Conference on Data Science and Law

Call for Papers

Sponsored by Fordham University, ETH Zurich, and the University of Virginia.

Interest is growing among scholars from a variety of disciplines and across the globe in research at the intersection of data science and law. In recent years, the digitization of legal texts and developments in statistics and computer science have paved the way for new methodological approaches in this area. This constellation of new data and methods has created exciting opportunities for progress on old questions as well as the prospect of opening entirely new areas in empirical legal scholarship.

The 3rd Conference on Data Science and Law will convene researchers across disciplines who are interested in this burgeoning field. Scholars in law, social and behavioral sciences, digital humanities, computer science, machine learning, and data analytics are invited to present works-in-progress in all areas of empirical legal studies that involve big data sources or use data science techniques, including natural language processing, machine learning, algorithmic fairness, topic modeling, or network analysis. The purpose of the conference is to highlight the best and most innovative scholarship in data science and law and to help build an intellectual community in support of this new field. Works that are descriptive in nature are invited as well as research that focuses on causal inference.

The workshop will be held at Fordham Law School in New York City on August 5th – 6th, 2025. Researchers are invited to submit unpublished working papers for presentation at the conference by April 15, 2025. Papers will be selected through a peer review process. While full drafts are recommended, we will accept and review extended abstracts or slide decks.

Submissions for the conference have now closed. If you are interested in attending, please register at this link.

Please feel free to circulate this call to colleagues or graduate students who may be interested.
On behalf of the organizers,
Elliott Ash, ETH Zurich
Mike Livermore, University of Virginia
Aniket Kesari, Fordham University

Please see the tentative conference schedule below

CDSL 2025 – August 5

Time	Room 4-04	Room 4-05
9:15 AM	Welcome and Opening Remarks – Room 4-08
9:30 AM	Adam Badawi (UC Berkeley) Separating Fact and Opinion in Financial Disclosures Discussant: Sabrina Arias Weikun Dong (WashU) AI Teaching Puffery Discussant: Adam Badawi Sabrina Arias (Lehigh) Everything Old is New Again: Textual Recycling in UN Resolutions Discussant: Weikun Dong	Jakob Merane (ETH Zurich) Machine Learning Compliance Analysis for Email Regulation Discussant: Janet Freilich Emily Hua (Harvard) How Close is Close Enough: Examining TransUnion’s Impact on Statutory Privacy Violations Discussant: Jakob Merane Janet Freilich (BU) Using Legal Texts to Assess the Novelty of AI-Generated Drugs Discussant: Emily Hua
11:30 AM	Plenary – Room 4-08 Dan Milo (NYU) The Costs of Housing Regulation: Evidence From Generative Regulatory Measurement Discussant: Ryan Hubert
12:15 PM	Lunch (on your own)
1:30 PM	Kevin Cope (UVA) Judicial Dimensions Discussant: Josh Fischman Jon Choi (WashU) Large Language Models Are Unreliable Judges Discussant: Kevin Cope Joshua Fischman (UVA) Ideology in the Circuit Courts: Estimates from Criminal Cases, 2008–23 Discussant: Jon Choi	Justin Simard (Michigan State) Mapping the Canon: Case Selection in Law School Casebooks Discussant: Mike Livermore Eric Martinez (UChicago) Traditional and Computational Canons Discussant: Justin Simard Mike Livermore (UVA) Speaking With or Talking Past: Discursive Cooperation on the U.S. Supreme Court Discussant: Eric Martinez
3:30 PM	Break
4:00 PM	Lightning Talks (12 talks – 5 min each): 1. Vivian Nastl (ETH Zurich), Extending Legal Databases with LLM Annotations: Opportunities and Challenges 2. Yu Fan (ETH Zurich), AI and Law School Exams 3. Ryan Leung (Northwestern University), Testing the Rule of Law: Authoritarian Institutional Shock in Hong Kong 4. Karolina Naranjo (University of Virginia), Arinbjörn Kolbeinsson (UVA, Regava), Benedikt Kolbeinsson (Imperial College London, Regava), Jonathan Kropko (UVA), Yangfeng Ji (UVA), and Thomas Hartvigsen (UVA), Extracting Patterns of Legal Citations over Time with Large Language Models: A Case Study of Colombia and Iceland 5. Matthew Dahl (Yale University), Bye-bye, Bluebook? Testing AI's Ability to Automate Legal Procedure 6. Rui Zuo (University of Texas at Austin), Algorithm as Manager: How Algorithmic Judge-Case Assignment Influences Court Performance 7. Yawri Carr (TU Munich), Explainable AI in Natural Language Processing: Enhancing Transparency in Legal Judgment Predictions with Shapely Values 8. Qin (Sky) Ma (Max Planck Institute for the Study of Crime, Security and Law), The Dual Impact of Generative AI on Judicial Efficiency: A Cross-Jurisdictional Analysis 9. Bao Kham (Cornell Tech), Measuring Legal Importance: From Case Citations to Linguistic Shifts
5:00 PM	Cocktail Hour and Poster Session
7:00 PM	Dinner. All & Sundry (312 W 58th St, New York, NY 10019)

CDSL 2025 – August 6

Time	Room 4-04	Room 4-05
9:30 AM	Zubin Jelveh (University of Maryland) Perils and Pitfalls in the Use of Synthetic Control Methods to Study Public Safety Interventions Discussant: Talia Gillis David Abrams (UPenn) Prose and Cons: Measuring Policing Disparities with Text Data Discussant: Zubin Jelveh Talia Gillis (Columbia) Algorithmic UDAAP Discussant: David Abrams	Aniket Kesari (Fordham University) What Are Oral Arguments For? Discussant: Dan Milo Ryan Copus (UMKC) and Hannah Laqueur (UC Davis) Error in the Loop: How Human Mistakes Can Improve Algorithmic Learning Discussant: Daniel Chen Daniel Chen (Harvard Radcliffe) Large Language Models as Machini Moralis: Aligning AI with Social Preferences Discussant: Ryan Copus
11:30 AM	Plenary Discussion
12:15 PM	Lunch (on your own)
1:30 PM	Marshall Steinbaum (University of Utah) The Balance of Power in Franchising Discussant: Ben Chen Ben Chen (HKU) Official Discourses of Legality in China: A Computational Analysis of 30 Years of the People's Daily Discussant: Marshall Steinbaum	David Schwartz (Northwestern) SCALES: Systematic Content Analysis of Litigation Events Discussant: Dominik Stammbach Dominik Stammbach (Princeton) An open-source and free Search Engine for Paragraph Retrieval from United States' Caselaw Discussant: David Schwartz
2:50 PM	Concluding Remarks