This field is required or invalid. Please provide a valid input.
This field is required or invalid. Please provide a valid input.
This field is required or invalid. Please provide a valid input.
This field is required or invalid. Please provide a valid input.
This field is required or invalid. Please provide a valid input.
Mode of Participation: *
This field is required or invalid. Please provide a valid input.
Mailing List Registration: *
This field is required or invalid. Please provide a valid input.
MPI Privacy Policy: *
This field is required or invalid. Please provide a valid input.
This field is required or invalid. Please provide a valid input.

Fields marked with * are required.

Artificial Justice Speaker Series - Virtual Lecture with Jed Stiglitz

 

"Precedent-Predictability: Stability and Innovation in Law, 1790–2026"

 Wednesday, 7 October 2026, 2:00 p.m. - 3:00 p.m. (CEST)

 

About the Speaker:

Jed Stiglitz is the Richard and Lois Cole Professor of Law at Cornell University. His research focuses on administrative law and the intersection of law and artificial intelligence. In administrative law, he examines the relationship between judicial review and the values of trust and accountability in the administrative state. In his work on AI, he explores how data-driven methods and machine learning can inform legal reasoning, institutional design, and regulatory governance. He also studies legislation and other areas of public law. His work has appeared or is forthcoming in the leading law review and peer review outlets, such as the Yale Law Journal, University of Pennsylvania Law Review, Cornell Law Review, Journal of Legal Studies, Journal of Law, Economics, & Organization, and the Journal of Legal Analysis. His co-authored book on American elections was published by Princeton University Press. His most recent book, on the architecture of the modern state, was published by Cambridge University Press. Following law school, he clerked for the Honorable Stephen F. Williams of the D.C. Circuit Court of Appeals.

 

About the Topic:

How well do like prior cases predict the outcomes of Supreme Court decisions? And how has that changed over time? This article develops a contamination-sensitive language model instrument to identify relevant precedents, determine their implications for a subject case, and aggregate those implications for the case. Applied against decided cases from founding to the present, this instrument allows us to assess the outcome of a case that precedents would have ex ante predicted, and to identify instances in which the Court does or does not follow the outcome forecasted by precedent. The results provide insight into historical stability and innovation in law, especially as against identifiable instances of settled law. Preliminary results based on a fractional run suggest weak stability in the 1930s and 1940s, strong stability in the second half of the twentieth century and early twenty-first century, and weak stability in recent years. The descriptive results generate questions about the rule of law implications for the Court’s historical institutional and jurisprudential regimes.

 

About the Speaker Series:

The Artificial Justice Speaker Series features guests working at the intersection between law, computer science, and the humanities. Neither technical nor juristic knowledge is a prerequisite for participation—the Series is aimed at anyone with an interest in critical and interdisciplinary perspectives on “Law and AI”. The event takes place on Zoom and is scheduled to last one hour.

Max Planck Institute for Comparative and International Private Law