Even if transfer learning is a thing that could work, in any given domain that doesn’t have terrible feedback loops, would it not be more efficient to just apply the deliberate practice and metacognition to the domain itself? Like, if I’m trying to learn how to solve puzzle games, would it not be more efficient to just practice solving puzzle games than to do physics problems and try to generalise? Or if you think that this sort of general rationality training is only important for ‘specialising in problems we don’t understand’ type stuff with bad feedback loops, how would you even figure out whether or not it’s working given the bad feedback loops? Like sure, maybe you measure how well people perform at some legibly measurable tasks after the rationality training and they perform a bit better, but the goal in the first place was to use the rationality training’s good feedback loops to improve in domains with bad feedback loops, and those domains seem likely to be different enough that a lot of rationality lessons or whatever just don’t generalise well.
It just feels to me like the world where transfer learning works well enough to be worth the investment looks a lot different wrt how specialised the people who are best at X are for any given X. I can’t off the top of my head think of anyone who became the best at their thing by learning very general skills first and then applying them to their domain, rather than just focusing really hard on whatever their thing was.
would it not be more efficient to just apply the deliberate practice and metacognition to the domain itself
Yes, if that’s the only thing you want to learn. The more domains you want to understand the more it makes sense to invest in cross-domain meta skills.
Even if transfer learning is a thing that could work, in any given domain that doesn’t have terrible feedback loops, would it not be more efficient to just apply the deliberate practice and metacognition to the domain itself? Like, if I’m trying to learn how to solve puzzle games, would it not be more efficient to just practice solving puzzle games than to do physics problems and try to generalise? Or if you think that this sort of general rationality training is only important for ‘specialising in problems we don’t understand’ type stuff with bad feedback loops, how would you even figure out whether or not it’s working given the bad feedback loops? Like sure, maybe you measure how well people perform at some legibly measurable tasks after the rationality training and they perform a bit better, but the goal in the first place was to use the rationality training’s good feedback loops to improve in domains with bad feedback loops, and those domains seem likely to be different enough that a lot of rationality lessons or whatever just don’t generalise well.
It just feels to me like the world where transfer learning works well enough to be worth the investment looks a lot different wrt how specialised the people who are best at X are for any given X. I can’t off the top of my head think of anyone who became the best at their thing by learning very general skills first and then applying them to their domain, rather than just focusing really hard on whatever their thing was.
Yes, if that’s the only thing you want to learn. The more domains you want to understand the more it makes sense to invest in cross-domain meta skills.