Lazy semi-tangential reply: I recently gave a presentation that was partly about how I’ve used forecasting in my nuclear risk research and how I think forecasting could be better used in research. Here are the slides and here’s the video. Slides 12-15 / minutes 20-30 are most relevant.
I also plan to, in ~1 or 2 months, write and publish a post with meta-level takeaways from the sprawling series of projects I ended up doing in collaboration with Metaculus, which will have further thoughts relevant to your question.
(Also keen to see answers from other people at RP.)
We at Rethink Priorities definitely have made an increasingly large effort to include forecasting in our work. In particular, we just recently have been running a large Nuclear Risks Tournament on Metaculus. My guess is that the reasons we don’t have even more forecasting relates to not all of our researchers being experienced forecasters and it hasn’t been a sufficient priority to generate sufficiently useful and decision-relevant forecasting questions for every research piece.
What are the bottlenecks to using forecasting better in your research?
Lazy semi-tangential reply: I recently gave a presentation that was partly about how I’ve used forecasting in my nuclear risk research and how I think forecasting could be better used in research. Here are the slides and here’s the video. Slides 12-15 / minutes 20-30 are most relevant.
I also plan to, in ~1 or 2 months, write and publish a post with meta-level takeaways from the sprawling series of projects I ended up doing in collaboration with Metaculus, which will have further thoughts relevant to your question.
(Also keen to see answers from other people at RP.)
We at Rethink Priorities definitely have made an increasingly large effort to include forecasting in our work. In particular, we just recently have been running a large Nuclear Risks Tournament on Metaculus. My guess is that the reasons we don’t have even more forecasting relates to not all of our researchers being experienced forecasters and it hasn’t been a sufficient priority to generate sufficiently useful and decision-relevant forecasting questions for every research piece.