EA - Some more projects I’d like to see by finm

Link to original articleWelcome to The 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 more projects I’d like to see, published by finm on February 25, 2023 on The Effective Altruism Forum.I recently wrote about some EA projects I’d like to see (also on the EA Forum). This went well!I suggested I’d write out a few more half-baked ideas sometime. As with the previous post, I make no claim to originating these ideas, and I’ll try to attribute them where possible. I also make no claim to being confident that all the ideas are any good; just that they seem potentially good without much due diligence. Since many of these are based on shallow dives, I’ve likely missed relevant ongoing projects.If you’re considering writing a similar list, at the end of this post I reflect on the value of writing about speculative project ideas in public.The order of these ideas is arbitrary and you can read any number of them (i.e. there’s no thread running through them).SummaryFermi gamesBOTEC toolsBillionaire impact listForecasting guideShort stories about AI futuresTechnical assistance with AI safety verificationInfosec consultancy for AI labsAchievements ledgerWorld health dashboardThe Humanity TimesFermi gamesMany people are interested in getting good at making forecasts, and spreading good forecasting practice. Becoming better (more accurate and better calibrated) at forecasting important outcomes — and being willing to make numerical, testable predictions in the first place — often translates into better decisions that bear on those outcomes.A close (and similarly underappreciated) neighbor of forecasting is the Fermi estimate, or BOTEC. This is the skill of considering some figure you’re uncertain about, coming up with some sensible model or decomposition into other figures you can begin guessing at, and reaching a guess. It is also the skill of knowing how confident you should be in that guess; or how wide your uncertainty should be. If you have interviewed for some kind of consulting-adjacent job you have likely been asked to (for example) size a market for whiteboard markers; that is an example.As well as looking ahead in time, you can answer questions about how the past turned out (‘retrocasting’). It’s hard to make retrocasting seriously competitive, because Google exists, but it is presumably a way to teach forecasting: you tell people about the events that led up to some decision in a niche of history few people are familiar with, and ask: did X happen next? How long did Y persist for? And so on. You can also make estimates without dates involved. Douglas Hofstadter lists some examples in Metamagical Themas:How many people die per day on the earth?How many passenger-miles are flown each day in the U.S.?How many square miles are there in the U.S.? How many of them have you been in?How many syllables have been uttered by humans since 1400 A.D.?How many moving parts are in the Columbia space shuttle?What volume of oil is removed from the earth each year?How many barrels of oil are left in the world?How many meaningful, grammatical, ten-word sentences are there in English?How many insects [.] are now alive? [.] Tigers? Ostriches? Horseshoe crabs?How many tons of garbage does New York City put out each week?How fast does your hair grow (in miles per hour)?What is the weight of the Empire State Building? Of the Hoover Dam? Of a fully loaded jumbo jet?Again, most forecasts have a nice feature for evaluation and scoring, which is that before the time where a forecast resolves nobody knows the answer for sure, and after it resolves everyone does, and so there is no way to cheat other than through prophecy.This doesn’t typically apply for other kinds of Fermi estimation questions. In particular, things get really interesting where nobody really knows the correct answer, though a correct answer clearly exists. This pays when ‘ground ...