy to answer questions in the comments (have anticipated some below). Relatively small amounts would allow us to keep things going long enough to gain the information needed to determine whether the experiment is/was worthwhile. As it is, if the project fails down to lack of funds now, we feel that we are leaving a lot of Value of Information on the table. Our costs are ~£5,700/month (based on the last 5 months’ spending). Even 1 month of funding will allow us some breathing space to get some of the work done. To donate, and for more info (past posts making the case for the hotel), see: eahotel.org/fundraiser. List of proposed posts for the continuation of this series (renewed runway permitting; provisional; linked when complete): EA Hotel Fundraiser 6: Concrete outputs after 17 months EA Hotel Fundraiser 7: Pitch focusing on case studies with counterfactuals EA Hotel Fundraiser 8: Life at the EA Hotel, and testimonials EA Hotel Fundraiser 9: Estimating the relative Expected Value of the EA Hotel (Part 2) Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio., published by Luisa_Rodriguez on the Effective Altruism Forum. Summary Frustrated by the lack of progress on nuclear disamarment, a growing movement of government and civil society actors has emerged hoping to reignite efforts to move toward de-proliferation and disarmament. Out of this movement came the Treaty on the Prohibition of Nuclear Weapons (TPNW), a legally-binding treaty that would prohibit party countries from possessing, using, threatening to use, hosting, testing, or developing nuclear weapons. The treaty would also forbid parties from contributing to or encouraging those activities, for example by aligning themselves with nuclear weapons states with the explicit aim of being shielded by a nuclear umbrella. In this post, I investigate whether the TPNW is likely to have an impact on nuclear deproliferation through formal legal channels — for example, by keeping countries that might have considered building nuclear weapons programs from doing so.[1] To do this, I first looked into whether any of the countries that are currently doing things that would be banned by the TPNW might ratify the treaty in the next 20 years (and stop doing those things). Next, I looked into whether the TPNW will keep any countries that ratify the treaty from becoming non-compliant — for example, by trying to get a sense of whether the treaty could counterfactually cause them not to pursue nuclear weapons. I came out feeling very pessimistic about the likelihood that countries that are non-compliant with the TPNW will ratify it, largely because none of the 40 non-compliant countries have signed or ratified the TPNW, and several have spoken out against it. Additionally, I’m somewhat pessimistic about the potential for the TPNW to causally influence the decision of TPNW supporters to pursue, host, or manufacture nuclear weapons, or to join a nuclear weapons alliance, though I have more uncertainty about this. This leads me to think that the TPNW is unlikely to have much of an impact on nuclear deproliferation through legal channels overall. That said, it’s quite possible that the TPNW will have an impact on nuclear weapons policies through informal channels. I’ll explore this possibility extensively in a future post. Project Overview This is the sixth post in Rethink Priorities’ series on nuclear risks. In the first post, I look into which plausible nuclear exchange scenarios should worry us most, ranking them based on their potential to cause harm. In the second post, I explore the make-up and survivability of the US and Russian nuclear arsenals. In the third post, I estimate the number of people that would die as a direct result of a nuclear exchange between NATO states and Russia. In the fourth post, I estimate the severity of the nuclear famine we might expect to result from a NATO-Russia nuclear war. In the fifth post, I get a rough sense of the probability of nuclear war by looking at historical evidence, the views of experts, and predictions made by forecasters. In this post, explore the potential for the Treaty on the Prohibition of Nuclear Weapons (TPNW) to affect nuclear deproliferation through legal channels. Future work will explore the possible impacts of the TPNW on nuclear deproliferation through informal channels — things like norm-shifting — as well as the direct and indirect effects of nuclear exchanges between (1) India and Pakistan and (2) China and its adversaries, the contradictory research around nuclear winter. The Rationale for the Treaty on the Prohibition of Nuclear Weapons Nuclear de-proliferation was enormously successful from the late 80s to the early 2000s. Following the Cold War, a series of bilateral t...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: How has biosecurity/pandemic preparedness philanthropy helped with coronavirus, and how might it help with similar future situations?, published by vipulnaik on the Effective Altruism Forum. My understanding is that Open Philanthropy's biosecurity and pandemic preparedness focus area is intended partly to target situations like the ongoing coronavirus pandemic. Though biosecurity philanthropy hasn't caught on a lot in the EA community at large, it has attracted some commentary and thought in the community. I'm wondering a few things: How has Open Philanthropy's biosecurity/pandemic preparedness philanthropy so far affected the way people have dealt with the coronavirus pandemic? How might the biosecurity/pandemic preparedness philanthropy affect similar situations in the future? Is it laying the groundwork for improving how we address such situations in the future? Are there any learnings so far from the coronavirus pandemic, for what to focus on in biosecurity/pandemic preparedness philanthropy? Some of these questions may be better answered after the coronavirus pandemic settles down. Thanks to Issa Rice for hearing out my original version of the question. He did not review this post. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Correlations Between Cause Prioritization and the Big Five Personality Traits , published by ElizabethE on the Effective Altruism Forum. Late Edit: This post received way more attention than I expected. For important context, please see David Moss's first comment, especially his helpful visualization. "One thing worth bearing in mind is that these are very small proportions of the responses overall..." I am ultimately talking about small groups of people within the total number of survey respondents, and although I think my claims are true, I believe they are trivially so; I created this post largely for fun and practice, not for making important claims. Note to EA Forum users: Please pardon the introductory content; this post is for sharing with my classmates and professors who are otherwise unaware of the EA movement. Content warning: Frequentist statistics The effective altruism community is a group of nerds, but instead of nerding out about train engines, Star Wars, or 18th-century sword-fighting, they nerd out about one question: Given limited resources and all of humanity's accumulated knowledge about the social and physical sciences, what is the most cost-effective way to improve the world? While the focus began on figuring out which charity is the best place to spend your marginal dollar, and much work still focuses on how to do that, the EA community has expanded to questions of how analytic, altruistic-minded people should best allocate their time and social capital, as well. People in the community have settled on several possible answers to the question, "Of all the problems to work on, what should members of the EA community focus on the most?" Some examples of those answers include improving animal welfare, global poverty reduction, and improving biosecurity measures against engineered or accidental pandemics. (Notably, members of the community personally prepared for COVID weeks before their governments enacted emergency orders.) For years, I've assumed that the differences in cause area selection are determined solely by people's prior beliefs, i.e. if you believe animals are "moral patients" in the philosophy lingo, then you're more likely to prioritize animal welfare; if you believe currently living people are moral patients and people who haven't been born yet are not, then you're more likely to prioritize global poverty reduction (over e.g. existential risk reduction). However, with the fresh acquisition of some basic data science skills and some anonymized survey data, I thought of an interesting question: Do a person's personality traits affect which cause area they're likely to prioritize? And if so, how? You see, in 2018, the EA-affiliated (but not me-affiliated!) organization Rethink Charity included optional questions at the end of their annual community survey which recorded people's scores on the Big Five personality traits, so we have rough data on how nearly 1200 members of the EA community score on traits of openness, extroversion, conscientiousness, agreeableness, and "emotional stability" (in the survey data and in this analysis, the opposite of the trait usually labeled "neuroticism" in Big Five inventories). If you're already familiar with the EA community, then just for fun, you could try making some guesses about the relationships between personality traits and cause prioritization before you scroll down any further. In the interest of transparent calibration, I'll divulge the three conjectures I jotted down prior to running any of my statistical tests. I expected higher openness to correlate with AI safety prioritization, higher conscientiousness to correlate with animal welfare prioritization, and lower emotional stability to correlate with prioritizing mental health interventions. None of my predictions were borne out by my ana...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Getting money out of politics and into charity , published by UnexpectedValues on the Effective Altruism Forum. I’m Eric Neyman, a grad student working on mechanism design at Columbia. I am working with Yash Upadhyay, a student at UPenn (and previously Y Combinator Summer ‘19), to build a platform that would match donations to opposing political campaigns and send the money to charities instead. Here’s the basic idea: let’s say that in 2024 Kamala Harris (D) will be running against Mike Pence (R) for president. The platform would collect money from donors to both campaigns; let’s say for example that Harris donors give us $10 million and Pence donors give us $8 million. We would send matching amounts ($8 million on each side) to charity and donate the remaining amount to the political campaign that raised more ($2 million to Harris). The result is that $16 million more gets sent to charity, while not changing how much money the campaigns have relative to one another. From a donor’s perspective, one way to think about this is: if you donate $100 to the platform, then in the worst case, your money will not end up matched and will go to your preferred campaign (as it would have gone if you’d contributed directly). But in the best case, your money will be matched with $100 on the other side, reducing the opposing candidate’s cash on hand by $100 and causing an extra $200 to go to charity. As a back-of-the-envelope calculation: $7 billion was spent on the 2016 election cycle, a number that has been rapidly increasing. If just 0.1% of the money spent on the 2016 election had instead gone to effective charitable causes, that would amount to a few thousand lives saved. If you’d like to read more about this idea, see here for a more extensive write-up and here for an analysis of possible incentives issues with the platform, as well as possible fixes. This idea has been tried before: during the 2012 election, Eric Zolt and Jonathan DiBenedetto tried to create a platform like this and called it Repledge; here’s a Washington Post profile. Unfortunately they didn’t get past the testing phase. Yash and I talked to the two of them a couple weeks ago to learn what worked and what didn’t. They told us that the primary obstacle they ran into wasn’t a technical one (web infrastructure etc.) but a legal one: campaign finance law is complicated, plus the political parties won’t like you (you’re taking their money) and will very likely sue you. Dr. Zolt said that these lawsuits are dangerous despite an FEC ruling saying that Repledge was legal, because there are various ways to interpret the ruling. He gave us a ballpark estimate that creating something like Repledge would cost a quarter of a million dollars. (We are working on getting a more granular estimate for the legal and marketing costs individually, but the largest component would probably be legal.) The purpose of this post is basically to gauge interest and ask for advice. Here are some concrete questions: If we successfully built this platform, would you consider using it? If your answer is “it depends”, what does it depend on? Do you think building this platform is worth the cost? If so, do you have suggestions for how we might be able to finance this project? What grant-awarding organizations might be a good fit for our project? In particular, would it be reasonable for us to contact the Open Philanthropy Project? One thing I didn’t specify in the description above is how exactly the charity donation process will work. Our tentative plan is to offer a list of charities for donors to choose from; whatever fraction of a donor’s money gets matched will go to the charity they chose. If you have a suggestion you think is better, we’d love to hear it. But if we end up going with this plan, how should we choose the charities? I thin...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Type Checking GiveWell's GiveDirectly Cost Effective Analysis, published by Hazelfire on the Effective Altruism Forum. tldr: You can check for the consistent use of units to find assumptions and/or errors within calculations. I use this on GiveDirectly's Cost Effective Analysis by GiveWell to find two implicit assumptions that impact the result. I think they should probably be included explicitly within the model, and that this technique could be used for other Cost Effectiveness Analysis. If you are not interested in the specifics of how the effectiveness of charities are calculated, you will probably find this read a waste of time. Numerical models could describe the world, or it might not describe the world. However, there's an interesting way that you can work out whether your model does describe the world without even looking at any data. To do that, we turn to the field of Dimensional Analysis. Dimensional Analysis is based off really simple ideas. Basic Dimensional Analysis pretty much has two rules: You can only equate, add or subtract numbers that have the same units Multiplying/dividing numbers means multiplying/dividing their units We use dimensional analysis all the time. If I have 4 apples per bag, and 5 bags, then we 4 × 5 20 apples. In this case we multiplied the units together a p p l e s b a g × b a g s a p p l e s This is the second rule above. We however, cannot add units that are different. It doesn't make sense to say that I have 4 apples per bag + 5 bags. a p p l e s b a g b a g s We do not know what the units of the result would be. This is the first rule above. What's great about physical equations is that you can vary the units of the equation and it still means the same thing. Say instead of talking about apples, you cut each apple in half and talk about apple halves. This changes the units from apples to apple halves. So we would have 8 apple halves per bag and 5 bags. How many apple halves do you have? Well, we have 8 × 5 40 apple halves, which is exactly the same prediction as 20 apples. The fact that we can change our units without changing the meaning of a physical equation I'll call "scale invariance". If you have equations that are not physical, then that law can be violated. For instance, if we assumed (wrongly) that we can add the apples per bag and bags to get apples. a p p l e s b a g b a g s a p p l e s Then scale invariance will be violated. Because in the first example, if you have 4 apples per bag, and 5 bags, this would predict you would have 4 5 9 apples in total. However, if we start talking about apple halves, and say we have 8 apple halves per bag, then the equation would give 8 5 13 apples halves. 13 apple halves is not the same as 9 apples. Therefore scale invariance has been violated and this equation therefore must be wrong. If dimensional analysis is not followed, then simply changing the units of your equation would change it's results! An equation that follows these rules is deemed "physical". In physics, this is such a powerful tool in finding incorrect equations, that it's possible to derive many equations by looking at the units of the parameters alone. I was particularly blown away by an example of deriving the range equation from the units of it's parameters on Wikipedia. I'm from a software background, so I like to consider this as type checking math. Hence the title. There are a lot of long calculations done in Cost Effectiveness Analysis (CEAs). As of such, I investigated as to whether these calculations were physical for GiveDirectly. That is, do these calculations abide by the rules of Dimensional Analysis. Dimensional Analysis has two important but distinct concepts, "units" and "dimensions". Examples of dimensions include "length", "time", "money". Examples of units include "meters", "feet", "seconds", ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Thoughts on 80,000 Hours’ research that might help with job-search frustrations, published by Ardenlk on the Effective Altruism Forum. intend to start working at 80,000 Hours this September, and in the meantime they're contracting me to write some articles about careers and doing good, including this one. Nonetheless, this article represents my personal opinions only, and does not necessarily reflect the views of the 80,000 Hours team. An EA Forum post from earlier this year demonstrated the difficulty of getting a job in effective altruism organisations, the frustration many people feel as a result, and the sense that other ways of doing good are not as highly valued by the EA community as they should be. People in the community have published a number of thoughtful responses. I am currently doing some part-time contract work for 80,000 Hours, and I plan to start working there full-time in the fall. As such, I’ve been thinking a lot about 80,000 Hours’ research. And I wanted to add to the discussion a few ways I think that 80,000 Hours content might have inadvertently contributed to these problems, as well as some ideas for how people can get more out of their advice. The main takeaways are: Roles outside explicitly EA organizations are most people’s best career options. Sometimes these roles aren’t as visible to the community, including to 80,000 Hours, but that doesn’t mean they aren’t highly impactful. Many especially impactful roles require specific skills. If none of these roles are currently a great fit for you, but one could be if you developed the right skills, it can be worth it to take substantial time to do so. You should use 80,000 Hours to figure out what your best career is and how to get there, not what “the” best careers are. I haven’t seen people talk that much about the last point, so I spend the most time on it. Over-representation of EA organizations in 80,000 Hours content Given unlimited resources, 80,000 Hours could catalog every job opportunity that might be someone's best option, and then direct that person toward it. But 80,000 Hours is a small team, and has only been around for 7 years. Because of this, their ideas and recommendations should be treated as tentative and growing over time. Not only that, they are growing outward from the knowledge most central to EA. This means that 80,000 Hours is less likely to know about, and thus less likely to recommend, opportunities that are less familiar within the EA community. It will be rare for an opportunity at an EA organization to escape their notice. But many great jobs in the wider world never come to 80,000 Hours' attention, and when they do, there may be no time to look into them. Thus, opportunities at EA organizations are more likely to be featured -- in write-ups, in the job-board, in coaching advice -- than opportunities at unaffiliated organizations that are less familiar to the EA community. And this will be the case even if the roles at the less familiar organizations have higher potential impact. The contrast between career paths that 80,000 Hours explicitly recommends and those it doesn't often reflects differences in those paths’ effectiveness, but sometimes it just reflects differences in how much they've been vetted. Just as GiveWell's recommendations might be missing an effective nonprofit because they haven't yet looked into it, so might the 80,000 Hours job board be missing many promising roles for high-impact work. And this is more likely when the role or the problem it addresses is less familiar to the EA community, and so less likely to be researched by the 80,000 Hours team. Talk of talent gaps One thing the original Forum poster emphasized is that because they had heard there were “talent gaps” in the EA community, they thought getting a job at an EA organization would ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Invertebrate Welfare Cause Profile , published by Jason Schukraft on the Effective Altruism Forum. Executive Summary More than 99.9% of animals are invertebrates. There is modest evidence that some large groups of invertebrates, especially cephalopods and arthropods, are sentient. The effective animal activism community currently allocates less than 1% of total spending to invertebrate welfare. That share should rise so that we can better understand invertebrate sentience and investigate the tractability of improving invertebrate welfare. Introduction and Context This post is the tenth in Rethink Priorities’ series on invertebrate welfare. In the first post we examine some philosophical difficulties inherent in the detection of morally significant pain and pleasure in nonhumans. In the second post we discuss our survey and compilation of the extant scientific literature relevant to invertebrate sentience, as well as the strengths and weaknesses of our approach to the subject. In the third post we explain some anatomical, evolutionary, and behavioral features potentially indicative of the capacity for conscious experience in invertebrates. In the fourth post we explain some drug responses, motivational tradeoffs, and feats of cognitive sophistication potentially indicative of the capacity for conscious experience in invertebrates. In the fifth post we explain some learning indicators, navigational skills, and mood state behaviors potentially indicative of the capacity for conscious experience in invertebrates. The sixth post announces our Invertebrate Sentience Table. In the seventh and eighth posts, we present our summary of findings by feature and by taxa. The ninth post asks what we can learn about sentience from examining process that operate unconsciously in humans. In this post we apply the standard importance-neglectedness-tractability framework to invertebrate welfare to determine, as best we can, whether this is a cause area that is worth prioritizing. We conclude that it is. In a separate post, slated to be published next month, we present and examine the best arguments against our analysis. What Is Invertebrate Welfare? Invertebrates[1] comprise an enormous and diverse array of animals, from nematodes and earthworms to jumping spiders and jellyfish, crabs and krill to cuttlefish and cockroaches. Because invertebrates are a large and heterogeneous class of animals, there are few things that can be said about invertebrates in general (other than that they are animals that lack a backbone). Moreover, it is uncertain which (if any) invertebrates have the capacity for valenced experience,[2] so it is unclear whether these animals have a welfare. Thus, the term ‘invertebrate welfare’ is inevitably misleading.[3] Using the term to denote a cause area is something of a terminological simplification. If invertebrate welfare were a mature field, it would encompass perhaps dozens of distinct and unrelated interventions.[4] A campaign to promote the use of humane insecticides is quite different in kind from a campaign to promote strict laboratory standards for the treatment of octopuses.[5] What the interventions have in common is that they concern a group of animals whose welfare has historically been ignored. When we consider the arguments for and against prioritizing invertebrate welfare as a cause area, what we are considering is whether we should prioritize learning more about this group of animals. At this early stage, supporting the cause of invertebrate welfare means supporting additional research on invertebrate sentience, advocacy strategies, and cost-effective interventions. Opposing the cause means de-prioritizing this research. It’s possible to support the cause now, and, as the results of the additional research come in, later oppose the cause. Complicati...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Space governance is important, tractable and neglected , published by Tobias_Baumann on the Effective Altruism Forum. Summary I argue that space governance has been overlooked as a potentially promising cause area for longtermist effective altruists. While many uncertainties remain, there is a reasonably strong case that such work is important, time-sensitive, tractable and neglected, and should therefore be part of the longtermist EA portfolio. I also suggest criteria for what good space governance should look like, and outline possible directions for further work on the topic. What is space governance? It’s plausible that humans, or their successors, will eventually be able to colonise space. There are already various Mars missions, and future technological advances might make large-scale colonisation economically feasible. Space governance encompasses the laws, rules, norms and institutions that structure interactions in space, as well as mechanisms that are used to establish and enforce those. For the purposes of this post, we’re interested in a subset of space governance that I will call long-term space governance. Long-term space governance refers to the processes of interaction and decision-making among the actors involved in the large-scale settlement of space. Space colonization is currently not well covered by existing governance mechanisms. The most significant treaty in internal space law is the Outer Space Treaty, signed in 1967, which establishes that space shall be free for exploration and use by all nations, but that no nation may claim sovereignty of outer space or any celestial body.[1] Subsequent efforts to establish more comprehensive rules, such as the Moon Treaty (which grants jurisdiction over celestial bodies to the international community), have largely failed to achieve widespread assent. Therefore, we currently lack a coherent global framework for space governance. As of now, space is a free-for-all.[2] This is particularly true for challenges that arise in the context of humanity expanding beyond Earth: large-scale settlements in space are currently infeasible, so much of the existing debate centers on more immediate concerns (e.g. related to satellites or exploration of space). The work I have in mind aims to replace the current state of ambiguity with a coherent framework of (long-term) space governance that ensures good outcomes if and when large-scale space colonisation becomes feasible. In the following, I will argue that such work is important, tractable, and neglected. Importance The case for the importance of space governance is straightforward: it directly affects astronomical stakes. On a cosmic scale, Earth is a tiny point in a vast universe containing hundreds of billions of galaxies. Our own galaxy, the Milky Way, already contains at least 100 billion planets. So, while space governance is not fundamentally different from existing governance problems, it takes place on a scale never before seen in human history. Also, the range of possible outcomes is huge. The right space governance regime could enable an outcome that is very good from (almost) every perspective - through positive-sum cooperation and compromise between the relevant actors, combined with the vast amount of resources that an intergalactic civilisation can access. (Cf. Eric Drexler’s Paretotopia.) On the other side of the spectrum, escalating conflicts and warfare on a cosmic level could cause actors to inflict unimaginable horrors on each other, resulting in suffering on an astronomical scale. That said, one could object that anything we can do now will be overturned in the future, rendering our efforts irrelevant. In particular, one might expect transformative AI to happen relatively soon (which may be the trigger for large-scale space colonisation), and power...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Doing good is as good as it ever was, published by Denise_Melchin on the Effective Altruism Forum. Summary: most effective interventions to do good are still roughly as high impact as they were a few years ago. [1] Unfortunately, some people in the EA community don’t feel as happy about the amount of good they can do as they did in the past. This is true even when the amount of good they are doing or can expect to do hasn’t decreased. While I think there are other sources of unhappiness with doing good, I am going to discuss adaptation to an increased expectation of the amount of good we can do as a major contributor to this problem. The original prompt to do good from the EA community was: did you know that with just giving 10% of your income you can save a life or even multiple per year? But long-termism and the astronomical waste argument have shifted the community towards expecting to personally be able to accomplish a much larger amount of good. Anything less feels insufficient to many. The community and the individuals within have adapted to this higher expectation. For the majority of people, this expectation to do an existential amount of good does not materialise, and so they feel disappointed. But that’s silly. As a first example, we can still save lives with only a small fraction of our income. Saving lives has not become any less tremendously important. Over 200,000 children under 5 still die of malaria each year. I am concerned that as people have become disappointed with not living up to their hopes of possibly saving billions of lives or fundamentally shaping the far future, they become disappointed with their ability to do good in general and give up. Nobody should give up for this reason. You can still do an amazing amount of good by saving lives. The same is true for other ways to do good. Factory farming is as big an issue as it was a few years ago, with dozens of billions of animals living in factory farms under dreadful conditions. Becoming vegetarian still saves over a dozen land animals in expectancy per year from suffering and death. The same is true in areas outside of EA’s traditional causes. If you have been a regular blood donor or working on solar panels, your efforts produce roughly as much value as they did in the past. Having learnt tools from the EA community to quantify these efforts doesn’t change the bottom line of actual impact, it just helps prioritising between options. This equally applies to work on long-termist problems. People working on AI Safety or biorisk might have had the hope to make critical contributions that might fundamentally shape the future, but reality shows these problems to be very hard. Most people working on them will only make a small contribution towards solving them and that can feel disappointing. But many of these small marginal contributions are necessary. Remember that the argument for long-termism is that people might be able to have more impact by focussing on global catastrophic risks or by shaping the long term future in some other way. Whether you agree with this premise or not, the argument for long-termism is not that you will have less impact in total by saving lives or other interventions now than previously assumed. This means that fighting factory farming and other do gooding efforts are as good and important as they ever were. In some sense, this is obviously true. Yet I do not have the impression that this feels true to people. If saving lives and other do gooding efforts now feel less good to you than they did when you first heard about EA, that probably means you have adapted to expecting to do a lot more good now. That’s terrible! Participating in the EA community should make you feel more motivated about the amount of good you are able to do, not less. If it makes you feel less motiv...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Food Crisis - Cascading Events from COVID-19 & Locusts, published by AronM on the Effective Altruism Forum. “There are no famines yet. But I must warn you that if we don’t prepare and act now – to secure access, avoid funding shortfalls and disruptions to trade - we could be facing multiple famines of biblical proportions within a short few months.” - Warning of the WFP (World Food Programme) Chief to the United Nations Security Council, 21 April 2020 Authors: Aron Mill, Sahil Shah with assistance from Max Carpendale Helpful feedback and discussions: ALLFED team, David Kristoffersson & Michael Aird (Convergence), and Denisa Pop ABSTRACT This is a longer read since we, the authors, haven’t seen much discussion in the EA community about the impacts from COVID-19 on global food security and therefore we thought it would be useful to provide an overview of the current situation and upcoming risks. If you are short on time please read the last section “Call to action: Food Crisis Handbook” and read the following key takeaways: There is currently a food crisis and it will get worse. It is expected that the number of people on the brink of starvation will double from 135 million to 260 million within the next few months. This crisis adds to already existing hunger issues, including the 821 million people who are already food insecure. There are 5 major areas to this crisis: Loss of food purchasing power, farmers facing disruption of capital, inputs and market access, global supply chain disruptions, trade policies restricting food exports and the worst locust plague in decades. In the last section is a call to action to contribute to a Food Crisis Handbook. Please take a look and see if you can help. 1. Why is there a food crisis? Despite sufficient global food stock (the 3rd highest in history), we are facing an imminent food crisis that threatens hundreds of millions of people. Why is this? A mixture of shocks affecting production, transport, prices and access affect every aspect of our food system. Many nations have issued lockdown measures to prevent the spread of COVID-19. This section will analyse the cascading effects of these lockdowns on food access. Most affected is food purchasing power and accessibility in less developed countries (LDCs). In these regions between 50 and 90% of the workforce is part of the informal sector (ILO). These people are often unbanked, lack social protection measures and get paid on a day-by-day or week-by-week basis. Due to the lockdowns, their source of income is gone. Without any savings, they are unable to afford food, and risk starvation. Due to travel restrictions and self-isolation, farmers, which can be highly dependent on seasonal workers, are lacking the labour to harvest their fields and transport their yields from the rural areas to the markets. Farmers who are used to this supply chain lack sufficient storing capacities, meaning that one rain can destroy whole harvests, if the crops don’t rot on the fields in the first place without being gathered. Similar events have also been observed in more developed nations, where the demand for long lasting foods like rice or pasta has gone up while the demand for fresh vegetables has shrunk, leading to vast spoilage of harvests. Expanding the scope to a more holistic view, we can see similar disruptions to the global food system, which is heavily interconnected, with almost every region in the world depending on imports and exports. Many ports around the world have declared restrictions, like 14 day quarantines for vessels coming from COVID-19 affected regions. This causes significant delays in the global supply chain, since shipping makes up over 90% of the global trade. Additionally, port-workers might quarantine at home or fear off-loading cargo due to COVID-19 related health risks...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Report on careers in politics and policy in Germany , published by careersthrowaway on the Effective Altruism Forum. There is a German version of this post at the bottom. If you're interested in talking to me about any of this, message me on this forum or send an email to careersthrowaway@protonmail.com. I publish this anonymously since there are downsides to being perceived as very strategic about one’s career choice outside of this community. Summary Careers in and around the German federal government can be very influential, as Germany has significant international weight. I recommend that students considering such a career should get involved in party politics, apply for scholarships from party-affiliated foundations, complete relevant internships, and study law. The executive branch dominates the political system in Germany. Think tanks in Germany are (still) quite academic. The political culture in Germany is characterized by legalism, consensus, and a lot of internal coordination. A good network is indispensable for all political or policy-related careers. I distinguish between three paths: (1) civil service, (2) party-politics, (3) external advisors. (1) Civil service The influence of civil servants can be considerable since government policy is largely shaped by the administration. They often draft legal norms, speeches, press releases, etc. middle management positions have a lot of power. Prerequisites for Höhere Dienst (highest civil service track) are at least 300 ECTS (10 semesters). The most sought-after candidates are fully qualified lawyers ("legal monopoly"). Entry positions are very competitive. Lateral entry is rare. It is advisable to work in different departments, especially in the Stabsabteilungen (departments associated with ministerial leadership). Appointments to top positions are influenced by political considerations. So party affiliation or proximity and networks can be decisive. Generalists do well in the civil service. The best civil servants are distinguished by their political intuition and political communication skills. They also need patience, perseverance, resilience, and high intrinsic motivation. Mastering "office politics" is important. (2) Party-politics I distinguish between decision-makers (usually members of the German Bundestag) and advisors/aides. The latter can again be split into two different roles: (1) strategy/communication aides of individual top decision-makers; (2) specialist policy advisors for Fraktionen (parliamentary groups). Members of the Bundestag (MdB): They have influence through the legislative process and their public platform. They gain a lot of power through appointments to leadership positions in the Fraktionen and executive offices in government or the administration. The most common way to become an MdB is the slow advance through the party structures ("Ochsentour"). Lateral entries are rare. To succeed, you need to excel at building political alliances and majorities. You should also be able to give the impression of being down-to-earth. You need "political intuition and skill". Good manners, media skills, etc. are also required. Subject matter competence is secondary. For top-level politics, you might need a quality that is best described as "will to power." It refers to the determination to take risks and sacrifices in order to get ahead. Strategy/communication aides of individual top decision-makers: The influence as a close aide is considerable but depends decisively on the power of the decision-maker they advise. Such aides often follow the decision-makers they advise to their appointed positions. So the best strategy seems to be to gain the trust of "rising stars" within the party. In such a role, you do whatever needs to be done, which usually requires a generalist profile. You coordinate ne...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Using Subjective Well-Being to Estimate the Moral Weights of Averting Deaths and Reducing Poverty , published by MichaelPlant, JoelMcGuire, ClareDonaldson on the Effective Altruism Forum. Write a Review [Edit: 11/02/2021: changed how results were calculated in response to Aidan's comments.] [Edit: 03/09/2020: a few minor typos corrected.] Summary[1] To determine how to do good as cost-effectively as possible, it is necessary to estimate the value of bringing about different outcomes. We briefly outline the recent methods GiveWell has used to do this. We then introduce an alternative method – Well-Being Adjusted Life-Years, or ‘WELLBYs’ – and use it to estimate the values of two key inputs in GiveWell’s analysis: doubling consumption for one person for one year and averting the death of a child under 5 years old. On the WELLBY approach, outcomes are assessed in terms of their impact on subjective well-being – here, we use self-reported life satisfaction. Our primary aim is to show that the WELLBY approach could be used, rather than that it should be used. Our estimate of the relative value of the two outcomes should be taken as preliminary rather than definitive. We estimate the effects of doubling consumption using evidence from randomised controlled trials of cash transfers in Kenya conducted in collaboration with GiveDirectly. The total effect of the transfers is calculated by inferring an annual decay in life satisfaction. We include intra-household spillovers but exclude, due to mixed evidence, inter-household effects[2]. To account for uncertainty in our model, we input 90% subjective confidence intervals and run Monte Carlo simulations. The value of saving a life to the person whose life is saved is estimated on two philosophical views of death: deprivationism (the disvalue is the total lost life satisfaction) and the time relative interest account (TRIA) (the disvalue is total lost life satisfaction, discounted by the psychological connectedness to one’s future self). In effect, deprivationism holds it’s better to save 2-year-olds than 20-year-olds; TRIA the reverse. We also assess the effect of grief on family members using life satisfaction data. These estimates rely on certain (implicit) philosophical assumptions. We note how different assumptions would substantially change the results and reduce the relative value of saving lives. These issues are separate from how or whether to use WELLBYs; given different assumptions, one would simply calculate the WELLBYs differently. Our task is only to highlight the implications of (some) theories, rather than evaluate them. Our model estimates that the value ratio of averting the death of an under-5 to doubling consumption of one person for one year is 154:1 on deprivationism and 33:1 on TRIA. For reference, GiveWell currently uses a ratio of 100:1[3], based on a staff aggregate of 47:1 and an estimate of 230:1 from IDinsight’s beneficiary preference survey (described in the main text).[4] We close by setting out various uncertainties with the WELLBY estimate that are tractable with further research: the effects of cash transfers over time; spillover effects (of cash transfers and of deaths); the location of the ‘neutral point’ equivalent to non-existence; and the impacts assessed in terms of happiness rather than life satisfaction. Introduction There are many ways to help others. Anyone allocating resources towards this end – ranging from policy-makers disbursing government budgets to individuals giving to charity – must choose between programmes with different outcomes, such as averting deaths, alleviating poverty, enhancing education and improving mental health. Comparing the value of these outcomes is a difficult, but necessary, task if we want to use these resources to benefit others as much as possible. Much of...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: What drew me to EA: Reflections on EA as relief, growth, and community , published by vaidehi_agarwalla on the Effective Altruism Forum. In this post, I want to share my outlook on discovering EA, and my early experiences in the community. For those who don’t know me, hello! My name is Vaidehi. I work on a few independent community projects such as the EA Hub and the EA Fellowship Weekend. I have a background in sociology and have done some work on understanding the careers advice landscape and community building theory. I share this for a couple of reasons: I haven't seen some of these points discussed a lot, at least not publicly and/or recently I've found it useful to read about other people's different experiences, particularly when I was newer to the community The following is a series of related but somewhat unordered thoughts. EA as relief There seems to be a somewhat prevalent experience that people feel overwhelmed or guilty about not doing enough when they first discover EA.[1] I have never felt this way. As someone from a developing country, it's normal to be accustomed to many of the inequalities of the world. Seeing the contrast between Singapore (where I grew up) and India it was easy to understand, more viscerally, the suffering present, and the scale of that suffering. What always motivated me was that my life was really good in most ways, and many others’ lives were not. It seems natural that we should spend most of our resources fixing that until the injustice is rectified. Seeing the inefficiencies and limitations of many charities first-hand growing up, it was obvious to me that this should be done as effectively as possible. Discovering GiveWell was a relief. Not only was there an entire organisation that actually cared about having an impact, but through GiveWell, I also found there was the whole field of developmental economics dedicated to it, with research organizations like JPAL and on-the-ground charities. And later, through 80,000 Hours, I learnt that there was already a framework for evaluating different causes and career paths and planning your carer strategically - a convenient starting point to build off of, rather than trying to figure it all out from scratch. On a related note, I was surprised and disappointed by the lack of discussion about the developing world in my American undergraduate college, and frustrated by the prevalent discourse norms. In EA, I found a group of people who cared about the whole world, not just their small part of it, and who didn’t need to agree on everything be part of the same community. Most of all, what made EA compelling to me was that people actually cared about the pursuit of truth - about getting things right even when it wasn’t convenient. GiveWell's mistakes page was a really important example of this in action. Why would an organization - and a charity at that - put their mistakes out in the open, unless they really cared about improving and doing better? I still had a lot of questions and concerns, but what kept me engaging was the fact that whenever I’d have a doubt, I’d dig deeper and find that there was more to the conversation. (I still have concerns, but now I’m working to improve them directly.) As an aside, I am also not very motivated by the opportunity framing of EA - the idea that one cause or intervention is 100 or 1000 times better than another, which creates an exciting opportunity to act. To me, a little better is still better. It doesn't really matter if I help 1 or 10 or 10,000 beings, as long as I help as many as I can. I don't care about whether a problem is difficult, or whether there are low hanging fruits. If the problem is important enough, then it's worth trying to solve. Of course, if there are good, or even great, opportunities, it’s a no-brainer to pursue them. I’ve al...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: The EA Forum Editing Festival has begun! , published by Aaron Gertler on the Effective Altruism Forum. Over the last few months, we’ve been ramping up the creation of new articles for the EA Forum Wiki. (Some of these articles can be applied to posts: we call those “tags”.) Today, we’re starting the EA Forum Editing Festival. The festival is an all-out blitz of tagging and article editing, with the goal of: Applying as many useful tags as possible to as many posts as possible, so that tags become a much better way to find relevant content. Creating and updating Wiki articles, so that someone interested in a topic can reliably get a good summary and know what to read next. Improving the way the whole system is organized — including the layout of our tag portal, which tags even exist, and the way posts are ranked within individual tags. To kick things off, we’ve released an update to the tag portal, showing almost every article on the Forum (not just tags — we may change the title) in a collection of tables. While the new portal isn't complete, and we may end up reorganizing it entirely, we hope it inspires you to find an article to edit, create a new article, or suggest improvements to the portal itself. People often say they’re looking for a way to do some small, useful thing for the community in their spare time. This is one such way. You’ll make the Forum better with every tag you apply, every edit you make, and every suggestion you share. How long is the festival? One month. Until Friday, May 7th, we’ll consider any edits, tags, etc., to be part of the festival. This means they’ll make you eligible for fabulous prizes. If you’ve already been doing lots of editing and tagging — good news! Your past efforts have not gone unnoticed, and we’ll consider them when prizes are given. Why hold a festival? What’s with all the hullabaloo? At the moment, most of the tagging and article editing that now happens on the Forum comes from a very small number of people. We really appreciate their work, but we also want to get more people in the habit of adding tags, editing articles, and generally taking part in the crowdsourced bits of the Forum. So we’re writing a loud, flamboyant post, pinning it to the top of the frontpage, and giving away fame, glory, and money. We hope the festival will help the Forum settle into a new pattern of broad participation. If you don’t do much editing or tagging yet, now’s the time! See below for ideas on how to start. Why is this important? Improving the Wiki See my previous post. In short, we’d like people to have access to a collection of material that sums up lots of important bits of EA knowledge: philosophy, cause areas, organizations, even memes. Pablo is working full-time to generate and organize content, but he can only write so much — a really good wiki has to be a community effort. Tagging posts There are new posts on the Forum every day. And every day, it becomes just a bit harder to catch up on everything that came before, and a bit harder to feel as though you’ve read the “right” content on a given topic. Tags make this better. Ideally, a tag will: Summarize a concept well enough to give someone a basic understanding Gather together many posts that can help them learn about the concept Sort those posts according to their relevance I’ve had many people tell me they feel overwhelmed when they try to explore EA. Our massive backlog of content has been a barrier. But properly tagged and sorted, it can also be one of our greatest strengths. And you can help to make that happen! How can you help? As I said before, every tag and every edit helps. The Forum Wiki has no perfect articles, and few posts have every tag they should. That said, here are some easy ways to get involved: Tagging Tag your own posts with as many relevant tags as you can...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Data on forecasting accuracy across different time horizons and levels of forecaster experience, published by Charles Dillon on the Effective Altruism Forum. Key Points Forecasting well is a valuable skill for many purposes and people, including for EA organisations aiming to identify which areas they should focus on and what the outcomes of various initiatives would be. There is a limited public record of people making scored forecasts over time horizons greater than ~1 year. Here I use data from PredictionBook and Metaculus to study performance of predictions over different time horizons. I also looked at performance between users with different levels of forecasting practice. When looking at individual predictors, it seems that a very common failure mode among newer or less dedicated predictors is overconfidence, and that it is more prevalent than underconfidence across most subgroups. Across both PredictionBook and Metaculus, there seemed to be a significant bias towards overestimating the chances of positive resolution. This effect seemed to get stronger as time to resolution increased. At least in the PredictionBook data, there was some weak evidence to suggest prediction performance improves with making more predictions, but there were too many confounding factors here to draw any confident conclusion. The conclusions I was able to draw from this were limited, and working to improve this by expanding the amount and quality of data available for analysis like this seems worth doing. This post draws a lot on niplav's Range and Forecasting Accuracy, not least for much of the code used to extract the PredictionBook forecasts, and also in identifying the most promising sources of useful data. I think that this post is probably most useful to individuals making forecasts being aware of common failure modes and attempting to learn from them, and informing decision makers about these failure modes also, rather than attempting to provide those looking to use forecasts with e.g. a transform they should apply to long term forecasts. Background There has been a great deal of interest in forecasting in the EA community in recent years, particularly with the prominence of longtermist thinking. It is clearly of great interest that we be well equipped to make predictions about future events, and to understand the accuracy and failure modes of such predictions. Additionally, many of the questions we care most about will have long time horizons, therefore any evidence we can gain which helps us become better at making better long term predictions in particular could be quite valuable (see also Muehlhauser, 2019). Some potential tools for making longer term forecasts include: extrapolating from shorter term forecasts expected to be correlated to the long term question - this to an extent transforms the question to a different problem, that of forecasting which intermediate milestones might usefully predict our ultimate questions, and how well. assuming that those who are well calibrated in the short term will also do well in the long term, and using their forecasts. The second point here is probably to a certain extent unavoidable, as most forecasters will get few totally independent iterations of making long term forecasts in their lifetimes. One could potentially make hundreds of 10 year predictions now, but lessons cannot be drawn directly from these for 10 years, and if the wrong lessons are learned, it could take another 10 year iteration to realise that. In addition, these hundreds of forecasts may not be independent. I think many forecasts made over longer time horizons will be subject to errors from the same sources, due to society wide effects such as, for example, rates of economic and technological development, a more/less peaceful climate for international relations,...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Gifted $1 million. What to do? (Not hypothetical), published by BenWilder on the Effective Altruism Forum. I recently was unexpectedly gifted a little less than $1 million in stock. I am speaking with a financial advisor, but I want EA advice. What are my most important next steps? I want to be part of doing the most good possible for living, feeling beings before I die. I know this is very personal. It is different for each situation. What are the most important factors to keep in mind? I am open to radical thinking, but only if it can be practically implemented by an ordinary imperfect person. Thank you for your time--I am serious about this. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Wikipedia editing is important, tractable, and neglected, published by Darius_M on the Effective Altruism Forum. 1. Key Takeaways The case for Wikipedia editing in a nutshell: Wikipedia articles are widely read and trusted, there is much low hanging fruit for improvement, and editing Wikipedia has low barriers to entry and is relatively low effort. Consequently, improving a Wikipedia article may benefit the reasoning and actions of its thousands, and often millions, of readers. Moreover, since Wikipedia is a global public good, improvements to Wikipedia are likely undersupplied relative to the socially optimal level. Careful prioritisation is crucial. Improving or creating some Wikipedia articles could easily be 100x to 1,000x as valuable as others. The key factors to consider for prioritisation are (i) pageviews, (ii) audience, (iii) topic, (iv) room for improvement, and (v) language. Respecting Wikipedia community rules and norms is key. The Wikipedia community is wary of people making edits to promote a particular idea, person, or organisation, especially when there are relevant conflicts of interest. Consequently, edits that violate Wikipedia rules and norms may be actively harmful and are likely to be deleted. However, there are currently still very many genuine gaps in the quality and coverage of Wikipedia articles, and filling these gaps tends to work well and is regarded highly. Contributing to or starting a WikiProject on an important topic may be valuable. A WikiProject is a group of contributors who want to work together as a team to improve Wikipedia. A WikiProject allows for more efficient collaboration, by providing a centralised place where interested editors can make plans and discuss proposals. There are self-interested reasons to edit Wikipedia. In particular, Wikipedia editing can be really fun, it is a great opportunity to learn more about a topic, it may help you improve your writing, and it may be a useful signal in some communities or for some professional opportunities. Some EA-relevant content is better suited to a specialised EA Wiki than to Wikipedia. For instance, content that is too niche to meet Wikipedia’s notability requirements. Please note that much of this post is not original, drawing on existing writing (see the “Relevant Resources” section). However, I felt it was important to add to, synthesise and popularise these ideas here on the forum. Any mistakes are my own. 2. Respecting Wikipedia Rules Before giving the positive argument for Wikipedia editing, I want to stress the importance of becoming familiar with and respecting the rules and norms governing Wikipedia editing. Lack of familiarity with the relevant rules and norms is one of the main reasons editors have their contributions reverted. The most important ones include: Neutral point of view: “All Wikipedia articles (...) must be written from a neutral point of view, representing significant views fairly, proportionately and without bias.” Verifiability: “Material challenged or likely to be challenged, and all quotations, must be attributed to a reliable, published source.” No original research: “Wikipedia does not publish original thought (...) Articles may not contain any new analysis or synthesis of published material that serves to advance a position not clearly advanced by the sources.” Notability: “Article and list topics must be notable, or “worthy of notice”. (...) if no reliable, independent sources can be found on a topic, then it should not have a separate article.” Conflict of interest (COI): “COI editing involves contributing to Wikipedia about yourself, family, friends, clients, employers, or your financial and other relationships. (...) COI editing is strongly discouraged on Wikipedia.” Paid-contribution disclosure: “If you are paid in any way for contributin...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: In defence of epistemic modesty , published by scottweathers on the Effective Altruism Forum. A hugely popular EA Forum post this past winter illustrated the tremendous difficulty in getting hired by effective altruist organizations. This week at Berkeley REACH, Kelsey Piper highlighted a few shifts in the EA community that seem relevant. As EA has become more focused on big-picture ideas, we've become less excited by the prospect of giving ~10% of your income every year, for example by saving lives in developing countries. Still, it's pretty incredible that that's something most people can do! In the vein of high-impact, accessible opportunities, Kelsey also noted that Impossible Foods has ~30 openings at the moment, many of them doable by EAs without even requiring any specialized skills. Do you live in the San Francisco bay area? Can you do manufacturing work? Then there's a job there for you. To widen this a bit, there are frankly a bajllion jobs right now working on plant-based and cell-based meat. So I've highlighted a few below, focusing on breadth of companies and less technical positions. Happy applying! Seattle Food Tech: Plant-Based Meat Production (Part-time/Full-Time, Seattle, WA) Seattle Food Tech: People and Culture Manager (Seattle, WA) Impossible Foods: Chief of Staff to the CEO (Redwood City, CA) Impossible Foods: Lead Processing, 2nd shift (Oakland, CA) Beyond Meat: Facilities & Maintenance Coordinator (El Segundo, CA) Beyond Meat: Front Desk Specialist (El Segundo, CA) Califia Farms: Production Lead (Bakersfield, CA) Califia Farms: Data Engineer (Bakersfield, CA) Huel: Head of Sales (New York, NY) Ginkgo Bioworks: Software Architect (Boston, MA) Ginkgo Bioworks: Program Management Lead (Boston, MA) Daiya: Brand Manager (Vancouver, Canada) Hodo: Production Worker (Oakland, CA) Miyoko's: Sanitation Associate (Petaluma, CA) Quorn: Logistics Coordinator (Stokesley, United Kingdom) Ripple: Financial Analyst (Berkeley, CA) Memphis Meats: Research Associate (Berkeley, CA) JUST: Research Associate, Food Science (San Francisco, CA) Mission Barns: Clean Meat R&D Intern (Berkeley, CA) Perfect Day: Supply Chain Manager (Emeryville, CA) Clara Foods: Process Associate (South San Francisco, CA) Finless Foods: Senior Scientist (Berkeley, CA) Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: There are a bajillion jobs working on plant-based foods right now , published by scottweathers on the Effective Altruism Forum. A hugely popular EA Forum post this past winter illustrated the tremendous difficulty in getting hired by effective altruist organizations. This week at Berkeley REACH, Kelsey Piper highlighted a few shifts in the EA community that seem relevant. As EA has become more focused on big-picture ideas, we've become less excited by the prospect of giving ~10% of your income every year, for example by saving lives in developing countries. Still, it's pretty incredible that that's something most people can do! In the vein of high-impact, accessible opportunities, Kelsey also noted that Impossible Foods has ~30 openings at the moment, many of them doable by EAs without even requiring any specialized skills. Do you live in the San Francisco bay area? Can you do manufacturing work? Then there's a job there for you. To widen this a bit, there are frankly a bajllion jobs right now working on plant-based and cell-based meat. So I've highlighted a few below, focusing on breadth of companies and less technical positions. Happy applying! Seattle Food Tech: Plant-Based Meat Production (Part-time/Full-Time, Seattle, WA) Seattle Food Tech: People and Culture Manager (Seattle, WA) Impossible Foods: Chief of Staff to the CEO (Redwood City, CA) Impossible Foods: Lead Processing, 2nd shift (Oakland, CA) Beyond Meat: Facilities & Maintenance Coordinator (El Segundo, CA) Beyond Meat: Front Desk Specialist (El Segundo, CA) Califia Farms: Production Lead (Bakersfield, CA) Califia Farms: Data Engineer (Bakersfield, CA) Huel: Head of Sales (New York, NY) Ginkgo Bioworks: Software Architect (Boston, MA) Ginkgo Bioworks: Program Management Lead (Boston, MA) Daiya: Brand Manager (Vancouver, Canada) Hodo: Production Worker (Oakland, CA) Miyoko's: Sanitation Associate (Petaluma, CA) Quorn: Logistics Coordinator (Stokesley, United Kingdom) Ripple: Financial Analyst (Berkeley, CA) Memphis Meats: Research Associate (Berkeley, CA) JUST: Research Associate, Food Science (San Francisco, CA) Mission Barns: Clean Meat R&D Intern (Berkeley, CA) Perfect Day: Supply Chain Manager (Emeryville, CA) Clara Foods: Process Associate (South San Francisco, CA) Finless Foods: Senior Scientist (Berkeley, CA) Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Database of existential risk estimates, published by MichaelA on the Effective Altruism Forum. This post was written for Convergence Analysis, though the opinions expressed are my own. This post: Provides a spreadsheet you can use for making your own estimates of existential risks (or of similarly “extreme” outcomes) Announces a database of estimates of existential risk (or similarly extreme outcomes), which I hope can be collaboratively expanded and updated Discusses why I think this database may be valuable Discusses some pros and cons of using or making such estimates Key links relevant to existential risk estimates Here’s a spreadsheet listing some key existential-risk-related things people have estimated, without estimates in it. The link makes a copy of the spreadsheet so that you can add your own estimates to it. I mention this first so that you have the option of providing somewhat independent estimates, before looking at (more?) estimates from others. Some discussion of good techniques for forecasting, which may or may not apply to such long-range and extreme-outcome forecasts, can be found here, here, here, here, and here. Here’s a database of all estimates of existential risks, or similarly extreme outcomes (e.g., reduction in the expected value of the long-term future), which I’m aware of. I intend to add to it over time, and hope readers suggest additions as well. Here's an EAGx talk I gave that's basically a better structured version of this post (as I've now thought about this topic more), though without the links. So you may wish to watch that, and then just skim this post for links. The appendix of this article by Beard et al. is where I got many of the estimates from, and it provides more detail on the context and methodologies of those estimates than I do in the database. Beard et al. also critically discuss the various methodologies by which existential-risk-relevant estimates have been or could be derived. And Baum provides additional excellent commentary. In this post, I discuss some pros and cons of using or stating explicit probabilities in general. Why this database may be valuable I’d bet that the majority of people reading this sentence have, at some point, seen one or more estimates of extinction risk by the year 2100, from one particular source.[1] These estimates may in fact have played a role in major decisions of yours; I believe they played a role in my own career transition. That source is an informal survey of global catastrophic risk researchers, from 2008. As Millett and Snyder-Beattie note: The disadvantage [of that survey] is that the estimates were likely highly subjective and unreliable, especially as the survey did not account for response bias, and the respondents were not calibrated beforehand. Additionally, in any case, it was just one informal survey, and is now 12 years old.[2] So why is it so frequently referenced? And why has it plausibly (in my view) influenced so many people? I also expect that essentially the same pattern is likely to repeat, perhaps for another dozen years, but now with Toby Ord’s recent existential risk estimates. Why do I expect this? I originally thought the answer to each of these questions was essentially that we have so little else to go on, and the topic is so important. It seemed to me there had just been so few attempts to actually estimate existential risks or similarly extreme outcomes (e.g., extinction risk, reduction in the expected value of the long-term future). I’d argue that this causes two problems: We have less information to inform decisions such as whether to prioritise longtermism over other cause areas, whether to prioritise existential risk reduction over other longtermist strategies, and especially which existential risks to be most concerned about. We may anchor too strong...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Politics on the EA Forum, published by Aaron Gertler on the Effective Altruism Forum. With the U.S. presidential election cycle in full swing, we want to lay out the way we think about political discussion on the Forum. Political issues are clearly relevant to improving the world. However, in our experience, we’ve seen that partisan political discussion tends to have a strong polarizing effect on public forums; it consumes a lot of a community’s attention and can lead to emotionally charged arguments. Overall, we think the EA Forum will be healthier, and better-positioned to achieve its goals, if we limit the space given to political topics. We don’t plan to prohibit any content based on its political nature. However, the following types of post will remain in the “Personal Blog” category (meaning that they will not appear on the Forum’s homepage, but will appear in “All Posts,” in the author’s profile, and on any relevant tag pages): Posts advocating for or against a specific political candidate or group of candidates (e.g. “Why effective altruists should vote for candidate Y”) This policy also applies to posts which neutrally solicit opinions on a particular candidate, since those opinions are generally going to be advocacy for or against the candidate, which risks leading to the same issues. Posts discussing policy issues with only tenuous connection to the main EA cause areas (e.g. “What John Smith’s position on gun rights means for EA voters”) Some political content will continue to receive “Frontpage” categorization: Posts discussing general systems for evaluating any political candidate (e.g. “Candidate Scoring System, Third Release”) Posts discussing policy issues that are directly connected to core EA cause areas (e.g. this post on a campaign to boost Canadian development assistance) These policies aren't set in stone, and we'd welcome any feedback. (Also, we reserve the right to make exceptions in exceptional circumstances. For example, if the favored candidate of the "Destroy Human Civilization" party is leading the polls in a nuclear-armed nation, that seems to merit a Frontpage post about how to stop them.) Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: An introduction to global priorities research for economists, published by DavidBernard on the Effective Altruism Forum. Summary It’s difficult for aspiring economists to understand how they can contribute to global priorities research. This post shares a syllabus and extended literature for an introduction to global priorities for economists, provides background on the development of the syllabus, its use for a reading group, and advice to others who want to use it. The syllabus was designed with graduate students in mind, but advanced undergraduates will likely be able to get the relevant points from almost all papers. We hope this will be useful for aspiring economists who want to contribute to global priorities research but don’t know where to start. Link to syllabus Link to core readings folder Link to other EA/GPR syllabi For those who are just interested in economics literature relevant to global priorities research just follow the link to the syllabus above and ignore the rest of the post. If you want more information about what purpose the syllabus serves, how it came to be, and advice for using it for your own reading groups, read on. It probably makes most sense to read the syllabus alongside the 'Using the syllabus' section. I also recommend the generic Reading group guide for EA groups. Please contact me in the comments section or privately if you have any questions about running your own reading group based on this syllabus. Thanks to Aaron Gertler, Rossa O'Keeffe-O'Donovan, Philip Trammell, and Duncan Webb for feedback. Opinions and errors remain my own. Motivation Global priorities research (GPR) is concerned with the question ‘If our aim is to do the most good possible, from a totally impartial perspective, with limited resources, what should we do?’. Two fundamental fields in this endeavour are economics and philosophy. Since its inception, the Global Priorities Institute (GPI) has made progress in GPR research itself and the instrumental goal of developing GPR as an academic field. However, this progress is currently lopsided, with much more progress being made in philosophy. Most staff at GPI are philosophers (but they have recently hired their first two postdoctoral economists). All of the papers currently in the GPI Working Paper Series are philosophy papers (but they aim to add ~5 economics papers soon). A comment in a relevant EA Forum post: “One economics student told me that when reading the GPI research agenda, the economics parts read like it was written by philosophers”, also suggests that the economics side of GPR is less clear than the philosophy side (but the research agenda is currently being refreshed). Numerous academic EA/GPR courses have been run in philosophy departments, but as far as I can tell, none have been run in economics. The result of this state of affairs is that the budding philosopher is easily able to understand what the core texts, seminal papers and cutting edge articles are for philosophical global priorities research, while the budding economist is left with not much to go on. The philosopher has plenty of senior role models and potential supervisors to look to while the economist is unsure who they can speak to about their wacky cause prioritisation ideas. The subfields which GPR philosophy mostly relies on are ethics, decision theory and epistemology, while GPR-relevant economics is spread across a wide variety of subfields, relying on theory and empirics, and normative and positive approaches. The aim of this syllabus is to help partially solve these issues, by providing a framework and literature to introduce people to global priorities research through published articles in and around the economics literature. It is not a reading list for GPI’s current research priorities. It has a broader scope than GPI’s r...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: EA Survey 2020: Demographics, published by David_Moss on the Effective Altruism Forum. EA Survey 2020: Community Demographics Summary We collected 2,166 valid responses from EAs in the survey The composition of the EA community remains similar to last year, in terms of age (82% 34 or younger), race (76% white) and gender (71% male) The median age when EAs reported getting involved in the community was 24 More than two thirds (69%) of our sample were non-students and <15% were undergraduates. Roughly equal proportions of non-student EAs report being in for-profit (earning to give), for-profit (not earning to give), non-profit (EA), non-profit (not EA), government, think tank/lobbying/advocacy careers. More respondents seem to be prioritizing career capital than immediate impact Introduction The demographic composition of the EA community has been much discussed. In this post we report on the composition of the EA Survey sample. In future posts we will investigate whether these factors influence different outcomes such as cause selection or experience of the EA community. This year, we removed questions about religion, politics, and diet to make room for an additional set of requested questions. However, we intend to re-include these next year and at least every other year going forward. The normal caveats about not knowing the degree to which the EA Survey sample is representative of the broader EA population apply. Ultimately, since no one knows what the true composition of the EA community is, it is impossible for us to know to what degree the EA Survey is representative. We discuss these issues further here in a hosted dynamic document (with data, code, and commentary). In that document we investigate how key characteristics of our sample are sensitive to which source (e.g. EA Newsletter, Facebook link) referred participants to the EA Survey and to measures that seem like they may be proxies for participation rates (such as willingness to be contacted about future surveys). Note: full size versions of graphs can be viewed by opening them in a new tab. Basic Demographics Gender The proportion of respondents who were male, female or other was very similar (to within a percentage point) to last year. Race/ethnicity Our race/ethnicity question allowed respondents to pick multiple categories. We re-coded respondents based on whether they selected only one category or multiple. While around 83% of respondents selected ‘White’ (compared to 86.9% last year), some of these respondents also selected other categories. Taking this into account, around 75.9% of the sample selected only white. Age The EA community remains disproportionately young, with a median age of 27 (mean 29). Moreover, there is an extremely sharp dropoff in the frequency of respondents from around age 35. Around 80% of our respondents are younger than this age, which means that there are fewer respondents in our sample older than 34 than there are women or non-white respondents. Changes in Age over Time That said, as we noted , the average age of EA Survey respondents appears to have increased fairly steadily over time. This makes sense because EAs (like non-EAs) get one year older annually. However, this effect is counterbalanced by new EAs joining the movement each year, and these new members being younger than average. In this year’s survey, the average age of respondents was slightly lower than last year (though still higher than 2014-2015). Age of First Getting Involved in EA The age at which people typically first get involved in EA has previously been discussed (e.g. ). The median age when respondents reported having first gotten involved in EA was 24 (with a slightly higher mean of 26). Notably, while young, this is slightly older than the typical age of an undergraduate student (which is often tho...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Working in the U.S. helped us get more money to international recipients, published by GiveDirectly on the Effective Altruism Forum. This is a linkpost for/ Our U.S. COVID-19 response was based on a bet In April 2020, we launched Project 100, a U.S. COVID-19 response, in partnership with Propel and Stand for Children. To date, the program has delivered one-time $1,000 payments to over 178K Americans living in poverty, with the most recent round going out last week. For the past decade, our core mission has been to reach people living in extreme poverty. While many millions in the United States are in poverty, they’re typically not facing extreme poverty as it is officially defined (living below $1.90/day). We decided to launch the program given: the growing need we saw in the U.S. that could be met with cash the number of funders interested in getting cash to people in the U.S. who would not otherwise give internationally the opportunity to raise direct giving’s public profile beyond what we could do with our international programs alone Our bet, based on points 2 and 3, was that a justified U.S. cash program would also end up drawing in more funding for people living below the extreme poverty line internationally. We kept funds & attention going to our global work We continued to focus on driving attention to our global work and took precautions not to divert funds when setting up Project 100: We only allocated funds specifically donated to the U.S. program to American recipients. No other funding went to the program We tested and tracked whether donors who first gave to the U.S. would be interested in giving internationally with their future gifts We maximized press/social media attention on direct giving and ensured the press mentioned our international work wherever possible Our U.S. work helped make 2021 our best fundraising year yet for international recipients A year and a half on, the results suggest the bet has paid off. This has already been our strongest year raising funds for people living in poverty internationally with $138.8M YTD in 2021 versus $121.4M and $47.2M total raised for int’l recipients in 2020 and 2019, respectively. Beyond that: We’ve driven over $70M to international programs from donors who initially gave to U.S. projects — more than our revenue for any year before 2020 Our U.S. program had over 100 press mentions, helping to raise direct cash giving’s profile on the national and global stage We expect to reach even more international recipients by the end this year than last: We will continue to work in the U.S. We expect there to continue to be a legitimate need in the US that can be met with cash, be it after a catastrophic hurricane or in geographies that are chronically poor & under-resourced. We also know there will always be funders who are more focused on giving within the U.S. (perhaps some immutably, and some not). So, moving forward, we’ll launch U.S. programs that we think could both fill a real need and raise direct giving’s profile to drive more support to international recipients. This was a bet that we’re glad paid off. We’re proud to have helped 178K Americans living in poverty: Numbers as of Sept 13th, 2021. To hear more from recipients themselves, check out stories from Project 100 recipients and GDLive to hear from folks we’ve reached internationally. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: EA Communication Project Ideas , published by Ben_West on the Effective Altruism Forum. These are some small EA communication projects which I think independent EA's with reasonable understandings of EA and communication practices can do, without needing to be employed by an EA organization etc. They mostly come from random discussions I have with people and in general are not original to me. A twitter bot which tweets out forum articles [EDIT: This already exists] This could be based on parsing the forum RSS feed You could imagine a number of variants: only tweeting articles with >X karma, only tweeting those with a specific tag, only those from specific authors, etc. Could also tweet out links to EA newsletters, or parse them and tweet the individual articles linked therein Repurposing EAG videos Professional content studios squeeze the last drop of value out of every single piece of content they get: they put the full long video on YouTube for diehard fans, take short highlight clips and post them on Instagram, take key quotes and post them on twitter, put compilations on TikTok, etc. We have dozens (hundreds?) of hours of video from speakers at EAG, which generally doesn't get a ton of engagement on YouTube. Someone with editing skills and reasonable understanding of EA could repurpose this content in a bunch of different ways, without needing to come up with original ideas, write scripts, etc. Create posts to drive engagement e.g. after EAG create a thread on the Forum asking people to post their biggest takeaways from the event. Or you could do this on social media It would probably have to be combined with some proactive outreach to get people to post in order to be successful Make a map of EA Domain of Science created "map of X" for various fields. I honestly don't understand why these videos were so popular, but they are (the map of mathematics got 8.6 million views). You could imagine doing something similar for EA. Probably you should understand why the original videos were so popular though, if you’re going to replicate the success. Anna Riedl made a map of cognitive science and is interested in collaborating if you want to do this project. Make a scratch off list of EA reading Inspired by posters like this one which list famous novels, the intention being that you scratch off each novel as you read it You could create this for key EA reading, perhaps based on the readings listed in the handbook, or introductory program If you do this, let me know because CEA might be interested in providing the scratch off list to virtual program participants or Forum readers Anna is also interested in collaborating on this one Summarize prolific authors (Or run a contest, similar to Richard Ngo's bounty for compiling Robin Hanson's best posts.) "The collected works of (famous intellectual)" is a pretty popular format; the idea is to do something similar for prolific EA authors. A lot of EA thinkers have shifted their publications to target more esoteric audiences (e.g. academics), and, as a result, the median EA is less in touch with what e.g. Will MacAskill or Toby Ord are thinking than they were a few years ago. I think it will be more successful if it's just excerpts of the most important ideas though, rather than a complete compendium. Make podcasts that read out newsletters Robert Miles does this for the alignment newsletter, for example There are a bunch of other newsletters you could do this for Make a written intro similar to Ajeya's talk I ask many group organizers what they give to people who are new to EA as an introduction, and this talk from Ajeya is perhaps the most frequently mentioned thing. Organizers usually say that this talk does the best job within EA content of being "warm" and showing the passion and motivation for EA, in addition to the intellect...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: New book — Suffering-Focused Ethics: Defense and Implications , published by MagnusVinding on the Effective Altruism Forum. I have recently published a book on suffering-focused ethics (free PDF). The following is a short description: The reduction of suffering deserves special priority. Many ethical views support this claim, yet so far these have not been presented in a single place. Suffering-Focused Ethics provides the most comprehensive presentation of suffering-focused arguments and views to date, including a moral realist case for minimizing extreme suffering. The book then explores the all-important issue of how we can best reduce suffering in practice, and outlines a coherent and pragmatic path forward. An invitation for reflection I realize that some people will feel a strong aversion to suffering-focused views — I certainly did for years myself, and in many ways still do. Yet as I note in the introduction, I hope readers will see this book as an invitation and an opportunity to reflect on their priorities. I hope readers will agree that it is vitally important to get our priorities right, and that we should let our ethics be guided by open-ended reflection that remains charitable and fair even to views that seem disagreeable at first sight. The book in relation to EA: Core values are all-important yet strangely undiscussed I think reflection on values is crucial to effective altruism: our priorities will ultimately be determined by our core values. It is therefore quite puzzling to me why there are so relatively few discussions in EA centered around values, as opposed to specific causes and interventions. I can only speculate as to why this is the case. Is a certain value system tacitly assumed? Do we think questions concerning core values are not sufficiently relevant? Do we avoid discussing it because that is the status quo? Is it because we are too agreeable and afraid of causing division? Is it because discussing values is considered uncooperative? Is it because EA objectives tend to be framed in terms of "doing" rather than "reflecting"? I don't know. But whatever the explanation may be, I think it would be good if reflection on core values were given greater priority in EA; if it were considered a top cause, even. I think such reflection is likely to give us significantly more sophisticated views of which values we should steer by, and in turn update our practical priorities appreciably. I consider this a cooperative endeavor that we can all contribute to and benefit from, and my book represents an attempt to contribute to this project. (As for the notion that this project, including my book in particular, is uncooperative, I present various arguments to the contrary in Section 12.3 in my book.) Blurbs and table of contents Below are some blurbs for the book: “An inspiring book on the world’s most important issue. Magnus Vinding makes a compelling case for suffering-focused ethics. Highly recommended.” David Pearce, author of The Hedonistic Imperative and Can Biotechnology Abolish Suffering? “We live in a haze, oblivious to the tremendous moral reality around us. I know of no philosopher who makes the case more resoundingly than Magnus Vinding. In radiantly clear and honest prose, he demonstrates the overwhelming ethical priority of preventing suffering. Among the book’s many powerful arguments, I would call attention to its examination of the overlapping biases that perpetuate moral unawareness. Suffering-Focused Ethics will change its readers, opening new moral and intellectual vistas. This could be the most important book you will ever read.” Jamie Mayerfeld, professor of political science at the University of Washington, author of Suffering and Moral Responsibility and The Promise of Human Rights “In this important undertaking, Magnus Vinding me...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Why do social movements fail: Two concrete examples, published by NunoSempere on the Effective Altruism Forum. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org. Status: Time-capped analysis. Introduction. I look at two social movements which I think failed in their time: the Spanish Enlightenment (1750-1850), and the General Semantics movement (1938-2003). The first one is more similar to the effective altruism community, and the second one is more similar to the rationality community. Example 1: Why did the Spanish Enlightenment movement fail (1750-1850)? Why do I care about this movement? The Spanish Enlightenment was probably the closest thing you could find in Spain to the EA/rationality movements in the 18th century. I'm interested in seeing why it failed, and whether any lessons can be carried over. Note: Followers of Enlightenment values called themselves liberals / neoclassicists. Cause 1: The movement played politics, and lost. The French, under Napoleon, invaded Spain. The Enlightenment movement aligned itself with French revolution ideals and values, whereas the common folk hated the invasion. Liberals took positions of power in the new administration, for which they were perceived as traitors. After the French were defeated, most of the Spanish elite went into exile by royal decree (not only those who had worked with the French, but also those who had received offers). In general, liberals and their ideas were perceived as foreign to Spain; to a certain degree, because they were. Cause 2: Lack of organizational power? This seems to not have been the case. "Sociedades de amigos del pais", which roughly translate to "societies of friends of the country" seemed to be abundant. Several institutions which remain until this day were created: The Royal Spanish Academy (entrusted with the Spanish Language) (1713), the Royal Academy of History (1738), the Royal Botanic Gardens (1755), the Prado Museum (among the top 10 museums in the world) (1819). Cause 3: Their literary works were not that popular Example: Cartas marruecas (Letters from Morocco). A Spanish Noble and his Moroccan Noble friend talk about stuff pertaining Spain. While insightful and interesting for me, I do not believe that they were interesting for a majority of Spaniards. Example: Moratin, Spanish playwright, wrote 5 comedies. Consider his most popular comedy El sí de las niñas (The consent of the maidens) Pro: Wildly popular Was watched by 37 000 people, 25% of the population of Madrid at the time. Pro: The plot is about the right to choose; a 16 year old girl confronts an arranged marriage with a 59 old man. It may have had an effect on arranged marriages? Counterexample: Ramón de la Cruz. Started as neoclassicist, but couldn't make enough money. He tried seducing the public instead, which made him wildly popular. He wrote more than 300 theater pieces, which people liked but which weren't particularly Enlightened. Note: This is a 60x factor over the previous author. 300 vs 5 works. The Spanish public developed a strong dislike for moralizing works; works which pushed for the reader to, in some sense, become more virtuous. This remains today: A bright friend of mine gave her dislike of "prosa didáctica" (didactic prose) as the reason for not continuing to read HPMOR after the first few chapters. Anyways, there doesn't seem to be that clear a connection between their fiction and their actual work, unlike in Ayn Rand's Atlas Shrugged, or in Yudkowsky's HPMOR. Interestingly enough, the EA movement doesn't yet have such fiction, that I know of. Cause 4: Lack of permanent political power. Example: Carlos III, King of Spain, embraced Enlightened absolutism (everything for the people, nothing by the people), and is generally considered to have...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Why those who care about catastrophic and existential risk should care about autonomous weapons , published by aaguirre on the Effective Altruism Forum. (crossposted to Lesswrong here.) Although I have not seen the argument made in any detail or in writing, I and the Future of Life Institute (FLI) have gathered the strong impression that parts of the effective altruism ecosystem are skeptical of the importance of the issue of autonomous weapons systems. This post explains why we think those interested in avoiding catastrophic and existential risk, especially risk stemming from emerging technologies, may want to have this issue higher on their list of concerns. We will first define some terminology and do some disambiguation, as there are many classes of autonomous weapons that are often conflated; all classes have some issues of concern, but some are much more problematic than others. We then detail three basic motivations for research, advocacy, coordination, and policymaking around the issue: Governance of autonomous weapon systems is a dry-run, and precedent, for governance of AGI. In the short term, AI-enabled weapons systems will share many of the technical weaknesses and shortcomings of other AI systems, but like general AI also raise safety concerns that are likely to increase rather than decrease with capability advances. The stakes are intrinsically high (literally life-or-death), and the context is an inevitably adversarial one involving states and major corporations. The sort of global coordination amongst potentially adversarial parties that will be required for governance of transformative/general AI systems will not arise from nowhere, and autonomous weapons offer an invaluable precedent and arena in which to build experience, capability, and best practices. Some classes of lethal autonomous weapon systems constitute scalable weapons of mass destruction (which may also have a much lower threshold for first use or accidental escalation), and hence a nascent catastrophic risk. By increasing the probability of the initiation and/or escalation of armed conflict, including catastrophic global armed conflict and/or nuclear war, autonomous weapons represent a very high expected cost that overwhelmingly offsets any gain in life from substituting autonomous weapons for humans in armed conflict. Classes of autonomous weapons Because many things with very different characteristics could fall under the rubric of “autonomous weapon systems” (AWSs) it is worth distinguishing and classifying them. First, let us split off cyberweapons – including AI-powered ones – as being an important but distinct issue. Likewise, we’ll set aside AI in other aspects of the military not directly related to the use of force, from strategy to target identification, where it serves to augment human action and decision-making. Rather, we focus on systems that have both (some form of) AI and physical armaments. We now consider in turn these armaments’ target types, which we will break into categories of anti-personnel weapons, force-on-force (i.e. attacking manned enemy vehicles or structures) weaponry, and those targeting other autonomous weapon systems. Anti-personnel AWSs can be further divided into lethal (or grossly injurious) ones versus nonlethal ones. While an interesting topic,[1] we leave aside here non-lethal anti-personnel autonomous weapon systems, which have a somewhat distinct set of considerations.[2] We regard force-on-force systems designed to attack manned military vehicles and installations as relatively less intrinsically concerning. The targets of such weapons will, with considerably higher probability, be valid military targets rather than civilian ones, and insofar as they scale to mass damage, that damage will be to an adversary’s military. Of course if these weapon...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: New? Start here! (Useful links) , published by Aaron Gertler on the Effective Altruism Forum. If we should change something in this post, or add something new, please let us know. Thanks! This post lays out resources that might be valuable to Forum users, new or experienced. We want to keep it visible and up-to-date at all times. New to effective altruism? Learn the basics A lot of posts on the Forum might be confusing if you’re not very familiar with effective altruism (“EA”). If you’ve just begun to learn about EA, try these resources: The EA Handbook covers a range of core concepts in effective altruism. You can read the content on your own, or take an online course to discuss the ideas with other people. If you want to really dive in, this is a great place to start. If you'd prefer just one article, try this one. Giving What We Can, one of the first EA charities, has a great list of books, videos, essays, and podcasts. Ask a question If you have a specific question about EA, you should post it on the Forum: go to this page and click “New Question”. No matter how simple your question is, people here will be happy to help. Don’t be shy! New to the Forum? How to use the site You should start with “How to Use the Forum”, which covers ground rules and basic functionality. Introduce yourself People use our monthly “open threads” to introduce themselves and talk about what they’ve been doing. This is a great way to make your first comment! We also recommend writing a bio. Share your thoughts Another good way to start commenting: read posts, and provide feedback to the authors. Positive feedback can be especially valuable! Looking for something to read? Get the weekly email digest Every week, the Forum’s moderators send an email sharing some of their favorite recent posts. Sign up for the emails with this form. See posts that won prizes Some of the Forum’s best posts have been awarded the EA Forum Prize. Here’s a list of all the winning posts. Sort posts by topic Want something more specific? Look at our tag page, which sorts articles by topic. Read user-made sequences We also have sequences — lists of related posts that people have glued together for a better reading experience. View and sort every single post For a more “choose your own adventure” feel, check out the “All Posts” page, which lets you filter thousands of posts using different criteria. Want to write a post? Videos with advice on writing for the Forum As the Forum’s lead moderator, I’ve given a few talks on how to find good ideas and write good posts (EAGxVirtual, EA Student Summit). If you want motivation or brainstorming tips, you might find it helpful to skim through them. See what other people want Other places to find ideas: 1. “What posts do you want someone to write?” If you publish something based on a comment here, be sure to tell the commenter! This is also a good place to post if you want someone else to write something. 2. "A central directory for open research questions" Many people and organizations have made lists of questions they think could be very impactful to answer. This post contains most of those lists. If you want to explore a question you find here, consider messaging the person/org that originally asked the question, so you can ask for feedback on your plans. Consider an "Ask Me Anything" post "Ask Me Anything" posts (AMAs) are some of the Forum's most useful. Rather than guessing what writing would help readers, you can answer questions directly! AMAs can come from a wide range of people; you don't have to have a lot of experience in the EA movement or hold an EA-related job. See our guide to running an AMA for more information. Choose your post format (Markdown vs. CKEditor) The Forum's default editor (CKEditor) handles almost everything you'd want in a post... but not footnote...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Deference for Bayesians, published by John G. Halstead on the Effective Altruism Forum. Most people in the knowledge producing industry in academia, foundations, media or think tanks are not Bayesians. This makes it difficult to know how Bayesians should go about deferring to experts. Many experts are guided by what Bryan Caplan has called ‘myopic empiricism’, also sometimes called scientism. That is, they are guided disproportionately by what the published scientific evidence on a topic says, and less so by theory, common sense, scientific evidence from related domains, and other forms of evidence. The problem with this is that, for various reasons, standards in published science are not very high, as the replication crisis across psychology, empirical economics, medicine and other fields has illustrated. Much published scientific evidence is focused on the discovery of statistically significant results, which is not what we ultimately care about, from a Bayesian point of view. Researcher degrees of freedom, reporting bias and other factors also create major risks of bias. Moreover, published scientific evidence is not the only thing that should determine our beliefs. 1. Examples I will now discuss some examples where the experts have taken views which are heavily influenced by myopic empiricism, and so their conclusions can come apart from what an informed Bayesian would say. Scepticism about the efficacy of masks Leading public health bodies claimed that masks didn’t work to stop the spread at the start of the pandemic.1 This was in part because there were observational studies finding no effect (concerns about risk compensation and reserving supplies for medical personnel were also a factor).2 But everyone also agrees that COVID-19 spreads by droplets released from the mouth or nose when an infected person coughs, sneezes, or speaks. If you put a mask in the way of these droplets, your strong prior should be that doing so would reduce the spread of covid. There are videos of masks doing the blocking. This should lead one to suspect that the published scientific research finding no effect is mistaken, as has been confirmed by subsequent research. Scepticism about the efficacy of lockdowns Some intelligent people are sceptical not only about whether lockdowns pass the cost-benefit analysis, but even about whether lockdowns reduce the incidence of covid. Indeed, there are various published scientific papers suggesting that such measures have no effect.3 One issue such social science studies will have is that the severity of a covid outbreak is positively correlated with the strength of the lockdown measures, so it will be difficult to tease out cause and effect. This is especially in cross-country regressions where the sample size isn’t that big and there are dozens of other important factors at play that will be difficult or impossible to properly control for. As for masks, given our knowledge of how covid spreads, on priors it would be extremely surprising if lockdowns don’t work. If you stop people from going to a crowded pub, this clearly reduces the chance that covid will pass from person to person. Unless we want to give up on the germ theory of disease, we should have an extremely strong presumption that lockdowns work. This means an extremely strong presumption that most of the social science finding a negative result is false. Scepticism about first doses first In January, the British government decided to implement ‘first doses first’ - an approach of first giving out as many first doses of the vaccine as possible before giving out second doses. This means leaving a longer gap between the two doses - from 12 weeks rather than 21 days. However, the 21 day gap was what was tested in the clinical trial of the Oxford/AstraZeneca vaccine. As a result, we don’t ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: [Past Event] US Policy Careers Speaker Series - Summer 2021, published v on the Effective Altruism Forum. This event has passed. I'll leave the post up for the fake internet points for reference. This summer, in collaboration with DC-based members of our community, the Stanford Existential Risks Initiative (SERI) is organizing a virtual speaker series on US policy careers. Sign up to receive further information and event access here. Many people in our community recognize the value of policy work, but it is often hard to access information about how to get your foot in the policy door or what working in “policy” even means in practice. This speaker series is intended to be useful for people who are looking to learn more about which types of US policy jobs are good fits for them and what steps they can take to prepare for these jobs. More than a dozen speakers will share their policy career experiences and provide advice for those seeking to enter the field. Speakers will include people who are currently working in or have worked at a wide range of organizations involved in policy making, as directors, researchers, advisors, lawmakers, and other roles. Live (virtual) attendance is required — to respect the privacy of speakers and to allow them to speak freely, the talks will not be recorded. Sessions will highlight speakers’ experiences in different kinds of US policy jobs. Most speakers have backgrounds in technology policy, especially biosecurity and AI policy, but the sessions are designed to be useful to people with a wide range of interests. Currently scheduled sessions are: Working in the executive branch / White House Working in Congress Working in think tanks Graduate school for government careers (JD, PhD, Masters) Political campaigning / ballot initiatives Policy journalism Sessions will last about an hour, opening with 10-15 minute talks from 2-3 policy professionals on their career trajectory, what their work is like, and advice for people hoping to enter the US policy world. The second half of the session will involve a moderated Q&A conversation based on audience questions. After each session, the organizers will follow up with attendees with related links and other relevant career resources. Additional information: There will be at least 5 sessions: one per week, starting early July. To accommodate speakers’ schedules, most sessions will take place between 6:00 pm and 9:00 pm Eastern Time. Sessions will build on each other and we encourage attendance of the full series. However, signing up is not a hard commitment; no need to let organizers know if you are unable to attend some session. Speakers are not necessarily affiliated with this forum or related organizations, communities, and ideas. If you have any other questions, please comment them below or message me through this forum. If you are interested, sign up here. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: US bill limiting patient philanthropy?, published by Max_Daniel on the Effective Altruism Forum. This is a linkpost for [Linked article might be behind a paywall. Sorry.] I just read a New York Times article titled How Long Should It Take to Give Away Millions? Subtitle: The promise of philanthropy was that the wealthy could enjoy tax breaks for their charitable contributions. The pandemic laid bare how accumulation can trump getting money to those in need. A Senate bill aims to change that. [Boldface emphases in quotes will be mine throughout this post.] It seems that a coalition of stakeholders including policymakers, advocacy groups, and some billionaires essentially has for a while objected to the idea of 'giving later'. For instance, they want to increase per-year spending requirements for foundations, regulate donor-advised funds (DAFs), and close what they perceive to be various loopholes. The participants wanted, among other reforms, to ensure that money stashed in donor-advised funds, which had already earned those donors significant tax savings, ended up in the hands of working charities more quickly. Last summer, Patriotic Millionaires — a group of about 200 wealthy individuals including the Disney heiress Abigail Disney — joined the left-leaning Institute for Policy Studies in asking Congress to double for the next three years the amount of their assets private foundations are required to pay out, to 10 percent. Mr. Arnold, Ms. Madoff and others began recruiting support for proposals to regulate donor-advised funds and to curb practices by private foundations like counting salaries and benefits to family members toward their legal payout requirements. In December, the Initiative to Accelerate Charitable Giving was announced, with the support of big names in the field like the Ford Foundation, the Hewlett Foundation and the Kellogg Foundation. This June, bipartisan legislation along these lines was introduced to Congress, sponsored by senators Angus King (I. - Maine) and Charles E. Grassley (R. - Iowa). The bill would close a loophole in order to speed giving to working charities: Foundations would no longer be able to meet the 5 percent annual payout requirement by giving to a donor-advised fund where there currently is no payout requirement. The bill also would prohibit foundations from counting the salaries or travel expenses of a donor’s family members toward the 5 percent minimum. For donor-advised funds, the proposed legislation would require a donor who wanted the full tax benefit right away to ensure that the funds were dispensed within 15 years. If that is too fast a pace, or if donors are focused on giving over a longer time span, they could take 50 years to pay out. But they would need to wait until then to claim the full tax deduction. (I don't know the status of this bill.) I know almost nothing about US tax and nonprofit law. I don't have a good sense of the overall impact it would have on the philanthropy landscape, or on the feasibility of patient philanthropy. In any case it seems clear that the vast majority of giving that might be pushed from later to earlier times was not motivated by EA-style 'giving later' reasons anyway, and that EA-inspired patient philanthropy would at most be a freak casualty. To be very clear, this means that I don't have a considered view on whether or not this bill would be net good, and what share of the reasoning behind it might be sound. I found this article interesting primarily from a political communications, issue framing, and agenda setting perspective. In particular, I thought it was interesting that the discussion (at least as represented by this article) is an arguably muddled mix of empirical concerns about unintended tax loopholes, a perceived linkage to the more general issue of wealth inequality,...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Sleep: effective ways to improve it , published by Ben Williamson on the Effective Altruism Forum. Introduction Our research found that melatonin supplementation, cognitive behavioural therapy for insomnia (CBT-I), light regulation, mindfulness-based stress reduction (MBSR), and improved night-time air circulation could all be effective ways for you to increase the quality and quantity of your sleep. This is a summary of research conducted into the most worthwhile practices for sleeping better. The post is the first in a series looking into the most effective ways people can improve their wellbeing, aiming to present this information as simply and practically as possible. Thanks to the EA Infrastructure Fund for financing this project. If you find this information useful and/ or take up any of the suggestions, please let me know in the comments or a personal message! Important note: None of the following constitutes professional medical advice. Some of the interventions suggested have risks of negative side effects that are discussed below. We encourage you to experiment with these practices but please be cautious in doing so and take any risks seriously. Top takeaway Our principal recommendations for improving sleep quality are (in order): Melatonin supplements: 0.3mg (300mcg) daily taken two hours before bed. CBT-I: a six-to-seven-week, self-guided course in cognitive behavioural therapy for insomnia, accessed through an app. Light therapy: greatly increasing exposure to bright light during the day, either through building a lumenator or purchasing a SAD lamp. Improved night-time air circulation: opening a window to reduce overnight CO2 accumulation. Mindfulness-based stress reduction: mindfulness training through an app with a focus on sleep. Key Findings Following a broad search of possible interventions, this review evaluated the effectiveness of 11 practices for improving sleep quality and quantity using an adapted weighted factor model.[1] The five most promising interventions are listed below along with a brief explanation. More detailed assessments of all 11 practices are provided further down. This research compared interventions across six criteria: strength of evidence, quality of evidence, ease of implementation, risk, externalities, and novelty. Full results from the model, along with reasoning for the metrics used and their respective weightings, can be found here. Melatonin Ranking: 1st Intervention: 0.3mg daily supplementation (e.g. Options A, B and C) Summary: Melatonin is a natural sleep hormone that can improve sleep quality and quantity when taken in small, daily doses. Melatonin supplementation appears highly practical, with a low risk of notable side effects as well as possible spillover benefits for other conditions. CBT-I Ranking: 2nd Intervention: Completion of an app-based CBT-I course (e.g. Dozy; CBT-I Coach) Summary: Cognitive Behavioural Therapy for Insomnia (CBT-I) involves a combination of reframing negative thoughts around sleep, improving sleep hygiene, and implementing sleep restriction. We found good evidence that completing a self-guided CBT-I course via an app can be an effective way to sleep better. Light therapy Ranking: 3rd Intervention: Increasing indoor lighting brightness, preferably up to 10,000 lux or more (e.g. a ‘lumenator’ or a Seasonal Affective Disorder [SAD] lamp). Summary: Multiple studies have found that significantly increased exposure to bright morning light improves sleep quality and quantity. We found negligible risks to this practice as well as possible benefits to mood and alertness, though this does require some time and money to set up. Improved night-time air circulation Ranking: 4th Intervention: Leaving a window or internal door open while sleeping. Summary: There is reasonable evidence to suggest that ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Ben Garfinkel: How sure are we about this AI stuff?, published by by Ben Garfinkel, EA Global on the Effective Altruism Forum. It is increasingly clear that artificial intelligence is poised to have a huge impact on the world, potentially of comparable magnitude to the agricultural or industrial revolutions. But what does that actually mean for us today? Should it influence our behavior? In this talk from EA Global 2018: London, Ben Garfinkel makes the case for measured skepticism. The Talk Today, work on risks from artificial intelligence constitutes a noteworthy but still fairly small portion of the EA portfolio. Only a small portion of donations made by individuals in the community are targeted at risks from AI. Only about 5% of the grants given out by the Open Philanthropy Project, the leading grant-making organization in the space, target risks from AI. And in surveys of community members, most do not list AI as the area that they think should be most prioritized. At the same time though, work on AI is prominent in other ways. Leading career advising and community building organizations like 80,000 Hours and CEA often highlight careers in AI governance and safety as especially promising ways to make an impact with your career. Interest in AI is also a clear element of community culture. And lastly, I think there's also a sense of momentum around people's interest in AI. I think especially over the last couple of years, quite a few people have begun to consider career changes into the area, or made quite large changes in their careers. I think this is true more for work around AI than for most other cause areas. So I think all of this together suggests that now is a pretty good time to take stock. It's a good time to look backwards and ask how the community first came to be interested in risks from AI. It's a good time look forward and ask how large we expect the community's bet on AI to be: how large a portion of the portfolio we expect AI to be five or ten years down the road. It's a good time to ask, are the reasons that we first got interested in AI still valid? And if they're not still valid, are there perhaps other reasons which are either more or less compelling? To give a brief talk roadmap, first I'm going to run through what I see as an intuitively appealing argument for focusing on AI. Then I'm going to say why this argument is a bit less forceful than you might anticipate. Then I'll discuss a few more concrete arguments for focusing on AI and highlight some missing pieces of those arguments. And then I'll close by giving concrete implications for cause prioritization. The intuitive argument So first, here's what I see as an intuitive argument for working on AI, and that'd be the sort of, "AI is a big deal" argument. There are three concepts underpinning this argument: The future is what matters most in the sense that, if you could have an impact that carries forward and affects future generations, then this is likely to be more ethically pressing than having impact that only affects the world today. Technological progress is likely to make the world very different in the future: that just as the world is very different than it was a thousand years ago because of technology, it's likely to be very different again a thousand years from now. If we're looking at technologies that are likely to make especially large changes, then AI stands out as especially promising among them. So given these three premises, we have the conclusion that working on AI is a really good way to have leverage over the future, and that shaping the development of AI positively is an important thing to pursue. I think that a lot of this argument works. I think there are compelling reasons to try and focus on your impact in the future. I think that it's very likely that the world w...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Shapley values: Better than counterfactuals, published by NunoSempere on the Effective Altruism Forum. [Epistemic status: Pretty confident. But also, enthusiasm on the verge of partisanship] One intuitive function which assigns impact to agents is the counterfactual, which has the form: CounterfactualImpact(Agent) = Value(World) - Value(World/Agent) which reads "The impact of an agent is the difference between the value of the world with the agent and the value of the world without the agent". It has been discussed in the effective altruism community that this function leads to pitfalls, paradoxes, or to unintuitive results when considering scenarios with multiple stakeholders. See: Triple counting impact in EA The counterfactual impact of agents acting in concert In this post I'll present some new and old examples in which the counterfactual function seems to fail, and how, in each of them, I think that a less known function does better: the Shapley value, a concept from cooperative game theory which has also been brought up before in such discussions. In the first three examples, I'll just present what the Shapley value outputs, and halfway through this post, I'll use these examples to arrive at a definition. I think that one of the main hindrances in the adoption of Shapley values is the difficulty in its calculation. To solve this, I have written a Shapley value calculator and made it available online: shapleyvalue.com. I encourage you to play around with it. Example 1 & recap: Sometimes, the counterfactual impact exceeds the total value. Suppose there are three possible outcomes: P has cost $2000 and gives 15 utility to the world Q has cost $1000 and gives 10 utility to the world R has cost $1000 and gives 10 utility to the world Suppose Alice and Bob each have $1000 to donate. Consider two scenarios: Scenario 1: Both Alice and Bob give $1000 to P. The world gets 15 more utility. Both Alice and Bob are counterfactually responsible for giving 15 utility to the world. Scenario 2: Alice gives $1000 to Q and Bob gives $1000 to R. The world gets 20 more utility. Both Alice and Bob are counterfactually responsible for giving 10 utility to the world. From the world's perspective, scenario 2 is better. However, from Alice and Bob's individual perspective (if they are maximizing their own counterfactual impact), scenario 1 is better. This seems wrong, we'd want to somehow coordinate so that we achieve scenario 2 instead of scenario 1. Source Attribution: rohinmshah In Scenario 1: Counterfactual impact of Alice: 15 utility. Counterfactual impact of Bob: 15 utility. Sum of the counterfactual impacts: 30 utility. Total impact: 15 utility. The Shapley value of Alice would be: 7.5 utility. The Shapley value of Bob would be: 7.5 utility. The sum of the Shapley values always adds up to the total impact, which is 15 utility. In Scenario 2: Counterfactual impact of Alice: 10 utility. Counterfactual impact of Bob: 10 utility. Sum of the counterfactual impacts: 20 utility. Total impact: 20 utility. The Shapley value of Alice would be: 10 utility. The Shapley value of Bob would be: 10 utility. The sum of the Shapley values always adds up to the total impact, which is 10+10 utility = 20 utility. In this case, if Alice and Bob were each individually optimizing for counterfactual impact, they'd end up with a total impact of 15. If they were, each of them, individually, optimizing for the Shapley value, they'd end up with a total impact of 20, which is higher. It would seem that we could use a function such as CounterfactualImpactModified = CounterfactualImpact / NumberOfStakeholders to solve this particular problem. However, as the next example shows, that sometimes doesn't work. The Shapley value, on the other hand, has the property that it always adds up to total value. Property 1: T...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Notes on hiring a copyeditor for CEA, published by Aaron Gertler on the Effective Altruism Forum. Over the last year, there’s been a lot of discussion about the “EA job market” and how to build an effective career in an EA field. A few months ago, I went through my first hiring process from the employer side when I found a part-time copyeditor to work on CEA’s social media posts (and a few other tasks). I thought my process might be interesting to people who've been following the aforementioned discussion, so I’m writing up my notes in this post. Meta: It can be legally tricky to write applications, conduct job interviews, and provide feedback to applicants. (Though feedback can also be really valuable!) I recommend consulting your local HR expert before attempting to hire. Statistics on the hiring process The initial application was meant to give me information about applicants’ editing skills and experience, as well as their familiarity with EA (which I felt would be helpful for the role, given the material they’d be editing and sometimes writing). Applicants were asked to edit half of a transcript of an EA Global talk generated by a transcription service, which contained many errors. They were given a two-hour limit to make it as clean and readable as they could. Only a few applicants didn’t finish the full edit, some because they went over the time limit and others because they applied very soon before the deadline. It’s possible that some people ignored the limit; I spot-checked the edit history of some of the best transcripts and didn’t see this, but I didn’t check all transcripts in this way. Applicants were also asked to provide some information about themselves; see the next section for a link to the full job description. Number of applicants who completed the initial work trial: 183 Number of applicants who scored at least “1” on each of two 1-3 scales (one for EA/editing experience, one for editing skill): 147 (I describe my system in more detail below, but you can think of this as “the number of people who followed the instructions, seemed to be fluent in English, and indicated a genuine interest in the position.”) Number of applicants who reached the interview stage: 21 Number of applicants who reached the “final work trial” stage: 8 The job description Here’s the description I used to advertise the position. I shared it through the EA Newsletter, the 80,000 Hours job board, the EA Job Postings Facebook group, and EA Work Club. I didn’t try to track how many candidates came through each source. The position was posted in the first week of June, and was open until the last day of June. Some thoughts on how I handled this process, and what I wish I’d changed: I didn’t have a good sense for how many people would apply, so I erred on the side of having a more “open” description: I described an “ideal” candidate, but didn’t set out many strict requirements. On the one hand, this led to many more people applying than I had expected, and quite a lot of applicant time being invested in a work test for minor (if any) benefit to applicants. This makes me wish I’d done more research beforehand to better understand how many people tend to apply for these positions — for example, by asking GiveWell about their past experience hiring people to write up conversation notes (a position with similarly loose qualifications). On the other hand, had I screened for professional editing experience or professional EA experience, I might have missed out on some of my best candidates,perhaps including the person I eventually hired. I could have saved even more applicant time by asking contacts in the EA community for references; several candidates I chose to interview were people I expect I’d have found through this method. However, since I didn’t think the position would require...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: My experience as a CLR grantee and visiting researcher at CSER, published by Jsevillamol on the Effective Altruism Forum. Last year I applied and was offered a grant from the Center for Long-Term Risk (CLR) fund to conduct independent research. Me and the Center for the Study of Existential Risk (CSER) of the University of Cambridge agreed that I would spend my grant period as a visiting researcher at their institution. I am quite grateful to both organizations for supporting my work over the last six months. Now that the period has ended, I have decided to write a blogpost reflecting on my experience and achievements these last six months. Experience First and foremost, my experience applying and receiving the grant from CLR was as good as one could hope for. There was no major bureaucratic load, and CLR’s staff was very supportive, flexible and professional through the process. I kept them updated monthly on the activities I engaged with, not as a requirement for the grant but more as a form of self accountability, keeping in touch with each other’s research and providing them with some useful information which I hoped would help them with future grantmaking. As I started the visitorship at CSER I found a really welcoming group that went out of their way to make me feel included. As I arrived I was offered to share my current work and participate in their weekly meetings, and I always had people who would listen to my problems and concerns. In CSER I found people whose reasoning I’ve come to admire greatly, and I’ve come off with a greater understanding of the world. I want to highlight Seán ó Héigeartaigh, Jess Whittlestone and Shahar Avin who are excellent researchers with very good epistemics and very goal driven. As negatives, it was quite hard to move to Cambridge. The friends I knew from before who live here were quite busy and at times I felt very lonely. I think the short hours of light in winter contributed to me feeling down. Some things that helped mitigate this were roleplaying with the friends I made at CSER, informal light therapy with a SAD lamp, joining the Cambridge MTG community, biking every day for at least an hour. Special props to Haydn Belfield for keeping me sane through these six months by being a great supervisor and friend, and to Sabin Roman for being a great friend and coworker. The COVID19 pandemic caused me a lot of anxiety and stress, but overall my situation was much better than others’. I could keep working from home, I had stockpiled a lot of Soylent beforehand and my family is all healthy and safe. Achievements In the first week of my visitorship I discussed with my supervisor my goals for the six months. This were the five things I set for myself as goals: Write at least two academic writings: a report on moral patience and another one on quantum computing Figure out what to do after my visit ended, and particularly apply to some PhD programs Learn about CSER’s research and collaborate with people here Contribute to the CaSPAR community Overall I feel I met all my goals, albeit I am left with the impression that I could have been more proactive on collaborating with CSER people and their research. Six months after, my main academic outputs during this period were: An exploration of optimal intervention timing from a decision-theoretic standpoint, plus a blogpost with a summary and discussion. This was a very ambitious project and I am glad I undertook it. But as I advanced and received very little positive feedback I resolved to publish an unpolished exploration and focus on my other projects. A preliminary exploration of quantum computing technologies from a philanthropic point of view. This was a blurb collecting my thoughts in the issue rather than formal academic work. Putting it out there helped me connect with a coauthor f...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Comparisons of Capacity for Welfare and Moral Status Across Species, published by Jason Schukraft on the Effective Altruism Forum. Executive Summary Effective altruism aims to allocate resources so as to promote the most good in the world. To achieve the most efficient allocation of resources, we need to be able to compare interventions that target different species, including humans, cows, chickens, fish, lobsters, and many others. Comparing cause areas and interventions that target different species requires a comparison in the moral value of different animals (including humans). Animals differ in their cognitive, emotional, social, behavioral, and neurological features, and these differences are potentially morally significant. According to many plausible philosophical theories, such differences affect (1) an animal’s capacity for welfare, which is the range of how good or bad an animal’s life can be, and/or (2) an animal’s moral status, which is the degree to which an animal’s welfare matters morally. Theories of welfare are traditionally divided into three categories: (1) hedonistic theories, according to which welfare is the balance of experienced pleasure and pain, (2) desire-fulfillment theories, according to which welfare is the degree to which one’s desires are satisfied, and (3) objective list theories, according to which welfare is the extent to which one attains non-instrumental goods like happiness, virtue, wisdom, friendship, knowledge and love. Most plausible theories of welfare suggest differences in capacity for welfare among animals, though the exact differences and their magnitudes depend on the details of the theories and on various empirical facts. A central question in the literature on moral status is whether moral status admits of degrees. The unitarian view, endorsed by the likes of Peter Singer, says ‘no.’ The hierarchical view, endorsed by the likes of Shelly Kagan, says ‘yes.’ If moral status admits of degrees, then the higher the status of a given animal, the more value there is in a given unit of welfare obtaining for that animal. Status-adjusted welfare, which is welfare weighted by the moral status of the animal for whom the welfare obtains, is a useful common currency both unitarians and hierarchists can use to frame debates. Different theories entail different determinants of capacity for welfare and moral status, though there is some overlap among positions. According to most plausible views, differences in capacity for welfare and moral status are determined by some subset of differences in things like: intensity of valenced experiences, self-awareness, general intelligence, autonomy, long-term planning, communicative ability, affective complexity, self-governance, abstract thought, creativity, sociability, and normative evaluation. Understanding differences in capacity for welfare and moral status could significantly affect the way we wish to allocate resources among interventions and cause areas. For instance, some groups of animals that exhibit tremendous diversity, such as fish or insects, are often treated as if all members of the group have the same moral status and capacity for welfare. Further investigation could compel us to prioritize some of the species in these groups over others. More generally, if further investigation suggested we have been overestimating the moral value of mammals or vertebrates compared to the rest of the animal kingdom, we might be compelled to redirect many resources to invertebrates or non-mammal vertebrates. To understand the importance of these considerations, we must first develop a broad conceptual framework for thinking about this issue. Moral Weight Series Comparisons of Capacity for Welfare and Moral Status Across Species How to Measure Capacity for Welfare and Moral Status The Subjectiv...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: EAGxVirtual Unconference (Saturday, June 20th 2020), published by CristinaSchmidtIbáñez, Sebastian Schwiecker on the Effective Altruism Forum. In addition to the main event of EAGxVirtual 2020 on June 13th and 14th, there will be another chance to speak up, present your thoughts, discuss your paper, raise a question, host a discussion. If you think there was anything missing during the first weekend, we would love for you to join the EAGxVirtual Unconference on Saturday, June 20th. The EAGxVirtual team will provide the schedule and tech support, and will help spread the word, but we’ll need you to come up with the actual content. This event is especially meant for people who haven’t had a chance to discuss their ideas or research with a broader audience before, or who want to get feedback on novel ideas. Your presentation could be pure theory, or a concrete proposal for a project or a startup. Currently, we plan to have two session blocks: Early sessions: 8 x 30 min. sessions from 10 AM till 12 PM GMT+2 Late sessions: 8 x 30 min. sessions from 7 PM till 9 PM GMT+2 Each session will last 30 minutes, and there will be 2 sessions running in parallel. Each session comprises a 15 min. talk and a 15 min. Q&A. If you’d like to run a session, please post your proposal as a comment below, include any relevant links, and let us know whether you would prefer to be part of the early or the late sessions. The 8 pitches that receive the most votes (for the early and the late sessions respectively) by 10am CET on Monday, June 15th will be picked. If you're not planning to present something yourself but know someone who should, please share this post with them! Either way, we would love for you to join the Unconference and be part of the discussion. Once the schedule is finalized, we’ll post it to the Forum, the Facebook event, and the EAGxVirtual 2020 website. This event is open to everyone. UPDATE (June 19): We are excited to announce the speakers for the EAGxVirtual Unconference (please note that we put together the schedule based on the number of votes and the speakers’ availability to give a talk). If you were an attendee of EAGxVirtual 2020 you will also find the sessions in the official schedule of the conference on Grip: (Time zone: GMT+2) You can also add each session from our shared Google calendar. We look forward to seeing you there! UPDATE (July 6): (Most) speakers have kindly given their permission to add their talks to this public Youtube playlist: You can find the crowdsourced notes for all the sessions (incl. Q&A) here: Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: The Subjective Experience of Time: Welfare Implications, published by Jason Schukraft on the Effective Altruism Forum. Executive Summary The subjective experience of time refers to how slow or fast time appears to pass for an individual. Animals with faster rates of subjective experience undergo more subjective moments per objective unit of time than animals with slower rates of subjective experience. Roughly speaking, animals with faster rates of subjective experience perceive the world as if it were slowed down compared to the perceptions of animals with slower rates of subjective experience. Based on human reports of alterations in the subjective experience of time, as well as general differences in behavior, neurology, and temporal resolution across animals, I estimate there is a ~70% chance that there exist morally relevant differences in the subjective experience of time across species. Differences in the subjective experience of time would affect the perceived duration of experiences and thus would affect the quality of experiences. An animal’s subjective rate of experience determines the number of subjective moments of pain (or pleasure) a painful (or pleasurable) event of a given objective duration generates. Such differences would be relevant to most plausible theories of welfare because most plausible theories of welfare hold that the subjective nature of experience matters morally. An animal’s maximum rate of subjective experience helps determine its capacity for welfare. Animals with faster rates of subjective experience will, all else equal, have a higher capacity for welfare than animals with slower rates of subjective experience. Unlike many other determinants of capacity for welfare, the subjective experience of time is also directly relevant to an animal’s realized welfare. The quality of experience is the product of its valence, phenomenal intensity, and subjective rate of experience. For many animals, the phenomenal intensity of experiences varies considerably throughout an individual's lifetime. Subjective rates of experience may be malleable, but for most animals they appear to vary much less frequently than phenomenal intensity. For this reason, even those skeptical of the practical import of capacity for welfare will want to incorporate rates of subjective experience into their welfare measures. Differences in neurology, reaction times, and temporal integration windows provide means to roughly measure the subjective experience of time across species. Based on 13 relevant metrics I have identified, I estimate that characteristic differences in the subjective experience of time span no more than two orders of magnitude, with humans falling approximately midway on the spectrum. Arranging animals on this spectrum is likely to produce a radically different ordinal ranking than arranging animals according to neuron count, encephalization quotient, brain-mass-to-body-mass ratio, or other metrics related to brain size. Incorporating considerations about the subjective experience of time into our interspecies comparisons (currently dominated by brain size considerations) would likely change the way we prioritize animals. Although much uncertainty remains, it appears many animals have rates of subjective experience faster than that of humans. For example, convergent evidence from their neurology, behavior, and the temporal resolution of their senses indicates songbirds and honeybees experience 2-10 times as many subjective moments per objective unit of time as humans. Thus, all else equal, the painful experiences of animals like songbirds and honey bees likely generate more suffering per objective unit of time than comparable animals with slower rates of subjective experience. Incorporating this sort of information into our prioritization decisions may ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: The Fermi Paradox has not been dissolved , published by Fods12 on the Effective Altruism Forum. Introduction This article is a response to the 2018 paper ‘Dissolving the Fermi Paradox’ by Anders Sandberg, Eric Drexler, and Toby Ord. The Fermi Paradox is the apparent contradiction between the great size and age of the universe, which seem to imply a high probability of extra-terrestrial life, and the fact that no extra-terrestrial life has been definitively observed. In their paper, Sandberg et al. use the Drake equation to estimate the expected number of alien civilizations in the Milky Way galaxy and in the observable universe. What differentiates their approach from previous efforts to answer this question is that they do not simply make a point estimate for the number of alien civilizations. Instead, they estimate the uncertainty for each parameter in the Drake equation, and then take random draws from the distribution of each parameter to estimate the distribution for the end result. Using this technique, they find that, although the mean expected number of alien civilizations may be high, there is a large tail of very low expected values, which means that overall the probability of Earth being the only planet to harbour civilization in the Milky Way, and indeed even in the observable universe, is fairly high. On this basis, the authors argue that since it is quite likely given our existing knowledge that no other intelligent alien civilizations exist, the Fermi Paradox is not paradoxical at all, and is therefore dissolved. In this essay, I will argue that the analysis of Sandberg et al. is flawed in a number of key respects, and as a result the Fermi Paradox remains an open question. Here I briefly list the key problems with the Sandberg et al. paper, before proceeding to discuss each in more detail. The method used of multiplying uncertainties of many small numbers, most of which have an upper bound of one, is biased towards yielding a result of a high probability of Earth being unique, while also leading to various dubious results. The key result of the paper is driven largely by uncertainty in the parameter fl, which is modeled in an unusual way without clear justification. Adoption of slightly different (and I believe more plausible) modelling choices and parameter values yields totally different results, which do not result in the Fermi paradox being dissolved. I illustrate this by re-estimating the Sandberg et al. models using different parameters and modelling assumptions. Multiplying small numbers The very nature of the Drake equation, in which seven apparently-independent parameters (four of which are fractions) are multiplied together, means that it has the potential to give very low numbers. Indeed, since the rate of star formation is fairly well-established to be around 1-10, the average longevity of detectable civilizations is ultimately bounded by the age of the universe to around 10 years, and the number of Earth-like planets per star is generally set at one, it follows that the largest possible number detectable civilizations in the Milky Way galaxy is 10^11, or about the same as the number of stars in the galaxy. By contrast, there is no lower bound to any of these numbers, especially the four fractions, which can potentially be set to arbitrarily low non-zero values. The potential for abusing multiplication of fractions to give extremely low numbers is well known. A particularly egregious example of this can be found in the work of Christian apologist Tim McGrew, who estimates the prior probability of having the evidence we do pertaining to the resurrection of Jesus at less than 10^-40, on the basis of multiplying together supposedly independent probabilities of each of Jesus’ disciples separately experiencing a hallucination. The Drake equatio...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: [PR FAQ] Sharing readership data with Forum authors , published by Aaron Gertler on the Effective Altruism Forum. The EA Forum team is sharing our project proposals publicly on the Forum, as an experiment during August. They’re written as though the product were already finished, but for now, they are only proposals. See here for a description of PR FAQs. We appreciate hearing comments from everyone, even if they are brief opinions like “I'd be happy to see this" or "I quickly skimmed the post and it doesn’t seem like this is something I would use, but I’m not sure”. “Post Metrics” Help Forum Users Track Impact Newly available data lets people see how many views, clicks, and minutes of reading their EA Forum posts have generated Summary For years, votes and comments were the only way to see whether your Forum posts had found an audience. But from now on, you’ll be able to see data from all your posts through our “Post Metrics” feature. This will display how many times your post has been viewed, how much time people spent reading it, and how many of them clicked on links within the post. You’ll also be able to see total figures for these metrics across all of your posts. Problem When you share a post on the Forum, it can be hard to tell whether anyone read it. The average post gets about 15 votes and a few comments, but gets about 500 views. This means that until now, authors only saw a tiny fraction of their readers. Knowing your work has been read is a powerful motivator, but that knowledge wasn’t available. Solution “Post metrics” give authors more data on how people have engaged with their posts, motivating them to write more and share their writing in more places. They’ll be able to see how many times their posts have been read or viewed, but also how much time readers spent on the posts — which is a more useful metric for long posts that take a while to read. Getting started You can see the metrics for all your posts already — no need to change anything! You can see a post’s metrics by hovering over the “data” icon, which appears next to the comment count at the top of the post. You can also see the icon next to the comment count in each post on your profile. Finally, you can hover over the icon at the top of your profile to see the total number of views and clicks your posts have gotten. If you’d rather not see these, go to your profile editor and uncheck the “View post metrics” box. Quotes “We deeply appreciate the authors who use our forum, and we hope the new metrics will help them see how many people they’ve reached with their writing.” Aaron Gertler, Content Specialist, CEA “I’m looking forward to writing more on the Forum now. It’s nice to learn more about my audience, and see how well I’m holding their attention.” Rachel Researcher, aspiring blogger ”I decided to share my first post on Reddit and Hacker News to see how many people would read it. I didn’t get much additional karma, but there were almost 500 new views, and two people made Forum accounts to make their first comments!” Avery Newauthor, Good School University FAQs How far back does this data go? The data is based on engagement going back to March 30, 2020. (Meta: This is an arbitrary date — the actual date is "sometime in the spring of 2020".) How does the viewership data count multiple views from the same person? We only share unique views; if you see that your post has 100 views, that means it was viewed from 100 different (logged-in Forum accounts + unique IP addresses from readers who weren't logged in). How does the viewership data count views from bots? We only count users who have Javascript enabled, which should screen out most bots. Does the reading time data include time spent reading and writing comments? Yes, it does. We may take steps to exclude this in the future, though it s...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: AGI Safety Fundamentals curriculum and application, published by richard_ngo on the Effective Altruism Forum. This is a linkpost for Over the last year EA Cambridge has been designing and running an online program aimed at effectively introducing the field of AGI safety; the most recent cohort included around 150 participants and 25 facilitators from around the world. Dewi Erwan runs the program; I designed the curriculum, the latest version of which appears in the linked document. We expect the program to be most useful to people with technical backgrounds (e.g. maths, CS, or ML), although the curriculum is intended to be accessible for those who aren't familiar with machine learning, and participants will be put in groups with others from similar backgrounds. If you're interested in joining the next version of the course (taking place January - March 2022) apply here to be a participant or here to be a facilitator. Applications are open to anyone and close 15 December. EDIT 29 Nov: We've now also released the curriculum for the governance track. EDIT 10 Dec: Facilitators will be paid $1000; the time commitment is 2-3 hours a week for 8 weeks. This post contains an overview of the course and an abbreviated version of the curriculum; the full version (which also contains optional readings, exercises, notes, discussion prompts, and project ideas) can be found here. Comments and feedback are very welcome, either on this post or in the full curriculum document; suggestions of new exercises, prompts or readings would be particularly helpful. I'll continue to make updates until shortly before the next cohort starts. Course overview The course consists of 8 weeks of readings, plus a final project. Participants are divided into groups of 4-6 people, matched based on their prior knowledge about ML and safety. Each week (apart from week 0) each group and their discussion facilitator will meet for 1.5 hours to discuss the readings and exercises. Broadly speaking, the first half of the course explores the motivations and arguments underpinning the field of AGI safety, while the second half focuses on proposals for technical solutions. After week 7, participants will have several weeks to work on projects of their choice, to present at the final session. Each week's curriculum contains: Key ideas for that week Core readings Optional readings Two exercises (participants should pick one to do each week) Further notes on the readings Discussion prompts for the weekly session Week 0 replaces the small group discussions with a lecture plus live group exercises, since it's aimed at getting people with little ML knowledge up to speed quickly. The topics for each week are: Week 0 (optional): introduction to machine learning Week 1: Artificial general intelligence Week 2: Goals and misalignment Week 3: Threat models and types of solutions Week 4: Learning from humans Week 5: Decomposing tasks for outer alignment Week 6: Other paradigms for safety work Week 7: AI governance Week 8 (several weeks later): Projects Abbreviated curriculum (only key ideas and core readings) Week 0 (optional): introduction to machine learning This week mainly involves learning about foundational concepts in machine learning, for those who are less familiar with them, or want to revise the basics. If you’re not already familiar with basic concepts in statistics (like regressions), it will take a bit longer than most weeks; and instead of the group discussions from most weeks, there will be a lecture and group exercises. If you’d like to learn ML in more detail, see the further resources section at the end of this curriculum. Otherwise, start with Ngo (2021), which provides a framework for thinking about machine learning, and in particular the two key components of deep learning: neural networks and optimisation....
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Announcing EA Hub 2.0 , published by Michal_Trzesimiech, Richenda on the Effective Altruism Forum. We’re happy to announce that the new EA Hub has launched. Our vision is to enable and inspire collaboration between EAs by making it easier for people to network, and work together on promising initiatives. Connecting ideas with talent, resources and support is one of the biggest bottlenecks of high potential individuals and a cause of promising ideas not reaching fruition. By synchronising and showcasing projects, individuals, and groups, initiatives can build traction more effectively. The platform also links to other resources and platforms in the EA space, including the Effective Altruism Forum. Over the last year, we’ve redesigned and rebuilt the Hub from scratch, with the help of dedicated and talented volunteers. In this release, we restore and improve most of the functionality from the original EA Hub. It includes: The ability to search for people (in the near future also based on cause area, skillset, job status, organisational affiliation, and availability for volunteer roles or speaking engagements). The capability to join or register a local group, to contact a group, to ‘claim’ a group, and to report a group inactive. The map of EAs, highlighting EA groups and personal profiles. The map now distinguishes between active and inactive groups. Customisable personal profiles. Future Features In the coming months, we will be building a feature for coordinating EA projects, and a cross-platform search functionality. We anticipate the ‘Projects’ feature will offer an inventory of EA projects of all sizes, the option to express interest in an initiative, and enable project leads to signal opportunities for funding, volunteering, paid work, or partnership. Projects will be integrated into the map of EAs, and users will be able to display project roles on their profiles. Our cross-platform search functionality will draw together results from relevant sources of information we use as a community. Doing this will consolidate existing resources, lower the navigation cost for users and multiply the impact of our collective work. As the product matures, we will take our cue from users when fine-tuning our functionality and future features. The Hub will also serve to collate data on groups and movement trends year round, allowing records to be more seamlessly maintained. This should benefit group organisers, enabling them to track group metrics more easily. EA Survey data will also be integrated into the platform—we hope to offer data visualisations that will enable individuals and organisations outside of Rethink Charity to review and utilise longitudinal community research more easily. In keeping with our ethos, we want to collaborate with other EA projects as much as possible. The Hub presently connects with the EA Forum, EA Work Club, PriorityWiki, EA Donation Swap and Effective Thesis. We expect to expand this list in the future, and we are very open to integrating relevant projects where mutually desirable. Acknowledgements Originally created by .impact in 2014, the new EA Hub has been delivered by LEAN, a project of Rethink Charity. As with the original website, EA Hub 2.0 has been created on a relatively small budget thanks to our generous donors and the efforts of our talented staff and volunteers: Taymon Beal Sebastian Becker Alexander Herwix Richenda Herzig Marcin Kowrygo Manoj Nathwani Michal Trzesimiech Nadia Williams We’d also like to acknowledge the input of David Moss, Luke Freeman, Ozzie Gooen, Peter Hurford, Sarah Spikes, Katie Glass, David Furlong, and the Rethink Charity team. If you’re as keen as we are to see the Hub reach its potential, the project has considerable room for funding, and we also welcome volunteers with software engineering experience. ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Which nuclear wars should worry us most?, published by Luisa_Rodriguez on the Effective Altruism Forum. Summary A nuclear exchange may have the potential to kill millions or billions of people, and possibly lead to human extinction. In this post, I rank plausible nuclear exchange scenarios in terms of their potential to cause harm based on three factors: 1) The size of the involved countries’ nuclear arsenals; 2) The size of the involved countries’ populations; 3) The probability of the given nuclear exchange scenario. Based on my rough prioritization, I expect the following nuclear exchange scenarios have the highest potential for harm: Russia and the US India and Pakistan China and either the United States, India, or Russia Project Overview This is the first post in Rethink Priorities’ series on nuclear risks. In this post, I look into which plausible nuclear exchange scenarios should worry us most, ranking them based on their potential to cause harm. In the second post, I explore the make-up and survivability of the US and Russian nuclear arsenals. In the third post, I estimate the number of people that would die as a direct result of a nuclear exchange between NATO states and Russia. In the fourth post, I estimate the severity of the nuclear famine we might expect to result from a NATO-Russia nuclear war. In the fifth post, I get a rough sense of the probability of nuclear war by looking at historical evidence, the views of experts, and predictions made by forecasters. Future work will explore scenarios for India and Pakistan, scenarios for China, the contradictory research around nuclear winter, the impact of several nuclear arms control treaties, and the case for and against funding particular organizations working on reducing nuclear risks. Toward a better understanding of nuclear risks A nuclear exchange may have the potential to kill millions or billions of people, and possibly lead to human extinction. There have been many cases where nuclear weapons have almost been launched by mistake (Baum, de Neufville & Barrett, 2018).[1] And if a nuclear exchange — started by accident or on purpose — were to escalate to a full-scale nuclear war, the nuclear detonations could lead to a nuclear winter, a state where soot launched into the atmosphere blocks out enough sunlight to cause a famine so severe and long-lasting that almost everyone on Earth could starve to death before its end. Because there seems to be a non-negligible probability of a large-scale nuclear exchange, and because the stakes would be so high in the event that a nuclear exchange did escalate, many effective altruists believe reducing nuclear risks should be among the top priorities for the EA community. For example, 80,000 Hours published a problem profile on nuclear security, giving a score of 15 out of 16 on Scale (though it scores relatively low on Solvability and Neglectedness).[2] But my sense is that some details of the nuclear risks problem area aren’t well-understood by most EAs — for example, how bad nuclear war would actually be, the mechanisms behind nuclear winter, and where EAs that prioritize reducing nuclear risks should donate. In a number of upcoming posts, I’ll try to understand, in somewhat concrete terms, how much harm nuclear war would cause and how plausible nuclear risks are. One of the things I'll do to better understand the risks posed by nuclear winter is review the implications of recent academic literature that is interpreted by some as casting doubt on the science behind the nuclear winter phenomenon. Finally, I’ll also evaluate some of the work being done to reduce nuclear risks. In particular, I’ll focus on a recent treaty that’s been adopted by the United Nations, the Treaty on the Prohibition of Nuclear Weapons (TPNW), which would make the research and use of nuclea...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Complete archive of the Felicifia forum , published by Louis_Francini on the Effective Altruism Forum. Prior to the existence of a unified effective altruism movement, a handful of proto-EA communities and organizations were already aiming towards similar ends. These groups included the web forum LessWrong and the charity evaluator GiveWell. One lesser-known community that played an important role in the history of the EA movement is the Felicifia utilitarian forum. The name "Felicifia," a reference to Jeremy Bentham's felicific calculus, was originally used as the title of Seth Baum's personal blog which he started in September 2006. In December 2006, Baum moved to Felicifia.com, which became a community blog/forum. A minority of the posts from this site are viewable on the Wayback Machine and archive.is. (Brian Tomasik is slowly working on producing a better archive at oldfelicifia.org.) The final iteration of Felicifia, and the one I'm concerned with here, launched in 2008 as a phpBB forum. Unfortunately, for years the site has been glitchy, and for the past several months it has been completely inaccessible. Thus I thought it would be valuable to produce an archive that is more easily browsable than the Wayback Machine. Hence: felicifia.github.io The site featured some of the earliest discussions of certain cause areas, such as wild animal suffering. Common EA concepts such as the meat eater argument and s-risks were developed and refined here. Of course, the forum also delved into the more theoretical aspects of utilitarian ethics. A few of the many prominent EAs who participated in the forum include Brian Tomasik, Peter Hurford, Ryan Carey, Pablo Stafforini, Carl Shulman, and Michael Dickens. While not all of the threads contained detailed discussion, some of the content is quite high-quality. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Ranking animal foods based on suffering and GHG emissions, published by VilleSokk on the Effective Altruism Forum. Introduction I created a simple web-based tool which ranks animal species according to the harm caused by consuming them. The user can specify the relative priority of two subscales of harm: animal suffering and greenhouse gas emissions. Numerous analyses have been published on how much suffering is caused by eating various animals. For example by Peter Hurford, Brian Tomasik, Charity Entrepreneurship and Dominik Peters. Results of these analyses hint at the small animal replacement problem which is the concern that advocating for reduced meat consumption for environmental reasons leads people to replace beef with smaller animals such as chicken and fish. This increases total suffering because more farmed animals are consumed for the same amount of calories. I was inspired by Dominik Peters' tool and was wondering if a similar ranking could be developed which accounts for animal suffering, greenhouse gas emissions and human health. My main motivation was to better understand the climate change/animal welfare trade-off when deciding which animals to leave off our plates. Due to difficulties with modeling health effects I eventually narrowed down the harms to just animal suffering and greenhouse gas emissions and developed a tool based on Dominik's model. Methods A simple model is used to calculate the animal suffering and greenhouse gas emissions subscale scores of each species in the data set. The subscale scores are then combined into a single score which is used to rank the species. The animal suffering subscale estimates the number of hours spent on a farm to produce 2000 kcal of food energy. The climate change subscale estimates CO2-equivalent greenhouse gas emissions produced per 2000 kcal of food. The suffering subscale can be adjusted according to the relative suffering intensity of the species and brain size/neuron count. Both subscales can be adjusted by supply and demand elasticity. The subscale scores are exponentiated using the subscale priorities that the user has provided and then multiplied to get a single score (weighted product model). The combined scores are normalised to the 0-100 range and used to display a ranking of the species based on the estimated harm. The user interface allows the user to set the subscale priorities, toggle the adjustments, change the relative suffering intensities and choose the brain weighting function. The goal is to enable the user to specify their beliefs if they don't agree with the default parameters. When playing around with the sliders it seems that the model is generally consistent with the welfare/climate trade-off. If climate is prioritised, ruminants rank higher on the combined scale. If welfare is prioritised, smaller animals rank higher on the combined scale. Limitations The model does not consider indirect effects on wild animal welfare. The suffering of wild animals could significantly exceed that of farmed animals. Indirect effects of farming contribute to wild animal suffering. It would be interesting to also analyse how changes in animal consumption affect wild animals through indirect effects on feed crop production. It is difficult to come up with meaningful subscale priorities. It would make sense to measure the disvalue of emissions and suffering based on the underlying values which cause us to be concerned about these issues in the first place. If, for example I am motivated by improving welfare, it would be helpful to estimate the welfare impacts of climate change and factory farming on a common scale which seems difficult. Heather Browning's doctoral thesis outlines several issues with common methods of measuring animal welfare. This includes the hours lived on a farm and relative suf...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: My Career Decision-Making Process , published by ShayBenMoshe on the Effective Altruism Forum. Summary In this post I share my career decision-making process. I hope that it will help others in their career decisions, by serving as a detailed case study. I believe that the general framework I used can be useful to a wide audience. Furthermore, in the last section (which comprises more than half of the post), I detail all of the options that I considered, many of which are not frequently discussed in EA, and I believe they will be particularly relevant for people with technological or scientific background. I encourage all community members to share their career decision-making process as well. About half a year ago, I left my math PhD to pursue a more impactful career. In the past few months, I was working on generating a long-list of options, learning more about them and making a decision. Ultimately, I decided to start a PhD in computational healthcare, aiming to work on neglected areas in the healthcare system (in developed countries) and employ tools that are not commonly used in healthcare. I tried (and failed) to keep this post short. If you want more details on anything, don't hesitate to reach out (by a comment, private message, email [shaybm9@gmail.com] or any other method). I have also tried (and hopefully succeeded) to write it so that each section can be read independently, according to the reader's interests. Table of Contents Goals of this Post My Background Preferences and Constraints Methodology Narrowing Down the Long-List Making a Final Decision Final Plan General Helpful Resources Options Considered Acknowledgements It is a pleasure to thank Edo Arad for numerous conversations that were instrumental in my process, for connecting me to my new PhD advisor, and for carefully reading this post. I would also like to thank Nadav Brandes, Omri Sheffer, Shahar Lahad, Sella Nevo and Gidon Kadosh for their valuable feedback on this post. This post does not necessarily reflect their views, and all mistakes are mine. 1. Goals of this Post There are several reasons for me writing this post, I wish to emphasize the main one - I want more people to write posts like this one. They don't have to be as detailed, don't have to follow the same format, and don't have to discuss the same aspects. Many of us are making career decisions at one point or another, and I believe that it will be extremely valuable to the community to have many detailed and diverse case studies. In particular, I hope this and other people's posts will serve the following purposes: Learn from each other's methodologies. We can learn how others generate ideas and figure out which of them are best for their purposes. In my experience, the material on 80,000 hours' website is very helpful, but I felt that it lacks concrete examples of making career choices. I hope we can fill this gap together. Share vague and concrete career options, our take on them, and references to read more about them. Get to know more people in the community who are (at least somewhat) interested in career paths we are interested in. Share our struggle and frustration in this journey. 2. My Background tl;dr - I'm Shay Ben Moshe, 26 years old from Israel. I have a BSc and an MSc in mathematics, and I have worked as a programmer and cyber-security researcher for about 10 years. I have been involved in the EA community for the past 4 years, and I recently decided to leave my math PhD after one year in (out of five), to pursue a more EA-aligned career. I started programming when I was in high school - I worked as a freelance web developer (doing both front- and back-end). At the age of 18 I joined the Israel Defense Forces (mandatory) for 5 years, where for the most part I served as a cyber-security researcher, and in the last y...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: On future people, looking back at 21st century longtermism , published by Joe_Carlsmith on the Effective Altruism Forum. (Cross-posted from Hands and Cities) “Who knows, for all the distance, but I am as good as looking at you now, for all you cannot see me?” – Whitman, Crossing Brooklyn Ferry Roughly stated, longtermism is the thesis that what happens in the long-term future is profoundly important; that we in the 21st century are in a position to have a foreseeably positive and long-lasting influence on this future (for example, by lowering the risk of human extinction and other comparable catastrophes); and that doing so should be among the key moral priorities of our time. This post explores the possibility of considering this thesis — and in particular, a certain kind of “holy sh” reaction to its basic empirical narrative — from the perspective of future people looking back on the present day. I find a certain way of doing this a helpful intuition pump. I. Holy sh the future “I announce natural persons to arise, I announce justice triumphant, I announce uncompromising liberty and equality, I announce the justification of candor and the justification of pride. O thicker and faster—(So long!) O crowding too close upon me, I foresee too much, it means more than I thought.” – Whitman, So Long! I think of many precise, sober, and action-guiding forms of longtermism — especially forms focused on existential risk in particular — as driven in substantial part by a more basic kind of “holy sh” reaction, which I’ll characterize as follows: Holy sh there could be a lot of sentient life and other important stuff happening in the future. And it could be so amazing, and shaped by people so much wiser and more capable and more aware than we are. Wow. That’s so crazy. That’s so much potential. Wait, so if we mess up and go extinct, or something comparable, all that potential is destroyed? The whole thing is riding on us? On this single fragile planet, with our nukes and bioweapons and Donald Trumps and ~1.5 centuries of experience with serious technology? Do other choices we make influence how that entire future goes? This is wild. This is extremely important. This is a crazy time to be alive. This sort of “holy sh” reaction responds to an underlying empirical narrative — one in which the potential size and quality of humanity’s future is (a) staggering, and (b) foreseeably at stake in our actions today. Conservative versions of this narrative appeal to the spans of time that we might live on earth, and the number of people who might live during that time. Thus, if earth will be habitable for hundreds of millions of years, and can support some ten billion humans per century, some 10^16 humans might someday live on earth — ~a million times more than are alive today. I’m especially interested here, though, in a less conservative version: in which our descendants eventually take to the stars, and spread out across our own galaxy, and perhaps across billions of other galaxies — with billions or even trillions of years to do, build, create, and discover what they see as worth doing, building, creating, and discovering (see Ord (2020), Chapter 8, for discussion). Sometimes, a lower-bound on the value at stake in this sort of possibility is articulated in terms of human lives (see e.g. Bostrom (2003)). And as I wrote about last week, I think that other things equal, creating wonderful human lives is a deeply worthwhile thing to do. But I also think that talking about the value of the future in terms of such lives should just be seen as a gesture — an attempt to point, using notions of value we’re at least somewhat familiar with, at the possibility of something profoundly good occurring on cosmic scales, but which we are currently in an extremely poor position to understand or anticipa...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Why I prefer "Effective Altruism" to "Global Priorities" , published by AllAmericanBreakfast on the Effective Altruism Forum. Edit: Jonas responds in comments that he was not intending to argue for a name change, but more a change of emphasis. I respond explaining why I took “name change” as a reasonable interpretation, but you should read his OP and decide for yourself. In comments to Jonas Vollner’s post, Ryan Carey makes a good argument that we should change the name of our movement from EA to Global Priorities, or at least change the emphasis. Among other options, “global priorities” was suggested. Tractability concerns aside, I have six key arguments for why this specific name change would not be the right move. These are my personal intuitions on the implications of names. I don't consider this a strong form of evidence. So I will keep this brief. "Global Priorities" sounds more arrogant than "Effective Altruism." Yes, EA can sound arrogant to some people. But many people wrestle with the question of how to make real positive change, and it makes sense to build a community to support that. Saying you're part of a Global Priorities movement sounds like you're wanting to impose your views on what those priorities should be. Don't trust me, though. Run a poll, maybe on Amazon's Mechanical Turk. Give a one-paragraph description of the EA movement's mission and principles, but randomly title it the "Global Priorities" or "Effective Altruism" movement. Randomly show one or the other to respondents. Ask them which sounds more arrogant, and which they'd be more likely to support or join. "Global Priorities" doesn't convey the moral or political basis for that prioritization. Whose priorities? The national interests of the most powerful nations? Are we advocating for world government? For a command economy? To give a voice to less powerful groups? What makes something a priority? Are those priorities supposed to be good? The meaning of the name is more open to interpretation. "Global Priorities" implies a focus on institutions. Altruism is clearly something that individuals can do. But most individuals don't have a say in what our global priorities should be. I can be an effective altruist while working in a purely technical role. But it's not clear to me that I can be involved in a movement for global priorities doing that sort of work. GP sounds like it's all about governance. "Global Priorities" doesn't necessarily imply a need for change. GP could easily just be about gathering inputs from a bunch of powerful interests about what they consider their priorities to be, and then coordinating to achieve them. Those priorities don't necessarily have to be transcendently important or good from a consequentialist standpoint. If I had to guess, many major powers would currently consider the free flow of oil to be a greater global priority than minimizing animal cruelty, and that sounds like a very different sort of movement from the one we've got. "Global Priorities" doesn't necessarily imply an emphasis on neglected issues. Some of our causes may only need to comprise a tiny fraction of global spending or work hours to be sufficient. Perhaps the world only needs to sink a total of $20 billion/year into biosecurity to do a good job. That would be about half of one percent of the US government's 2019 tax revenue. But if you asked somebody to look at a budget and rank causes by the importance they are assigned, it would be reasonable to rank them by the amount of budget that's been allocated. And also to spend the most time arguing over the biggest budget allocations. Spend 1/200th of your time arguing over 1/200th of the budget. We're trying to create a movement that inverts this. We deliberately try to spend the majority of our time arguing over the issues that get a very s...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: CEA update: Q1 2021, published by MaxDalton on the Effective Altruism Forum. This is a linkpost for This update covers CEA's work in the first quarter of 2021. Background Our mission is to build a community of students and professionals acting on EA principles, by creating and sustaining high-quality discussion spaces. In 2019, we focused on stabilizing the organization and improving execution. In 2020, we clarified and narrowed our scope (by setting strategy and spinning off Funds and GWWC). In 2021, we are focused on working towards our annual goals, as well as growing our team. Program progress These are brief summaries; you can find more details for each program further down in this post. Groups Support We had around 100 calls and 120 in-depth email / Slack exchanges with group leaders. We received positive feedback on the calls (average likelihood to recommend >9/10). We increased 1:1 support for highly-ranked university groups, and helped to seed a group at Georgetown University. Fellowships We worked with Emma Abele (a contractor and CBG recipient) and EA groups at Oxford and Stanford to set up virtual fellowships. We also hired a contractor to provide 1:1 support for groups running fellowships. The number of people attending a fellowship grew 3x quarter-on-quarter (according to our records - there may have been some underreporting last quarter. We expect there was substantial growth in any case.) We’re working with Max Daniel to develop a new curriculum for the In-Depth Fellowship. Enhanced support We’re trying out enhanced support for law students, Black and Hispanic/Latinx community members, and group organizers in areas where the movement is just beginning to grow. Community building grants: We made several renewal grants and several new grants. We are looking to expand our capacity in this area. Forum The number of hours people spent engaging with the Forum grew by 19% quarter-on-quarter, and we’re on track to exceed our target of doubling engagement time from 2020 to 2021. We published all content from the Introductory Fellowship[1] as a series of sequences on the Forum, which will make the Forum a better place to learn about EA. We’re hiring for a full-stack engineer to help us to develop features more quickly. We cross-posted a lot of old content (so that more high-quality content is searchable via the Forum), and began to build a wiki, in collaboration with Pablo Stafforini. Events (EA Global: Reconnect) EA Global: Reconnect was focused on building connections between existing highly-engaged community members. 850 people attended, and they booked about 7 meetings on average. We recorded more meetings than we did in all of 2020, though that’s partly due to a different system of measurement. Community health The team made good progress on a variety of small proactive projects, and continued to do reactive work on areas like media, interpersonal situations in the community, and reducing risk in spaces and locations where EA is newly developing. Expanding capacity My (Max’s) main focus in 2021 is on hiring. Reasons for this: Stable base: We now have funding, strategy, and management capacity to build on. Important areas: We think that EA survey data + program data suggests that we are operating in some extremely important areas (e.g. university groups, events). Room for growth: We’re still taking only a small fraction of the opportunities available in those areas. In Q1 we opened two rounds, for a finance lead and a full-stack engineer. We also began to redraft our careers page and made some improvements to our hiring process. We’re on track to open more rounds in Q2. Other progress We have secured enough funding to cover our next two years of operation and expansion. We have moved into our new Oxford office, improved our cybersecurity, and streamlined a ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: You can now apply to EA Funds anytime! (LTFF & EAIF only), published by Jonas Vollmer on the Effective Altruism Forum The Long-Term Future Fund (LTFF) and the EA Infrastructure Fund (EAIF) are looking for grant applications: You can now apply for a grant anytime. We have removed the previous round-based system, and now aim to evaluate most grants within 21 days of submission (and all grants within 42 days), regardless of when they have been submitted. If you indicate that your application is time-sensitive, we will aim to get back to you more quickly (potentially within just a few days). Apply now. You can now suggest that we give money to other people, or let us know about ideas for how we could spend our money. We’re interested in both high-level ideas and concrete, shovel-ready grant opportunities. We will read all suggestions, but we expect to follow up on only a small number. It’s hard to find great grants, so we really appreciate your suggestions! Suggest a grant. We fund student scholarships, career exploration, local groups, entrepreneurial projects, academic teaching buy-outs, top-up funding for poorly paid academics, and many other things. We can make anonymous grants without public reporting. We will consider grants as low as $1,000 or as high as $500,000 (or more in some cases). As a reminder, EA Funds is more flexible than you might think. The LTFF is managed by Asya Bergal (chairperson), Adam Gleave, Evan Hubinger (newly appointed), and Oliver Habryka. For the coming months, they will be joined by Luisa Rodriguez as a guest manager. See its recent payout report. The EAIF is managed by myself (interim/acting chairperson), Max Daniel (chairperson), Buck Shlegeris, and Michelle Hutchinson. For the coming months, Linh Chi Nguyen and Michael Aird will join as guest managers. See its recent payout report and AMA. The Animal Welfare Fund will continue on a round-based system. For recent updates, see Request For Proposals: EA Animal Welfare Fund and Animal Welfare Fund: Ask us anything! Apply here. We look forward to hearing from you! Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: What is the EU AI Act and why should you care about it? , published by MathiasKB on the Effective Altruism Forum. On April 21 the European Commission announced their proposal for European regulation of AI The proposal strives to be for AI what GDPR has been for data protection. Over the coming years the proposal will go through multiple readings in the Parliament and Council, where modifications can be proposed to the act before it is finally adopted or dismissed. After the AI Act was announced, most attention fell on the act's wide definition of AI and blanket bans on 'manipulative AI'. Unfortunately this focus has led many to miss out on the most important points of the act. I noticed there were no forum posts that would help someone get up to speed on the act. In this post I will summarise the act's most important points, how it may affect the development of transformative AI, as well as the EA community's response to the proposal. What are the act's important points? I below outline what I deem the most important points of the regulation, based on their effect on the development of transformative AI. I skip lightly over many details of the act, such as regulatory sandboxes and special rules for biometric systems, to keep the summary brief. The act will apply to all EU countries and supersede any conflicting national law. Because of the act's broad definition of AI, it is difficult for any EU countries to make laws on AI which would not be in conflict. It does not apply to military use of AI. Here countries are free to do as they see fit. Rules for 'high-risk' AI The Act lists a series of 'high-risk' areas. Systems operating in a high-risk area are considered high-risk and must be reviewed and approved before they can be placed on the market. This means that the AI Act's regulation will not apply to AI developed and used internally by companies. High-risk systems include everything from AI management of electricity grids, to AI that determines who to promote or fire. Areas that are considered high-risk where certain uses are restricted are the following: biometric identification and categorization management and operation of critical infrastructure educational and vocational training employment, worker management, and access to self-employment access to and enjoyment of essential services and benefits law enforcement migration, asylum and border management administration of justice and democracy A red thread across the systems which are considered high-risk, is that they make decisions which significantly affect the lives of citizens. The full list of high-risk systems is two pages and can be read in Annex III. After the law is passed, the commission can add new uses of AI that must be approved as long as they fall under any of the existing high-risk areas. For a high-risk system to be approved the provider must submit detailed technical documentation for the system.¹ Requirements for technical documentation include: design specifications, key design choices, description of what the system is optimizing. description of any use of third party tools. description of training data, how it has been obtained, how it has been processed. How the system can be monitored and controlled. The system must have in-built operational constraints that cannot be overridden by the system itself and is responsive to the human operator (!!) Description of foreseeable risks the system poses to EU citizens' health, safety and fundamental rights. In other words the act creates a large, (partially) updatable list of areas where nobody is allowed to deploy AI without explicitly getting approval, which you only get by living up to numerous safety requirements of which one is a working off-switch. High-risk systems not only need approval, but must also be continuously monitored after they ar...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: EA Hotel with free accommodation and board for two years, published by Greg_Colbourn on the AI Alignment Forum. [Posted about previously here and here] Overview Do you long to be free from material needs and be able to focus on the real work you want to do? I know I’ve certainly been in that situation a few times in the past, but instead have lost time doing unimportant and menial jobs in order to be able to get by financially. Talented effective altruists losing time like this is especially tragic given that a lot of cause areas are currently constrained by the amount of quality direct work being done in them. Buildings in the seaside holiday resort of Blackpool (UK) are really cheap. I’ve bought a 17 bedroom hotel with dining room, lounge and bar for £130k. Assuming a 7% rental yield (which is reasonably high), this works out at about £45 per person per month rent. Factoring in bills, catering, and a modest stipend/entertainment budget, living costs could be as low as £5700/person/year (or lower for people sharing rooms, see budget). This is amazing value for hotel living with all basic services provided. The idea is to invite people to live there, with all their expenses covered by donors, for up to two years. Funding is already in place (via me) for the first year of operations. The project will be managed by someone who lives on site and deals with all the admin/finances, shopping/cooking/cleaning/laundry, socials/events and morale - they will also have free living expenses, and be paid a modest salary. Note that this should be considered as a potential high impact, high prestige supporting role, for those excited to be involved in such a capacity on an EA mission. Guests will be free from concerns of material survival, and be able to have prolonged and uninterrupted focus on whatever projects they are working on. Obviously these will be largely limited to purely desk-based, or remote work. Potential people suited to being guests are those who want to: - self-study economics, philosophy, science, AI, programming etc, in order to contribute to future efforts in various EA cause areas, without having to worry about - or waste time - getting (mostly irrelevant or menial) paid work in order to fund themselves - immerse themselves in desk-based research/writing on an EA-related subject without having to worry about fundraising, a job, grants, teaching, tenure etc. - work on a mostly software or research based start-up/project(/phase of a project) without having to worry about runway (be it for profit with a view to earning to give, or an EA-aligned/adjacent charity) A somewhat out of the way location with little in the way of outside distractions most of the year, combined with fully catered living arrangements, should be ideal for engaging in deep work (usual focusing hacks applied) Whilst a simple pledge to work on useful EA things is required (“I pledge to work towards doing the most good that I can whilst staying at the hotel”), there is no formal requirement for people to produce more value than is put in to help them. Given the low costs involved, it’s a fairly low bar to clear though - produce more value in a year than £5700 donated to the most effective charity (+ opportunity cost; for more see Value Proposition section). And just one major success will make the whole thing worth it. A useful analogy might be a catered and managed university residence (paid for by a grant), or perhaps even New York’s Chelsea Hotel, which produced billions of dollars worth of art, despite many guests not paying rent (and was an inspiration for this project). The slightly anarchic feel to it with a lack of formal structure does appeal too. Not requiring people to submit detailed grant applications is also something that may seem like a breath of fresh air to people used to cont...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Which Community Building Projects Get Funded?, published by AnonymousEAForumAccount on the AI Alignment Forum. Disclosure: This analysis is mine alone, and does not reflect the belief of any individuals or organizations I’m affiliated with. To protect my anonymity I’m not providing a full history of my experiences with the programs I’ve analyzed, but readers can assume that I’ve unsuccessfully attempted to get funding through one or more of the channels discussed below and could potentially benefit from changes to these grantmaking processes. Most Effective Altruists (myself included) would agree that the stronger the EA community is, the more good it will be able to accomplish. This idea has motivated the development of multiple programs that have granted millions of dollars to dozens of organizations, groups, and individuals working on “community building” (CB). This analysis examines the processes and grant history of three grantmaking channels: EA Community Building Grants (CBGs), EA Grants, and the EA Meta Fund. Evaluating the efficacy of specific grantees or grantmakers is not feasible given the large number of grants, their broad scope, and the lack of publicly available information about many of the projects that have been funded. While I don’t want to be critical of any particular grantee, grantmaker, or platform, I do want to call attention to concerning patterns revealed by a meta-analysis of these grantmaking channels in aggregate. Below, I show that all three of these grantmaking channels use processes that implicitly or explicitly restrict the number and type of CB projects that are considered. The outcome of these processes have been grants that primarily fund CB projects in close geographical proximity to the grantmakers. Just over half of CB funding has gone to people or projects closely connected to “Oxbridge” (Oxford or Cambridge) or London, and 85% of funding has gone to European efforts. As discussed in more detail in the section on the Meta Fund, this concentration isn’t simply a result of the largest CB organizations being based in Oxford or London. Nor is it the result of the EA community itself being geographically concentrated. While the community does have some large hubs, individual EAs (per the EA Survey) and EA groups (per EA Hub) are significantly more dispersed than CB funding. The landscape for CB funding is shifting rapidly. There’s been some turnover in the leadership of specific funding channels, CEA recently announced a new CEO, and the EA Grants program might be discontinued altogether. This creates an opportunity to reflect on how CB funding can best be structured going forward. I hope my analysis helps ground this discussion in hard data and highlights some of the issues that new processes should try to resolve. If my findings are correct, there are likely valuable CB projects from certain geographic regions and/or interpersonal networks that are being neglected. Note: It’s clear which locations are funded by EA Community Building Grants. However, more interpretation is required for the Meta Fund and EA Grants, as many grantees belong to multiple geographic networks. To highlight the patterns I’ve observed, the preceding table and subsequent analyses attribute grants to the Oxbridge/London network where grantees have, or previously had, strong ties to that area. For instance, a Meta Fund grant allowing an Oxford graduate to study at Harvard is attributed to the Oxbridge/London area, rather than the Rest of World or a split between Oxbridge/London and the Rest of World. Similarly, the Other Europe category is best thought of as “tied to Europe (but not Oxbridge/London)”, the Bay Area category as “tied to Bay (but not Europe)”, and the Rest of World as “no ties to Europe or Bay”. All calculations and categorizations can be found ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: EA and tackling racism , published by Sanjay on the AI Alignment Forum. Write a Review As I write, the world is gripped in shockwaves of hurt and anger about the recent death of George Floyd and the issue of racism. And many are asking what effective altruism (or EA) has to say about this (see here, or here, or here) I have engaged with the EA community for many years, but I don't consider myself an authoritative voice on effective altruism. I am a non-white person living in a predominantly white country, but I don't consider myself an authoritative voice on racism. But I wanted to share some thoughts. First of all, let's just acknowledge that the EA community has been -- in its own way -- fighting against a particular form of racism right from the earliest days of the EA movement. What greater racism is there than the horrifically uneven distribution of resources between people all because of an accident of their birth? And how disgusting that some of the worst off should be condemned to death as a result? Is not the obscene wealth of the developed world in the face of tractable, cost-effective ways of saving lives in the developing world wholly unjustifiable if we were treating people as equals, regardless of where they are, and regardless of the colour of their skin? I still find this argument compelling. And I would encourage the EA movement to be proud of what it has done, proud of the hundreds of millions of dollars already moved in an expression of global solidarity to people around the world. But in some ways this argument feels insular. Is EA really all about taking every question and twisting it back to malaria nets and AI risk? Those of us who, like me, have spent most of their lives in the UK and are old enough will remember the name of Stephen Lawrence. And for those of us, like me, who have spent a substantial chunk of their lives in charities in South East London, his name will have followed us like a ghost. For those who have sensed or lived systemic racism, I do think that the EA way of thinking has something to offer. And something more than “donate to the Against Malaria Foundation”. In this post, I set out some thoughts. I would love to have provided good solutions, like "this is the best place to donate" or "this is the best thing to do" but the range of existing thoughts on this topic is too broad and complex for me to be able to do that now. I think the most important thing that an EA mindset has to offer is this: EA is not just about finding the right answers, it's about asking fundamental questions too. The effective altruism movement is unusual. Not only do EA-minded people answer questions like "what is the best way to improve global health" (finding the right answers). The EA approach also poses questions like "what is the best cause area to tackle, is it global health, or is it existential risk, or is it something else?" (asking more fundamental questions). At first glance, asking the more fundamental questions about cause prioritisation risks subverting our goal. We may conclude that tackling an intractable thing like systemic racism isn’t really the best bang for your buck, and then we’re back to turning everything into malaria nets again. On second glance, it's clear that EA does have something to offer. For example, someone who cares about animals would be encouraged by an effective altruist to consider the different "sub-causes" within the animal cause area, and provided data and arguments about why some are much more effective than others. So in that vein, here are some thoughts about tackling systemic racism as seen through (my interpretation of) an EA lens. These thoughts will raise more questions than answers. My hope and intention is that these are good, useful questions. Before I get started, just an observation: achieving chan...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Things CEA is not doing , published by MaxDalton on the AI Alignment Forum. This is a linkpost for/ There are many things in EA community-building that the Centre for Effective Altruism is not doing. We think some of these things could be impactful if well-executed, even though we don't have the resources to take them on. Therefore, we want to let people know what we're not doing, so that they have a better sense of how neglected those areas are. To see more about what we are doing, look at our plans for 2021, and our summary of our long-term focus. Things we're not actively focused on We are not actively focusing on: Reaching new mid- or late-career professionals Reaching or advising high-net-worth donors Fundraising in general Cause-specific work (such as community building specifically for effective animal advocacy, AI safety, biosecurity, etc.) Career advising Research, except about the EA community Content creation Donor coordination Supporting other organizations Supporting promising individuals By “not actively focusing on”, I mean that some of our work will occasionally touch on or facilitate some of the above (e.g. if groups run career fellowships, or city groups do outreach to mid-career professionals), but our main efforts will be spent on other goals. One caveat to the below is that our community health team sometimes advises people who are working in the areas below (but don’t do the object-level work themselves). For example, they will sometimes advise on projects related to policy (even though none of them work on policy). Reaching new mid- or late-career professionals As mentioned in our 2021 plans, we intend to focus our efforts to bring new people into the community on students (especially at top universities) and young professionals. We intend to work to retain mid- and late-career professionals who are already highly engaged in EA, but we do not plan to work to recruit more mid- or late-career people. Reaching or advising high-net-worth donors We haven't done this for a while, but other EA-aligned organizations are working in this area, including Longview Philanthropy and Effective Giving. Fundraising in general Not focusing on fundraising is a change for us; we used to run EA Funds and Giving What We Can. These projects have now spun out of CEA, and we hope that this will give both these projects and CEA a clearer focus. Cause-specific work (such as community building specifically for effective animal advocacy, AI safety, biosecurity, etc.) As part of our work with local groups, we may work with group leaders to support cause-specific fellowships, workshops, or 1:1 content. However, we do not have any other plans in this area. Career advising As part of our work with local groups, we may work with group leaders to support career fellowships, workshops, or 1:1 content. And at our events, we try to match people with mentors who can advise them on their careers. We do not have any other plans in this area. 80,000 Hours clarified what they are and aren’t doing in this post. Research, except about the EA community We haven't had full-time research staff since ~2017, although we did support the CEA summer research fellowship in 2018 and 2019. We’ll continue to work with Rethink Priorities on the EA Survey, and to do other research that informs our own work. We’ll also continue to run the EA Forum and EA Global, which are venues where researchers can share and discuss their ideas. We believe that supporting these discussions ties in with our goals of recruiting students and young professionals and keeping existing community members up to speed with EA ideas. Content creation We curate content when doing so supports productive discussion spaces (e.g. inviting speakers to events, developing curricula for fellowships run by groups). We occasionally write c...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: On the assessment of volcanic eruptions as global catastrophic or existential risks , published by Mike Cassidy, Lara Mani on the AI Alignment Forum. By Mike Cassidy and Lara Mani Ord 2020, and others have suggested that the existential risk posed by volcanoes is the largest of the potential ‘natural’ catastrophes - 100 times that of asteroids and comets combined. As volcanologists we wanted to delve a bit deeper into the x - risks and also global catastrophic risks from large explosive eruptions, adding insight from the latest volcano and climate science, including challenging some of the assumptions that have been put forward so far. Significant global impacts from large explosive eruptions will be described, which have a ~1 in 6 probability of occurring this century. Introduction I’m Mike and new to EA world, having just been introduced to it early this year from a friend in Oxford and having thoroughly enjoyed reading The Precipice, the super-eruption part sparked my interest. I’m a senior research fellow based in the earth science department at the University of Oxford, and specialise in volcano research. I research a range of different aspects in volcanology, but principally I aim to understand what influences the explosivity of eruptions and how best to forecast them. Lara works for the Centre for the Study of Existential Risk (CSER) at the University of Cambridge and has been thinking about extreme volcanic risk scenarios since joining the centre in January 2020. In particular, Lara has been exploring the systemic nature of volcanic risk from the view point of cascading and compound risks. The idea of this post here is to provide some thoughts that might interest the EA community from a different perspective. I am also slowly catching up with the existential risk literature (this is partly time, but also because I wanted to provide a fresh insight initially without thoughts being diluted by later reading), so if you know literature that may be connected with some of the themes we cover, then please let us know. This really is the start of us thinking about this topic and as you’ll see there’s lots of uncertainty and we’d welcome some thoughts and questions about this generally to assess the gaps going forward. Challenging assumptions and why we think the current risk may be underappreciated The focus of impacts from large explosive eruptions has so far focussed on the initial cooling effect (which could be substantial), but the effects are far more varied than this, which we’ll discuss in later in this article and in our modern, connected world, perhaps means that we could more vulnerable to these. In this post we aim to challenge two notions that have been put forward in the existential risk community previously: 1) That the risk from volcanic eruptions is ‘natural’ and hasn’t changed/won’t change going forward 2) That humans have survived 2000 centuries therefore the natural risk must be low The first assumption is challenged by recent studies which show that anthropogenic climate change increases the climatic cooling effect of large magnitude explosive eruptions (potentially by as much as 60%; Aubry, 2021 & Fasullo et al 2017); climate change itself also may increase the likelihood of triggering eruptions through glacial retreat and sea level change. Furthermore as we explore below, the more extreme climatic effects are not always attributed to the largest magnitude eruptions, in other words, you don’t need a ‘supereruption’ to cause global climatic impacts. All these factors, along with new ice core records showing large explosive eruptions are more common than values Ord 2020 used, mean that our current base rates for global catastrophic risk and existential risks might be higher than initially appreciated. The 2nd assumption seems to be more based on hu...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: EA residencies as an outreach activity , published by Buck on the AI Alignment Forum. [This was partially inspired by some ideas of Claire Zabel's. Thanks to Jessica McCurdy, Neel Nanda, Kuhan Jeyapragasan, Rebecca Baron, Joshua Monrad, Claire Zabel, and the people who came on my Slate Star Codex roadtrip for helpful comments.] A few months ago, some EAs and I went on a trip to the East Coast to go to a bunch of Slate Star Codex meetups. I'm going to quote that entire post here (with a couple edits): Our goals are: - to meet promising people at the SSC meetups and move them into the EA recruiting pipeline - to spend some time with promising new EAs, eg those at student groups, in the hope that spending a few hours of focused one-on-one time with one of us will help get them more into EA. Like, I think 80K finds people who are excited about AI safety stuff but aren't very knowledgeable about it yet; I think that those people can maybe get a lot out of a few hours' conversation with a few people who have worked professionally on this stuff. - to visit EAs who are "in holding" doing things like PhD or EtG tech jobs, with possible good outcomes being that they'll be fired up wrt EA and more likely to do really impactful EA stuff on a timescale of like a year, or that their improved (Bay Area/professional EA) connections make it easier for them to spot good opportunities or move into doing more impactful work. - (less primary) to talk to hardcore EAs and swap arguments and get to know each other better Here's why I think it's worth us talking to various promising new EAs and enthusiastic EAs who haven't worked in the EA scene full time: - There are a lot of accumulated arguments about EA topics which I think it’s really helpful to think about but which are hard to access when you only know EAs on the internet, because those arguments haven't been written up clearly or at all, or because their writeups are hard to find and rely on background knowledge that you don't know how to acquire. - A lot of the time, EAs present versions of arguments that are strong enough to convince you to tentatively think that it's worth engaging seriously with the possibility that the conclusion might be true, but which have a bunch of holes in them that require substantial thinking to fill. Sometimes EAs (eg me) make the mistake of conflating these two levels of strength of argument, and act as if people should be persuaded by the initial sketch. One way that I notice when I'm making this mistake is by getting in arguments with people who've thought about stuff more than me. I hope that talking to more knowledgeable EAs might help some of the EAs we hang out spot holes in their understanding that might help improve their understanding and their epistemics. Here is a reason that I think that having SF Bay Area EAs talk to rationalists in these cities at SSC meetups is plausibly worthwhile: When smart people are skeptical of some of my weird beliefs, eg that AI x-risk is really important, or that they should consider working on EA stuff, or that long term we should consider radically restructuring the world to make it better for animals, a lot of the time their disagreement stems from something true about the world that the arguments they've seen didn't address. This is hard to avoid because if you try to write an argument that addresses all the potential concerns, it will be incredibly long. But this makes me think that it's often really high impact for people who have thought a lot about these arguments to talk to people who have heard of them but felt very unpersuaded. My predictions mostly matched my impressions of what happened. But I think you might be able to get many of these benefits more efficiently by doing something more like a residency, where you spend a relatively long time in eac...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: We're Rethink Priorities. AMA , published by Peter Wildeford on the AI Alignment Forum. Hi there, We're the staff at Rethink Priorities and we would like you to Ask Us Anything! We'll be answering all questions tomorrow on Friday, 13 December. About the Org Rethink Priorities is an EA research organization focused on influencing funders and key decision-makers to improve decisions within EA and EA-aligned organizations. You might know of our work on the impact of cage-free corporate campaigns, invertebrate welfare as a cause area, the risk of nuclear winter, or running the EA Survey, among other projects. We spend 80% of our time working on research relevant to farmed and wild animal welfare. You can see all our work to date here. Over the next two years we plan to try to find new actionable interventions to improve animal welfare, further analyze nuclear risks, use polling to find winning policy changes, study EA movement growth, and much more. About the Team Marcus A. Davis - Lead Researcher Marcus A. Davis works on Rethink Priorities strategy and oversees research. He previously co-founded Charity Science Health, where he systematically analyzed global poverty interventions, led cost-effectiveness analyses, and oversaw all technical aspects of the project. Before joining the Charity Science Health team, he ran Effective Altruism Chicago and worked with Rethink Charity coordinating outreach to local EA groups around the globe. Peter Hurford - Lead Researcher Peter Hurford works on Rethink Priorities strategy and oversees research. He also is a Data Scientist at DataRobot. He co-founded Rethink Charity, and is on the board of Charity Science Health and Animal Charity Evaluators. He has reviewed and produced research on cause prioritization and effective altruism since 2013. David Moss - Senior Research Analyst David Moss is a Senior Research Analyst at Rethink Priorities. He previously worked for Charity Science and has worked on the EA Survey for several years. David studied Philosophy at Cambridge and is an academic researcher of moral psychology. Kim Cuddington - Research Analyst Kim Cuddington is a Research Analyst at Rethink Priorities and is an Associate Professor at the University of Waterloo. She has a PhD in Zoology, a Masters in Biology, and a Masters in Philosophy. She also has a background in ecology and mathematical modeling. Derek Foster - Research Analyst Derek Foster is a Research Analyst at Rethink Priorities. He studied philosophy and politics as an undergraduate, followed by public health and health economics at master's level. Before joining RP, Derek worked on the Global Happiness Policy Report and various other projects related to global health, education, and subjective well-being. Luisa Rodriguez - Research Analyst Luisa Rodriguez is a Research Analyst at Rethink Priorities and a Visiting Researcher at the Future of Humanity Institute. Previously, she conducted cost-effectiveness evaluations of nonprofit and government programs at ImpactMatters, Innovations for Poverty Action, and GiveWell. Saulius Šimčikas - Research Analyst Saulius Šimčikas is a Research Analyst at Rethink Priorities. Previously, he was a research intern at Animal Charity Evaluators, organized Effective Altruism events in the UK and Lithuania, and worked as a programmer. Neil Dullaghan - Junior Research Analyst Neil Dullaghan is a Junior Research Analyst at Rethink Priorities. He is also a Ph.D. candidate in Political and Social Science at the European University Institute. He has volunteered for Charity Entrepreneurship and Animal Charity Evaluators. Before joining RP, Neil worked as a data manager for an online voter platform. Jason Schukraft - Junior Research Analyst Jason Schukraft is a Junior Research Analyst at Rethink Priorities. Before joining the RP team, Jason ear...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: A Case and Model for Aggressively Funding Effective Charities, published by aaronhamlin on the AI Alignment Forum. [This is cross-posted from my Medium account and referenced on my personal website. I've pasted the article in its entirety (plus images to keep the reader going) here for convenience. Special thanks to those who gave early feedback on this article.] Here’s the common wisdom from the nonprofit sector: Avoid providing or taking significant funding that comes largely from one source. But is that always good advice? If it is good advice, then no one told the larger nonprofits. Their funding is undeniably concentrated with funding from few funding sources within the same domain. This is how most nonprofits get large. Further, nonprofits who get their primary income from either individual donations or institutional funding—where we tell nonprofits to go—comprise just 8% of nonprofits. Unless the nonprofit is a good candidate for government grants or in-kind corporate donations, then it’s unlikely to grow significantly. Also, being underfunded as a nonprofit and unable to pick up the remainder brings its own frustration. That’s because a failure while being underfunded makes it hard to tell whether a nonprofit’s intervention was inherently ineffective or if it just didn’t have the funding it needed to succeed. No funding, on the other hand, provides no useful feedback. Given how funding currently takes place—quite conservatively—perhaps we should encourage a more aggressive approach. I’d like us to consider the main goals of both the nonprofit and funders—referring particularly to funders with $100M+ resources. Then, appreciating any constraints that are present, let’s consider an alternative funding model—one that includes concentrated funding of greater than half, or even much more, of a nonprofit’s income. Charitable Goals Just so we’re on the same page, let’s be clear on what each groups’ goals are. Funders’ Goals Funders—like typical nonprofits—generally have a vision of what they set out to do, a particular problem (or class of problems) they want to solve. They want to have the greatest impact possible with their funds. They must factor in a number of issues concerning their grant recipients, including their ability to achieve the sought outcomes. Nonprofits’ Goals Nonprofits—the ones getting the funding—also have a vision. But unlike funders, these are the organizations that do the lifting to get the work done. Most nonprofits have the constant issue of making sure they bring in enough money to do the work that moves them closer to their organization’s vision. When is significant funding too concentrated? Of course, there are some real cases when concentrated funding actually is bad. 1. The funder mandates conditions that compromise the nonprofit’s work. It may also make sense for a nonprofit itself to refuse concentrated funding. If a funder compromises a nonprofit’s ability to carry out its mission, then receiving concentrated funding is bad. We might see this with a funder that puts heavy restrictions on funding or adds unreasonable obstacles. This can keep the nonprofit from being as nimble as it needs to be—particularly smaller or newer nonprofits. In any case that a funder substantially compromises a nonprofit’s ability to advance its mission, that’s a valid reason for the nonprofit to refuse funding. 2. The nonprofit has many existing funding sources. If there are multiple sources of funding for a nonprofit that are easily within reach and sufficiently large, then it may not make sense for a funder to provide especially concentrated financial support. A smaller grant may make sense here—particularly if the nonprofit doesn’t have significant room for extra funding. Technically, this means a nonprofit isn’t that neglected. If the organization can ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Project Ideas in Biosecurity for EAs, published by Davidmanheim on the AI Alignment Forum. In conjunction with a group of other EA biosecurity folk, I helped brainstorm a set of projects which seem useful, and which require various backgrounds but which, as far as we know, aren't being done, or could use additional work 1 . Many EAs have expressed interest in doing something substantive related to research in bio, but are unsure where to start - this is intended as one pathway to do so. Note: I'm also happy to hear from people who weren't involved in our brainstorming about additional ideas - but privately! Please don't post them as comments, both because we aren't necessarily endorsing their usefulness / relevance, and because many project ideas are close to infohazards, and we don't advise people going and doing such work without (private) discussions about risks and precautions, to avoid unilateralist's curse. (For further information, see this comment.) Ideally, this post will be updated as people publish work on these topics - let me know and I can link to Contributions, or perhaps even things to mark Done. What is this list for? We think that each of these is both a substantive and valuable question, which we'd like to see someone answer well. We think they are minimally info-hazardous, but still urge some degree of mindfulness about the issue. All of these projects should start with literature reviews - there is relevant work on all of these, and you need to know about it. Sometimes, the paper that does what we asked for exists - and if so, finding it is helpful. If not, a literature review is, by itself, often a useful post / paper, and for some of the questions, it's all that is needed. If you're not sure where to start, here's a good basic introduction. If you do a literature review, and think there is more to be done, or want to publish them and aren't sure how, or want feedback, there are many researchers that can advise or help on next steps. (But only ask once you have drafts of the literature review, or better, project plans - until that point, the goal is to see if more people can do research, and have more EAs able to do this type of work on their own!) If you're fairly confident you have a track record that shows you know how to do this type of work, many seem like good subjects for grant proposals. They would also be clear evidence that you can do research. If you're interested in academia, like getting into a graduate program is biosecurity, publishing a paper is a great idea. (If you're interested in working in EA research, since doing such projects is a good way to show people you can do that as well.) And if you're in school, and think you can make one of these into a thesis or paper, that would be great as well. Note that many of these, or parts of them, could be something as short as a good EA forum post, but some could easily be as long as a PhD dissertation - or more. A critical part of doing research is narrowing your scope based on what you can do! Ideas by Discipline / Subject Areas We've split these up roughly by area of knowledge or type of work they involve. Many could be approached more than one way, but it's useful even though disciplinary boundaries are always a bit overly restrictive and imprecise. Economics Analysis of size/other characteristics of bioeconomy versus other transformative tech economies past and present. Additional Rob Carlson-like estimates for overall technology proliferation, similar to e.g./, http://www.synthesis.cc/synthesis/2016/03/on_dna_and_transistors Economic assessment of the cost to do a given type of project, for example, analysis of bio-related job salaries in different sectors across nations, estimating market sizes in different countries, economic proxies (e.g. reagents, raw materials, capital etc.)...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: A ranked list of all EA-relevant (audio)books I've read , published by MichaelA on the AI Alignment Forum. Or: "50+ EA-relevant books your doctor doesn't want you to know about" This post lists all the EA-relevant books I've read since learning about EA,[1] in roughly descending order of how useful I perceive/remember them being to me. (In reality, I mostly listened to these as audiobooks, but I'll say "books I've read" for simplicity.) I also include links to where you can get each book, as well as remarks and links to reviews/summaries/notes on some books. This is not quite a post of book recommendations, because: These rankings are of course only weak evidence of how useful you'll find these books[2] I list all EA-relevant books I've read, including those that I didn't find very useful Let me know if you want more info on why I found something useful or not so useful. I'd welcome comments which point to reviews/summaries/notes of these books, provide commenters' own thoughts on these books, or share other book recommendations/anti-recommendations. I'd also welcome people making their own posts along the lines of this one. (Edit: I think that recommendations that aren't commonly mentioned in EA are particularly valuable, holding general usefulness and EA-relevance constant. Same goes for recommendations of books by non-male, non-white, and/or non-WEIRD authors. See this comment thread.) I'll continue to update this post as I finish more EA-relevant books. My thanks to Aaron Gertler for sort-of prompting me to make this list, and then later suggesting I change it from a shortform to a top-level post. The list Or: "Michael admits to finding a Harry Potter fan fiction more useful than ~15 books that were written by professors, are considered classics, or both" The Precipice, by Ord, 2020 See here for a list of things I've written that summarise, comment on, or take inspiration from parts of The Precipice. I recommend reading the ebook or physical book rather than audiobook, because the footnotes contain a lot of good content and aren't included in the audiobook The book Superintelligence may have influenced me more, but that’s just due to the fact that I read it very soon after getting into EA, whereas I read The Precipice after already learning a lot. I’d now recommend The Precipice first. See here for some thoughts on this and other nuclear-risk-related books, and here for some thoughts on this and other authoritarianism-related books. Superforecasting, by Tetlock & Gardner, 2015 How to Measure Anything, by Hubbard, 2011 Rationality: From AI to Zombies, by Yudkowsky, 2006-2009 I.e., “the sequences” Superintelligence, by Bostrom, 2014 Maybe this would've been a little further down the list if I’d already read The Precipice Expert Political Judgement, by Tetlock, 2005 I read this after having already read Superforecasting, yet still found it very useful Normative Uncertainty, by MacAskill, 2014 This is actually a thesis, rather than a book I assume it's now a better idea to read MacAskill, Bykvist, and Ord's book on the same subject, which is available as a free PDF Though I haven't read the book version myself Secret of Our Success, by Henrich, 2015 See also this interesting Slate Star Codex review The WEIRDest People in the World: How the West Became Psychologically Peculiar and Particularly Prosperous, by Henrich, 2020 See also the Wikipedia page on the book, this review on LessWrong, and my notes on the book. I rank Secret of Our Success as more useful to me, but that may be partly because I read it first; if I only read either this book or Secret of Our Success, I'm not sure which I'd find more useful. See here for some thoughts on this and other authoritarianism-related books. The Strategy of Conflict, by Schelling, 1960 See here for my notes on this book, and h...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: EA is a Career Endpoint, published by AllAmericanBreakfast on the AI Alignment Forum. The EA movement has a lot of money. Why is it so hard to launch good projects? We can shed light on this by comparing EA grantmakers with for-profit firms. They have a list of investment projects. Each offers an expected rate of return: in dollars for for-profit firms, and in altruistic utilons for EA funders. Firms and EA Funders will invest their capital in projects offering return superior to the hurdle rate or cost of capital. The hurdle rate for a for-profit firm is the expected rate of return on an investment in the stock market. If the best investment project available offers a 9% rate of return, but the stock market offers a 10% rate of return, then the firm will not invest in the project. Instead, they should return it to shareholders as a dividend. Otherwise, they will underperform the market, and shareholders will sell the stock. For EA funders, the investment decision is a little tricker. First, they are constrained by their mission. For example, the mission of EA Infrastructure Fund reads, in part: While the other three Funds support direct work on various causes, this Fund supports work that could multiply the impact of direct work, including projects that provide intellectual infrastructure for the effective altruism community, run events, disseminate information, or fundraise for effective charities. Money is fungible. In theory, so are utilons. But if you donate to EA Infrastructure Fund, they are not going to use it to fund direct work, and they are not going to return it to you as a dividend if they can't find a use for it. So they have to find mission-aligned projects. They could simply give out grants in descending order from highest-value/most-mission-aligned to least. This might result in throwing away cash on risky/low-value projects that aren't aligned with their mission. Past a certain point, that seems unwise. So they need to set a hurdle rate, similar to the one that for-profit firms must consider. A minimum threshold of value, security (non-riskiness), and mission alignment. They need to set the bar and hold it firmly in place. Determining where to set the bar is another challenge. If they set it too low, they'll throw away money. If they set it too high, they'll have money sitting around with nothing to do. This isn't necessarily bad, though. They can save it for the future, in hopes that more high-quality projects will appear later. It might seem like they could just use that extra money to invest in developing more high-quality projects. Perhaps they could create a school or workshop to help low-quality projects turn into high-quality projects. However, that in itself is a project. If they had a great idea for how to go about it, a strong team committed to the idea, and access to whatever outside resources they needed to make it a success, then it might be a high-quality project and surpass the investment bar. If not, though, they would reject that idea along with the rest. They money would sit around unspent. What makes a project high-quality isn't just the idea itself. "A project to generate higher-quality EA projects" is the barest whisp of an idea. The concept needs to be much more specific, with a fairly detailed plan, a team of demonstrated excellence and clear ability to succeed fairly well organized and committed to it. That's not something you typically put together with one blog post. So EA funders shouldn't lower the bar just because they can't find adequate outlets for their money right now. That would mean they never set a bar in the first place. There's also not an obvious way of finding more high-quality projects. Finally, there's no guarantee that the influx of wealth into the movement will last. Saving that money for the right opportu...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Introducing Fish Welfare Initiative, published by TomBill on the AI Alignment Forum. We’re excited to announce the launch of Fish Welfare Initiative (FWI), a new EA organization incubated under Charity Entrepreneurship. Our mission is to reduce the suffering of fish as much as possible. We aim to achieve this via a two-stage process: Identifying which welfare improvements, fish species, and countries have the highest potential for impact. Implementing a pilot program based on our findings, which we can later scale up or pivot to a new approach. In this post, we make a case for focusing on fish and outline our plan for doing so. Why focus on fish? Others in the effective altruism community have already argued that working on fish could be high-impact (see here, here, and here). Below we examine working on fish through the ITN framework. Importance: Fish are farmed in massive numbers: 111 billion fish are alive in aquaculture at any given point, mostly in intensive systems. 0.79 to 2.3 trillion more wild-caught fish are slaughtered annually. To put this into perspective, there are 31 billion terrestrial farmed animals alive at any given point [1]. Since fish, like other groups of farmed animals, are so numerous, scale will unfortunately not be a limiting factor anytime soon. Of course, scale only matters insofar as the fish involved live miserable lives. Sadly, fish suffering can be extreme. While different species, different regions, and different farming techniques involve different welfare challenges, some common issues include bad water quality and stocking densities, parasites, limited ability to express natural behaviors, and prolonged deaths without prior stunning. For a more complete list of fish welfare issues, see Compassion in World Farming’s report on the welfare of farmed fish. There is also now a scientific consensus that fish very likely feel pain [2]. Neglectedness: Currently, few groups advocate for fish welfare. However, this is changing as fish welfare becomes a greater focus in both academia and advocacy organizations [3]. We expect that fish will be a future focus of the animal advocacy movement, as chickens are currently. Tractability: This is the most uncertain aspect of working on fish issues, given the little historical advocacy and public support there has been for fish. However, there are several reasons in favor of fish being tractable: There is a growing scientific literature on the welfare needs of many species, which helps advocates know what standards to promote [4]. Some of these welfare needs, mostly relating to stunning before slaughter, have already been implemented. For instance, most UK rainbow trout are now stunned before slaughter, in large part due to support and pressure from the RSPCA and Humane Slaughter Association [5]. Just last week, Tesco announced that it would stop selling live fish in their Polish locations, at least partly in response to pressure from advocacy groups [6]. Some changes, such as improving dissolved oxygen levels for farmed fish, may not be very costly to implement [7]. We hope that our work will provide further evidence to the tractability of fish. For more information on why we chose fish and the causes of their suffering, see our previous blog post: Why focus on fish? Which fish? Currently, we intend to focus primarily on farmed fish. Unlike wild-caught fish, humans influence the whole lives of farmed fish, not just their deaths. Additionally, the number of farmed fish stands to increase as the aquaculture industry continues to grow [8]. However, we do not mean to say that we should not work on the welfare of wild-caught fish and we are open to doing so in the future. Some neglected fish groups that we probably will not focus on for the foreseeable future but are still promising include juvenile fish ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: It's OK to feed stray cats, published by Julia_Wise on the AI Alignment Forum. Write a Review This is a linkpost for http://www.givinggladly.com/2020/01/its-ok-to-feed-stray-cats.html Before we had kids, Jeff and I fostered a couple of cats. One had feline AIDS and was very skinny. Despite our frugal grocery budget of the time, I put olive oil on her food, determined to get her healthier. I knew that stray cats were not a top global priority, and that this wasn’t even the best way of helping stray cats, but it was what I wanted to do. . . . . . The bike path near where I live has a lot of broken glass on the ground nearby. My family likes to go barefoot in the summer, and a lot of people walk their dogs there. Last summer I started bringing a container when we went out and cleaning a patch of ground each time. Picking up glass gave me something a little goal-oriented to do while the kids were playing. The kids got excited about spotting pieces of glass and pointing them out to me. Neighbors would stop and join me for a while. . . . . . I don’t want to hold these up as an example of impact. They’re not, or at least not examples of any important impact. I think there are way too many narratives encouraging people to practice small acts of kindness that produce equally small benefits. Women especially may be encouraged to see their life’s impact as resting on their service to friends, family, and local community. That’s why I felt kind of worried to find myself engaging in these small acts. I want people to look at the big picture and aim high. If you’ve been taught that “doing your part” meant recycling and a bit of volunteering, you’ll need to find something more ambitious if you want to make a bigger difference. But it can be painful to stare at the scale of the world’s problems, and I don’t recommend doing it all the time. Not every part of your life will be optimized for maximum altruistic impact. Some of those small acts can be pretty satisfying. Humans do best when we’re in connection with other humans. And we feel mastery when we have small goals that we can meet. Doing your best for a stray cat, bringing the snacks to a game night, going to a rally, or helping a neighbor restart their car are achievable in a way that “reduce the risk of nuclear war” is not. They also strengthen your relationships with those around you. (One year when my coworkers and I were preparing for the EA Global conference, one of our speakers went for a walk in Oakland and was gone for a surprisingly long time. It turned out someone had flagged him down and asked him to help move her furniture. He said it was refreshing to spend half an hour doing something so obviously not the best use of his time.) As Gregory Lewis argues, it’s unlikely that any one action is going to be optimal for all your goals. The food that’s tastiest is unlikely to also be the most nutritious and also the most ethically produced. So you might need to make some tradeoffs, and acknowledge that both chocolate and dark leafy greens are good, but not for the same things. Prioritize big problems. Spend a good chunk of your money and/or your time working on them. But in your other time, do what’s refreshing and restorative to you. Some of that will purely hedonic — sleeping in, music, cake. And some might be small acts of kindness that make your day brighter, even though they’re not saving the world. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: APPG on Future Generations impact report – Raising the profile of future generation in the UK Parliament, published by weeatquince on the AI Alignment Forum. Introduction for EA Forum I have copied below the impact report for the All-Party Parliamentary Group for Future Generations. It was a pain to write because just as I finished the report we went from “having almost no impact” to “having some impact” as our request for a new Committee to scrutinise how the UK prepares for future risks was approved. Ah well! It is my first year working on such a project, and as such it is hard for me to judge whether we have done a good job or just been lucky (or even unlucky, or badly run). That said I hope this provides a reasonable yardstick to think about the impact of policy influencing, that you find it an interesting tale and that it gives a sense of what working in policy is like. The write-up does not assess whether trying to improve policy, (such as policy on future risks) will actually lead to clear counterfactual impact on the world and I leave this part of the puzzle to readers. If I was giving advice to others taking on similar projects I would say: Put yourself in a position of influence. You can create change by working with those who have power and taking opportunities when they arise. For example finding and working with or for political actors who are aligned with the change you want to create. Find quality experts. You can get access to high quality experts through the combination of having a role in the politics/government sphere and being willing to ask (politely with confidence and credentials). We have had some really top level speakers at our events. Policy development is never as simple as you think and experienced input is super useful. For developing policy an hour conversation with the CEO of a government agency can be worth days of desk research. I would also add that: I am unconvinced the EA community gets policy and has prioritised the correct policy areas. For example if you believe the longtermist arguments that top programmers should work on AI alignment, it does not at all follow that good policy people can have more impact on AI policy compared to policy on resilience, macroeconomics, institution design, nuclear non-proliferation, climate change, etc. Similarly bednets are likely not the answer to international development policy, and the effect of policy on international development is under researched by EA folk. (I will hopefully write more on all of this shortly). If you think this is a good project and want to support it in any way or have feedback on it do get in touch. We are developing our plans for 2020-21. (A better formatted pdf version of the below is available here.) ––––––––––––––––––––– Introduction Thank you for reading our impact report. We hope you find it an interesting examination of the work of the APPG for Future Generations.The All-Party Parliamentary Group for Future Generations was established in 2017 with a view to represent and to safeguard the rights of future generations and to push back on political short termism. We support our Members and Parliamentarians to fairly consider the interests of all future generations and ensure that they have the resources to work and plan for the long-term. To effectively assess the impact that our work has had over the past year, we have produced this report which details both the clear, and likely impact that the APPG has had from 1st March 2019 - 31st May 2020. Like many APPGs we are funded by various charitable actors: the Centre for Effective Altruism, the Berkley Existential Risk Initiative, the Long Term Future Fund and the Survival and Flourishing Fund. This report demonstrates to our funders how an active APPG can play a role in moving debate forward, as well as facilitatin...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Disappointing Futures Might Be As Important As Existential Risks, published by MichaelDickens on the AI Alignment Forum. Confidence: Possible Summary Perhaps the most concerning risk to civilization is that we continue to exist for millennia and nothing particularly bad happens, but that we never come close to achieving our potential—that is, we end up in a "disappointing future." [More] A disappointing future might occur if, for example: we never leave the solar system; wild animal suffering continues; or we never saturate the universe with maximally flourishing beings. [More] In comparison to civilization's potential, a disappointing future would be nearly as bad as an existential catastrophe (and possibly worse). We can make several plausible arguments for why disappointing futures might occur. [More] According to a survey of quantitative predictions, disappointing futures appear roughly as likely as existential catastrophes. [More] Preventing disappointing futures seems less tractable than reducing existential risk, but there are some things we might be able to do. [More] Cross-posted to my website. Introduction As defined by Toby Ord in The Precipice, "An existential catastrophe is the destruction of humanity’s longterm potential." Relatedly, a disappointing future is when humans do not go extinct and civilization does not collapse or fall into a dystopia, but civilization[1] nonetheless never realizes its potential. The most salient (although perhaps not the most probable) example of a disappointing future: civilization continues to exist in essentially the same form that it has for the past few hundred years or so. If we extrapolate from civilization's current trajectory, we might expect the long-run future to have these features: The human population size stabilizes at around 10 billion. Global poverty ceases to exist, and all humans become wealthy by today's standards. Scientific and societal advances make people somewhat happier, but not transformatively so. Humans continue not to care about wild animals' welfare. Wild animal suffering continues to massively dominate human happiness, such that sentient life as a whole experiences more suffering than happiness. We never populate other planets. Call this the "naively extrapolated future". We could certainly extrapolate other plausible futures from civilization's current trajectory—for example, if we extrapolate the expanding circle of moral concern, we might predict that future humans will care much more about animals' welfare. And if humans become sufficiently technologically powerful, we might decide to end wild animal suffering. I don't actually believe the naively extrapolated future is the most plausible outcome—more on that later—but I do think if you asked most people what they expect the world to look like a thousand years from now, they'd predict something like it. A note on definitions: Under the definitions of "existential catastrophe" and "disappointing future", it's debatable whether a disappointing future counts as a type of existential catastrophe. But when people talk about interventions to reduce existential risk, they almost always focus on near-term extinction events or global catastrophes. If civilization putters around on earth for a few billion years and then goes extinct when the sun expands, that would qualify as a disappointing future. It might technically count as an existential catastrophe, but it's not what people usually mean by the term. If we want to reduce the risk of a disappointing future, we might want to focus on things other than typical x-risk interventions. Therefore, it's useful to treat disappointing futures as distinct from existential catastrophes. In this essay, I argue that disappointing futures appear comparably important to existential catastrophes. I do not atte...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: What actually is the argument for effective altruism?, published by Benjamin_Todd on the AI Alignment Forum. We just released a podcast with me about what the core arguments for effective altruism actually are, and potential objections to them. I wanted to talk about this topic because I think many people – even many supporters – haven’t absorbed the core claims we’re making. As a first step in tackling this, I think we could better clarify what the key claim of effective altruism actually is, and what the arguments for that claim actually are. I think it would also help us improve our understanding of effective altruism. The most relevant existing work is Will MacAskill's introduction to effective altruism in the Norton Introduction to Ethics, though it argues for the claim that we have a moral obligation to pursue effective altruism, and I wanted to formulate the argument without making it a moral obligation. What I say is also in line with MacAskill's definition of effective altruism. I think a lot more work is needed in this area, and don’t have any settled answers, but I hoped this episode would get discussion going. There are also many other questions about how best to message effective altruism after it's been clarified, which I mostly don't get into. In brief, here’s where I’m at. Please see the episode to get more detail. The claim: If you want to contribute to the common good, it’s a mistake not to pursue the project of effective altruism. The project of effective altruism: is defined as the search for the actions that do the most to contribute to the common good (relative to their cost). It can be broken into (i) an intellectual project – a research field aimed at identifying these actions and, (ii) a practical project to put these findings into practice and have an impact. I define the ‘common good’ in the same way Will MacAskill defines the good in “The definition of effective altruism”, as what most increases welfare from an impartial perspective. This is only intended as a tentative and approximate definition, which might be revised. The three main premises supporting the claim of EA are: Spread: there are big differences in how much different actions (with similar costs) contribute to the common good. Identifiability: We can find some of these high-impact actions with reasonable effort. Novelty: The high-impact actions we can find are not the same as what people who want to contribute to the common good typically do. The idea is that if some actions do far more to contribute than others, we can find those actions, and they’re not the same as what we’re already doing, then – if you want to contribute to the common good – it’s worth searching for these actions. Otherwise, you’re failing to achieve as much for the common good as you could, and could better achieve your stated goal. Moreover, we can say that it’s more of a mistake not to pursue the project of effective altruism the greater the degree to which each of the premises hold. For instance, the greater the degree of spread, the more you’re giving up by not searching (and same for the other two premises). We can think of the importance of effective altruism quantitatively as how much your contribution is increased by applying effective altruism compared to what you would have done otherwise. Unfortunately, there’s not much rigorously written up about how much actions differ in effectiveness ex ante, all considered, and I’m keen to see more research in this area. In the episode, I also discuss: Some broad arguments for why the premises seem plausible. Some potential avenues to object to these premises – I don’t think these objections work as stated, but I’d like to see more work on making them better. (I think most of the best objections to EA are about EA in practice rather than the underlying ide...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Investing to Give: FP Research Report, published by SjirH on the AI Alignment Forum. Write a Review See below for the executive summary. The full report can be found here. For context, see also our previous forum posts on our plans to set up a Long-Term Investment Fund and the early stages of this research project. Investing to give In 1784, the French mathematician Charles-Joseph Mathon de la Cour wrote a parody of Benjamin Franklin’s then-famous Poor Richard’s Almanack. In it, Mathon de la Cour joked that Franklin would be in favour of investing money to grow for hundreds of years and then be spent on utopian projects. Franklin, amused, thanked Mathon de la Cour for the suggestion, and left £1,000 each to the cities of Philadelphia and Boston in his will. This money was to be invested and only to be spent a full 200 years after his death. As time went by, the money grew, and in 1990 Boston received an impressive $5 million and Philadelphia $2.3 million, which was spent on charitable causes on behalf of Ben Franklin.[1] Benjamin Franklin is one of the first people we know of who practised investing to give: purposely investing funds at one point in time in order to have more impact later. This report investigates how promising this strategy is today, and whether we could do even better than Franklin did. In particular, we are trying to answer whether, if we want to maximise our impact as philanthropists, we should do one of two things: either give to the highest-impact opportunities available now, or invest in order to give even more impactfully at a later date. At Founders Pledge, we are considering launching a Long-Term Investment Fund for our members who would like to invest to give for maximum long-term impact.[2] This Fund would take contributions from members, invest them, and disburse the resulting funds to nonprofits at those times when the long-term impact of doing so appears highest, whether this is in five years or in 500 years. This research project on investing to give is key to our ongoing decision process on whether we should create such a Fund. Therefore, this project’s primary purpose was to evaluate investing to give from a long-term impact perspective, but we have also looked into its potential from the perspective of benefitting the current generation, and from the perspective of averting animal suffering in the near term. In this summary, we highlight the key findings of our research project and their practical significance. For a more detailed and exhaustive explanation of our approach, our model, and the evidence and reasoning supporting our findings, we refer the reader to our full report. 1. Mary and our proxy model We start by answering a proxy question, featuring the fictional Founders Pledge member Mary. Mary cares deeply about others regardless of where or when they live. She has $1 million that she wants to spend on making the world a better place in a way that has the highest expected long-term impact: she is open to opportunities that have a high chance of failing but would yield an outsized reward if successful. So, how can Mary best achieve this impact? Should she allocate her $1 million to a Fund which invests her money and then gives to the highest-impact funding opportunity Founders Pledge is able to find? Importantly, for this proxy question, we choose to disregard what we call investment-like giving opportunities. We also fix the timeline of investing to give at 10 years, and assume equity market index funds as our investment strategy. The implications of releasing these restrictions are discussed later. In order to answer the question, we estimate Mary’s expected impact of investing to give relative to her expected impact of giving today. We identify three key factors: The financial returns we are able to achieve in 10 years: ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: AMA: Elizabeth Edwards-Appell, former State Representative, published by ElizabethE on the AI Alignment Forum. Edit 16 Jan: I answered a few more questions and will try to get to the rest tomorrow! Also, here's my Ballotpedia link if you want a list of the bills I sponsored. Note that a bill which legalized syringe service programs isn't listed because of the way bills with more than 10 sponsors are processed on the back end of our legislative services office's software. Edit 11 Jan: I see that I got some more questions after I signed off at the end of the day on Saturday; I can't answer them right now, but I'm going to try to get them all answered by the end of this week. Hi everyone! Aaron Gertler asked me to come do an AMA, and today is the day! When I decided to run for New Hampshire state office in 2014, I was an ideological anarchist. I moved to a different part of my city, filed to run as a Democrat, campaigned, and won my primary. My election to the State House became virtually assured at that point, and I decided it was finally time to read a series of blog posts I'd heard about called the Sequences. It suddenly felt real to me, that I'd have a tiny bit of power over other people's lives, and I wanted to be sure my head was on straight: that good arguments convinced me and bad arguments failed to convince me. Reading and internalizing the material caused me to realize none of my confidence was justified and that I'd have to start over from scratch to build a new world view and new political beliefs. When I was sworn into office that December, I didn't have much except lots of confusion, a desire to do the best I could with the small opportunity I had in front of me, and knowledge of a community centered around something called "effective altruism." My first term ended in 2016 and I won my re-election campaign on the same day Trump defeated Clinton. I spoke at EA Global in 2017 and 2018, the recordings of which are available upon request. I decided not to run for a third term in 2018 for many reasons, one of them that I was earning a yearly salary of $100 as a State Rep! Ask Me Anything! Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is:
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Biology project in search of first author: imaging the brain of popular farmed insect Black Soldier Fly, published by Holly_Elmore on the AI Alignment Forum. I developed this project as an employee of Rethink Priorities. Without access to a lab or instrument core facilities, I cannot complete it myself. I will gladly collaborate with anyone who wants to do the imaging work to obtain funding or connections. I also commit to assisting whoever completes this project in publishing the results in an academic journal if they so desire. The project is very straightforward, but potentially high impact because Black Soldier Fly larvae are and will be farmed in such numbers and because the study of its nervous system has been so neglected. Because of the short timeline and defined labor requirements, I think this is an excellent opportunity for a high school, undergraduate, or graduate student to gain low-committment lab experience while working on an effective animal altruism/animal welfare project. If you are interested in working on this project, have a lead on someone who is, or want to share useful resources, please message me at holly@rethinkpriorities.org. Abstract Black Soldier Fly (Hermetia illucens) is poised to become one of the largest insect crops in the coming decades, with trillions of larvae projected to be raised for slaughter each year. Yet little is known about the capacities of these animals for sentience or suffering. H. illucens is a dipteran, in the same Order as powerhouse model insect Drosophila melanogaster. Comparatively much is known about the cognitive sophistication of D. melanogaster as well as their capacity to suffer, and this information could be leveraged to assess the capacities of H. illucens. Here, I proposed confocal or lightsheet microscopy of larval H. illucens brains so that the images may be compared to those of D. melanogaster. Research Plan Specific aims Obtain detailed images of the H. illucens larval brain. Use detailed images of the H. illucens larval brain to compare to D. melanogaster’s larval brain, which has been extensively studied in connection to its behavior, which has been used to infer D. melanogaster experience. Improve our understanding of the experiences of H. illucens larvae. Predict the experience of H. illucens larvae under farmed conditions. Research design and methods The plan is to obtain detailed images of the brain using confocal or lightsheet microscopy. No culturing should be necessary, so any larvae will do. (It would be ideal to use the same strain as farms, though they may not be available in small enough quantities, and little is known about the worldwide genetic structure of H. illucens.) New protocols may have to be developed for preparing H. illucens tissue for imaging, though the well-developed D. melanogaster protocols may suffice and at the very least serve as an informed starting point. Images of the H. illucens larval brain will be compared to similarly-obtained images of the D. melanogaster larval brain, which has been linked to experiences of pain and indicators of possible suffering and sentience by extensive study. The H. illucens image should be taken with a specific D. melanogaster reference in mind so they can be prepared as similarly as possible to minimize uncontrolled variation between them. The selection of a D. melanogaster reference will depend on many factors, most notably the availability of similar technology and skill for the H. illucens imaging and how well that reference captures brain features relevant to sentience and suffering. Budget and Justification Obtaining larvae: ~$20 from pet food stores or free from colleagues. Extra expense may be justified to obtain strains being used in agriculture, although it is not clear how distinct these are from those available for sale in...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: I'm Michelle Hutchinson, head of advising at 80,000 Hours, AMA, published by Michelle_Hutchinson on the AI Alignment Forum. Write a Review I found Will’s and Buck’s AMAs really interesting. I’m hoping others follow suit, so I thought I’d do one too. What I work on: I’m head of advising (what we used to call ‘coaching’) for 80,000 Hours. That means I chat to people who are in the process of making impact-focused career decisions and help them with those decisions. I also hire people to the team, and manage them - currently we have one other adviser, and we have another joining us next year. Alongside my usual calls, I answer career related questions in other formats, for example on the 80,000 Hours podcast (the episode will come out next year). My background: I joined 80,000 Hours from the Global Priorities Institute, which I set up with Hilary Greaves. Before that I ran Giving What We Can and did the operational set up of the Centre for Effective Altruism. I have a philosophy PhD on prioritising in global health. I wrote about how I initially got involved with effective altruism here. I’ll be answering in a personal capacity so I won’t comment much on 80,000 Hours overall strategy except as it relates to the advising team. I’m very happy to answer questions related to career decisions, and to work I’ve done in the past. Right now I’m on maternity leave with my first baby, so how fast I respond will depend on how he behaves himself. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Can we drive development at scale? An interim update on economic growth work, published by smclare, AidanGoth on the AI Alignment Forum. Disclaimer: This is an interim report and the views expressed here do not represent "house views" of our employer Founders Pledge Introduction Global health and development is still arguably the most popular EA cause. For example, payouts from the Global Health and Development EA Fund comprise 45 percent of the total amount of money granted from EA Funds. Almost all of this spending supports so-called “randomista”-type development: direct interventions that have strong experimental evidence of effectiveness. This allocation is justified by the claim that these interventions are the most cost-effective way to improve the lives of people in low- and middle-income countries (LMICs). Earlier this year, John Halstead and Hauke Hillebrandt published an EA Forum post that argued this is likely mistaken. In “Growth and the case against randomista development” they write that past poverty alleviation has overwhelmingly been achieved by economic growth, not direct interventions. They argue that the magnitude of the gains of growth are so large that interventions which can increase growth rates are likely more cost-effective even if there is less evidence of their effectiveness or they have a low chance of success. The post generated a lot of discussion and commenters raised several important potential objections. These included: Growth work is not neglected and there are no good marginal funding opportunities Economic growth does not make people much happier Economic growth does not help the poorest of the poor We are clueless about the causes of growth Implementing better economic policies faces political economy challenges that EA funding cannot overcome Over the past few months, we have spent between 100 and 150 hours looking deeper into these challenges to try to determine the likelihood of finding concrete, cost-effective funding opportunities to promote economic growth. We conducted a brief literature review, but given the breadth of the subject matter and the uncertainty of the research question we relied heavily on conversations with experts. After about 30 such interviews, we’ve decided to stop looking for concrete funding opportunities for now. So far we haven’t found any growth-focused policies or programs which experts agree would be highly-valuable to support. We think good opportunities probably exist, but identifying them will require thorough evaluations of potential funding opportunities. Since evaluating policy-focused interventions requires considerable investment from both us and representatives from the organisation under investigation, we’re deprioritizing this project for now. We’re posting this wrap-up to share what we’ve learned, get feedback on our current conclusions, and stimulate further discussion on this important topic. Is growth work neglected? A key question we looked into was whether or not research and advocacy into economic growth is relatively neglected compared to direct, randomista-style interventions. A complication here is that almost all development programs, including randomista programs, affect growth at some level. This makes it difficult to separate out funding for the policy-focused work we’re interested in. For example, at first glance the International Growth Centre seems like it would be a relevant funding opportunity with a large budget. After further investigation, though, our impression is that the IGC’s work is more in the randomista school.[1] If one were to simply add up all the money multilateral organisations like the World Bank, Official Development Assistance (ODA) agencies, and large NGOs spend on work they classify as “economic growth”, it would be a large amount—much more than $1...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Formalising the Washing Out Hypothesis, published by dwebb on the AI Alignment Forum. Thanks to the members of the Global Priorities Reading Group at the Paris School of Economics, especially David Bernard, Christian Abele, Eric Teschke, Matthias Endres, Adrien Fabre, and Lennart Stern, for inspiring this post, and for giving me great feedback. Thanks too to Aaron Gertler for very helpful comments. Brief Summary Longtermists face a tradeoff: the stakes of our actions may be higher when looking further into the future, but predictability also declines when trying to affect the longer-run future. If predictability declines quickly enough, then long term effects might “wash out”, and the near term consequences of our actions might be the most important for determining what we ought to do. Here, I provide a formal framework for thinking about this tradeoff. I use a model in which a Bayesian altruist receives signals about the future value of a neartermist and a longtermist intervention. The noise of these signals increases as the altruist tries to predict further into the future. Choosing longtermist interventions is relatively less appealing when the noise of signals increases more quickly. And even if a longtermist intervention appears to have an effect that lasts infinitely long into the future, predictability may decline sufficiently quickly that the ex ante value of the longtermist intervention is finite (and therefore may be less than the neartermist intervention). Intro Longtermism is roughly the claim that what we ought to do is mostly determined by how our actions affect the very long-run future. The intuition that underlies this claim is that the future might be very long and very big, meaning that the vast majority of value is likely to be realised over the long-run future. On the other hand, the predictability of the effects of our actions is likely to decrease as we extend our time-horizon to the very long-run future. For example, it may be impossible to have a predictable and significant effect on the state of the world more than 1,000 years from now. Altruists thus face a trade-off: if we attempt to improve the future over the long run rather than in the near term, there may be higher stakes, but less predictability. If the predictability of the effects of our actions declines quickly enough to counteract the increased stakes, then near term effects will dominate our ex ante moral decision-making, contrary to the claims of the longtermist. This objection to longtermism has been called the “washing out hypothesis” and the “epistemic challenge to longtermism”, and you can find further discussions of it in the links. It is seen as one of the most important and plausible objections to the claims of the longtermist. In this post, I aim to provide a simple mathematical framework for thinking about the washing out hypothesis that formalises the tradeoff between stakes and predictability. Model summary The basic idea behind the model is as follows: An altruist tries to determine the best intervention by carrying out cost-effectiveness calculations. We assume that these exercises will yield an unbiased but noisy signal of the value of an intervention at every time t in the future. In order to account for the fact that predictability decreases as we extend the time horizon, we assume that the noise on these cost-effectiveness signals will increase as the altruist looks further into the future. Using a Bayesian framework, we can show that this gives the altruist an as-if discounting function, where the altruist acts “as if” the future matters less. The altruist has perfectly patient preferences, so they do not discount the future because they “care” about the future less (see Hilary Greaves’ discussion for why we might think this is ethically inappropriate). Rather, ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Other comments that make my day: What people have said when signing up to GWWC, published by lukefreeman on the AI Alignment Forum. I read every single new member signup survey filled in when someone takes a Giving What We Can pledge. This means that several times a week I'm blessed with what is the favourite part of my job: reading the "other comments" that people leave just before they complete a pledge. This along with the question about how GWWC influenced where they donate sparks some incredibly heartwarming things to share. This is part of what gets me out of bed in the morning (sometimes as early as 5:30am due to the varied timezones across our global community). I've recently started sharing some of these with our team of volunteers and they've also found them to be inspiring. One thing that consistently strikes me is that the impact of joining the community extends beyond the impact of those whom our donations help: the donor is also impacted, often mentioning how they find meaning in this commitment. Many of you have advocated for GWWC/EA in your personal lives without seeing the impact ("referred by a friend" is one of our top sources of new members). It can be demotivating not seeing the impact of your efforts, so... Here are some anonymised messages (from the past month) showing you the the impact that you have when you spread the word: Being part of a community feels meaningful and powerful to me. I am thrilled to see the effect we can have together. You shifted how I view myself in relation to the rest of the world, makes me realise that even right out of college I have an opportunity to make change. The Pledge helps me feel more comfortable making a lifestyle change knowing that others have done so (irrational as that may be) and helping me realise the positive impact I want to make with my life. I am motivated to make a real impact. I hope that by making this commitment, I connect to a movement of like-minded people empowered to minimise suffering in the world. As a curious, inquiring mind, the kind of work you do here is exactly enough to convince me to go into action rather than stay with the status quo of, "yeah I would contribute, but what’s the point" or "it’s wasted". A grand mission as far as I’m concerned. I never signed up, because I thought it was not my time, but when I saw “Giving what we can” on Instagram I was like “oh, right! I can become a member as a student now and donate 1% at least” and then I can my easily promote “Giving what we can” and say that I also do it and recommend fellow students to join. Main point: It's really good that you are on Instagram now and spreading the word there. I want to get better at tracking my giving and keeping myself accountable, and I think Giving What We Can, can help in that regard. I’ve started donating through the my local EA organisation and you have motivated me to slowly increase my donations up to 10% within a year. Giving What We Can has caused me to pause and think about where my donations go, and whether or not those donations are doing the most good that they could do. I now know look for more effective causes rather than what I “feel” will do the most good. I was skeptical about charities misusing money and confused about where to donate in the first place, although it’s something I knew wanted to do. I was influenced in terms of confidence in and the necessity of charity, as well as overcoming indecision by making donation strategy simple. I now understand that simply giving is not enough: I must do the research so that my donations can have the greatest impact possible. I now will be donating over the course of my life a lot more than I otherwise would have. I have always been interested in doing good, but I had no idea how much of a difference donating to the RIGHT charities can make...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: EA Survey 2020: Cause Prioritization, published by David_Moss on the AI Alignment Forum. Summary Global Poverty is the highest rated cause overall We found support for longtermist and meta causes to increase with higher self-reported engagement in EA We also observed higher support for neartermist causes in non-male respondents across engagement levels, though there was no gender difference in support for longtermist causes among more engaged respondents Comparing ratings across separate EA surveys, we observe a decrease in support for global poverty over time, and an increase in support for animal welfare and AI risk Full Scale Responses We asked respondents to evaluate a series of different causes[1] on the same 5 point scale as used in previous years.[2] Comparing mean ratings across causes As the same participants rated multiple causes, we used a linear mixed model, with respondent as a random factor, to compare the mean ratings of different causes. This confirms that the mean rating for Global Poverty is significantly higher than all other causes, followed by Cause Prioritization and Reducing Risks from AI. AI Risk and Cause Prioritisation receive very similar mean ratings to each other and are the second most highly ranked. Biosecurity, Climate Change, EA Movement Building and Existential Risk (other) all receive similar ratings (although Biosecurity and Existential Risk (other) do differ significantly[3]). Animal Welfare and Broad Longtermism are the next highest ranked, followed by Nuclear Security and Meta (not movement building) and Mental Health. Top Cause Percentages As in previous years, we report the percentages of respondents rating each cause as the ‘top cause.’ Of course, this is essentially just looking at one level of the responses shown in the graph above. While this leads to simple headline findings (e.g. which cause has the most people rating it ‘top’), it is likely more informative to look at the full range of responses. One result that may be of particular interest, however, is support for Biosecurity (and pandemic preparedness), given the pandemic. This increased from 4% in 2018 and 2019 to 6% in 2020. Relationships Between Causes We explored relationships between ratings of different causes by conducting an exploratory factor analysis. This procedure aims to identify latent factors underlying the data (for example, support for longtermism might be related to support for a number of different longtermist causes). Across a series of different models, we identified three factors underlying the data, with the same causes associated with them to similar degrees. These were: Note: Broad longtermism and Animal Welfare only very weakly loaded onto their respective factors. Exactly how to interpret each factor is, of course, somewhat open to debate, but we think that responses to the causes in each of these different groupings can, to a significant degree, be thought of as reflecting common factors, such as support for existential risk reduction causes or neartermist causes. Predictors of cause ratings To simplify analysis, we reduced the ratings of the individual causes above into the three groupings identified by our EFA above (‘longtermist’ ‘meta’ and ‘neartermist), by averaging the scores for each of those categories. As before, we used a linear mixed model to account for the fact that respondents each rated multiple causes. We provide the raw average ratings for each individual cause in the tables in Appendix 2. Another decision we took to simplify the model was to only examine the influence of people’s level of self-reported engagement with EA and gender. The first plot below simply shows the mean ratings for each of the three broad cause areas across engagement levels. As we can see, average support for Near-termist causes declines with increa...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Get 100s of EA books for your student group , published by velutvulpes on the AI Alignment Forum. If you run an EA student group we’d be interested in potentially enabling you to receive dozens to hundreds of EA books for you to use and give out at your student group. This service is run by a new student group support team made up of: James Aung, Emma Abele, Bella Forristal, and Henry Sleight; with support from Ed Fage. If eligible, you’d be able to on-demand request books to be delivered to you within a few days and we’d cover the costs of the books and delivery. Giving out EA books is a potentially quite cost-effective means of outreach: We think books are great because you can get someone to engage with EA ideas for ~10 hours, without it taking up any of your organiser time. Even if a given recipient is only ~20% likely to read the book, we believe it would still be cost-effective to give out the book. We think the main bottleneck in these large book projects is finding ways to give people books in a way that doesn’t come across as weird or strange in your local context. If you are interested in receiving dozens, hundreds, or even thousands of EA-relevant books for your local group, we’d love for you to order them through our service. Below we list out some example ways in which you might give out books at your group. Give out books as part of your programs and events If you run a program such as an Introduction to EA Program/Fellowship, you could give out EA books to all your participants You can give away copies of books at your speaker events, intro talks, socials, careers fairs, and meet-ups. You can add an option to your event feedback forms for people to tick if they want to receive an EA book, and then deliver the book to them afterwards Give out books via your mailing list You could run regular book giveaways via your mailing-list where people can sign up to receive a book. You could then either deliver them the books you’ve received in bulk, or use our service for us to mail them the book directly. (estimate: 2-5 hours) You can offer a free book in return for signing people onto your mailing list at your activities’ fair General tips We recommend you offer a selection of different books (not just one), only give them to people who show interest, and combine the book give-aways with mailing list sign-ups and other activities/offerings. If you are interested in signing up your group for this service, we’d love to talk to you and chat about the details in more depth. Please start by filling out this expression of interest form. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: A Model of Patient Spending and Movement Building, published by NunoSempere, trammell on the AI Alignment Forum. This project began during Nuño's 2020 summer research fellowship at FHI. Phil was the project mentor. Motivation The EA movement has tradeoffs to make about where to deploy its capital and labor. However, for now, these decisions seem like they are mostly made heuristically and intuitively. To make those decisions more robust, we have set up a reasonably general model to try to capture the most important dynamics. We hope that the model is informative enough to influence decisions directly, and that it motivates more gathering and systematization of empirical data about variables that the model finds crucial (rate of expropriation, the shape of returns to movement building, etc.). We also hope that it inspires further modelling work. Setup The model looks something like: That is, the social movement has access to labor and capital. In combination, they can be: Allocated to paid movement-building efforts, which return more labor Allocated to direct work, which returns goods in the world (malaria nets, etc.) Alone, capital can be: Transformed into more capital with time Transformed into labor through hiring (only possible in one of the two models; this is why this step is greyed out in the diagram) Alone, labor can be: Left alone to produce more labor, or decay, depending on the specifics of the model Allocated to earning to give, which returns more capital (only possible in one of the two models; this is why this step is grayed out in the diagram) Note that the diagram only lays out the possible flows of labor and capital, but many parameters and functions determine how exactly that flow looks in practice. The paper defines these in more detail, but some which turn out to be important are: Utility is isoelastic in "direct work", meaning that as the quantity of "direct work" (e.g., malaria nets delivered) increases, the utility function is assumed to have constant curvature, in a certain sense. For instance, as the number of malaria nets delivered increases, they get sent to places where the need for them is less great: this would imply a curvature that is less than linear. In our model, this curvature is represented by η. η = 1 defines a logarithmic utility function, η > 1 defines a function which exhibits sharper diminishing returns than the logarithm, and η < 1 defines a function that exhibits returns which diminish more slowly. (η = 0 defines linear utility.) Diminishing returns under some values for η in a isoelastic utility function Capital has a rate of return r δ is the “discount rate” (more technically, the time preference), i.e. the rate of intrinsically caring less about the future (pure time preference) we have—if any—plus the annual rate at which we collectively face risks of expropriation, value drift, existential catastrophe, etc. Labor, if left alone, depreciates (i.e., movement participants leave or die), at a rate d Labor productivity grows at a rate γ, to reflect the growing labor productivity seen in the economy as a whole Using these functions and parameters, we set up a system in terms of rather general functions for the production of direct work and recruitment. We then solve it to arrive at the optimal solution, either across all points in time (if we allow for both earning to give and hiring) or only asymptotically (if we don't.) If you are familiar with what the terms "isoelastic" and "constant elasticity of substitution" mean, you might want to just read the document. Main results If the social movement is "patient" (in that δ < r − γη), then under some reasonable assumptions about diminishing returns to movement building (see this comment), our model finds that total labor (i.e., total movement size) approaches a constant value. T...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Ambitious Altruistic Software Engineering Efforts: Opportunities and Benefits, published by Ozzie Gooen on the AI Alignment Forum. This is part 1 of what I expect to be a 3-part series. The next parts will focus on the costs of these technical projects and more specific ways to kickstart them. Meta Rigor: Writing based on my experiences and education in the tech industry. I spent around 50 hours on this series plus some sporadic thinking and discussion. I focused more on idea quantity than neatness or data. Intended Audience: Effective altruists interested in either funding or working on ambitious software projects. History: This series was originally written as one Google Doc in March 2021 for private conversations. I've since done some updating to post it publicly. One important update since this document was written is that the CEA tech team has seemed to really up hiring considerably. This seems great, though I'm sure we could have even more, so it still seemed useful to post this. About me (Ozzie Gooen): I’ve been thinking about this a lot over the last several years. I joined 80,000 Hours as a web developer in 2013 hoping to do major/ambitious work, but there I realized that the funding situation at the time wasn’t large enough for most ambitious software efforts. I’ve since spent time in other startups, making my own startups, and doing consulting for small and large companies. Recently I’ve been planning what work QURI should do. We’re considering focusing on engineering. Some of the motivation for this topic is to help make decisions for QURI. Acknowledgments: Many thanks to Aaron Gertler, Rachel Bui, JP Addison, Daniel Kokotajlo, Adam Gleave, Daniel Eth, Oliver Habryka, Jonas Vollmer, and Nuño Sempere for their comments. Motivation When I think of, There’s an elite community with a net worth of over $40 Billion, made up of many genius mathematicians, engineers, and entrepreneurs and they’re trying to optimize the future of the world I think of things like this: Lots of monitors/ From Iron Man 2 (From Iron Man 2) Right now we clearly don’t have this. Open Philanthropy and other core effective altruism organizations are highly philosophically focused as opposed to technically focused. This seems like a good beginning, but perhaps a suboptimal end. Large technical implementations would be expensive ($10 Million to $100 Million+ per year). They would be different from current setups in some key ways. But I think they could be worth it. Perhaps the best analogy would be that of the finance industry. Early on there were clever individuals or small teams who would intuitively make bets with very little information. Financial bets are very similar to making altruistic decisions. Charitable funding decisions are particularly equivalent, but so might be more generic things like career decisions. Over time the financial sector became far more sophisticated, with intense specialization, formalization, and expertise. Data-heavy and quant-based approaches have become decisive in much of the market, and continue to expand. We might expect altruistic decisions to follow a similar trajectory; begin with clever people using intuitions (like with existing EA funders), and expand to use more data and automation. One counter-example in the field of finance is venture capital firms that invest with (relatively) little data. However, they exist in environments with applications like Crunchbase, AngelList, and other tools, that organize and charge for data. Select Project Ideas What should we code? I'm less certain about particular software interventions than I am about us being able to find some good bets (assuming we have good people). I personally see software opportunities all around me, but it's difficult to put them into distinct large-project-size clusters. Lots of internal...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: You are probably underestimating how good self-love can be, published by CharlieRS on the AI Alignment Forum. I am very grateful to the following people, in general, and for their helpful feedback on this post: Nick Cammarata, Kaj Sotala, Miranda Dixon-Luinenburg, Sam Clarke, Mrinank Sharma, Matej Vrzala, Vlad Firoiu, Ollie Bray, Alan Taylor, Max Heitmann, Rose Hadshar, and Michelle Hutchinson. This is a cross-post from LessWrong. I almost didn't post here, since this type of content is a little unfamiliar to the forum. But it saddens me to see my friends pour their hearts into the flourishing of humanity, and yet hurt so badly. I write later in the post: A lot of people go their whole lives making their self-worth conditional in order to act better: they take damage--dislike or judge themselves--whenever they act imperfectly or realise they are imperfect or don’t achieve the things they want to. In a world as unfair and uncontrollable as this one, I think taking so much damage is often not that functional. Moreover, I claim that you can care deeply while feeling worthwhile and suffused with compassion and affection and joy. It is hard to do the most good when depressed, burned out, or feeling worthless. Even if this is not you, I think self-love might be worth aiming for--especially if you want to do something as difficult as saving the world. I was on a plane to Malta when I realised I had lost something precious. I was struggling to meditate. I knew there was some disposition that made meditation easier for me in the past, something to do with internal harmony and compassion and affection. Alas, these handles failed to impact me. On a whim, I decided to read and meditate on some of my notes. 3h later, I had recovered the precious thing. It was one of the most special experiences of my life. I felt massive relief, but I was also a little scared--I knew that this state would likely pass. I made a promise to myself to not forget what I felt like, then, and to live from that place more. This post is, in part, an attempt to honour that promise. I spent most of my holiday in Malta reading about and meditating on the precious thing, and I now feel like I'm in a place where I can share something useful. This post is about self-love. Until recently, I didn’t know that self-love was something I could aim for; that it was something worth aiming for. My guess is that I thought of self-love as something vaguely Good, a bit boring, a bit of a chore, a bit projection-loaded (I’m lovable; I love me so you can love me too), and lumped together with self-care (e.g. taking a bath). Then I found Nick Cammarata on Twitter and was blown away by the experiences he was describing. Nick tweeted about self-love from Sep 2020 to May 2021, and then moved on to other things. His is the main body of work related to self-love that I’m aware of, and I don't want it to be lost to time. My main intention with this post is to summarise Nick’s work and build on it with my experiences; I want to get the word out on self-love, so that you can figure out whether it’s something you want to aim for. But I'm also going to talk a little about how to cultivate it and the potential risks to doing that. One caveat to get out of the way is that I’m a beginner--I’ve been doing this stuff for under a year, for way less than 1h/day. Another is that I expect that my positive experiences with self-love are strongly linked to me being moderately depressed before I started. What is self-love? Self-love is related to a lot of things and I'm not sure which are central. But I can point to some experiences that I have when I'm in high self-love states. While my baseline for well-being and self-love is significantly higher than it used to be, and I can mostly access self-love states when I want to, most of the time I am n...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: High School EA Outreach, published by cafelow on the AI Alignment Forum. Contributions by the Students for High-Impact Charity Team (Catherine Low, Baxter Bullock, Tee Barnett, David Vatousios and Callum Hinchcliffe), the Run to Better Days Team (Brenton Mayer, Daniel Charles, Laura Koefler), Jessica McCurdy, Daniel, Alex, Jamie Harris and Sebastian Becker[1]. Compiled by Catherine Low. Introductory segments written by Catherine Low. Summary This post compiles summarized reports on several projects and instances in which effective altruism (EA) concepts have been introduced to school students aged 13 to 18 (referred to hereafter as high school students): Guest presenters running workshops in high schools (Run to Better Days and Students for High-Impact Charity). Resourcing university student coordinators to help high school students set up EA-aligned groups in their in high schools (Students for High-Impact Charity). Recruiting and resourcing high school student leaders to run sessions on EA concepts with their peers (Students for High-Impact Charity). Recruiting non-EA teachers run EA sessions in schools (Students for High-Impact Charity). University students running EA sessions as part of the Splash program in USA Universities. EA-aligned teachers presenting concepts in classes and extracurricular clubs. The content delivered to students varied from project to project, and included charity comparisons, ethical questions, cause prioritization, high-impact career choices, and discussions of common EA cause areas. We hope this post will be a useful resource for people who are interested in communicating the basic principles of EA to young people. This post was prompted by Students for High-Impact Charity (SHIC) recently choosing to suspend outreach to high school students. We begin by explaining the generally accepted reasons for why reaching out to high school students may be useful, and our tentative conclusions. This is followed by detailed descriptions of some projects that have been tried, written by that project’s team or coordinator. For each project, we explain the method used and any measured impact. Why choose high school outreach? Many self-identified effective altruists state that they wished they had gained EA knowledge much earlier than they did, so that they could have had a roadmap to effectively improve the world from a younger age. These statements suggest it was worth testing whether high school students are a good group to educate about EA. Our initial reasons for believing that high school students could be a good audience were: They are less likely to have fixed opinions about the best way to do good than people who have been doing altruistic actions for some years. They may be more open to new ideas than older people. They are in a significantly better position to make impactful life decisions than university students or adults, as they haven’t sunk time and resources into a potentially lower impact path. It’s possible to gain access to an audience of high school students more easily than audiences of older people. Anecdotally, EA ideas seem to be more appealing if they’re presented by someone more senior than they are, which most EAs are relative to high school students. There are several ways that reaching high school students could have an impact: Guiding high school students towards higher impact career paths, volunteering and donations. Influencing school fundraisers. Providing a positive first experience of EA concepts, increasing the chances that these students would take action after subsequent exposures to EA—for example, when they are at university. Conclusions Catherine’s conclusions This section was authored by Catherine Low (Manager of SHIC since 2018, closely involved with SHIC since early 2016, and a former teacher). The contribut...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: How bad would nuclear winter caused by a US-Russia nuclear exchange be?, published Luisa_Rodriguez on the LessWrong. Summary In this post, I quantify the severity of the nuclear winter we might expect to result from a nuclear war between the US and Russia (Guesstimate model here). Researchers who have studied nuclear winter estimate that a nuclear war that produced between 50 and 150 teragrams of smoke would make agriculture nearly impossible, causing most people on Earth to starve to death and leaving humanity on the brink of extinction. But most of the research into nuclear winter was done at the height of the Cold War when the US and Russian nuclear arsenals and nuclear policies looked quite different. I previously argued that the US and Russia would be more likely to target each others’ nuclear forces during a nuclear war, rather than target each others’ cities as they would have done during the Cold War. This makes a big difference in whether a US-Russia nuclear exchange would lead to a severe nuclear winter. Nuclear attacks on cities would likely produce much more smoke than attacks on missile silos, military bases, and other nuclear arsenal targets. This is mainly because cities have much more flammable material to burn than the remote wildlands — mostly cropland and grasslands — that surround, for example, missile silos. This leads me to conclude that a nuclear war between the US and Russia would likely produce closer to 31 teragrams of smoke (90% confidence interval: 14 Tg to 68 Tg of smoke) — suggesting that nuclear winter is not as synonymous with US-Russia nuclear war as many effective altruists seem to assume. The ~31 teragrams of smoke that would be vaulted into the atmosphere would undoubtedly produce severe climate effects, likely leading to food shortfalls and regional famines, and killing between 36% and 96% of the world population. I think the finding points us toward being a bit more skeptical of the idea that some effective altruists seem to hold — that a nuclear war between the US and Russia would necessarily lead to a nuclear winter that posed a large risk of extinction. There’s about an 11% chance that 50 Tg of smoke — the threshold at which the literature suggests the resulting nuclear winter would be catastrophic — are released into the atmosphere by a Russia-US nuclear war. To be clear, this 11% risk is non-trivial, and it’s plausible that even a so-called nuclear autumn (the result of between ~5 and ~50 Tg of smoke) would pose some sort of x-risk. As a final point, I’d like to emphasize that the nuclear winter is quite controversial (for example, see: Singer, 1985; Seitz, 2011; Robock, 2011; Coupe et al., 2019; Reisner et al., 2019; Pausata et al., 2016; Reisner et al., 2018; Also see the summary of the nuclear winter controversy in Wikipedia’s article on nuclear winter). Critics argue that the parameters fed into the climate models (like, how much smoke would be generated by a given exchange) as well as the assumptions in the climate models themselves (for example, the way clouds would behave) are suspect, and may have been biased by the researchers’ political motivations (for example, see: Singer, 1985; Seitz, 2011; Reisner et al., 2019; Pausata et al., 2016; Reisner et al., 2018). I take these criticisms very seriously — and believe we should probably be skeptical of this body of research as a result. For the purposes of this estimation, I assume that the nuclear winter research comes to the right conclusion. However, if we discounted the expected harm caused by US-Russia nuclear war for the fact that the nuclear winter hypothesis is somewhat suspect, the expected harm could shrink substantially. December 19, 2019 Update In light of feedback from Carl Schulman, Kit Harris, MichaelA, David Denkenberger, Topher Brennan, and others, I’ve m...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: If you value future people, why do you consider near term effects? , published by Alex HT on the LessWrong. [Nothing here is original, I’ve just combined some standard EA arguments all in one place] Introduction I’m confused about why EAs who place non-negligible value on future people justify the effectiveness of interventions by the direct effects of those interventions. By direct effects I mean the kinds of effects that are investigated by GiveWell, Animal Charity Evaluators, and Charity Entrepreneurship. I mean this in contrast to focusing on the effects of an intervention on the long-term future as investigated by places like Open Phil, the Global Priorities Institute, and the Future of Humanity Institute. This post lays out my current understanding of the problem so that I can find out the bits I’m missing or not understanding properly. I think I’m probably wrong about something because plenty of smart, considerate people disagree with me. Also, to clarify, there are people I admire who choose to work on or donate to near-term causes. Section one states the problem of cluelessness (for a richer treatment read this: Cluelessness, Hilary Greaves) and explains why we can’t ignore the long-term effects of interventions. Section two points at some implications of this for people focussed on traditionally near-term causes like mental health, animal welfare, and global poverty. I think these causes all seem pressing. I think that they are long-term problems (ie. poverty or factory farms now are just as bad as poverty or factory farms in 1000 years) and that it makes sense to prioritise the interventions that have the best long-term effects on these causes. Section three tries to come up with objections to my view, and respond to them. 1. Cluelessness and Long-term Effects Simple cluelessness All actions we take have huge effects on the future. One way of seeing this is by considering identity-altering actions. Imagine that I pass my friend on the street and I stop to chat. She and I will now be on a different trajectory than we would have been otherwise. We will interact with different people, at a different time, in a different place, or in a different way than if we hadn’t paused. This will eventually change the circumstances of a conception event such that a different person will now be born because we paused to speak on the street. Now, when the person who is conceived takes actions, I will be causally responsible for those actions and their effects. I am also causally responsible for all the effects flowing from those effects. This is an example of simple cluelessness, which I don’t think is problematic. In the above example, I have no reason to believe that the many consequences that would follow from pausing would be better than the many consequences that follow from not pausing. I have evidential symmetry between the two following claims: Pausing to chat would have catastrophic effects for humanity Not pausing to chat would have catastrophic effects for humanity And similarly, I have evidential symmetry between the two following claims: Pausing to chat would have miraculous effects for humanity Not pausing to chat would have miraculous effects for humanity (I’m assuming there’s nothing particularly special about this chat - eg. we’re not chatting about starting a nuclear war or influencing AI policy.) And for all resulting states of the world between catastrophe and miracle. I have evidential symmetry between act-consequence pairs. By evidential symmetry between two actions, I mean that, though massive value or disvalue could come from a given action, these effects could equally easily, and in precisely analogous ways, result from the relevant alternative actions. In the previous scenario, I assume that each of the possible people that will be born are as like...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is:I Want To Do Good - an EA puppet mini-musical!, published by spanrucker on the LessWrong. This is a linkpost for Hi folks! I'm a composer who writes music and songs for Cartoon Network. I also make short films! Last year I wrote a post asking if my filmmaking/songwriting skills could be put to use somehow to help promote EA ideas or charities. I ended up collaborating with The Life You Can Save to create this puppet and animation based mini-musical! It aims to playfully discuss some ideas around effective giving in the global health and development arena, and to promote The Life You Can Save. I wanted the video to express my own joy at having found a way to make a large positive impact in the world, and to lightheartedly address some concerns people might have around global charities. For transparency's sake: I self-funded the production costs of the video. I'd love to know what you think! If you like it please consider sharing it to help it get seen by more people. I hope it might pique some curiosity about TLYCS and gain more donations for their recommended charities. As I understand it the team at TLYCS plan to create a pack to use this video as a kicking off point for educating children about effective giving, so I'm interested to learn if it's useful in that area. I also wrote a supporter story on their website with a bit more personal background, if you're interested. If you have any questions, comments or critical feedback fire away! I'd like to learn from this foray and hopefully lend my creative skills to future projects (not necessarily puppet-based!) in the EA world if it seems like a worthwhile thing to do. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: EA Survey 2019 Series: Community Information , published by David_Moss on the LessWrong. Summary More respondents’ level of interest in EA increased over the last year (43%) than decreased (18%). The most common reasons for interest increasing were local EA groups (14%), the respondent being new to EA (12%), the local EA community more broadly (10%), or career change (10%). The most common reasons for interest decreasing were people being too busy (18%), a perceived mismatch between the person’s cause preferences with that of the overall EA community (12%), or finding diminishing returns from involvement in EA (10%). The most commonly cited barriers to further involvement in EA were lack of job opportunities that were a good fit (29%), no close friends in EA (28%), and it being too hard to get an EA job (23%). The main ways people wanted to become more involved in EA were an EA-aligned career (58%), donating more (55%), socialising with EAs (44%), and participating in more local EA events (43%). The factors most often cited as important for retaining people in EA were personal contacts (43%), local EA groups (27%), and reading SlateStarCodex (21%). Among those who knew of someone who had been involved in EA but then became disengaged (27%), the most commonly cited reasons were lack of interest in EA (31%), bad experiences with other EAs (30%), lack of opportunities to implement effective altruism in their lives (28%), and lack of friends or community interested in EA (25%). We found significant gender differences and differences between low/high engagement EAs in what they selected as barriers to further involvement in EA and as important for their retention in EA, however we found few signs of differences between white/non-white EAs. Introduction The 2019 EA Survey included a number of new questions concerning experiences of the EA community, many of which were requested by the Centre for Effective Altruism. Questions about these topics seem particularly likely to raise concerns about the representativeness of the survey sample, since individuals who have had particularly negative experiences of the EA community are plausibly less likely to take the EA Survey. Nevertheless, we think that this data provides important qualitative and quantitative information to the community. Changes in level of interest in EA Respondents were asked “In the last year, how would you say that your level of interest in effective altruism has changed?”. 1934 respondents answered this question. alt_text While the modal response by a large margin was “Stayed the same”, on the whole, we can see that more respondents’ level of interest increased (43%) than decreased (18%) over the last year. Naturally, as mentioned above, the fact that people whose interest has decreased may be less likely to take the survey is potentially a significant factor here. We examine predictors of change in interest in a later section of this post. Changes in level of interest in EA: Qualitative Data Respondents were also asked “If your level of interest in effective altruism has changed, please explain why (if possible).” 968 respondents answered this question (out of 1196 who indicated that their level of interest changed).[1] alt_text Among those who reported that their level of interest decreased, the most common reason given, by a wide margin, was that they had become increasingly busy (17.7%). This was followed by references to “cause preferences” (11.7%). These often alluded to EA being uninteresting if you didn’t share mainstream EA preferences and/or to frustration that EA had come to be dominated by a certain cause area. 9.7% were classified as mentioning “diminishing returns.” Such comments often suggested that respondents thought that they had already internalised or acted on the core EA lessons and ther...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Long-Term Future Fund: Ask Us Anything! , published by AdamGleave on the LessWrong. The Long-Term Future Fund (LTFF) is one of the EA Funds. Between Friday Dec 4th and Monday Dec 7th, we'll be available to answer any questions you have about the fund – we look forward to hearing from all of you! The LTFF aims to positively influence the long-term trajectory of civilization by making grants that address global catastrophic risks, especially potential risks from advanced artificial intelligence and pandemics. In addition, we seek to promote, implement, and advocate for longtermist ideas, and to otherwise increase the likelihood that future generations will flourish. Grant recommendations are made by a team of volunteer Fund Managers: Matt Wage, Helen Toner, Oliver Habryka, Adam Gleave and Asya Bergal. We are also fortunate to be advised by Nick Beckstead and Nicole Ross. You can read our bios here. Jonas Vollmer, who is heading EA Funds, also provides occasional advice to the Fund. You can read about how we choose grants here. Our previous grant decisions and rationale are described in our payout reports. We'd welcome discussion and questions regarding our grant decisions, but to keep discussion in one place, please post comments related to our most recent grant round in this post. Please ask any questions you like about the fund, including but not limited to: Our grant evaluation process. Areas we are excited about funding. Coordination between donors. Our future plans. Any uncertainties or complaints you have about the fund. (You can also e-mail us at ealongtermfuture[at]gmail[dot]com for anything that should remain confidential.) We'd also welcome more free-form discussion, such as: What should the goals of the fund be? What is the comparative advantage of the fund compared to other donors? Why would you/would you not donate to the fund? What, if any, goals should the fund have other than making high-impact grants? Examples could include: legibility to donors; holding grantees accountable; setting incentives; identifying and training grant-making talent. How would you like the fund to communicate with donors? We look forward to hearing your questions and ideas! Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Kessler Syndrome in Effective Altruism, published by aaronmayer on the LessWrong. And how to be mindful with beginners I love Effective Altruism. ❤ That’s not an exaggeration — I truly love the community and the way I’ve grown as a result of joining the movement. I first heard about EA back in 2013 when its messaging was pretty straightforward: use data to donate to more effective charities that will alleviate the suffering of the global poor. Now, the scope of EA has broadened significantly, and the number of people who subscribe to the philosophy of EA has also ballooned. For the record, I think this is fabulous and should celebrate our growth so far! We can and must continue to expand our areas of inquiry, and I’m proud of the way that EA has grown to include animal welfare, long term flourishing, and many more topics. But this growth comes with a byproduct: much more content. While the early content on the web about EA was focused predominantly on global health and development, the current messaging includes things like AI safety research and ancient viruses trapped in permafrost. Given the increase in our interests as a community in the last decade, it’s no wonder that the amount of content on the web about Effective Altruism has skyrocketed as well. But just like rockets, there is sometimes a risk of too much content. In cosmic terms, there is a phenomenon known as Kessler Syndrome, which is a hypothetical (but very plausible) scenario in which the outer atmosphere becomes so clouded with debris from defunct satellites and other space junk that it becomes impossible to safely launch more rockets into space. If such an event were to happen, humans would effectively be locked in (barring some new technology that would clean up outer space), and things would only get worse as time went on, since the space junk could collide with other space junk, leading to more space junk. Locked in or locked out? I worry that something similar may be happening with content online about EA. 10 years ago, there were early forum posts, GiveWell, and a few books by Peter Singer. Now, there are conferences and podcasts and tons of forum posts and lots of books and local EA chapters and newsletters and much, much more. Don’t get me wrong, I love all of this content! As a firm believer in EA, I’m excited by the meteoric rise in activity and the increasing diversity of our interests. However, for newbies to the movement, we may run into a risk of Kessler Syndrome when it comes to online content. I’ll give you an example using someone very near to my heart: my grandma. I recently became the EA NYC co-director through the Community Building Grant at CEA. I’m SO excited for the role, and of course I told my family. My grandma is 93 (and she would absolutely MURDER me if she knew I disclosed her real age in public, so please don’t send this article to her!) - and she did what any curious grandma would do about her grandson’s new interests: she Googled Effective Altruism. Now, I don’t know exactly how she got there, but she wound up calling me about the coming AI apocalypse and whether we should have an emergency plan in case robots start taking over the world. While I think it’s fabulous that my grandma has a budding interest in AI safety, it may not have been the best introduction for her. In effect, she was launched into the vacuum of space (i.e. the internet) and bombarded by the blog posts, podcasts, books, etc. I believe we may risk alienating some newcomers if they feel overwhelmed or confused by the central tenets of EA, what it stands for, and how they can easily get involved. Keep in mind, I don’t think the answers to these tenets are at all hard to come by. In fact, we have more of an apparatus for newcomers than ever before thanks to the amazing work of CEA, 80,000 hours, and pro...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Against neutrality about creating happy lives , published by Joe_Carlsmith on the LessWrong. (Cross-posted from Hands and Cities) (Warning: spoilers for the movie American Beauty.) “Once for each, just once. Once and no more. And for us too, once. Never again. And yet it seems that this—to have once existed, even if only once, to have been a part of this earth—can never be taken back. And so we keep going, trying to achieve it, trying to hold it in our simple hands, our already crowded eyes, our dumbfounded hearts.” Rilke, Ninth Elegy Various philosophers have tried hard to validate the so-called “intuition of neutrality,” according to which the fact that someone would live a wonderful life, if created, is not itself reason to create them (see e.g. Frick (2014) for efforts in this vicinity). The oft-quoted slogan from Jan Narveson is: “We are in favor of making people happy, but neutral about making happy people” (p. 80). I don’t have the neutrality intuition. To the contrary, I think that creating someone who will live a wonderful life is to do, for them, something incredibly significant and worthwhile. Exactly how to weigh this against other considerations in different contexts is an additional and substantially more complex question. But I feel very far from neutral about it, and I’d hope that others, in considering whether to create me, wouldn’t feel neutral, either. This post tries to point at why. I. Preciousness “Earth, loved one, I will. Believe me, you don’t need any more of your springtimes to win me: one is already more than my blood can take. For as long as I can remember, I’ve been yours completely.” Rilke, Ninth Elegy My central objection to the neutrality intuition stems from a kind of love I feel towards life and the world. When I think about everything that I have seen and been and done in my life — about friends, family, partners, dogs, cities, cliffs, dances, silences, oceans, temples, reeds in the snow, flags in the wind, music twisting into the sky, a curb I used to sit on with my friends after school — the chance to have been alive in this way, amidst such beauty and strangeness and wonder, seems to me incredibly precious. If I learned that I was about to die, it is to this preciousness that my mind would turn. Here I think of the final scene (warning: spoilers, violence) of American Beauty, narrated by a character who has just been shot: “I had always heard your entire life flashes in front of your eyes the second before you die. First of all, that one second isn’t a second at all, it stretches on forever, like an ocean of time. For me, it was lying on my back at Boy Scout camp, watching falling stars. And yellow leaves, from the maple trees, that lined our street. Or my grandmother’s hands, and the way her skin seemed like paper. And the first time I saw my cousin Tony’s brand new Firebird. And Janie. And Janie. And. Carolyn. I guess I could be pretty pissed off about what happened to me. but it’s hard to stay mad, when there’s so much beauty in the world. Sometimes I feel like I’m seeing it all at once, and it’s too much, my heart fills up like a balloon that’s about to burst.” Or this passage, in All Quiet on the Western Front, in which a soldier in World War I describes how desirable life, for all its flaws, has come to seem, in the midst of the war, and the ever-present threat of death: “The red poppies in the meadows round our billets, the smooth beetles on the blades of grass, the warm evenings in the cool, dim rooms, the black mysterious trees of the twilight, the stars and the flowing waters, dreams and long sleep – O Life, life, life!” To me, the idea that life is, or can be, “good” doesn’t seem to cover it. “Good” feels too thin and controlled; too compared. The thing I’m talking about feels related to recognizing goodness, but in ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: EA Survey 2020: How People Get Involved in EA, published by David_Moss on the LessWrong. EA Survey 2020: How EAs get involved in EA Summary Personal contacts (16.3%) remain the most common way people that people have first heard about EA, throughout the history of the movement, followed by 80,000 Hours (12.8%) Among EAs who first got involved in EA in 2020, 17.1% first heard about EA through a personal contact and 16.5% from 80,000 Hours Podcasts have increased in importance as a source of people first hearing about EA, accounting for 15.2% of people who got involved in 2020 More than half (50.7%) of respondents cited 80,000 Hours as important for them getting involved in EA A much larger proportion of non-male respondents first heard about EA from a personal contact compared to male respondents Significantly higher proportions of non-male respondents found personal contacts or local groups important for them getting involved in EA Where do people first hear about EA? 1,912 (88%) respondents replied to the question, “Where did you first hear about Effective Altruism?” Note: full size versions of graphs can be viewed by opening them in a new tab. ‘Personal Contact’ was the most selected option (16%) followed by 80,000 Hours (13%), and Book, article, or blog post (9%). In 2019, Book and Article or blog post were separate categories but summed to roughly 11%. Similarly, EA Global and EAGx were separate categories in 2019. The other options remained the same so we can analyze across years. Personal Contact, 80,000 Hours, Podcast, and Local or University Group had an increased share of responses from 2019 (ranging from 1.6% to 3.2% increases). Book, Article, or Blog, LessWrong, Slate Star Codex (SSC), GiveWell, and I don’t remember had a decreased percentage of responses (-1.4% to -1.9%). All remaining categories had a <1% change from 2019. Some of the underlying causes of these shifts in replies will be discussed below. Where People First Hear of EA: Other Of the 167 Other replies, 40% were categorized as fitting into an existing category. About 26% of these reported first hearing about EA from a personal contact, an EA talk/conference, a local group, or through animal advocacy work. A further 26% mentioned a public intellectual or blogger, the majority of which were Peter Singer (28) and Sam Harris (9). Roughly 20% mentioned hearing about EA from social media. Of the 17 responses (10%) which referenced YouTube, 9 mentioned French channels called Mr. Phi and Science4All and 2 mentioned a Polish channel called Everyday Hero. A further 10% referenced some other form of media including Wikipedia, news articles, films, and podcasts. 15 people (9%) referenced an EA or EA-adjacent organization, and another 15 people mentioned a forum or blog. Where People First Hear of EA: Further Details As last year, we also asked respondents to give more details about how they first heard about EA. We then classified these responses into discrete categories. We display these results divided by the category of fixed response that respondents selected (i.e. all the open comment further explanations provided by those who indicated that they first heard about EA from 80,000 Hours). We provide mosaic plots showing the proportion of responses within each superordinate category with the largest number of responses, and include bar charts for the categories with lower numbers of responses in the appendix. Where People First Hear of EA: Changes Over Time Using information on when people first got into EA, we can examine differences in where people first hear about EA across more or less recent cohorts of EAs. Of course, it is important to bear in mind that this does not necessarily represent changes in where people hear about EA across time, since people in earlier cohorts who heard about EA from di...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is:Shelly Kagan - readings for Ethics and the Future seminar (spring 2021) , published by velutvulpes on the LessWrong. This is a linkpost for This is a list of the readings from Shelly Kagan's seminar, “Ethics and the Future,” taught at Yale in Spring 2021. See the original linked Google Doc for full introduction. Background on Existential Risks: 1. Toby Ord, The Precipice, Chapters 3-6 and Appendices C and D (about 124 pages) The Basic Case for Longtermism: 1. Perhaps start with this very brief overview: Todd, “Future Generations and Their Moral Significance” (about 7 pages), which can be found online at:/ 2. Then look at the somewhat longer (but still breezy) exposition in Ord, The Precipice, Intro and Chapters 1-2, and Appendix E (65 pgs.) 3. Then read Chapters 1 and 3 from Nick Beckstead’s dissertation, On the Overwhelming Importance of Shaping the Far Future (about 44 pages) 4. Finally, Greaves and MacAskill, “The Case for Strong Longtermism” (about 25). That will come to about 140 pages, most of which reads fairly quickly. If you want even more (consider what is listed next as recommended but not required)--look at: 5. Bostrom, “Existential Risk Prevention as Global Priority” (17 pages), and also 6. Bostrom, “Astronomical Waste” (10 pages) 7. Finally, there is a passage from Derek Parfit, Reasons and Persons, that is quoted regularly in the longtermist literature (for example, by Beckstead). If you would like to see it in its original context, it is on pp. 453-4 (2 pages). All of these things can be found in the Files folder for the class, other than the Todd, the Ord, and the Parfit. The Social Discount Rate: 1. Start with Cowen, Discount Rates Table, a short passage from his Stubborn Attachments, which gives a quick sense of how even a “modest” discount rate effectively wipes out the significance of the long term future (1 page). 2. Then Parfit, Reasons and Persons, Appendix F (7 pages), for arguments against the social discount rate. 3. Cowen and Parfit, “Against the Social Discount Rate,” (from Peter Laslett & James S. Fishkin (eds.) Justice between age groups and generations, Yale University Press: New Haven, 1992, pp. 144–161) repeats much of the Parfit but gives some additional arguments. To (mostly) avoid the repetition, only read the two introductory pages (pp. 144-145) and the section on “economic arguments” (pp. 150-158). Though the first such economic argument (on opportunity costs) very closely follows the earlier Parfit, it does add some extra details. (11 pages.) 4. Then Ord, The Precipice, Appendix A (6 pages) for further discussion. 5. Next, read Greaves, “Discounting for Public Policy,” section 7, which is pages 404-409 (5 pages). That’s the bit on the “pure” discount rate. (The rest of the paper isn’t required, but is recommended for anyone who would like a thorough (though a bit technical) survey of some of the economics debates on the discount rate.) 6. Finally, Mogensen, “The Only Ethical Argument for Positive Delta” (33 pages). That’s about 62 pages. 7. If you are interested in further discussion of the discount rate from an economist’s perspective, you could take a look at Broome, “Discounting the Future,” (29 pages) though this is primarily on discounting with regard to future resources, not pure discounting of future welfare, so it is only recommended. Population Ethics I: Parfit, Reasons and Persons, Chapters 16-18, and Appendix G (70 pages). Population Ethics II: 1. Start with Boonin, “How to Solve the Non-Identity Problem” (30 pages) 2. Next, Harman, “Can We Harm and Benefit in Creating?” (25 pages) 3. Then McMahan, “Climate Change, War, and the Non-Identity Problem” (27) 4. Beckstead, Overwhelming Importance, Chapter 4 (23 pages) 5. Ord, The Precipice, Appendix B (6 pages) 6. Finally, a few pages from Kagan, “Singer on Killing Animals...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Some thoughts on David Roodman’s model of economic growth and its relation to AI timelines, published by Tom_Davidson on the LessWrong. [Also posted on LW.] I’ve been working on a report (see blog) assessing possible trajectories for Gross World Product (GWP) out to 2100. A lot of my early work focussed on analysing a paper of my colleague David Roodman. Roodman fits a growth model to long-run GWP; the model predicts a 50% probability that annual GWP growth is >= 30% by 2043. I was thinking about whether to trust this model’s GWP forecasts, compared with the standard extrapolations that predict GWP growth of ~3% per year or less.[1] I was also thinking about how the model might relate to AI timelines. This post briefly describes some of my key takeaways, as they don’t figure prominently in the report. I explain them briefly and directly, rather than focussing on nuance or caveats.[2] I expect it to be useful mostly for people who already have a rough sense for how Roodman’s model works. Many points here have already been made elsewhere. Although for brevity I sometimes refer to “Roodman’s extrapolations”, what I really mean is the extrapolations of his univariate model once it’s been fitted to long-run GWP data. Of course, David does not literally believe these extrapolations. More generally, this post is not about David’s beliefs at all but rather about possible uses and interpretations of his model. [Views are my own, not my employers] Economic theory doesn’t straightforwardly support Roodman’s extrapolation over standard extrapolations Early on in the project, I had the following rough picture in my mind (oversimplifying for readability): Standard extrapolations use what are called ‘exogenous growth models’. These fit the post-1900 data well. However, the exponential growth is put in by hand and isn’t justified by economic theory. (Exogenous growth models assume technology grows exponentially but don’t attempt to justify this assumption; the exponential growth of technology then drives exponential growth of GDP/capita.) On the other hand, endogenous growth models can explain growth without putting in the answer by hand. They explain technological progress as resulting from economic activity (e.g. targeted R&D), and they find that exponential growth is implausible - a knife-edge case. Ignoring this knife-edge case, growth is either sub- or super- exponential. Roodman fits an endogenous growth model to the data and finds super-exponential growth (because growth has increased over the long-run on average). So Roodman’s model uses a better growth model (endogenous rather than exogenous). Roodman’s model also has the advantage of taking more data in account (standard economists typically don‘t use pre-1900 data to inform their extrapolations). Overall, we should put more weight on Roodman than standard extrapolation, at least over the long-run. I no longer see things this way. My attitude is more like (again oversimplifying for readability): Although exogenous growth models don’t justify the assumption of exponential growth of technology, semi-endogenous growth models justify this claim pretty nicely._[3] _These semi-endogenous models can explain the post-1900 exponential growth and the pre-1900 super-exponential growth in a pretty neat way - for example see Jones (2001). Roodman’s model departs from these semi-endogenous models primarily in that it assumes population is ‘output-bottlenecked’._[4] _This assumption means that if we produced more output (e.g. food, homes), population would become larger as a result: more output → more people. This assumption hasn’t been true over the last 140 years, and doesn’t seem to be true currently: since the demographic transition in ~1880 fertility has decreased even while output per person increased. (That said, significant behav...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Honoring Petrov Day on the EA Forum: 2021 , published by Aaron Gertler on the AI Alignment Forum. Petrov Day Today we celebrate not destroying the world. We do so today because 38 years ago, Stanislav Petrov made a decision that averted tremendous calamity. It's possible that an all-out nuclear exchange between the US and USSR would not have actually destroyed the world, but there are few things with an equal chance of doing so. As a Lieutenant Colonel of the Soviet Army, Petrov manned the system built to detect whether the US government had fired nuclear weapons on Russia. On September 26th, 1983, the system reported five incoming missiles. Petrov’s job was to report this as an attack to his superiors, who would launch a retaliative nuclear response. But instead, contrary to the evidence the systems were giving him, he called it in as a false alarm, for he did not wish to instigate nuclear armageddon. For more information, see: 1983 Soviet nuclear false alarm incident Petrov is not alone in having made decisions that averted destruction — presidents, generals, commanders of nuclear submarines, and similar also made brave and fortunate calls — but Petrov's story is salient, so today we celebrate him and all those who chose equally well. As the world progresses, it's likely that many more people will face decisions like Petrov's. Let's hope they'll make good decisions! And if we expect to face decisions ourselves, let us resolve to decide wisely! Mutually Assured Destruction (??) The Petrov Day tradition is to celebrate Petrov's decisions and also to practice not destroying things, even when it's tempting. In both 2019 and 2020, LessWrong placed a large red button on the frontpage and distributed "launch codes" to a few hundred "trustworthy" people. A launch would bring down the frontpage for the duration of Petrov Day, denying hundreds to thousands of people access to LessWrong. In 2019, all was fine. In 2020... let's just say some bad decisions were made. And yet, having a button on your own page that brings down your own site doesn't make much sense! Why would you have nukes pointed at yourself? It's also not very analogous to the cold war nuclear scenario between major world powers. For those reasons, in 2021, LessWrong is teaming up with the Forum to play a game of mutual destruction. Two buttons, two sets of codes, and two sets of hopefully trustworthy users. (The button will appear on the homepage on Sunday morning, 8 AM PST.) If LessWrong chose any launch code recipients they couldn't trust, the EA Forum will go down, and vice versa. One of the sites going down means that people are blocked from accessing important resources: the destruction of significant real value. What's more, it will damage trust between the two sites ("I guess your most trusted users couldn't be trusted to not take down our site") and also for each site itself ("I guess the admins couldn't find a hundred people who could be trusted"). For exact rules of the game, see the final section below. Last year, it emerged that there was ambiguity about how serious the Petrov Day exercise was. I'll be clear as I can via text: there is real value on the line here, and this is a real trust-building exercise that was not undertaken lightly by either LessWrong or the Forum. Both sites have chosen recipients who we hope will understand this. How Do I Celebrate? If you were one of the two hundred people to receive launch codes for LessWrong or the Forum, celebrate by doing nothing! Other ways of celebrating: You can discuss Petrov Day and threats to humanity with your friends. You can hold a quiet, dignified ceremony with candles and the beautiful booklets created by Jim Babcock. And you can also play on hard mode: "During said ceremony, unveil a large red button. If anybody presses the button, the cere...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: CEA’s headcount nearly doubled in 2021 (and other updates), published by MaxDalton on the AI Alignment Forum. For CEA's Q3 update, we're sharing multiple posts on different aspects of our work. People At this time one year ago, we had 16 people on our core team. Accounting for confirmed arrivals and departures, we now have 29 people on our core team. Overall, we think we’ve managed to grow the team rapidly while also raising our bar for new hires. Role Changes Nicole Ross is transitioning to the role of manager of the Community Health team. Katie Glass, who was previously the team’s interim manager, is now focused on developing hiring systems and helping to build systems for tracking metrics. Hires In Q3, we made the following hires: Jonathan Michel (Operations Associate, incoming in December) Lizka Vaintrob (Events Generalist, started in September) Ollie Base (Community Events Manager, incoming in November) Jessica McCurdy (Scalable Uni Support, part-time) Will Payne (Groups Associate: Campus Specialist Manager) Kuhan Jeyapragasan (Groups Associate: Campus Specialist Manager, part-time) We had been planning to hire about five people in Q3. We surpassed this target, but some of our new joiners had already been working with us in a contracting capacity, and are simply increasing their hours or becoming more integrated with the team. For at least one hiring round, I think we should have communicated more promptly with applicants and given them more detailed feedback. We’ve increased tracking of applicant communications, and email support for hiring managers, to try to ensure prompt responses and substantive feedback for applicants that make it far in our process. Hiring plans We’re currently hiring for an Executive Assistant and a Finance Associate. We’re also welcoming general expressions of interest, as well as expressions of interest for a Full Stack Engineer. Departures Barry Grimes, Harri Besceli, and Aaron Gertler will transition out of CEA during Q4. Sky Mayhew is transitioning from being a member of the Community Health team to contracting with CEA. Louis Dixon also departed CEA at the end of Q3, replaced in his role as our finance lead by Litawn Gan (as mentioned in a previous update). Morale The average morale reported for Q3 was 7.17/10, compared with 7.03/10 in Q2. Org chart Team retreat We ran our first team retreat since the pandemic in late August/September. 16 people came together in a venue near Oxford. The average likelihood to recommend the event was 9.07/10, and attendees thought the event was 7x more valuable than the counterfactual use of their time (geometric mean). Broadly, we think that this helped a lot with onboarding new hires, and that people left the event feeling excited about the impact we can have together. Operations The Operations team aims to provide the financial, legal, administrative, grantmaking, logistical, and fundraising support that enables CEA, 80,000 Hours, the Forethought Foundation, EA Funds, the Centre for the Governance of AI and Giving What We Can to run efficiently. Operations Associate hiring: We hired Jonathan Michel to run operations in our Oxford office. Jonathan will start in December. Office refurbishment: The office is now fully up and running. We’re still making small improvements to lighting and catering, but users are happy. Improvements to financial systems: We adjusted our financial year in the USA so that it aligns with the UK entity, which will allow us to present consolidated accounts going forward. Audits were completed for both the UK and the US. Customer Relationship Management (CRM) software: We have completed the discovery phase with our Salesforce developer partner, and they have begun to build the CRM. In Q4, our primary focus will be working with the groups team and group organisers to make sure...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: From humans in Canada to battery caged chickens in the United States, which animals have the hardest lives: results, published by KarolinaSarek on the AI Alignment Forum. Write a Review With Charity Entrepreneurship team after spending considerable time on creating the best system we could for evaluating animal welfare, we applied this system to 15 different animals/breeds. This included 6 types of wild animal and 7 different types of farm animal environments, as well as 2 human conditions for baseline comparisons. This was far from a complete list, but it gave us enough information to get a sense of the different conditions. Each report was limited to 2-5 hours with pre-set evaluation criteria (as seen in this post), a 1-page summary, and a section of rough notes (generally in the 5-10 page range). Each summary report was read by 8 raters (3 from the internal CE research team, 5 external to the CE team). The average weightings and ranges in the spreadsheet below are generated by averaging the assessments of these raters. Click to view the report The goal of Charity Entrepreneurship is to compare the different charitable interventions and actions so that new strong charities can be founded. One of the necessary steps in such a process is having a way to compare different animals in different conditions. We have previously written both about our criteria for evaluating animals and about our process for coming to that criteria. This post explains our process and how the results for this system are being applied to different animal conditions. One of the goals of our system was to be applicable across different animals and different situations. We ended up comparing 9 animals (Humans, Hens, Turkeys, Fish, Cows, Chimpanzees, Birds, Rats, Bugs). These animals are not based on consistent biological taxonomy due to limited information being available on certain types (e.g. there was enough information on rats specifically to do a report on them, but for wild birds we had to look at a variety of birds to get sufficient data). We are not concerned about this limitation, as most of the interventions we are considering would hit a wide range of animals (e.g. a humane insecticide would most likely not be target-specific, so the most relevant data here is an index for bugs as a whole as opposed to an index on a specific species.) The reports are formatted so that it is easy to quickly grasp the main information connected with the specific rating. Each report is a summary page with the key information and a short description as to why the given rating, and thus, should be polished and readable to all. Each report was time capped at 1-5 hours, so they are limited in both scope and depth. We are keen to get more information on any of these areas (particularly information that is numerically quantified or related to wild animals, as this information was the hardest to find). Sample report: After each of the reports were drawn up, each summary report was read and evaluated by 8 raters. We tried to get a diverse set of raters but all with a broadly utilitarian and EA framework. Three raters were from our internal CE research team (the staff who created or contributed to the reports) and five raters were external to the CE team, but involved in the animal rights’ research space (e.g. working or interning for EA animal organizations). The CE research team talked over ratings and disagreements openly, but the external raters did not see or disclose any CE ratings until after they had put in theirs. Ethically, people were best described as classical utilitarians, but with some slight variation (e.g. some more prioritarian, some negative leaning utilitarians). We liked the concept of multiple independent raters as there are many soft judgment calls and increasing the numbers of people doing...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: AMA or discuss my 80K podcast episode: Ben Garfinkel, FHI researcher, published by Ben Garfinkel on the AI Alignment Forum. Write a Review [[THIRD EDIT: Thanks so much for all of the questions and comments! There are still a few more I'd like to respond to, so I may circle back to them a bit later, but, due to time constraints, I'm otherwise finished up for now. Any further comments or replies to anything I've written are also still be appreciated!]] Hi! I'm Ben Garfinkel, a researcher at the Future of Humanity Institute. I've worked on a mixture of topics in AI governance and in the somewhat nebulous area FHI calls "macrostrategy", including: the long-termist case for prioritizing work on AI, plausible near-term security issues associated with AI, surveillance and privacy issues, the balance between offense and defense, and the obvious impossibility of building machines that are larger than humans. 80,000 Hours recently released a long interview I recorded with Howie Lempel, about a year ago, where we walked through various long-termist arguments for prioritizing work on AI safety and AI governance relative to other cause areas. The longest and probably most interesting stretch explains why I no longer find the central argument in Superintelligence, and in related writing, very compelling. At the same time, I do continue to regard AI safety and AI governance as high-priority research areas. (These two slide decks, which were linked in the show notes, give more condensed versions of my views: "Potential Existential Risks from Artificial Intelligence" and "Unpacking Classic Arguments for AI Risk." This piece of draft writing instead gives a less condensed version of my views on classic "fast takeoff" arguments.) Although I'm most interested in questions related to AI risk and cause prioritization, feel free to ask me anything. I'm likely to eventually answer most questions that people post this week, on an as-yet-unspecified schedule. You should also feel free just to use this post as a place to talk about the podcast episode: there was a thread a few days ago suggesting this might be useful. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Possible gaps in the EA community, published by Michelle_Hutchinson on the AI Alignment Forum. I’m interested in having a better sense of what new kinds of projects should be set up within the EA community. I think I tend to bias towards scepticism, and so find it easier to get a sense of what worries me about projects than which projects I’m excited about. I thought I’d have a go at writing out a few ideas which seem promising to me. I’d love to hear people’s views on them, and also to read other people’s lists. To provide a nudge towards others producing such lists, I’ve also shared some of the prompts I used to come up with the thoughts below. I haven’t put a lot of time into this list, so I’m not suggesting any, let alone all, are great ideas - they’re just ones I’d be interested to hear more discussion around. I’m also biased by the corners of EA and the world I’ve spent most time in, for example academia. Prompts for ideas Aside from ‘what could we do with more of in EA?’, here are some of the specific questions I considered: How do we win? Along with: How are we currently falling short on that? This is a different way of asking what our theory of change as a movement is, and what part of that theory of change currently seems weakest. For example: I think one way we could make the world far better in decades’ time is by making it the case that all major decision makers (politicians, business leaders etc) use ‘will this most improve wellbeing over the long run?’ as their main decision criterion. Something which would make that most likely to happen is having EA ideas discussed in courses in all top universities. That led me to wonder whether we’re currently neglecting supporting and encouraging lecturers to do that. What have I wanted from EA (but not gotten)? For example: The UK government discussed the possibility of folding the Department for International Development into the Foreign and Commonwealth Office, and subsequently did so. DfID, in addition to having an extremely important mission, was achieving that mission pretty well: It had a reputation for being unusually evidence-based amongst development agencies. I had the general sense that the merger would be bad, and would redirect money from trying to help those in the poorest countries to pursuing British interests abroad. But I didn’t have good evidence about whether it would be good or bad overall, or an idea of what I should do about it if it was bad (write to my local MP? Sign a particular petition?). It’s possible I simply missed the work that was done on this (there certainly is some EA work adjacent to this). What I’d have liked was: A succinct summary of what seemed good and bad about the change to give me an idea of whether I agreed with it. A really clear action plan if I wanted to help in some way. That might include, for example: sample letters to send to your MP, some considerations on what makes letters to your MP more/less likely to succeed (are emails better than physical letters, or vice versa?), a link to where you can find out who your local MP is and what the best way to contact them is. What problems have others experienced in EA? For example: People often appreciate being surrounded by like-minded people. That’s one benefit people often seek from working at an organisation which explicitly identifies as EA. Another possible benefit is a clearer sense that you’re probably heading in the right direction. That comes from others with the same goals as you being able to give you frequent feedback on your direction. But almost all of the impactful positions in the world are at organisations which don’t identify as EA. So it’s important for us to find ways to make sure that wherever they work, people can still have a sense of being often around people with similar values and who help the...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: How to PhD, published by eca on the AI Alignment Forum. Many thanks to Andrew Snyder-Beattie, Howie Lempel, Alex Norman and Noga Aharony for thoughtful feedback. Mistakes are mine. Status: Some obviously right stuff. Some spicy takes. In places I'm trying to illustrate a pattern of thinking rather than an explicit recipe. Aimed at a particular audience, YMMV. These are a few thoughts on how to approach graduate school effectively. This is not a guide or anything of the sort. Just an attempt to write down a set of considerations I use when thinking about my own grad school, and what seems to be helpful from convos I’ve had with other EA PhD-seekers. I have not tried to make this generally applicable. So some background facts in case you are looking for something else: I am a grad student at MIT I work on catastrophic risks from biology My background is synthetic biology/ bioinformatics/ deep learning I have most personal experience with synthetic biology academia My favorite theory of change for addressing these risks goes substantially through EAs taking on a lot more object level work— founding organizations, engineering systems, making scientific progress— than I expect is the median view I still think policy-ish stuff is important; a substantial part of the reason I’m doing my PhD is to be credible to fancy people types I’m not inside-view excited about young longtermist EAs pursuing faculty positions, basically at all. Others I think are reasonable do argue for this, so I’ve tried to include a relevant example. Some general things Academic incentives are nefarious and horrible and will poison your brain. This happens to the best people. You can become a status monster unless you know this in your bones and remind yourself of it every day. Recognize it now, and inoculate yourself by knowing what you want before the poison seeps in. If you want to do anything that isn’t optimizing for academic prestige, like spending some of your PhD research time on publishing directly impactful papers or developing directly impactful technologies, or doing these things later in your career, you will need to have a strategy for managing the ways academic incentives push you to waste your brilliance. This probably involves maintaining and strengthening your EA-adjacent network. This is also broadly important, IMO. If you are doing a PhD for EA career development, remember that 3-7 years is a long time and that you will not just be sacrificing direct impact in that time, but also relationships and EA-specific knowledge and context. Despite the intention to develop career capital, you could come out of a PhD stupider and less useful than you went in if you lose track of what is impactful and are 5 years behind everyone on the best mental models. A PhD is also in many ways a prolongation of the perpetual childhood instantiated in western education systems. I notice that between people of the same age, one of whom just completed a PhD and the other who has been doing direct work for that duration, the PhD is a little “less grown up” on average (this is a comment about the average and not some claim about strict dominance! I love you, all my PhD bearing friends and colleagues). Most PhDs do not teach you many of the life-lesson-y adult-y things you actually need to be effective. E.g.: taking sole ownership and responsibility for solving a real problem rather than optimizing for fake metrics like impact factor and having your PI to fall back on, leading and managing others, communicating with people who are in a very different place than you, robustness in the face of a wide range of challenges instead of narrow specialization on a few, knowing when something is or isn’t worth your time and developing a palpable urgency, learning how effective organizations work, being held accountable f...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: EA Infrastructure Fund: May 2021 grant recommendations, published by Jonas Vollmer, Max_Daniel, Buck, Michelle_Hutchinson, Ben_Kuhn on the AI Alignment Forum. Introduction The Effective Altruism Infrastructure Fund (EAIF) made the following grants as part of its Q1 2021 grant cycle: Total grants: $1,221,178 (assuming all grantees accept the full grants) Number of grants: 26 Number of applications (excluding desk rejections): 58 Payout date: April 2021 We expect that we could make valuable grants totalling $3–$6 million this year. The fund currently holds around $2.3 million. This means we could productively use $0.7–$3.7 in additional funding above our current reserves, or $0–$2.3 million (with a median guess of $500,000) above the amount of funding we expect to get by default by this November. This is the first grant round led by the EAIF’s new committee, consisting of Buck Shlegeris, Max Daniel, Michelle Hutchinson, and Ben Kuhn as a guest fund manager, with Jonas Vollmer temporarily taking on chairperson duties, advising, and voting consultatively on grants. For more detail on the new committee selection, see EA Funds has appointed new fund managers. Some of the grants are oriented primarily towards causes that are typically prioritized from a ‘non-longtermist’ perspective; others primarily toward causes that are typically prioritized for longtermist reasons. The EAIF makes grants towards longtermist projects if a) the grantseeker decided to apply to the EAIF (rather than the Long-Term Future Fund), b) the intervention is at a meta level or aims to build infrastructure in some sense, or c) the work spans multiple causes (whether the case for them is longtermist or not). We generally strive to maintain an overall balance between different worldviews according to the degree they seem plausible to the committee. One report includes an embedded forecast; you can add your own prediction and related comments as you read. We’re interested to see whether we find the community’s prediction informative. The reports from this round are unusually thorough, with the goal of providing more transparency about the thinking of the fund managers. Would you like to get funded? You can apply for funding at any time. If you have any question for fund managers not directly related to the grants described here, you’re welcome to ask it in our upcoming AMA. Highlights Our grants include: Two grants totalling $139,200 to Emma Abele, James Aung, Bella Forristal, and Henry Sleight. They will work together to identify and implement new ways to support EA university groups – e.g., through high-quality introductory talks about EA and creating other content for workshops and events. University groups have historically been one of the most important sources of highly engaged EA community members, and we believe there is significant untapped potential for further growth. We are also excited about the team, based significantly on their track record – e.g., James and Emma previously led two of the globally most successful university groups. $41,868 to Zak Ulhaq to develop and implement workshops aimed at helping highly talented teenagers apply EA concepts and quantitative reasoning to their lives. We are excited about this grant because we generally think that educating pre-university audiences about EA-related ideas and concepts could be highly valuable; e.g., we’re aware of (unpublished) survey data indicating that in a large sample of highly engaged community members who learned about EA in the last few years, about ¼ had first heard of EA when they were 18 or younger. At the same time, this space seems underexplored. Projects that are mindful of the risks involved in engaging younger audiences therefore have a high value of information – if successful, they could pave the way for many more proj...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Invertebrate Sentience Table, published by Daniela R. Waldhorn on the AI Alignment Forum. Write a Review Table Introduction While invertebrates make up the majority of animal species, our knowledge about their capacity for valenced experience is overlooked compared to existing evidence about vertebrates. In particular, whether invertebrates have the capacity to have valenced experience is uncertain, and hence, it remains unclear whether these organisms have a welfare of their own we should care about. Rethink Priorities has been systematically exploring this issue during the past months. First, we examined the philosophical difficulties inherent in the detection of instances of morally significant pain and pleasure in nonhumans. Second, given the current epistemic state about invertebrate consciousness, we have been compiling and analyzing relevant scientific evidence regarding this issue. In particular, we investigated the degree to which different features potentially indicative of phenomenal consciousness are found throughout different taxa. In a second post, we described our approach, the rationale of this project, and its limitations. The features we believe to be most relevant for assessing invertebrate sentience are explained in detail in a third, fourth, and fifth post. In this sixth post, we present our summary of findings, both in narrative form and as a database. Overview The database is available here. It is an interactive table, where we summarize scientific data about 53 features potentially indicative of the capacity for valenced experience and examine the degree to which these features are found throughout 18 representative biological taxa. 12 invertebrate taxa are included: honey bees (genus Apis), cockroaches (genus Periplaneta), fruit flies (Drosophila melanogaster), ants (family Formicidae), spiders (order Araneae), the nematode Caenorhabditis elegans, sea hares (genus Aplysia), moon jellyfish (genus Aurelia), crabs (infraorder Brachyura), crayfish (family Cambaridae), and octopuses (family Octopodidae). For comparative purposes, we included three kinds of non-animal organisms –prokaryotes, protists and plants (kingdom Plantae)– and three vertebrate species –chickens (Gallus gallus domesticus), cows (Bos taurus), and humans (Homo Sapiens). For each taxon and feature, we reviewed the existing literature and determined whether there was sufficient scientific data to make a call as to whether that taxon possesses the feature in question. Then, we evaluated the likelihood that the taxon possesses that feature. For those cases where we found direct evidence, we established four different responses corresponding to four rough probability ranges: “Likely No”: representing credences of 0% - 25% “Lean No”: 25% - 50% “Lean Yes”: 50% - 75% “Likely Yes”: 75% - 100% As mentioned in a previous post, these four “credence buckets” represent our position regarding whether an animal possesses a feature; they do not necessarily represent the extent to which the animal possesses that feature. Given that current evidence about invertebrate consciousness is limited and unequal –i.e. some taxa have been much more studied than others, or specific features, unlike others, are well-studied phenomena– our credences are not necessarily well-calibrated in all cases. Further research is likely to contribute to revising and improving our confidence and reliability in our assessment of features potentially indicative of consciousness in different invertebrate taxa. On top of that, there are several cases where no direct evidence of a specific feature for a given taxon was found. For those cases in which there have been only indirect studies and a specific feature was expected to be observed but, finally, no evidence arises, we used the category “not observed”. When no direct or ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: How many people would be killed as a direct result of a US-Russia nuclear exchange?, published by Luisa_Rodriguez on the AI Alignment Forum. Write a Review Summary In this post, I estimate the number of fatalities caused directly by nuclear detonations in the US/NATO and Russia. I model these effects in Guesstimate using expert surveys and interviews, forecasts made by Good Judgment Project superforecasters, academic research, and media coverage of international relations, along with academic research into the effects of nuclear war and nuclear weapons policy. There are many determinants that factor into the number of people that would die as a direct result of nuclear detonations during a US-Russia nuclear exchange. I consider the following six factors the most important. They make up the key parameters in my model: The targeting strategy (i.e. what kinds of targets will each country attack?) The number of military facilities each country might target Whether each country would also target cities, in addition to military facilities If they were to target cities, the number of cities each country might target The sizes of the nuclear weapons in each country’s nuclear arsenal The population size of the cities that might be targeted during an exchange When I take all of these factors into account, I expect that we’d see a total of 51 million deaths caused directly by nuclear detonations on military and civilian targets in NATO countries and Russia (90% confidence interval: 30 million — 75 million deaths). December 8 2019 Update In light of feedback from Carl Schulman, Kit Harris, MichaelA, David Denkenberger, Topher Brennan, and others, I’ve made several revisions to this post that are now reflected in the text, figures, and estimates in the body of this post. The original post can still be found here. The changes that had the largest bearing on my results included: Changing the way I estimate the number of nuclear weapons that would be used in a countervalue nuclear exchange in expectation so that I don’t accidentally truncate the tails of the distributions (details here and here). Generating a formula that can be directly entered into Guesstimate to estimate the number of deaths caused by a countervalue nuclear exchange rather than using a simplified formula to estimate the parameters for triangular distributions that are then entered into Guesstimate (details here and here). After making these revisions, my estimate of the number of people that would be killed directly by nuclear detonations during a US-Russia nuclear exchange is about 51 million (90% confidence interval: 30 million — 75 million deaths) — ~43% more than my original estimate of 35 million (90% confidence interval: 23 million — 50 million deaths). The impacts that each individual change had on my results can be seen here. I’ve also added a bit more discussion on the probability that a countervalue nuclear exchange would escalate, and sensitivity analysis so that people who disagree with my views on this can see how the results change under more pessimistic assumptions. My sensitivity analysis shows that, if you’re more pessimistic than me about the probability of countervalue targeting and escalation, around 88 million people would be killed in expectation during a US-Russia nuclear exchange (details here and here). Thanks again to those who offered feedback, and also to Jaime Sevilla, Ozzie Gooen, Max Daniel, and Marinella Capriati for feedback and technical support implementing the revisions. Project Overview This is the third post in Rethink Priorities’ series on nuclear risks. In the first post, I look into which plausible nuclear exchange scenarios should worry us most, ranking them based on their potential to cause harm. In the second post, I explore the make-up and survivability of the US and R...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Use resilience, instead of imprecision, to communicate uncertainty, published by Gregory_Lewis on the AI Alignment Forum. Write a Review BLUF: Suppose you want to estimate some important X (e.g. risk of great power conflict this century, total compute in 2050). If your best guess for X is 0.37, but you're very uncertain, you still shouldn't replace it with an imprecise approximation (e.g. "roughly 0.4", "fairly unlikely"), as this removes information. It is better to offer your precise estimate, alongside some estimate of its resilience, either subjectively ("0.37, but if I thought about it for an hour I'd expect to go up or down by a factor of 2"), or objectively ("0.37, but I think the standard error for my guess to be ~0.1"). 'False precision' Imprecision often has a laudable motivation - to avoid misleading your audience into relying on your figures more than they should. If 1 in 7 of my patients recover with a new treatment, I shouldn't just report this proportion, without elaboration, to 5 significant figures (14.285%). I think a similar rationale is often applied to subjective estimates (forecasting most salient in my mind). If I say something like "I think there's a 12% chance of the UN declaring a famine in South Sudan this year", this could imply my guess is accurate to the nearest percent. If I made this guess off the top of my head, I do not want to suggest such a strong warranty - and others might accuse me of immodest overconfidence ("Sure, Nostradamus - 12% exactly"). Rounding off to a number ("10%"), or just a verbal statement ("pretty unlikely") seems both more reasonable and defensible, as this makes it clearer I'm guessing. In praise of uncertain precision One downside of this is natural language has a limited repertoire to communicate degrees of uncertainty. Sometimes 'round numbers' are not meant as approximations: I might mean "10%" to be exactly 10% rather than roughly 10%. Verbal riders (e.g. roughly X, around X, X or so, etc.) are ambiguous: does roughly 1000 mean one is uncertain about the last three digits, or the first, or how many digits in total? Qualitative statements are similar: people vary widely in their interpretation of words like 'unlikely', 'almost certain', and so on. The greatest downside, though, is precision: you lose half the information if you round percents to per-tenths. If, as is often the case in EA-land, one is constructing some estimate 'multiplying through' various subjective judgements, there could also be significant 'error carried forward' (cf. premature rounding). If I'm assessing the value of famine prevention efforts in South Sudan, rounding status quo risk to 10% versus 12% infects downstream work with a 1/6th directional error. There are two natural replies one can make. Both are mistaken. High precision is exactly worthless First, one can deny the more precise estimate is any more accurate than the less precise one. Although maybe superforecasters could expect 'rounding to the nearest 10%' would harm their accuracy, others thinking the same are just kidding themselves, so nothing is lost. One may also have some of Tetlock's remarks in mind about 'rounding off' mediocre forecasters doesn't harm their scores, as opposed to the best. I don't think this is right. Combining the two relevant papers (1, 2), you see that everyone, even mediocre forecasters, have significantly worse Brier scores if you round them into seven bins. Non-superforecasters do not see a significant loss if rounded to the nearest 0.1. Superforecasters do see a significant loss at 0.1, but not if you rounded more tightly to 0.05. Type 2 error (i.e. rounding in fact leads to worse accuracy, but we do not detect it statistically), rather than the returns to precision falling to zero, seems a much better explanation. In principle: If a measure ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: CEA Mid-year update (2020), published by MaxDalton on the AI Alignment Forum. Write a Review This is a linkpost for/ We'd like to share an update on our recent progress. In a previous post, we set out five goals for 2020: Developing our strategy: We're on track, with more work needed on metrics and data. Narrowing our scope by considering spinning off EA Funds and Giving What We Can: We're slightly ahead of expectations; we hired leaders and set an initial strategic direction for each project. Expanding group and community health support: We're somewhat behind expectations. Improving online discussion: We're somewhat ahead of expectations. We learned a lot about how to run virtual events, and EA Forum engagement has grown significantly. Streamlining internal collaboration and processes: We're on track or ahead of expectations on finances, customer relationship management (CRM), and culture. We're behind on hiring and the Oxford office move. Overall, I think we're making good progress toward our goals for the year. Specific progress: We hired Jonas Vollmer to lead EA Funds, and Luke Freeman to lead Giving What We Can. Jonas and Luke are experienced EAs with executive experience and excellent skillsets for the roles. We plan to investigate spinning off both organisations from CEA in the next year or so, although we will continue to support them both operationally. We hired Catherine Low as a contractor to improve support for groups, and she's had 60+ calls with organisers who gave the calls an NPS of 70+, which is excellent. We've also updated 16 resources for local groups, including an improved introductory fellowship curriculum template, discussion group guides, and advice on how to host virtual events in light of COVID-19 restrictions. Further progress here is a major focus. We renewed several Community Building Grants and made three new grants to EA Brown, EA NYC, and EA MIT. Events collaborated with EAGx organisers from around the world to create EAGx Virtual. With over 1,400 attendees, it was the largest EA event ever held. Virtual events are unlikely to be as valuable as in-person events, but now that we've developed the capacity to hold virtual events, we will likely continue to do so (in addition to holding live events), since they are less expensive and more accessible. Our key Forum metric (views of good posts) has doubled so far this year, meaning that more good content is being posted to the Forum and more people are reading that content. We also introduced highly-demanded features like tags, and some core introductory content. We've focused our community health work on mentorship and networking for underrepresented EA groups, and developing long-term plans to further improve diversity, equity, and belonging in the community. I also feel that we've fixed a lot of internal issues over the last 18 months and that we continue to gradually improve. We have 13 months of runway. Staff performance, morale, and retention appear to be solid and improving. We've improved our accounting systems, grantmaking records, and HR compliance/onboarding, and invested our reserves to protect against inflation. Program updates Groups We’re in the early stages of improving our support for groups. This is a major focus at the moment. Groups support We are working to improve the introductory EA fellowship template with Community Building Grant recipients Huw Thomas, James Aung, and Alex Holness-Tofts. Introductory EA fellowships are eight-week reading and discussion groups run on university campuses. We estimate that approximately 400 students participated in an intro fellowship last year. We brought on Catherine Low, who had been an extraordinarily active volunteer supporter of EA groups, as a contractor to improve our support of groups. Catherine has had 60+ calls with group org...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: 10 Habits I recommend (2020), published by Michelle_Hutchinson on the AI Alignment Forum. For the new year, I’m thinking about what habits I want to try, develop and drop. I’ve hugely benefited from the suggestions and support of others in picking up and sticking with good habits in the past. So I wanted to share some habits I’ve found useful in case others do too. Here are some I’ve particularly appreciated this year. I’d love to hear others people recommend! 1. Photographing things that are hard to let go of We’ve accumulated a lot of stuff due to having a baby, and so I’ve been trying to declutter our house of other things. I used to be a bit of a hoarder, so I find it hard to let go of things - whether books I’ve read or cards I particularly appreciated receiving. For things like the latter, I’ve started taking photos of them, so that I can still look at them whenever I want, but they don’t take up physical space (H/t Tara Mac Aulay). I’ve also found it motivating to listen to the Slow Home Podcast while doing this tidying. (H/t Nicole Ross) 2. Coworking in pomodoros I prefer working with other people, which has made the pandemic challenging. I’ve found it decidedly easier to stay on track with difficult tasks by working with a video call open with other people. We tend to check in every half hour, which is motivation to do what you set out to and is cheerfully social. I have a few weekly coworking slots with a partner booked for each week, and that’s often when I get some particularly aversive task done. I’m also on a Whatsapp group with some friends, where we can post if we fancy coworking. Another option is using FocusMate, which is great for its flexibility - you just sign up for a slot whenever you want and will get matched with someone to co-work with for an hour. There’s an EA group on there, and you can see which other EAs have booked when and sign up to join them. 3. Going for a walk during daylight every day This seems so basic it probably shouldn’t count, but I’ve been grateful that Rob has hassled me enough about getting light and exercise every day that it feels non-negotiable rather than a luxury. I think that made maternity leave and lock down decidedly easier. 4. Caffeine tablets for waking up I hate mornings. But I find it much easier to wake and get up if I set my alarm for 40min before I need to get up, take a caffeine tablet and then go back to sleep. (H/t Roman Duda) (I still have an alarm for when I actually need to get up!) I also wear a sleep mask which I take off at that point. When it won’t disturb others, I use a light alarm clock. The combination of these things makes me way more cheerful to get out of bed. 5. Anki I’m really glad I have Anki for remembering things - whether people’s names, what acronyms stand for, or difficult concepts. I found this article useful for getting the most out of it. I have yet to find a time to go through my cards that makes me fully consistent with it though. 6. Recurring social calls During the pandemic I’ve particularly appreciated having recurring video calls set up with friends - weekly, fortnightly or monthly. Somehow when I need to schedule calls it’s easy not to get around to it for ages, and have insufficient social time plus miss out on knowing what people are up to. Some are purely social, some are part work. 7. Buying spares I used to be in the habit of avoiding buying a second of things, in order to save money. But that periodically resulted in things like me leaving my computer charger at home when going to work. Now I keep one charger at work and one at home. For something like a charger, it’s worth having a spare anyway in case you break it. If something is cheap and I’ll likely use two up, it’s even more of a no-brainer: so I have vitamins on my desk and at home, so I can take them whenev...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Some EA Forum Posts I'd like to write, published by Linch on the AI Alignment Forum. I decided to write a list of posts I’d like to write, on the hypothesis that perhaps I can crowdsource interest or pre-emptively get people’s takes on goodness to a) prioritize my writings better and b) to develop better intuitions for which systems/processes can preemptively determine what research/writings are valuable. Note that I’m currently quite unlikely to write >2 of these posts unless I get substantive feedback otherwise. Unless explicitly stated otherwise, names/links/quotes of other people are referenced for partial attribution. They should not be construed as endorsements by those people, and on base rates it should be reasonable to assume that in this post I misrepresented someone at least once. This post is written in my own capacity, and does not represent the position or output of my employer (RP) or past employers. After the Apocalypse: Why Personal Survival in GCR Scenarios Should Be Unusually High Priority For Altruists/Consequentialists I think if your ensemble of beliefs include substantial credence in both urgent and patient longtermism, this should lead to a fairly high credence in the importance of the survival and proliferation of certain key ideas One way to ensure the survival of those ideas is through the survival of individuals with those ideas This is especially relevant if you have high credence in the probability of large-scale non-existential GCRs, particularly ones with a population fatality rate of closer to 99.99% than 50%. An alternative way to frame this is to consider the analogy to the Hinge of History hypothesis. All else equal, individuals are more likely to live at the hinge of history if there’s 6.5 million other humans than 6.5 billion. Shelters MVP: A Concrete Proposal to Robustly Mitigate Global Catastrophes I haven’t yet seen shelter designs with all the desiderata that I’d like to see. I’ve seen preliminary discussions that analyzed shelter intervention viability/cost-effectiveness in the abstract, but not stuff that looked at a specific well-defined target to aim for (or decide it’s not worth doing). I think that while reducing GC risks is of utmost importance, for longtermist goals, a potentially important part of the web-of-protection/defense-in-depth story should involve substantial work on catastrophe mitigations. I claim for a number of GCRs (with the notable exception of AI or other agent-heavy risks), certain shelter designs should robustly reduce the overall harm. I suspect (without yet having done the numbers) that this may not end up being worthwhile to implement at the current margin, however it is still worthwhile to have a blueprint ready as a robust baseline for GCR mitigation, so we have a direct comparison class/bar for what marginal Open Phil/EA longtermist dollars necessarily must beat. (I’m currently more excited about this as a baseline for “last longtermist dollar,” akin to GiveDirectly for global poverty, than the clean energy funding that others in EA propose). Moral Circle Expansion: Is it Highly Overrated? Many EAs (myself somewhat included) believe in some form of moral circle expansion as something that a) descriptively happened/is happening, b) is worthwhile to have, and c) is plausibly worth EA effort to ensure happening. I think I (used to?) believe in some version of this, at the risk of simplifying too much: The story of moral progress is in large part a story of the expansion of who we choose to care about. From only individuals to family members, trible, nation, race, etc, and expanding outwards to people of other races, locations, sexualities, and mental architectures. Future moral progress may come from us caring about more entities worthy of moral consideration (“moral circle expansion”). However, ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: 2020 Annual Review from the Happier Lives Institute, published by ClareDonaldson, MichaelPlant on the AI Alignment Forum. This (cross-)post is an update from the Happier Lives Institute (HLI) and contains our 2020 Annual Review. In it, we describe and explain the research we conducted in 2020; comment on our research evaluation procedure, the outcomes of our work (that we are aware of), and some lessons learned; lay out our research priorities and plans for 2021, and our longer-term vision; describe ways you can support us on our mission. This review is about 5,000 words in length. We have provided an executive summary and note some readers may want to check the contents sidebar, then go straight to specific sections, rather than read the whole thing in order. Executive Summary HLI searches for the best ways to measure and increase global well-being; we believe that subjective well-being (SWB) scores (self-rated happiness and life satisfaction) are both a highly promising and under-utilised tool for this purpose. 2020 was HLI's first full year of research and operations as an organisation - it was an opportunity to focus on addressing the most important questions on our research agenda, and to develop our capacities as an organisation that conducts careful and action-relevant research. The ‘backbone’ of our work is assessing the value of different outcomes in terms of ‘Wellbeing-Adjusted Life-Years’ or ‘WELLBYs’, an approach recently pioneered in economics that we are applying and developing. In our post on ‘moral weights’ we explain the method and use it to compare, for the first time, the relative values of two actions that are particularly relevant for the effective altruism community: doubling household consumption for a year and averting the death of an under-5, both in low-income contexts. We worked on the theoretical underpinnings of the WELLBY framework by producing: a working paper on the nature of well-being; another on the comparability of subjective scales; and a report on the validity of SWB (to be published soon). We also applied the WELLBY methodology to evaluating interventions and programmes. We conducted a systematic review and meta-analysis on the impact of cash transfers on SWB, and started work on other interventions - cataract surgery, lay-delivered psychotherapy and positive education. Further, we reviewed two cause areas - pain and mental health (coming soon) - as a way to scan the horizon for potentially highly cost-effective interventions. We also continued to work on our mental health programme evaluation project, aiming to identify impactful donation opportunities in global mental health. We mainly saw 2020 as a year to establish and develop our research capacity, but we are pleased that various academics and organisations in the effective altruism community are already using our work. Founders Pledge, for example, used the results from our ‘moral weights’ post in their internal prioritisation of charities. Our main focus for 2021 is to continue applying the WELLBY framework to various ‘micro’-interventions. We will continue to investigate whether using SWB indicates new priorities for the effective altruism community. Further, we hope to further demonstrate that WELLBYs enable comparisons to be made between a wide range of interventions, and search for new, potentially highly cost-effective interventions. As we demonstrated in our moral weights post last year, this analysis is highly sensitive to various moral assumptions, such as the views taken about what well-being consists in, the badness of death, or population ethics. We plan to present the ‘results’ for various viewpoints, so readers can make their own moral judgements. We also plan to continue our foundational work on measuring well-being, for example, by investigating how to comp...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Some AI Governance Research Ideas, published by MarkusAnderljung, Alexis Carlier on the AI Alignment Forum. Compiled by Markus Anderljung and Alexis Carlier Junior researchers are often wondering what they should work on. To potentially help, we asked people at the Centre for the Governance of AI for research ideas related to longtermist AI governance. The compiled ideas are developed to varying degrees, including not just questions, but also some concrete research approaches, arguments, and thoughts on why the questions matter. They differ in scope: while some could be explored over a few months, others could be a productive use of a PhD or several years of research. We do not make strong claims about these questions, e.g. that they are the absolute top priority at current margins. Each idea only represents the views of the person who wrote it. The ideas aren’t necessarily original. Where we think someone is already working on or has done thinking about the topic before, we've tried to point to them in the text and reach out to them before publishing this post. If you are interested in pursuing any of these projects, please let us know by filling out this form. We may be able to help you find mentorship, advice, or collaborators. You can also fill out the form if you’re intending to work on the project independently, so that we can help avoid duplication of effort. If you have feedback on the ideas, feel free to email researchideas@governance.ai. You can find the ideas here. Our colleagues at the FHI AI Safety team put together a corresponding post with AI safety research project suggestions here. Other Sources Other sources of AI governance research projects include: AI Governance: A Research Agenda, Allan Dafoe Research questions that could have a big social impact, organised by discipline, 80,000 Hours The section on AI in Legal Priorities Research: A Research Agenda, Legal Priorities Project Some parts of A research agenda for the Global Priorities Institute, Global Priorities Institute AI Impact’s list of Promising Research Projects Phil Trammell and Anton Korinek's Economic Growth under Transformative AI Luke Muehlhauser's 2014 How to study superintelligence strategy You can also look for mentions of possible extensions in papers you find compelling A list of the ideas in the document: The Impact of US Nuclear Strategists in the early Cold War Transformative AI and the Challenge of Inequality Human-Machine Failing Will there be a California Effect for AI? Nuclear Safety in China History of existential risk concerns around nanotechnology Broader impact statements: Learning lessons from their introduction and evolution Structuring access to AI capabilities: lessons from synthetic biology Bubbles, Winters, and AI Lessons from Self-Governance Mechanisms in AI How does government intervention and corporate self-governance relate? Summary and analysis of “common memes” about AI, in different communities A Review of Strategic-Trade Theory Mind reading technology Compute Governance ideas Compute Funds Compute Providers as a Node of AI Governance China’s access to cutting edge chips Compute Provider Actor Analysis Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Anki deck for Some key numbers that (almost) every EA should know, published by Pablo, jablevine on the AI Alignment Forum. Here is the promised Anki deck for "Some key numbers that (almost) every EA should know". Due to time constraints, we were not able to include all of the numbers suggested in the original thread. These may be added in a future version. Please go to the deck's GitHub repository for details on how to be notified when new versions are released. Please report problems, or leave suggestions, below. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: EA Giving Tuesday Donation Matching Initiative 2018 Retrospective, published AviNorowitz on the AI Alignment Forum. Write a Review November 12, 2019 update: Facebook has announced that it will be matching $7 million donations on Giving Tuesday 2019. To stay up to date, please sign-up on our website. Avi Norowitz, William Kiely, Anisha Zaveri, and Arushi Gupta, were on the organizer team for this project, and many others also provided valuable contributions. See "Project contributors" at the end of this post for more information. Summary In 2018, Facebook and PayPal announced plans to match up to $7 million in donations on Giving Tuesday. This represented an unusual opportunity to get EA donations counterfactually matched. We made a coordinated effort to direct matching funds to EA-aligned organizations, with a focus on donating fast and starting preparation work early. Our efforts were successful: We had $469k (65%) of our $719k donations matched, representing a 10x increase from our coordinated efforts in 2017. We’re currently involved in follow-up work with organizations to help them ensure they receive the expected amounts, and that the amounts are allocated correctly. We also conducted a follow-up survey with donors, which provided some insight on payment problems and the experience of donors outside the US. The responses also suggest that $85k (12%) of donations may have been counterfactually caused by our initiative, though this estimate is highly uncertain. I discuss how we improved since 2017, including: focusing on donating fast, starting early, focusing on payment problems, improving outreach, improving coordination with organizations, and improving data collection and analytics. I also discuss areas we could improve on in 2019, including: improving communication with donors, preparing instructions earlier, helping organizations fundraise, investing more in technology, and incorporating donation survey results. The experienced further confirms to me that EAs can follow instructions and work well as a community. It also further confirms to me that effective coordination with key organizations can yield large benefits. I discuss some unexpected problems we discovered that could have led to substantially less matching funds, and how we avoided these problems. I discuss a few questions for next year, including: how much time we’ll have before the match runs out, what problems we might face, and how open we should be about our work. I discuss our project costs, which consisted of an estimated 330 hours contributed among our organizer team, and an unknown number of hours by other contributors. I conclude with a list of project contributors and some of their contributions. Facebook’s Giving Tuesday matching program In early October 2018, Facebook announced that Facebook and PayPal would match donations made on Facebook on Giving Tuesday (November 27, 2018) up to $7 million. Facebook later provided the following details on the match: In support of #GivingTuesday 2018, we're partnering with PayPal to match donations made on Facebook to nonprofits up to a total of $7 million. Start a fundraiser for Giving Tuesday or donate to a nonprofit. About the match - Facebook and PayPal will start matching donations at 8:00am ET (5:00am PT) on Tuesday, November 27, 2018. The matching offer will expire when $7 million in donations is reached or at 11:59pm PT on November 27. - Donations will be matched dollar for dollar on a first-come, first-served basis. - Matching is available for any eligible US-based 501(c)(3) nonprofit that can receive donations on Facebook. - Donations up to $250k per nonprofit and $20k per donor are eligible to be matched. In addition to the limits described in the announcement, we determined that the maximum amount permitted per donation in the US was $2...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: 35-150 billion fish are raised in captivity to be released into the wild every year, published by saulius on the AI Alignment Forum. Write a Review Summary Fish stocking[1] is the practice of raising fish in hatcheries and releasing them into rivers, lakes, or the ocean. 35-150 billion finfish are stocked every year. Fish are stocked to: increase the catch in commercial fisheries (probably tens of billions of stocked fish annually), increase the catch in recreational/sport fisheries (billions of stocked fish annually), restore a population of threatened or endangered species (the number of stocked fish seems to be lower) Fish can be stocked when they are anywhere between the egg stage and multiple years old. The mean time spent in hatcheries/farms seems to be somewhere between 8 days and 4 months. Fish stocked to enhance recreational fisheries tend to be released when they are older than those stocked to enhance commercial fisheries. Usually, fish are stocked to maximize economic outputs so we shouldn’t expect fish welfare to be given sufficient consideration. It’s unclear how much hatcheries are incentivized to breed healthy and unstressed fish that would have higher survivorship after the release. Bigger fish may also starve and suffer after their release due to their lack of survival skills. I was unable to find any animal advocacy organization that is working on reducing the suffering caused by fish stocking. I found very few articles that talk about fish stocking from an animal welfare perspective.[2] Possible interventions include lobbying to decrease the number of fish stocked for recreational fishers and requiring better conditions in hatcheries. I am very uncertain if such interventions would be cost-effective compared to ACE’s recommended charities. Fish stocking has various ecological effects (e.g., a decrease in the genetic diversity of wild populations) that would need to be well-understood before seriously considering trying to reduce the number of stocked fish. Context This article is a part of a series of articles by Rethink Priorities about animals farmed for various purposes. We chose to write about this topic because it seems fairly important and it’s possible that animal advocates haven’t addressed welfare problems related to fish stocking simply because they didn’t know about them. Charity Entrepreneurship (CE) has recently released a report that considered the advantages and disadvantages of founding a charity that tackles problems related to fish stocking and baitfish. The report used my preliminary research on fish stocking, but it was written before I wrote most of this article. CE’s report provisionally concluded that interventions in these areas are only “somewhat promising” compared to other interventions they considered. I disagree with some aspects[3] of their report, but I have no opinion on whether the conclusion is correct. In general, I think that more in-depth research would be needed to determine whether this is a problem that should eventually be tackled by animal activists. I am uncertain if such research should currently be a priority. The number of fish stocked annually worldwide I haven’t found any estimates of the number of fish stocked worldwide, but I found estimates for various countries and regions: China: A 2006 programme planned to release 20 billion juvenile fish annually and to increase it to 40 billion by 2020. China’s 2011-2015 Fisheries Plan includes releasing 150 billion juvenile fish (which is 30 billion per year)[4] and claims that 109 billion young fish were released since a previous five-year plan was made in 2006.[5] It should be noted that these statistics are from China’s government and some doubt whether China’s government is a reliable source. For example, China has probably over-reported the catch from w...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: EAF/FRI are now the Center on Long-Term Risk (CLR), published by Jonas Vollmer on the AI Alignment Forum. Write a Review We have renamed the Foundational Research Institute (FRI) to the Center on Long-Term Risk (CLR) and will stop using the Effective Altruism Foundation (EAF) brand. The CLR will operate under the domain longtermrisk.org with the following logo: Motivation. We are renaming for the following reasons: Change of strategy. We now focus on building a research community working on reducing risks of astronomical suffering (s-risks). Our change of strategy entailed several changes to our organization. In addition to rebranding, we made the following changes over the past year: We moved to London (Primrose Hill) to better attract and retain staff and collaborate with other researchers in London and Oxford. We hired a new Research Director: Jesse Clifton. We published a new research agenda and are hiring talented researchers interested in our topics. For more background, see Effective Altruism Foundation: Plans for 2020. Renaming FRI. We perceive the FRI brand as confusing and grandiose given the scope and nature of our activities. We also received feedback from others to this effect in the past. The term “institute” is protected in the UK and does not appear adequate given the small size of our research group. It also suggests we mainly focus on academic publications, whereas we also make grants through our fund, host workshops, and advise people on their careers. Additionally, we work in areas where academic publications are less common, such as grantmaking research and macrostrategy. Handing off community building. We originally chose the EAF brand (German: “Stiftung für Effektiven Altruismus”) to coordinate the effective altruism (EA) community in the German-speaking area, but we handed off our community-building activities in 2018. The EAF name does not describe our activities well anymore and can be easily confused with the Centre for Effective Altruism, especially after our move to the UK. However, to reduce the effort from rebranding, we will continue to use EAF as the name of our legal entities. Process for renaming. We started out defining desiderata for the new name: it should be descriptive, flexible with respect to our future activities, intuitively understandable, respectable (including in academia), short, easy to pronounce and understand, unique, appealing, and memorable. We brainstormed an initial list of over 600 ideas with community members and shortened it iteratively. We also thought carefully about abbreviations or possible short forms. The winning name idea was generated during a brainstorming session with our core team. We decided to highlight our focus on reducing suffering in the tagline and mission statement rather than in the name itself. Based on feedback and our own experience, we believe academics and other non-EA audiences tend to associate the word “suffering” with direct charity or activism in near-term cause areas. A more neutral name works better for these audiences. We think the emphasis on “risk” still intuitively conveys our focus on preventing negative outcomes to some degree. Overall, we think the new name is more descriptive of our work, more modest, easier to understand, while still being compatible with potential future changes to our focus and strategy. We would like to thank the many people in our networks who helped us with their ideas and feedback. We are excited about the new name and design, and hope you are, too! Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Prioritizing COVID-19 interventions & individual donations, published by IanDavidMoss, catherio on the AI Alignment Forum. Write a Review UPDATE 7/23: Our group has concluded research activities for the time being. Previous updates have been moved to the bottom of the post. All information and recommendations below are current as of late June 2020. If you have questions or are considering a donation, feel free to reach out to one of the authors and we will help you if we can. Authors: Catherine Olsson and Ian David Moss, with contributions from the collective members of the "Funding Rational Actors Promptly" Pandemic Endowment (FRAPPE). At the beginning of April, a group of about 20 friends pulled together a messenger chat to discuss how to most effectively spend personal donation funds towards mitigating global suffering caused by COVID-19. What started as an informal effort has since resulted in the distribution of at least $410,000 to charities on this list and indirectly influenced $16 million in additional capital, mostly via the decisions of a single large foundation. A defining motivation of our group was to find time-sensitive and neglected bottlenecks to effective COVID response that could be eased with rapid funding or other supportive actions. Fast action can be an important source of philanthropic leverage in responses to the current pandemic, a factor that we did not see explored in depth in available analyses of COVID-related giving opportunities. Accordingly, we have summarized our research here in hopes that others can use it to inform their own giving. This article is organized in two parts. The first shares our working framework for prioritizing interventions, which helped us get oriented in a fast-changing and otherwise confusing landscape. In the second part, we enumerate specific giving opportunities (jump to section) we have found that currently rate highly on this framework as of right now (late June 2020). We've written this post primarily for the benefit of donors who have already decided to focus on COVID-19 for their own reasons. We haven't made it a priority to weigh the relative value of COVID-related donations as compared to other issues or causes, although we address this briefly at the end. Some disclaimers: this research is being done and our donations are being made in a purely personal capacity, and none of us is acting as an employee, representative, or spokesperson of our employer or any other organization. Furthermore, because we don't have complete information on many opportunities and the situation is changing so rapidly, none of what follows should be treated as the final word on COVID-related giving opportunities. With that said, we have tried hard to come to the best decisions we could in a short period of time using the resources we had, and are updating this post periodically as our perspective continues to evolve. I. Executive Summary & Recommendations When evaluating COVID-19 interventions for importance/scale, our intuition is to look for the following five "scale factors": ⏰Acting quickly, because widespread avoidable suffering is already taking place, because mitigation is more cost-effective when active case numbers are smaller, and because many potentially impactful interventions require lead time to set up. 🌍Concentrating benefits on the global poor, due to both disproportionate vulnerability and huge numbers. 😷Cheap mitigation strategies to limit or slow the spread of the disease, even in populations where full containment is not possible. We are particularly interested in interventions that are cost-effective relative to the burden they impose on society. 🔬Scientific research & development in support of any of the above facets of the problem, because a dollar spent on research can unlock orders of magnitude more ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: 2020 Top Charity Ideas - Charity Entrepreneurship, published by KarolinaSarek on the AI Alignment Forum. Write a Review This article was also published at Charity Entrepreneurship's blog. We’re proud to announce our 2020 Top Charity Ideas! Each year Charity Entrepreneurship identifies highly effective interventions in chosen cause areas. Our Incubation Program gives participants the skills they need to start high-impact nonprofits based on our top intervention recommendations. Our 2020 research period focused on four cause areas: mental health, animal advocacy, family planning, and health & development policy. We began with several hundred ideas in each cause area. Progressive stages of our extensive research process whittled down to eight recommended ideas. Eighty-hour reports linked below illustrate how we came to recommend this year’s top interventions. We also provide Incubation Program participants with implementation reports, which provide specific recommendations to map a path forward for a new charity. Our 2020 top recommendations are as follows (in no particular order): MENTAL HEALTH: 1. Guided self-help – Distributing workbooks to enable individuals to work independently on their mental health, supported by short weekly calls from lay health workers. HEALTH & DEVELOPMENT POLICY: 2. Lead paint regulation – Advocating for tighter regulation of lead paint to reduce the burden of lead exposure on human health and economic prosperity. 3. Alcohol regulation – Advocating for increased alcohol taxation to mitigate the harmful effects of consumption. ANIMAL ADVOCACY: 4. Shrimp welfare – Improving the welfare of farmed shrimp, e.g. through collaborating with Vietnamese farmers to better oxygenate the water, thus reducing chronic suffering for shrimp. 5. Feed fortification – Fortifying feed with micronutrients to combat deficiencies and improve the health of laying hens. 6. Ask research – Helping organizations and policy-makers decide what best to ask of the animal agriculture industry. (We explored this intervention during our 2019 research period and passed it on to 2020, as despite its promise it was not started.) FAMILY PLANNING: 7. Mass media campaigns – Broadcasting information about family planning to reduce misconceptions and empower women to make decisions about their fertility. 8. Postpartum family planning – Providing family planning guidance to women at pivotal moments for their health and fertility, such as after giving birth.The above reports are time-capped at eighty hours and follow the chronology of our research process. The reports begin with preliminary research and identifying crucial considerations. Next, we consult with experts. We then create a weighted factor model and a cost-effectiveness analysis. These two methodologies allow us to numerically quantify an intervention; by including both, we balance out their different strengths and weaknesses. Our final section brings together information gained throughout the research process. We have chosen to organize our reports in this way to increase transparency. Readers are able to follow the research as it unfolds and develops, and can see how an idea performs from multiple perspectives. For specific questions on the research process, reach out to Karolina Sarek at karolina@charityscience.com. MENTAL HEALTH Lead researcher: George Bridgwater george@charityscience.com Our four cause areas achieve impact in different ways, so we tailor our metrics accordingly. In this cause area, our cost-effectiveness analyses quantify impact using two metrics: the satisfaction with life scale (SWLS), and quality-adjusted life years (QALYs). We measure the expected number of incremental increases on the SWLS, and of QALYs per dollar spent. We use two metrics because of how difficult it is to capture subjective well-b...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: microCOVID.org: A tool to estimate COVID risk from common activities, published by catherio on the AI Alignment Forum. Write a Review This is a linkpost for/ This is a linkpost for a model and web tool (that I and several friends created) to quantitatively estimate the COVID risk to you from your ordinary daily activities: This website contains three outputs of our work: 1. a web calculator that you can use to calculate your COVID risk (in units of microCOVIDs, a 1-in-a-million chance of getting COVID). 2. a white paper that explains our estimation method. EAs might be particularly interested in the footnotes throughout, and the detailed research sources section. 3. a spreadsheet to compute your COVID risk in more detail and to track your risk over time. EAs might find this more customizable and powerful than the web calculator. We hope this will directly help the EA community by resolving some of the issues highlighted in an earlier post: "[Many EAs] are doing [COVID modeling] work themselves: it's time-costly, and it is mentally draining and stressful. It's also wasteful if a lot of this analysis work ends up getting replicated privately across many people. At the same time, [if people don't do these analyses,] households don't have ways of analyzing risks and deciding on acceptable behaviors" If you have different beliefs than us and would like to use a version of the model that reflects your beliefs rather than ours, you can make modifications to your copy of the spreadsheet, or fork the repository and make a personal copy of the web calculator. We also hope you will submit suggestions, either by emailing us or by making issues or pull requests directly on github. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: New book: Moral Uncertainty by MacAskill, Ord & Bykvist, published by frankieaw on the AI Alignment Forum. Write a Review Very often we are uncertain about what we ought, morally, to do. We do not know how to weigh the interests of animals against humans, how strong our duties are to improve the lives of distant strangers, or how to think about the ethics of bringing new people into existence. But we still need to act. So how should we make decisions in the face of such uncertainty? Moral Uncertainty, a new book by William MacAskill, Krister Bykvist & Toby Ord, tackles this question. It is an academic book, and might be especially interesting for philosophers, psychologists & economists. It’s open-access: you can download the book as a free PDF here, or order a hard copy via Amazon UK. The book is due to come out in the USA in November. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Scope-sensitive ethics: capturing the core intuition motivating utilitarianism, published by richard_ngo on the AI Alignment Forum. Classical utilitarianism has many advantages as an ethical theory. But there are also many problems with it, some of which I discuss here. A few of the most important: The idea of reducing all human values to a single metric is counterintuitive. Most people care about a range of things, including both their conscious experiences and outcomes in the world. I haven’t yet seen a utilitarian conception of welfare which describes what I’d like my own life to be like. Concepts derived from our limited human experiences will lead to strange results when they’re taken to extremes (as utilitarianism does). Even for things which seem robustly good, trying to maximise them will likely give rise to divergence at the tails between our intuitions and our theories, as in the repugnant conclusion. Utilitarianism doesn’t pay any attention to personal identity (except by taking a person-affecting view, which leads to worse problems). At an extreme, it endorses the world destruction argument: that, if given the opportunity to kill everyone who currently exists and replace them with beings with greater welfare, we should do so. Utilitarianism is post-hoc on small scales; that is, although you can technically argue that standard moral norms are justified on a utilitarian basis, it’s very hard to explain why these moral norms are better than others. In particular, it seems hard to make utilitarianism consistent with caring much more about people close to us than strangers. I (and probably many others) think that these objections are compelling, but none of them defeat the core intuition which makes utilitarianism appealing: that some things are good, and some things are bad, and we should continue to want more good things and fewer bad things even beyond the parochial scales of our own everyday lives. Instead, the problems seem like side effects of trying to pin down a version of utilitarianism which provides a precise, complete guide for how to act. Yet I’m not convinced that this is useful, or even possible. So I’d prefer that people defend the core intuition directly, at the cost of being a bit vaguer, rather than defending more specific utilitarian formalisations which have all sorts of unintended problems. Until now I’ve been pointing to this concept by saying things like “utilitarian-ish” or “90 percent utilitarian”. But it seems useful for coordination purposes to put a label on the property which I consider to be the most important part of utilitarianism; I’ll call it “scope-sensitivity”. My tentative definition is that scope-sensitive ethics consists of: Endorsing actions which, in expectation, bring about more intuitively valuable aspects of individual lives (e.g. happiness, preference-satisfaction, etc), or bring about fewer intuitively disvaluable aspects of individual lives (e.g. suffering, betrayal). A tendency to endorse actions much more strongly when those actions increase (or decrease, respectively) those things much more. I hope that describing myself as caring about scope-sensitivity conveys the most important part of my ethical worldview, without implying that I have a precise definition of welfare, or that I want to convert the universe into hedonium, or that I’m fine with replacing humans with happy aliens. Now, you could then ask me which specific scope-sensitive moral theory I subscribe to. But I think that this defeats the point: as soon as we start trying to be very precise and complete, we’ll likely run into many of the same problems as utilitarianism. Instead, I hope that this term can be used in a way which conveys a significant level of uncertainty or vagueness, while also being a strong enough position that if you accept scope-...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Be Specific About Your Career, published by Mark Xu on the AI Alignment Forum. This is a linkpost for Alice is trying to maximize the impact of her career. She is deciding between biosecurity research and building the effective altruism community (meta-EA). As far as she can tell, her fit is about the same for both paths. She attempts to decide between them by zooming out. What cause has a higher impact? Which one is more neglected? Which cause is more tractable? These are all useful questions to ask. However, they are very abstract. There is another set of questions that Alice is likely to find very useful: If I chose meta-EA as my career path, what, specifically, would I be doing? At which organization would I work? What would I do at that organization? Would I plan events? Which events? What would the goals of those events be? If I chose biosecurity, what, specifically, would I be doing? Would I get a Ph.D.? If so, where? Who would be my advisor? What would the topic of my thesis be? What lines of research would I be pursuing? It doesn't matter whether meta-EA is better than biosecurity research in general; what matters is whether biosecurity research is better than meta-EA for Alice. An analysis of Alice's individual impact screens off any analysis of average impact. (Of course, the impact of the specific things she would be doing is informed by an average impact analysis.) Being specific about your career is very difficult. This is a feature. If you can't tell a plausible story for why the work you would do as a biosecurity researcher is impactful, you don't know enough about being a biosecurity researcher. One example of such a story is: "I would work at X research group studying ways to use lasers to neutralize viral pathogens, developing technology that would allow future pandemics to be quickly stamped out without waiting for the development of vaccines." If you can't construct a story of similar detail for yourself, you probably do not know what biosecurity researchers do. I often see people think about their careers from the perspective of abstract cause prioritization. Besides such broad analysis, they should construct specific narratives linking potential career paths to impact. Jerry Cleaver: "What does you in is not failure to apply some high-level, intricate, complicated technique. It's overlooking the basics. Not keeping your eye on the ball." Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Why fun writing can save lives: the case for it being high impact to make EA writing entertaining, published by Kat Woods on the AI Alignment Forum. EA content is often dry, which leads to fewer people reading it, which leads to the content having less impact. Dry writing → ↓ People reading → ↓ Impact EA writing can’t have an impact if the right people don’t read it, and the right people are more likely to read it if it’s interesting. Therefore, if you want to maximize impact (which I imagine you do since you’re reading this), you shouldn’t make your writing dry. In the rest of this essay I'll explain why it's a problem, potential objections, and practical tips for how to make writing more engaging. Is this really a problem? Of course, there’s a spectrum of how entertaining EA writing is and it’s a wide distribution, with some very engaging writing being produced. Joe Carlsmith’s “Against neutrality about creating happy lives” and Nate Soares’ Replacing Guilt series come to mind. However, I think we can all agree that a large amount of the writing is a bit. . . well, mostly sticking to a dry, unobjectionable list of claims and arguments. The percentage of posts that have a single joke in them is probably less than half, perhaps as low as 10%. The numbers are similarly bad for most other ways that an article can be spiced up, such as with clever turns of phrase, images, or anything that might cause you to feel any sort of emotion. The focus is almost entirely on accuracy with little consideration to other possible metrics, such as being engaging or beautiful. The writing is, in perhaps unsurprising news, rather utilitarian. Why this matters: dry writing leads to less utility for the world on average This is a problem because if nobody reads an article, it has no impact. Research and writing have an impact through other people, so other people need to have a way of being affected by the research, which is typically by reading or listening to the content. Here’s a quick excerpt from a previous post I wrote about why increasing (impact-adjusted) readership is important: Here are some purely hypothetical numbers just to illustrate this way of thinking: Imagine that you, a researcher, have spent 100 hours producing outstanding research that is relevant to 1,000 out of a total of 10,000 EAs. Each relevant EA who reads your research will generate $1,000 of positive impact. So, if all 1,000 relevant EAs read your research, you will generate $1 million of impact. You post it to the EA Forum, where posts receive 500 views on average. Let’s say, because your report is long, only 20% read the whole thing - that’s 100 readers. So you’ve created 1001,000 = $100,000 of impact. Since you spent 100 hours and created $100,000 of impact, that’s $1,000 per hour - pretty good! But if you were to spend, say 1 hour, promoting your report - for example, by posting links on EA-related Facebook groups - to generate another 100 readers, that would produce another $100,000 of impact. That’s $100,000 per marginal hour or ~$2,000 per hour taking into account the fixed cost of doing the original research. Likewise, if you spend a bit of time while writing your essay to make it interesting and fun, you could potentially 2-100x the readership and thus impact of your research. In this example, that could lead to another tens of thousands to millions of dollars worth of value per marginal hour. This is an extremely good investment of your effort. Perhaps the most compelling example of this effect is Eliezer Yudkowsky. I remember one day deciding that I would read decision theory books instead of relying on LessWrong. To my surprise, I realized that pretty much everything in the sequences is in the intro to decision theory textbooks. However, they present it in the most boring, theoretical, non-actionab...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is:Penn EA Residency Takeaways, published by Thomas Kwa on the AI Alignment Forum. Thanks to Zack Dugue, Oliver Habryka, Adam Krivka, and the Penn EA team for useful comments. In September 2021, sydv and I (Thomas Kwa) helped revive the University of Pennsylvania EA group through a residency. We think this went very well, and the ~300 hours invested during the 3 weeks we were there probably sped up the group by 4 months, and possibly made the group significantly better overall [3]. As of November 2021, Penn EA is currently a thriving group with six organizers, ~30 Intro Program participants and ~20 weekly dinner attendees, and potential to grow further into its huge 10,000 undergrad population, whereas I'd guess the counterfactual looks something like slowly building up to this size over the course of ~8 months with significant risk of the group dying again. What is a residency? In (our model of) a residency, one or two EA community builders travel to a large university at the start of the school year, and spend at least 1 FTE building a new or existing EA student group. At the end, the group is handed off to students, and there might be a retreat for new organizers. The primary goal is to build organizer capacity to rapidly make the group large and self-sustaining (at least 2 students with 10h/week each); a secondary goal is general community-building. Penn is strong evidence that this model can work well. It's only one data point, but we think a lot of the success is generalizable. Note there were other residencies this fall that didn't go as well. Misc comments Sydney (a Stanford student) and I (a Caltech student) were able to invest this much time despite being full-time students with our own groups to run because Penn starts 3 weeks earlier than Caltech or Stanford. [1] Our time was mostly spent building the website, tabling (sitting outside in a high-traffic area and advertising the club), having one-on-ones with prospective organizers and others who signed up through the website, organizing and speaking at events like intro sessions and dinners, other advertising (like flyers) and organizing a retreat (see below). Of these actions, we spent the most time tabling. But one-on-ones and the retreat were the most efficient use of time, as they build organizer capacity. The other actions are still roughly as good as standard university organizer time, given the importance of the first few weeks of uni. Tabling: At Penn, it's really hard to send emails to the whole school. Emails are necessary to get attendance at events. We used the labor-intensive but very effective strategy of tabling to collect ~900 emails, and averaged ~20 emails and ~1 Intro Program application per hour (more on club fair days). Just as importantly, we met a couple more potential organizers. We highly recommend that group organizers read our Guide to Tabling, because following these practices more than doubled our tabling effectiveness. One-on-ones: Sydney did most of these; the goal was to identify potential organizers / active members and what they might contribute to the club, and also just get to know people. I think there were about 20 one-hour 1-1s. Retreat: We ran a weekend retreat for Mid-Atlantic region EA group organizers after the residency, with a total of ~30 people including ~8 from Penn. Retreats are out of scope of this post, but we think they're great and pair well with residencies; all the newly excited people you've had 1-1s with can talk to each other and learn more about EA and EA community building. We did expensive messaging experiments which were inconclusive (we technically started 3 different clubs, and tabled once as Penn Rationality and a couple times as Penn Impactful Careers). In the end we stuck with neutral EA branding, roughly "we want to help students solve the wor...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is:Terrorism, Tylenol, and dangerous information, published by Davis_Kingsley on the AI Alignment Forum. Write a Review Author's note: Sincere thanks to those who assisted me with this post; their assistance has made it safer and more compelling. An earlier but very similar version of this post was posted on LessWrong some time ago. Recently, there has been an alarming development in the field of terrorist attacks; more and more terrorists seem to be committing attacks via crashing vehicles, often large trucks, into crowds of people. This method has several advantages for an attacker - it is very easy to obtain a vehicle, it is very difficult for police to protect against this sort of attack, and it does not particularly require special training on the part of the attacker. While these attacks are an unwelcome development, I would like to propose an even more worrisome question - why didn't this happen sooner? I see no reason to believe that there has been any particular technological development that has caused this method to become prevalent recently; trucks have been in mass production for over a hundred years. Similarly, terrorism itself is not particularly new - just look to the anarchist attacks of the late 19th and early 20th century. Why, then, weren't truck attacks being made earlier? The answer, I think, is both simple and frightening. The types of people who make attacks hadn't thought of it yet. The main obstacle to these attacks was psychological and intellectual, not physical, and once attackers realized these methods were effective the number of attacks of this sort began increasing. If the Galleanists had realized this attack method was available, they might well have done it back in '21 -- but they didn't, and indeed nobody motivated to carry out these attacks seemed to until much later. Another instance - though one with less lasting harm - pertains to Tylenol. In 1982, a criminal with unknown motives tampered with several Tylenol bottles, poisoning the capsules with cyanide and then replacing them on store shelves. Seven people died in the original attack, which caused a mass panic to the point where police cars were sent to drive down the streets broadcasting warnings against Tylenol from their loudspeakers; more people still were killed in later "copycat" crimes. In this case, there was a better solution than with the truck rammings - in the aftermath of these events, greatly increased packaging security was put into place for over-the-counter medications. Capsules (which are comparatively easy to adulterate) fell out of favor somewhat in favor of tablets; further, pharmaceutical companies began putting tamper-resistant seals on their products and the government made product tampering a federal offense. Such attacks are now much harder to commit. However, the core question remains - why was it that it took until 1982 for there to be a public attack like this, and then there were many more (TIME claims hundreds!) in short succession? The types of people who make attacks hadn't thought of it yet. Once the first attack and the panic around it exposed this vulnerability, opportunistic attackers carried out their own plans, and swift action suddenly became necessary - swift action to close a security hole that had been open for years and years! One practical implication of this phenomenon is quite worrisome - one must be very careful to avoid accidentally spreading dangerous information. If the main constraint on an attack vector can really just be that the types of people who make attacks haven't thought of it yet, it's very important to avoid spreading knowledge of potential ways in which we're vulnerable to these attacks - you might wind up giving the wrong person dangerous ideas! Many otherwise analytical or strategic thinkers that I have encountered ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: The career and the community, published by richard_ngo on the AI Alignment Forum. Write a Review tl;dr: for the first few years of their careers, and potentially longer, most effective altruists should focus on building career capital (which isn’t just 'skills’!) rather than doing good or working at EA organisations. However, there are social dynamics which push new grads towards working at EA orgs, which we should identify and counteract. Note that there are a lot of unsubstantiated claims in this post, and so I’d be grateful for pushback on anything I’m incorrect about (throughout the post I’ve highlighted assumptions which do a lot of work but which I haven’t thoroughly justified). This post and this post point at similar ideas less lengthily. Contents: 1. Advantages of working at EA organisations. 2. Advantages of external career pathways. 3. Social dynamics and implicit recommendations. 4. Building a community around moonshots. 5. Long-term and short-term constraints. What are the most important bottlenecks limiting the amount of good the effective altruism movement can do? The original message (or at least, the one which was received by the many people who went into earning to give) was that we were primarily funding-constrained. The next message was that direct work was the most valuable career pathway, and was talent-constrained. This turned out to be a very misleading phrase, and led a bunch of talented people, particularly recent graduates who hadn’t yet built up on-the-job skills, to be unable to find EA jobs and become disillusioned with the movement. And so 80,000 Hours recently published a blog post which tries to correct that misconception by arguing that instead of being bottlenecked on general talent, EA lacks people with specific skills which can help with our favoured cause areas, for example the skill of doing great AI safety research. I have both a specific and a general disagreement with this line of thinking; I’ll discuss the specific one first. I worry that ‘skills-constrained’ is open to misinterpretation in a similar way as ‘talent-constrained’ was. It’s true that there are a lot of skills which are very important for EA cause areas. However, often people are able to be influential not primarily because of their skills, but because of their career capital more broadly. (Let me flag this more explicitly as assumption 1.) For example, I’m excited about CSET largely because I think that Jason Matheny and his team have excellent networks and credentials, specific familiarity with how US politics works, and generally high competence. These things seem just as important to me as their ‘skills’. Similarly, I think a large part of the value of getting into YCombinator or Harvard or the Thiel Fellowship comes from signalling + access to networks + access to money. But the more we rely on explicit arguments about what it takes to do the most good, the more likely we are to underrate these comparatively nebulous advantages. And while 80,000 Hours does talk about general career capital being valuable, we’ve already seen that the specific headline phrases they use can have a disproportionate impact. It seems plausible to me that EAs who hear about the ‘skill gap’ will prioritise developing skills over other forms of career capital, and thereby harm their long-term ability to do good compared with their default trajectory (especially since people are generally are able to make the biggest difference later in their careers). I don’t want to be too strong on this point. Credentials are often overrated, and many people fall into the trap of continually creating career capital without ever using it to pursue their true goals. In addition, becoming as skilled as possible is often the best way to both amass career capital and do good in the long term. However, ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Cluster Headache Frequency Follows a Long-Tail Distribution, published by algekalipso on the AI Alignment Forum. Write a Review [Warning: Disturbing content ahead. Why talk about it? This is an ethically very serious topic and it deserves more attention. But please beware that thinking about this might be bad for one’s mental health.] One of the key insights that shows why Effective Altruism is so important is that the positive effect on the world that results from donating to various charities follows a long-tail distribution: Cost-effectiveness of health interventions as found in the Disease Controls Priorities Project 2. See “The moral imperative towards cost-effectiveness in global health” by Toby Ord for more explanation. [Taken from: The world’s biggest problems and why they’re not what first comes to mind] It is for this reason why focusing on the best interventions really pays off. Where else can we expect long-tails to appear? In Get-Out-Of-Hell-Free Necklace we discussed how introducing a new metric into the Effective Altruist ecosystem could shed light on neglected cost-effective interventions. We presented the Hell-Index: A country’s Hell-Index could be defined as the yearly total of people-seconds in pain and suffering that are at or above 20 in the McGill Pain Index (or equivalent). This index captures the intuition that intense suffering can be in some ways qualitatively different and more serious than lesser suffering in a way that isn’t really captured by a linear pain scale. In a future article we will discuss how the quality of suffering as a function of different medical and psychological conditions very likely follows a long-tail distribution. That is, some conditions such as Cluster Headaches (which affect about 1 in 1000 people worldwide) produce pain that is orders of magnitude worse than the pain experienced in other kinds of medical conditions, such as migraines (which are themselves already described as orders of magnitude worse than tension headaches). In other words, a 0-10 pain-scale is better thought of as a logarithmic compression of the true levels of pain rather than a linear scale. So concentrating on the worst conditions could really pay off for reducing suffering in bulk amounts. Now: the long-tailed nature of suffering may extend beyond the quality of suffering, and show up also in its quantity. That is, the frequency with which people experience episodes of intense suffering, even among those who experience the same kind of suffering, is unlikely to be normally distributed. Intuitively, one may think that how much suffering people endure on a given year follows a normal distribution. This intuition says that if the median number of hell-seconds people endure in a year is, say, 1,000, then people who are at the 90% percentile of hell-seconds experienced per year will be experiencing something like 1,500 or at most 2,000. If suffering follows a long-tail distribution, in reality the 90% percentile might be experiencing something more akin to 10,000 hell-seconds per year, the 99% percentile something akin to 100,000, and the 99.9% something akin to 1,000,000. If true, such a heavy skew of the distribution would suggest that we should concentrate our energies on addressing the problems of the people who are unlucky to be on the upper ranges, rather than be overly concerned with “the typical person”. Unfortunately, I come to share the bad news that suffering probably follows a very long-tail distribution: It is generally acknowledged that Cluster Headaches are some of the most painful experiences that people endure. Having a single Cluster Headache, lasting anywhere between 15 minutes to 4 hours, is already an ethically unacceptable situation that should never happen to begin with. It is disheartening to know that 1 in 1,000 people e...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Technical AGI safety research outside AI, published by richard_ngo on the AI Alignment Forum. Write a Review I think there are many questions whose answers would be useful for technical AGI safety research, but which will probably require expertise outside AI to answer. In this post I list 30 of them, divided into four categories. Feel free to get in touch if you’d like to discuss these questions and why I think they’re important in more detail. I personally think that making progress on the ones in the first category is particularly vital, and plausibly tractable for researchers from a wide range of academic backgrounds. Studying and understanding safety problems How strong are the economic or technological pressures towards building very general AI systems, as opposed to narrow ones? How plausible is the CAIS model of advanced AI capabilities arising from the combination of many narrow services? What are the most compelling arguments for and against discontinuous versus continuous takeoffs? In particular, how should we think about the analogy from human evolution, and the scalability of intelligence with compute? What are the tasks via which narrow AI is most likely to have a destabilising impact on society? What might cyber crime look like when many important jobs have been automated? How plausible are safety concerns about economic dominance by influence-seeking agents, as well as structural loss of control scenarios? Can these be reformulated in terms of standard economic ideas, such as principal-agent problems and the effects of automation? How can we make the concepts of agency and goal-directed behaviour more specific and useful in the context of AI (e.g. building on Dennett’s work on the intentional stance)? How do they relate to intelligence and the ability to generalise across widely different domains? What are the strongest arguments that have been made about why advanced AI might pose an existential threat, stated as clearly as possible? How do the different claims relate to each other, and which inferences or assumptions are weakest? Solving safety problems What techniques used in studying animal brains and behaviour will be most helpful for analysing AI systems and their behaviour, particularly with the goal of rendering them interpretable? What is the most important information about deployed AI that decision-makers will need to track, and how can we create interfaces which communicate this effectively, making it visible and salient? What are the most effective ways to gather huge numbers of human judgments about potential AI behaviour, and how can we ensure that such data is high-quality? How can we empirically test the debate and factored cognition hypotheses? How plausible are the assumptions about the decomposability of cognitive work via language which underlie debate and iterated distillation and amplification? How can we distinguish between AIs helping us better understand what we want and AIs changing what we want (both as individuals and as a civilisation)? How easy is the latter to do; and how easy is it for us to identify? Various questions in decision theory, logical uncertainty and game theory relevant to agent foundations. How can we create secure containment and supervision protocols to use on AI, which are also robust to external interference? What are the best communication channels for conveying goals to AI agents? In particular, which ones are most likely to incentivise optimisation of the goal specified through the channel, rather than modification of the communication channel itself? How closely linked is the human motivational system to our intellectual capabilities - to what extent does the orthogonality thesis apply to human-like brains? What can we learn from the range of variation in human motivational systems (e.g. induced b...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Virtual EA Global: News and updates from CEA, published by Amy Labenz, BarryGrimes on the AI Alignment Forum. Write a Review As you may have heard already, we’ll be holding our first Virtual EA Global instead of an in-person event this coming weekend. This will include: A live broadcast featuring content from some of our planned speakers, which everyone is welcome to attend. A series of “Ask Me Anything” posts on the Forum, in which anyone can ask questions. The EA Global Broadcast Everyone is welcome to watch the broadcast! We encourage you to invite your friends. During this time of social distancing, when many community events have been canceled, we hope this can serve as a gathering point for EAs around the world. It will take place from 10:30 AM to 2:30 PM Pacific Time on March 21st and 22nd. We chose these times with US and European time zones in mind, as most of our attendees live in those areas. (Note that the US recently switched over to daylight savings time, so time zone differences outside the US may be different than for most of the year. Please check your local time to confirm.) The agenda for the broadcast is here. A live host will provide updates and commentary during a varied programme of pre-recorded videos. On Saturday morning, you can visit the agenda page to see a link to the broadcast. “Ask Me Anything” Sessions Several speakers have agreed to run AMAs on the Forum in advance of the event. (For examples of past AMAs, see Will MacAskill or Rob Mather.) In past AMAs, posters have replied to questions on the Forum. This time, they’ll be recording answers on video; we’ll stream those videos during the broadcast. They’ll also be posted on YouTube and linked from the AMA posts, so you don’t have to catch them live to view answers. Later, we’ll link to the videos from the EA Forum. Current AMAs: Elie Hassenfeld, co-founder and CEO of GiveWell Leah Edgerton, Executive Director of Animal Charity Evaluators Toby Ord, author of "The Precipice" and co-founder of the EA movement You can subscribe to comments on any of the AMA posts; this is the best way to learn when AMA videos are posted. And if you subscribe to comments on this post, you’ll get notifications whenever a new AMA post is published. One-on-one Meetings We still think that individual connections between attendees are one of the most valuable aspects of the conference, and we don’t want to sacrifice that just because we aren’t gathering in person. We are piloting the use of “virtual meeting rooms” for attendees to connect with each other via the Grip app. Attendees should have received a Grip invitation a while ago after having been accepted to EA Global; if you have not received an invitation, please contact us at hello@eaglobal.org. To get the most out of Grip, you’ll need to fill out your profile and schedule meetings ahead of time. We recommend doing this as soon as you can, so that you’ll be prepared well in advance of the weekend. We are very uncertain how well the “virtual meeting rooms” will work. If they are well-received, we may consider having more “virtual” events or otherwise coordinating virtual one-on-one’s in the future, possibly with a broader audience (i.e. not just those accepted to the conference). Another way you can set up one-on-ones is to use this Forum thread, where you can share your contact information and notes on who you'd like to meet. Enjoy the (virtual) conference! We hope to see you at the broadcast this weekend, and asking questions on AMA posts this week! Please comment on this post or contact us if you have any questions or suggestions relating to the weekend’s events. (We will do our best to respond to questions, but please keep in mind that we are trying to organize a new type of conference with only two weeks’ notice, and might not respond as rapidly as usu...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Some history topics it might be very valuable to investigate, published by MichaelA on the AI Alignment Forum. Write a Review In the recent article Some promising career ideas beyond 80,000 Hours' priority paths, Arden Koehler (on behalf of the 80,000 Hours team) highlights the pathway “Become a historian focusing on large societal trends, inflection points, progress, or collapse”. I share the view that historical research is plausibly highly impactful, and I’d be excited to see more people explore that area. I commented on that article to list some history topics I’d be excited to see people investigate, as well as to provide some general thoughts on the intersection of history research and effective altruism. Arden suggested I adapt that comment into a top-level post, which led me to write this. Note that: As zdgroff points out, you don’t actually have to be a historian to do this sort of historical research. (I’d add that you don’t even necessarily have to be in academia at all.) I’m sure there’s at least some relevant existing work on each of these topics. What I’m suggesting is that it seems likely there’s room for more work, work better targeted towards informing decisions in areas EAs care about, and/or summaries and syntheses of existing work (for EAs unfamiliar with that work). I have basically no background in academic history myself, am only ~6 months into my EA-aligned research career, and wrote this post fairly quickly. I lean towards longtermism, which influenced which history topics came to mind for me. Thus, this post should be seen merely as a starting point. I expect I’ve failed to include some topics it could be valuable to investigate. I’d therefore be really keen to see people comment on this post to mention additional topics, their thoughts or criticisms regarding anything I say here, or additional general thoughts on the intersection of history research and EA. 10 history topics it might be very valuable to investigate (Note: The article Some promising career ideas beyond 80,000 Hours' priority paths also mentions something similar to the 1st and 3rd of these topics.) 1. The history of various types of growth and progress (economic, intellectual, technological, moral, political, etc.) Investigations into this topic could give us evidence about: What developments are likely in the future How tractable influencing the speed or direction of various forms of growth and progress might be, and what the best interventions for doing that might be See also We Need a New Science of Progress. How severe and lasting the consequences of civilizational collapse and global (but non-existential) catastrophes might be, and thus how much we should prioritise work on those issues For example, let’s say humanity is currently experiencing various positive trends, but we discover these trends aren’t very common across different times and societies and appear to depend on many conditions being just right. We might then have additional reason to see that trend as “fragile” and worth protecting from various types of disruptions. See The long-term significance of reducing global catastrophic risks and Civilization Re-Emerging After a Catastrophic Collapse. On economic growth, see here and here. I'd include as part of this topic research into trends in various forms of violence over time. See e.g. The Better Angels of Our Nature and What are the implications of the offence-defence balance for trajectories of violence? 2. The history of societal collapse and recovery Investigations into this topic could provide evidence about things like how high existential and global catastrophic risks are, how likely humanity is to recover from a collapse, how civilization might be changed by the process of collapse and recovery, and what we can do to reduce chances of collapse and/or ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Introducing Family Empowerment Media, publishedKen_Scheffler, Anna_Christina on the AI Alignment Forum. Write a Review Working towards better health, education, and economic outcomes through more informed family planning and birth spacing TL;DR Greater adoption of contraceptives has a lot of positive benefits. Studies indicate that radio campaigns can be highly cost-effective in increasing adoption. Our new organization will implement radio campaigns where they can have the greatest impact, starting in Nigeria. If this sounds promising to you, there are several ways you can help us move from proof of concept to full rollout. In September, we founded Family Empowerment Media (FEM), a non-profit organization that will help people plan their families. We will provide clear, compelling, and accurate information on modern contraceptives through the radio. We believe a well-run family planning charity focused on social and behavior change (SBC) campaigns on the radio could achieve outcomes in the realm of the most effective global health charities. Increasing access to and understanding of family planning services has been shown to have substantial positive effects on health, as well as education, income, and several other dimensions. SBC campaigns on family planning have generally been cost-effective, and a recent randomized control trial indicates that high-intensity radio-based SBC campaigns have the potential to be especially cost-effective. This post describes (I) the challenge we aim to solve, (II) our approach, (III), our value add, and (IV) our progress and plans. We close with a quick note on (V) how you can help FEM navigate its first year. I. The challenge: Modern contraception’s vast benefits are not fully realized due to information gaps In countries with developing health systems, pregnancy can be a major health risk for women. According to the Guttmacher Institute, just under 300,000 women and girls in low and middle-income countries die of pregnancy-related complications each year. Pregnancy is the most common source of mortality for adolescent girls. Pregnancy is also a source of non-fatal but serious morbidity. Conditions arising from pregnancy and childbirth include obstetric fistula - which 50,000-100,000 women experience each year - postpartum anemia, and postnatal depression. Helping women avoid unintended pregnancies is a cost-effective means of reducing maternity-related health burdens. Almost a quarter of women in low and middle-income countries want to avoid pregnancy but are not using modern contraceptives. This “unmet need” for modern contraceptives results in 85 million unintended pregnancies per year. If all women with unmet need were provided access to and used modern contraceptives 70,000 maternal deaths per year would be averted. Guttmacher estimates, “every dollar spent on contraceptive services beyond the current level would reduce the cost of pregnancy-related and newborn care by three dollars,” while helping couples realize their family planning intentions. The Copenhagen Consensus estimates that a dollar spent on access to modern contraception leads to 120 dollars of social, economic, and environmental benefits. In addition to reducing maternity-related health issues, helping women avoid unintended pregnancies can have positive effects on education, income generation, and children’s welfare (Figure 1). For example, a study in Indonesia found that providing access to family planning was three times more powerful than improving school quality in keeping girls in school an extra year. Research in Colombia found that girls with access to family planning clinics were 7% more likely to participate in the formal workforce as adults. More long term, a Brookings Institution study examined the effect of providing access to family planning progra...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Mitigating x-risk through modularity, published by Toby Newberry on the AI Alignment Forum. Write a Review 0. Abstract and main claims [Skip this section if you want a minimally repetitive reading experience :)] This post discusses an approach to x-risk management called ‘mitigation through modularity’. Roughly speaking, the approach involves decorrelating risks, as opposed to minimising them; its slogan would be "don’t put all your eggs in one basket", rather than "don’t drop the basket full of eggs". As you might suspect (given it can be summarised by a well-known proverb), this kind of thinking recurs in lots of places: diversification in finance, redundancy in software development, etc. To some extent, it has also already been applied to x-risk - most notably in the context of space settlement. But my impression is that its application to x-risk so far leaves quite a bit of value on the table (in particular, space settlement isn’t the only kind of strategy this approach points to). Below, I draw together what’s been said about the approach already, present a new frame through which this work could usefully be extended, and make a number of more speculative suggestions. My central claims are: 1. In principle, the strategy discussed below (‘mitigation through modularity’) is a robust way of achieving existential security.[1] 2. In practice, it is unlikely to be effective against: unaligned AI; and some other risks.[2] 3. It is likely to be (at least somewhat) effective against: asteroid or comet impact; supervolcanic eruption; nuclear war; climate change; other environmental damage; naturally arising pandemics; engineered pandemics; and some other risks.[3] 4. Near-term space settlement, as one possible implementation of this strategy, is not sufficient for existential security, and unlikely to be cost-effective. 5. One promising reframing of the strategy is to take a ‘risk-first, rather than a ‘proposal-first’, approach. By this, I mean taking a specific risk (e.g. climate change), and then thinking of ways to decorrelate this across human civilisation - rather than taking a specific proposal (e.g. Martian settlement), and then thinking of the ways it might reduce risk. 1. Mitigation through modularity Superficially, certain species of butterfly appear to be quite bad at survival. They live in small, isolated groups (around different meadows, for example). They are relatively poor flyers, meaning reliable inter-group travel is not an option. In addition, the groups are individually vulnerable, such that each one can be obliterated by a passing squall, a disease affecting host plants, or just an unfortunate role of the Darwinian die.[4] And yet, the butterflies persist. We can explain their surprising resilience through the use of metapopulation models. In such a model, the total butterfly population is divided into numerous subpopulations, representing the isolated groups. For any given subpopulation, there is some risk of local extinction (e.g. squall). If the subpopulations were fully disconnected from one another, this process would eventually lead to the species’ global extinction, as each group of butterflies meets with its private doom. In practice, however, the metapopulation achieves global stability. While the butterflies cannot routinely travel between different meadows, there is nonetheless a small amount of exchange between subpopulations: every so often, a butterfly will be blown from one meadow to the next, or will happen to fly an unusually long distance in one direction. As a result, when one subpopulation becomes extinct, the area it previously occupied will be resettled by accidental pioneers of this sort. Moreover, the rate at which such resettlement events occur more than balances the rate of local extinction events. Even though each subpopulat...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: How You Can Counterfactually Send Millions of Dollars to EA Charities, published by Brendon_Wong, Tharun Sonti on the AI Alignment Forum. Write a Review Summary We have developed a methodology to estimate how much money any U.S. charity is losing every year by keeping money in low-interest accounts This methodology is easy for anyone to replicate and is based on publicly available nonprofit financial statements (IRS Form 990) that all U.S. charities are required to file yearly We approximate GiveWell’s five-year opportunity cost at $4 million dollars, and other EA charities have six-figure or seven-figure five-year opportunity costs as well Like most U.S. charities, many EA charities across various cause areas do not follow the best practice of storing cash in high-interest accounts (which have the same level of risk as low-interest accounts) It only takes several hours of staff time for organizations to set up a high-interest account to move money into (similarly quick to opening up a personal savings account online) High-interest accounts are considered a best practice at major companies like Apple, Google, and Facebook, as well as at large EA charities like the Against Malaria Foundation See our comprehensive EA Forum post in 2019 for more information on selecting low-interest and high-interest bank accounts and investment options Actions an EA community member can take: Contribute online by posting on our action thread: scroll to our action thread in the comments section Advise one or more EA organizations you have a close connection with We’ve been able to help all of the charities our staff have previously worked at to make these improvements, but we’ve noticed that the less connected we are with an organization, the harder it is to get in touch with their staff We hope that readers can help us make the case for better cash management practices to a wide range of EA charities—by doing so, any given reader might be able to "contribute" up to millions of counterfactual dollars to these organizations Take action by directly advising an EA organization you are closely connected with, or by filling out our outreach request form This article was published by Antigravity Investments, an EA social enterprise with the mission of leveraging finance to drive millions of dollars to high-impact charities Our intention here is to simply encourage institutional behavior change and engage in discussion on cash management practices; this recommendation can be implemented independently of our involvement The ideas expressed in this article are also available as a 10-minute EAGxVirtual Unconference talk Form 990 The majority of charities, including EA charities, do not optimize their interest on cash. In this section, we will introduce our cash interest opportunity cost estimation methodology for U.S. 501(c)(3) charities and use GiveWell’s Form 990 as an example. The U.S. tax collection agency known as the Internal Revenue Service (IRS) requires that all tax-exempt organizations, including charities, fill out a financial report known as Form 990 every calendar or fiscal year. The IRS mandates that all Form 990 reports be made publicly available. The Form 990 report for any nonprofit can be found with a quick Google search. GiveWell’s historical Form 990 reports, and other financial information, can be found on its official records page. The IRS’s official instructions for Form 990, the primary source for our analysis methodology, can be found here. We consulted with the IRS and an independent CPA to get their input on various facets of our methodology. Here is a link to GiveWell’s 2019 Form 990 report (the most recent Form 990 available at publication) which we will use as an example: Calculating Cash The balance sheet of any organization describes what it owns as well as what it...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Notes on EA-related research, writing, testing fit, learning, and the Forum, published by MichaelA on the AI Alignment Forum. Cross-posted to LessWrong. I've had calls with >30 people who are interested in things like testing their fit for EA-aligned research careers, writing on the Forum, "getting up to speed" on areas of EA, etc. (This is usually during EA conferences.) I gradually collected a set of links and notes that I felt that many such people would benefit from seeing, then turned that into a Google Doc. Many people told me they found that doc useful, so I'm now (a) sharing it as a public post, and (b) still entertaining the hypothesis that those people were all just vicious liars and sycophants, of course. Disclaimers Not all of these links/notes will be relevant to any given person These links/notes are most relevant to people interested in (1) research roles, (2) roles at explicitly EA organisations, and/or (3) longtermism But this just because that’s what I know best There are of course many important roles that aren’t about research or aren’t at EA orgs! And I'm happy with many EAs prioritising cause areas other than longtermism But, in any case, some of the links/notes will also be relevant to other people and pathways This doc mentions some orgs I work for or have worked for previously, but the opinions expressed here are my own, and I wrote the post (and the doc it evolved from) in a personal capacity Regarding writing, the Forum, etc. Why you (yes, you) should post on the EA Forum (a talk by Aaron Gertler) How you can make an impact on the EA Forum (another talk by Aaron Gertler) Aaron also made a companion document which I think is useful even if you don't watch the talk Feedback available for EA Forum drafts (a post by that Aaron Gertler guy I've been hearing so much about lately) Effective Altruism Editing and Review Reasoning Transparency This has great writing tips that definitely apply on the Forum, and ideally would apply everywhere, but unfortunately they don’t perfectly align with the norms in some areas/fields Readings and notes on how to write/communicate well Reasons for and against posting on the EA Forum Regarding types of writing you can do: Write about any of the research ideas in the links in the next section Write summaries and/or collections Write book reviews (see Buck's suggestion, my suggestion, and posts tagged books) "deep dive into seminal papers/blog posts and attempt to identify all the empirical and conceptual errors in past work, especially writings by either a) other respected EAs or b) other stuff that we otherwise think of as especially important." (see Linch's shortform) I also encourage you to consider reading, commenting, and posting on LessWrong See Welcome to LessWrong! for a great introduction to that site Sometimes people worry that a post idea might be missing some obvious, core insight, or just replicating some other writing you haven't come across. I think this is mainly a problem only inasmuch as it could've been more efficient for you to learn things than slowly craft a post. So if you can write (a rough version of) the post quickly, you could just do that. Or you could ask around or make a quick Question post to outline the basic idea and ask if anyone knows of relevant things you should read. Research ideas Research questions that could have a big social impact, organised by discipline A central directory for open research questions Crucial questions for longtermists Some history topics it might be very valuable to investigate This is somewhat less noteworthy than the other links Programs, approaches, or tips for testing fit for (longtermism-related) research Programs Not all of these things are necessarily "open" right now. Here are things I would describe as research training programs (in alphabetical ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: What are your main reservations about identifying as an effective altruist?, published by richard_ngo on the AI Alignment Forum. A recent EA forum post mentioned that at the Leaders Forum 2019, around half of the participants (including key figures in EA) said that they don’t self-identify as "effective altruists". That seems pretty high to me! So I'd be interested in hearing more from people who are hesitant to identify as effective altruists, about why that's the case. If you'd prefer to answer anonymously, you can fill in this form instead. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Writing about my job: Research Fellow, FHI, published by rgb on the AI Alignment Forum. Following Aaron Gertler’s prompt, I am writing about my job as a researcher at the Future of Humanity Institute: the path that led to me applying for it, the application itself, and what it’s like to do the job. See also the 80,000 Hours guides on academic research and philosophy academia. The basics Research fellow, Future of Humanity Institute (FHI) at Oxford University October 1, 2020 - present When I started this position, I was still working on a PhD in philosophy at New York University. I am still finishing up my dissertation, while working for FHI full-time (here's my FHI page). Background and path to applying I graduated from Harvard in 2011 with a degree in Social Studies (comparable to the UK’s PPE). I did a masters in philosophy at Brandeis University and started a PhD at NYU in fall 2015. EA Global 2016 My path to FHI can be directly traced back to my desire, in the summer of 2016, to get my travel to EA Global reimbursed. I got interested in EA around 2015 and took the Giving What We Can Pledge in summer 2016. Flushed with enthusiasm, I looked into going to EA Global 2016, which was in Berkeley. Michelle Hutchinson organized an academic poster session for that EAG; somehow I was on a list of people who got an email encouraging me to submit a poster. It occurred to me that NYU’s Center for Mind, Brain, and Consciousness reimburses the travel expenses for PhD students who are giving talks and presentations in philosophy of mind. Driven in no small measure by this pecuniary motive, I hastily threw together a poster presentation at the intersection of EA and philosophy of mind. The most important thing about the poster is simply that it got me to the conference.[1] That’s where I first met Michelle Hutchinson; I surmise that meeting Michelle, and being a presenter, got me on a list of EA academics. GPI As a result (I think), about a year later I was invited to be part of the Global Priority Institute’s first group of summer fellows in the summer of 2018. For my project, I worked on applying Lara Buchak’s work on risk aversion to longtermism and cause prioritization.[2] That summer I met lots of people at FHI, who we shared an office and a kitchen with - most notably for the purposes of this post, Katja Grace and Ryan Carey. AI Impacts Meeting Katja Grace in summer 2018 led to me doing research for AI Impacts in the summer of 2019. Also in summer 2019, Ryan Carey messaged me to encourage me to apply for the FHI Research Fellow role. All told, that's all three of my EA gigs - GPI, AI Impacts, FHI - that stemmed from my decision to go to EA Global 2016 and my cheeky quest to get it reimbursed.[3] PhD research Throughout this time, I was doing my PhD research. It was during my PhD that I wrote a paper on fairness measures in machine learning that I would eventually use as my writing sample for FHI. My PhD research also gave me enough familiarity with AI to work on AI-related topics at AI Impacts and eventually FHI.[4] I also ran a reading group on philosophy and AI. The application Materials and process The application required, if I recall correctly: cover letter, CV/resume, research proposal, writing sample, and two references. The process involved a 2-hour (maybe 3?) timed work test, and two rounds of interviews. My research proposal, inspired by issues I had been thinking about at AI Impacts, outlined ways to get evidence for or against the Prosaic AGI thesis. In an interview, the selection committee made it clear that they were not especially excited about this research direction. I also discussed my work in AI ethics. My references were Katja Grace and my dissertation supervisor, David Chalmers. My writing sample was the aforementioned paper on fairness in machine learn...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: A Framework for Assessing the Potential of EA Development in Emerging Locations, published by jahying on the AI Alignment Forum. Write a Review I would like to thank Max Daniel, Jan Kulveit, Alex Barry, Ozzie Gooen, David Nash, Rose Hadshar, Harri Besceli, Emiel Riiko, Florent Berthet, Jaime Sevilla, Chi Nguyen and Aaron Gertler for reviewing this post. Special thanks to Vaidehi Agarwalla for her immense help with copyediting and research assistance. Also thank you to Wanyi Zeng who inspired my research project and has offered generous support since its inception. This framework evolved out of research conducted as part of the 2019 CEA Summer Research Fellowship. My research project looks at how EA should be developed and approached in Asia. My research mentors were Rose Hadshar and Jan Kulveit. Please note that this post is not endorsed by the FHI, CEA, Open Phil, or other individuals and organizations interviewed as part of the research project. If you would like to support my work, I am currently looking for funding, advisors and collaborators. You can reach me at jahying.chung@gmail.com. If you are short on time, the Summary, Background and Summary Table sections should provide a sufficient overview of the framework. Summary Effective Altruism is growing globally. In Asia, for instance, the number of groups has doubled in the last 2 years [1]. Both group organizers and core EA decision-makers have voiced different views and concerns on how (or whether) this growth should happen. In order to avoid overlooking major risks and opportunities, improve communication, and prevent frustration across parties, how might we get everyone on the same page and have productive conversations about developing EA in an emerging location? This framework attempts to answer that question. It aims to provide a common basis on which different stakeholders can evaluate the potential of EA development in emerging locations. It arose out of expert interviews with core EAs who are actively thinking about community and movement building strategy, including staff at CEA and Open Phil, community managers within other EA organizations, and leading group organizers around the world. This post will first outline the reasons to work on this topic, the value of the framework, and its current status and limitations. Then it will present the framework in the form of a summary table before going in depth into each dimension. Finally, I outline my next steps in applying this framework to Asian locations. In short, the framework applies two types of analyses: group analysis and geographic analysis, and considers two perspectives: cause-generic and cause-specific. In the group analysis, the framework breaks down the question of “how promising is this group?” into three aspects: Group traction: what has the group accomplished so far? Capabilities: what resources do they have? Connections: how do they collaborate/coordinate with other EAs? How are resources transferred? Who do they most frequently interact with, and in what capacity? In the geographic analysis, the framework breaks down the question “how exciting would EA be in this location?” into three aspects: Existing Alignment: how much alignment already exists with EA ideas? Talent: what types of talent exist here, in quantity and quality? Business and Politics: how does power work here? What influential institutions exist here? The analysis can be done from a cause-generic perspective and cause-specific [2] perspective. The full framework has not yet been applied to specific locations and I expect to make adjustments based on feedback from group organizers and core EAs as it is applied and evaluated. Background Terminology Throughout this post I will use the following terms which need some justification or clarification: EA development: instead of ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: How much EA analysis of AI safety as a cause area exists?, published by richard_ngo on the AI Alignment Forum. Write a Review AI safety has become a big deal in EA, and so I'm curious about how much "due diligence" on it has been done by the EA community as a whole. Obviously there have been many in-person discussions, but it's very difficult to evaluate whether these contain new or high-quality content. Probably a better metric is how much work has been done which: 1. Is publicly available; 2. Engages in detail with core arguments for why AI might be dangerous (type A), OR tries to evaluate the credibility of the arguments without directly engaging with them (type B); 3. Was motivated or instigated by EA. I'm wary of focusing too much on credit assignment, but it seems important to be able to answer a question like "if EA hadn't ever formed, to what extent would it have been harder for an impartial observer in 2019 to evaluate whether working on AI safety is important?" The clearest evidence would be if there were much relevant work produced by people who were employed at EA orgs, funded by EA grants, or convinced to work on AI safety through their involvement with EA. Some such work comes to mind, and I've listed it below; what am I missing? Type A work which meets my criteria above: A lot of writing by Holden Karnofsky A lot of writing by Paul Christiano This sequence by Rohin Shah These posts by Jeff Kaufman This agenda by Allan Dafoe This report by Tom Sittler Type A work which only partially meets criterion 3 (or which I'm uncertain about): These two articles by Luke Muehlhauser This report by Eric Drexler This blog by Ben Hoffman AI impacts Type B work which meets my criteria above: This talk by Ben Garfinkel This talk by Daniel Dewey This report by the Oxford Prioritisation Project Things which don't meet those criteria: This 80,000 hours report (which mentions the arguments, but doesn't thoroughly evaluate them) Superintelligence The AI Foom debate Edited to add: Wei Dai asked why I didn't count Nick Bostrom as "part of EA", and I wrote quite a long answer which explains the motivations behind this question much better than my original post. So I've copied most of it below: The three questions I am ultimately trying to answer are: a) how valuable is it to build up the EA movement? b) how much should I update when I learn that a given belief is a consensus in EA? and c) how much evidence do the opinions of other people provide in favour of AI safety being important? To answer the first question, assuming that analysis of AI safety as a cause area is valuable, I should focus on contributions by people who were motivated or instigated by the EA movement itself. Here Nick doesn't count (except insofar as EA made his book come out sooner or better). To answer the second question, it helps to know whether the focus on AI safety in EA came about because many people did comprehensive due diligence and shared their findings, or whether there wasn't much investigation and the ubiquity of the belief was driven via an information cascade. For this purpose, I should count work by people to the extent that they or people like them are likely to critically investigate other beliefs that are or will become widespread in EA. Being motivated to investigate AI safety by membership in the EA movement is the best evidence, but for the purpose of answering this question I probably should have used "motivated by the EA movement or motivated by very similar things to what EAs are motivated by", and should partially count Nick. To answer the third question, it helps to know whether the people who have become convinced that AI safety is important are a relatively homogenous group who might all have highly correlated biases and hidden motivations, or whether a wide range of people hav...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Snails used for human consumption: The case of meat and slime, published by Daniela R. Waldhorn on the AI Alignment Forum. Write a Review Executive summary The number of snails produced for human consumption increases gradually every year. Still, there is very little awareness about the details of snail production or how serious an ethical problem it might be. In this report (full version available here[1]), I assess snail production and farming-specific welfare concerns, and discuss some scale, neglectedness, and tractability considerations. Some of our main findings are: Welfare concerns: In the farm: High density, movement restrictions, and different kinds of diseases result in high mortality rates. Processing: Commonly traded alive, and again with virtually no space to move. Slaughter: Typically boiled to death. Scope: It can be estimated that between 2.9B to 7.7B[2] snails were slaughtered for their meat worldwide in 2016. Neglectedness: invertebrate welfare is an issue that has not gained much attention within the effective altruism community. Even in academia, there is a general lack of concern for studying welfare-related issues about snails. Tractability: The most prevalent snail pathologies and their possible treatments need to be identified. We know of no large-scale initiatives to improve the situation of snails used for human purposes. Although the snail market looks strong, a sharp increase in production is not expected. All things considered, I conclude that investing specific efforts on behalf of snails used as food may not be cost-effective. Still, further research may uncover specific welfare measures on behalf of these animals. Introduction For the last while, Rethink Priorities has been studying invertebrate sentience, invertebrate welfare, and more recently, the lives of farmed invertebrates. All our work on invertebrates is available here. Currently, we are focusing our efforts on farmed invertebrates because ameliorating their suffering is likely to be more tractable than intervening in nature to help wild invertebrates. Additionally, the number of farmed invertebrates for different purposes stands to increase in the future, while that is unclear regarding invertebrates living in the wild. Understanding the situation of farmed snails seems relevant since these animals are consumed by humans in many cultures. Presumably, the problem is of considerable magnitude, and it may be increasing steadily. Indeed, according to FAO (2019a) data[3], the tonnes of snails produced for human consumption (e.g., 18,331 tonnes in 2017) rise gradually every year. However, not much is known about these animals' quality of life and the conditions in which they are raised. Still, it is known that snails are typically slaughtered by boiling. If these animals have valenced experiences, it is probably an extremely painful way to die. While snails are used for different purposes–e.g., to eat their meat, to eat their eggs as a type of caviar, or to obtain snail slime for use in cosmetics–, this report focuses on what appears to be, nowadays, the main driver of snail farming: snail meat consumption. Since the use of snails in cosmetics is rapidly growing in popularity, relevant aspects about snails exploited for extracting their slime are addressed, where possible. This report is organized as follows: First, some general aspects of snail production are assessed. Second, some welfare issues associated with snail production and consumption are raised. Third, I discuss some scale, neglectedness, and tractability considerations. Fourth, I suggest key issues that further research should attend to, in order to improve our current understanding of snail sentience and welfare. Lastly, I conclude by emphasising some directions for future work on snails used for human purposes. Stil...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Update from the Happier Lives Institute, published by ClareDonaldson, MichaelPlant on the AI Alignment Forum. Summary This post is an update on the progress and plans of the Happier Lives Institute (HLI), particularly focussing on our ongoing research and projects for the rest of 2020. Our last post on the forum was in June 2019, and our strategy has changed enough since then to warrant a new post. We welcome feedback on our plans. We are a research organisation searching for the most effective methods to improve global well-being. We are doing this by using subjective well-being (SWB) - self-reported happiness and life satisfaction - as the key measure of value in impact evaluation. We think there's a strong theoretical case that SWB is the best way to measure how people's lives go. As effective altruists haven't made much use of this approach, or the existing social science evidence on it, we are exploring what it would look like to do cause prioritisation in terms of SWB. Currently, our two main research projects are: (1) theoretical research into SWB and its measurement, (2) evaluating various life-improving interventions, e.g. cash transfers, in terms of SWB. Our secondary projects explore promising areas when viewed through the SWB lens: (3) evaluating promising mental health programmes, and (4) broad but shallow cause reports into pain, mental health, and positive education. While HLI is interested in mental health, we do not see ourselves as "the EA mental health org”, but as conducting global priorities research. Our three staff members are conducting projects 1 and 2; volunteers are working on projects 3 and 4. We have room for more funding in 2020. Our motivation Many people aligned with effective altruism (EA) aim to maximise well-being. A common approach in impact evaluation is to measure the changes in people’s health or wealth and use these as proxies for well-being. For example: the use of disability-adjusted life years (DALYs) and quality-adjusted life years (QALYs) is fairly routine; GiveWell’s cost-effectiveness model converts outcomes into the equivalent of doubling consumption and averting the deaths of under-5s. While health and wealth clearly contribute to well-being, few would accept they are, in the end, what ultimately matters (i.e. are intrinsically valuable). Hence, the further challenge is to determine how much impact those, as well as other goods, directly have on well-being, so we can make trade-offs between them. To do this, we could rely on the hypothetical or actual choices that either decision-makers or members of the public make (see some of GiveWell’s recent discussion). However, there are several reasons to believe that human biases may lead individuals to make poor assessments (e.g. Wikipedia article on affective forecasting). We do not clearly choose what is best for us. An alternative is to ask people about their lives as they live them. Subjective well-being (SWB) is an umbrella term that includes self-reported life satisfaction and happiness data. We expect most readers would agree that well-being consists in happiness or life satisfaction, at least in part. Research into SWB is rising quickly in academia; over 170,000 books and articles have been published on the topic in the last 15 years (Diener et al., 2018). EA organisations have not (yet) made much use of the existing work on SWB to determine the priorities, and this may lead us to different and surprising conclusions. Therefore, we think that exploring the use of SWB in determining our priorities is a project with high expected value. At HLI, we plan to spend the bulk of our research time over the next year on projects that show how and why subjective well-being can be used to evaluate impact in areas already of interest to EAs, for instance, the effect on SWB from ca...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Gordon Irlam: an effective altruist ahead of his time, published by Louis_Francini on the AI Alignment Forum. Write a Review When people think about the history of effective altruism as a memeplex, they generally assume that it developed into a coherent philosophy around the time of Giving What We Can’s founding in 2009. Of course, you could point to moral philosophers like Bentham, Singer, or Unger whose ideas naturally implied EA, but they never fully laid the conceptual groundwork for EA methodology. You could also point to altruists who were highly effective, but who didn’t develop a detailed EA worldview or methodology. To be sure, the idea of altruism was not new, nor was the idea of effectiveness, but the unique combination—emphasizing principles of cause neutrality, epistemic and instrumental rationality, quantitative analysis, and the importance of considering counterfactuals—had never been seen before. Or had it? Enter the work of Gordon Irlam. Irlam has a varied resume which includes software engineering at Google in 2004, working as a grad student in a malaria research lab in 2005, and most recently self-study in artificial intelligence. He also runs a small charitable foundation that has donated over $1.7 million to charities, mostly working on developing world health/poverty and global catastrophic risks. But what I would like to highlight is his essay “Making a difference,” which does not list its creation date but was last edited in January 2004. The similarities between this 2004 essay and modern EA philosophy are uncanny. The article begins by discussing the difficulty of attributing counterfactual impact, and then goes into a very detailed discussion of replaceability, similar to what would later be seen in William MacAskill’s 2014 paper “Replaceability, Career Choice, and Making a Difference”. Here is one quote: We each seek to exercise our free will in such a way as to maximize our preferred utility function of the world. What makes this difficult is the interlinking of any action we might take with the action of others. For instance, if somebody accepts a job working as a youth counsellor, offsetting the good that might be done, is the loss of good the next best candidate would have contributed. Taking the job causes things to ripple down the line, as they in turn, displace somebody else from some other job, and so on. While there are earlier predecessors to the idea of “earning to give”, Irlam provides the clearest pre-EA argument I have seen: Suppose you have a skill that is highly valued by employers, but you lack skills highly valued with respect to your utility function. Then, one option that makes a lot of sense is to take a high paying job that is neutral with respect to your utility function, and to donate much of what you earn to an organization that works on what you care about. This allows you to translate the skill you don't value into being effectively highly skilled at what you care about. You will undoubtedly be able to achieve more by working in this fashion than working on the issues you care about directly. The article concludes by discussing the pivotal role one person, Viktor Zhdanov, played in the eradication of smallpox. This is eerily similar to the way EAs often talk about Stanislav Petrov or Vasili Arkhipov. William MacAskill would later write an article praising Zhdanov in 2015. Irlam did more than theorize about the economics of doing good. He also tried to put these principles into action by developing his “Back of the Envelope Guide to Philanthropy” which compares various philanthropic causes according to their “leverage factor”, which refers to the cost-effectiveness of the interventions as opposed to relying on overhead ratio. According to the copyright notice, this project was started in 2005, but the earliest arc...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Differences in the Intensity of Valenced Experience across Species, published by Jason Schukraft on the AI Alignment Forum. Key Highlights Differences in the intensity range of valenced experience across species may affect how we ought to allocate resources to help different types of animals Humans and other mammals likely share a roughly similar intensity range It is unlikely that any species of animal possesses an intensity range that is exclusively extraordinarily mild Some aspects of cognitive sophistication appear to be positively correlated with intensity range; other aspects of cognitive sophistication appear to be negatively correlated with intensity range Affective complexity generally appears to be positively correlated with intensity range There is as yet no good objective measure of valence intensity, though there is much interesting work ongoing in this area Executive Summary This post is the fifth in Rethink Priorities’ moral weight series. In this report, I explain why it would matter if different sorts of animals possessed characteristically different intensity ranges of valenced experience, what factors might affect the intensity range of valenced experience, and how we might begin to measure differences in the intensity of valenced experience. Animals differ in their perceptual abilities, their physiology and neural architecture, and their cognitive, affective, and social complexity. Given these differences, it would be surprising if the intensity range of valenced experience were uniform across species. To investigate differences in the intensity range of valenced experience across species, I adopted a three-stage methodology: First, I explored what, if anything, theoretical evolutionary biology could tell us about the function of valenced experience. Next, I explored how different aspects of intellectual and emotional complexity might affect the characteristic intensity of valenced experience. Finally, I explored potential neurobiological, behavioral, and physiological markers of the intensity of valenced experience in humans and nonhuman animals. Broadly speaking, the evolutionary function of valenced experience is to promote fitness-improving behaviors. It’s plausible that natural selection would not produce animals for whom valenced experiences were always extraordinarily weak because subjective experiences that were so faint as to be almost imperceptible would appear to do a poor job motivating behavior. Conversely, it appears unlikely that evolution would select for animals with a non-contiguous range that was exclusively extraordinarily strong because extremely intense experiences are distracting in a way that appears likely to reduce fitness. ‘Cognitive sophistication’ is a nebulous term that may refer to any of a constellation of mostly independent traits. Many of these traits plausibly affect the intensity of valenced experience, but the sign of the effect is often unclear. ‘Affective complexity’ refers to the diversity and depth of emotional sensations an animal can experience. Increased affective complexity may unlock qualitatively unique emotional states—such as fear, depression, or love—that by themselves or in combination with physical states increase the intensity range of experience. There are currently no good cross-species measures of the intensity of valenced experience, though there is intriguing recent evidence that neural oscillations in the gamma band may track differences in pain intensity in both humans and nonhuman mammals. Humans and nonhuman mammals possess neurologically and behaviorally similar affective systems, suggesting that most mammals are capable of experiencing roughly the same base set of emotions. It’s unclear how stark the differences in cognitive sophistication are across mammalian species and how these di...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Evidence, cluelessness, and the long term - Hilary Greaves, published by velutvulpes, juliakarbing on the AI Alignment Forum. Hilary Greaves is a professor of philosophy at the University of Oxford and the Director of the Global Priorities Institute. This talk was delivered at the Effective Altruism Student Summit in October 2020. This transcript has been lightly edited for clarity. Introduction My talk has three parts. In part one, I'll talk about three of the basic canons of effective altruism, as I think most people understand them. Effectiveness, cost-effectiveness, and the value of evidence. In part two, I'll talk about the limits of evidence. It's really important to pay attention to evidence, if you want to know what works. But a problem we face is that evidence can only go so far. In particular, I argue in the second part of my talk that most of the stuff that we ought to care about is necessarily stuff that we basically have no evidence for. This generates the problem that I call 'cluelessness'. And in the third part of my talk, I'll discuss how we might respond to this fact. I don't know the answer and this is something that I struggle with a lot myself, but what I will do in the third part of the talk is I'll lay out five possible responses and I'll at least tell you what I think about each of those possible responses. Part one: effectiveness, cost-effectiveness, and the importance of evidence. Effectiveness So firstly, then, effectiveness. It's a familiar point in discussions of effective altruism and elsewhere that even most well-intentioned interventions don't in fact work at all, or in some cases, they even do more harm than good, on net. One example (which may be familiar to many of you already) is that of Playpumps. Playpumps were supposed to be a novel way of improving access to clean water across rural Africa. The idea is that instead of the village women laboriously pumping the water by hand themselves, you harness the energy and enthusiasm of youth to get children to play on a roundabout; and the turning of the roundabout is what pumps the water. This perhaps seemed like a great idea at the time, and millions of dollars were spent rolling out thousands of these pumps across Africa. But we now know that, well intentioned though it was, this intervention does more harm than good. The Playpumps are inferior to the original hand pumps that they replaced. For another example, one might be concerned to increase school attendance in poor rural areas. To do that, one starts thinking about: "Well, what might be the reasons children aren't going to school in those areas?" And there are lots of things you might think about: maybe because they're so poor they're staying home to work for the family instead, in which case perhaps sponsoring a child so they don't have to do that would help. Maybe they can't afford the school uniform. Maybe they're teenage girls and they're too embarrassed to go to school if they've got their period because they don't have access to adequate sanitary products. There could be lots of things. But let's seize on that last one, which seems like a plausible thing. Maybe their period is what's keeping many teenage girls away from school. If so, then one might very well think distributing free sanitary products would be a cost-effective way of increasing school attendance. But at least in one study, this too turns out to have zero net effect on the intended outcome. It has zero net effect on child years spent in school. That's maybe surprising, but that's what the evidence seems to be telling us. So many well-intentioned interventions turn out not to work. Cost-effectiveness Secondly, though, comes cost-effectiveness: even amongst the interventions that do work, there's an enormous variation in how well they work. If you have a fixed s...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: AMA: Ajeya Cotra, researcher at Open Phil, published by Ajeya on the AI Alignment Forum. [EDIT: Thanks for the questions everyone! Just noting that I'm mostly done answering questions, and there were a few that came in Tuesday night or later that I probably won't get to.] Hi everyone! I’m Ajeya, and I’ll be doing an Ask Me Anything here. I’ll plan to start answering questions Monday Feb 1 at 10 AM Pacific. I will be blocking off much of Monday and Tuesday for question-answering, and may continue to answer a few more questions through the week if there are ones left, though I might not get to everything. About me: I’m a Senior Research Analyst at Open Philanthropy, where I focus on cause prioritization and AI. 80,000 Hours released a podcast episode with me last week discussing some of my work, and last September I put out a draft report on AI timelines which is discussed in the podcast. Currently, I’m trying to think about AI threat models and how much x-risk reduction we could expect the “last long-termist dollar” to buy. I joined Open Phil in the summer of 2016, and before that I was a student at UC Berkeley, where I studied computer science, co-ran the Effective Altruists of Berkeley student group, and taught a student-run course on EA. I’m most excited about answering questions related to AI timelines, AI risk more broadly, and cause prioritization, but feel free to ask me anything! Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Important Between-Cause Considerations: things every EA should know about, published by jackmalde on the AI Alignment For Overview Choosing a preferred cause area is arguably one of the most important decisions an EA will make. Not only are there plausibly astronomical differences in value between non-EA and EA cause areas, but this is also the case between different EA cause areas. It therefore seems important to make it easy for EAs to make a fully-informed decision on preferred cause area. In this post I claim that, to make the best choice on preferred cause area, EAs should have at least a high-level understanding of various ‘Important Between-Cause Considerations’ (IBCs). An IBC is an idea that a significant proportion of the EA community takes seriously, and that is important to understand (at least at a high-level) in order to aid in the act of prioritising between the potentially highest value cause areas, which I classify as: extinction risk, non-extinction risk longtermist, near-term animal-focused, near-term human-focused, global priorities research and movement building. I provide illustrations of the concept of an IBC, as well as a list of potential IBCs. Furthermore, I think that the EA community needs to do more to ensure that EAs can easily become acquainted with IBCs, by producing a greater quantity of educational content that could appeal to a wider range of people. This could include short(ish) videos, online courses, or simplified write-ups. An EA movement where most EAs have at least a high-level understanding of all known IBCs should be a movement where people are more aligned to the highest value cause areas (whatever these might be), and ultimately a movement that does more good. Note: I am fairly confident in the claim that it would be good for the EA community to do more to enable EAs to better understand important ideas, and that a greater variety of educational content would help with this. Any of my stronger claims are more speculative, but I hold to be true until convinced otherwise. Acknowledgement: Many thanks to Michael Aird for some helpful comments on a first draft of this post. Illustrations of the idea Here are two fictional stories: Arjun is a university student studying Economics and wants to improve health in the low-income world. He has been convinced by Peter Singer’s shallow pond thought experiment and is struck by how one can drastically improve the lives of those in different parts of the world at little personal cost. On the other hand, he has never been convinced of the importance of longtermist cause areas. In short, Arjun holds a person-affecting view of population ethics which makes him relatively unconcerned about the prospect of human extinction. One day, Arjun comes across a blog post on the EA Forum which summarises the core arguments of a paper called “The Case for Strong Longtermism” by Greaves and MacAskill. He’s heard of the paper but, not being an academic, has never quite felt up for reading it. A blog post however seems far more accessible to him. On reading the post, Arjun is struck by the claim that longtermism is broader than just reducing extinction risk. He is surprised to learn that there may be tractable ways to improve average future well-being, conditional on humanity not going prematurely extinct, for example by improving institutions. Whilst Arjun doesn’t feel the need to ensure people exist in the future, he thinks it an admirable goal to improve the wellbeing of those who will live anyway. Over the next month, Arjun reads everything on longtermism he can get his hands on and, whilst this doesn’t convince him of the validity of longtermism, it convinces him that it is at least plausible. Ultimately, because the stakes seem so high, Arjun decides to switch from working on global health to researc...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Possible misconceptions about (strong) longtermism, published by jackmalde on the AI Alignment Forum. Overview In this post I provide a brief sketch of The case for strong longtermism as put forward by Greaves and MacAskill, and proceed to raise and address possible misconceptions that people may have about strong longtermism. Some of the misconceptions I have come across, whilst others I simply suspect may be held by some people in the EA community. The goal of this post isn’t to convert people as I think there remain valid objections against strong longtermism to grapple with, which I touch on at the end of this post. Instead, I simply want to address potential misunderstandings, or point out nuances that may not be fully appreciated by some in the EA community. I think it is important for the EA community to appreciate these nuances, which should hopefully aid the goal of figuring out how we can do the most good. EDIT: I realise this is a long post. Feel free just to read misconceptions you are interested in as opposed to the whole post! NOTE: I certainly do not consider myself to be any sort of authority on longtermism. I partly wrote this post to push me to engage with the ideas more deeply than I already had. No-one has read through this before my posting, so it’s certainly possible that there are inaccuracies or mistakes in this post and I look forward to any of these being pointed out! I’d also appreciate ideas for other possible misconceptions that I have not covered here. Defining strong longtermism The specific claim that I want to address possible misconceptions about is that of axiological strong longtermism, which Greaves and MacAskill define in their 2019 paper The case for strong longtermism as the following: Axiological strong longtermism (AL): “In a wide class of decision situations, the option that is ex ante best is contained in a fairly small subset of options whose ex ante effects on the very long-run future are best.” Put more simply (and phrased in a deontic way that assumes we should do is what will result in the best consequences), one might say that: “In most of the choices (or, most of the most important choices) we face today, what we ought to do is mainly determined by possible effects on the far future.” Greaves and MacAskill note that an implication of axiological strong longtermism is that: “for the purposes of evaluating actions, we can in the first instance often simply ignore all the effects contained in the first 100 (or even 1000) years, focussing primarily on the further-future effects. Short-run effects act as little more than tie-breakers.” I think most people would agree that this is a striking claim. Sketch of the strong longtermist argument The argument made by Greaves and MacAskill (2019) begins with a plausibility argument that goes roughly as follows: Plausibility Argument: In expectation, the future is vast in size (in terms of expected number of beings) All consequences matter equally (i.e. it doesn’t matter when a consequence occurs, or if it was intended or not) Therefore it is at least plausible that the amount of ex ante good we can generate by influencing the expected course of the very long-run future exceeds the amount of ex ante good we can generate via influencing the expected course of short-run events, even after taking into account the greater uncertainty of further-future effects. Also, because of the near-term bias exhibited by the majority of existing actors, we should expect tractable longtermist options (if they exist) to be systematically under-exploited at the current margin The authors then consider the intractability objection: that it is essentially impossible to significantly influence the long-term future ex ante, perhaps because the magnitude of the effects of one’s actions (in expected value-d...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: A bunch of reasons why you might have low energy (or other vague health problems) and what to do about it, published by alexlintz on the AI Alignment Forum. Epistemic status: This post leans heavily on my personal experience and is not well-researched. I’m not a doctor, nor have I studied medicine. I do consider myself pretty good at Googling things though. Also, a real doctor did look over and at least tacitly approve of this post. I’m not doing much in the way of literature review, validating claims, etc so take everything with a teaspoon of salt. There are also more side effects and bad interactions than I’m able to mention. Do your own research before you try any interventions I suggest! Also, if you find something definitely wrong in the post let me know in the comments and I’ll try to correct it. Over the past two years or so I’ve been on a long journey to figure out why I often have joint pain (gradually expanding to almost all my joints), gut problems, and episodes of extreme fatigue about once a week. When I say extreme fatigue try to imagine the following: moving sucks and you don’t want to do it, same with thinking about things, and lying on the floor for half an hour because you slid off your chair seems like a reasonable thing to do. I am not totally sure I’m at the end of this journey but I’ve learned enough to say things which will probably be useful for some people. I was really surprised by a lot of what I found and I expect many of you will be too. I’m also really surprised by the lack of something like this piece out in the world as this is so clearly a thing many people struggle with (if it already exists please post a link in the comments!). The main things I have looked at are food sensitivities, stress, irritable bowel syndrome (IBS), and gut health. There are obviously a ton of reasons why you could be fatigued (or have other hard-to-diagnose health issues). To demonstrate how hard this is, this is why we have catch-all diagnoses like fibromyalgia and chronic fatigue which nobody really knows what to do with. They just represent some bundle of symptoms with no clear underlying cause (and people have really been trying to find a cause!). Fatigue is a symptom of tons of major illnesses. Suffice to say this is super difficult and I’m just covering a few possibilities. Also, obligatory disclaimer: this is not medical advice. Why is this important? My guess is that a bunch of you, maybe most, are not at or near optimal health. This might be a not-knowing-what-the-world-should-look-like-before-you-try-on-glasses kind of thing. You might not realize just how much energy you could have. For example, you probably don’t need to be tired for the first hour or two after you wake up! It’s possible to wake up and feel great most of the time (I’m pretty sure...). Of course sleep, exercise, and nutrition are the obvious things to do and you should almost certainly try those first.[1] There are also good guides on those already (and I see them discussed often in EA circles) [edit: Good sleep guide from Lynette Bye]. If you’re still having problems after that though you probably don’t need to keep having those problems. And if you can solve those problems now the expected value is generally extraordinary. If you get a 1% energy gain consistently through your lifetime because of something you find out now, that is super valuable. Like more valuable than almost anything else you could possibly do for your productivity. If you already have health issues then probably you’re going to get a whole lot more than a 1% energy gain (I’d estimate a 20-100% gain for me if I can solve my issue. This could lead to a much higher boost in impact over the long-term[2]). That’s going to matter a whole lot more than whether you use ultraworking or focusmate, what note-taking soft...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: New blog: Cold Takes, published by Holden Karnofsky on the AI Alignment Forum. I've started a (free) blog/newsletter at . The target audience for many posts will be people who are interested in EA-ish topics, but don't necessarily have any background in them. Sharing the blog and/or its posts in ways that are likely to find readers like that would be appreciated. The longer and more EA-relevant pieces will be cross-posted here, and will contain links to the Forum for people interested in discussing them (I won't be hosting my own comments section). I'll also sometimes post a companion piece to a blog post on the Forum only, when the companion piece requires more existing familiarity with EA. I'm expecting to put out one long piece and a couple of shorter pieces each week (for at least the first few months). The first set of long pieces will be a series laying out the case as I see it that we're in the most important century ever for humanity; this will include topics like "consequences of mind uploading" as well as extensive discussion of the various approaches to forecasting when transformative AI will be developed (a lot of this will be summarizing work like Ajeya Cotra's timelines analysis). After that I'm going to write about a number of other topics, including whether life has gotten better over the course of history, whether the world is getting worse at innovation, and pros and cons of the epistemology and ethics common in the rationalist and effective altruist communities. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Writing about my job: Economics Professor, published by Kevin Kuruc on the AI Alignment Forum. I am following the advice of Aaron Gertler and writing a post about my job. 80000 hours has independent career path pages dedicated to getting an economics PhD and doing academic research, but the specifics of my personal experience may be of interest. Plus, it was fun to recount! Summary of Current Role Tenure track professor of economics (since 2019) at large state school in the US (University of Oklahoma; Boomer Sooner!) Its not MIT, but I have very bright and active colleagues. Some of you may even know of Joan Hamory of deworming fame. I research macroeconomic topics, primarily questions that are, at least loosely, within Global Priorities Research (GPR). This focus has lead to frequent engagement with the Global Priorities Institute as well as some folks at Open Philanthropy (though the latter has been very limited and informal so far). My Background and Path to Applying Went to a not-very-prestigious, but large, research university (Temple University; Go Owls!) In undergrad I couldn't get enough of my math and economics courses and was (probably) the best economics student at my University while I was there. This allowed me a lot of access to faculty. Neither parent went to college, so I was lucky that a professor pushed the idea of a PhD. That was not on my radar (nor did I understand it). I also enjoyed researching my honors thesis, learning how to write code, and the development economics internship I had in Cape Town. These made me confident a PhD was a good future move. My only useful extra curricular was a job tutoring math at the university learning center (this honed my only marketable skill - math - and I now recommend it to my students with mathematical aptitude). I then went directly from undergrad to a graduate school ranked ~25 the US (University of Texas at Austin; Hook 'Em!). I considered taking a job as a research assistant at a Federal Reserve Bank to improve my grad placement. Ultimately I decided the 2 year life-cost was not worth it. Despite the popularity of that route, I very much continue to think I made a good decision in my case. At Texas I worked in the macroeconomics group, but also had a development economics co-advisor. I sat a bit awkwardly between fields. In my 3rd year of graduate school I became very interested in more (not-yet-longtermist) EA ideas. I figured a job at an international organization would be a good path to impact and ended up landing an internship at the IMF. This internship probably only helped a bit towards my current academic life, but I learned a lot, enjoyed it, and can imagine scenarios where this did help land me in an international organization. Getting my Current Job There is plenty of advice on navigating the PhD economics job market, so I won't recount my general strategy here. If you're an undergrad instead looking for PhD application advice, check out the GPI mentoring program! Personally, I would have been happy at an academic job or a policy making organization (preferably something like IMF or World Bank). I ended up with offers from (i) my current academic institution and (ii) the Reserve Bank of India in their research department. The stark difference in these offers fairly represents the tightrope I was trying to walk between (i) showing I could do academic-style research (ii) working on applied policy questions and (iii) starting to get interested in GPR-style topics. I honestly feel like I didn't blend these very well; yet somehow I managed to land a job I was happy with. I'd be willing to talk with anyone entering the economics job market in the near future about my thoughts on this challenge. Also, I was on the hiring committee at my University this last year, so I now have a clearer understandin...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Working at a (DC) policy think tank: Why you might want to do it, what it’s like, and how to get a job, published by Locke_USA on the AI Alignment Forum. Summary and background Note: If you are interested in working on US policy at DC think tanks, consider applying to Open Philanthropy’s new Technology Policy Fellowship (September 15th deadline), which has think tank fellowship opportunities for both entry-level (“junior fellow”) and more senior (“fellow”) roles. Working at a think tank could be a great way for EAs to build policy-relevant skills and networks and to promote high-impact policy ideas, as 80,000 Hours has discussed in its think tank research career guide. This post complements that guide by explaining in more detail how the think tank world works, focusing specifically on US policy and Washington DC-based think tanks. Our goal is to allow EAs to make informed decisions about (a) whether think tanks are a good place for them to work, (b) which think tank jobs they could/should target and why, and (c) how to find and pursue specific job opportunities. The post has content for both students and people further along in their career. This post discusses (1) why you might want to work at DC think tanks, (2) the types of think tanks that exist in DC and what work they do, (3) some questions you may want to ask yourself if you’re thinking about think tank work, and (4) pointers on how to find and apply for jobs at think tanks. Appendix sections provide further resources on think tanks and EA-related DC think tank programs (especially in AI and biosecurity) and link to a database we put together with a sample of ~100 think tank job postings. A few key takeaways that we elaborate on below: Think tanks are useful launching pads for policy work, providing a perch from which you can get a broad perspective on the policy ecosystem. Almost nobody has a “think tank career” — instead, see a think tank job as one possible part of a “policy career.” Direct policy impact is possible, but most think tank jobs will be useful primarily for (a) testing fit (for both think tank work specifically and policy work more broadly), (b) building and demonstrating relevant aptitudes, and (c) growing your network. There are many kinds of think tanks and they have a wide variety of jobs beyond pure research roles (e.g. in comms and ops). EAs who are interested in policy but don’t want to do research could still be a good fit for think tank work. Getting a think tank job is often challenging, but can be made easier by bringing your own “fellowship” funding. Several EA funders may be interested in funding you for a think tank placement. The post is published anonymously for reputational reasons. The content of the posts is based on the authors’ personal experiences working on policy in DC for several years, background reading, and conversations with dozens of EAs and non-EAs with extensive think tank experience. If you are interested in working in DC, you may also enjoy our companion EA Forum posts on working in Congress (part #1, part #2). Feedback request We aim to write more US policy career-focused posts like this in the future (e.g. on the executive branch). Feedback on which types of content are (not) helpful to you, and what content to prioritize, is very welcome. Please send us your (potentially anonymous) thoughts via this short form! 1. What are think tanks, and why might you want to work there? Washington DC is home to more than a hundred think tanks, running the gamut from rigorous and relatively objective research institutions focused on generating novel policy insights to more advocacy-oriented organizations seeking to justify and amplify certain predefined policy priorities. But all think tanks are united by a common goal: to inform and ultimately influence policymaking (mor...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Evidence from two studies of EA careers advice interventions, published by Jamie_Harris on the AI Alignment Forum. Many thanks to Lauren Mee, David Reinstein, Brenton Mayer, Aaron Gertler, Alex Holness-Tofts, Lynn Tan, Vaidehi Agarwalla, David Moss, and Renee Bell for providing feedback on drafts of this writeup, as well as all who provided feedback on the studies themselves. Summary Animal Advocacy Careers (AAC) ran two longitudinal studies aiming to compare and test the cost-effectiveness of our one-to-one advising calls and our online course. Various forms of these two types of careers advice service have been used by people seeking to build the effective altruism (EA) movement for years, and we expect the results to be informative to EA movement builders, as well as to AAC. We interpret the results as tentative evidence of positive effects from both services, but the effects of each seem to be different. Which is more effective overall depends on your views about which sorts of effects are most important; our guess is that one-to-one calls are slightly more effective per participant, but not by much. One-to-one calls seem substantially more costly per participant, which makes the service harder to scale. There therefore seems to be a tradeoff between costs and apparent effects per participant. We’d guess that the online course was (and will be, once scaled up) slightly more cost-effective, all things considered, but the services might just serve different purposes, especially since the applicants might be different for the different services. Background Animal Advocacy Careers (AAC) ran a longitudinal study testing the effects of our ~1 hour one-to-one careers advising calls, which operated in a similar style to calls given by 80,000 Hours and the organisers of local effective altruism (EA) groups across the world. Over roughly the same time period, we ran a second study using very similar methodology that tested the effects of our ~9 week online course, which taught some core content about effective animal advocacy, effective altruism, and impact-focused career strategy and culminated in support to develop a career plan, either via a group workshop or by redirecting to planning materials by 80,000 Hours. Each study was designed as a randomised controlled trial,[1] and pre-registered on the Open Science Framework (here and here), although a few methodological difficulties mean that we shouldn’t interpret the results as giving very conclusive answers. Despite these difficulties, we think that the studies provide useful evidence both for AAC and others focusing on building the effective altruism movement (i.e. the community striving to help others as much as possible using the best evidence available) to help us prioritise our time and resources. We’ll be sharing more about the methodological lessons from the studies in a forthcoming post called “EA movement building: Should you run an experiment?” The findings are also written up in the style of a formal academic paper, viewable here. That version provides more detail on the methodology (participants, procedure, and instruments) and contains extensive appendices (predictions, full results, anonymised raw data, R code, and more). In the rest of this post, we summarise some of the key results and takeaways. Which service has larger effects? The ideal evaluation of whether a career advice intervention genuinely increases a participant’s expected impact for altruistic causes would be very challenging and expensive.[2] So instead, we designed and collected data on four metrics that we expected to be useful indicators of whether people were making changes in promising directions: “Attitudes,” e.g. views on cause prioritisation, inclination towards effective altruism. “Career plans,” e.g. study plans, internship plans, j...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Liberty in North Korea, quick cost-effectiveness estimate, published by MichaelStJules on the AI Alignment Forum. In 2019, Liberty in North Korea (LINK) claims to have rescued 222 North Koreans, spending $3,660,223 across all programs, including refugee resettlement. In 2018, it was 326 rescues, spending $3,604,423. Combining, that's 548 rescued for $7,264,646, or $13,257 per rescue. Rescue expenses alone (so excluding employee pay, other program expenses, and everything else) over both years totaled $932,456, which would come out to $1,702 per rescue. For comparison, GiveWell's recommended life-saving charities are estimated to save a life for $3000-5000 on average. EDIT (credits to Denis Drescher for pointing this out): What they do: They rescue already escaped North Koreans from China using secret routes, since if they are caught, Chinese authorities would send them back, or the women could be sold into sex trafficking or as brides. LINK doesn't help North Koreans escape in the first place. LINK claims thousands of North Koreans attempt to escape each year. They also write: It costs $3,000 to help a North Korean refugee travel from Northern China to safety in South East Asia The Changing Costs of A Rescue The cost of rescues varies on where a North Korean refugee begins their journey. The closer they are to the North Korean border when our partners find them, the greater the cost because of heightened security and increased travel time. A generous foundation funds these high-risk extractions from the border region. There are likely several ways these cost-effectiveness estimates may be off (including possibly having the wrong sign) due to indirect effects and not accounting properly for the counterfactuals, and a cost-effectiveness model should take such considerations into account. Here are some: Less cost-effective: How likely is it that these people would have succeeded anyway, on their own or with the help of another group? Their website had someone who made 4 escape attempts (Jo Eun, on this page). How much earlier does LINK move their success if they would have been caught and made further attempts? Unclear, lean more cost-effective: What are the risks or benefits to the families of rescues, and how likely are they? If someone is caught, their family may be punished, e.g. with labour camps or execution, and by rescuing them, we may prevent this. On the other hand, we may incentivize further escapes, which risk punishment for them and their families. To what extent are the families also aware of and accept these risks? (Credits to Bruce Tsai and Denis Drescher.) Less cost-effective: They only rescued 15 North Koreans in 2020 due to increased security due to COVID, and maybe we should expect it to be similar going forward. Unclear: Does this undermine reform in North Korea, by taking those disproportionately likely to push for reform? (Credits to edwardhaigh) On the other hand, LINK says that refugees send money and information back to their families in North Korea, and it's possible this could undermine the regime. (Credits to Khorton) Less cost-effective: How would North Korea respond to increasing rescues? Harsher punishments and security? Further encouraging births? Unclear, but lean less cost-effective: Where does marginal funding actually go? Would they actually rescue more, or just spend more on resettlement and other services? In what proportions? If we funded them, could we get them to spend disproportionately more on rescues? How much could this scale before further rescues became very difficult? Unclear: How are descendants affected? Escapees who are caught and sent back may be prevented from having children, or have children anyway in North Korea (this is something to check). This may extent to their families, as well. Rescued escapees seem likely ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: EA syllabi and teaching materials, published by Julia_Wise on the AI Alignment Forum. Write a Review I've been collecting a list of all the known courses taught about EA or closely related topics. Please let me know if you have others to add! AGI safety fundamentals For 2022, Richard Ngo Syllabus "Are we doomed? Confronting the end of the world" at University of Chicago Spring 2021, Daniel Holz & James A. Evans Syllabus "Ethics and the Future" at Yale Spring 2021, Shelly Kagan Syllabus "The Great Problems" at MIT Spring 2021, Kevin Esvelt Syllabus Improving Science Reading Group 2021, EA Cambridge Reading list Longtermism syllabus 2021, Joshua Teperowski Monrad Syllabus Effective Animal Advocacy Fellowship Winter 2021, EA at UCLA Syllabus and discussion guide Social Sciences & Existential Risks Reading Group Winter 2021 Reading list Global Development Fellowship Winter 2021, Stanford One for the World Syllabus "Ethics for Do-Gooders" at University of Graz Summer 2020, Dominic Roser Syllabus Cause Area Guide: Institutional Decision Making May 2020, EA Norway Guide, with reading list (focused on forecasting) Intro to Global Priorities Research for Economists Spring 2020, David Bernard and Matthias Endres Description, with link to reading list and materials Governance of AI Reading List Oxford, Spring 2020, Markus Anderljung Reading list EA course at Brown University Spring 2020, Emma Abele and Nick Whittaker, based on Harvard Arete fellowship syllabus Syllabus "Psychology of (Effective) Altruism" at University of Michigan Winter 2020, Izzy Gainsburg Syllabus "Philosophy and Philanthropy" at University of Chicago Winter 2020, Bart Schultz Syllabus Syllabus: Artificial Intelligence and China Jan. 2020, Ding, Fischer, Tse, and Byrd Reading list In-Depth Fellowship at EA Oxford Reading list "Topics in Global Priorities Research" at Oxford University Spring 2019, William MacAskill and Christian Tarsney Syllabus AI alignment reading group at MIT Fall 2019 Reading list "Normative Ethics, Effective Altruism, and the Environment" at University of Vermont Fall 2019, Mark Budolfson Syllabus Arete fellowship at MIT Fall 2018, MIT EA group Syllabus with discussion prompts "Safety and control for artificial general intelligence" at UC Berkeley Fall 2018, Andrew Critch and Stuart Russell Syllabus "Artificial Intelligence and International Security" July 2018, Remco Zwetsloot Reading list “The Psychology of Effective Altruism” at University of New Mexico Spring 2018, Geoffrey Miller Syllabus “Training Changemakers” program Spring 2018, Philanthropy Advisory Fellowship at Harvard University Program plan “The Ethics and Politics of Effective Altruism” at Stanford University Spring 2018, Ted Lechterman Syllabus “Effective Philanthropy: Ethics and Evidence” at London School of Economics 2017/2018, Luc Bovens and Stephan Chambers Summary Seminar on EA at University of Toronto Fall 2017, Jordan Thomson Summary "Effective altruism" course at University of St Andrews 2016-2017, Theron Pummer and Tim Mulgan Syllabus “How to actually change the world” session at MIT Fall 2016, Angelina Li and Daniel Ziegler Evaluation and course materials EA course at St. Catherine’s University Fall 2016, Jeff Johnson and Kristine West Syllabus EA course at University of Saint Andrews Fall 2016, Theron Pummer and Tim Mulgan Syllabus EA course at University of York Spring 2016, Richard Yetter Chappell Syllabus EA Syllabus Stefan Schubert and Pablo Stafforini This syllabus is intended for use in philosophy, political science, or general humanities programs. EA courses at UC Berkeley In spring 2015 and 2016, students at UC Berkeley have led a full-semester class on effective altruism. Organizers spring 2015: Ajeya Cotra, Oliver Habryka Organizers spring 2016: Ajeya Cotra, Rohin Shah Materials: Syllabus 2015 Syllab...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Impact investing is only a good idea in specific circumstances, published by HaukeHillebrandt on the AI Alignment Forum. This is a linkpost for/ I've recently written a report on impact investing in collaboration with John Halstead at Founders Pledge. We find that effective impact investing is very hard and, to maximize social impact, it is usually much more effective to donate. You can read the Executive Summary below. You can download the full report on the Founders Pledge research page as well as Lets-Fund.org. [Edit: 09/01: We have made some minor adjustments to the framing of our findings in the Executive Summary and Section 4.3 of this report following the publication of a piece on impact investing by Vox that mentioned this report. We believe the Vox piece took a more critical stance on impact investing than was warranted from the arguments here, and have made changes to our report to avoid misunderstanding. ] EXECUTIVE SUMMARY Impact investing – investing in, or divesting from, for-profits for the purpose of social impact – is an increasingly popular approach to doing good. It seems to offer the promise of a double bottom line: direct social impact and profits that you can keep or reinvest in other socially beneficial businesses. A donation to charity, in contrast, yields no monetary returns and can only be spent once. In this report, we discuss whether impact investing is indeed a promising approach for people who want to have social impact. Impact investors face two distinct challenges: Investors must find companies with enterprise impact – companies that make a positive difference to the world. Investors must have additionality – they need to make a difference to the performance of those companies, either through providing additional capital (known as investment impact) or through providing non-monetary support, such as advice or access to networks. For both of these challenges, it is crucial to consider the counterfactual. That is, we have to ask: what would have happened had we not invested? Will a given solar power company merely displace another near-identical solar power company? Will my capital merely displace another investor? This marks a crucial difference between investing for profit and investing for impact. When investing for profit, we do not need to consider these kinds of questions. If the solar power company I invested in is making a $100 million profit, it doesn’t matter whether an identical solar power company would have sprung up one week later if the company did not exist. And if I made a substantial profit from my investment in the company, the fact that someone else would have acquired those profits had I not done so is irrelevant. When aiming for social impact, however, these questions are fundamental. When we are deciding whether to impact invest, we must also consider the opportunity cost of impact investing. In the same way, if we want to make a profit, we wouldn’t compare the return on our investment to what we would have got if we had done nothing. Instead, we would compare our ROI to what we could have done otherwise with the money: if I chose an investment with a 3% return, but another available investment had an 8% return, then I would have made a mistake. The same is true if our aim is to have social impact. If our aim is to do the most good, there are two alternatives to impact investing: Investing to give – Investing for profit to donate later to effective charities Donating now – Donating the money to effective charities now Having social impact through donations is much more difficult than many people imagine, and it is easy to miss out on huge impact multipliers in philanthropy. However, if done carefully, the social benefits of these alternative approaches can be substantial. Reviews of our recommended high-impact char...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Interview with Jon Mallatt about invertebrate consciousness, published by Max_Carpendale on the AI Alignment Forum. Jon Mallatt is a biologist who along with his colleague Todd Feinberg have recently published some books and articles on the evolution of consciousness on the question of which animals are conscious, as well as their general position on consciousness. These include the Ancient Origins of Consciousness and Consciousness Demystified. Their books combine biology, neuroscience, and philosophy, and I would consider them to be among the leading experts on invertebrate consciousness and their publications to be among the best on the subject. I am conducting these interviews to try and advance knowledge on the question of which (if any) invertebrate animals are conscious to help with efforts to extend due moral consideration to groups of invertebrates that are conscious. For more background as to why I'm focusing on this question, see my post here. Questions: 1. In The Ancient Origins of Consciousness you wrote that you think that having multiple orders of sensory processing indicates or is evidence of consciousness. Would you mind elaborating on why you think that having multiple orders of sensory processing indicates consciousness in some way? I should start by saying that I and my colleague Todd Feinberg, like most other scientists, say consciousness is a strictly natural phenomenon produced in living organisms by neurons, and not by a fundamental or exotic mind force. We are not dualists. It is also important to state that we study only the most basic type of consciousness, called phenomenal (primary) consciousness, defined as the ability to experience (feel) anything at all. Unlike higher types of consciousness, it need not involve any reflection, higher thought, self-consciousness, nor the ability to report the feelings being felt. The difficult problem is finding how phenomenal consciousness appeared; it is less difficult to discover how the higher levels evolved from there. We see phenomenal conscious as having two main aspects: 1) building and experiencing a mapped, mental simulation of the world (and of one’s own body) from the extensive sensory information one receives; and 2) feeling affects, which are emotions and moods, and which we boil down to either positive (good) or negative (bad) feelings. Your question refers to aspect 1, building a mental image from sensory input. The answer is that if there were just one level of sensory processing --- where a sensory nerve cell (neuron) receives a stimulus and sends it directly to a motor neuron (which signals a behavioral response) --- then this would be just a reflex, and we know reflexes are not consciousness. The additional levels of neurons are needed to process the bits of sensory information, received from many different senses (seen, heard, smelled, touched), and to assemble all these into a sensory image of the world, a mapped, conscious image to guide one’s movements and behaviors in the environment. 2. One of your main doubts about the possibility of insect consciousness is a relatively small number of neurons that insects have. Would you mind fleshing out why you find this objection to be compelling? The point was that consciousness is an extremely complex neural process, so one wonders whether something as tiny as an insect brain has enough neurons to bring it about. The brains of the only other animals that met our criteria for consciousness --- all the vertebrates and the cephalopod molluscs like octopuses and squids --- have millions of neurons. However, since our Ancient Origins book came out in 2016, we put aside our doubts and accepted that insects and other arthropods are conscious. The evidence for this is that their compact brains do build mapped images of the world from many differ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Invertebrate Sentience: A Useful Empirical Resource, published by Jason Schukraft on the AI Alignment Forum. Executive Summary Rethink Priorities reviewed the scientific literature relevant to invertebrate sentience. We selected 53 features potentially indicative of the capacity for valenced experience and examined the degree to which these features are found throughout 18 representative biological taxa. These data have been compiled into an easily sortable database that will enable animal welfare organizations to better gauge the probability that (various species of) invertebrates have the capacity for valenced experience. This essay details what we’ve done, why, and the strengths and weaknesses of our approach. Project Overview This post is the second in our series on invertebrate[1] welfare. In the first post we examine some philosophical difficulties inherent in the detection of morally significant pain and pleasure in nonhumans. In the third, fourth, and fifth posts we explain in detail the features we believe to be most relevant for assessing invertebrate sentience. In the sixth, seventh, and eighth posts, we present our summary of findings, both in narrative form and as an interactive database. In forthcoming work (to be published late July), we analyze the extent to which invertebrate welfare is a promising cause area. We focus on invertebrates for two reasons: (1) We are already reasonably confident that mammals, birds, reptiles, amphibians, and most fish[2] feel morally significant pain and pleasure, and hence must be included in our moral calculations, but we are unsure if more distantly related animals warrant similar concern, and (2) The subject of invertebrate welfare, though recently gaining traction both in the scientific literature and the effective altruism community, appears neglected relative to the sheer number[3] of potentially suffering invertebrates. To develop accurate cost-benefit models that can be used to allocate resources across the animal welfare movement, we need to take the possibility of invertebrate pain and pleasure seriously. But determining whether invertebrates have the capacity to experience pain and pleasure in a morally significant way is an extraordinarily complex and difficult undertaking. There is tremendous uncertainty at virtually every level at which one might investigate the matter. We don’t expect to conclude with high confidence that invertebrates do or do not experience morally significant pain and pleasure. Such an outcome is too ambitious. Rather, our goal is to clearly map out the problem so that we can begin to systematically reduce key uncertainties in a cost-effective manner. One tractable way to improve our credences with respect to invertebrate welfare is to create a comprehensive collection and analysis of the extant scientific studies relevant to the subject. While some scientific studies directly address the issue of animal pain, the vast majority of studies that are relevant at all to invertebrate welfare are relevant only tangentially. For example, studies on cockroach navigation and place memory don’t directly address the issue of invertebrate welfare. Nonetheless, the ability to accomplish certain navigational feats might be decent evidence that creatures with that ability are conscious, which is itself a necessary condition on experiencing pain and pleasure. However, a search for “invertebrate welfare” on Google Scholar doesn’t deliver any studies on cockroach navigation. Gathering all the relevant scientific literature in one place is thus a nontrivial and, to-date, unaccomplished task. Rethink Priorities has spent the last ten months completing just such a task. We have analyzed the degree to which more than 50 features potentially indicative of phenomenal consciousness[4] are found throughout 18 r...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Effective Altruism Foundation: Plans for 2020, published by Jonas Vollmer on the AI Alignment Forum. Summary Our mission. We are building a global community of researchers and professionals working on reducing risks of astronomical suffering (s-risks). Our plans for 2020 Research. We aim to investigate the questions listed in our research agenda titled “Cooperation, Conflict, and Transformative Artificial Intelligence” and other areas. Research community. We plan to host research workshops, make grants to support work relevant to our priorities, present our work to other research groups, and advise people who are interested in reducing s-risks in their careers and research priorities. Rebranding. We plan to rebrand from “Effective Altruism Foundation” to a name that better fits our new strategy. 2019 review Research. In 2019, we mainly worked on s-risks as a result of conflicts involving advanced AI systems. Research workshops. We ran research workshops on s-risks from AI in Berlin, the San Francisco Bay Area, and near London. The participants gave positive feedback. Location. We moved to London (Primrose Hill) to attract and retain staff better and collaborate with other researchers in London and Oxford. Fundraising target. We aim to raise $185,000 (stretch goal: $700,000). If you prioritize reducing s-risks, there is a strong case for supporting us. Make a donation. About us We are building a global community of researchers and professionals working on reducing risks of astronomical suffering (s-risks). (Read more about us and our values.) We are a London-based nonprofit. Previously, we were located in Switzerland (Basel) and Germany (Berlin). Before shifting our focus to s-risks from artificial intelligence (AI), we implemented projects in global health and development, farm animal welfare, wild animal welfare, and effective altruism (EA) community building and fundraising. Background on our strategy For an overview of our strategic thinking, see the following pieces: Gloor: Cause prioritization for downside-focused value systems Althaus & Gloor: Reducing Risks of Astronomical Suffering: A Neglected Priority Gloor: Altruists Should Prioritize Artificial Intelligence (somewhat dated) The best work on reducing s-risks cuts across a broad range of academic disciplines and interventions. Our recent research agenda, for instance, draws from computer science, economics, political science, and philosophy. That means (a) we must work in many different disciplines and (b) find people who can bridge disciplinary boundaries. The longtermism community brings together people with diverse backgrounds who understand our prioritization and share it to some extent. For this reason, we focus on making reducing s-risks a well-established priority in that community. Strategic goals Inspired by GiveWell’s self-evaluations, we are tracking our progress with a set of deliberately vague performance questions: Building long-term capacity. Have we made progress towards becoming a research group that will have an outsized impact on the research landscape and relevant actors shaping the future? Research progress. Has our work resulted in research progress that helps reduce s-risks (both in-house and elsewhere)? Research dissemination. Have we communicated our research to our target audience, and has the target audience engaged with our ideas? Organizational health. Are we a healthy organization with an effective board, staff in appropriate roles, appropriate evaluation of our work, reliable policies and procedures, adequate financial reserves and reporting, and so forth? Our team will answer these questions at the end of 2020. Plans for 2020 Research Note: We currently carry out some of our research as part of the Foundational Research Institute (FRI). We plan to consolidate our activities r...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Launching Utilitarianism.net: An Introductory Online Textbook on Utilitarianism, published by Darius_M on the AI Alignment Forum. We are excited to announce the launch of Utilitarianism.net, an introductory online textbook on utilitarianism, co-created by William MacAskill, James Aung and me over the past year. The website aims to provide a concise, accessible and engaging introduction to modern utilitarianism, functioning as an online textbook targeted at the undergraduate level . We hope that over time this will become the main educational resource for students and anyone else who wants to learn about utilitarianism online. The content of the website aims to be understandable to a broad audience, avoiding philosophical jargon where possible and providing definitions where necessary. Please note that the website is still in beta. We plan to produce an improved and more comprehensive version of this website by September 2020. We would love to hear your feedback and suggestions on what we could change about the website or add to it. The website currently has articles on the following topics and we aim to add further content in the future: Introduction to Utilitarianism Principles and Types of Utilitarianism Utilitarianism and Practical Ethics Objections to Utilitarianism and Responses Acting on Utilitarianism Utilitarian Thinkers Resources and Further Reading We are particularly grateful for the help of the following people with reviewing, writing, editing or otherwise supporting the creation of Utilitarianism.net: Lucy Hampton, Stefan Schubert, Pablo Stafforini, Laura Pomarius, John Halstead, Tom Adamczewski, Jonas Vollmer, Aron Vallinder, Ben Pace, Alex Holness-Tofts, Huw Thomas, Aidan Goth, Chi Nguyen, Eli Nathan, Nadia Mir-Montazeri and Ivy Mazzola. The following is a partial reproduction of the Introduction to Utilitarianism article from Utilitarianism.net. Please note that it does not include the footnotes, further resources, and the sections on Arguments in Favor of Utilitarianism and Objections to Utilitarianism. If you are interested in the full version of the article, please read it on the website. Introduction to Utilitarianism "The utilitarian doctrine is, that happiness is desirable, and the only thing desirable, as an end; all other things being only desirable as means to that end." - John Stuart Mill Utilitarianism was developed to answer the question of which actions are right and wrong, and why. Its core idea is that we ought to act to improve the wellbeing of everyone by as much as possible. Compared to other ethical theories, it is unusually demanding and may require us to make substantial changes to how we lead our lives. Perhaps more so than any other ethical theory, it has caused a fierce philosophical debate between its proponents and critics. Why Do We Need Moral Theories? When we make moral judgments in everyday life, we often rely on our intuition. If you ask yourself whether or not it is wrong to eat meat, or to lie to a friend, or to buy sweatshop goods, you probably have a strong gut moral view on the topic. But there are problems with relying merely on our moral intuition. Historically, people held beliefs we now consider morally horrific. In Western societies, it was once firmly believed to be intuitively obvious that people of color and women have fewer rights than white men; that homosexuality is wrong; and that it was permissible to own slaves. We now see these moral intuitions as badly misguided. This historical track record gives us reason to be concerned that we, in the modern era, may also be unknowingly guilty of serious, large-scale wrongdoing. It would be a very lucky coincidence if the present generation were the first generation whose intuitions were perfectly morally correct. Also, people have conflicting moral intuitions ab...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Pangea: The Worst of Times, published by John G. Halstead on the AI Alignment Forum. 260 million years ago, our planet had an unfamiliar geography. Nearly all of the landmasses were united into a single giant continent known as ‘Pangea’ that stretched from pole to pole. On the other side of the world you would find a vast ocean, even larger than the present Pacific, called Panthalassa. The Pangean era lasted 160 million years, and 80 million of these were extremely inhospitable to animal and plant life, coinciding with two mass extinctions and four other major extinction events. This is why Paul Wignall, a Professor of Palaeoenvironments at Leeds has called the Pangean era ‘The Worst of Times’. Understanding why the Pangean era was so miserable helps inform several questions of interest to those studying existential risk. ● What level of natural existential risk do we face now, and have we faced in the past? ● What is the threat of super-volcanic eruptions? ● How much existential risk does anthropogenic climate change pose? 1. Background There have been five mass extinctions so far. The Ordovician–Silurian (450-440 million years ago) and the Late Devonian (375-360 million years ago) each preceded the age of Pangea. The Pangean period coincided with the two worst mass extinctions, the huge Permian-Triassic mass extinction (252 million years ago) and the Triassic-Jurassic extinction event (201 million years ago).[1] The last crisis, the Cretaceous–Paleogene event (65 million years ago), accounted for the dinosaurs and occurred once continental drift had done its business and Pangea had broken apart. With the exception of the end Cretaceous extinction, since the breakup of Pangea, it has been relatively plain sailing for Earth’s various species, until humans started killing off other species themselves. [2] As one can see on this diagram, in the 145 million years since the start of the Cretaceous, the average rate of global genus extinctions from extinction events has been around 5% and never passed 15%, except for the death of the dinosaurs. But in the 80 million years from the first Pangean extinction event, the Capitanian, to the early Jurassic extinction events, the average rate of global genus extinctions in extinction events is more around 15-20%, and 12 events produced global genus extinction rates in excess of 15%. Below is a useful chart from Wikipedia on the Phanerozoic, which shows the long-term trend in biodiversity as well as the impact of different extinction events. Again, this highlights how unusually bad things were in the Pangean era - specifically the 80 million years after the Capitanian extinction event 260 million years ago. But it also highlights how good things have been since the end of the Pangean era and the start of the Cretaceous (145 million years ago). 2. What caused such ecological trauma in Pangea? Huge volcanic eruptions were implicated in all of the six major extinction events in the Pangean era. One can see this in the first diagram above, where the volcanic eruptions are shown at the top and the line traces down to corresponding extinction events at the bottom. Every Pangean extinction event coincided with the outpouring of enormous fields of lava that, once cooled, produced what geologists call Large Igneous Provinces (LIPs).[3] To put these LIPs in context, the eruption of Mount Pinatubo in 1991 produced 10 cubic km of magma, which caused the Earth to cool by about half a degree. The eruption of the Siberian Traps which appeared to cause the end Permian extinction produced 3 million cubic km of magma. You can see the volume of magma for all major LIPs at the top of the first diagram above. These volcanic eruptions emitted sulphur dioxide, carbon dioxide and halogen gases, each of which could potentially have an effect on the ecosys...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is:Critical Review of 'The Precipice': A Reassessment of the Risks of AI and Pandemics, published by Fods12 on the AI Alignment Forum. Write a Review Introduction In this essay I will present a critical response to Toby Ord’s recent book The Precipice (page numbers refer to the soft cover version of this book). Rather than attempting to address all of the many issues discussed by Ord, I will focus on what I consider to be one of the most critical claims of the book. Namely, Ord claims that the present century is a time of unprecedented existential risk, that “we stand at a crucial moment in the history of our species” (p. 3), a situation which is “unsustainable” (p. 4). Such views are encapsulated in Ord’s estimate of the probability of an existential catastrophe over the next century, which he places at one in six. Of this roughly seventeen percent chance, he attributes roughly ten percentage points to the risks posed by unaligned artificial intelligence, and another three percentage points to the risks posed by engineered pandemics, with most of the rest of the risk is due to unforeseen and ‘other’ anthropogenic risks (p. 167). In this essay I will focus on the two major sources of risk identified by Ord, artificial intelligence and engineered pandemics. I will consider the analysis presented by Ord, and argue that by neglecting several critical considerations, Ord dramatically overestimates the magnitude of the risks from these two sources. This short essay is insufficient to provide a full justification for all of my views about these risks. Instead, my aim is to highlight some of what I believe to be the major flaws and omissions of Ord’s account, and also to outline some of the key considerations that I believe support a significantly lower assessment of the risks. Why probability estimates matter Before analysing the details of Ord’s claims about the risks of engineered pandemics and unaligned artificial intelligence, I will first explain why I think it is important to establish as accurate as possible estimates of the magnitude of these existential risks. After all, it could be argued that even if the risks are significantly less than those presented by Ord, nevertheless the risks are still far higher than we would like them to be, and causes such as unaligned AI and engineered pandemics are clearly neglected and require much more attention than they currently receive. As such, does it really matter what precise probabilities we assign to these risks? I believe it does matter, for a number of reasons. First, Ord’s core thesis in his book is that humanity faces a ‘precipice’, a relatively short period of time with uniquely high and unsustainable levels of existential risk. To substantiate this claim, Ord needs to show not just that existential risks are high enough to warrant our attention, but that existential risk is much higher now than in the past, and that the risks are high enough to represent a ‘precipice’ at which humanity stands at the edge. Ord articulates this in the following passage: “If I’m even roughly right about their (the risks’) scale, then we cannot survive many centuries with risk like this. It is an unsustainable level of risk. Thus, one way or another, this period is unlikely to last more than a small number of centuries. Either humanity takes control of its destiny and reduces the risk to a sustainable level, or we destroy ourselves.” (p. 31) Critical here is Ord’s linkage of the scale of the risk with our inability to survive many centuries of this scale of risk. He goes on to argue that this is what leads to the notion of a precipice: This comparatively brief period is a unique challenge in the history of our species... Historians of the future will name this time, and schoolchildren will study it. But I think we need a name now. I call i...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Crucial questions for longtermists, published by MichaelA on the AI Alignment Forum. This post was written for Convergence Analysis. It introduces a collection of “crucial questions for longtermists”: important questions about the best strategies for improving the long-term future. This collection is intended to serve as an aide to thought and communication, a kind of research agenda, and a kind of structured reading list. Introduction The last decade saw substantial growth in the amount of attention, talent, and funding flowing towards existential risk reduction and longtermism. There are many different strategies, risks, organisations, etc. to which these resources could flow. How can we direct these resources in the best way? Why were these resources directed as they were? Are people able to understand and critique the beliefs underlying various views - including their own - regarding how best to put longtermism into practice? Relatedly, the last decade also saw substantial growth in the amount of research and thought on issues important to longtermist strategies. But this is scattered across a wide array of articles, blogs, books, podcasts, videos, etc. Additionally, these pieces of research and thought often use different terms for similar things, or don’t clearly highlight how particular beliefs, arguments, and questions fit into various bigger pictures. This can make it harder to get up to speed with, form independent views on, and collaboratively sculpt the vast landscape of longtermist research and strategy. To help address these issues, this post collects, organises, highlights connections between, and links to sources relevant to a large set of the “crucial questions” for longtermists.[1] These are questions whose answers might be “crucial considerations” - that is, considerations which are “likely to cause a major shift of our view of interventions or areas”. We collect these questions into topics, and then progressively then progressively break “top-level questions” down into the lower-level “sub-questions” that feed into them. For example, the topic “Optimal timing of work and donations” includes the top-level question “How will ‘leverage over the future” change over time?’, which is broken down into (among other things) “How will the neglectedness of longtermist causes change over time?” We also link to Google docs containing many relevant links and notes. What kind of questions are we including? The post A case for strategy research visualised the “research spine of effective altruism” as follows: This post can be seen as collecting questions relevant to the “strategy” level. One could imagine a version of this post that “zooms out” to discuss crucial questions on the “values” level, or questions about cause prioritisation as a whole. This might involve more emphasis on questions about, for example, population ethics, the moral status of nonhuman animals, and the effectiveness of currently available global health interventions. But here we instead (a) mostly set questions about morality aside, and (b) take longtermism as a starting assumption.[2] One could also imagine a version of this post that “zooms in” on one specific topic we provide only a high-level view of, and that discusses that in more detail than we do. This could be considered to be work on “tactics”, or on “strategy” within some narrower domain. An example of something like that is the post Clarifying some key hypotheses in AI alignment. That sort of work is highly valuable, and we’ll provide many links to such work. But the scope of this post itself will be restricted to the relatively high-level questions, to keep the post manageable and avoid readers (or us) losing sight of the forest for the trees.[3] Finally, we’re mostly focused on: Questions about which different longtermists hav...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: The Folly of "EAs Should, published by Davidmanheim on the AI Alignment Forum. I've seen and heard many discussions about what EAs should do. William McAskill has ventured a definition of Effective Altruism, and I think it is instructive. Will notes that "Effective altruism consists of two projects, rather than a set of normative claims." One consequence of this is that if there are no normative claims, any supposition about what ought to happen based on EA ideas is invalid. This is a technical point, and one which might seem irrelevant to practical concerns, but I think there are some pernicious consequences of some of the normative claims that get made. So I think we should discuss why "Effective Altruism" implying that there are specific and clear preferable options for "Effective Altruists" is often harmful. Will's careful definition avoids that harm, and I think should be taken seriously in that regard. Mistaken Assertions Claiming something normative given moral uncertainty, i.e. that we may be incorrect, is hard to justify. There are approaches to moral uncertainty that allow a resolution, but if EAs should cooperate, I argue that it may be useful, regardless of normative goals, to avoid normative statements that exclude some viewpoints. This is not because they cannot be justified, but because they can be strategic mistakes. Specifically, we should be wary of making the project exclusive rather than inclusive. EA is Young, Small, and Weird EA is very young. Some find this an obvious situation - aren't most radical movements young? Are most people willing to embrace new ideas young? - but I disagree. Many of the most popular movements sweep across age groups. Environmentalism, Gay rights, and Animal welfare all skewed young, but were increasingly adopted by those of all ages. In part, that is because they allow people to embrace them. There is no widespread belief in environmentalism that doctors have wasted their careers focusing on saving lives at the retail level rather than saving the world. There is little reason that anyone would hesitate the raise the pride flag because they are not doing enough for the movement. But effective altruism is often perceived differently. To the extent that EAs embrace a single vision (a very limited extent, to be clear,) they often exclude those who differ on details, intentionally or not. "Failing" to embrace longtermism, or ("worse"?) disagreeing about impartiality, is enough to start arguments. Is it any wonder that we have so few people with well-established lives and worldviews willing to consider our project, "the use of evidence and careful reasoning to work out how to maximize the good with a given unit of resources"? Nothing about the project is exclusive - it is the community that creates exclusion. And it would be a shame for people to feel useless and excluded. Of course, allowing more diversity will allow the ideas of effective altruism to spread - but it will also reduce the tension which seems to exist around disagreeing with the orthodoxy. People debate whether EA should be large and welcoming or small and weird. But as John Maxwell suggests, large and weird might be a fine compromise. We see this - the LGBT movement, now widely embraced, famously suggests that people should "let your freak flag fly," but the phrase dates back to the 60s counterculture. Neither stayed small and weird, and despite each leading to a culture war, each seems to have been, at least in retrospect, very widely embraced. And neither needed to develop a single coherent worldview to get there; no-one can argue that LGBT groups all agree about many issues. And despite the fragmentation and arguments, the key messages came through to the broader public just fine. EA is Already Fragmented It may come as a surprise to readers of the forum...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: The Duplicator: Instant Cloning Would Make the World Economy Explode, published by Holden Karnofsky on the AI Alignment Forum. Audio link This is the second post in a series explaining my view that we could be in the most important century of all time. Here's the roadmap for this series. The first piece in this series discusses our unusual era, which could be very close to the transition between an Earth-bound civilization and a stable galaxy-wide one. Future pieces will discuss how "digital people" - and/or advanced AI - could be key for this transition. This piece explores a particularly important dynamic that could make either digital people or advanced AI lead to explosive productivity. I explore the simple question of how the world would change if people could be "copied." I argue that this could lead to unprecedented economic growth and productivity. Later, I will describe how digital people or advanced AI could similarly cause a growth/productivity explosion. When some people imagine the future, they picture the kind of thing you see in sci-fi films. But these sci-fi futures seem very tame, compared to the future I expect. In sci-fi, the future is different mostly via: Shiny buildings, gadgets and holograms. Robots doing many of the things humans do today. Advanced medicine. Souped-up transportation, from hoverboards to flying cars to space travel and teleportation. But fundamentally, there are the same kinds of people we see today, with the same kinds of personalities, goals, relationships and concerns. The future I picture is enormously bigger, faster, weirder, and either much much better or much much worse compared to today. It's also potentially a lot sooner than sci-fi futures:[1] I think particular, achievable-seeming technologies could get us there quickly. Such technologies could include "digital people" or particular forms of advanced AI - each of which I'll discuss in a future piece. For now, I want to focus on just one aspect of what these sorts of technology would allow: the ability to make instant copies of people (or of entities with similar capabilities). Economic theory - and history - suggest that this ability, alone, could lead to unprecedented (in history or in sci-fi movies) levels of economic growth and productivity. This is via a self-reinforcing feedback loop in which innovation leads to more productivity, which leads to more "copies" of people, who in turn create more innovation and further increase productivity, which in turn ... In this post, instead of directly discussing digital people or advanced AI, I'm going to keep things relatively simple and discuss a different hypothetical technology: the Duplicator from Calvin & Hobbes, which simply copies people. How the Duplicator works The Duplicator is portrayed in this series of comics. Its key feature is making an instant copy of a person: Calvin walks in, and two identical Calvins walk out. This is importantly different from the usual (and more realistic) version of "cloning," in which a person's clone has the same DNA but has to start off as a baby and take years to become an adult.[2] To flesh this out a bit, I'll assume that: The Duplicator allows any person to quickly make a copy of themselves, which starts from the same condition and mental state or from an earlier state (for example, I could make a replica of "Holden as of January 1, 2015").[3] Unlike in many sci-fi films, the copies function normally (they aren't evil or soulless or decaying or anything). It can be used to make an unlimited number of copies, though each has some noticeable cost of production (they aren't free).[4] Productivity impacts It seems that much of today's economy revolves around trying to make the most of "scarce human capital." That is: Some people are "scarce" or "in demand." Extreme examples include...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: You should write about your job, published by Aaron Gertler on the AI Alignment Forum. If you have a job, you are one of the world's foremost experts on your job — at least within the EA community, which is not large. Jobs are a useful thing to know about. We spend more time on them than anything else, and most of our impact comes from jobs + their outcomes (e.g. salary). Thus, I think people should write more posts that talk about: How they got their jobs What they learned in the process of getting hired What it's like to work at their job, day-to-day If you have a job, there's a chance that writing about it is one of the best ways you could contribute to the Forum. And you can do it without reading anything, or having any opinions whatsoever! Jobs are mysterious... The job market, both inside and outside of EA, feels weird and mysterious and intimidating to a lot of people: Almost everyone gets rejected from most jobs they apply for. Almost no jobs provide feedback to applicants. Almost all job applications go toward the small fraction of jobs with the most applicants, which creates the impression that the average job is more competitive than it actually is (see many comments on this post). Almost all jobs are more about "content" than "topic": your experience with them depends on what you actually do with your time, rather than what the job is "about". ...but they don't have to be Almost everyone gets a job — and within the EA community, almost everyone gets a job with some kind of relevant upside (good money, skills training, networking, etc.) Even if few people get their first-choice job, they tend to end up doing something that someone else in EA might also want to do. People who get a job know a lot about the application process for that job, and what that job entails — more than anyone else who hasn't had exactly that job. "Job posts" can help Just reading about how something happens, in detail, can make it seem less mysterious and intimidating — like the hiring process for a given job It's also good to hear about the journey involved in finding a job, and the ways in which it isn't always smooth or flawless (even people who get jobs typically get lots of rejections, too) If someone wants to do the same kind of job you do, writing a job post helps them in multiple ways; they can read it, and they can ask you questions! Your job doesn't have to be with an EA-aligned organization. This kind of resource is hard to find even in bigger fields, and many existing examples have problems (written by someone who wants to sell you something, written by people who won't respond to questions, ten years out of date, etc.) Jobs outside EA that will be relevant to many Forum readers might include: PhD student Programmer (though this might be the job with the best existing "literature") Academic researcher Journalist Biologist Anything that involves working with public policy If you're not sure whether people want to know about your job, leave a comment here to find out What a job post might look like Here's my suggestion for a minimum viable job post. It's fine to start minimal, because people who want to know more can leave a comment! Or message you with a question! Background: What were some past jobs or other experiences that helped you prepare for getting your current job? Which ones would you especially recommend? Bonus: What other, irrelevant stuff did you "waste time" on? This helps readers (a) avoid doing irrelevant things, and (b) understand that it's possible to get a job even without a perfect, focused resume. Application process: What was it like to apply to your job? Were there parts of the process you wish you'd prepared for differently? Bonus: What other jobs did you apply for? Which ones rejected you? How far did you get, and how much time did that take? This...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Persistence - A critical review [ABRIDGED], published by Jsevillamol on the AI Alignment Forum. [this is a link post to the preprint Persistence - a Critical Review, by Jaime Sevilla] EDIT: For a more informal and less dry piece read my takeaways here. IN SHORT: I review, replicate and extend the analysis from seven econometric papers studying how events that happened to and values held by our ancestors affect their descendants several generations afterwards (intergenerational persistence). I argue that together the papers provide moderate evidence of the existence of long term causal effects mediated by parentage. KEYWORDS: persistence, cultural persistence, economic history, multiple hypothesis testing, post design power analysis, spatial autocorrelation bias, causality, natural experiments, instrumental variables. Intergenerational persistence is an important topic for Effective Altruism, because it can help us understand how our actions today can affect many generations after. I undertook this research to help us shed light on whether cultural interventions (like increasing the degree at which present people value truth and cooperation) can be an effective way of affecting the long-term future. The papers I review are: The long term effects of Africa’s slave trades (Nunn, 2008) The slave trade and the origins of mistrust in Africa (Nunn & Wantchekon, 2011) On the Origins of Gender Roles: Women and the Plough (Alesina et al., 2013) The Church, intensive kinship, and global psychological variation (Schulz et al., 2019) Persecution perpetuated: The Medieval Origins of Anti-Semitic Nazi Violence (Voigtländer & Voth, 2012) Trade, Institutions, and Ethnic Tolerance: Evidence from South Asia (Jha, 2013) Long-term persistence (Guiso et al., 2016) HIGHLIGHTS: I discuss a gold standard for cultural persistence studies, covering how to (1) identify robust long term correlations via regression studies under different sets of controls, (2) identify causal effects via natural experiments and (3) identify whether culture is a significant mediator via children-of-immigrant studies. More I find that many of the papers manage to find statistically significant results. A naive aggregation of the estimated correlation effect sizes suggests that future correlational studies might find effects of around β ≈ 0.28 (0.13) standard deviations per standard deviation of exposure variation. That is, future studies in similar topics should expect to find that one standard deviation of variation on an event would predict ~28% of variation in long term outcomes. However it is hard to rule out spurious correlations due to issues such as spatial autocorrelation or outliers. More Some of the papers attempt to study causation via natural experiments. While a couple of such papers arguably succeed in identifying a causal effect, we cannot discard that subsequent robustness checks will cast doubt on the results. A naive aggregation of the estimated correlation effect sizes suggests that future causal studies might find effects of around β ≈ 0.11 (0.02) standard deviations per standard deviation of exposure variation. That is, future studies in similar topics should expect to find that one standard deviation of difference on an event would cause ~11% of variation in long term outcomes. More I find that children-of-immigrant analysis suggests the possibility of long term persistence of variation mediated by parentage. The authors of the papers tend to explain this persistence in terms of cultural variation, relying mostly on historical accounts as evidence. More Whether long term persistence of variation usually stays constant, wanes or increases with time is an open question. Studying better these dynamics of persistence would be critical to understand the very long-term impact of cultural interventio...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Effective Altruism Stipend: A Short Experiment by EA Estonia, published by Risto_Uuk on the AI Alignment Forum. Summary In addition to other priorities at Effective Altruism Estonia, we want to cooperate with and support EA groups in other countries. As part of that, we have recently been experimenting with an effective altruism stipend. We offered a stipend of 350 euros to at least 18-year-olds to read, translate, and discuss effective altruism related articles for two months. 10 people applied for our stipend and we selected five to proceed with. Based on our current understanding, all five people who participated in the stipend want to spend time with aspiring effective altruists. We expect 2-3 people to take significant education and career-related actions from the perspective of effective altruism in the near future, but this is yet to be seen. In addition to reading and discussing articles we chose for the stipend receivers, they, for example, started reading EA-related books, taking an EA course, wrote an essay for university, started preparing for an EA presentation in school, met with other local EAs, and helped to organize our outreach event. In this post, I will give an overview of our effective altruism stipend, including how we tried to reach our target audience, what our application process was like, what resources stipend receivers used for learning, what our stipend process was like, and what the costs and results of our experiment were. Introduction One of our biggest priority at EA Estonia is to find, motivate, educate, and engage most promising people to sustain and grow the effective altruism community in Estonia. Even larger EA groups suffer from what could be called brain drain, but that is perhaps even more of an issue for small Nordic countries like Estonia. We don’t want the community to stop functioning if one or a few motivated people leave for potentially more impactful roles abroad. That said, another priority we have is to find promising people who could get into effective altruism jobs in the near future (e.g. within one year). We also focus on people who are earlier in their careers such as first or second year undergraduate students. They probably are not ready for EA jobs in the next years, but could be able to contribute longer-term. With the former, our main job probably is to provide these people with specific options, motivate them to take action on these, and provide them with advanced effective altruism related information. With the latter, our main job probably is to provide resources, learning projects, connections, and introductory career advice among other things. We have a lot of work to do in areas mentioned above, but our third priority is to benefit the larger EA community. We want to cooperate with other EA groups and support each other as much as we can. For example, we’ve been doing coworking sessions and check-ins with some groups during the last few months. In addition, we want to run experiments and try out things so that other groups could learn from our tests and mistakes. We’ve been experimenting with an EA stipend and recently started an NGO impact assessment project. EA Helsinki’s organizer is participating in that project explicitly with the idea that he can learn from our mistakes and implement an improved version with Finns. In this post, I will give an overview of our effective altruism stipend, including how we tried to reach our target audience, what our application process was like, what resources stipend receivers used for learning, what our stipend process was like, and what the costs and results of our experiment were. Advertising the stipend In order to find people interested in learning about effective altruism via translating and discussing articles, we tried to reach out to those people through ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Impact Report for Effective Altruism Coaching, published by lynettebye on the AI Alignment Forum. This report summarizes the impact evaluation for EA Coaching’s first year and a half from its founding in October 2017 until May 2019. It’s supplemented by a longer document that includes the appendixes and footnotes. Executive Summary What Does EA Coaching Do? EA Coaching helps people working on the most pressing problems get more done. As of May 2019, I have had 800+ sessions with 100+ clients. I work with professionals who already accomplish a lot -- consultants, professors, software engineers, managers, researchers -- to pinpoint their bottlenecks and help them solve the biggest problems holding them back from accomplishing more. Together, we clarify their goals, implement more effective strategies, and increase focused work time on their top priorities. Coaching typically consists of four to twelve 50-minute calls. Key Takeaways Most of my work is with clients who are likely to contribute to top cause areas, since marginal improvements in productivity for this group may have a disproportionately large impact on the world. Half of my current clients are at FHI, Open Phil, CEA, MIRI, DeepMind, the Forethought Foundation, and ACE. I expect productivity coaching to have an impact by improving prioritization and increasing focused work. Clients report an average of 16 extra productive hours a month, and it’s not uncommon for them to claim the coaching doubled their output via prioritization changes. Clients think coaching is useful, as evidenced by client surveys, impact case studies, and revealed preferences. These metrics support the conclusion that the coaching is valuable as implemented, and not just in theory. However, it seems likely these metrics imprecisely correlate with objective output, the ultimate goal, due to biases in self-report and uncertainty about counterfactual impact. I built a rough model quantifying the impact for a cost-benefit comparison, which suggests that the benefit from coaching is about twice the opportunity cost. My calculations indicate clients reported 20% more benefit on average per session in the first half of 2019 compared to 2018 (see Appendix B), and I think there’s still significant room for improvement. Why Lynette? I’ve been involved in Effective Altruism since 2014; I interned at GiveWell, started the Careers Chair role for Harvard College Effective Altruism, and started an EA Fellowship with Penn Effective Altruism. After graduating from Harvard University with a degree in psychology, I researched self-control under Angela Duckworth at the University of Pennsylvania. I’m also trained in Person-Centered Therapy (non-directional, non-judgmental active listening) with the peer counseling group Room 13, and I’m a mentor for the Center for Applied Rationality (CFAR). I wanted to do more direct work after leaving the Duckworth Lab, and 80,000 Hours suggested I try coaching to help EAs level up. So I used my knowledge of psychology and counseling to start EA Coaching. Confidentiality Unfortunately, many details can’t be shared publicly due to confidentiality. If you’re considering donating, I can share more details if you email lynettebye at gmail.com. Who Do I Work With? I work with people I think can contribute toward important cause areas, primarily those identified on 80,000 Hours’ global problems page. Most of my expected impact comes from working with this group, since marginal improvements in their productivity may have a disproportionately large impact on the world. Half of my current clients (a third of all clients I’ve worked with) are at FHI, Open Phil, CEA, MIRI, DeepMind, the Forethought Foundation, and ACE. Approximately half of my current clients are working on X-risk areas, primarily artificial intelligence safety and ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Cause X Guide, published by Joey on the AI Alignment Forum. One of the factors that makes the effective altruism movement different from so many others is that its members are unified by the broad question “How can I do the most good” instead of by specific solutions, such as “reduce climate change.” One of the most important questions EAs need to consider is what cause area presents the highest impact for their work. There are four established cause areas in effective altruism: global poverty, factory-farmed animals, artificial intelligence existential risk, and EA meta. However, there are dozens of other cause areas that some EAs consider promising. The concept behind a “cause X” is that there could be a cause neglected by the EA community but that is as important, or more important, to work on than the four currently established EA cause areas. Finding a new cause X should be one of the biggest goals of the EA movement and one of the largest opportunities for an individual EA to achieve counterfactual impact. One example of many of cause X’s posts having an impact is that some of these posts have influenced Charity Entrepreneurship’s focus on mental health. The Cause X discussion has also influenced one of the largest foundations in the world, Good Ventures. This guide, however, aims to compile the most useful content for evaluating new possible cause Xs and compare them to the currently established top cause areas. Some of the content is old, and some of it does not perfectly address its question. However, these were the best sources I could find to debate and explain the issues. This guide is aimed at an intermediate EA audience who already has a solid understanding of EA ideas. Organization The guide is broken down into three sections. The introduction aims to explain the concepts needed to compare cause areas such as “Cause X,” “How a new cause area might be introduced to the EA community,” “Current methods used to split resources between causes,” and “Concerns with some of those methodologies.” The second section is focused on comparing top causes and reviewing some of the key issues that divide current supporters of the big four cause areas. The final section aims to present several possible candidates for cause X as new areas worth considering. It is only a small sample of the full list of causes presented and considered in the EA movement, but they were selected to represent the areas (other than the big four) that many EAs would consider promising. I used three different methods to devise a list of 15 cause areas that might be considered promising candidates for cause X, selecting five causes per method. Method 1: Cause areas among the top ten listed on the EA survey Method 2: Cause areas endorsed by two or more major EA organizations Method 3: Cause profiles or pitches with 50 or more upvotes on the EA Forum Goal This guide aims to be a resource wherein cause Xs can be noticed, read about, and more deeply considered. There are hundreds of ways to make the world a better place. Given the EA movement’s relative youth and frequently unsystematic way of reviewing cause areas, there is ample room for more consideration and research. The goal of the guide is for more people to consider a wider range of cause areas so we, as a movement, have a better chance of finding new and impactful ways to do good. Cause X guide content Introduction -Four focus areas of EA -EA cause selection -World view diversification -Cause X -What if you’re working on the wrong cause? -EA representativeness -How to get a cause into EA Comparing top causes -Animals > Humans -Humans > Animals -Long-term future > Near-term future -Near-term future > Long-term future -Meta > Direct -Direct > Meta New causes one could consider. -Mental health -Climate change -Nuclear war -Rationality -Biosec...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: EA Philippines' Strong Progress and Learnings in 2019, published by BrianTan on the AI Alignment Forum. Hi, EAs! I’m Brian Tan, co-founder of Effective Altruism Philippines. I’m writing this post to share the great progress we’ve made in starting and growing the EA Philippines community in our first full year in 2019. We’ve learned a lot of things along the way, and we’d like to share what worked and what hasn’t for us here. How EA Philippines Started EA Philippines was first started by Kate Lupango in September 2018. Through help from LEAN and Wanyi Zeng (of EA Singapore), she was able to connect with other EA community builders in other countries and get resources on how to start a local community. She created a Facebook page for EA Philippines, and she posted on a Facebook volunteer group looking for volunteers to join the EA Philippines community. Jeffrey Escobal reached out to her to express interest after seeing that post. Kate also posted looking for mentors in the EA Group Organizers Facebook group. David Nash (of EA London) connected Kate with Tanya Quijano, a Filipina who had previously attended an EA London event. Finally, I found the page on Facebook a few weeks after Kate made it, and decided to reach out. The four of us met for the first time in November 2018, and decided to co-found the group and start growing the community. From left to right: Kate, Tanya, Jeffrey, and I (Brian) When we started, we had three main goals: 1. To increase awareness about EA in Manila 2. To build a friendly community for people interested in EA 3. To get Filipinos to increase their involvement in or donations to EA’s top cause areas We’ve mostly been successful at the first two goals, but we aren’t satisfied with our progress on the third. We'll talk more about that towards the end of the post. Key Outcomes in 2019 (our 1st year) 1. We’ve now identified 11 contributors and 7 participants in our local community (including us four core team members). We classified them based on CEA's Concentric Circles Model and our evaluation of where they fit in the funnel. 2. Around May 2019, we successfully applied for a general group funding grant from CEA, which allowed us to fund our operations from May to December 2019. Later, we successfully applied for a grant that covers January to December 2020. 3. In 2019, we held a total of 14 events - usually doing one per month. We now average 20 attendees per event, and we get an average of four “repeat” attendees per event (not including us co-founders). 4. We've been able to partner with the local offices of EA-recommended organizations such as Oxfam, Innovations for Poverty Action, and IDInsight, and have representatives from their orgs speak and attend our events. 5. We've also met or had calls with members from various EA communities, such as EA Singapore, Toronto, Montreal, Norway, and London, and with members of EA organizations, such as GiveWell, LEAN, CEA, Rethink Charity, and The Life You Can Save. 6. 5 student members of EA PH started a chapter named EA Blue at the Ateneo De Manila University in August, and they recruited 60 students to join their chapter. On Organizing Events Photos from some of our events in 2019 When we started, we didn't know anyone else in Manila who was interested in EA. We were all fairly new to the movement. As such, we decided to focus on holding monthly events in order to spread awareness about EA and its various facets and cause areas. We worked on EA PH part-time, on top of our day jobs. At first, we were paying for expenses out of our own pockets. Thankfully, we got funding from CEA to fund our events from May to December 2019. This table includes information on all the events we’ve held so far: To explain some things about the table above: The March 26 talk was given by Yuna Liang, a Senior Research ...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Some learnings I had from forecasting in 2020, published by Linch on the AI Alignment Forum. crossposted from my own short-form Here are some things I've learned from spending a decent fraction of the last 6 months either forecasting or thinking about forecasting, with an eye towards beliefs that I expect to be fairly generalizable to other endeavors. Before reading this post, I recommend brushing up on Tetlock's work on (super)forecasting, particularly Tetlock's 10 commandments for aspiring superforecasters. 1. Forming (good) outside views is often hard but not impossible. I think there is a common belief/framing in EA and rationalist circles that coming up with outside views is easy, and the real difficulty is a) originality in inside views, and also b) a debate of how much to trust outside views vs inside views. I think this is directionally true (original thought is harder than synthesizing existing views) but it hides a lot of the details. It's often quite difficult to come up with and balance good outside views that are applicable to a situation. See Manheim and Muelhauser for some discussions of this. 2. For novel out-of-distribution situations, "normal" people often trust centralized data/ontologies more than is warranted. See here for a discussion. I believe something similar is true for trust of domain experts, though this is more debatable. 3. The EA community overrates the predictive validity and epistemic superiority of forecasters/forecasting. (Note that I think this is an improvement over the status quo in the broader society, where by default approximately nobody trusts generalist forecasters at all) I've had several conversations where EAs will ask me to make a prediction, I'll think about it a bit and say something like "I dunno, 10%?"and people will treat it like a fully informed prediction to make decisions about, rather than just another source of information among many. I think this is clearly wrong. I think in almost any situation where you are a reasonable person and you spent 10x (sometimes 100x or more!) time thinking about a question then I have, you should just trust your own judgments much more than mine on the question. To a first approximation, good forecasters have three things: 1) They're fairly smart. 2) They're willing to actually do the homework. 3) They have an intuitive sense of probability. This is not nothing, but it's also pretty far from everything you want in a epistemic source. 4. The EA community overrates Superforecasters and Superforecasting techniques. I think the types of questions and responses Good Judgment . is interested in is a particular way to look at the world. I don't think it is always applicable (easy EA-relevant example: your Brier score is basically the same if you give 0% for 1% probabilities, and vice versa), and it's bad epistemics to collapse all of the "figure out the future in a quantifiable manner" to a single paradigm. Likewise, I don't think there's a clear dividing line between good forecasters and GJP-certified Superforecasters, so many of the issues I mentioned in #3 are just as applicable here. I'm not sure how to collapse all the things I've learned on this topic in a few short paragraphs, but the tl;dr is that I trusted superforecasters much more than I trusted other EAs before I started forecasting stuff, and now I consider their opinions and forecasts "just" an important overall component to my thinking, rather than a clear epistemic superior to defer to. 5. Good intuitions are really important. I think there's a Straw Vulcan approach to rationality where people think "good" rationality is about suppressing your System 1 in favor of clear th...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Long-Term Future Fund: November 2020 grant recommendations, published by Habryka on the AI Alignment Forum. This is a linkpost for Introduction As part of its November 2020 grant application round, the Long-Term Future Fund supported ten projects that we expect to positively influence the long-term trajectory of civilization, with a total of up to $355,000. We also made an additional off-cycle grant of up to $150,000. Compared to our previous round, we received triple the number of total applications this round, and double the number of high-quality applications (as measured by average fund manager score). We've added an optional referral question to our application form to understand why this is. Our current guess is that it's largely a result of better outreach, particularly through the 80,000 Hours job board and newsletter. To help improve fund transparency, we've written a document describing our overall process for making grants. We'll also be running an 'Ask Me Anything' session on the Effective Altruism Forum from December 4th to 7th, where we answer any questions people might have about the fund. We received feedback this round that our payout reports might discourage individuals from applying if they don't want their grant described in detail. We encourage applicants in this position to apply anyway. We are very sympathetic to circumstances wherein a grantee might be uncomfortable with a detailed public description of their grant. We run all of our grant reports by grantees and think carefully about what information to include to be as transparent as we can while still respecting grantees' preferences. If considerations around reporting make it difficult for us to fund an application, we can refer to private donors who don't publish payout reports. We might also be able to make an anonymous grant, as we did in this round. Highlights Our grants include: An up-to-$150,000 grant to Richard Ngo to do a PhD at Cambridge University on understanding the analogy between the development of human intelligence and artificial general intelligence (AGI). This grant is part of our efforts to reduce potential risks from transformative artificial intelligence. Richard has a strong background for this work: He previously worked at DeepMind and completed a Bachelor's degree in computer science and philosophy at the University of Oxford, and a Master's degree with distinction in computer science at the University of Cambridge. He has also released impressive work in this area before. Human-AGI analogies form the foundation of many researchers' current beliefs about future AI systems; further clarifying them is likely to bring major benefits to the field of AI safety research. A $3,579 grant to Maximilian Negele to investigate the historical longevity of institutions, in order to better understand the feasibility of setting up charitable foundations that last hundreds of years. This grant is part of our efforts to set up institutions that protect future generations. Existing work on patient philanthropy relies on the ability to transfer wealth and resources into the future; understanding how likely an institution is to be able to do this will be hugely informative for understanding whether to spend long-termist resources now or later. Grant recipients See below for a list of grantees' names, grant amounts, and project descriptions. Most of the grants have been accepted, but in some cases, the final grant amount is still uncertain. Grants made during the last grant application round: Anonymous (up to $40,000): Supporting a PhD student's career in technical AI safety. David Bernard (up to $55,000): Testing how the accuracy of impact forecasting varies with the timeframe of prediction. Lee Sharkey ($44,668): Researching methods to continuously monitor and analyse artificial agents...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Relative Impact of the First 10 EA Forum Prize Winners, published by NunoSempere on the AI Alignment Forum. Summary We don’t normally estimate the value of small to medium-sized projects. But we could! If we could do this reliably and scalably, this might lead us to choose better projects Here is a small & very speculative attempt My estimates are very uncertain (ranging several orders of magnitude), but they still seem useful for comparing projects. Nonetheless, the reader is advised to not take them too seriously. Introduction The EA forum—and local groups—have been seeing a decent amount of projects, but few are evaluated for impact. This makes it difficult to choose between projects beforehand, beyond using personal intuition (however good it might be), a connection to a broader research agenda, or other rough heuristics. Ideally, we would have something more objective, and more scalable. As part of QURI’s efforts to evaluate and estimate the impact of things in general, and projects QURI itself might carry out in particular, I tried to evaluate the impact of 10 projects I expected to be fairly valuable. Methodology I chose the first 10 posts which won the EA Forum Prize, back in 2017 and 2018, to evaluate. For each of the 10 posts, each estimate has a structure like the one below. Note that not all estimates will have each element: Title of the post Background information: What are some salient facts about the post? Theory of change: If this isn’t clear, how is this post aiming to have an impact? Reasoning about my estimate: How do I arrive at my estimate of impact given what I know about the world? Guesstimate model: Verbal reasoning can be particularly messy, so I also provide a guesstimate model Ballpark: A verbal estimate Estimate: A numerical estimate of impact If a writeup refers to a project distinct from the writeup, I generally try to estimate the impact of both the project and the writeup. Where possible, I estimated their impact in an ad-hoc scale, Quality Adjusted Research Papers (QARPs for short), whose levels correspond to the following: Value Description Example ~0.1 mQARPs A thoughtful comment A thoughtful comment about the details of setting up a charity ~1 mQARPs A good blog post, a particularly good comment What considerations influence whether I have more influence over short or long timelines? ~10 mQARPs An excellent blog post Humans Who Are Not Concentrating Are Not General Intelligences ~100 mQ A fairly valuable paper Categorizing Variants of Goodhart's Law. ~1 QARPs A particularly valuable paper The Vulnerable World Hypothesis ~10-100 QARPs A research agenda The Global Priorities Institute's Research Agenda. ~100-1000+ QARPs A foundational popular book on a valuable topic Superintelligence, Thinking Fast and Slow ~1000+ QARPs A foundational research work Shannon’s "A Mathematical Theory of Communication." Ideally, this would both have relative meaning (i.e., I claim that an average thoughtful comment is worth less than an average good post), and absolute meaning (i.e., after thinking about it, a factor of 10x between an average thoughtful comment and an average good post seems roughly right). In practice, the second part is a work in progress. In an ideal world, this estimate would be cause-independent, but cause comparability is not a solved problem, and in practice the scale is more aimed towards long-term focused projects. To elaborate on cause independence, upon reflection we may find out that a fairly valuable paper on AI Alignment might be 20 times as a fairly valuable paper on Food Security, and give both of their impacts in a common unit. But we are uncertain about their actual relative impacts, and they will not only depend on uncertainty, but also on moral preferences and values (e.g., weight given to animals, weight given to pe...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: EA Funds has appointed new fund managers , published by Jonas Vollmer, SamDeere on the AI Alignment Forum. Summary Effective Altruism Funds has appointed new fund management teams, composed of both existing and new fund managers, to the following funds (new roles bold): Animal Welfare Fund (AWF): Kieran Greig (chairperson), Lewis Bollard, Alexandria Beck, Karolina Sarek, Marcus Davis, Mikaela Saccoccio EA Infrastructure Fund (EAIF): Max Daniel, Buck Shlegeris, Michelle Hutchinson, with Jonas Vollmer as the acting interim chairperson until we appoint a chairperson later this year Long-Term Future Fund (LTFF): Asya Bergal (chairperson), Oliver Habryka, Adam Gleave To expand our grantmaking capacity, we ran a private appointment process from December 2020 to February 2021. Existing fund managers were given the opportunity to re-apply if they wished, and new candidates were sourced through our networks. We received 66 applications from new candidates. Fund managers were appointed on the basis of their performance on work tests, their past experience in grantmaking or other relevant areas, and formal and informal references. These fund managers have been appointed for a two-year term, after which we will run a similar process again. We still have a larger application load than our regular fund manager team can support, so we plan to appoint further fund managers over the coming months. We are also considering setting up one or several additional funds (primarily a legible longtermist fund). As a result, we still expect significant changes to fund management over the coming months. We’re also experimenting with a new system of guest fund managers, allowing people who might be a good fit to provide input to the fund for a single grant round. We hope that this will give more people in the community an opportunity to improve their judgment, reasoning, and grantmaking skills, add additional viewpoint diversity to the grant evaluation process, and build a bank of strong candidates to potentially appoint as regular fund managers when we need more capacity. We hope that these changes will substantially increase each fund’s capacity to evaluate grants. In addition, we expect the following improvements: The Animal Welfare Fund plans to communicate more proactively about its priorities. The Long-Term Future Fund has increased its leadership capacity and will increasingly focus on proactively creating new grant opportunities (active grantmaking). The EA Infrastructure Fund aims to do more active grantmaking, build long-term funding relationships, fund more small or medium-sized projects rather than established organizations, and more clearly define its priorities. We would also like to extend our thanks to the previous fund managers, for their work in evaluating grants and improving our grantmaking processes, done entirely on a volunteer basis. Rationale for appointing new fund managers EA Funds has historically appointed fund managers in a somewhat ad hoc way, and we’ve never had a defined length of time that they’ll serve for. In 2020, we began consultations with existing fund managers to make the process of appointment more clearly defined. We decided that fund managers should serve for a defined period of time (currently two years), after which they can reapply for another term. New fund managers start with a trial period, so that we can assess their skills and collaboration with their colleagues. Considerations that we took into account included: Increasing overall capacity: Our November 2020 grant round received a record number of applications, and all three funds were limited by the time the fund managers had available to consider applications. (We again broke that record with an even higher number of applications in March 2021.) Also, a number of the existing fund managers ha...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Writing about my job: Internet Blogger , published by AppliedDivinityStudies on the AI Alignment Forum. Response to Aaron Gertler's You should write about your job. Background I've been writing since September 1st, 2020, initially about voting and mechanism design, then about an increasingly varied assortment of topics ranging from the importance of economic growth within an EA framework, to the organization of research institutions and more generic career advice. The blog has been moderately successful in terms of attracting attention from people I respect without causing any major scandals or other negative effects. I occasionally have some interruptions, but mostly work on the blog full time. Skills Some skills I've developed include: Self-management: I have no deadlines, no manager, and generally speaking, no accountability. If I don't choose to do something, it won't get done. The sub-skills include finding good ideas for posts, prioritizing them correctly, avoiding distractions, and actually executing and "shipping". Anecdotally, many of the people I talk to seem to be held back here, whether they're blogging, starting a company or just trying to take a hobby more seriously. If all I got out of the last 9 months was this skill, it all would have been worth it. Patience: It's one thing to build intuitions for exponential growth, another to actually follow through and make investments on long time scales. Since we're systematically over-exposed to successful blog posts, your view of success is likely distorted, and it will take far longer than you think to become a good writer and to get noticed. Writing: This sounds obvious, but it's worth noting that you don't already have to be a good writer. The critical thing is not just practice, but having feedback loops, mentorship and goals. Many bloggers have public contact info, and will happily read your draft. Talking to people: I started blogging in part because I hated lockdown-era Zoom calls, and just wanted to avoid meetings and work alone in peace. Recently, as I've ramped up on more rigorous research projects, I've had to proactively reach out to more senior researchers, ask them for introductions and email authors for clarification or feedback. I was pretty bad at this initially, and would just publish without talking to a single person, even if I was a total amateur in a field with several readily-accessible experts. Since then, I've gotten a lot better at figuring out who to talk to, which questions to ask them, and then actually taking the time to do it. These are all skills I've developed during the course of blogging, but you can also see them as (very soft) pre-requisites. If you're really terrible at self-management, blogging might not be a good career. The degree to which this is true depends on your views on growth mindset, your own learning ability, etc. I wrote here that several prominent bloggers were "losers" in some sense in their previous endeavors, and so you shouldn't let failure in some other domain discourage you. Career Growth Blogging can be an end-unto-itself, but can also be a useful and low-cost way to earn a formal role at a research or media organization. You quickly build up a portfolio of past writing projects, as well as an audience and potentially connections. Some potential next steps could include: Research Scholars Program at FHI Future Perfect Fellow at Vox Junior Researcher at an EA org I haven't applied for any of these myself, but have talked to people selecting for these roles, and have some sense that they believe blogging is a reasonable entry point. Of course, that depends a lot on what kind of blogging you end up doing, and how well it fits with the interests of those programs. Path to Impact Scott Alexander famously wrote "The less useful, and more controversial, a po...
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Towards a longtermist framework for evaluating democracy-related interventions, published by 22tom, Buhl on the AI Alignment Forum. Many people have suggested that improving, safeguarding, or promoting liberal democracy should perhaps be a priority for longtermists. For example, 80,000 Hours lists improving institutional decision making, safeguarding liberal democracy and voting reform as potentially high-impact cause areas (Koehler, 2020). However, it remains unclear how high-priority these areas and specific interventions within them are, and why. This post attempts to (1) tease apart different features of liberal democracy and (2) analyse how increasing or decreasing a society’s level of each feature would affect various potential intermediate goals for longtermists. By potential intermediate goals, we mean goals we could pursue to potentially increase the expected value of the far future, via four broad categories: existential risk reduction, trajectory changes, speeding up development, or “meta-longtermism” (Greaves and MacAskill, 2021)[1]. This is intended as a step towards a general framework for evaluating: how high longtermists should want societies to be on each feature of liberal democracy the positive or negative long-term effects of specific democracy-related interventions the extent to which longtermists should in general prioritise causes or interventions related to liberal democracy We also provide some initial thoughts on these points, and outline some directions for further research. We hope this post, and possible future work building on this framework, could inform longtermism-inclined people who are interested in potentially researching or funding democracy-related interventions, are making career decisions, or are designing and implementing democracy-related interventions. Key takeaways The features of liberal democracy we identify in Section 1 are[2]: Competitive democracy: There are free, fair, and competitive elections (representative and/or direct) and their results are peacefully implemented. Accuracy: Politicians are elected in a way that accurately reflects the preferences of voters. Responsiveness: Policy choices reflect the preferences of voters. Participation: The public exercises their right to vote and participates in decision-making through avenues other than just voting. Voter competence: The public is well-informed and are good decision-makers. Liberalism: The power of the government is limited so as to preserve rule of law and individual rights, including minority rights. Inclusion: Voting rights and other rights are extended to most or all of the population, and the interests of most or all beings are taken into account in decision-making. In Section 2, we then discuss some ways those features may affect a set of seven potential intermediate goals for longtermists, as well as some positive or negative effects these potential goals may have on the long-term future. We suggest that: Boosting most of the seven features of democracy identified may reduce great power conflict (though as with the other effects mentioned here, this is uncertain and depends on the context and details of the intervention). This in turn could potentially reduce existential risk and the risk of negative trajectory changes. Increasing participation and liberalism may enhance intellectual progress, which could reduce existential risk (provided there is differential progress), speed up development, and help improve meta-longtermism. Higher responsiveness & accuracy, liberalism and voter competence could speed up moral circle expansion, which in turn could make some existential risks less likely, speed up moral progress, and affect meta-longtermism. Greater inclusion & participation in a competitive democracy could cause economic growth, which would impact exi...