"we estimated the time trends of decision quality only for the decisions that differed from the optimal AI decisions." which I take to mean that the graph above shows only the improved decision quality of moves that are not direct memorizations of moves done by AIs?
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Graph of decision quality among professional Go players. A sudden increase after AlphaGo. It is not only because they are learning from the AI. Players are suddenly inventing new moves at a faster rate too!
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I saw the graph here, which links to original study:
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Ok, so this is interesting: it seems maybe the quality improved not after AlphaGo, but after the release of open source versions. Because they allowed players to look under the hood and understand the strategy. Just seeing the AI moves was not enough.
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The significant improvements seems to have come not after May 2016 when AlphaGo was released but after October 2017 when Leela Zero was open sourced.
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There is a parallel here to cognitive apprenticeship theory, ie the idea that the reason cognitive skills are hard to learn is that we can't see them so you should externalize them for students. For humans to learn from AIs, perhaps making reasoning explicit is needed.
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The data is from Games of Go on Disk which transcribes games from pro tournaments. I suspect that it is pretty hard to cheat on a live pro tournament, but not sure what precautions they take.
@phokarlsson
That paper does not even once (that I can see) mention the hypothesis that better go AIs allow for easier cheating.
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I collected my thoughts in more detail here.
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