Brown University AI cheating scandal highlights pressures on Ivy League students

Ivy League college students are, by definition, intelligent. They don't need to use generative AI to cheat on exams; they could just learn the material. But they also tend to be competitive, ambitious, and overscheduled, so AI can look like an easy shortcut that makes more time in their lives for things that can't be done by a chatbot.

When the pressure is on, which approach do they choose? A new scandal at Brown University reveals that huge numbers of these students are likely to cheat. A recent survey of Princeton students found that 29.9 percent admitted to cheating with AI on at least one exam or assignment.

But the recent situation at Brown gives us a better sense of what this kind of cheating looks like in one particular class—and just how much it may be substituting for actual learning. And we know all this because the blind economics professor at the center of it all, Roberto Serrano, is not letting it go. Why this matters: The Brown University AI cheating scandal highlights the intense pressures faced by Ivy League students, who are often expected to excel academically while also pursuing extracurricular activities and maintaining a social life.

The fact that nearly a third of Princeton students admitted to cheating with AI suggests that this is a widespread problem that could have serious implications for the education system. If students are relying on AI to complete assignments and exams, they are missing out on the opportunity to learn and engage with the material, which could ultimately undermine the value of their education. As educators and policymakers grapple with the consequences of AI cheating, they will need to consider how to support students in managing their workload and finding alternative ways to succeed.

Ultimately, the scandal raises important questions about the role of AI in education and the need for a more nuanced approach to teaching and learning.