Quibblers and cynics might call AI a solution in search of a problem. We couldn’t possibly comment on such a stance—but we will note that the list of problems that stand waiting for AI-powered salvation does seem to be diminishing by the day. Today’s banished potential use case: remote exam supervision. The exam in question was the annual entrance exam for the National Autonomous University of Mexico (UNAM), Mexico’s largest and most prestigious university. As El País explains, while UNAM will admit just over 50,000 students this year, more than half of those places go to students whose places are assured by virtue of attending one of 14 UNAM prep high schools. The remaining places—just under 22,000 this year—go to the best performers in the university’s annual entrance exam. As one might expect, then, the exam is highly competitive—nearly 160,000 applicants sat for it this year—and with stakes so high, it’s easy to see why any opportunity to cheat might prove irresistible. With all that in mind, one might well ask why on earth UNAM decided that this, of all exams, was the one it would use to decide on whether an AI-supervised remote exam is a great idea. The answer to that question remains unclear, but what is clear is that things didn’t go especially well.