[salty_biscuits]

If you count all the work in AI/ML then the criticism has been overwhelmingly in the other direction, i.e. to much "just trying stuff to see what happens" and not enough "really understanding what is going on". Always seemed like a weak criticism to me honestly. You can advance theory, or you can advance through experimental insight. Neither is the right or wrong path, just whichever seems like the best way to make progress given the state of current knowledge.

[kevinventullo]

Yeah, I feel ML would have been a more apt analogy than complexity theory. For some problems it's an ugly, "brute force" approach that works really really well.

[m463]

I think AI/ML has changed things.

I think Computer Science used to be more aligned with math, in the sense that the mathematics courses most people took in school were overwhelmingly symbol manipulation. Just like CS.

Now I think things are not only more data driven, any sort of "undertanding" might be prioritized away forever, unless some adversarial network requires it. :)