I think chess engines are an amazing thing to study. So much fundamental computer science is covered, from extremely low level CPU instructions to high level data structures and algorithms. There's no surprise to me that many of the greats have turned their eye to representing and solving chess, from Turing to Knuth. I strongly suspect you could teach an entire CS degree never stepping outside of chess.
Even now there are so many rich directions you could go in. For example, many people are working on explainability in machine learning, but I think in many applications you want to go even further and actually optimise a model to _teach humans_ not just explain its predictions. This is especially relevant to engines when making strategic moves rather than calculating short term tactics.
I also think engines as tools for match preparation could be much better. What if you could more easily set an engine to find forced draws in certain lines, or tailor an engine to find tricky lines that a particular opponent is less likely to follow correctly, or find and optimise for certain endgame structures an opponent is weak at? Doing this in ChessBase (a truly awful but necessary piece of software) is quite painful.
Even now there are so many rich directions you could go in. For example, many people are working on explainability in machine learning, but I think in many applications you want to go even further and actually optimise a model to _teach humans_ not just explain its predictions. This is especially relevant to engines when making strategic moves rather than calculating short term tactics.
I also think engines as tools for match preparation could be much better. What if you could more easily set an engine to find forced draws in certain lines, or tailor an engine to find tricky lines that a particular opponent is less likely to follow correctly, or find and optimise for certain endgame structures an opponent is weak at? Doing this in ChessBase (a truly awful but necessary piece of software) is quite painful.