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The Future of Artificial Intelligence, June 23, 2016 Stanford The Future of Artificial Intelligence Emerging Topics and Societal Benefit A Partner Event of the 2016 Global Entrepreneurship Summit Hosted by The White House Office of Science and Technology Policy and Stanford University June 23, 2016 5:30–9:30 p.m. Paul Brest Hall 555 Salvatierra Walk Stanford University ABOUT THIS EVENT Welcome to The Future of Artificial Intelligence Partner Event of the 2016 Global Entrepreneurship Summit at Stanford University. Today leading artificial intelligence (AI) researchers will discuss the most impactful research topics in AI and highlight the challenges and potentials of artificial intelligence. There is a lot of excitement about AI and how to create computers capable of intelligent behavior. After years of steady but slow progress on making computers “smarter” at everyday tasks, a series of breakthroughs in the research community and industry have recently spurred momentum and investment in the development of this field. There is a sense that AI has made sufficient inroads into everyday life that we should pause and take stock of the great opportunities and challenges before us. We are aware of self- driving cars, intelligent assistants on phones and mobile devices, and the use of data for many activities in academia, government and industry. Now is a good time to think about the anticipated evolution of these capabilities and how they might impact economic, social, political and cultural activities. We look forward to engaging with you about how best to harness the innovations and the array of considerations brought by artificial intelligence. Best Regards, Russ Altman, Co-Chair Fei-Fei Li, Co-Chair Professor, Bioengineering, Genetics, Medicine, and Associate Professor, Computer Science and Computer Science (by courtesy); Chair, Biomedical Psychology (by courtesy); Director, Stanford Artificial Informatics Training Program; Faculty Director, One Intelligence Lab; Director, Stanford-Toyota Center for Hundred Year Study on Artificial Intelligence (AI100) AI Research 2016 Conference Agenda Thursday, June 23, 2016 5:30 p.m. Reception in the Rehnquist Courtyard outside of Paul Brest Hall 6:30 p.m. Opening Remarks and Keynote Presentations Introduction: Russ Altman (Stanford) Government: Megan Smith (Office of Science and Technology Policy) Academic: Fei-Fei Li (Stanford) 7:05 p.m. Invited Talks Daniela Rus (MIT) Anshul Kundaje (Stanford) Chris Manning (Stanford) 7:30 p.m. Panel: 100 Year Study of Artificial Intelligence Moderator: Russ Altman Barbara Grosz (Harvard), panelist Yoav Shoham (Stanford), panelist Milind Tambe (USC), panelist 8:15 p.m. Invited Talks Finale Doshi-Velz (Harvard) Stefano Ermon (Stanford) John Duchi (Stanford) Dieter Fox (University of Washington) Chris Ré (Stanford) 8:55 p.m. Keynote Presentation Industry: Arvind Krishna (IBM) 9:10 p.m. Closing Remarks 9:15 p.m. Meeting ends Speakers Russ Biagio Altman Kenneth Fong Professor of Bioengineering, Genetics, Medicine and, by courtesy, of Computer Science, Stanford University Russ Biagio Altman is a professor of bioengineering, genetics, & medicine (and of computer science, by courtesy) and past chairman of the Bioengineering Department at Stanford University. His primary research interests are in the application of computing and informatics technologies to problems relevant to medicine. Dr. Altman holds an A.B. from Harvard College, and M.D. from Stanford Medical School, and a Ph.D. in Medical Information Sciences from Stanford. He received the U.S. Presidential Early Career Award for Scientists and Engineers and a National Science Foundation CAREER Award. He has chaired the Science Board advising the FDA Commissioner, and currently serves on the NIH Director’s Advisory Committee. He is an organizer of the annual Pacific Symposium on Biocomputing (http://psb.stanford.edu/), and a founder of Personalis, Inc. Dr. Altman is board certified in Internal Medicine and in Clinical Informatics. Altman is the faculty director of the 100 year study of Artificial Intelligence (ai100.stanford.edu). https://profiles.stanford.edu/russ-altman Finale Doshi-Velez Assistant Professor, Harvard University Finale Doshi-Velez leads the Data to Actionable Knowledge group at the Harvard Paulson School of Engineering and Applied Science. She completed her Ph.D. from MIT and her postdoc at Harvard Medical School. She was a Marshall Scholar at the University of Cambridge and was named one of IEEE’s “AI Top 10 to Watch” in 2013. Doshi-Velez is excited about methods to turn data into actionable knowledge. Her core research in machine learning, computational statistics, and data science is inspired by—and often applied to—the objective of accelerating scientific progress and practical impact in healthcare and other domains. https://www.seas.harvard.edu/directory/finale John C. Duchi Assistant Professor of Statistics and Electrical Engineering, Stanford University John C. Duchi completed his Ph.D. in computer science at Berkeley in 2014. His research interests are a bit eclectic, and they span statistics, computation, optimization, and machine learning. At Berkeley, he worked in the Statistical Artificial Intelligence Lab (SAIL) under the joint supervision of Michael Jordan and Martin Wainwright. He obtained his master’s degree (MA) in statistics in Fall 2012. He was also an undergrad and a master’s student at Stanford University, where he worked with Daphne Koller in her research group, DAGS. He also spends some time at Google Research, where he had (and continue to have) the great fortune to work with Yoram Singer. https://profiles.stanford.edu/john-duchi Stefano Ermon Assistant Professor of Computer Science, Stanford University Stefano Ermon is Assistant Professor in the Department of Computer Science at Stanford University, where he is affiliated with the Artificial Intelligence Laboratory and a fellow of the Woods Institute for the Environment. Ermon received his Bachelors and Master’s degrees in Electrical and Electronic Engineering from the Università degli Studi di Padova and he completed his Ph.D. in computer science at Cornell in 2014. His research is centered on techniques for scalable and accurate inference in graphical models, statistical modeling of data, large-scale combinatorial optimization, and robust decision making under uncertainty, and is motivated by a range of applications, in particular ones in the emerging field of computational sustainability. Stefano has won several awards, including two Best Student Paper Awards, one Runner-Up Prize, and a McMullen Fellowship. https://cs.stanford.edu/~ermon/ Dieter Fox Professor of Computer Science, University of Washington Dieter Fox is a Professor in the Department of Computer Science & Engineering at the University of Washington, Seattle, where he heads the UW Robotics and State Estimation Lab. From 2009 to 2011, he was also Director of the Intel Research Labs Seattle. Fox obtained his Ph.D. from the University of Bonn, Germany. Before joining the faculty of UW, he spent two years as a postdoctoral researcher at the CMU Robot Learning Lab. Fox’s research is in robotics and artificial intelligence, with a focus on state estimation and perception applied to various problems in robotics and activity recognition. Dieter is an IEEE Fellow, a Fellow of the AAAI, and he received several best paper awards at major robotics, AI, and computer vision conferences. He was an editor of the IEEE Transactions on Robotics, program co-chair of the 2008 AAAI Conference on Artificial Intelligence, and program chair of the 2013 Robotics: Science and Systems conference. https://homes.cs.washington.edu/~fox/ Speakers, continued Barbara J. Grosz Higgins Professor of Natural Sciences, Harvard University Barbara J. Grosz’s contributions to AI include establishing the research field of computational modeling of discourse, developing some of the earliest computer dialogue systems, pioneering models of collaboration, and the development of collaborative multi-agent systems and collaborative systems for human-computer communication. Grosz is a member of the National Academy of Engineering, the American Philosophical Society, and the American Academy of Arts and Sciences and a corresponding fellow of the Royal Society of Edinburgh, and she is a fellow of the Association for the Advancement of Artificial Intelligence (AAAI), the Association for Computing Machinery (ACM) and the American Association for the Advancement of Science. She is recipient of the University of California, Berkeley Distinguished Alumna Award in Computer Sciences and Engineering (1997), the ACM/AAAI Allen Newell Award (2009), and the 2015 IJCAI Research Excellence Award. http://grosz.seas.harvard.edu/ Arvind Krishna Senior Vice President and Director, IBM Research Arvind Krishna helps guide IBM’s overall technical strategy in core and emerging technologies, including cognitive computing, quantum computing, cloud platform services, data-driven solutions and blockchain. Krishna was general manager of IBM Systems and Technology Group’s development and manufacturing organization, responsible for the advanced engineering and development of a full technology portfolio, ranging from advanced semiconductor materials to leading-edge microprocessors, servers and storage systems. Krishna has an undergraduate degree from the Indian Institute of Technology, Kanpur, and a Ph.D. from the University of Illinois at Urbana-Champaign. He is the recipient of a distinguished alumni award from the University of Illinois, is the co-author of 15 patents, has
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