Software engineers are primarily outcome-oriented.
Mathematicians are primarily understanding-oriented.
Leveraging AI to tackle new frontiers without true understanding converts mathematicians to engineers.
I usually hate analogies because they're imprecise.
But in this case, isn't use of llm / generative ai to tackle new frontiers just another instrument to be used to understand the universe?
An engineer picks up a telescope, and uses it to build new applied technologies, a scientist uses the data it produces to answer new mysteries.
No one's saying, "we have to be careful with the information the telescope produces".
Well at the end of the day, the point of trying to understand the universe is to achieve specific goals leveraging that understanding.
It seems to me that all of these hundreds of proofs we've seen recently are glorified academic exercises, whose purpose is curiosity for its own sake without any practical application, or we'd already hear about at least one of them being implemented to some gain somewhere. It's all woefully unimpressive. It's not like anything stops mathematicians from trying to find more elegant solutions to their machine solved pet problems, since that's what they were going to try and do anyway despite it being completely pointless in practice.
Actually both are outcome oriented and both can use AI to compress decades of progress. One camp accepts this naturally. Other camp is making their profession to be mysterious and spiritual to run away from the implications of AI
Social roles get created at the frontier of what isn't technologically feasible without a human, as culture develops around some form of human activity. Role A does B, role X does Y; I don't know, maybe its just time for new roles that didn't exist before.