I think one aspect you can examine about a scientific field is it’s “spread”-ness of ideas and resources.
High energy particle physics is an interesting extrema here—there’s broad agreement in the field about building higher energy accelerators, and this means there can be lots of consensus about supporting a shared collaborative high energy accelerator.
I think a feature of mature scientific fields that “more consensus” can unlock more progress. Perhaps if there had been more consensus, the otherwise ill-fated superconducting super collider would have worked out. (I don’t know if other extenuating circumstances would still prevent it.)
I think a feature of less mature scientific fields that “more ideas” (and less consensus) would unlock more progress. In this case, we’re more limited about generating and validating new good ideas. One way this looks is that there’s not a lot of confidence with what to do with large sums of research funding, and instead we think our best bet is making lots of small bets.
My field (AI alignment) is a less mature scientific field in this way, I think. We don’t have a “grand plan” for alignment, which we just need to get funding. Instead we have a fractal of philanthropic organizations empowering individual grantmakers to try to get small and early ideas off the ground with small research grants.
A couple thoughts, if this model does indeed fit:
There’s a lot more we could do to orienting as a field with “the most important problem is increasing the rate of coming up with good research ideas”. In addition to being willing to fund lots of small and early stage research, I think we could factorize and interrogate the skills and mindsets needed to do this kind of work. It’s possible that this is one of the most important meta-skills we need to improve as a field.
I also think this could be more of a priority when “field building”. When recruiting or trying to raise awareness of the field, it would be good to consider more focus or priority on places where we expect to find people who are likely to be good generators of new ideas. I think one of the ways this looks is to focus on more diverse and underrepresented groups.
Finally, at some point it seems like we’ll transition to “more mature” as a field, and it’s good to spend some time thinking about what would help that go better. Understanding the history of other fields making this transition, and trying to prepare for predicted problems/issues would be good here.
More Ideas or More Consensus?
I think one aspect you can examine about a scientific field is it’s “spread”-ness of ideas and resources.
High energy particle physics is an interesting extrema here—there’s broad agreement in the field about building higher energy accelerators, and this means there can be lots of consensus about supporting a shared collaborative high energy accelerator.
I think a feature of mature scientific fields that “more consensus” can unlock more progress. Perhaps if there had been more consensus, the otherwise ill-fated superconducting super collider would have worked out. (I don’t know if other extenuating circumstances would still prevent it.)
I think a feature of less mature scientific fields that “more ideas” (and less consensus) would unlock more progress. In this case, we’re more limited about generating and validating new good ideas. One way this looks is that there’s not a lot of confidence with what to do with large sums of research funding, and instead we think our best bet is making lots of small bets.
My field (AI alignment) is a less mature scientific field in this way, I think. We don’t have a “grand plan” for alignment, which we just need to get funding. Instead we have a fractal of philanthropic organizations empowering individual grantmakers to try to get small and early ideas off the ground with small research grants.
A couple thoughts, if this model does indeed fit:
There’s a lot more we could do to orienting as a field with “the most important problem is increasing the rate of coming up with good research ideas”. In addition to being willing to fund lots of small and early stage research, I think we could factorize and interrogate the skills and mindsets needed to do this kind of work. It’s possible that this is one of the most important meta-skills we need to improve as a field.
I also think this could be more of a priority when “field building”. When recruiting or trying to raise awareness of the field, it would be good to consider more focus or priority on places where we expect to find people who are likely to be good generators of new ideas. I think one of the ways this looks is to focus on more diverse and underrepresented groups.
Finally, at some point it seems like we’ll transition to “more mature” as a field, and it’s good to spend some time thinking about what would help that go better. Understanding the history of other fields making this transition, and trying to prepare for predicted problems/issues would be good here.