I want to add something: It probably has been discussed before, but it occurs to me that when thinking about prioritisation in general it’s almost always better to think at the lowest level possible. That’s because the impact per dollar is only evaluable for specific interventions, and because causes that at first don’t appear particularly cost effective can hide particular interventions that are. And those particular interventions could be in principle even more cost effective than other interventions in causes that do appear cost effective overall. I think high-level cause prioritisation is mostly good for gaining a first superficial understanding of the promise of a particular class of altruistic interventions.
I disagree. If we are fairly certain, that the average intervention in Cause X is 10 times more effective than the average Intervention in Cause Y (For a comparision, 80000 hours currently believes, that AI-safety work is 1000 times as effective as global health), it seems like we should strongly prioritize Cause X. Even if there are some interventions in Cause Y, which are more effective, than the average intervention in Cause X, finding them is probably as costly as finding the most effective interventions in Cause X (Unless there is a specific reason, why evaluating cost effectiveness in Cause X is especially costly, or the distributions of Intervention effectiveness are radically different between both causes). Depending on how much we can improve on our current comparative estimates of cause effctiveness, the potential impact of doing so could be quite high, since it is essentially multiplies the effects of our lower level prioritization. Therefore it seems, like high to medium level prioritization in combination with low-level prioritization restricted to the best causes seems the way to go. On the other hand, it seems at least plausible, that we cannot improve our high-level prioritization significantly at the moment and should therefore focus on the lower level within the most effective causes.
Yes, maybe I exaggerated saying “almost always” or at least I have been too vague. If you haven’t any idea of specific interventions to evaluate, then a good way to go is to do superficial high level analyses first and then proceed with lower level ones. Sometimes the contrary could happen though, when a particular promising intervention is found without first investigating its cause area.
I want to add something: It probably has been discussed before, but it occurs to me that when thinking about prioritisation in general it’s almost always better to think at the lowest level possible. That’s because the impact per dollar is only evaluable for specific interventions, and because causes that at first don’t appear particularly cost effective can hide particular interventions that are. And those particular interventions could be in principle even more cost effective than other interventions in causes that do appear cost effective overall. I think high-level cause prioritisation is mostly good for gaining a first superficial understanding of the promise of a particular class of altruistic interventions.
I disagree. If we are fairly certain, that the average intervention in Cause X is 10 times more effective than the average Intervention in Cause Y (For a comparision, 80000 hours currently believes, that AI-safety work is 1000 times as effective as global health), it seems like we should strongly prioritize Cause X. Even if there are some interventions in Cause Y, which are more effective, than the average intervention in Cause X, finding them is probably as costly as finding the most effective interventions in Cause X (Unless there is a specific reason, why evaluating cost effectiveness in Cause X is especially costly, or the distributions of Intervention effectiveness are radically different between both causes). Depending on how much we can improve on our current comparative estimates of cause effctiveness, the potential impact of doing so could be quite high, since it is essentially multiplies the effects of our lower level prioritization. Therefore it seems, like high to medium level prioritization in combination with low-level prioritization restricted to the best causes seems the way to go. On the other hand, it seems at least plausible, that we cannot improve our high-level prioritization significantly at the moment and should therefore focus on the lower level within the most effective causes.
Yes, maybe I exaggerated saying “almost always” or at least I have been too vague. If you haven’t any idea of specific interventions to evaluate, then a good way to go is to do superficial high level analyses first and then proceed with lower level ones. Sometimes the contrary could happen though, when a particular promising intervention is found without first investigating its cause area.