Hi Dan,
Thanks for writing this! Some (weakly-held) points of skepticism:
*OTOH, I think Eli is also hinting at a definition of forecasting that is too narrow. I do think that generating models/rationales is part of forecasting as it is commonly understood (including in EA circles), and certainly don't agree that forecasting by definition means that little effort was put into it!
Maybe the right place to draw the line between forecasting rationales and “just general research” is asking “is the model/rationale for the most part tightly linked to the numerical forecast?" If yes, it's forecasting, if not, it's something else.
As the program is about forecasting, what is your stance on the broader field of foresight & futures studies? Why is forecasting more promising than some other approaches to foresight?
We are open to considering projects in “forecasting-adjacent" areas, and projects that combine forecasting with ideas from related fields are certainly well within the scope of the program.
As for projects that would exclusively rely on other approaches: My worry is that non-probabilistic foresight techniques typically don’t have more to show in terms of evidence for their effectiveness, while being more ad hoc from a theoretical perspective.
Just confirming that informing our own decisions was part of the motivation for past grants, and I expect it to play an important role for our forecasting grants in the future.
[The forecasting money] seems to have overwhelmingly gone to community forecasting sites like Manifold and Metaculus. I don't see anything like "paying 3 teams of 3 forecasters to compete against each other on some AI timelines questions".
That’s directionally true, but I think “overwhelmingly” isn’t right.
I’m glad to see the debate on decision relevance in the comments! I think that if we end up considering forecasting a successful focus area in 5-10 years, thinking hard about the value-add to decision-making will likely have played a crucial role in this success.
As for my own view, I do agree that judgmental / subjective probability forecasting hasn’t been as much of a success story as one might have expected about 10 years ago. I also agree that many of the stories people tell about the impact of forecasting naturally raise questions like “so why isn’t this a huge industry now? Why is this project a non-profit?”. We are likely to ask questions of this kind to prospective grantees way more often than grantmakers in other focus areas.
However, I (unsurprisingly) also disagree with the stronger claim that the lack of a large judgmental forecasting industry is conclusive evidence that forecasting doesn’t provide value, and is just an EA hobby horse. While I don’t have capacity to engage in this debate deeply, a few points of rebuttal:
I think it’s borderline whether reports of this type are forecasting as commonly understood, but would personally lean no in the specific cases you mention (except maybe the bio anchors report).
I really don’t think that this intuition is driven by the amount of time or effort that went into them, but rather the percentage of intellectual labor that went into something like “quantifying uncertainty” (rather than, e.g. establishing empirical facts, reviewing the literature, or analyzing the structure of commonly-made arguments).
As for our grantmaking program: I expect we’ll have a more detailed description of what we want to cover later this year, where we might also address points about the boundaries to worldview investigations.