Not really, humans barely provide insight (if anything), which chess engines don’t already consider. Deep Blue could evaluate 200 million different moves... per second. And that’s from 1997.

The few and rare times an engine gets funky is usually in end-game positions where the engine can’t seem to find a sacrifice to win the game and will output a current position as drawn. These cases are few and I very much doubt that a human would be able to find these moves in an actual match.

Now if you’re talking about the way the chess engine learns, it can learn in two different ways: without human help (learning completely on its own giving it nothing but the rules which is how AlphaGo works), or with human aid (through chess theory accumulated over centuries of human matches that these engines have built in as part of their evaluations). Things get very interesting.

I’d recommend you to look up a few games between AlphaGo and Stockfish, which embody these two different philosophies and battle it to the teeth and bones. The matches are brilliant. I would say though that it seems like AlphaGo (learning the game entirely through scratch without human help) has seemed to triumph more times than Stockfish and with the nature of these systems, I’d suspect it to continue that trend.