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A laptop ban at one of America’s leading law schools might appear to be an unusual response to the rise of artificial intelligence. Yet the University of Chicago Law School is not turning its back on technology. Instead, it is drawing a clear distinction between developing legal reasoning and using AI tools.
Beginning with the 2026-27 academic year, first-year students will no longer be permitted to use laptops, tablets or mobile phones in required classes. Core examinations will also move to supervised, offline settings, with limited exceptions for accessibility and specific teaching requirements. At the same time, the school is expanding formal instruction on generative AI, encouraging students to understand where the technology adds value and where it introduces risk.
The distinction matters because it reflects a broader question facing universities and employers alike. As AI becomes embedded in professional work, when should people rely on technology, and when should they be expected to solve problems independently?
The first year of legal education remains a training ground for judgment
The University of Chicago argues that foundational legal education requires sustained attention, discussion and independent analysis before students begin incorporating AI into their workflow. That philosophy aligns with the law school’s long-standing emphasis on the Socratic method, where students are expected to defend arguments, respond to challenges and explain how they reached their conclusions.
Generative AI complicates that process. Students can now produce well-written summaries, draft legal arguments and identify case law within seconds. These capabilities improve efficiency, but they also reduce the intellectual effort required to reach an answer. The danger is not simply that students become faster. It is that they may never develop the habits of reasoning needed to recognize when AI has produced incomplete, misleading or fabricated information.
The school’s strategy reflects this concern. Rather than treating AI as something to prohibit, it distinguishes between learning fundamental legal reasoning and applying technology after those skills have been established. Students are expected to learn to think without AI before learning how to work alongside it.
Research into classroom technology provides additional context. Long before generative AI became widely available, studies suggested unrestricted laptop use could reduce student attention, lower memory retention and distract nearby classmates. AI raises the stakes because the device is no longer just a source of distraction. It has become an active participant in the learning process, capable of completing analytical tasks that were once central to legal education.
The policy does not suggest AI is inherently harmful. Instead, it argues there is value in delaying reliance on the technology until students have developed independent competence.
The policy combines restrictions with practical AI education
The most overlooked aspect of the University’s strategy is that it expands AI instruction while introducing device-free classrooms.
Students will continue learning how to use AI during legal research and writing courses, where the technology will support research, drafting, revision and preparation for oral arguments under structured supervision. The curriculum also introduces oral defenses for substantial research papers, requiring students to explain and defend their work directly to faculty members.
This approach acknowledges a simple reality. Future lawyers will almost certainly work alongside AI throughout their careers. Legal research platforms already integrate generative AI capabilities, while document review, contract analysis and litigation support continue shifting toward automated systems.
Teaching students to ignore these tools would leave graduates unprepared for modern legal practice. Teaching them to depend on AI from the outset may create professionals who struggle to evaluate the quality of machine-generated advice.
The balance is becoming increasingly relevant across the legal profession. The American Bar Association reported that AI adoption among law firms increased from 11% in 2023 to 30% in 2024, with adoption reaching 46% among firms employing at least 100 lawyers. Thomson Reuters has also reported that more than half of surveyed legal, tax, risk and government professionals now use generative AI in some capacity.
Those figures suggest AI literacy is becoming a professional requirement rather than an optional skill. They also reinforce why foundational judgment remains valuable. Lawyers remain responsible for the advice they provide, regardless of whether that advice originated from their own analysis or an AI platform.
The profession has already witnessed the consequences of misplaced trust in generative AI through court filings containing fabricated legal citations and inaccurate case references. Those incidents have reinforced that AI can accelerate legal work, but it cannot replace professional accountability.
The debate extends well beyond legal education
Although the policy focuses on law students, its underlying principles apply across knowledge-intensive industries.
Engineering firms increasingly use AI-assisted design software. Manufacturers rely on predictive maintenance systems and production planning algorithms. Financial institutions deploy AI across compliance, fraud detection and investment research. Logistics providers use machine learning to optimize routing and inventory decisions.
Each sector faces the same challenge. New employees need to understand how systems function before relying on automated recommendations. Without that foundation, professionals may struggle to identify flawed outputs, challenge assumptions or explain why a decision was made.
That suggests the University of Chicago’s approach may offer a broader framework for professional education. Learners first demonstrate they can complete a task independently. They then repeat the exercise with AI assistance before comparing the two approaches and defending their final decision.
Such a model does not slow innovation. It creates confidence that technology supports expertise rather than replacing it.
The conversation surrounding the laptop ban is larger than a classroom policy. It raises a question every profession will need to answer as AI becomes commonplace. The organizations that benefit most from artificial intelligence may not be those that encourage constant reliance on it. They may be those that know precisely when independent human judgment should come first.
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