I'm confident it's an amplifier for people who know how learning works and already do a lot of it, successfully. However the level of "learning fluency" I'm talking about isn't reached for many until late college or grad school, and sometimes not at all. So I'm not surprised by the quoted results for 12-18 year olds.
How would you prove/disprove this assumption without falling into a True Scotsman fallacy?
It would not prove that "the results depend on the operator". To prove this (and figure out the traits that make a proficient operator) you would either need a massive dataset to which you'd apply some machine learning to figure out the correlations, or at least you'd need a hypothesis on the traits you want to test.
Do left-handed people perform better with LLMs? Analytical thinkers? Dyslexic people?
It's not enough to just claim "some individuals will perform better with these tools" without any notion of who does, and whether it's possible to become one of these people, and what is the expected gain in this group.
Otherwise, sure, we could sell unsecured chainsaws as a tool for making ice sculptures and observe that "some people" are indeed more proficient at not getting their face cut off ; but if the tool is being marketed to schools, such a vague statement is not helpful in making a case for it.
My only point was I think it's possible to do. I personally think it's pretty clear. And there's nothing special about AI. In rural places, you could replace it with "access to books" or "access to a good tutor" and so on.
I also think you'd see the same effect with "motivation" (if you could test it), with performance on standardized tests, and with grades. AI will boost the better (by these metrics) students more.
It seems that the students who had the most skill and motivation from the start, have the most to lose.
The discussion is about "AI", so common sense is out the window. These people's professional reputations depend on addict-level "AI" usage remaining socially acceptable.