TECH Signal 488
Berkeley Law sets default AI ban across coursework and exams, effective Summer 2026
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Berkeley Law adopted a default policy prohibiting students from using generative AI to conceptualize, outline, draft, revise, translate, or edit any work submitted for credit, and barring AI use entirely in exams, taking effect Summer 2026.
The policy frames AI as opt-in rather than opt-out for graded legal education and spells out prohibited activities in concrete terms that other institutions can adopt or adapt. For instructors, the written-opt-in requirement means faculty who want AI in their courses must publish an alternative rule and collect disclosures, which is a non-trivial administrative change. For engineers building tools aimed at law students or law schools, the policy removes a permissive default and narrows the legitimate use cases to source identification and instructor-approved exercises.
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The default rule enumerates six prohibited activities on credit-bearing work, conceptualizing, outlining, drafting, revising, translating, and editing, and adds an outright ban on any AI use in any exam situation.
Instructors may deviate from the default only by issuing an alternative rule in writing with notice and by requiring students to disclose any authorized AI use.
Students may not upload course materials into generative AI systems, and citations to non-existent sources will raise a presumption that the student violated the AI rule.
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What the cluster adds up to.
Berkeley Law has codified a default prohibition on student use of generative AI, effective Summer 2026, rather than leaving each instructor to set classroom rules. The policy enumerates six activities that count as prohibited AI use on credit-bearing work: conceptualizing, outlining, drafting, revising, translating, and editing. The exam carve-out is starker than the coursework one, AI is forbidden for any purpose during any exam, with no research-style exception. The shift from course-by-course decisions to an institution-wide default is the concrete change, and the effective date gives a roughly two-year runway before the rule binds.
The cost of the policy falls on instructors who want AI in their classes. Any deviation from the default must be put in writing, announced to students in advance, and paired with a disclosure requirement so that authorized AI use is visible on submitted work. Faculty teaching AI fluency itself get a built-in carve-out, but everyone else has to publish an alternative rule to permit what would otherwise be prohibited. The narrow research allowance, AI only for identifying cases, statutes, or secondary sources, leaves source verification and synthesis as student work, which means the policy treats research as a cognitive skill, not a retrieval task.
The rule also constrains what students can hand to a model. Uploading course materials, including assignments, readings, slides, class recordings, or other class content, into generative AI systems is itself prohibited, regardless of whether the resulting output ends up in submitted work. That puts a hard line around instructor-authored content and treats the act of submission as much as the act of generation. Enforcement leans on a presumption: citations to sources that do not exist will raise a presumption of prohibited AI use, shifting the evidentiary burden onto the student when fake citations appear.
Where the policy stops working is in the gaps it does not address. It does not speak to AI use outside of submitted work, studying, study groups, or preparation that never becomes a graded artifact, which leaves a category of student behavior outside the rule. It also does not cover AI used by instructors in designing or grading coursework, only by students on submitted work. The translation prohibition applies even where a student is composing originally in another language and translating into legal English for credit, which is a deliberate trade-off favoring English fluency over accommodation.
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