Regarding your “outside view” point: I agree with what you say here, but think it cannot directly undermine my original “outside view” argument. These clarifications may explain why:
My original outside view argument appealed to the process by which certain global health interventions such as distributing bednets have been selected rather than their content. The argument is not “global health is a different area from economic growth, therefore a health intervention is unlikely to be optimal for accelerating growth”; instead it is “an intervention that has been selected to be optimal according to some goal X is unlikely to also be optimal according to a different goal Y”.
In particular, if GiveWell had tried to identify those interventions that best accelerate growth, I think my argument would be moot (no matter what interventions they had come up with, in particular in the hypothetical case where distributing bednets had been the result of their investigation).
In general, I think that selecting an intervention that’s optimal for furthering some goal needs to pay attention to all of importance, tractability, and neglectedness. I agree that it would be bad to exclusively rely on the heuristics “just focus on the most important long-term outcome/risk” when selecting longtermist interventions, just as it would be bad to just rely on the heuristics “work on fighting whatever disease has the largest disease burden globally” when selecting global health interventions. But I think these would just be bad ways to select interventions, which seems orthogonal to the question when an intervention selected for X will also be optimal for Y. (In particular, I don’t think that my original outside view argument commits me to the conclusion that in the domain of AI safety it’s best to directly solve the largest or most long-term problem, whatever that is. I think it does recommend to deliberately select an intervention optimized for reducing AI risk, but this selection process should also take into account feedback loops and all the other considerations you raised.)
The main way I can see to undermine this argument would be to argue that a certain pair of goals X and Y is related in such a way that interventions optimal for X are also optimal for Y (e.g., X and Y are positively correlated, though this in itself wouldn’t be sufficient). For example, in this case, such an argument could be of the type “our best macroeconomic models predict that improving health in currently poor countries would have a permanent rate effect on growth, and empirically it seems likely that the potential for sustained increases in the growth rate is largest in currently poor countries” (I’m not saying this claim is true, just that I would want to see something like this).
Ok, I understand your point better now, and find that it makes sense. To summarize, I believe that the art of good planning to a distant goal is to find a series of intermediate targets that we can focus on, one after the other. I was worried that your argument could be used against any such strategy. But in fact your point is that as it stands, health interventions have not been selected by a “planner” who was actually thinking about the long-term goals, so it is unlikely that the selected interventions are the best we can find. That sounds reasonable to me. I would really like to see more research into what optimizing for long-term growth could look like (and what kind of “intermediate targets” this would select). (There is some of this in Christiano’s post, but there is clearly room for more in-depth analysis in my opinion.)
Regarding your “outside view” point: I agree with what you say here, but think it cannot directly undermine my original “outside view” argument. These clarifications may explain why:
My original outside view argument appealed to the process by which certain global health interventions such as distributing bednets have been selected rather than their content. The argument is not “global health is a different area from economic growth, therefore a health intervention is unlikely to be optimal for accelerating growth”; instead it is “an intervention that has been selected to be optimal according to some goal X is unlikely to also be optimal according to a different goal Y”.
In particular, if GiveWell had tried to identify those interventions that best accelerate growth, I think my argument would be moot (no matter what interventions they had come up with, in particular in the hypothetical case where distributing bednets had been the result of their investigation).
In general, I think that selecting an intervention that’s optimal for furthering some goal needs to pay attention to all of importance, tractability, and neglectedness. I agree that it would be bad to exclusively rely on the heuristics “just focus on the most important long-term outcome/risk” when selecting longtermist interventions, just as it would be bad to just rely on the heuristics “work on fighting whatever disease has the largest disease burden globally” when selecting global health interventions. But I think these would just be bad ways to select interventions, which seems orthogonal to the question when an intervention selected for X will also be optimal for Y. (In particular, I don’t think that my original outside view argument commits me to the conclusion that in the domain of AI safety it’s best to directly solve the largest or most long-term problem, whatever that is. I think it does recommend to deliberately select an intervention optimized for reducing AI risk, but this selection process should also take into account feedback loops and all the other considerations you raised.)
The main way I can see to undermine this argument would be to argue that a certain pair of goals X and Y is related in such a way that interventions optimal for X are also optimal for Y (e.g., X and Y are positively correlated, though this in itself wouldn’t be sufficient). For example, in this case, such an argument could be of the type “our best macroeconomic models predict that improving health in currently poor countries would have a permanent rate effect on growth, and empirically it seems likely that the potential for sustained increases in the growth rate is largest in currently poor countries” (I’m not saying this claim is true, just that I would want to see something like this).
Ok, I understand your point better now, and find that it makes sense. To summarize, I believe that the art of good planning to a distant goal is to find a series of intermediate targets that we can focus on, one after the other. I was worried that your argument could be used against any such strategy. But in fact your point is that as it stands, health interventions have not been selected by a “planner” who was actually thinking about the long-term goals, so it is unlikely that the selected interventions are the best we can find. That sounds reasonable to me. I would really like to see more research into what optimizing for long-term growth could look like (and what kind of “intermediate targets” this would select). (There is some of this in Christiano’s post, but there is clearly room for more in-depth analysis in my opinion.)
.