Eric Horvitz will share reflections on promising directions with fielding AI solutions in the open world, where systems need to grapple with uncertainty and incompleteness and to work effectively with people. He will touch on several areas of research, including enhancing robustness via leveraging algorithmic portfolios, learning from experiences in simulation environments, harnessing transfer learning, and learning from small numbers of training examples. Beyond automation, Eric will discuss methods that center on collaborations between AI systems and people in the open world, highlighting directions and opportunities.
Eric Horvitz is a technical fellow and director of Microsoft Research Labs. He is interested in computational models of perception, inference, and decision making. Eric has been elected fellow of the National Academy of Engineering (NAE), the Association for the Advancement of AI (AAAI), and the Association for Computing Machinery (ACM). He received the Feigenbaum Prize and the ACM-AAAI Allen Newell Award for contributions in artificial intelligence. He was inducted into the CHI Academy for advances in human-AI collaboration. Eric has served as president of AAAI, chair of the AAAS Section on Computing, and on advisory committees for NIH, NSF, and DARPA. He received Ph.D. and M.D. degrees from Stanford University. More information and a publication list can be found at http://erichorvitz.com.
