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Berkeley Law Bans Generative AI for Credit Work, Sparking Debate Over Student Use
When Berkeley Law announced a sweeping ban on generative AI for credit work on May 22, 2026, students and faculty were thrust into a heated debate about the future of legal education.
The new policy forbids the use of generative AI in any coursework or exam, applying to all students regardless of program. Its stated purpose is to safeguard intellectual development, but the restriction has raised questions about academic integrity, learning outcomes, and the role of emerging technology in law schools.
Lakshita Bhargava, an LL.M. student specializing in AI governance, told Artificial Lawyer that the ban was drafted by a professor and extends even to summer examinations. She argued that a model that is “permitted‑but‑disclosed” would enhance accountability and learning.
Bhargava explained that her LL.M. program runs only during the summer and that the policy’s urgent goals should be: helping students use AI productively and protecting the integrity of legal education. She outlined three core elements:
1. Use‑based framework – treating AI as an assistant for low‑risk tasks such as summarizing, outlining, editing, translating, and study preparation. 2. Meaningful disclosure – requiring students to report any AI use, which would help the school understand patterns and improve policy. 3. Concrete safeguards – prohibiting confidential data, mandating citation verification, and holding students fully accountable for final work.
The student compared the ban to removing books from libraries, noting that students would still find and use AI tools covertly. She cited a Stanford Law webinar where Dr. Megan Ma said AI can broaden a student’s understanding of legal issues by providing counterpoints. Bhargava maintained that transparent, wise use of AI can aid education, whereas a ban drives it underground.
Berkeley Law’s policy follows a broader trend among top U.S. law schools. According to a gradpilot report, institutions such as Harvard, Columbia, Duke, UCLA, UC Berkeley, Michigan, USC Gould, UVA, Buffalo, Richmond, and Baylor have adopted AI‑prohibited classifications for certain programs. Other schools are rolling out AI training programs to equip students with job‑ready skills.
The ban has sparked concerns about cheating, over‑reliance, and reduced critical thinking—issues that frequently surface in AI‑in‑education research. It also limits students’ exposure to tools that could enhance research and drafting skills. Advocates for balanced policies argue that disclosure and safeguards can mitigate risks while allowing practical learning.
As of now, Berkeley Law enforces a blanket AI ban for credit work, while students like Bhargava push for a more nuanced approach. The school’s leadership has not yet announced a revision to the policy. The debate reflects a national conversation about how legal education should integrate emerging AI technologies.
In the coming months, law schools across the country will likely revisit their AI policies as the technology evolves. Stakeholders will need to balance the benefits of AI for legal research and drafting against the risks of academic integrity and skill development. The outcome of Berkeley Law’s policy debate may influence future regulatory and institutional decisions, and the community will continue to monitor how the ban affects student outcomes and employer expectations.
The new policy forbids the use of generative AI in any coursework or exam, applying to all students regardless of program. Its stated purpose is to safeguard intellectual development, but the restriction has raised questions about academic integrity, learning outcomes, and the role of emerging technology in law schools.
Lakshita Bhargava, an LL.M. student specializing in AI governance, told Artificial Lawyer that the ban was drafted by a professor and extends even to summer examinations. She argued that a model that is “permitted‑but‑disclosed” would enhance accountability and learning.
Bhargava explained that her LL.M. program runs only during the summer and that the policy’s urgent goals should be: helping students use AI productively and protecting the integrity of legal education. She outlined three core elements:
1. Use‑based framework – treating AI as an assistant for low‑risk tasks such as summarizing, outlining, editing, translating, and study preparation. 2. Meaningful disclosure – requiring students to report any AI use, which would help the school understand patterns and improve policy. 3. Concrete safeguards – prohibiting confidential data, mandating citation verification, and holding students fully accountable for final work.
The student compared the ban to removing books from libraries, noting that students would still find and use AI tools covertly. She cited a Stanford Law webinar where Dr. Megan Ma said AI can broaden a student’s understanding of legal issues by providing counterpoints. Bhargava maintained that transparent, wise use of AI can aid education, whereas a ban drives it underground.
Berkeley Law’s policy follows a broader trend among top U.S. law schools. According to a gradpilot report, institutions such as Harvard, Columbia, Duke, UCLA, UC Berkeley, Michigan, USC Gould, UVA, Buffalo, Richmond, and Baylor have adopted AI‑prohibited classifications for certain programs. Other schools are rolling out AI training programs to equip students with job‑ready skills.
The ban has sparked concerns about cheating, over‑reliance, and reduced critical thinking—issues that frequently surface in AI‑in‑education research. It also limits students’ exposure to tools that could enhance research and drafting skills. Advocates for balanced policies argue that disclosure and safeguards can mitigate risks while allowing practical learning.
As of now, Berkeley Law enforces a blanket AI ban for credit work, while students like Bhargava push for a more nuanced approach. The school’s leadership has not yet announced a revision to the policy. The debate reflects a national conversation about how legal education should integrate emerging AI technologies.
In the coming months, law schools across the country will likely revisit their AI policies as the technology evolves. Stakeholders will need to balance the benefits of AI for legal research and drafting against the risks of academic integrity and skill development. The outcome of Berkeley Law’s policy debate may influence future regulatory and institutional decisions, and the community will continue to monitor how the ban affects student outcomes and employer expectations.
