I expect the optimal fraction of resources going to research being lower for less neglected areas, whose ideas space has been more explored. So, for example, I guess the fraction of resources going into research should be higher for AI safety than for global health and development.
That being said, as you pointed out, if the current fraction of resources going into research is lower than the optimal fraction f, at the margin, it makes sense to direct more resources into research. This could mean, for instance, EA funders of global health and develoment moving much more than f to research.
I think it is also worth noting that, if I understand correctly, this analysis assumes the budget of each cause area is constant. However, moving resources to different activities (research or not) may also influence future funding. If non-research activities lead to more funding than research ones (I do not know whether this is the case), the optimal fraction of resources going to research will tend to decrease.
I agree that the optimal percentage of research funding is higher/lower for areas where less/more science and R&D have been done so far. We don’t really know yet how different areas correspond to which of the simulated scenarios. I think establishing this correspondence will be a crucial next step in our project. Moreover, some topics and potential interventions within a broad cause area, such as global health and development, might have been researched much less than others. Therefore, it probably makes most sense to apply our analysis at the level of specific research topics or interventions.
Thank you for pointing out that the amount of available resources can change. Contrary to your intuition, I suspect that taking this into account would tilt the analysis in favor of even more research if the amount of funding an area receives depends on the cost-effectiveness and scalability of its best intervention. Successful research results in new interventions that are more cost-effective or more scalable than the best previous ones. This can significantly increase how much the cause area appeals to the EA community and how much finding it can absorb. Suppose, research in a cause area without any highly cost-effective interventions leads to the development of an intervention that is more cost-effective than the best interventions in any other area. That would probably increase the amount of money that will be donated to the cause. Or suppose that the research makes a highly effective intervention much more scalable. That would likely increase the amount of money that will be donated to the corresponding cause as well.
Great analysis!
I expect the optimal fraction of resources going to research being lower for less neglected areas, whose ideas space has been more explored. So, for example, I guess the fraction of resources going into research should be higher for AI safety than for global health and development.
That being said, as you pointed out, if the current fraction of resources going into research is lower than the optimal fraction f, at the margin, it makes sense to direct more resources into research. This could mean, for instance, EA funders of global health and develoment moving much more than f to research.
I think it is also worth noting that, if I understand correctly, this analysis assumes the budget of each cause area is constant. However, moving resources to different activities (research or not) may also influence future funding. If non-research activities lead to more funding than research ones (I do not know whether this is the case), the optimal fraction of resources going to research will tend to decrease.
Thank you, Vasco!
I agree that the optimal percentage of research funding is higher/lower for areas where less/more science and R&D have been done so far. We don’t really know yet how different areas correspond to which of the simulated scenarios. I think establishing this correspondence will be a crucial next step in our project. Moreover, some topics and potential interventions within a broad cause area, such as global health and development, might have been researched much less than others. Therefore, it probably makes most sense to apply our analysis at the level of specific research topics or interventions.
Thank you for pointing out that the amount of available resources can change. Contrary to your intuition, I suspect that taking this into account would tilt the analysis in favor of even more research if the amount of funding an area receives depends on the cost-effectiveness and scalability of its best intervention. Successful research results in new interventions that are more cost-effective or more scalable than the best previous ones. This can significantly increase how much the cause area appeals to the EA community and how much finding it can absorb. Suppose, research in a cause area without any highly cost-effective interventions leads to the development of an intervention that is more cost-effective than the best interventions in any other area. That would probably increase the amount of money that will be donated to the cause. Or suppose that the research makes a highly effective intervention much more scalable. That would likely increase the amount of money that will be donated to the corresponding cause as well.
That makes sense to me, thanks for clarifying!