Why can't academia deal with AI?

It’s old news by now, but OpenAI solved 372 open math problems. They released the results suddenly, and the response was equally swift and contentious. Fields Medalists put out a letter calling for attention to what they call a “severe misalignment” between mathematics and AI companies. Their central claim is that mathematics works towards collective understanding, and that more solutions alone don’t advance that goal. Soon after, OpenAI committed millions of dollars to damage control to help mathematicians use AI. Much has already been said about this letter, and I suggest that anyone interested read it themselves, so I will cling to just one idea from the joint statement: “We are witnessing a general threat to intellectual work.” The following is a collection of reflections attempting to address this claim, each coming from my own experiences in my department and university, alongside trends I’ve picked up from national reports. Some of it’s intuition, some of it’s observation, and I’m sure at other institutions the state of the discourse might be quite different. Still, everywhere I look, AI-use seems to be a persistent issue. I want to consider why that is, and why it feels lik