An economics professor at Brown University suspects most of his class cheated with AI, and he has the numbers to make the case. Roberto Serrano watched his take-home midterm average hit 96 out of 100. When he switched the final to an in-person test, the average fell to 48. He has taken the story public, telling El País and Inside Higher Ed that he will not let it go.
The take-home format came out of tragedy. After a gunman killed two students on campus last December, many said they felt anxious sitting exams in a room full of people. Serrano offered take-home midterm and final papers to ease that. The irony stings: the one time in decades he relaxed the rules, much of the class cheated.
The numbers that gave it away
Serrano’s course, ECON 1170, is an advanced undergraduate economics class that usually draws a small, strong group. He had never taught more than 30 students, and once had just eight. This term, 86 signed up. The new take-home format likely drew them in.
The midterm results were, in his word, extraordinary. The class averaged 96, and 40 students scored a perfect 100. The historical average for the course sits between 65 and 80, and this exam was harder than usual. Take-home, Serrano reasoned, was a chance to push the class further, given the unlimited time.
The answers themselves felt off. Many correct ones carried a “very convoluted style”. When Serrano and his graders fed the questions to ChatGPT, they got similar results back.
The test he set to prove it
So he set a trap. He told the class the final would be in-person, and that he would compare the two distributions. If they matched, he would keep the midterm. If not, he would void it and reweight the final.
The response spoke for itself. Eighteen students dropped the course, and nine more skipped the final. Of those 27, El País noted, 22 had scored a perfect 100 on the midterm. Among the students who did sit the exam, the average dropped from 96 to 48. By Serrano’s count, at least 50 students cheated on the midterm, and he calls the evidence overwhelming.
A wider reckoning
Brown is not alone. A recent survey of Princeton students found that 29.9 per cent admitted to cheating on at least one exam or assignment, most of it using AI. Schools have spent two years chasing detection tools and rethinking how they test at all.
Students feel the strain too. Brown’s own provost-led report found that most undergraduates use generative AI weekly or daily. Yet large majorities also worry about the effect on their learning, and fear what it does to their “cognitive capacity”.
That worry sits alongside a broader shift, as AI reshapes who gets hired and even how people think and write. Serrano frames it in the starkest terms.
Why it matters
“We cannot afford to have a society in which a significant fraction of our best young minds think that cheating is okay,” Serrano told Inside Higher Ed. “That leads to a declining society, to a failed society. We cannot choose to become idiots.”
His experiment is small, one class, one term. But it turns a fuzzy worry into a hard number. Take the AI away, and half the apparent knowledge goes with it. That is the figure universities now have to sit with.
