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[Title from this unrelated story or this unrelated essay] Last week I wrote about how conspiracy theories spread so much faster on Facebook than debunkings of those same theories. A few commenters chimed in to say that of course this was true, the conspiracy theories had evolved into an almost-perfect form for exploiting cognitive biases and the pressures of social media. Debunkings and true beliefs couldn’t copy that process, so they were losing out. This sounded like a challenge, so here you go:
[With apologies to Putnam, Pope, and all of you] Two children are reading a text written by an AI: The hobbits splashed water in each other’s faces until they were both sopping wet One child says to the other “Wow! After reading some text, the AI understands what water is!” The second child says “It doesn’t really understand.” The first child says “Sure it does! It understands that water is the sort of substance that splashes. It understands that people who are splashed with water get wet. What else is left to understand?” The second child says “All it understands is relationships between words. None of the words connect to reality. It doesn’t have any internal concept of what water looks like or how it feels to be wet. Only that the letters W-A-T-E-R, when appearing near the letters S-P-L-A-S-H bear a certain statistical relationship to the letters W-E-T.” The first child starts to cry. Two chemists are watching the children argue with each other. The first chemist says “Wow! After seeing an AI, these kids can debate the nature of water!” The second chemist says “Ironic, isn’t it? After all, the children themselves don’t understand what water is! Water is two hydrogen atoms plus one oxygen atom, and neither of them know!” The first chemist answers “Come on. The child knows enough about water to say she understands it. She knows what it looks like. She knows what it tastes like. That’s pretty much the basics of water.” The second chemist answers “Those are just relationships between pieces of sense-data. The child knows that (visual perception of clear shiny thing) = (tactile perception of cold wetness) = (gustatory perception of refreshingness). And she can predict statistical relationships, like that if she sees someone throw a bucket of (visual perception of clear shiny thing) at her, she will soon feel (tactile perception of cold miserable sopping wetness). She uses the word “water” as a concept-hook that links all of these relationships together and makes predicting the world much easier. But no matter how well she masters these facts, she can never connect them to H2O or any other real chemical facts about the world beyond mere sense-data.”
The Verge writes a story (an exposé?) on the Facebook-moderation industry. It goes through the standard ways it maltreats its employees: low pay, limited bathroom breaks, awful managers – and then into some not-so-standard ones. Mods have to read (or watch) all of the worst things people post on Facebook, from conspiracy theories to snuff videos. The story talks about the psychological trauma this inflicts: It’s an environment where workers cope by telling dark jokes about committing suicide, then smoke weed during breaks to numb their emotions…where employees, desperate for a dopamine rush amid the misery, have been found having sex inside stairwells and a room reserved for lactating mothers… It’s a place where the conspiracy videos and memes that they see each day gradually lead them to embrace fringe views. One auditor walks the floor promoting the idea that the Earth is flat. A former employee told me he has begun to question certain aspects of the Holocaust. Another former employee, who told me he has mapped every escape route out of his house and sleeps with a gun at his side, said: “I no longer believe 9/11 was a terrorist attack. One of the commenters on Reddit asked “Has this guy ever worked in a restaurant?” and, uh, fair. I don’t want to speculate on how much weed-smoking or sex-in-stairwell-having is due to a psychological reaction to the trauma of awful Facebook material vs. ordinary shenanigans. But it sure does seem traumatic. Other than that, the article caught my attention for a few reasons. First, because I recently wrote a post that was a little dismissive of moderators, and made it sound like an easy problem. I think the version I described – moderation of a single website’s text-only comment section – is an easi-er problem than moderating all of Facebook and whatever horrible snuff videos people post there. But if any Facebook moderators, or anyone else in a similar situation, read that post and thought I was selling them short, I’m sorry.
[Epistemic status: I am basing this on widely-accepted published research, but I can’t guarantee I’ve understood the research right or managed to emphasize/believe the right people. Some light editing to bring in important points people raised in the comments.] You all know this graph: Median wages tracked productivity until 1973, then stopped. Productivity kept growing, but wages remained stagnant. This is called “wage decoupling”. Sometimes people talk about wages decoupling from GDP, or from GDP per capita, but it all works out pretty much the same way. Increasing growth no longer produces increasing wages for ordinary workers. Is this true? If so, why? 1. What Does The Story Look Like Across Other Countries And Time Periods? Here’s a broader look, from 1800 on: It no longer seems like a law of nature that productivity and wages are coupled before 1973. They seem to uncouple and recouple several times, with all the previous graphs’ starting point in 1950 being a period of unusual coupledness. Still, the modern uncoupling seems much bigger than anything that’s happened before. What about other countries? This graph is for the UK (you can tell because it spells “labor” as “labour”) It looks similar, except that the decoupling starts around 1990 instead of around 1973. And here’s Europe: This is only from 1999 on, so it’s not that helpful. But it does show that even in this short period, France remains coupled, Germany is decoupled, Spain is…doing whatever Spain is doing, and Italy is so pathetic that the problem never even comes up. Overall not sure what to think about these. 2. Could Apparent Wage Decoupling Be Because Of Health Insurance? Along with wages, workers are compensated in benefits like health insurance. Since health insurance has skyrocketed in price, this means total worker compensation has gone up much more than wages have. This could mean workers are really getting compensated much more, even though they’re being paid the same amount of money. This view has sometimes been associated with economist Glenn Hubbard. There are a few lines of argument that suggest it’s not true. First, wage growth has been worst for the lowest-paid workers. But the lowest-paid workers don’t usually get insurance at all.
Imagine a black box which, when you pressed a button, would generate a scientific hypothesis. 50% of its hypotheses are false; 50% are true hypotheses as game-changing and elegant as relativity. Even despite the error rate, it’s easy to see this box would quickly surpass space capsules, da Vinci paintings, and printer ink cartridges to become the most valuable object in the world. Scientific progress on demand, and all you have to do is test some stuff to see if it’s true? I don’t want to devalue experimentalists. They do great work. But it’s appropriate that Einstein is more famous than Eddington. If you took away Eddington, someone else would have tested relativity; the bottleneck is in Einsteins. Einstein-in-a-box at the cost of requiring two Eddingtons per insight is a heck of a deal. What if the box had only a 10% success rate? A 1% success rate? My guess is: still most valuable object in the world. Even an 0.1% success rate seems pretty good, considering (what if we ask the box for cancer cures, then test them all on lab rats and volunteers?) You have to go pretty low before the box stops being great. I thought about this after reading this list of geniuses with terrible ideas. Linus Pauling thought Vitamin C cured everything. Isaac Newton spent half his time working on weird Bible codes. Nikola Tesla pursued mad energy beams that couldn’t work. Lynn Margulis revolutionized cell biology by discovering mitochondrial endosymbiosis, but was also a 9-11 truther and doubted HIV caused AIDS. Et cetera. Obviously this should happen. Genius often involves coming up with an outrageous idea contrary to conventional wisdom and pursuing it obsessively despite naysayers. But nobody can have a 100% success rate. People who do this successfully sometimes should also fail at it sometimes, just because they’re the kind of person who attempts it at all. Not everyone fails. Einstein seems to have batted a perfect 1000 (unless you count his support for socialism). But failure shouldn’t surprise us.
[This post is having major technical issues. Some comments may not be appearing. If you can’t comment, please say so on the subreddit.] I. I Come To Praise Caesar, Not To Bury Him Several years ago, an SSC reader made an r/slatestarcodex subreddit for discussion of blog posts here and related topics. As per the usual process, the topics that generated the strongest emotions – Trump, gender, race, the communist menace, the fascist menace, etc – started taking over. The moderators (and I had been added as an honorary mod at the time) decreed that all discussion of these topics should be corralled into one thread so that nobody had to read them unless they really wanted to. This achieved its desired goal: most of the subreddit went back to being about cognitive science and medicine and other less-polarizing stuff. Unexpectedly, the restriction to one thread kick-started the culture war discussions rather than toning them down. The thread started getting thousands of comments per week, some from people who had never even heard of this blog and had just wandered in from elsewhere on Reddit. It became its own community, with different norms and different members from the rest of the board. I expected this to go badly. It kind of did; no politics discussion area ever goes really well. There were some of the usual flame wars, point-scoring, and fanatics. I will be honest and admit I rarely read the thread myself. But in between all of that, there was some really impressive analysis, some good discussion, and even a few changed minds. Some testimonials from participants: For all its awfulness there really is something special about the CW thread. There are conversations that have happened there that cannot be replicated elsewhere. Someone mentioned its accidental brilliance and I think that’s right—it catches a wonderful conversational quality I’ve never seen on the Internet, and I’ve been on the Internet since the 90s – werttrew I feel that, while practically ever criticism of the CW thread I have ever read is true, it is still the best and most civil culture war-related forum for conversation I have seen. And I find the best-of roundup an absolute must-read every week – yrrosimyarin
I was going back over yesterday’s post, and something sounded familiar about this paragraph: A very careless plagiarist takes someone else’s work and copies it verbatim: “The mitochondria is the powerhouse of the cell”. A more careful plagiarist takes the work and changes a few words around: “The mitochondria is the energy dynamo of the cell”. A plagiarist who is more careful still changes the entire sentence structure: “In cells, mitochondria are the energy dynamos”. The most careful plagiarists change everything except the underlying concept, which they grasp at so deep a level that they can put it in whatever words they want – at which point it is no longer called plagiarism. After rereading it a few times, it hit me. A few days ago, I’d come across this quote from Miss Manners: There are three possible parts to a date, of which at least two must be offered: entertainment, food, and affection. It is customary to begin a series of dates with a great deal of entertainment, a moderate amount of food, and the merest suggestion of affection. As the amount of affection increases, the entertainment can be reduced proportionately. When the affection IS the entertainment, we no longer call it dating. I laughed at it, I thought it was great, and I stored it in my head as the sort of thing I should quote at some point in order to sound witty. And although I wasn’t consciously thinking about it at the time, I’m sure the last sentence of my paragraph comes from the last sentence of Miss Manners’. It would be easy to dismiss it as a coincidence, it probably seems like a coincidence to you, I can’t explain how I know that the one comes from the other, but when I replay in my mind the process that made me write that, it’s obvious that it did.
A machine learning researcher writes me in response to yesterday’s post, saying: I still think GPT-2 is a brute-force statistical pattern matcher which blends up the internet and gives you back a slightly unappetizing slurry of it when asked. I resisted the urge to answer “Yeah, well, your mom is a brute-force statistical pattern matcher which blends up the internet and gives you back a slightly unappetizing slurry of it when asked.” But I think it would have been true. A very careless plagiarist takes someone else’s work and copies it verbatim: “The mitochondria is the powerhouse of the cell”. A more careful plagiarist takes the work and changes a few words around: “The mitochondria is the energy dynamo of the cell”. A plagiarist who is more careful still changes the entire sentence structure: “In cells, mitochondria are the energy dynamos”. The most careful plagiarists change everything except the underlying concept, which they grasp at so deep a level that they can put it in whatever words they want – at which point it is no longer called plagiarism. GPT-2 writes fantasy battle scenes by reading a million human-written fantasy battle scenes, distilling them down to the concept of a fantasy battle scene, and then building it back up from there. I think this is how your mom (and everyone else) does it too. GPT-2 is worse at this, because it’s not as powerful as your mom’s brain. But I don’t think it’s doing a different thing. We’re all blending experience into a slurry; the difference is how finely we blend it.
Last week OpenAI announced its latest breakthrough. GPT-2 is a language model that can write essays to a prompt, answer questions, and summarize longer works. For example (bold prompt is human-written, all other text is the machine-generated response): Prompt: For today’s homework assignment, please describe the reasons for the US Civil War. It is easy to identify why the Civil War happened, because so many people and so many books and so much television and films tell us that it was the cause, that it has something to do with race or economics or religion. There is much agreement that it was essentially a war of slavery on behalf of capitalism, about a century of slavery. But that’s not what most people think of when they think of the Civil War. Many people think of the war as about states rights. You’re not wrong about that, but it’s kind of misleading to say that the Civil War was a conflict between states’ rights and federalism. So let’s try again. What’s the idea that has inspired so many people to go onto the battlefields of Gettysburg and Antietam and Gettysberg and Petersburg and Fredericksburg? The American idea of the republic–a notion of limited government–is a great part of the history. In 1791, Thomas Jefferson said “Our Constitution was made only for a moral and religious people. It is wholly inadequate to the government of any other.” The “founding fathers” were basically religious men who were not very concerned with states’ rights. The Civil War occurred in reaction to the idea that the federal government was taking far too much power away from the states, that they weren’t sovereign. Jefferson himself, as you well know, is an author of the Declaration of Independence who had some really crazy ideas about, well, you know, secession for a variety of reasons. The War Between the States (later the Great Rebellion) was a radical re-imagining of the American idea and not surprisingly, Jefferson’s grandson, who took after both his father and his grandfather and wrote about it, was named Thomas, after the president. “The federal and state governments are both contrived for the benefit of the rich and large property,” This view of the Founding Fathers has been promoted by some of today’s most prominent politicians, including some who hold prominent national offices and have a direct stake in a Republican Party that has been hijacked by the “federalist” wing of the party. So why is it that so many people have an easy-to-spot way of understanding the Civil War that has everything to do with the South and nothing to do with the South? The Confederate flag has been a symbol of racism for a long time, but when the Civil War started and the Civil War ended, many people suddenly began to see it differently. There was a change of heart, which I think is what led people to take the question of why the Civil War happened quite seriously… Although OpenAI calls this a “language model”, modeling language necessarily involves modeling the world. Even if the AI was only supposed to learn things like “texts that talk about the Civil War use the word ‘Confederate’ a lot”, that has flowered into a rudimentary understanding of how the Civil War worked. Its training corpus (8 million web pages) was large enough that in the course of learning language it learned the specific idiom and structure of all sorts of different genres and subtopics. For example:
I. Chefs. Hundreds of them. Tall chefs, short chefs, black chefs, white chefs. I pushed forward through them, like an explorer hacking away at undergrowth. They muttered curses at me, but I was stronger than they were. I came to a door. I opened it. Sweet empty space. I shut the door behind me, sat down in the chair. “Hello,” I said. “Detective Paul Eastman, pleased to make your acquaintance.” “Doctor Zachary LaShay,” said the man behind the desk. His little remaining hair was greying; his eyes showed hints of the intellect that had been buried beneath the dullness of an administrative career. “I hope you didn’t have any trouble getting here. Did my secretary warn you about the chefs?” “She did not,” I said. “Well, forewarned is forearmed,” he answered, inanely and incongruously. “But I trust you got my message about the federal investigators?” “Once a federal investigation has started, we’ll retreat and let them take over. But two women died here. We can’t just not investigate because you tell us you’re trying to get the Feds involved.” “Yes, ah, of course. It’s just that we’re a sort of, ah, defense contractor. None of our projects are officially classified, yet, but we were hoping to get someone with a security clearance, in case this touched on sensitive areas.” “I won’t pry further than I have to, but until someone from the government says something official, this is a matter for city police. Maybe you could start by telling me more about exactly what you do here.” “We’re the United States’ only proverb laboratory. Our mission is to stress-test the nation’s proverbs. To provide rigorous backing for the good ones, and weed out the bad ones.” “I’d never even heard of your organization before today, I have to admit. And now that I’m here…it’s huge! Who pays for all of this?” “Everybody who uses proverbs,” said the Doctor, “which is to say, everybody. Consider: he who hesitates is lost. But also: look before you leap. Suppose you’re a business executive who spots a time-limited opportunity. What do you do? Hesitate? Or leap without looking? Eggheads devise all sorts of fancy rules about timing the market and relying on studies, but when push comes to shove most people are going to rely on the simple sayings they learned as a child. If you can keep your stock of proverbs more up-to-date than your competitor’s, that gives you a big business advantage.” A smartly-dressed woman came in, handed Dr. LaShay a cup of boiling liquid. He put it to his lips, then spat. “This is terrible!” he said. “Try it!” I had been expecting it to be tea, but it wasn’t. I didn’t know what it was. But it was terrible. Somehow too plain, too salty, and too bitter all at once. I gagged. “That settles it!” said the Doctor. “Too many cooks really do spoil the broth. Tricia, tell the chefs they can all go home now.” “So that’s what you were doing!” I said.
SSRIs are the most widely used class of psychiatric medications, helpful for depression, anxiety, OCD, panic, PTSD, anger, and certain personality disorders (Why should the same drug treat all these things? Great question!) They’ve been pretty thoroughly studied, but there’s still a lot we don’t understand about them. The SSC Survey is less rigorous than most existing studies, but its many questions and very high sample size provide a different tool to investigate some of these issues. I asked fifteen questions about SSRIs on the most recent survey and received answers from 2,090 people who had been on SSRIs. The sample included people on all six major SSRIs, but there were too few people on fluvoxamine (15) to have reliable results, so it was not included in most comparisons. Here’s what we found: 1. Do SSRIs work? People seem to think so: Made me feel much worse: 6% Made me feel slightly worse: 7.4% No net change in how I felt: 23.7% Made me feel slightly better: 41.4% Made me feel much better: 21.4% Of course, these statistics include the placebo effect and so cannot be taken entirely at face value. 2. Do some SSRIs work better than others? I asked people to rate their experience with the medication, on a scale from 1 to 10. Here were the results: Lexapro (356): 5.7 Zoloft (470): 5.6 Prozac (339): 5.5 Celexa (233): 5.4 Paxil (126): 4.6 Paxil differed significantly from the others; the others did not differ significantly among themselves. In a second question where participants were just asked to rate their SSRIs from -2 (“made me feel much worse”) to +2 (“made me feel much better”), the ranking was preserved, and Lexapro also separated from Celexa. This ranking correlates at r = 0.98 (!?!) with my previous study of this taken from drugs.com ratings. I don’t generally hear that Paxil is less effective than other SSRIs, but I have heard that it causes worse side effects. The survey question (probably wrongly) encouraged people to rate side effects as “negative efficacy”. My guess is that the difference here is mostly driven by side effects.
I. I don’t know much about gay history, but the heavily mythicized version of it I heard goes like this: At first open homosexuality was totally taboo. A few groups of respectable people with hilariously upper-class names like The Mattachine Society and The Daughters Of Bilitis quietly tried to influence elites in favor of more tolerance, using whatever backchannels elites use to influence one another. They had limited success, but they comforted themselves that at least they were presenting a likeable and respectable face for homosexuality that was improving the lifestyle’s public reputation. Then a few totally-non-respectable outsiders with nothing to lose – addicts, drag queens, men with lots of chest hair who dressed in leather and called themselves “bears” – publicly came out as gay, held pride parades, shouted things about “WE’RE HERE, WE’RE QUEER”, et cetera. They were very easy to dislike and most people easily disliked them. But once they did this enough, people who were maybe 10% of the way to being respectable – people not addicted to quite so many drugs, men without quite so much chest hair – felt comfortable joining in. Once enough of them were out, people who were 20% of the way to being respectable felt comfortable coming out, and so on. Then 30% respectable people, then 40% respectable people, all the way up to the present day where there are a bunch of openly gay members of Congress. I know there are lots of debates over whether this kind of “respectability cascade” is the way it really happened, but it’s a neat model of a way that these things can happen. II. And it’s especially interesting because it’s the opposite of the way I usually think about these things. When I did pre-med in college, I learned physiology from a distinguished professor whose focus was herpetology – the study of reptiles and amphibians. His pet issue was endocrine disruption – hormone-like pollutants that were changing the sexual maturation of frogs and other animals, and which were suspected to have deleterious effects on humans. He made us read a bunch of papers on this, all of which demonstrated a clear scientific consensus that this was a well-known environmental problem and all the respectable environmentalists and herpetologists were concerned about it. After college I went about a decade without thinking about it. Then people started making fun of Alex Jones’ CHEMICALZ R TURNING TEH FROGZ GAY!!! shtick. I innocently said that this was definitely happening and definitely deserved our concern, and discovered that this was no longer an acceptable thing to talk about in the Year Of Our Lord Two Thousand And Whatever. Okay. Lesson learned.
I. Zero To One might be the first best-selling business book based on a Tumblr. Stanford student Blake Masters took Peter Thiel’s class on startups. He posted his notes on Tumblr after each lecture. They became a minor sensation. Thiel asked if he wanted to make them into a book together. He did. The title comes from Thiel’s metaphor that ordinary businessmen like restaurant owners take a product “from 1 to n” (shouldn’t this be from n to n+1?) – they build more of something that already exists. But the greatest entrepreneurs bring something “from 0 to 1” – they invent something that has never been seen before. The book has various pieces of advice for such entrepreneurs. Three sections especially struck me: on monopolies, on secrets, and on indefinite optimism. II. A short review can’t fully do justice to the book’s treatment of monopolies. Gwern’s look at commoditizing your complement almost does (as do some tweets). But the basic economic argument goes like this: In a normal industry (eg restaurant ownership) competition should drive profit margins close to zero. Want to open an Indian restaurant in Mountain View? There will be another on the same street, and two more just down the way. If you automate every process that can be automated, mercilessly pursue efficiency, and work yourself and your employees to the bone – then you can just barely compete on price. You can earn enough money to live, and to not immediately give up in disgust and go into another line of business (after all, if you didn’t earn that much, your competitors would already have given up in disgust and gone into another line of business, and your task would be easier). But the average Indian restaurant is in an economic state of nature, and its life will be nasty, brutish, and short. This was the promise of the classical economists: capitalism will optimize for consumer convenience, while keeping businesses themselves lean and hungry. And it was Marx’s warning: businesses will compete so viciously that nobody will get any money, and eventually even the capitalists themselves will long for something better. Neither the promise nor the warning has been borne out: business owners are often comfortable and sometimes rich. Why? Because they’ve escaped competition and become at least a little monopoly-like. Thiel says this is what entrepreneurs should be aiming for. He hates having to describe how businesses succeed, because he thinks it’s too anti-inductive to reduce to a formula: Tolstoy opens Anna Karenina by observing “All happy families are alike; each unhappy family is unhappy in its own way.” Business is the opposite. All happy companies are different: each one earns a monopoly by solving a unique problem. All failed companies are the same: they failed to escape competition. But he grudgingly describes four ways that a company can successfully reach monopolyhood:
At the beginning of every year, I make predictions. At the end of every year, I score them. So here are a hundred more for 2019. Rules: all predictions about what will be true on January 1, 2020. Any that involve polling will be settled by the top poll or average of polls on Real Clear Politics on that day. Most predictions about my personal life, or that refer to the personal lives of other people, have been redacted to protect their privacy. I’m using the full 0 – 100 range in making predictions this year, but they’ll be flipped and judged as 50 – 100 in the rating stage, just like in previous years. I’ve tried to avoid doing specific research or looking at prediction markets when I made these, though some of them I already knew what the markets said. Feel free to get in a big fight over whether 50% predictions are meaningful. US 1. Donald Trump remains President: 90% 2. Donald Trump is impeached by the House: 40% 3. Kamala Harris leads the Democratic field: 20% 4. Bernie Sanders leads the Democratic field: 20% 5. Joe Biden leads the Democratic field: 20% 6. Beto O’Rourke leads the Democratic field: 20% 7. Trump is still leading in prediction markets to be Republican nominee: 70% 8. Polls show more people support the leading Democrat than the leading Republican: 80% 9. Trump’s approval rating below 50: 90% 10. Trump’s approval rating below 40: 50% 11. Current government shutdown ends before Feb 1: 40% 12. Current government shutdown ends before Mar 1: 80% 13. Current government shutdown ends before Apr 1: 95% 14. Trump gets at least half the wall funding he wants from current shutdown: 20% 15. Ginsberg still alive: 50%
Lots of people have asked me to recommend them a psychiatrist or therapist. I’ve done a terrible job responding: it’s a conflict of interest to recommend my own group, and I don’t know many people outside of it. So now I’ve put together a list (by which I mostly mean blatantly copied a similar list made by fellow community member Anisha M) of mental health professionals whom members of the rationalist community have had good experiences with. So far it’s short and mostly limited to the Bay Area. You can find it at the “Psychiat-List” button on the top of the blog, or at this link. My hope is to crowd-source additional recommendations to expand the list to more providers and cities. Please let me know, either on this post or on the comments to the list itself, if you have any extra recommendations to add – especially if you’re in a city likely to have many other SSC readers. Please also let me know if you’ve had any positive or negative experiences with people already on the list, so I can change their status accordingly.
At the beginning of every year, I make predictions. At the end of every year, I score them. Here are 2014, 2015, 2016, and 2017. And here are the predictions I made for 2018. Strikethrough’d are false. Intact are true. Italicized are getting thrown out because I can’t decide if they’re true or not. Please don’t complain that 50% predictions don’t mean anything; I know this is true but there are some things I’m genuinely 50-50 unsure of. US: 1. Donald Trump remains president at end of year: 95% 2. Democrats take control of the House in midterms: 80% 3. Democrats take control of the Senate in midterms: 50% 4. Mueller’s investigation gets cancelled (eg Trump fires him): 50% 5. Mueller does not indict Trump: 70% 6. PredictIt shows Bernie Sanders having highest chance to be Dem nominee at end of year: 60% 7. PredictIt shows Donald Trump having highest chance to be GOP nominee at end of year: 95% 8. [This was missing in original] 9. Some sort of major immigration reform legislation gets passed: 70% 10. No major health-care reform legislation gets passed: 95% 11. No large-scale deportation of Dreamers: 90% 12. US government shuts down again sometime in 2018: 50% 13. Trump’s approval rating lower than 50% at end of year: 90% 14. …lower than 40%: 50% 15. GLAAD poll suggesting that LGBQ acceptance is down will mostly not be borne out by further research: 80%
Thanks to everyone who commented on the review of The Structure Of Scientific Revolutions. From David Chapman: It’s important to remember that Kuhn wrote this seven decades ago. It was one of the most influential books of pop philosophy in the 1960s-70s, influencing the counterculture of the time, so it is very much “in the water supply.” Much of what’s right in it is now obvious; what’s wrong is salient. To make sense of the book, you have to understand the state of the philosophy of science before then (logical positivism had just conclusively failed), and since then (there has been a lot of progress since Kuhn, sorting out what he got right and wrong). The issue of his relativism and attitude to objectivity has been endlessly rehashed. The discussion hasn’t been very productive; it turns out that what “objective” means is more subtle than you’d think, and it’s hard to sort out exactly what Kuhn thought. (And it hasn’t mattered what he thought, for a long time.) Kuhn’s “Postscript” to the second edition of the book does address this. It’s not super clear, but it’s much clearer than the book itself, and if anyone wants to read the book, I would strongly recommend reading the Postscript as well. Given Scott’s excellent summary, in fact I would suggest starting with the Postscript. The point that Kuhn keeps re-using a handful of atypical examples is an important one (which has been made by many historians and philosophers of science since). In fact, the whole “revolutionary paradigm shift” paradigm seems quite rare outside the examples he cites. And, overall, most sciences work quite differently from fundamental physics. The major advance in meta-science from about 1980 to 2000, imo, was realizing that molecular biology, e.g., works so differently from fundamental physics that trying to subsume both under one theory of science is infeasible. I’m interested to hear him say more about that last sentence if he wants. Kaj Sotala quotes Steven Horst quoting Thomas Kuhn on what he means by facts not existing independently of paradigms: [Kuhn wrote that]: A historian reading an out-of-date scientific text characteristically encounters passages that make no sense. That is an experience I have had repeatedly whether my subject is an Aristotle, a Newton, a Volta, a Bohr, or a Planck. It has been standard to ignore such passages or to dismiss them as products of error, ignorance, or superstition, and that response is occasionally appropriate. More often, however, sympathetic contemplation of the troublesome passages suggests a different diagnosis. The apparent textual anomalies are artifacts, products of misreading. For lack of an alternative, the historian has been understanding words and phrases in the text as he or she would if they had occurred in contemporary discourse. Through much of the text that way of reading proceeds without difficulty; most terms in the historian’s vocabulary are still used as they were by the author of the text. But some sets of interrelated terms are not, and it is [the] failure to isolate those terms and to discover how they were used that has permitted the passages in question to seem anomalous. Apparent anomaly is thus ordinarily evidence of the need for local adjustment of the lexicon, and it often provides clues to the nature of that adjustment as well. An important clue to problems in reading Aristotle’s physics is provided by the discovery that the term translated ‘motion’ in his text refers not simply to change of position but to all changes characterized by two end points. Similar difficulties in reading Planck’s early papers begin to dissolve with the discovery that, for Planck before 1907, ‘the energy element hv’ referred, not to a physically indivisible atom of energy (later to be called ‘the energy quantum’) but to a mental subdivision of the energy continuum, any point on which could be physically occupied. These examples all turn out to involve more than mere changes in the use of terms, thus illustrating what I had in mind years ago when speaking of the “incommensurability” of successive scientific theories. In its original mathematical use ‘incommensurability’ meant “no common measure,” for example of the hypotenuse and side of an isosceles right triangle. Applied to a pair of theories in the same historical line, the term meant that there was no common language into which both could be fully translated. (Kuhn 1989/2000, 9–10) While scientific theories employ terms used more generally in ordinary language, and the same term may appear in multiple theories, key theoretical terminology is proprietary to the theory and cannot be understood apart from it. To learn a new theory, one must master the terminology as a whole: “Many of the referring terms of at least scientific languages cannot be acquired or defined one at a time but must instead be learned in clusters” (Kuhn 1983/2000, 211). And as the meanings of the terms and the connections between them differ from theory to theory, a statement from one theory may literally be nonsensical in the framework of another. The Newtonian notions of absolute space and of mass that is independent of velocity, for example, are nonsensical within the context of relativistic mechanics. The different theoretical vocabularies are also tied to different theoretical taxonomies of objects. Ptolemy’s theory classified the sun as a planet, defined as something that orbits the Earth, whereas Copernicus’s theory classified the sun as a star and planets as things that orbit stars, hence making the Earth a planet. Moreover, not only does the classificatory vocabulary of a theory come as an ensemble—with different elements in nonoverlapping contrast classes—but it is also interdefined with the laws of the theory. The tight constitutive interconnections within scientific theories between terms and other terms, and between terms and laws, have the important consequence that any change in terms or laws ramifies to constitute changes in meanings of terms and the law or laws involved with the theory (though, in significant contrast with Quinean holism, it need not ramify to constitute changes in meaning, belief, or inferential commitments outside the boundaries of the theory). While Kuhn’s initial interest was in revolutionary changes in theories about what is in a broader sense a single phenomenon (e.g., changes in theories of gravitation, thermodynamics, or astronomy), he later came to realize that similar considerations could be applied to differences in uses of theoretical terms between contemporary subdisciplines in a science (1983/2000, 238). And while he continued to favor a linguistic analogy for talking about conceptual change and incommensurability, he moved from speaking about moving between theories as “translation” to a “bilingualism” that afforded multiple resources for understanding the world—a change that is particularly important when considering differences in terms as used in different subdisciplines. Syrrim offers a really neat information theoretic account of predictive coding:
In 2010, Ben Tilly of the blog Random Observations wrote Analysis Vs. Algebra Predicts Eating Corn?, which said: I like learning about odd connections between disparate things. This probably is the oddest example that I know. Broadly speaking, mathematicians can be divided into those who like analysis, and those who like algebra. The distinction between the two types runs throughout math. Even those who work in areas that are far from analysis or algebra are very aware of the difference between them, and usually are very clear on which their preference is. I’ll delve into this in more depth soon, but for now let’s just take it for granted that this is a well-known distinction, and it has meaning for mathematicians. Back when I was in grad school there was a department lunch with corn on the cob. Partway through the meal one of the analysts looked around the room and remarked, “That’s odd, all of the analysts are eating corn one way and the algebraists are eating corn another!” Everyone looked around. In fact everyone was eating the corn in one of two ways. One way was to munch over the length of the corn in a straight line, back up, turn slightly, and do another row across. Kind of like how an old typewriter goes. The other way was to go around in a spiral. All of the analysts were eating in spirals, and the algebraists in rows. There were a number of mathematicians present whose fields of study didn’t make it clear whether they were on the analysis or algebra side of things. We went around and asked, and in every case the way they ate corn matched their preference. Since then I’ve made a point of amusing myself by asking mathematicians I meet whether they prefer algebra or analysis, and then predicting which way they will eat corn. I’m probably up to 40 or so by now, and in every case but one I’ve been able to correctly predict how they eat corn. The one exception was a logician who claimed to be exactly on the fence between the two. When I explained the corn thing to him he looked surprised, and said that he had an unusual way of eating corn. He went in loose spirals! In other words he truly was a perfect combination of algebra and analysis!
[Content warning: References to anti-Semitic and anti-Catholic canards] I feel deep affection for Gary Allen’s None Dare Call It Conspiracy, a bizarre screed about the Federal Reserve/Communist/Trilateral Commission plot for a one world government. From its ridiculous title to its even-more-ridiculous cover image, this is a book that accepts its own nature. In the Aristotelian framework, where everything is trying to be the most perfect example of whatever it is, None Dare Call It Conspiracy has reached a certain apotheosis. But my problem is the opposite of Allen’s. Too many people dare call too many things conspiracy. Perfectly reasonable hypotheses get attacked as conspiracy theories, derailing the discussion into arguments over when you’re allowed to use the phrase. These arguments are surprisingly tough. Which of the following do you think should be classified as “conspiracy theories”? Which ones are so deranged that people espousing them should be excluded from civilized discussion? 1. Donald Trump and his advisors secretly met with Russian agents to discuss how to throw the 2016 election in his favor. 2. Donald Trump didn’t collaborate with any Russians, but Democrats are working together to convince everyone that he did, in the hopes of getting him indicted or convincing the electorate that he’s a traitor. 3. Insurance companies are working to sabotage any proposal for universal health care; if not for their constant machinations, we would have universal health care already. 4. The ruling classes constantly use lobbyists and soft power to sabotage tax increases, labor laws, and any other policy that increase the relative power of the poor. 5. America’s aid to Israel is not in America’s best interest, but is maintained through the power of AIPAC and other pro-Israel groups mainly supported by America’s Jewish community. 6. The Jews are behind Brexit as a plot to weaken Western Europe. 7. Climate scientists routinely exaggerate or massage their studies to get the results they want, or only publish studies that get the results they want, both because of their personal political leanings and because they know it is good for their field to constantly be discovering exciting things that their funders and their supporters among the public want to hear.
Thanks to the 8,171 people who took the 2019 Slate Star Codex survey. Some of the links below will say 13,171 people took the survey, but that’s a bug – sometimes Google just adds 5,000 to things. You can: – See the questions for the SSC survey. – See the results from the SSC survey. I’ll be publishing more complicated analyses over the course of the next year, hopefully starting later this week. If you want to scoop me, or investigate the data yourself, you can download the answers of the 7000 people who agreed to have their responses shared publicly. The public datasets will not exactly match the full version, nor will they include some of the sensitive sections like illegal drug use and sexual partners. Download the public data (.xlsx, .odf)