“It’s a difficult, delicate moment right now. And I’m not sure we have all the answers,” Kevin Yee, director of the Faculty Center for Teaching & Learning at the University of Central Florida, told Inside Higher Ed. “If faculty had an AI detector that was reliable, that’s what they would use. But many are reluctantly moving in the direction of assignment redesign because they are at wit’s end” over AI-powered cheating. From what he’s observed, about half of faculty want to make as few changes as possible to AI-proof their assessments. But staying the course may be a viable option only for those who teach in-person classes with fewer than 30 students. In a small environment, “they can actually succeed in convincing students not to take these shortcuts, establishing strong relationships and convincing students that the learning is really what matters here,” he said. “In larger classes, there’s less of a personal connection between students and faculty, so faculty need to redesign their assessments to be more AI-resilient or a completely kind of deliverable that AI can’t do, such as a blue book exam or an in-person oral exam.”