Jonathan Choi (USC; Google Scholar) has accepted a lateral offer from Washington University effective Spring 2026:

Jonathan H. Choi is a professor of law at USC Gould School of Law. He specializes in law and artificial intelligence (applying natural language processing to study legal issues), tax law and statutory interpretation. His work has appeared in the New York University Law Review, the Stanford Law Review, the Yale Journal on Regulation and the Yale Law Journal, among others. His work has been covered by a wide variety of news outlets, including ABC News, Bloomberg, CBS News, CNN, the Daily Mail, Fox News, NBC Nightly News, the New Yorker, Reuters, the Star Tribune, and the Washington Post.

Choi graduated summa cum laude from Dartmouth College, with a triple major in computer science, economics and philosophy and earned high honors for his computer science thesis. He earned 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, he practiced tax law at Wachtell, Lipton, Rosen & Katz in New York. He previously taught at the University of Minnesota Law School.

His recent publications include:

• AI Assistance In Legal Analysis: An Empirical Study, 73 J. Legal Educ. 384 (2025) (with Daniel Schwarcz (Minnesota; Google Scholar)) 
• How to Use Large Language Models for Empirical Legal Research, 180 J. Inst. & Theoretical Econ. 214 (2024)
• Lawyering in the Age of Artificial Intelligence, 109 Minn. L. Rev. 147 (2024), (with Amy Monahan (Minnesota; Google Scholar) &  Daniel Schwarcz (Minnesota; Google Scholar)) 
• Measuring Clarity in Legal Text, 91 U. Chi. L. Rev. 1 (2024) 
• Subjective Costs of Tax Compliance, 108 Minn. L. Rev. 1255 (2024) (with Ariel Jurow Kleiman (Loyola-LA; Google Scholar))
• A Limited Defense of Efficiency in a Tax-and-Transfer Framework, 37 Soc. Phil. & Pol’y 252 (2023) 
• AI Tools for Lawyers: A Practical Guide, 108 Minn. L. Rev. Online 1 (2023) (with Daniel Schwarcz (Minnesota; Google Scholar)) 
• Large Language Models Can Reason About Regulations, Philosophical Transactions of the Royal Society: A Mathematical, Physical and Engineering Sciences __ (2023) (with John Ney et al.)
• ChatGPT Goes to Law School, 72 J. Legal Educ. 387 (2022) (with Kristin Hickman (Minnesota; Google Scholar), Amy Monahan (Minnesota) & Daniel Schwarcz (Minnesota; Google Scholar)) 
• Beyond Purposivism in Tax Law, 107 Iowa L. Rev. 1439 (2022) 
• Legal Analysis, Policy Analysis, and the Price of Deference: An Empirical Study of Mayo and Chevron, 38 Yale J. on Reg. 818 (2021) (reviewed by Hayes Holderness  (Richmond) here)
•  The Substantive Canons of Tax Law, 72 Stan. L. Rev. 195 (2020) (reviewed by Kristin Hickman (Minnesota) here)
• An Empirical Study of Statutory Interpretation in Tax Law, 95 N.Y.U. L. Rev. 363 (2020) 
• In Defense of the Billable Hour: A Monitoring Theory of Law Firm Fees, 70 S.C. L. Rev. 297 (2018)

Editor’s Note:  If you would like to receive a daily email with links to tax posts on TaxProf Blog, email me here.