I might’ve used too strong of a language with my original post, such as the talk about being a sucker. For me it’s useful to think about donations as a product I’m buying, but I probably took it too far. And I don’t think I’ve properly emphasized my main message, which was (as I’ve added later) - the explore-exploit tradeoff for causes is really hard if you don’t know how far exploration could take you. Honestly, I’m most interested in your take on that.I initially only used GiveWell and CEARCH to demonstrate that argument and show I how got to it.
The drug analogy is interesting, although I prefer the start-up analogy. Drug development is more binary—some drugs can just flat-out fail in humans, while start-ups are more of a spectrum (the ROI might be smaller than thought etc.). I don’t see a reason to think of CEARCH recommended programs or for most other exploratory stuff as binary. Of course lobbying could flat-out fail, but it’s unlikely we’ll have to update our beliefs that this charity would NEVER work, as might happen in drug development. And obviously with start-ups, there’s also a lot of difference between the initial market research and the later stages (as you said).
GiveWell has a lot of flaws for cause exploration. They really focus on charity research, not cause research. It’s by design really biased towards existing causes and charities. The charities must be interested and cooperate with GiveWell. They look for the track record, i.e. charities operating in high-risk, low tractibillity areas such as policy have a harder time. In most cases it makes sense, sometimes it can miss great opportunities.
Yes, they’ve funded some policy focused charities, but they might’ve funded much more if they were more EV maximizing instead of risk-averse. Seeing the huge leverage such options provide, it’s entirely possible.
Also, they aren’t always efficient—look at GiveDirectly. Their bar for top charities was 10x GiveDirectly for years, yet they kept GiveDirectly as a top charity until last year??? This is not some small, hard to notice inefficiency. It literally is their consistent criteria for their flagship charities. Can you imagine a for-profit company telling their investors “well, we believe these other channels have a ROI of at least 10x, but please also consider investing in this channel with x ROI”, for multiple years? I can’t. Let alone putting that less efficient channel as one of the best investments…
That’s exactly what I mean when I say altruism, even EA, can have gross inefficiency in allocations. It’s not special to GiveWell, I’m just exemplifying.
If GiveWell can make such gross mistakes, then probably others can. Another example was their relative lack of research on family planning, which I’ve written about. They’re doing A LOT of great things too. But I must say I am a bit skeptical of their decision making sometimes.
Keep in mind, CEARCH would have to be EXTREMELY optimistic in order for us to say that it hasn’t found a couple of causes 10x GiveWell. We are talking about 40x optimistic. That might be the case, but IMO it’s a strong enough assertion to require proof. Do you have examples of something close to 40x optimism in cost-effectiveness?
I agree that a lot of the difference in EAs donations can come from differing perspectives, probably most. But I think even some utilitarian, EV maximizing, 0-future discount, animal equalists EAs donate to different causes (or any other set of shared beliefs). It’s definitely not impossible.
As for other examples of 10x GiveWell cost-effectiveness in global health:
An Israeli non-profit, which produced an estimate of 4.3$ QALYs per dollar, in cooperation with EA Israel. A volunteer said to me he believed they were about 3x too optimistic, but that’s still around 10x GiveWell.
Also here is an example of 4x disagreement between GiveWell and Founders Pledge, and an even bigger disagreement with RP, on a mass media campaign for family planning. Even the best in the business can disagree.
I might’ve used too strong of a language with my original post, such as the talk about being a sucker. For me it’s useful to think about donations as a product I’m buying, but I probably took it too far. And I don’t think I’ve properly emphasized my main message, which was (as I’ve added later) - the explore-exploit tradeoff for causes is really hard if you don’t know how far exploration could take you. Honestly, I’m most interested in your take on that. I initially only used GiveWell and CEARCH to demonstrate that argument and show I how got to it.
The drug analogy is interesting, although I prefer the start-up analogy. Drug development is more binary—some drugs can just flat-out fail in humans, while start-ups are more of a spectrum (the ROI might be smaller than thought etc.). I don’t see a reason to think of CEARCH recommended programs or for most other exploratory stuff as binary. Of course lobbying could flat-out fail, but it’s unlikely we’ll have to update our beliefs that this charity would NEVER work, as might happen in drug development. And obviously with start-ups, there’s also a lot of difference between the initial market research and the later stages (as you said).
GiveWell has a lot of flaws for cause exploration. They really focus on charity research, not cause research. It’s by design really biased towards existing causes and charities. The charities must be interested and cooperate with GiveWell. They look for the track record, i.e. charities operating in high-risk, low tractibillity areas such as policy have a harder time. In most cases it makes sense, sometimes it can miss great opportunities.
Yes, they’ve funded some policy focused charities, but they might’ve funded much more if they were more EV maximizing instead of risk-averse. Seeing the huge leverage such options provide, it’s entirely possible.
Also, they aren’t always efficient—look at GiveDirectly. Their bar for top charities was 10x GiveDirectly for years, yet they kept GiveDirectly as a top charity until last year??? This is not some small, hard to notice inefficiency. It literally is their consistent criteria for their flagship charities. Can you imagine a for-profit company telling their investors “well, we believe these other channels have a ROI of at least 10x, but please also consider investing in this channel with x ROI”, for multiple years? I can’t. Let alone putting that less efficient channel as one of the best investments…
That’s exactly what I mean when I say altruism, even EA, can have gross inefficiency in allocations. It’s not special to GiveWell, I’m just exemplifying.
If GiveWell can make such gross mistakes, then probably others can. Another example was their relative lack of research on family planning, which I’ve written about. They’re doing A LOT of great things too. But I must say I am a bit skeptical of their decision making sometimes.
Keep in mind, CEARCH would have to be EXTREMELY optimistic in order for us to say that it hasn’t found a couple of causes 10x GiveWell. We are talking about 40x optimistic. That might be the case, but IMO it’s a strong enough assertion to require proof. Do you have examples of something close to 40x optimism in cost-effectiveness?
I agree that a lot of the difference in EAs donations can come from differing perspectives, probably most. But I think even some utilitarian, EV maximizing, 0-future discount, animal equalists EAs donate to different causes (or any other set of shared beliefs). It’s definitely not impossible.
As for other examples of 10x GiveWell cost-effectiveness in global health:
CE has estimated another charity yields $5.62 per DALY.
An Israeli non-profit, which produced an estimate of 4.3$ QALYs per dollar, in cooperation with EA Israel. A volunteer said to me he believed they were about 3x too optimistic, but that’s still around 10x GiveWell.
Also here is an example of 4x disagreement between GiveWell and Founders Pledge, and an even bigger disagreement with RP, on a mass media campaign for family planning. Even the best in the business can disagree.
Sorry for this being a bit of a rave