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AI100 Standing Committee 

Vincent Conitzer photo

Vincent Conitzer (Chair) is a Professor of Computer Science (with affiliate/courtesy appointments in Machine Learning, Philosophy, and the Tepper School of Business) at Carnegie Mellon University, 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 Professor of Computer Science, Professor of Economics, and Professor of Philosophy at Duke University. He received Ph.D. (2006) and M.S. (2003) degrees in Computer Science from Carnegie Mellon University, and an A.B. (2001) degree in Applied Mathematics from Harvard University.

Sheila McIlraith photo

Sheila McIlraith (Chair-Elect) is a Professor in the Department of Computer Science at the University of Toronto, a Canada CIFAR AI Chair (Vector Institute), and an Associate Director and Research Lead at the Schwartz Reisman Institute for Technology and Society. McIlraith's research is in the area of AI sequential decision making broadly construed, with a focus on human-compatible AI. McIlraith is a Fellow of the ACM and the Association for the Advancement of Artificial Intelligence (AAAI).  She was a member of the 2009 study group on long-term AI futures.

Peter Stone photo

Peter Stone (Past-Chair) is the David Bruton, Jr. Centennial Professor and Associate Chair of Computer Science, as well as Chair of the Robotics Consortium, at the University of Texas. In 2013 he was awarded the University of Texas System Regents' Outstanding Teaching Award and in 2014 he was inducted into the UT Austin Academy of Distinguished Teachers, earning him the title of University Distinguished Teaching Professor. Professor Stone's research interests in Artificial Intelligence include machine learning (especially reinforcement learning), multiagent systems, and robotics. He is an Alfred P. Sloan Research Fellow, Guggenheim Fellow, AAAI Fellow, IEEE Fellow, and AAAS Fellow. In 2007 he received the IJCAI Computers and Thought Award and in 2016 he was awarded the ACM/SIGAI Autonomous Agents Research Award. Professor Stone co-founded Cogitai, Inc., a startup company focussed on continual learning, in 2015, and currently serves as President and COO.

Karen Levy is Associate Professor of Information Science at Cornell University and Associate Member of the Faculty at Cornell Law School. Her research focuses on legal, social, and ethical dimensions of data-intensive technologies. Much of her research focuses on the impacts of technology on work and workers. She is the author of Data Driven: Truckers, Technology, and the New Workplace Surveillance (Princeton University Press, 2023). She is a New America Fellow.

Liz Sonenberg photo

Liz Sonenberg is Professor of Information Systems at the University of Melbourne, Australia. Her expertise is in the design of reasoning mechanisms for multi-agent and human-agent systems intended to exhibit collaborative behaviours, and particularly in computational approaches that can support human decision-making. Her current research focus is on explanation and on strategic deception in AI. She has served on a variety of advisory boards and formal company boards. Liz previously held positions as Dean of the Faculty of Science and Head of the Department of Information Systems, and is currently Pro Vice Chancellor Research Systems, and Pro Vice Chancellor Digital & Data, with responsibility for a range of University-wide policies.

Shannon Vallor photo

Shannon Vallor is the Baillie Gifford Professor in the Ethics of Data and Artificial Intelligence at the University of Edinburgh. She serves as Director of the Centre for Technomoral Futures in the Edinburgh Futures Institute and is a Fellow of the Alan Turing Institute. Professor Vallor's research explores how emerging technologies reshape human moral and intellectual character, and maps the ethical challenges and opportunities posed by new uses of data and artificial intelligence. Her work includes advising academia, government and industry on the ethical design and use of AI. Her current project examines responsibility gaps in the governance of autonomous systems, as part of the UKRI Trustworthy Autonomous Systems programme. She is the author of Technology and the Virtues: A Philosophical Guide to a Future Worth Wanting (Oxford University Press, 2016) and editor of the Oxford Handbook of Philosophy of Technology (2022).

Judy Wajcman photo

Judy Wajcman is the Anthony Giddens Professor of Sociology at the London School of Economics, and a Fellow at the Alan Turing Institute for Data Science and AI. She has been the recipient of career achievement awards from both the American Sociological Association and the Oxford Internet Institute for her contributions to the field of the social study of science and technology. Her recent research is about the impact of digital technologies on the experience of time in everyday life. She is currently leading a project at the Turing Institute on Women in data science and AI.

Russ Altman photo

Russ Altman (Faculty Director) is the Kenneth Fong Professor at Stanford, where he holds appointments in bioengineering, genetics, medicine and computer science. He is interested in the application of computing to basic problems in biology. His current research includes a project on representing the knowledge in scientific papers so that computers can easily access and use it. He is a fellow of the American College of Physicians, the American Institute for Medical and Biological Engineering and the International Society for Computational Biology. He is also a member of the Institute of Medicine of the National Academies.

Past AI100 Officers

Study Panels

Study Panels are planned to convene every 5 years to examine some aspect of AI and its influences on society and the world. The first study panel was convened in late 2015 to study the likely impacts of AI on urban life by the year 2030, with a focus on typical North American cities.

2020 Study Panel Members

  • Michael Littman, Chair, Brown University
  • Ifeoma Ajunwa, Cornell University
  • Guy Berger, LinkedIn
  • Craig Boutilier, Google
  • Morgan Currie, The University of Edinburgh
  • Finale Doshi-Velez, Harvard University
  • Gillian Hadfield, University of Toronto
  • Michael Horowitz, University of Pennsylvania
  • Charles Isbell, Georgia Institute of Technology
  • Hiroaki Kitano, Sony AI, and Okinawa Institute of Science and Technology Graduate University
  • Karen Levy, Cornell University
  • Terah Lyons
  • Melanie Mitchell, Portland State University
  • Julie Shah, Massachusetts Institute of Technology
  • Steven Sloman, Brown University
  • Shannon Vallor, The University of Edinburgh
  • Toby Walsh, University of New South Wales

2015 Study Panel Members

  • Peter Stone, Chair, University of Texas at Austin
  • Rodney Brooks, Rethink Robotics
  • Erik Brynjolfsson, Massachusetts Institute of Technology
  • Ryan Calo, University of Washington
  • Oren Etzioni, Allen Institute for AI
  • Greg Hager, Johns Hopkins University
  • Julia Hirschberg, Columbia University
  • Shivaram Kalyanakrishnan, Indian Institute of Technology Bombay
  • Ece Kamar, Microsoft Research
  • Sarit Kraus, Bar Ilan University
  • Kevin Leyton-Brown, University of British Columbia
  • David Parkes, Harvard University
  • William Press, University of Texas at Austin
  • AnnaLee (Anno) Saxenian, University of California, Berkeley
  • Julie Shah, Massachussets Institute of Technology
  • Milind Tambe, University of Southern California
  • Astro Teller, X