Brown University Economics Professor Uncovers Massive AI Cheating Scandal

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.

Record scores

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.

In just the last week, Serrano—who was born in Spain—has told his story to El País and Inside Higher Ed, which have both run significant pieces on the scandal.

The story that Serrano told them begins in December 2025, when a gunman attacked Brown’s campus and killed two people, including one who had recently introduced herself to Serrano.

Shaken by the experience, Serrano decided that his spring 2026 section of the quite difficult ECON 1170 would allow take-home exams for both the midterm and the final. Suddenly, the course received an influx of students. El País has the story:

The course… typically attracts few students, but very good ones. [Serrano] has never had more than 30 students enrolled at a time, and on some occasions he had only eight. This semester, probably because of the new evaluation system, 86 students signed up for the class. The results of the midterm exam, which was administered on March 5, were extraordinary, with an average score of 96 out of 100. Forty students scored a perfect 100.

This was indeed extraordinary, because as Serrano told Inside Higher Ed, “Historically the average grade in the midterm of this course has ranged between 65 and 80 [percent], and this exam was harder than the exams I wrote in the past, because… take-home is an opportunity to challenge the class a little bit more, given that you’re giving the students unlimited time.”

Beyond the numbers, many of the answers, even when correct, felt slightly off. They had a “very convoluted style,” Serrano said. When he and his grad students ran the exam questions through ChatGPT, they received similar results.

A suspicious Serrano decided that he would make the final exam in-person; he would see if students did similarly well on it. He emailed his class, telling them, “I am not declaring [the midterm] void for now. I am going to give the class a chance to prove me wrong. That is, if the distribution of the final exam is roughly similar to the distribution of the midterm, I will count the midterm. Otherwise, which of course what I expect to happen, I will declare the midterm void and reweigh the final accordingly.”

Eighteen students suddenly dropped the course, while nine others didn’t even attend the final exam. Of those 27 students, El País noted, “22 had scored a perfect 100 in the midterm exam.”

Among those who took the test, the average score plunged—from 96 all the way down to 48.

A failed society?

The professor was horrified by what appeared to be massive cheating in his course—cheating that was preventing most of the students from learning the material.

Serrano comes across as someone with no inclination to coddle elite students. His attitude may be traceable in part to his own childhood, in which he went blind from retinal dystrophy at age 17 and had to make a choice about what the rest of his life would look like. From El País:

After a short-lived crisis, he decided [blindness] would not stop him. He learned Braille, and his excellent academic record opened up the doors of Harvard. “Of course it affects my life, but one shouldn’t over-dramatize. We economists understand reality as a set of people responding to optimization problems with restrictions. I view my disease simply as one more restriction that I have to deal with, and I optimize based on that,” he says.

As a university, Brown is grappling with hard questions about AI use at the moment. It recently released a provost-led report (PDF) on “Generative AI in Teaching and Learning,” which found that it’s not just professors who have concerns.