“An Ethical and Moral Problem”: How Professors are Reshaping Courses in the Age of AI The University of Chicago has no University-wide AI policy, leaving regulation, detection, and enforcement to programs and individual professors, English department chair Benjamin Morgan said. The university partnered with Anthropic in June to offer students free access to the Claude large language model ahead of the 2026–27 academic year, while the Law School banned AI in all introductory and required courses and the social sciences Core banned technology and AI in class across all sections. President Paul Alivisatos announced AI working groups as early as 2025, and nearly two years later the university remains in an exploratory phase. Over the last few months, the University has made headlines for implementing a wide array of approaches to artificial intelligence. In June, University President Paul Alivisatos announced https://president.uchicago.edu/from-the-president/announcements/ai-tools-at-uchicago that UChicago would partner with AI company Anthropic to offer students free access to their flagship large language model LLM , Claude, ahead of the 2026–27 academic year. Not long after, the Law School released https://www.law.uchicago.edu/news/ai-strategy-statement a detailed strategy statement outlining a nuanced approach to AI, banning its use in introductory sequences while slowly incorporating it in upper-level coursework. And just last month, the Maroon reported https://chicagomaroon.com/53262/news/sosc-core-to-institute-ai-ban-technology-free-classrooms-this-fall/ that social sciences sosc Core classes would ban the use of technology in class and AI altogether across all sections. Despite or perhaps because of the diversity of approaches, UChicago continues to lack a University-wide AI policy, instead leaving matters of regulation, detection, and enforcement up to programs, like the social science Core, or individual professors. Peer institutions vary in their approaches, with several https://provost.columbia.edu/content/office-senior-vice-provost/ai-policy opting https://www.it.northwestern.edu/about/policies/guidance-on-the-use-of-generative-ai.html to implement https://policy.usc.edu/generative-ai-general-policy/ university-wide policies. “It is absolutely not a top-down thing,” English department chair Benjamin Morgan said, describing how AI policies are developed for the classroom. “There is no kind of centralized directive coming from above saying, ‘Here are the policies that you must implement.’” The lack of a centralized AI policy comes with both benefits and drawbacks. “There being a universal policy would make it easier to do disciplinary casework and make it easier for students to know what is and is not accepted,” said Jessie Wang A.B. ’26 , who over the last two years served as president of the Student Advocate’s Office SAO , which assists students charged by the University with disciplinary infractions. On the other hand, “with the differences between the humanities and STEM classes, the standards for what can and can’t be done differ a lot.” Another obstacle to a University-wide standard is the traditional UChicago belief that “professors should have full control over the way that they teach in their classrooms,” Wang said. “A universal AI policy would definitely get in the way of that for some people.” Perhaps the Law School’s recent strategy statement can offer clues to the University’s developing philosophy regarding AI. In the coming academic year, AI will be banned https://chicagomaroon.com/53131/news/the-template-for-law-schools-around-the-world-uchicago-law-school-announces-new-ai-strategy/ from all introductory and required courses, but gradually incorporated into higher-level electives, several of which deal with AI directly. The Law School’s policy centers on the cultivation of “essential human” skills, such as judgment, reasoning, and critical thinking, so that students are able to use AI responsibly in the long run. The University as a whole, meanwhile, is in what can only be described as an experimental phase. As early as 2025, Alivisatos announced https://president.uchicago.edu/From-the-President/Announcements/Update-on-Faculty-Led-Efforts-on-AI the establishment of AI working groups to develop frameworks for the University’s approaches to AI both in the classroom and in research and scholarship. Nearly two years later, the University remains in that exploratory stage, allowing departments and professors space to work out what makes sense for their own disciplines. Whether that will—or should—change is another question entirely. How have AI policies shaped up thus far? Lisa Rosen, executive director of UChicago’s Science of Learning Center and a professor in the Committee on Education, spoke to the Maroon about how her policies have evolved in the past few years. She previously allowed students to use AI on their take-home essays as long as they disclosed it, and students were asked to submit their papers as a Google Doc with version history accessible. However, Rosen noticed that this combination did not necessarily lead to honest reporting of AI use. She has since “redesigned” the course so students must choose between an oral exam or an in-class written exam, making it “more or less impossible for them to cheat.” Rui Zhao, who teaches ECON 100: Principles of Microeconomics, one of the largest classes on campus, has changed the structure of her exams in recent years to focus less on factual knowledge and computation and more on explaining what calculations mean and how they are derived, in part as a method of combatting AI. However, she doesn’t unilaterally ban AI use for class assignments. “Even if I tell you that you shouldn’t use it, it just puts you in a disadvantageous position,” she said. But homework itself is part of the training process. She believes only once students internalize the trade-off can they understand they are “cheating themselves” by using AI. In addition to determining AI policy, professors are also responsible for identifying suspected misconduct. But the absence of a common AI standard makes both detection and disciplinary action more difficult. “What cheating means in one class can be different from what cheating means in another class,” Wang, the former SAO president, said. A student who uses AI to edit prose in an English course or debug code in a computer science CS course may be violating the rules of one course while acting within them in another. For that reason, the most important element in any AI-related disciplinary case is the syllabus of that particular course, Wang said. The stakes of the matter have risen quickly. According to Wang, the SAO had “basically no AI cases” two years ago. Today, she estimated, “maybe half of our cases or more are AI-related.” According to the University’s disciplinary action reports, there were four