Artificial intelligence models have been rapidly solving longstanding mathematical problems, with Open AI's agents cracking the Navier-Stokes problem in 88 hours and resolving over 100 problems across mathematics. This progress has raised concerns among mathematicians, including 27 Fields medalists who issued a joint declaration stating that solving famous open problems is not the goal—these problems serve as "landmarks and lighthouses" guiding conceptual understanding. Terence Tao, a signatory, warned of "strip-mining" mathematics, arguing that A.

I. could destroy the mathematical ecosystem by removing the problems young researchers need to train. Applied mathematicians like Steven Strogatz and Alex Townsend caution that the human process of trial and error is essential for progress, noting that ceding understanding to machines could be costly. While some view the mathematicians' stance as guild protection, the authors emphasize the distinction between pure and applied mathematics, arguing that history shows how damaging it would be to abandon human insight in favor of automated solutions.