Daniel E. Ho is the William Benjamin Scott and Luna M. Scott Professor of Law at Stanford Law School, Professor of Political Science, Senior Fellow at the Stanford Institute for Economic Policy Research, Associate Director of the Stanford Institute for Human-Centered Artificial Intelligence, and Director of the Regulation, Evaluation, and Governance Lab (RegLab).

Ho serves as an appointed member to the National Artificial Intelligence Advisory Commission (NAIAC), advising the White House National AI Initiative Office, and as Senior Advisor on Responsible AI to the U.S. Department of Labor. He is also a member of the Committee on National Statistics (CNSTAT) of the National Academies of Science, Engineering, and Medicine and a Public Member of the Administrative Conference of the United States (ACUS).

His scholarship focuses on administrative law, regulatory policy, and antidiscrimination law. With the RegLab, his work has developed high-demonstration projects of data science and machine learning in public policy, through partnerships with a range of government agencies, including the Internal Revenue Service, the Treasury Department, the Environmental Protection Agency, the Department of Labor, the Santa Clara County Public Health Department, and Seattle and King County Public Health. The collaboration with Santa Clara County was awarded the Innovative Practice Gold Award for “the highest level of program innovation” to serve “community during the COVID-19 pandemic” by the National Association of County and City Health Officials.

He received his J.D. from Yale Law School and Ph.D. from Harvard University and clerked for Judge Stephen F. Williams on the U.S. Court of Appeals, District of Columbia Circuit. He is the recipient of numerous awards, including the John Bingham Hurlbut Award for Excellence in Teaching at Stanford Law School, the Carole Hafner Award for the best paper at the International Conference on Artificial Intelligence and Law, the Best Empirical Paper Prize from the American Law and Economics Review, and the Warren Miller prize for the best paper published in Political Analysis.