alt Hacker NewsI guess as a physicist I am more hopeful - every revolution in how the world is understood (by humans) has been driven by new tools and data. Being able to measure single quanta, for instance, showed us just how weird and counter-intuitive the Universe can be. I think AI might do something similar for mathematics - make connections that a human brain might have missed, and so advance human knowledge.
But I totally get the anxiety - it's a real John Henry (https://en.wikipedia.org/wiki/John_Henry_(folklore)) moment for the mathematics field. Clearly this is going to restructure how mathematicians are going to be trained and how they work.
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The issue is when humans no longer understand what AI is telling us and then there is no real way to verify what we think we know, or at least what AI says.
We can't audit what we don't know.
I think AI will turn out to be quite different from those earlier advances in tooling, in that AI replaces thought itself. So next time it probably won’t be a human physicist that does the intellectually challenging work of constructing quantum mechanics from measurements of individual quanta. It will most likely be an AI.
I'm also a physicist. But I think the next 5 years are going to be a rough ride for math. I'm struck by the following observation, mainly from following HN links to Terrence Tao's blogs.
Novel proofs are the coin of the realm for junior mathematicians. They figure into training, career advancement, and indirectly, teaching. The reason I include teaching is because it requires tenure, which requires proofs. Teaching without tenure is gig work, not a career. But proofs can be devalued to zero.
The application deadline for grad school is a few months away. For a student considering a math career, they have to deliver a thesis in a few years, that their professor is willing to sign. Nobody knows what that will look like without proofs. "We will have to do something different" is weak sauce.