"Attempting a comeback" is a completely different task that usual, though.
When you're winning, a good move has a mathematical definition; it's a move that, given optimal play by both sides, will lead to victory for you. Computers aren't powerful enough to be able to calculate exactly what moves those are, but it's at least well-defined in a way that they know what they're looking for.
When you're losing, there's zero moves that, given optimal play by both sides, will lead to victory for you (so all moves are equally "bad" in a mathematical sense). Instead, "attempting a comeback" involves hoping your opponent will mess up some way, so in that sense, what constitutes a good move isn't mathematical but more about predicting how your opponent thinks and where they might mess up.
AlphaGo has mostly trained by playing itself, so the ways it thinks its opponent might mess up are probably completely different from how an actual human messes up.
When you're winning, a good move has a mathematical definition; it's a move that, given optimal play by both sides, will lead to victory for you. Computers aren't powerful enough to be able to calculate exactly what moves those are, but it's at least well-defined in a way that they know what they're looking for.
When you're losing, there's zero moves that, given optimal play by both sides, will lead to victory for you (so all moves are equally "bad" in a mathematical sense). Instead, "attempting a comeback" involves hoping your opponent will mess up some way, so in that sense, what constitutes a good move isn't mathematical but more about predicting how your opponent thinks and where they might mess up.
AlphaGo has mostly trained by playing itself, so the ways it thinks its opponent might mess up are probably completely different from how an actual human messes up.