If you’re going to select interventions specifically to reduce the human population and have downstream consequences, it seems absolutely essential to take a broader view of the empirical consequences than in the linked report. E.g. among others, effects on wild animals (not mentioned but most immediate animal effects of this change will be on wild animals), future technological advancement, and global catastrophic risks have good cases for being far larger and plausibly of opposite sign to the effects discussed in the report but are not mentioned even as areas for further investigation.
We are very skeptical about being able to make any progress on far future effects of population given the time cap we put on this report and our general skepticism towards being able to make accurate far future predictions. We use something closest to a “weighted quantitative model” but would only do a more explicit model of this for the top charity ideas we investigate deeper.
I think this is evidence that the time-cap model for research is problematic in at least some ways. I don’t think you can ignore long-term consequences just because you don’t have time to think them through, and if you find yourself running out of time before you really have to publish a report, the report should be very inconclusive.
Broadly we have not considered WAS due to separate reports/views on how to deal with that (coming out soon). In short, epistemically, we tend to take a cluster view, one of which would be a cluster concerned with flow through effects. We think wild animal suffering will often be the most important consideration within flow through effects and we expect flow through effects to carry between 1% and 25% of our endline evaluation of the intervention’s promisingness. Overall, we think the effects other interventions have on wild animal suffering should be considered as a non-trivial factor, but not a dominating one. We will analyze it thoroughly in the next stage of research if this intervention would make to top 3 after shallow research of all asks we consider.
Couldn’t you say the same about GiveWell’s evaluation of AMF, TLYCS’s evaluation of PSI or the evaluation of any other charity or intervention that would predictably affect population sizes? ACE doesn’t consider impacts on wild animals for most of the charities/interventions it looks into, either, despite the effects of agriculture on wild animals.
My impression is that Charity Science/Entrepreneurship prioritizes global health/poverty and animal welfare, so we shouldn’t expect them to consider the effects on technological advancement or GCRs anymore than we should expect GiveWell, TLYCS or ACE to.
If you’re going to select interventions specifically to reduce the human population and have downstream consequences, it seems absolutely essential to take a broader view of the empirical consequences than in the linked report. E.g. among others, effects on wild animals (not mentioned but most immediate animal effects of this change will be on wild animals), future technological advancement, and global catastrophic risks have good cases for being far larger and plausibly of opposite sign to the effects discussed in the report but are not mentioned even as areas for further investigation.
We are very skeptical about being able to make any progress on far future effects of population given the time cap we put on this report and our general skepticism towards being able to make accurate far future predictions. We use something closest to a “weighted quantitative model” but would only do a more explicit model of this for the top charity ideas we investigate deeper.
I think this is evidence that the time-cap model for research is problematic in at least some ways. I don’t think you can ignore long-term consequences just because you don’t have time to think them through, and if you find yourself running out of time before you really have to publish a report, the report should be very inconclusive.
Broadly we have not considered WAS due to separate reports/views on how to deal with that (coming out soon). In short, epistemically, we tend to take a cluster view, one of which would be a cluster concerned with flow through effects. We think wild animal suffering will often be the most important consideration within flow through effects and we expect flow through effects to carry between 1% and 25% of our endline evaluation of the intervention’s promisingness. Overall, we think the effects other interventions have on wild animal suffering should be considered as a non-trivial factor, but not a dominating one. We will analyze it thoroughly in the next stage of research if this intervention would make to top 3 after shallow research of all asks we consider.
FWIW, this is aimed at developing countries.
Couldn’t you say the same about GiveWell’s evaluation of AMF, TLYCS’s evaluation of PSI or the evaluation of any other charity or intervention that would predictably affect population sizes? ACE doesn’t consider impacts on wild animals for most of the charities/interventions it looks into, either, despite the effects of agriculture on wild animals.
My impression is that Charity Science/Entrepreneurship prioritizes global health/poverty and animal welfare, so we shouldn’t expect them to consider the effects on technological advancement or GCRs anymore than we should expect GiveWell, TLYCS or ACE to.
They have worked on evaluating animal welfare, though, so it would be nice to see this work applied here for wild animals.
EDIT: Oh, is the concern that they’re looking at a more biased subset of possible effects (by focusing primarily on effects that seem positive)?
″ Oh, is the concern that they’re looking at a more biased subset of possible effects (by focusing primarily on effects that seem positive)? ”
Yes. It doesn’t mention other analyses that have come to opposite conclusions by considering effects on wild animals and long-term development.