Our weekly SRI Seminar Series welcomes Vincent Conitzer, a professor of computer science at Carnegie Mellon University where he directs the Foundations of Cooperative AI Lab (FOCAL), head of technical AI engagement at the Institute for Ethics in AI, and a professor of computer science and philosophy at the University of Oxford.
Conitzer works on artificial intelligence, including the intersections between AI and game theory, and AI and ethics. His recent research explores how to determine the objectives AI systems should pursue, especially when these objectives have complex effects on various stakeholders.
Social choice and game theory for AI alignment
It is often hard to get an AI system to do what someone really wants it to do—a problem referred to as “aligning” the AI. But even if we can solve that problem reasonably well, other problems remain. One is the problem of accounting for multiple stakeholders: we generally want to take into account the preferences, values, or judgments of more than one party, even if they conflict with each other. Another is the problem of multiple interacting AI systems: even if each one of them individually is reasonably well aligned, interactions among them can produce disastrous outcomes. In this talk, I’ll discuss how social choice theory and game theory can be used and extended to address these problems. (No previous background in social choice or game theory required.)
Vincent Conitzer is a professor of computer science (with affiliate/courtesy appointments in machine learning, philosophy, and the Tepper School of Business) at Carnegie Mellon University (CMU), where he directs the Foundations of Cooperative AI Lab (FOCAL). He is also head of technical AI engagement at the Institute for Ethics in AI, and professor of computer science and philosophy at the University of Oxford.
Previous to joining CMU, Conitzer was the Kimberly J. Jenkins Distinguished University Professor of New Technologies and a professor of computer science, economics, and philosophy at Duke University. He received PhD (2006) and MS (2003) degrees in computer science from Carnegie Mellon University, and an AB (2001) degree in Applied Mathematics from Harvard University.
Conitzer has received the 2021 ACM/SIGAI Autonomous Agents Research Award, the Social Choice and Welfare Prize, a Presidential Early Career Award for Scientists and Engineers (PECASE), the IJCAI Computers and Thought Award, an NSF CAREER award, the inaugural Victor Lesser dissertation award, an honorable mention for the ACM dissertation award, and several awards for papers and service at the AAAI and AAMAS conferences. He has also been named a Guggenheim Fellow, a Sloan Fellow, a Kavli Fellow, a Bass Fellow, an ACM Fellow, an AAAI Fellow, and one of AI’s Ten to Watch. He has served as program and/or general chair of the AAAI, AAMAS, AIES, COMSOC, and EC conferences. Conitzer and Preston McAfee were the founding Editors-in-Chief of the ACM Transactions on Economics and Computation (TEAC).
To register for the event, visit the official event page.
The SRI Seminar Series brings together the Schwartz Reisman community and beyond for a robust exchange of ideas that advance scholarship at the intersection of technology and society. Seminars are led by a leading or emerging scholar and feature extensive discussion.
Each week, a featured speaker will present for 45 minutes, followed by an open discussion. Registered attendees will be emailed a Zoom link before the event begins. The event will be recorded and posted online.