This article was authored by Alex Thierer, ACUS Legal Intern.
At the upcoming 71st Plenary Session on June 13, the Administrative Conference of the United States will hear from renowned scholars on the use of artificial intelligence (AI) in the federal administrative process.
Federal agencies are increasingly considering the role that AI, machine learning, and related techniques can play in adjudication, rulemaking, and other regulatory activities. The ACUS Office of the Chairman is working with scholars and researchers on the forefront of researching how agencies are currently using AI, how agencies could use AI, and how these uses implicate core administrative law doctrines, such as the nondelegation doctrine, arbitrary-and-capricious review, due process, and rules governing reliance on subordinates for decisions.
During a special lunchtime session on June 13, Cary Coglianese will deliver a presentation on his work related to governmental uses of AI. Professor Coglianese is a Professor of Law and Political Science at the University of Pennsylvania, Director of the Penn Program on Regulation, and Chair of the ACUS Committee on Rulemaking. He is the co-author of Regulating by Robot: Administrative Decision-Making in the Machine Learning Era, published in the Georgetown Law Review, and a frequent commentator on the growing role of AI in government.
Stanford Law Professors David Freeman Engstrom and Daniel Ho and New York University Law Professor Catherine M. Sharkey will discuss the research they and California Supreme Court Justice Mariano-Florentino Cuéllar are undertaking on behalf of the Office of the Chairman. Professor Engstrom and Professor Ho are faculty affiliates at the Stanford Institute for Human-Centered AI. They recently co-taught a policy lab at Stanford exploring the growing role AI plays in federal agencies. The project they are leading for ACUS explores how federal agencies currently incorporate artificial intelligence into their decision-making processes and use AI to accomplish their statutory goals.
Learn more about ACUS’s AI initiatives in our November 2018 press release and on the project’s homepage here.
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