Seems like “the right prompt” is doing a lot of work here. How do we know if we have given it “the right prompt”?
Do you think GPT-4 could do my taxes?
1.) I think the core problem is that honestly no one (except 80K) actually is investing significant effort on growing the EA community since 2015 (especially comparable to the pre-2015 effort and especially as a percentage of total EA resources)
2.) Some of these examples are suspect. The GiveWell numbers definitely look to be increasing beyond 2015, especially when OpenPhil’s understandably constant fundraising is removed—and this increase in GiveWell seems to line up with GiveWell’s increased investment in their outreach. The OpenPhil numbers also look just to be sensitive to a few dominant eight figure grants, which understandably are not annual events. (Also my understanding is that Open Phil is starting off slowly intentionally but will aim to ramp up significantly in the near future.)
3.) As I capture in “Is EA Growing? EA Growth Metrics for 2018”, many relevant EA growth statistics have peaked after 2015 or haven’t peaked yet.
4.) There are still a lot of ways EA is growing other than what is captured in these graphs. For example, I bet something like total budget of EA orgs has been growing a lot even since 2015.
5.) Contrary to the “EA is inert” hypothesis, EA Survey data has shown that many people have been “convinced” of EA. Furthermore, our general population surveys show that the vast majority of people (>95% of US university students) have still not heard of EA.
FWIW I I put together “Is EA Growing? EA Growth Metrics for 2018” and I’m looking forward for doing 2019+2020 soon
Mr. Money Mustache has a lot of really good advice that I find a lot of value from. However, I think Mr. Money Mustache underestimates the ease and impact of opportunities to grow income relative to cutting spending—especially if you’re in (or can be in) a high-earning field like tech. Doubling your income will put you on a much faster path than cutting your spending a further 5%.
PredictionBook is really great for lightweight, private predictions and does everything you’re looking for. Metaculus is great for more fully-featured predicting and I believe also supports private questions, but may be a bit of overkill for your use case. A spreadsheet also seems more than sufficient, as others have mentioned.
Thanks. I’ll definitely aim to produce them more quickly… this one got away from me.
My understanding is that we also have and might in the future also spend a decent amount of time in a “level 2.5”, where some but not all non-essential businesses are open (i.e., no groups larger than ten, restaurants are closed to dine-in, hair salons are open).
A binary search strategy still could be more efficient, depending on the ratio of positives to negatives.
What about binary search?
This is a good answer.
Not really an answer, but a statement and a question—I imagine this is literally the least neglected issue in the world right now. How much does that affect the calculus? How much should we defer to people with more domain expertise?
Introduction to Statistical Learning
This paper also seems helpful: https://arxiv.org/pdf/1812.11118.pdf
Answered here: https://forum.effectivealtruism.org/posts/YAwLfgwhg7opp3rTp/please-take-the-2019-ea-survey#G8Hn64AEyh3uMY2SG
The EA Survey is closing today! Please take! https://www.surveymonkey.co.uk/r/EAS2019LW