University of Minnesota Under Scrutiny Following Expulsion of Ph.D. Student

A Case of Expulsion Amid AI Accusations

In November 2023, Haishan Yang, a third-year health economics Ph.D. student at the University of Minnesota, was expelled after faculty members accused him of using artificial intelligence (AI) during a critical exam. Yang, who denies these claims, has since taken legal action against the university, arguing that his rights to due process were violated throughout the disciplinary process. He has also filed a defamation lawsuit against one of the professors involved, bringing significant attention to the growing concerns tied to AI use in academia.

Allegations and Expulsion

The basis for Yang’s expulsion stems from suspicions that he utilized a large language model, like ChatGPT, during a written preliminary exam—a key requirement for doctoral candidates before progressing to the dissertation phase. According to the university’s disciplinary findings, faculty members raised “significant concerns” that Yang’s exam responses did not match his writing style, with some answers seemingly irrelevant or based on topics that had not been covered in coursework.

To substantiate their claims, two faculty members generated their own responses using ChatGPT for comparison, while also presenting results from AI detection software at Yang’s hearing. However, Yang maintains that he did not employ AI for the exam. He argues that the methods used to detect AI involvement are often unreliable and biased, particularly disadvantaging non-native English speakers—he himself grew up speaking Southern Min, a Chinese dialect.

The Disciplinary Hearing

Yang’s case marks a troubling trend in higher education, where concerns about academic integrity clash with the increasing prevalence of AI tools available to students. In the current academic year, the University of Minnesota identified 188 cases of scholastic dishonesty related to AI use, which accounts for roughly half of all confirmed dishonesty cases on the Twin Cities campus.

The university declined to publicly comment on Yang’s expulsion due to legal constraints but stated that all disciplinary processes adhered to established policies and procedures. Yang’s experience, however, raises pressing questions about how institutions investigate and manage accusations of academic misconduct linked to AI usage.

A Supportive Advocate

In the face of the accusations, Yang received support from his academic advisor, Bryan Dowd, who spoke in his defense during the hearing. Dowd, a professor with decades of experience, expressed skepticism over the notion that Yang would need AI to succeed in an exam. He emphasized that the punishment of expulsion seemed disproportionate for what should be a complex determination of whether AI had been utilized.

Dowd described Yang as an exceptional student, highlighting his dedication to research and the quality of his work. Amidst the controversy, Yang continues to assert his academic integrity and ability, having previously published research and presented at conferences.

The Examination in Question

Yang’s written examination, taken online in August, was an open-book format, with specific instructions that prohibited the use of AI. After the exam, Yang’s writing was compared against other samples, where faculty claimed to see similarities with AI-generated outputs. Yang contests this reasoning, indicating that the commonality lies not in AI use but in drawing from shared academic sources.

Furthermore, he argues that the panel’s decision relied heavily on potentially altered evidence and questionable methodologies. Yang asserts that the tools used to detect AI writing can yield varying results, thereby placing undue stress on students accused of misconduct.

The Response to the AI Detection Crisis

This case highlights a significant pivot in higher education as institutions grapple with how to handle AI. Experts have noted the limitations of AI detection software, which often misclassifies work by non-native English speakers or students who engage in practices such as language improvement tools. The shift in teaching practices encourages educators to design assignments that minimize AI’s potential misuse, such as personal reflections and project-based assessments.

The University of Minnesota has outlined guidelines for faculty regarding AI use, with recommendations to approach detection with caution and to focus on proactive policies that incorporate AI as a teaching tool rather than simply prohibiting it.

Broader Implications

Yang’s experiences and emerging legal battles serve as a cautionary tale for both students and institutions. In the fight to uphold academic integrity, universities must balance the need for vigilance against cheating with fair treatment of students—especially as AI technologies continue to evolve.

Yang is seeking over a million dollars in damages through his lawsuits and is also striving for a reversal of his expulsion and a public apology from the university. His story raises critical points about the implications of AI in academic settings, including the pressure learners face amid evolving definitions of cheating.

As universities navigate this complex terrain, it will be essential to craft clear policies that uphold standards of integrity while accommodating the realities of AI in the classroom.

Key Takeaways

• Haishan Yang was expelled from the University of Minnesota after accusations of AI use in a written exam, which he denies.
• Yang has filed lawsuits against the university and a professor, asserting his due process rights were violated.
• The case highlights the challenges of accurately detecting AI use, particularly among international students and non-native speakers.
• As institutions adapt to the integration of AI, they must balance academic integrity with fair treatment of students accused of misconduct.
• Yang’s situation may spark broader discussions about the role of AI in education and the necessity for transparent policies in handling allegations of dishonesty.

The University of Minnesota is expected to reveal its perspective through court filings, while Yang remains poised to advocate for changes in how future alleged offenses are handled—emphasizing the importance of safeguarding educational environments for all students.