AI Cheating Scandal Erupts at Brown University as Economics Exam Shows Suspicious Perfect Scores

AI Cheating Scandal Erupts at Brown University as Economics Exam Shows Suspicious Perfect Scores

Ivy League students are academically accomplished, making AI-assisted cheating unnecessary for learning fundamentals. However, their competitive nature and demanding schedules can make automated tools attractive shortcuts for maximizing productivity. This dynamic is now under scrutiny at Brown University following alarming exam results.

A recent incident involving economics professor Roberto Serrano has revealed potentially systemic academic dishonesty in his spring 2026 course. Serrano, a Spanish-born scholar who has spoken publicly about the situation with El País and Inside Higher Ed, documented unprecedented grading outcomes that suggest widespread use of artificial intelligence.

Roberto Serrano receiving an award from the King of Spain in 2025.

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The controversy began in December 2025 following a campus shooting that claimed two lives. In response, Serrano implemented take-home exams for both midterm and final assessments in his challenging ECON 1170 course. Enrollment surged to 86 students—a dramatic increase from his typical classes of fewer than 30 students.

The midterm results revealed startling anomalies. According to El País, the average score reached 96 out of 100, with 40 students achieving perfect marks. These figures starkly contrast with historical data: Serrano noted that previous midterm averages typically ranged between 65 and 80 percent. He emphasized that this exam was deliberately designed to be more challenging than past versions, as take-home format allowed for deeper analytical requirements.

The professor’s decision to permit take-home exams followed the traumatic campus shooting, which personally affected him. The stunning grade distribution has prompted serious questions about academic integrity standards at elite institutions increasingly grappling with AI integration in educational settings.

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