UChicago Law Bans Laptops to Build Thinkers Before It Teaches AI
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Walk into almost any school board meeting in America right now and the pitch sounds the same: AI tools for every student, as early as possible, to close the learning gap. One of the country’s top law schools looked at that pitch and moved in the opposite direction. On July 9, 2026, the University of Chicago Law School announced that first-year students will not use phones, laptops, or tablets in class for the entire 2026–27 academic year — across all nine core courses — as the cornerstone of a new AI strategy.
The mainstream coverage called it a tech ban. The school’s own strategy statement tells a different story, and the difference matters for every parent of a child who is still building the foundational skills reading and reasoning require.
TL;DR
UChicago Law School published “Rethinking Legal Education in the AI Era” on July 9, 2026, banning phones, laptops, and tablets from all nine core 1L courses during the 2026–27 academic year.
The school is not banning AI: it explicitly supports AI for studying outside class, including generating practice problems and clarifying background reading.
Dean Adam Chilton: “That mastery is not something you can outsource to any technology or machine.”
Robert Bjork’s desirable difficulties research and the retrieval practice literature show effortful, unassisted learning produces stronger, more transferable skills than conditions where tools remove the cognitive effort.
For parents of struggling readers: brain-imaging evidence shows reading pathways form through practice, and AI that replaces phonological, decoding, or working-memory practice removes the stimulus that builds those pathways.
One of America’s top law schools banned laptops from every first-year classroom as the centerpiece of a new AI strategy. Here is what the decision actually means, and why it matters for parents of children still building foundational learning skills.
Common questions
Why would banning laptops make law students better at using AI?
Because the sequence matters. UChicago’s strategy is explicit: build foundational legal reasoning through effortful, unassisted in-class engagement first, then introduce AI tools that amplify rather than substitute for that reasoning. Cognitive science research on desirable difficulties (Robert Bjork, UCLA) and retrieval practice shows that conditions that feel harder in the short term produce stronger, more transferable skills. A student who has worked through a problem under their own power is better positioned to use AI critically and productively than one who has outsourced the reasoning before building it.
Does this mean children with dyslexia or reading challenges should not use tech tools?
Scaffolding tools used alongside structured instruction are different from substitution tools that replace the practice of the underlying skill. A text-to-speech tool that lets a child access a history chapter while structured reading instruction runs separately is scaffolding. An AI tool that decodes words or composes sentences for a child whose phonological processing and working memory are still developing removes the practice stimulus that builds those systems. The key question is sequencing: is the tool a bridge toward a skill the child is actively building, or a bypass around a skill they still need to develop? A screener is a starting point, not a diagnosis. If your child might need formal accommodations such as an IEP or 504 plan, or you suspect a vision, hearing, or medical cause, a professional evaluation is the route to those supports.
What are “desirable difficulties” and why do they matter for reading?
Desirable difficulties is UCLA psychologist Robert Bjork’s term for learning conditions that feel harder in the short term but produce stronger, more durable learning over time. Examples include retrieval practice (recalling something without looking it up) and spaced practice (returning to material after a delay). The difficulty is the instruction: the cognitive effort of working through material without a shortcut is what strengthens the encoding. For reading, this means the work of sounding out an unfamiliar word, holding a sentence in working memory, or generating a written sentence independently is not an obstacle to work around. It is the activity that builds the reading brain. Brain-imaging studies from Yale and Stanford confirm that reading pathways physically form through intensive, appropriate practice.
How do I know if my child’s school is building reading skills or bypassing them?
Three questions worth asking: First, is structured reading or phonological instruction ring-fenced from AI substitution in literacy intervention sessions? Second, does the school distinguish between scaffolding tools (bridging toward a skill the child is actively building) and bypass tools (permanently replacing a skill the child still needs to develop)? Third, if AI tools are being used for a child who is behind in reading, what structured reading instruction runs alongside them? A tool should complement the intervention, not replace it. A screener is a starting point, not a diagnosis. If your child might need formal accommodations such as an IEP or 504 plan, or you suspect a vision, hearing, or medical cause, a professional evaluation is the route to those supports.
The strategy, titled “Rethinking Legal Education in the AI Era,” runs on three tracks: developing AI-resilient teaching and assessment, elevating what the school calls the “essential human” skills that distinguish excellent lawyers, and teaching students how to use AI responsibly and effectively. The device ban covers all nine core 1L courses, from Civil Procedure to Transactional Lawyering, during the 2026–27 pilot year. Exams in those courses will be administered in class, without access to the internet, electronic files, or apps.
Crucially, the school is not banning AI. The strategy statement explicitly encourages students to use AI outside the classroom: using AI to “clarify background concepts while reading before class” or to “generate practice problems while studying” are listed as uses the school wants to support. What the school is protecting is in-class reasoning, which the strategy calls “effortful and sustained engagement with the material.”
Dean Adam Chilton put the stakes plainly: “Our graduates are hired for their judgment, for their mastery of the law. That mastery is not something you can outsource to any technology or machine. A UChicago Law graduate’s good judgment, intellectual robustness and reputation in owning their own work is priceless.”
Author Quote"
Our graduates are hired for their judgment, for their mastery of the law. That mastery is not something you can outsource to any technology or machine. A UChicago Law graduate’s good judgment, intellectual robustness and reputation in owning their own work is priceless.
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What the coverage gets wrong
Most reporting frames UChicago’s laptop ban as a tech crackdown or an odd paradox from an institution also embracing AI. The school’s own strategy statement says the opposite: it explicitly encourages AI for studying outside class and wants to expand AI tools as students progress. The ban is not anti-AI. It is a sequencing decision — build foundational reasoning under conditions that reward effortful engagement first, then deploy AI to amplify rather than substitute for that foundation. Robert Bjork’s desirable difficulties research and the well-replicated retrieval practice literature back exactly this sequence. The story is not “law school bans AI.” It is “top institution applies what learning science actually shows.”
The research does not call this surprising
Decades of cognitive science have converged on a consistent finding: effortful, distraction-free practice builds cognitive architecture that later carries more complex skills. UCLA psychologist Robert Bjork calls these “desirable difficulties” — conditions that feel harder in the short term but produce stronger, more transferable learning over time. The mechanism is well-established: retrieval practice (working to recall something without looking it up) strengthens memory encoding more than re-reading, and learning conditions that remove that struggle remove the benefit with it. UChicago is not being contrarian. It is applying what the learning science says.
The connection to younger learners, including those who struggle with reading, is direct. Reading is biologically secondary: unlike spoken language, which human brains evolved to absorb without instruction, reading repurposes circuits built for other work and must be explicitly, systematically taught at every step (cognitive scientist Stanislas Dehaene; David Geary’s primary-versus-secondary knowledge framework; National Reading Panel, 2000). The International Dyslexia Association’s 2025 definition describes reading as drawing on multiple systems simultaneously: phonological awareness, working memory, processing speed, and attention all at once.
A child whose AI decodes words, looks up meanings, or composes sentences before those systems are exercised is not being helped to read. Brain-imaging studies from Yale (Shaywitz et al.) and Stanford (Temple et al.) show that reading pathways physically form through intensive, appropriate instruction. Practice changes the brain. A tool that removes the practice stimulus also removes the stimulus for neural change. What UChicago is protecting in their 1Ls is the same thing struggling readers need protected: the right kind of difficulty. Neuroplasticity research is unambiguous that the brain you are worried about today is not the brain your child will have after a year of the right kind of effort. The obstacle is not AI. It is arriving with the tool before the foundation is built.
Key Takeaways:
1
Not anti-AI: a sequencing decision: UChicago Law’s device ban covers all nine core 1L courses for 2026–27, while explicitly encouraging AI use for studying outside class. The strategy is build the reasoning first, then amplify with tools.
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The science behind the sequence: Robert Bjork’s desirable difficulties research shows effortful, unassisted engagement produces stronger, more transferable learning than conditions where tools remove the struggle. Retrieval practice without AI assistance strengthens encoding; offloading the retrieval weakens it.
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What it means for struggling readers: Brain-imaging studies (Shaywitz/Yale, Temple/Stanford) show reading pathways form through intensive practice. AI that decodes or composes for a child still building those systems removes the stimulus that builds the brain architecture reading requires. Ask what foundation comes before the tool.
What this asks of parents
None of this makes AI the enemy at your child’s school. The distinction that matters is sequencing. AI that frees a child to engage harder with a problem they have the underlying skills to attempt is a useful tool. AI that replaces the foundational practice of sounding out words, holding a sentence in working memory, or generating their own sentence removes the stimulus that builds those skills. The question is not “AI or no AI.” The question is: is the tool arriving before or after the foundation?
Three questions worth raising with your child’s school: First, is structured literacy or intervention instruction ring-fenced from AI substitution in the classroom? Decoding and phonological practice need protection, and it is worth confirming the school draws the distinction. Second, does the school classify tools as scaffolding (a bridge toward a skill the child is actively building) versus substitution (a permanent bypass of a skill the child needs to develop)? Third, if your child is behind in reading and the school is introducing AI tools for reading or writing tasks, what structured reading instruction runs alongside? The tool should not be the intervention.
The Socratic method UChicago is protecting in its first-year law classes is, at its heart, the same principle: a system that refuses to let the student bypass the difficulty, because the difficulty is the instruction.
The brain your child brings to reading practice today is not the brain they will have after six months of the right kind of effort. That is not a slogan. It is what the imaging actually shows. UChicago Law understood that a tool is only as powerful as the foundation it runs on, and built their entire AI strategy around that insight. The obstacle for parents is not finding the right app. It is protecting the effort that builds the cognitive architecture underneath. If you want to know exactly which foundational systems your child is still developing and a step-by-step plan to strengthen each one, the All Access program gives you that roadmap, with a free trial and a personalized Action Plan you keep regardless.
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