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It would be an interesting breakthrough if Alpha Go could explain its reasoning for various plays.

Maybe one day we'll write a deep net that captions other deep nets. Who will build the supervised learning training set though?

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Since alphago plays the game differently (optimizing on odds to win, even if by a little, instead of the human method which involves intuition about shapes), it may be that its explanation if it were programmed to provide one would not provide any human readable 'insight' which an expert could then take to improve his or her game. Imagine a simpler example, some optimization solution using multiple dimensions and linear algebra. A description of how this works would be unreadable to most people. Since most readable language operates in the world of at most four dimensions without introducing jargon, this is the real problem, not that the program cannot explain itself.

At the higher level it isn’t just shapes. The human player uses the shapes the help estimate the future value of any group of stones. They are running a priority queue of likelihood’s for each part of the board. When they resign that probability has dropped to zero.

If you’ve played against a dan player a few times, you might have had the experience of them ignoring a move you made and play elsewhere. That’s what happened. It’s also probably the moment you lost the game...

I've played against dan players who describe this decision (tenuki, like the tenuki suit in mario, or "to deceptively play elsewhere") as mainly an intuition about "balance" which they somewhat vaguely describe as deciding that although the shape may not be good, the context of the shape is balanced, so it is OK to leave it be. According to Michael Redmond's commentary during the alphago matches (paraphrasing) often times the ability to calculate value is one of the last skills professionals actually master, far behind the concepts of shape and balance, and even among them some rely more on that skill than others. Lee Sedol, as an example, is relatively weak in this regard, Lee Chang-ho, on the other hand, seemed to be a prodigy just at this skill alone, allowing him to play a style which otherwise most observers called 'rigid'. So it is in fact common to find relatively high level amateur players who aren't good at calculating value.

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