Katherine is a senior research scientist at Google DeepMind and co-founder of The GenLaw Center. Her work has provided essential empirical evidence and measurement for grounding discussions around concerns that language models infringe copyright, and about how language models can respect an individuals’ right to privacy and control of their data. Additionally, she has proposed methods of reducing memorization. Her work has received recognition at ACL, USENIX, and ICLR.

A. Feder Cooper is a scalable ML researcher, working on reliable measurement and evaluation and with contributions spanning distributed training, uncertainty estimation, generative AI, and associated questions in tech policy and law. Cooper is also an Affiliate at the Berkman Klein Center for Internet & Society at Harvard and a founder of The GenLaw Center, and was named a “Rising Star in EECS” by MIT. Cooper’s work has been awarded at top conferences, including NeurIPS, AAAI, and AIES.

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Hoda Heidari is the K&L Gates Career Development Assistant Professor in Ethics and Computational Technologies at Carnegie Mellon University, with joint appointments in Machine Learning and Societal Computing, and affiliations with the Human-Computer Interaction Institute and Heinz College of Information Systems and Public Policy. Her research is broadly concerned with the social, ethical, and economic implications of Artificial Intelligence, particularly issues of fairness and accountability through the use of Machine Learning in socially consequential domains. Her work in this area has won a best-paper award at the ACM Conference on Fairness, Accountability, and Transparency (FAccT), an exemplary track award at the ACM Conference on Economics and Computation (EC), and a best-paper award at the IEEE Conference on Secure and Trustworthy Machine Learning (SAT-ML). Dr. Heidari co-founded and co-leads the university-wide Responsible AI Initiative at CMU.

Alexandra Reeve Givens is the CEO of the Center for Democracy & Technology, a nonpartisan, nonprofit organization fighting to protect civil rights and civil liberties in the digital age. She is a frequent public commentator on ways to protect users’ online privacy and access to information, and to ensure emerging technologies advance human rights and democratic values.

At CDT, Alex leads an international team of lawyers and technologists shaping technology policy, governance and design. CDT advocates to policymakers and the courts in the U.S. and Europe, engages with companies to improve their policies and product designs, and shapes public opinion on major tech policy issues.

Alex previously served in the United States Senate, as the chief counsel on the Senate Judiciary Committee covering innovation and consumer protection. Prior to joining CDT, she was the founding Executive Director of Georgetown University’s Institute for Technology Law & Policy, where she set the Institute’s research agenda, and directed its public convenings, research activities, and strategic development. Alex began her career as a litigator at Cravath, Swaine & Moore in New York City, and taught for nine years as an adjunct professor at Columbia Law and Georgetown Law.

Alex serves as Vice Chair of the Christopher & Dana Reeve Foundation. She holds a B.A. from Yale University and a J.D. from Columbia University School of Law.

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Miranda Bogen is the founding director of the AI Governance Lab at the Center for Democracy & Technology, where she works to develop and promote adoption of robust, technically-informed solutions for the effective regulation and governance of AI systems. Prior to joining CDT, Miranda helped to lead strategy and implementation of responsible AI practices at Meta, conducted foundational research at the intersection of machine learning and civil rights at Upturn, and served as co-chair of the Fairness, Transparency, and Accountability Working Group at the Partnership on AI.

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Paul Ohm is a Professor of Law at the Georgetown University Law Center in Washington, D.C. In his research, service, and teaching, Professor Ohm builds bridges between computer science and law, utilizing his training and experience as a lawyer, policymaker, computer programmer, and network systems admininstrator. His research focuses on information privacy, computer crime law, surveillance, technology and the law, and artificial intelligence and the law. Professor Ohm has published landmark articles about the failure of anonymization, the Fourth Amendment and new technology, and broadband privacy. His work has defined fields of scholarly inquiry and influenced policymakers around the world.

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James is a professor at Cornell Law School and Cornell Tech, where he direct CTRL-ALT, the Cornell Tech Research Lab in Applied Law and Technology.

James studies how laws regulating software affect freedom, wealth, and power. He tries to help lawyers and technologists understand each other. His research interests include search engines, digital copyright, online governance, content moderation, and other topics in computer and Internet law.

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Hoon is a J.D. candidate and Tech Law & Policy Scholar at Georgetown Law. Hoon was a summer associate at HWG LLP (formerly Harris, Wiltshire & Grannis LLP) as a Federal Communications Bar Association (FCBA) Diversity Pipeline Intern. Prior to law school, Hoon worked at Tripadvisor and Applied Predictive Technologies where he acquired extensive experience with data science and analytics. Hoon also served in the Republic of Korea’s military intelligence where he specialized in Open Source Intelligence (OSINT). Hoon is interested in legal issues around regulating algorithms, data privacy, democracy in an online economy. Currently, Hoon is particularly interested in the intersection between online services, consumer protection, and tort liability.

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Nari Johnson is a Machine Learning PhD student at Carnegie Mellon studying tools and processes to govern artificial intelligence systems. Her present research interests include AI transparency, evaluation, and accountability.

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Michael Feffer is a Societal Computing PhD student at Carnegie Mellon University. His research focuses on the interplay between AI and society and includes topics such as algorithmic fairness, music information retrieval, participatory approaches to machine learning, and generative AI evaluation.

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Ningjing Tang is a PhD student at the Human Computer Interaction Institute at Carnegie Mellon University. Her research focuses on human-centered evaluation of AI systems.

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Administrative and Events Coordinator at CMU’s Block Center