Dan Bateyko studies AI and Law at Cornell University's Department of Information Science. His recent academic affiliations include fellowships at the Princeton Polaris Lab, the Stanford RegLab, and the Institute for Law & AI.
Prior to starting his PhD, Dan spent several years contributing to research and policy around emerging technologies—mostly at places with “Center” in their name—including the Center for Democracy & Technology, the Stanford Cyber Policy Center, and the Center on Privacy & Technology at Georgetown Law, where he now serves on the Advisory Board.
His work has been supported by the MacArthur Foundation through the Artificial Intelligence, Policy, and Practice initiative, a Google Public Policy Fellowship, and a Thomas J. Watson Fellowship. He holds a Master of Law and Technology from Georgetown University Law Center and a B.A. from Middlebury College.
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Selected work
| Hidden in Plain Text: LLM-Assisted Detection of Discriminatory Local Laws | International Conference on Artificial Intelligence and Law (ICAIL) | 2026 |
| RCTs for Human-AI Evaluation: Methodological Challenges and Practical Solutions | RAND Working Paper + AIES | 2026 |
| One Bad NOFO? AI Governance in Federal Grantmaking | ACM FAccT | 2025 |
| Bureaucratic Backchannel: How r/PatentExaminer Navigates AI Governance | Sociotechnical AI Governance workshop @ CHI | 2025 |
| Human-AI Collaboration workshop @ ACM EC | 2025 |
Shelved
| Mapping Funding Landscapes of Civil Society and Public Interest Technologies: Voids, Trends, and Stakes | Talk @ PLSC | 2025 |
| Poster @ AIPP | 2024 | |
| Internet Law Works in Progress | 2024 |