No, it isn't. The top humans are much better at Go than they were four years ago, largely due to learning from the new engines. If it were all just about sampling the phase space zillions of times, this would not be the case.
This is interesting to me ... how exactly is this assessed ...?
Do people keep around versions of “alpha go year 2017” and play against it in order to measure human improvement over time?
If the basis for observing improvement has become “I can beat old versions of the ai more reliably than I used to be able to” or if I have learned to beat players who have not studied alpha zero I suppose that’s a form of usefully learning “about go” by analyzing the games played by alpha zero ...
I wonder if we might ever arrive at a point where human vs fixed-year x ai performance at go pretty much stops increasing over time ...?
I admit that I do not have a quantitative measure to support my claim (as you note, constructing one is difficult). But qualitatively:
1) People have learned a lot from new engines: joseki (corner patterns), general strategy (e.g., moves on the side are now considered less valuable, making large moyos (largely empty space loosely surrounded by your stones) is less attractive because AIs have demonstrated that they're more invadable than previously thought) and are able to actually explain the new principles in human terms.
2) All go professionals now play in the new style, to some degree; ones who tried to continue in the old pre-AI style performed badly.
So I am comfortable claiming that human play has improved by learning from the new engines.
I'm not aware of a single "official" name for it that everyone uses, like the Hypermodern style of chess in the early 20th century. In English, people say things "AI-inspired" or "AlphaGo style" (although a lot of the ideas come not from AlphaGo directly but from the public engines that followed in its wake).
Do people keep around versions of “alpha go year 2017” and play against it in order to measure human improvement over time?
If the basis for observing improvement has become “I can beat old versions of the ai more reliably than I used to be able to” or if I have learned to beat players who have not studied alpha zero I suppose that’s a form of usefully learning “about go” by analyzing the games played by alpha zero ...
I wonder if we might ever arrive at a point where human vs fixed-year x ai performance at go pretty much stops increasing over time ...?