I work at the intersection of law and artificial intelligence — helping lawyers and legal organizations develop the judgment, skills, and institutional frameworks they need to use powerful new tools with competence and care. My practice draws on nearly a decade of law school teaching, deep engagement with the evolving AI landscape, and a focus on translating fast-moving technical developments into clear, usable guidance for legal professionals. I specialize in making complex, high-stakes information actionable.
A comprehensive, annotated generative AI policy for law clinics, synthesizing scholarly research and pedagogical best practices into a modular framework for institutional adoption. Includes a sample multiple-choice quiz to test knowledge and comprehension.
Explore the policyAn interactive tool for law school faculty and administrators to build, customize, and export a generative AI policy that prioritizes pedagogy, professional responsibility, and practice readiness.
Explore the builderA comprehensive legal research framework that integrates generative AI tools into the traditional research process, providing a structured methodology for balancing technological efficiency with rigorous verification and ethical standards. Designed for 1Ls but suitable for all law students.
Explore the guideA selection of invited keynote addresses, panels, and workshops centered on the intersection of generative AI and the law. These engagements reflect my commitment to distilling the complexities of emerging tech into accessible frameworks for legal scholars, practitioners, and general audiences.
This three-session, full-day workshop for Mitchell Hamline School of Law faculty covers AI fundamentals, policies, and assessments. The session on AI fundamentals addresses capabilities and limitations, prompting, and use cases; the policies session included customizable policies for all course types grounded in pedagogical principles; and the assessments session covered the spectrum of AI-resistant, AI-transparent, and AI-integrative assessments for in-person, hybrid, and remote course formats.
This workshop and CLE session for Rutgers Law School clinical faculty covers the responsible and ethical use, including necessary risks and safeguards for integrating Generative AI into clinical legal education.
In this presentation for Rutgers Law School senior leadership, I make the case for integrating AI literacy as an essential component of legal education curriculum and workflows.
Delivered at the RWJBarnabus Health Medical Humanities Conference, this presentation details the practical applications of Large Language Models for research, writing, studying, and skill development.
This symposium keynote talk explores the environmental regulation and responsibility of AI by applying key lessons learned from the history of consumer recycling.
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.
Covering ethical considerations, prompt engineering, and the limitations of LLMs, this remote presentation introduced members to fundamental generative AI skills.
This presentation (co-presented with Anna Elbroch) sought to inform educators and faculty about some best practices for integrating Generative AI tools into online and other educational courses.
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An introductory exploration of general AI models and prompting strategies, designed to highlight high-value use cases alongside the essential ethical guardrails required for legal work.
As a panelist for the AI and Legal Ethics portion of this symposium, I explained the academic integrity and professional responsibility implications of AI in law schools.
This brief ethics overview for legal writing professors analyzed the implications of ABA Formal Opinion No. 512 for Generative AI ethics in both legal writing and ethics instruction.
This keynote address (co-presented with Hon. Scott Schlegel) at the State Bar of Wisconsin Annual Meeting & Conference addressed the specific benefits and risks of using artificial intelligence in the practice of law, including hallucinations, deepfakes and authentication of evidence, and ethical duties.
In this CLE session at the State Bar of Wisconsin Annual Meeting & Conference, this presentation provided an overview of generative AI utility in legal practice, covering the mechanics of effective prompting, diverse workflow applications, and the critical security warnings inherent to the technology.
This presentation advocated for the integration of generative AI into law school curricula, exploring how faculty and administrators can master the technology's mechanics, ethics, and practical applications to effectively adapt teaching and assessment for an AI-augmented legal landscape.
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A comprehensive look at the capabilities and limitations of LLMs, featuring a deep dive into prompt design, practical office integration, and the primary ethical risks facing practitioners.
Focused on improving legal writing, this California CLE Webinar highlights essential techniques drawn from the distinct writing styles of renowned Supreme Court Justices.
"If a machine can easily do everything we are asking our students to do, then we are not asking enough of our students."
— David S. KempI contribute to the legal conversation through a mix of formal journal articles and digital editorials. My work often explores the intersection of emerging technologies, equity, and ethics, distilling complex legal frameworks into clear, accessible insights for scholars, industry leaders, and the public alike.
49 Seton Hall J. Legis. & Pub. Pol'y 633 (2025)
This article explores the integration of generative AI into legal education, examining its history and the potential for faculty to utilize it for pedagogical, administrative, and scholarly purposes. It further addresses the risks of student over-reliance on AI, proposing that law schools should treat AI as a collaborative tool and shift toward assessments that prioritize process and diverse lawyering skills over traditional exams.
Rutgers Comp. & Tech. L.J. (forthcoming 2025)
Drawing on the failures of consumer recycling, this article argues that AI's environmental impact cannot be solved through individual responsibility or voluntary corporate commitments alone. Instead, it proposes a regulatory framework that aligns market forces with sustainability by using mandatory disclosures, resource-weighted fees, and producer responsibility to reward resource efficiency.
Verdict (Sep. 2023)
The article argues that ChatGPT's well-known failures in legal research — such as hallucinating cases and misrepresenting the law — can be turned into a pedagogical advantage, by having law students use AI-generated output as a starting point for learning how to verify legal information using reliable tools like Westlaw and LexisNexis.
Verdict (Aug. 2023)
The article argues for the integration—rather than prohibition—of generative AI tools, specifically ChatGPT, into legal education. It suggests that guided AI instruction on how to harness this disruptive technology prepares law students for the evolving landscape of legal practice.
I spent nearly a decade teaching in law schools — at Rutgers Law School, UC Berkeley School of Law, and UC Law San Francisco — where I built curricula, assessment frameworks, and training programs around one of legal education's most pressing questions: how to prepare lawyers for a profession being reshaped by artificial intelligence. That work included six semesters of a course I designed, first called Emerging Tools & Technology in the Practice of Law and most recently AI Skills for Lawyers, centered on building the kind of transferable judgment and problem-solving skills that hold up as tools and circumstances change.
I now bring that same approach — grounded in learning science, professional responsibility, and close tracking of a field that shifts weekly — to the practice side, working on AI innovation within a global law firm. The transition from teaching to practice sharpened a conviction I've held throughout: the people building and deploying these tools need the same rigor around pedagogy, ethics, and institutional design that the best law schools demand.
My approach to training and curriculum development draws on how memory works, how skills transfer, and how judgment develops under pressure. That foundation shapes everything from how I sequence a training program to how I design individual exercises.
I remain actively engaged with legal education and welcome conversations with law school administrations, faculties, and legal organizations about AI pedagogy, curriculum design, and the institutional questions that don't yet have settled answers.
Juris Doctor
Bachelor of Arts, Psychology
A complete record of my academic appointments, publications, presentations, and professional experience.
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