strawberry calm

Karma: 47

strawberry calm 12 Nov 2022 23:20 UTC
2 points
1 ∶ 0
on: If EA has overestimated its projected funding, which decisions must be revised?
EA is constrained by the following formula:
Number of Donors x Average Donation = Number of Grants x Average Grant
If we lose a big donor, there are four things EA can do:
1. Increase the number of donors:
  1. Outreach. Community growth. Might be difficult right now for reputation reasons, though fortunately, EA was very quick to denounce SBF.
  2. Maybe lobby the government for cash?
  3. Maybe lobby OpenAI, DeepMind, etc for cash?
2. Increase average donation:
  1. Get another billionaire donor. Presumably, this is hard because otherwise EA would’ve done it already, but there might be factors that are hidden from me.
  2. 80K could begin pushing earning-to-give again. They shifted their recommendations a few years ago to promoting direct-impact careers. This made sense when EA was less funding-constrained.
  3. Get existing donors to ramp up their donations. In the good ol’ days, EA used to be a club for people donating 60% of their income to anti-malaria bednets. Maybe EA will return to that frugal ascetic lifestyle.
3. Reduce the number of grants:
  1. FTX was funding a number of projects. Some of these were higher priorities than others. Hopefully the high-priority projects retain their funding, whereas low-priority projects are paused.
  2. EA has been engaged in a “hit-or-miss” approach to grant-making. This makes sense when you have more cash than sure-thing ideas. But now we have less cash we should focus on sure-thing ideas.
  3. The problem with the “sure-thing” approach to grant-making is that it biases certain causes (e.g. global health & dev) over others (e.g. x-risk). I think that would be a mistake. Someone needs to think about how to calibrate for this bias.
    
    Here’s a tentative idea: EA needs more prizes and other forms of retrodictive funding. This will shift risk from the grant-maker to the researcher, which might be good because the researcher is more informed about the likelihood of success than the grant-maker.
4. Reduce average grant:
  1. Maybe EA needs to focus on cheaper projects.
  2. For example, in AI safety there has been a recent shift away from theoretic work (like MIRI’s decision theory) towards experimental work. This experimental work is very expensive because it involves (say) training large language models. This shift should be at least somewhat reversed.
  3. Academics are very cheap! And they often already have funding. EA (especially AI safety) needs to do more outreach to established academics, such as top philosophers, mathematicians, economists, computer scientists, etc.

strawberry calm 11 Nov 2022 20:01 UTC
13 points
2 ∶ 7
in reply to: Ferenc Huszár’s comment on: If EA has overestimated its projected funding, which decisions must be revised?
imo EA should have remained frugal.

For theoretical reasons, this makes sense. It’s incompatible with Singerite alturism to spend money on frivolous luxuries while people are still starving. EAs were supposed to donate their surplus income to GiveWell. This doesn’t change when your surplus income grows. At least, not as much as people behaved.
Also for practical reasons. We could’ve hired double the researchers on half the salary. Okay maybe 1.25x the researchers on 80% the salary. I don’t know the optimal point in the workforce-salary tradeoff but EA definitely went too far in the salary direction.
The result was golden handcuffs, grifters, and value drift.
Let’s bring back Ascetic EA. Hummus on toast.

strawberry calm 11 Nov 2022 18:43 UTC
5 points
0 ∶ 0
on: If EA has overestimated its projected funding, which decisions must be revised?
EA is constrained by the following formula:
Number of Donors x Average Donation = Number of Grants x Average Grant
If we lose a big donor, there are four things EA can do:
1. Increase the number of donors:
  1. Outreach. Community growth. Might be difficult right now for reputation reasons, though fortunately, EA was very quick to denounce SBF.
  2. Maybe lobby the government for cash?
  3. Maybe lobby OpenAI, DeepMind, etc for cash?
2. Increase average donation:
  1. Get another billionaire donor. Presumably, this is hard because otherwise EA would’ve done it already, but there might be factors that are hidden from me.
  2. 80K could begin pushing earning-to-give again. They shifted their recommendations a few years ago to promoting direct-impact careers. This made sense when EA was less funding-constrained.
  3. Get existing donors to ramp up their donations. In the good ol’ days, EA used to be a club for people donating 60% of their income to anti-malaria bednets. Maybe EA will return to that frugal ascetic lifestyle.
3. Reduce the number of grants:
  1. FTX was funding a number of projects. Some of these were higher priorities than others. Hopefully the high-priority projects retain their funding, whereas low-priority projects are paused.
  2. EA has been engaged in a “hit-or-miss” approach to grant-making. This makes sense when you have more cash than sure-thing ideas. But now we have less cash we should focus on sure-thing ideas.
  3. The problem with the “sure-thing” approach to grant-making is that it biases certain causes (e.g. global health & dev) over others (e.g. x-risk). I think that would be a mistake. Someone needs to think about how to calibrate for this bias.
    
    Here’s a tentative idea: EA needs more prizes and other forms of retrodictive funding. This will shift risk from the grant-maker to the researcher, which might be good because the researcher is more informed about the likelihood of success than the grant-maker.
4. Reduce average grant:
  1. Maybe EA needs to focus on cheaper projects.
  2. For example, in AI safety there has been a recent shift away from theoretic work (like MIRI’s decision theory) towards experimental work. This experimental work is very expensive because it involves (say) training large language models. This shift should be at least somewhat reversed.
  3. Academics are very cheap! And they often already have funding. EA (especially AI safety) needs to do more outreach to established academics, such as top philosophers, mathematicians, economists, computer scientists, etc.