For the first time since he started teaching Welfare Economics and Social Choice Theory nearly two decades ago, Brown University economics professor Roberto Serrano gave his students a take-home midterm this spring. Quite a few students had expressed anxiety about being in a classroom after a gunman killed two students and injured nine in a December mass shooting at Brown, and so “it was appropriate,” he said, to allow students to take their exams at home.
But by the end of the semester, Serrano regretted the decision. Dozens of students in the class likely used artificial intelligence to cheat and earn perfect or near-perfect scores on their midterm, he said. Serrano in turn made the final exam in-person, which led more than a dozen students to drop the course and even more to fail it. Administrators’ response to the widespread cheating event has been “meek,” he said, and the incident has raised questions about how universities can—and should—respond to AI-enabled cheating at scale.
His welfare economics class typically attracted up to 30 students, but this spring he taught 86—an increase he attributes to the promised take-home exams. When the midterm came along, the average score was 96 percent.
“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,” Serrano said.
He knew something “fishy” was going on, and so he and his graders ran the test through ChatGPT. The AI gave answers that mirrored what his students had written, and which were “kind of correct, but very off and with a very convoluted style,” Serrano said. For example, one question asked students to prove a mathematical statement that could most obviously be done using a “direct argument,” Serrano explained. ChatGPT—and many of his students—used a “contradiction argument,” which gave the right answer but was “very contrived” and which Serrano could tell wasn’t written by a human.
In a message to students after the midterm that he shared with Inside Higher Ed, he told them he suspected many of them of using AI to cheat and, with the blessing of his dean, changed the final exam to an in-person test.
“I am not declaring [the midterm] void for now. I am going to give the class a chance to prove me wrong,” he wrote. “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 is of course what I expect to happen, I will declare the midterm void and reweigh the final accordingly.”
Serrano heard crickets from his students, but 18 of them subsequently dropped the class. Nine students remained enrolled but did not take the final exam. And Serrano said the results proved him right; three students earned a zero, and the average score on the final was 48.6 percent—by far a historic low, he said. Previously, the average final exam score had never dropped below 65 percent. Only a few students scored similarly to how they did on the midterm.
ECON 1170 Midterm & Final Scores
After Serrano made the final in-person, 18 students dropped the class and nine students did not take the exam. The scores of the remaining 59 students are displayed here.

In a follow-up message to students, Serrano announced the midterm was void and the final exam would be worth 80 percent of the students’ final grade. Any student that scored a 40 percent or higher on the final earned a passing grade—previously, he set the passing line at 50 percent or higher. In total, 19 students failed the class.
‘We Cannot Choose to Become Idiots’
In May, Serrano submitted the data shown above to Brown’s Standing Committee on the Academic Code and received no response. After he went public with his story in late June, the committee, through his department chair, asked Serrano to submit individual complaints against each student suspected of cheating, including copies of their exams, he said.
“What they are asking is ridiculous … I believe they plan to run them through some AI-detection tool, which is well-known to give many false positives and false negatives,” he said. “Their response, I must tell you, is seen as appalling and insufficient by hundreds of people who have emailed me in support, many of them Brown alumni.”
Asked about the university’s response to the cheating, Brown spokesperson Brian Clark told Inside Higher Ed that the procedure for investigating cheating allegations is the same whether it’s one student or several.
“Brown treats every allegation of academic integrity with the utmost seriousness. In regard to this economics course, multiple academic leaders from Brown were in touch with the faculty member who raised concerns to provide details about how the allegations raised could be formally adjudicated. To date, the faculty member has not provided the necessary details to the Standing Committee on the Academic Code to pursue this path toward resolution,” Clark wrote.
Serrano will meet Wednesday with his dean to further discuss the incident, he said.
Adjudicating cheating allegations when so many students are suspected of having cheated is tough on faculty, said Tricia Bertram Gallant, director of the Academic Integrity Office and Triton Testing Center at the University of California, San Diego.
“They don’t get rewarded for dealing with a 60-person case of cheating,” she said. “They are not incentivized to really prevent cheating or to report it when it occurs … Their time is not compensated. If the professor’s a lecturer, and they get paid on the first day of class and stop getting paid on the last day of class, when are they supposed to do it? Or grad students who teach for the summer?”
At the same time, institutions can’t sacrifice fairness for efficiency, she said, but there are some steps colleges can take to find a middle ground. Bertram Gallant recommends that academic integrity committees allow students to accept responsibility for cheating via email rather than only during an in-person meeting, and to allow professors to submit complaints against multiple students at once. Ultimately, institutions that care most about upholding academic integrity will dedicate staffing and resources to the matter, she said.
“Edgar Schein, an organizational theorist, said leaders tell you what they value little by what they say, and more by what they spend their money on,” she said. “So the fact that most universities—especially rich ones—do not have academic integrity professionals that they pay, that’s symbolic.”
As the cheating scandal unfolded in Serrano’s classroom, a Brown committee on generative AI in teaching and learning was examining how the technology was being used at the university and formalizing recommendations for how Brown can adapt and respond to AI developments. Its inaugural report was published Tuesday.
Three-quarters of Brown professors said they are concerned about students using AI to cheat, according to feedback from 105 faculty members. The same share of respondents said the same in a 2025 nationwide survey from the American Association of Colleges and Universities. As part of a set of medium-term recommendations, the committee encouraged the university to amend the College Academic Code and the graduate student code “to address GenAI realities and safeguard against misuse.”
“The academic codes should speak to integrity, but also to the potential harms to student learning and personal growth,” the report states. “Beyond the campus baseline regarding GenAI use, it is important that bright lines around misuse be enforced. As such, the academic codes should explicitly address high-level issues such as: is something in ‘your own words’ if GenAI provides grammatical improvements? Are the thoughts ‘your own’ if you formed them through a brainstorming exercise with GenAI in the same way you would engage a colleague in conversation? How do we apply the concepts of knowledge production, original research, citation and attribution in the context of GenAI?”
The committee also suggests that faculty “de-emphasize punishment” and avoid highly restrictive rules around generative AI use.
“There is no way to check with 100 percent accuracy whether GenAI has been employed, and norms are likely to change in the years to come,” the report states. “Moving the conversation beyond punishment also allows for open dialogue that will be necessary as Brown navigates this moment.”
As colleges and universities grapple with AI, cheating must be taken seriously, Serrano said. “We cannot afford to have a society in which a significant fraction of our best young minds think that cheating is OK,” he said. “That leads to a declining society, to a failed society … We cannot choose to become idiots.”