Jonathan Choi
James Carr Professor of Law
Starting spring of 2026, Jonathan H. Choi will be the James Carr Professor of Law at WashU Law, specializing in law and artificial intelligence, tax law, and statutory interpretation. He is particularly interested in applications of natural language processing (NLP) to empirical legal studies and has published work applying NLP to issues in tax law, statutory interpretation, administrative law, judicial behavior, criminal law, and the legal profession.
His work has appeared in the New York University Law Review, the Stanford Law Review, the University of Chicago Law Review, the Yale Journal on Regulation, and the Yale Law Journal, among others. He has been interviewed or cited in a variety of media outlets, including ABC, Bloomberg, CBS, CNN, NBC, the New York Times, NPR, the New Yorker, and USA Today.
Professor Choi graduated summa cum laude from Dartmouth College, with a triple major in Computer Science, Economics, and Philosophy and high honors for his Computer Science thesis. He received a JD at the Yale Law School, where he was the Executive Bluebook Editor of the Yale Law Journal and a founding Co-Director of the Yale Journal on Regulation Online. Before entering academia, Professor Choi practiced tax law at Wachtell, Lipton, Rosen & Katz. He previously taught at the University of Southern California and the University of Minnesota, and he has been a Visiting Professor of Law at Harvard Law School.
- Education
- JD, Yale Law School, 2014
- BA, Dartmouth College, 2011
- Areas of Expertise
- Law and Artificial Intelligence
- Tax law
- Statutory Interpretation
- Publications
- Measuring Clarity in Legal Text, 91 UNIVERSITY OF CHICAGO LAW REVIEW 1 (2024)
- Subjective Costs of Tax Compliance, 108 MINNESOTA LAW REVIEW 1255 (2024) (with Ariel Jurow Kleiman)
- Lawyering in the Age of Artificial Intelligence, 109 MINNESOTA LAW REVIEW 147 (2024) (with Amy Monahan and Daniel Schwarcz)
- AI Tools for Lawyers: A Practical Guide, 107 MINNESOTA LAW REVIEW HEADNOTES 1 (2023) (with Daniel Schwarcz)
- Beyond Purposivism in Tax Law, 107 IOWA LAW REVIEW 1439 (2022)
- Legal Analysis, Policy Analysis, and the Price of Deference: An Empirical Study of Mayo and Chevron, 38 YALE JOURNAL ON REGULATION 818 (2021)
- The Substantive Canons of Tax Law, 72 STANFORD LAW REVIEW 195 (2020)
- An Empirical Study of Statutory Interpretation in Tax Law, 95 NEW YORK UNIVERSITY LAW REVIEW 363 (2020)
- In Defense of the Billable Hour: A Monitoring Theory of Law Firm Fees, 70 SOUTH CAROLINA LAW REVIEW 297 (2018) (law school paper)
- Early Release in International Criminal Law, Note, 123 YALE LAW JOURNAL 1784 (2014)
- Tax Commitment Devices, 15 JOURNAL OF BUSINESS AND SECURITIES LAW 1 (2014) (law school paper)
Published or Forthcoming (Peer-Reviewed or -Edited)
- Interrogating LLM Design Under a Fair Learning Doctrine, 2025 ACM CONFERENCE ON FAIRNESS, ACCOUNTABILITY, AND TRANSPARENCY (with Johnny Wei et al.)
- AI Assistance in Legal Analysis: An Empirical Study, 72 JOURNAL OF LEGAL EDUCATION (forthcoming 2025) (with Daniel Schwarcz)
- How to Use Large Language Models for Empirical Legal Research, 180 JOURNAL OF INSTITUTIONAL AND THEORETICAL ECONOMICS 214 (2024) (invited)
- Large Language Models as Tax Attorneys: A Case Study in Legal Capabilities Emergence, 382 PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A: MATHEMATICAL, PHYSICAL AND ENGINEERING SCIENCES 1 (2023) (with John Ney et al.) (invited)
- LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models, 37 PROCEEDINGS OF THE CONFERENCE ON NEURAL INFORMATION PROCESSING SYSTEMS TRACK ON DATA AND BENCHMARKS 44123 (2023) (with Neel Guha et al.)
- A Limited Defense of Efficiency in a Tax-and-Transfer Framework, 37 SOCIAL PHILOSOPHY AND POLICY 252 (2023) (invited)
- ChatGPT Goes to Law School, 72 JOURNAL OF LEGAL EDUCATION 387 (2023) (lead author, with Kristin Hickman, Amy Monahan & Daniel Schwarcz)