Eric Joel Horvitz (//) is an American computer scientist, and Technical Fellow at Microsoft, where he serves as director of Microsoft Research Labs, including research centers in Redmond, WA, Cambridge, Massachusetts, New York, NY, Montreal, Canada, Cambridge, UK, and Bangalore, India.
Horvitz received from Stanford University his Ph.D, 1991, and an M.D. in 1994. His doctoral dissertation, Computation and Action Under Bounded Resources, and follow-on research introduced models of bounded rationality founded in probability and decision theory. He did his doctoral work under advisors Ronald A. Howard, George B. Dantzig, Edward H. Shortliffe, and Patrick Suppes.
He is currently Technical Fellow at Microsoft, where he serves as director of Microsoft Research Labs. He has been elected Fellow of the Association for the Advancement of Artificial Intelligence (AAAI), the National Academy of Engineering (NAE), the American Academy of Arts and Sciences, and of the American Association for the Advancement of Science (AAAS). He was elected to the ACM CHI Academy in 2013 and ACM Fellow 2014 "For contributions to artificial intelligence, and human-computer interaction."
In 2015, he was awarded the AAAI Feigenbaum Prize, a biennial award for sustained and high-impact contributions to the field of artificial intelligence through the development of computational models of perception, reflection and action, and their application in time-critical decision making, and intelligent information, traffic, and healthcare systems.
In 2015, he was also awarded the ACM - AAAI Allen Newell Award, for "contributions to artificial intelligence and human-computer interaction spanning the computing and decision sciences through developing principles and models of sensing, reflection, and rational action."
He serves on the Scientific Advisory Committee of the Allen Institute for Artificial Intelligence (AI2), the Computer Science and Telecommunications Board (CSTB) of the US National Academies, and on the Board of Regents of the US National Library of Medicine (NLM). He was nominated in 2019 to serve on the U.S. National Security Commission on AI.
He has served as president of the Association for the Advancement of AI (AAAI), on the NSF Computer & Information Science & Engineering (CISE) Advisory Board, on the council of the Computing Community Consortium (CCC), and chair of the Section on Information, Computing, and Communications of the American Association for the Advancement of Science (AAAS).
Horvitz's research interests span theoretical and practical challenges with developing systems that perceive, learn, and reason. His contributions include advances in principles and applications of machine learning and inference, information retrieval, human-computer interaction, bioinformatics, and e-commerce.
Horvitz played a significant role in the use of probability and decision theory in artificial intelligence. His work raised the credibility of artificial intelligence in other areas of computer science and computer engineering, influencing fields ranging from human-computer interaction to operating systems. His research helped establish the link between artificial intelligence and decision science. As an example, he coined the concept of bounded optimality, a decision-theoretic approach to bounded rationality. The influences of bounded optimality extend beyond computer science into cognitive science and psychology.
He studied the use of probability and utility to guide automated reasoning for decision making. The methods include consideration of the solving of streams of problems in environments over time. In related work, he applied probability and machine learning to identify hard problems and to guide theorem proving. He introduced the anytime algorithm paradigm in AI, where partial results, probabilities, or utilities of outcomes are refined with computation under different availabilities or costs of time, guided by the expected value of computation.
He has issued long-term challenge problems for AI—and has espoused a vision of open-world AI, where machine intelligences have the ability to understand and perform well in the larger world where they encounter situations they have not seen before.
He has explored synergies between human and machine intelligence. In this area, he studied the value of displayed information, methods for guiding machine versus human initiative, learning models of human attention, and using machine learning and planning to identify and merge the complementary abilities of people and AI systems.
Horvitz speaks on the topic of artificial intelligence, including on NPR and the Charlie Rose show. Online talks include both technical lectures and presentations for general audiences (TEDx Austin: Making Friends with Artificial Intelligence). In 2018, he gave a conference at Sorbonne University on the advantages of Artificial Intelligence. His research has been featured in the New York Times and the Technology Review. He has testified before the US Senate on progress, opportunities, and challenges with AI.
AI and Society
He has addressed technical and societal challenges with the fielding of AI technologies in the open world, where AI systems and capabilities can have inadvertent effects, pose dangers, or be misused.
Asilomar AI Study
He served as President of the AAAI from 2007-2009. As AAAI President, he called together and co-chaired the Asilomar AI study which culminated in a meeting of AI scientists at Asilomar in February 2009. The study considered the nature and timing of AI successes and reviewed concerns about directions with AI developments, including the potential loss of control over computer-based intelligences, and also efforts that could reduce concerns and enhance long-term societal outcomes. The study was the first meeting of AI scientists to address concerns about superintelligence and loss of control of AI and attracted interest by the public.
In coverage of the Asilomar study, he said that scientists must study and respond to notions of superintelligent machines and concerns about artificial intelligence systems escaping from human control. In a later NPR interview, he said that investments in scientific studies of superintelligences would be valuable to guide proactive efforts even if people believed that the probability of losing of control of AI was low because of the cost of such outcomes.
One Hundred Year Study on Artificial Intelligence
In 2014, Horvitz defined and funded with his wife the One Hundred Year Study of Artificial Intelligence at Stanford University. According to Horvitz, the gift, which may increase in the future, is sufficient to fund the study for a century. A Stanford press release stated that sets of committees over a century will "study and anticipate how the effects of artificial intelligence will ripple through every aspect of how people work, live and play." A framing memo for the study calls out 18 topics for consideration, including law, ethics, the economy, war, and crime. Topics include abuses of AI that could pose threats to democracy and freedom and addressing possibilities of superintelligences and loss of control of AI.
The One Hundred Year Study is overseen by a Standing Committee. The Standing Committee formulates questions and themes and organizes a Study Panel every five years. The Study Panel issues a report that assesses the status and rate of progress of AI technologies, challenges, and opportunities with regard to AI's influences on people and society.
The 2015 study panel of the One Hundred Year Study, chaired by Peter Stone, released a report in September 2016, titled "Artificial Intelligence and Life in 2030." The panel advocated for increased public and private spending on the industry, recommended increased AI expertise at all levels of government, and recommended against blanket government regulation. Panel chair Peter Stone argues that AI won’t automatically replace human workers, but rather, will supplement the workforce and create new jobs in tech maintenance. While mainly focusing on the next 15 years, the report touched on concerns and expectations that had risen in prominence over the last decade about the risks of superintelligent robots, stating "Unlike in the movies, there's no race of superhuman robots on the horizon or probably even possible. Stone stated that "it was a conscious decision not to give credence to this in the report."
Founding of Partnership on AI
He served as founding co-chair of an effort to establish the Partnership on AI, an organization that brought Amazon, Facebook, DeepMind, Google, IBM, and Microsoft together to found and fund a non-profit, multi-stakeholder organization. A press release in September 2016 states that the non-profit organization will be guided by balanced leadership that includes “academics, non-profits, and specialists in policy and ethics.” The goals are stated as including research activities, recommending best practices, and publishing in “areas such as ethics, fairness, and inclusivity; transparency, privacy, and interoperability; collaboration between people and AI systems; and the trustworthiness, reliability, and robustness” of AI technologies.
Microsoft Aether Committee
He chairs the Aether Committee at Microsoft, Microsoft’s internal committee on the responsible development and fielding of AI technologies. He reported that the Aether Committee had made recommendations on and guided decisions that have influenced Microsoft’s commercial AI efforts.
- Horvitz, E. (December 1990), Computation and Action Under Bounded Resources (PDF) (Dissertation), Stanford, CA: Stanford University
- Kamar, E.; Hacker, S.; Horvitz, E. (June 2012), "Combining Human and Machine Intelligence in Large-scale Crowdsourcing" (PDF), AAMAS '12 Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 1, Richland, SC: International Foundation for Autonomous Agents and Multiagent Systems, 1: 467–474, ISBN 978-0-9817381-1-6
- Horvitz, E. (July 2008), "Artificial Intelligence in the Open World", Opening Session of the Annual Meeting, Association for the Advancement of Artificial Intelligence (Lecture), Chicago, IL
- Horvitz, E; Kadie, C; Paek, T; Hovel, D (March 2003), "Models of Attention in Computing and Communication: from Principles to Applications" (PDF), Communications of the ACM, ACM, 46 (3), pp. 52–59, doi:10.1145/636772.636798
- Horvitz, E. (February 2001), "Principles and Applications of Continual Computation" (PDF), Artificial Intelligence, 126 (1–2): 159–196, doi:10.1016/S0004-3702(00)00082-5
- Horvitz, E (May 1999), "Proceedings of the SIGCHI conference on Human factors in computing systems the CHI is the limit - CHI '99", CHI '99 Proceedings of the SIGCHI conference on Human Factors in Computing Systems, New York, NY: ACM, pp. 159–166, doi:10.1145/302979.303030, ISBN 0-201-48559-1
- Horvitz, E; Barry, M (August 1995), "Display of information for time-critical decision making" (PDF), UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence, San Francisco, CA: Morgan Kaufmann Publishers Inc, pp. 296–305, ISBN 1-55860-385-9
- D, Heckerman; Horvitz, E; Nathwani, Bharat (June 1992), Toward Normative Expert Systems: Part I, the Pathfinder Project (PDF), 31, pp. 90–105
- Henrion, M.; Breese, J.; Horvitz, E. (1991), "Decision analysis and expert systems" (PDF), AI Magazine, Menlo Park, CA: American Association for Artificial Intelligence, 12 (4): 64–91
- Shwe, M.; Middleton, B.; Heckerman, D.; Hernion, M.; Horvitz, E.; Lehmann, H.; Cooper, G. (October 1991), "Probabilistic diagnosis using a reformulation of the INTERNIST-1/QMR knowledge base" (PDF), Methods of Information in Medicine, 30 (4): 241–255, doi:10.1055/s-0038-1634846
- Horvitz, E.; Cooper, G.F.; Heckerman, D. (August 1989), "Reflection and action under scarce resources: Theoretical principles and empirical study" (PDF), IJCAI'89 Proceedings of the 11th International Joint Conference on Artificial Intelligence - Volume 2, San Francisco, CA: Morgan Kaufmann Publishers Inc.: 1121–1127
- Horvitz, E. (August 1988), "Reasoning under varying and uncertain resource constraints" (PDF), AAAI'88 Proceedings of the Seventh AAAI National Conference on Artificial Intelligence, AAAI Press: 111–116
- Horvitz, E.; Breese, J.; Henrion, M. (July 1988), "Decision theory in expert systems and artificial intelligence" (PDF), International Journal of Approximate Reasoning, New York, NY: Elsevier Science Inc., 2 (3): 247–302, doi:10.1016/0888-613X(88)90120-X
- Horvitz, E. (July 1987), Reasoning about beliefs and actions under computational resource constraints (PDF), Arlington, VA: AUAI Press, pp. 429–447, arXiv:1304.2759, Bibcode:2013arXiv1304.2759H, ISBN 0-444-87417-8
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- Horvitz, Eric (February 2001), "Principles and Applications of Continual Computation", Artificial Intelligence, 126 (1–2): 159–196, doi:10.1016/S0004-3702(00)00082-5
- Horvitz, Eric J.; Ruan, Y.; Gomes, C.; Kautz, H.; Selman, B.; Chickering, D.M. (July 2001), "A Bayesian Approach to Tackling Hard Computational Problems" (PDF), Proceedings of the Conference on Uncertainty and Artificial Intelligence: 235–244
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- Horvitz, Eric (August 1988). "Reasoning under varying and uncertain resource constraints" (PDF). AAAI'88 Proceedings of the Seventh AAAI National Conference on Artificial Intelligence. AAAI Press: 111–116.
- Horvitz, Eric J.; Cooper, Gregory F.; Heckerman, David E. (August 1989). "Reflection and action under scarce resources: theoretical principles and empirical study" (PDF). IJCAI'89 Proceedings of the 11th International Joint Conference on Artificial Intelligence - Volume 2. San Francisco, CA: Morgan Kaufmann Publishers Inc.: 1121–1127.
- Horvitz, Eric (December 1990). "Computation and Action Under Bounded Resources" (PDF) (Dissertation). Stanford, CA: Stanford University. Cite journal requires
- Selman, B.; Brooks, R.; Dean, T.; Horvitz, E.; Mitchell, T.; Nilsson, N. (August 1996), "Challenge Problems for Artificial Intelligence", Proceedings of AAAI-96, Thirteenth National Conference on Artificial Intelligence, Portland, Oregon: 1340–1345
- Horvitz, Eric (July 2008), "Artificial Intelligence in the Open World", AAAI Presidential Lecture
- Horvitz, Eric; Barry, Matthew (August 1995). "Display of information for time-critical decision making" (PDF). Proceeding, UAI'95 Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence. San Francisco, CA: Morgan Kaufmann Publishers Inc: 296–305. ISBN 1-55860-385-9.
- Horvitz, Eric (May 1999). "Principles of mixed-initiative user interfaces" (PDF). Proceeding, CHI '99 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. New York, NY: ACM: 159–166. doi:10.1145/302979.303030. ISBN 0-201-48559-1.
- Horvitz, Eric; Kadie, Carl; Peak, Tim; Hovel, David (March 2003). "Models of attention in computing and communication: from principles to applications" (PDF). Communications of the ACM. New York, NY: ACM. 46: 52–59. doi:10.1145/636772.636798.
- Markhoff, John (17 July 2000). "Microsoft Sees Software ´Agent´ as Way to Avoid Distractions". New York Times. Retrieved 3 June 2019.
- Kamar, Ece; Hacker, Severin; Horvitz, Eric (8 June 2018). "Combining human and machine intelligence in large-scale crowdsourcing" (PDF). Proceeding, AAMAS '12 Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 1. Richland, SC: International Foundation for Autonomous Agents and Multiagent Systems. 1: 467–474. ISBN 978-0-9817381-1-6.
- Krause, A.; Horvitz, E.; Kansal, A.; Zhao, F. (April 2008), "Toward Community Sensing", Proceedings of IPSN 2008
- Singla, A.; Horvitz, E.; Kamar, E.; White, R.W. (July 2014), "Stochastic Privacy" (PDF), AAAI, arXiv:1404.5454, Bibcode:2014arXiv1404.5454S
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- Waldrop, M. Mitchell (March–April 2008). "TR10: Modeling Surprise". Technology Review. Retrieved 12 March 2011.
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- Dietterich, Thomas G; Horvitz, Eric J. (October 2015). "Rise of Concerns about AI: Reflections and Directions" (PDF). Communications of the ACM. 58 (10): 38–40. doi:10.1145/2770869.
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- "One-Hundred Year Study of Artificial Intelligence: Reflections and Framing". Eric Horvitz. 2014. Retrieved 1 October 2016.
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- Profile page at Microsoft Research
- One Hundred Year Study on Artificial Intelligence (AI100)
- Audio: Challenge Problems for AI
- TEDx Austin: Making Friends with Artificial Intelligence
- NPR: Science Friday: Improving Healthcare One Search at a Time
- BBC: "Artificial intelligence: How to turn Siri into Samantha"
- Keynote address, Conference on Knowledge Discovery and Data Mining (SIGKDD), August 2014: Videolectures.net
- Eric Horovitz on IMDB