The University of Chicago Law School has introduced a new policy requiring students to keep their laptops closed during class sessions, a move designed to address growing concerns about artificial intelligence tools reshaping legal education. According to a report from Business Insider, the decision reflects broader tensions within higher education institutions as they grapple with the rapid adoption of generative AI systems like ChatGPT and similar platforms that can produce case summaries, draft arguments, and even analyze complex legal precedents in seconds.
This policy, set to take effect in the fall of 2026, marks one of the most direct institutional responses to date in the legal academic community. Faculty members at the school expressed worries that unrestricted laptop access during lectures allows students to rely too heavily on AI assistance, potentially undermining the development of critical thinking skills that have long formed the foundation of legal training. Instead of taking notes by hand or engaging directly with professors and peers, students might quietly query AI models for instant answers, a practice that several instructors described as eroding the Socratic method central to American legal education.
The policy does not ban laptops entirely from the classroom. Students may still bring their devices but must keep them shut unless a professor explicitly grants permission for specific activities, such as accessing digital case files or participating in approved simulations. Exceptions will likely apply during open-book examinations or when professors integrate technology into their teaching methods. The school administration emphasized that the rule aims to foster active participation rather than punish students for using available tools.
Legal educators across the country have watched similar experiments unfold with varying degrees of success. Some professors at other institutions have tried to incorporate AI directly into their curricula, teaching students how to prompt large language models effectively while also critiquing the systems’ frequent hallucinations and biases. Others have doubled down on traditional methods, arguing that the core competencies of legal reasoning cannot be outsourced to algorithms without significant loss in professional development. The University of Chicago’s approach represents a middle path that acknowledges the existence of these powerful tools while creating structured environments where their influence can be limited.
Faculty discussions leading to this decision highlighted several specific problems observed in recent semesters. In some classes, professors noticed students producing unusually polished responses during cold calls that seemed inconsistent with their earlier written work. Group projects occasionally revealed identical phrasing across multiple submissions, suggesting shared AI assistance rather than collaborative human effort. Perhaps most concerning were reports of students struggling to articulate basic legal concepts during office hours after depending on AI summaries throughout the term. These patterns convinced administrators that intervention was necessary to preserve the integrity of the learning process.
The policy arrives at a moment when law schools face mounting pressure to prepare graduates for a profession already being transformed by artificial intelligence. Major law firms have begun deploying AI systems for contract review, due diligence, and preliminary legal research, often reducing the time required for these tasks from hours to minutes. Clients increasingly demand faster turnaround times and lower costs, creating incentives for firms to adopt these technologies aggressively. Graduates who have never learned to think independently of AI assistance may find themselves at a disadvantage when expected to exercise professional judgment in high-stakes situations where algorithmic suggestions require careful human oversight.
Critics of the new rule argue that shielding students from AI during class creates an artificial environment that fails to mirror real-world practice. They contend that future lawyers will need sophisticated skills in working alongside AI systems, much like pilots learn to fly with advanced autopilot features while maintaining their ability to take manual control when necessary. Banning laptops, according to this perspective, might delay the development of those hybrid competencies rather than encourage them. Some students have already voiced concerns about the policy, suggesting it treats them as incapable of responsible technology use and potentially puts them at a disadvantage compared to peers at institutions taking a more integrated approach.
University administrators counter that the closed-laptop policy addresses a specific phase of legal education rather than denying the importance of AI literacy. They point out that dedicated courses on legal technology, professional responsibility in the age of AI, and advanced research methods will continue to be offered. The classroom itself, they maintain, should remain a space for developing foundational analytical abilities before students move on to more applied settings where technology assistance becomes appropriate. This staged approach echoes how other professions have handled disruptive technologies, introducing them gradually after core competencies have been established.
The decision also reflects growing recognition that AI tools present particular challenges in legal education due to the nature of the subject matter. Law school teaches students not simply to find answers but to construct arguments, anticipate counterarguments, and navigate ambiguity in ways that current AI systems struggle to replicate authentically. While generative AI can produce confident-sounding legal memos, these outputs often contain subtle errors in reasoning or fail to account for jurisdiction-specific nuances that experienced attorneys would immediately recognize. Students who become accustomed to accepting AI-generated content without rigorous scrutiny may develop habits that prove difficult to break in professional practice.
Implementation details for the policy remain under discussion, with faculty committees working to establish clear guidelines and consequences for violations. The school has indicated that enforcement will likely rely on a combination of professor observation and student self-reporting, avoiding overly intrusive monitoring methods that could create additional privacy concerns. Training sessions for faculty will focus on redesigning class activities to maximize engagement when digital devices are not available for note-taking or research. Many professors plan to incorporate more frequent small-group discussions, whiteboard exercises, and structured debate formats that encourage verbal reasoning over digital consultation.
This development at one of the nation’s most prestigious law schools will likely influence similar conversations at peer institutions. Already, several other top-tier schools have formed working groups to examine their own policies regarding AI in the classroom. Some are considering hybrid approaches that allow limited laptop use during certain portions of class while maintaining technology-free zones during others. Others are investing in detection software designed to identify AI-generated content in student submissions, though the effectiveness of such tools remains questionable as the technology continues to advance.
The broader implications extend beyond individual classrooms to questions about how legal education should evolve in response to technological change. For decades, law schools have followed a relatively stable model centered on case method instruction and Socratic dialogue. The introduction of generative AI challenges fundamental assumptions about what skills matter most and how they should be taught. Schools that adapt successfully may need to reconsider not only their classroom policies but also their assessment methods, curriculum design, and even admissions criteria to ensure they continue producing capable graduates.
Students themselves occupy a complicated position in these debates. Many entered law school expecting to learn traditional legal analysis while recognizing that technological proficiency will be essential for their careers. The closed-laptop policy may force them to develop stronger note-taking abilities and active listening skills that could prove valuable regardless of future technological developments. At the same time, they may feel caught between institutional restrictions and a professional world that increasingly expects comfort with AI tools from day one of employment.
As more institutions experiment with different approaches, a clearer picture will emerge about which strategies best serve both educational goals and professional preparation. The University of Chicago Law School’s decision represents an early and notable attempt to draw a boundary around classroom time, asserting that certain forms of learning require undivided human attention. Whether this approach will serve as a model for others or prove to be an outlier depends largely on how effectively it balances the development of independent analytical capabilities with the practical need to understand and work alongside increasingly sophisticated artificial intelligence systems.
The coming academic years will test these policies in real time as both students and faculty adapt to new expectations. Success will ultimately be measured not by how strictly rules are enforced but by whether graduates emerge with the combination of deep legal reasoning skills and technological fluency necessary to thrive in a rapidly changing profession. The University of Chicago’s experiment adds an important data point to an ongoing national conversation about technology’s proper place in legal education, one that will likely continue evolving as AI capabilities expand and professional demands shift accordingly.
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