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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: In current EA, scalability matters, published by Peter Wildeford on March 3, 2022 on The Effective Altruism Forum. Summary: A less cost-effective opportunity that is more scalable can be better than a more cost-effective but less scalable opportunity. That is, in the current effective altruism movement with lots of funding, to maximize the total effectiveness of the entire EA portfolio, scalability should be prioritized on the margin and cost-effectiveness should become more of a bar to meet than something to maximize. This is what motivates a lot of the current focus on highly scalable projects (megaprojects). The Case We're now in a world where effective altruism funding is definitely very plentiful[1]. At least for now, total available funding seems to currently exceed total available fundable opportunities[2]. This implies two things: (1) When looking for new opportunities, a less cost-effective (in terms of social good per dollar spent) opportunity that is more scalable (in terms of total dollars that can be spent to achieve the target cost-effectiveness) can sometimes be more exciting and more helpful to the overall EA portfolio than a more cost-effective but less scalable opportunity. (2) Cost-effectiveness still matters, but requires us either to threshold fund everything above a certain bar (e.g., everything that can be about as good as Against Malaria Foundation[3]) or identify very scalable opportunities that can take billions of dollars on the margin at a higher bar. My sense is that the earlier effective altruism movement of 2010-2014 spent all their time aiming to find opportunities that maximized cost-effectiveness per dollar without caring much about scalability (e.g., "how to do the most good with your limited money"), whereas if the above is right we need to shift to caring about scalability much more and use cost-effectiveness more as a threshold (e.g., identify very scalable opportunities that are as good as AMF or better)[4]. An Example Imagine that we had these five projects (and only these projects) in the EA portfolio: Alpha: Spend $100,000 to produce 1000 units of impact (after which Alpha will be exhausted and will produce no more units of impact; you can't buy it twice) Beta: Spend $100,000,000 to produce 200,000 units of impact (after which Beta will be exhausted and will produce no more units of impact; you can't buy it twice) Gamma: Spend $1,000,000,000 to produce 300,000 units of impact (after which Gamma will be exhausted and will produce no more units of impact; you can't buy it twice) GiveDeltaly: Spent any amount of money to produce a unit of impact for each $2000 spent (GiveDeltaly cannot be exhausted and you can buy it as many times as you want). Research: Spend $200,000 to create a new opportunity with the same "spend X for Y" of Alpha, Beta, Gamma, or GiveDeltaly. EA as of 2010-2014, with relatively fewer resources (we didn't have $100M to spend), would've been ecstatic about Alpha because it only costs $100 to buy one unit of impact, which is much better than Beta's $500 per unit, GiveDeltaly's $2000 per unit, or Gamma's $3333.33 per unit. But "modern" EA, with lots of money and a shortage of opportunities to spend it on would gladly buy Alpha first but would be more excited by Beta because it allows us to deploy more of our portfolio at a better effectiveness. Note though that no one in "modern EA" would be excited by Gamma - even though it's a huge megaproject and very scalable, it doesn't beat our baseline of GiveDeltaly. ...Now let's think of things as allocating an EA bank account and use Research. What should we use Research for? Early EA would want us to focus our research efforts on finding another opportunity like Alpha since it is very cost-effective! But modern EA would rather we look for opportunities like Beta - ev...