Comment by oytis

11 hours ago

It has been best at chess for quite a while. Yet everyone knows who is Magnus Carlsen, even though at no point of his career he was stronger than the machine

Magnus Carlsen plays fellow humans at the game because people still care about human competitions. What motivation would a mathematician have for solving already solved problems by hand? Can you imagine someone spending years working on a proof for an already-proved theorem just in case it leads to new insight?

  • If insights and human understanding are more important than specific results, I don't see why people should stop producing insights and human understanding. "Working on a proof" in today's sense of trying to come up with a proof before others probably stops being useful, other ways of working will be needed

  • Of course not. I'm so tired of the chess analogy. It was always a game and it was always performative.

    Research is fundamentally different. We are seeing the erosion of specific needs for thinking at depth. AI is the automobile for the mind. There will 100% be undesirable consequences and selective atrophy of cognitive abilities once prized. This is a loss. There's no getting the cat back in the bag at this point so long as the objective dimension of work, as in object opposed to subject, is held as the most important.

    SWEs felt this same crisis late last year. Now it's the mathematicians. They won't be the last.

    • actually I think the whole point is we're finding that the chess analogy to math is in fact quite apt. Math is just an extremely complex game. Its rules can be written down and there are win conditions. It's really not far fetched to think that through information theory, a reasonable measure of depth and beauty to a definition or conjecture can be defined. Then the game is simply to maximize the number of such artifacts produced of high depth and beauty along with proofs of the relevant conjectures.

      Philosophers I'm sure can debate this back and forth but it seems probable that some things we thought were ineffable are in fact quantifiable to a degree, and now we have the technology and the machines to bring that to the logical conclusion.