I think your comment is supposed to be an outside view argument that tempers the gears-level argument in the post. Maybe we could think of it as providing a base-rate prior for the gears-level argument in the post. Is that roughly right? I’m not sure how much I buy into this kind of argument, but I also have some complaints by the outside views lights.
First, let me quickly recap your argument as I understand it.
R&D increases welfare by allowing an increase in consumption. We’ll assume that our growth in consumption is driven, in some fraction, by R&D spending. Assuming utility isn’t linear in consumption, we need to have some story about how the increase in consumption is distributed. Given a bunch of such assumptions, we can get a net present value of the utility, which is 45% as large as giving cash to people with $500/year.
Then, we can look at how the value of interventions are distributed within “causes”. Some data suggest that the 97.5th percentile intervention is about 10x as good as the mean (and maybe 100x as good as the 50th percentile), across a few different intervention areas.
Assuming a lognormal fit, there aren’t enough R&D ideas for the best R&D dollars to be 10,000x as good as the mean R&D dollar.
But, this says nothing about differences in cost-effectiveness between different “causes”. So this argument doesn’t bite for, say, shrimp welfare interventions, which could be arbitrarily more impactful than global health, or R&D developments.
I hope that is a roughly correct rendition of your argument.
Here are my even-assuming-outside-view criticisms:
Even the Davidson model allows that the distribution for interventions that increase the rate/effectiveness of R&D (rather than just purchasing some at the same rate) could be much more effective. I think superresearchers (or even just a large increase in the number of top researchers) are such an intervention
To the extent we’re allowing cause-hopping to enable large multipliers (which we must to think that there are potentially much more impactful opportunities than superbabies), I care about superbabies because of the cause of x-risk reduction! Which I think has much higher cost-effectiveness than growth-based welfare interventions.
I hope that is a roughly correct rendition of your argument.
Thanks for the great summary, Kave!
So this argument doesn’t bite for, say, shrimp welfare interventions, which could be arbitrarily more impactful than global health, or R&D developments.
Nitpick. SWP received 1.82 M 2023-$ (= 1.47*10^6*1.24) during the year ended on 31 March 2024, which is 1.72*10^-8 (= 1.82*10^6/(106*10^12)) of the gross world product (GWP) in 2023, and OP estimated R&D has a benefit-to-cost ratio of 45. So I estimate SWP can only be up to 1.29 M (= 1/(1.72*10^-8)/45) times as cost-effective as R&D due to this increasing SWP’s funding.
Here are my even-assuming-outside-view criticisms:
Even the Davidson model allows that the distribution for interventions that increase the rate/effectiveness of R&D (rather than just purchasing some at the same rate) could be much more effective. I think superresearchers (or even just a large increase in the number of top researchers) are such an intervention
To the extent we’re allowing cause-hopping to enable large multipliers (which we must to think that there are potentially much more impactful opportunities than superbabies), I care about superbabies because of the cause of x-risk reduction! Which I think has much higher cost-effectiveness than growth-based welfare interventions.
Fair points, although I do not see how they would be sufficiently strong to overcome the large baseline difference between SWP and general R&D. I do not think reducing the nearterm risk of human extinction is astronomically cost-effective, and I am sceptical of longterm effects.
I think your comment is supposed to be an outside view argument that tempers the gears-level argument in the post. Maybe we could think of it as providing a base-rate prior for the gears-level argument in the post. Is that roughly right? I’m not sure how much I buy into this kind of argument, but I also have some complaints by the outside views lights.
I hope that is a roughly correct rendition of your argument.
Here are my even-assuming-outside-view criticisms:
Even the Davidson model allows that the distribution for interventions that increase the rate/effectiveness of R&D (rather than just purchasing some at the same rate) could be much more effective. I think superresearchers (or even just a large increase in the number of top researchers) are such an intervention
To the extent we’re allowing cause-hopping to enable large multipliers (which we must to think that there are potentially much more impactful opportunities than superbabies), I care about superbabies because of the cause of x-risk reduction! Which I think has much higher cost-effectiveness than growth-based welfare interventions.
Thanks for the great summary, Kave!
Nitpick. SWP received 1.82 M 2023-$ (= 1.47*10^6*1.24) during the year ended on 31 March 2024, which is 1.72*10^-8 (= 1.82*10^6/(106*10^12)) of the gross world product (GWP) in 2023, and OP estimated R&D has a benefit-to-cost ratio of 45. So I estimate SWP can only be up to 1.29 M (= 1/(1.72*10^-8)/45) times as cost-effective as R&D due to this increasing SWP’s funding.
Fair points, although I do not see how they would be sufficiently strong to overcome the large baseline difference between SWP and general R&D. I do not think reducing the nearterm risk of human extinction is astronomically cost-effective, and I am sceptical of longterm effects.