Given equal background and motivation, there is a lot less inequality in the rates human learn new tasks, compared to the inequality in how humans perform learned tasks.
Huh, my guess is the opposite. That is, all expert plumbers are similarly competent at performing tasks, and the thing that separate a bright plumber from a dull plumber is how quickly they become expert.
Quite possibly we’re looking at different tasks? I’d be interested in examples of domains where this sort of thing has been quantized and you see the hypothesized relationship (where variation in learning speed is substantially smaller than variation in performance). Most of the examples I can think of that seem plausible are exercise-related, where you might imagine people learn proper technique with a tighter distribution than the underlying strength distribution, but this is cheating by using intellectual and physical faculties as separate sources of variation.
Huh, my guess is the opposite. That is, all expert plumbers are similarly competent at performing tasks, and the thing that separate a bright plumber from a dull plumber is how quickly they become expert.
I don’t know much about plumbing, but a possible explanation here is that there’s a low skill ceiling in plumbing. If we were talking about chess, or Go, or other tasks with high skill ceilings, it definitely seems incorrect that the brightest players won’t be much better than the dullest players.
This also strikes me as backwards, and the literature seems to back this up. Learning rates seem to differ a lot between different people, and also be heavily g-loaded.
Do you have thoughts on what I said here? I agree that learning rates differ between people, but I don’t think that contradicts what I said? Perhaps you disagree. From my perspective, what matters more is whether learning rates have more or less variance than the variance of skill on learned tasks (especially those with high skill-ceilings).
Huh, my guess is the opposite. That is, all expert plumbers are similarly competent at performing tasks, and the thing that separate a bright plumber from a dull plumber is how quickly they become expert.
Quite possibly we’re looking at different tasks? I’d be interested in examples of domains where this sort of thing has been quantized and you see the hypothesized relationship (where variation in learning speed is substantially smaller than variation in performance). Most of the examples I can think of that seem plausible are exercise-related, where you might imagine people learn proper technique with a tighter distribution than the underlying strength distribution, but this is cheating by using intellectual and physical faculties as separate sources of variation.
I don’t know much about plumbing, but a possible explanation here is that there’s a low skill ceiling in plumbing. If we were talking about chess, or Go, or other tasks with high skill ceilings, it definitely seems incorrect that the brightest players won’t be much better than the dullest players.
This also strikes me as backwards, and the literature seems to back this up. Learning rates seem to differ a lot between different people, and also be heavily g-loaded.
Do you have thoughts on what I said here? I agree that learning rates differ between people, but I don’t think that contradicts what I said? Perhaps you disagree. From my perspective, what matters more is whether learning rates have more or less variance than the variance of skill on learned tasks (especially those with high skill-ceilings).