Some related questions with slightly different framings:
What types/​lines of research do you expect would be particularly useful for informing the LTFF’s funding decisions?
Do you have thoughts on what types/​lines of research would be particularly useful for informing other funders’ funding decisions in the longtermism space?
Do you have thoughts on how the answers to those two questions might differ?
What types/​lines of research do you expect would be particularly useful for informing the LTFF’s funding decisions?
I’d be interested in better understanding the trade-off between independent vs established researchers. Relative to other donors we fund a lot of independent research. My hunch here is that most independent researchers are less productive than if they were working at organisations—although, of course, for many of them that’s not an option (geographical constraints, organisational capacity, etc). This makes me place a bit of a higher bar for funding independent research. Some other fund managers disagree with me and think independent researchers tend to be more productive, e.g. due to bad incentives in academic and industry labs.
I expect distillation style work to be particularly useful. I expect there’s already relevant research here: e.g. case studies of the most impressive breakthroughs, studies looking at different incentives in academic funding, etc. There probably won’t be a definitive answer, so it’d also be important that I trust the judgement of the people involved, or have a variety of people with different priors going in coming to similar conclusions.
Do you have thoughts on what types/​lines of research would be particularly useful for informing other funders’ funding decisions in the longtermism space?
While larger donors can suffer from diminishing returns, there are sometimes also increasing returns to scale. One important thing larger donors can do that isn’t really possible at the LTFF’s scale is to found new academic fields. More clarity into how to achieve this and have the field go in a useful direction would be great.
It’s still mysterious to me how academic fields actually come into being. Equally importantly, what predicts whether they have good epistemics, whether they have influence, etc? Clearly part of this is the domain of study (it’s easier to get rigorous results in category theory than economics; it’s easier to get policymakers to care about economics than category theory). But I suspect it’s also pretty dependent on the culture created by early founders and the impressions outsiders form of the field. Some evidence for this is that some very closely related fields can end up going in very different directions: e.g. machine learning and statistics.
Do you have thoughts on how the answers to those two questions might differ?
A key difference between the LTFF and some other funders is we receive donations on a rolling basis, and I expect these donations to continue to increase over time. By contrast, many major donors have an endowment to spend down. So for them it’s a really important question to know how to time those donations: how much should they give now, v.s. donate later? Whereas I think for us the case for just donating every $ we receive seems pretty strong (except for keeping enough of a buffer to even out short-term fluctuations in application quality and donation revenue).
Some related questions with slightly different framings:
What types/​lines of research do you expect would be particularly useful for informing the LTFF’s funding decisions?
Do you have thoughts on what types/​lines of research would be particularly useful for informing other funders’ funding decisions in the longtermism space?
Do you have thoughts on how the answers to those two questions might differ?
I’d be interested in better understanding the trade-off between independent vs established researchers. Relative to other donors we fund a lot of independent research. My hunch here is that most independent researchers are less productive than if they were working at organisations—although, of course, for many of them that’s not an option (geographical constraints, organisational capacity, etc). This makes me place a bit of a higher bar for funding independent research. Some other fund managers disagree with me and think independent researchers tend to be more productive, e.g. due to bad incentives in academic and industry labs.
I expect distillation style work to be particularly useful. I expect there’s already relevant research here: e.g. case studies of the most impressive breakthroughs, studies looking at different incentives in academic funding, etc. There probably won’t be a definitive answer, so it’d also be important that I trust the judgement of the people involved, or have a variety of people with different priors going in coming to similar conclusions.
While larger donors can suffer from diminishing returns, there are sometimes also increasing returns to scale. One important thing larger donors can do that isn’t really possible at the LTFF’s scale is to found new academic fields. More clarity into how to achieve this and have the field go in a useful direction would be great.
It’s still mysterious to me how academic fields actually come into being. Equally importantly, what predicts whether they have good epistemics, whether they have influence, etc? Clearly part of this is the domain of study (it’s easier to get rigorous results in category theory than economics; it’s easier to get policymakers to care about economics than category theory). But I suspect it’s also pretty dependent on the culture created by early founders and the impressions outsiders form of the field. Some evidence for this is that some very closely related fields can end up going in very different directions: e.g. machine learning and statistics.
A key difference between the LTFF and some other funders is we receive donations on a rolling basis, and I expect these donations to continue to increase over time. By contrast, many major donors have an endowment to spend down. So for them it’s a really important question to know how to time those donations: how much should they give now, v.s. donate later? Whereas I think for us the case for just donating every $ we receive seems pretty strong (except for keeping enough of a buffer to even out short-term fluctuations in application quality and donation revenue).