Legal Writing
First-year and advanced legal research, analysis, and writing
David S. Kemp
Legal Education & Access Innovator
Advancing the responsible use of AI in legal education and practice.
About
David S. Kemp is the managing editor of Oyez and Justia's Verdict and a research associate faculty member at Rutgers Law School. He teaches lawyering skills courses including Legal Analysis, Writing, and Research Skills; Advanced Legal Writing; Generative AI Skills for Lawyers; Professional Responsibility; and Critical Legal Analysis (an academic success course).
He is committed to increasing public and student access to legal education — through improving information design, breaking down institutional and financial barriers, and developing effective and inclusive teaching methods.
His research and teaching focus on the intersection of legal writing and artificial intelligence, exploring how generative AI can enhance legal practice and education while maintaining the highest standards of professional and academic ethics.
Generative AI
Research and application of AI technologies in legal practice and education
Professional Responsibility
Ethics instruction for law students, including ethical use of AI
Academic Success
Comprehensive support for law students and bar preparation
Publications & Presentations
Selected Publications
Artificial Intelligence for Lawyers and Law Students: Crutch, Craft, or Catalyst?
49 Seton Hall J. Legis. & Pub. Pol'y 633 (2025)
Explores how generative AI is transforming legal education and practice, advocating for incorporating AI into law school pedagogy while addressing ethical, practical, and educational concerns. Calls for legal education standards to evolve by equipping students with both foundational legal skills and the capacity to collaborate effectively with AI.
Bins to Bots: Recycling, Individual Responsibility, and the Environmental Regulation of AI
Rutgers Comp. & Tech. L.J. (forthcoming 2025)
Drawing on the United States' recycling experience, this article shows how voluntarism, misaligned incentives, and the absence of efficiency rewards haunt AI's embodied, training, and inference phases. Proposes mandatory lifecycle disclosures, resource-weighted fees, extended producer responsibility, and incentives for low-resource models.
Should We Rely on AI to Help Avoid Bias in Patient Selection for Major Surgery?
24 AMA J. Ethics E773 (2022) · with Charles E. Binkley & Brandi Braud Scully
Explores surgeons' overestimations of operative risk based on patients' race and socioeconomic status, and considers AI-based clinical decision support systems that might offer more accurate, individualized risk assessment to make patient selection more equitable.
Abandoning Precedent: The Case for Bringing ChatGPT into Law Schools
Justia's Verdict (Aug. 25, 2023)
Argues that generative AI tools like ChatGPT can effectively complement conventional methods of learning in law school, predicting that generative AI is poised to revolutionize legal practice and urging forward-looking law educators to embrace the technology.
Selected Presentations
Generative AI for Law Faculty
Rutgers Law School Faculty Series · 2025
A four-session series covering: AI for drafting and reviewing hypos; AI assistance with recommendation and clerkship letters; AI for studying; and AI in writing courses and supervising student notes.
Generative AI Skills for Lawyers
State Bar of Wisconsin CLE · 2024
Practical Applications of AI
State Bar of Wisconsin Annual Meeting & Conference · 2024
Using Artificial Intelligence with Both Benefits and Risks in Mind
State Bar of Wisconsin Annual Meeting & Conference · 2024 · with Hon. Scott Schlegel
Curriculum Vitae
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