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Session Chair: Danny Weitzner

Liane Huttner is an Assistant Professor at University Paris-Saclay. She holds a PhD in law of the University Paris 1 Panthéon-Sorbonne. She’s specialised in digital law, in particular data protection and AI. Her first book on algorithmic decision-making has received the prize André Isoré of the University of Paris. Her works have been published in journals, such as Artificial Intelligence & Law, Communication Commerce Electronique and Dalloz IP/IT. Liane has been a visiting scholar at the University of Oxford and at the Max Planck Institute of Hamburg. She was also a Max Weber post-doctoral fellow at the European University Institute. In 2025, she is a Northwestern Pritzker School of Law Comparative Law Initiative visiting scholar. She has advised public authorities, such as the French data protection authority and the French government committee on AI, on topics relating to law and technologies. Liane is also the co-creator of the domain specific computer language Catala.

Kai Zenner is Head of Office and Digital Policy Adviser for MEP Axel Voss (European People’s Party) in the European Parliament. He focuses on AI, privacy, the EU’s digital transition and Better Regulation. Mr Zenner is a member of the OECD.AI Network of Experts and of the AI Governance Alliance at the World Economic Forum. He was also part of the temporary Expert Group that supported the ‘High-Level Advisory Body on AI’ of the United Nations. Mr Zenner was awarded best MEP Assistant in 2023, ranked Place #13 in Politico’s Power 40 – class 2023, received the European AI Award 2024 for AI policy shapers (EAIF), and was listed by Euronews as one of the ’14 movers and shakers to watch for in Tech policy in 2025′.

Frauke Kreuter holds the Chair of Statistics and Data Science at LMU Munich and, as a faculty member in the Joint Program in Survey Methodology (JPSM), co-directs the University of Maryland’s Social Data Science Center (SoDa). She is an elected fellow of the American Statistical Association and the International Statistical Institute. A widely recognized leader in her field, she has received multiple honors, including the Warren Mitofsky Innovators Award from the American Association for Public Opinion Research (AAPOR)—twice—and currently serves as AAPOR’s President. As Co-Founder of the Coleridge Initiative, she promotes secure and effective data access for policy and research. She also co-hosts the German-language podcast Dig Deep. Professor Kreuter’s work focuses on data quality, appropriate data flow, and their impact on research and policymaking, particularly in the context of AI regulation. She actively contributes to discussions on the AI Act, emphasizing the importance of reliable data for ethical and transparent AI systems.

Lilian Edwards is a leading academic in the field of Internet law. She has taught information technology law, e-commerce law, privacy law and Internet law at undergraduate and postgraduate level since 1996 and been involved with law and artificial intelligence (AI) since 1985. She is the editor and major author of Law, Policy and the Internet, one of the leading textbooks in the field of Internet law (Hart, 2018). She won the Future of Privacy Forum award in 2019 for best paper (“Slave to the Algorithm” with Michael Veale) and the award for best non-technical paper at FAccT* in 2020, on automated hiring. In 2004 she won the Barbara Wellberry Memorial Prize in 2004 for work on online privacy where she invented the notion of data trusts, a concept which ten years later has been proposed in EU legislation. She is a partner in the Horizon Digital Economy Hub at Nottingham, the lead for the Alan Turing Institute on Law and AI, and a fellow of the Institute for the Future of Work. At Newcastle, she is the theme lead in the data NUCore for the Regulation of Data. She currently holds grants from the AHRC and the Leverhulme Trust. Edwards has consulted for inter alia the EU Commission, the OECD, and WIPO.

Session Chair: Ran Canetti

Conference registration and badge pickup open for all participants.

Session Chair: Boris Paal

Session Chair: Ran Canetti

Abstract: The choice of features — also known as variables or attributes — is well understood to be a vector for the introduction of bias in decision-making procedures. With the goal of establishing norms of fairness, we interrogate the use of socially salient features in training and deployment of prediction algorithms and find that the lawyers have it right: it depends! Excavating examples leading to this and other features-first conclusions, and drawing on readings from the history of statistics, public health, and legal scholarship, we highlight new lessons for the theory and practice of algorithmic fairness.


Bio: Cynthia Dwork, Gordon McKay Professor of Computer Science at Harvard, and Affiliated Faculty at Harvard Law School and Department of Statistics, is renowned for placing privacy-preserving data analysis on a mathematically rigorous foundation. She has also made seminal contributions in cryptography and distributed computing, and she spearheaded the investigation of the theory of algorithmic fairness, her current focus. Dwork is the recipient of numerous awards, including the National Medal of Science, the IEEE Hamming Medal, the RSA award for Excellence in Mathematics, the Dijkstra, Gödel, and Knuth Prizes, and the ACM Paris Kanellakis Theory and Practice Award. She is a member of the US National Academy of Sciences and the US National Academy of Engineering, and is a Fellow of the American Academy of Arts and Sciences and the American Philosophical Society.

Session Chair: Sarah Scheffler

Session Chair: James Grimmelmann

Conference registration and badge pickup open for all participants.

Session Chair: Aloni Cohen

Session Chair: Felix Wu

Session Chair: Joan Feigenbaum

Session Chair: A. Feder Cooper