Thanks for all these great points (Derek sent these to me privately and I suggested it would be valuable for him to share them here for other interested parties). My brief replies, in order, to those comments that weren’t just informative:
1. fair cop. I think I was lazily using those as I first compiled these numbers back in 2015 (at the start of my PhD).
2. agree it’s unclear what these breakthrough drugs imply for EA
5. it makes sense to compare to GW because that’s who our audience is. People who already think GW is irrelevant and focus on e.g. far future are unlikely to be interested in the analysis here.
6. yes, there are probably flaws in the SM analysis. I look forward to mine being made obsolete in due course. I note that my points on negative spillovers should cause us to downgrade the effectiveness of anti-poverty charities.
8. agree, but this applies to mental health intervention too: their effects could also be larger if we take spillovers into account, e.g. reduced strain on family who care for them.
9. As I’m sympathetic to person-affecting views, I’m not too concerned about the long-term anyway. Even if I were a long-termist, the problem with including indirect effects is that it tends to make the analysis incredibly ‘hand-wavey’ (“ah, saving lives speeds up growth, which is bad for climate change, etc.). I think it makes sense to calculate what can easily be calculated first. If you can’t look anywhere else, at least look under the lamppost.
10. Probably correct. A better analysis would factor in how the LS of AMF recipients would change over their lives (presumably upwards and societal conditions improve)
11. I agree LS is not the ideal thing. If we had affect scores, I would say we use those, but we don’t! (“slaves to the data” etc)
12. I also agree moving to affect would make mental health score better than poverty. I left that out because I thought the analysis was complicated enough already.
Thanks for all these great points (Derek sent these to me privately and I suggested it would be valuable for him to share them here for other interested parties). My brief replies, in order, to those comments that weren’t just informative:
1. fair cop. I think I was lazily using those as I first compiled these numbers back in 2015 (at the start of my PhD).
2. agree it’s unclear what these breakthrough drugs imply for EA
5. it makes sense to compare to GW because that’s who our audience is. People who already think GW is irrelevant and focus on e.g. far future are unlikely to be interested in the analysis here.
6. yes, there are probably flaws in the SM analysis. I look forward to mine being made obsolete in due course. I note that my points on negative spillovers should cause us to downgrade the effectiveness of anti-poverty charities.
8. agree, but this applies to mental health intervention too: their effects could also be larger if we take spillovers into account, e.g. reduced strain on family who care for them.
9. As I’m sympathetic to person-affecting views, I’m not too concerned about the long-term anyway. Even if I were a long-termist, the problem with including indirect effects is that it tends to make the analysis incredibly ‘hand-wavey’ (“ah, saving lives speeds up growth, which is bad for climate change, etc.). I think it makes sense to calculate what can easily be calculated first. If you can’t look anywhere else, at least look under the lamppost.
10. Probably correct. A better analysis would factor in how the LS of AMF recipients would change over their lives (presumably upwards and societal conditions improve)
11. I agree LS is not the ideal thing. If we had affect scores, I would say we use those, but we don’t! (“slaves to the data” etc)
12. I also agree moving to affect would make mental health score better than poverty. I left that out because I thought the analysis was complicated enough already.