I'd prefer to try with a go player, because as you say, in chess it's hard to exactly control the input to the network, it's easier in Go.

There's current best weights available. Not alphazero, but I would expect that issues would be general and so if there are issues with leela zero they may transfer and if you don't see issues with leela zero they're unlikely to exist in alpha zero (at least, if they do they may be very particular to subtle training differences).

Would be very interested to see what you find if you get the chance.

If you want to construct a particular position on the board, you'd likely need to use multiple steps, require the AI to play very particular moves and then the outcome would be a certain move from the AI. Even then, a simple incorrect classification doesn't help all that much, you need your opponent to make repeated mistakes.

I think in reality if you uncovered a type of move it wasn't expecting you are likely to uncover a new strategy in general rather than a trick. Image classification however lets you play uninterrupted with tiny pixel value changes, and you only need a single incorrect output to "win".