Portrait of Eric Horvitz

Eric Horvitz

Technical Fellow and Director, Microsoft Research Labs and AI


Eric Horvitz is a technical fellow at Microsoft, where he serves as director of Microsoft Research Labs, including research centers in Redmond, Washington, Cambridge, Massachusetts, New York, New York, Montreal, Canada, Cambridge, UK, and Bangalore, India. He has pursued principles and applications of AI with contributions in machine learning, perception, natural language understanding, and decision making. His research centers on challenges with uses of AI amidst the complexities of the open world, including uses of probabilistic and decision-theoretic representations for reasoning and action, models of bounded rationality, and human-AI complementarity and coordination.

His efforts and collaborations have led to fielded systems in healthcare, transportation, ecommerce, operating systems, and aerospace. He received the Feigenbaum Prize and the Allen Newell Prize for contributions to AI. He received the CHI Academy honor for his work at the intersection of AI and human-computer interaction. He has been elected fellow of the National Academy of Engineering (NAE), the Association of Computing Machinery (ACM), Association for the Advancement of AI (AAAI), the American Association for the Advancement of Science (AAAS), the American Academy of Arts and Sciences, and the American Philosophical Society. He has served as president of the AAAI, and on advisory committees for the National Science Foundation, National Institutes of Health, President’s Council of Advisors on Science and Technology, DARPA, and the Allen Institute for AI.

Beyond technical work, he has pursued efforts and studies on the influences of AI on people and society, including issues around ethics, law, and safety. He chairs Microsoft’s Aether committee on AI, effects, and ethics in engineering and research. He established the One Hundred Year Study on AI at Stanford University and co-founded the Partnership on AI. Eric received PhD and MD degrees at Stanford University. More information can be found on his home page. A list of publications can be found here.





The Microsoft Research home page is a starting point for browsing through projects, events, and people at the lab at Redmond, and for our sister labs in the U.S. and throughout the world.

Students may find these career reflections by computer scientists interesting and inspirational–stemming from an event that we organized to mark the 20th anniversary of Microsoft Research.

Research overview

I’ve long been curious about the computational foundations of intelligence: How do our minds work? What computational principles and architectures underly thinking and intelligent behavior? I’ve pursued answers via studies of machine perception, learning, reasoning, and decision making. Many questions remain unanswered and much research is to be done. On the way to a deeper understanding, I work to field working systems that can immediately deliver value in the world. Projects include efforts in time-critical decisions, information retrieval, healthcare, urban infrastructure, sustainability, and development–with goals of understanding how computational models perform amidst real-world complexities, and of deploying systems that deliver value to people and society. A key focus of my work has been on opportunities to leverage the complementarities of human and machine intelligence. Related interests include machine learning and decision making for crowdsourcing and human computation, information triage and alerting that takes human attention into consideration, spanning work on notification systems, surprise modeling, multitasking, and psychological studies of interruption and recovery.

On the more theoretical front, I’ve been long interested in offline and real-time optimization of the expected value of computational systems under limited and varying resources. Areas of concentration in this realm include flexible or anytime computation, ideal metareasoning for guiding computation, compilation for reducing real-time deliberation, ongoing, continual computation, and the construction of bounded-optimal reasoning systems–systems that maximize the expected utility of the people they serve, given the expected costs of reasoning, the problems encountered over time, and assertions about a system’s constitution. Research in this arena includes tackling hard reasoning problems with learning and decision making methods.

Recent activities

Completed cycle of service as president and then past-president of the Association for the Advancement of Artificial Intelligence (AAAI), and remain active with AAAI strategic planning. Recently completed service as chair of the Section on Information, Computing, and Communication of the American Association for the Advancement of Science (AAAS), representing AAAS members with interests in data and computation. Serving this year on the PCAST NITR&D Working Group, NIH Advisory Committee to the Director (ACD) NLM Working Group, and National Academies Committee on Information Technology, Automation, and the Workforce. Served on the Computing Community Consortium, an organization that works to envision computing futures–and to stoke the fires of creativity within our community. As part of that effort, assisted with creating a whitepaper series for communicating the value of research on machine learning and decision support to government leaders and the public.

I’ve worked with colleagues to kick off a new AAAI conference in 2013 human computation and crowdsourcing, to serve an exciting and evolving community. Fellow of the AAAI, ACM, AAAS, the American Academy of Arts and Sciences, and National Academy of Engineering (NAE), and elected to the CHI Academy.

Recent news and events

Blast to the relevant past

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