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AI promises to transform how government agencies work. Where will it have the biggest impact? What are some challenges around transparency, privacy, bias, and accountability? This talk will go beyond the headlines and share highlights of a just-completed report on AI in the US Government.
Despite the rapid adoption of LLM chatbots, little is known about how they are used. We approach this question theoretically and empirically, modeling a user who chooses whether to complete a task herself, ask the chatbot for information that reduces decision noise, or delegate execution to the chatbot...
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Despite the rapid adoption of LLM chatbots, little is known about how they are used. We approach this question theoretically and empirically, modeling a user who chooses whether to complete a task herself, ask the chatbot for information that reduces decision noise, or delegate execution to the chatbot...
AI coding agents now complete multi-hour coding benchmarks with roughly 50% reliability, yet a randomized trial found experienced open-source developers took about 19% longer when allowed frontier AI tools than when tools were disallowed...
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AI coding agents now complete multi-hour coding benchmarks with roughly 50% reliability, yet a randomized trial found experienced open-source developers took about 19% longer when allowed frontier AI tools than when tools were disallowed...
How did we get to today’s technology which now supports a trillion dollar AI industry? What were the key scientific breakthroughs? What were the surprises and dead-ends along the way...
How did we get to today’s technology which now supports a trillion dollar AI industry? What were the key scientific breakthroughs? What were the surprises and dead-ends along the way...
David Freeman Engstrom - Professor and Associate Dean for Strategic Initiatives, Stanford Law School
David Freeman Engstrom is the Bernard D. Bergreen Faculty Scholar and an Associate Dean at Stanford Law School. He is an elected member of the American Law Institute and a faculty affiliate at the Stanford Institute for Human-Centered AI, CodeX: The Stanford Center for Legal Informatics, and the Regulation, Evaluation, and Governance Lab (RegLab). He received a J.D. from Stanford Law School, an M.Sc. from Oxford University, and a Ph.D. in political science from Yale University and clerked for Chief Judge Diane P. Wood on the U.S. Court of Appeals for the Seventh Circuit. Before joining Stanford's faculty, he practiced law, representing clients before the U.S. Supreme Court and other courts and agencies.
Daniel Ho - Professor of Law, Professor of Political Science, Director of the Regulation, Evaluation, and Governance Lab (RegLab) at Stanford University
Daniel Ho is the William Benjamin Scott and Luna M. Scott Professor of Law, Professor of Political Science, and Senior Fellow at the Stanford Institute for Economic Policy Research at Stanford University. Dr. Ho 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 directs the Regulation, Evaluation, and Governance Lab (RegLab) at Stanford, is a Faculty Fellow at the Center for Advanced Study in the Behavioral Sciences, and is an Associate Director of the Stanford Institute for Human-Centered Artificial Intelligence (HAI).