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| Eric Horvitz | |
|---|---|
| Name | Eric Horvitz |
| Birth date | 1958 |
| Birth place | San Francisco, California |
| Nationality | American |
| Alma mater | Stanford University; Brown University |
| Occupation | Computer scientist; researcher; executive |
| Known for | Research in artificial intelligence; decision theory; human-centered AI |
Eric Horvitz
Eric Horvitz is an American computer scientist and researcher noted for work in artificial intelligence, decision theory, and human-centered computing. He has held leadership roles in major technology organizations and advisory positions for governments and international institutions. His career spans academic appointments, industrial research leadership, and contributions to public policy on technology, ethics, and safety.
Born in San Francisco, California, Horvitz studied at Stanford University where he earned degrees including a Bachelor of Science. He completed doctoral studies at Brown University under the supervision of figures associated with probabilistic reasoning and decision analysis, intersecting with work from researchers at Carnegie Mellon University, Massachusetts Institute of Technology, and University of California, Berkeley. His formative training connected to traditions exemplified by researchers at RAND Corporation and laboratories at Bell Labs.
Horvitz began his professional career with appointments at academic and research institutions including affiliations with Stanford University and collaborations with teams at Microsoft Research, where he rose to leadership roles. At Microsoft he led efforts alongside organizations such as OpenAI, Google DeepMind, and industrial labs like IBM Research and Facebook AI Research. He has engaged with government entities including the White House and the National Science Foundation, and consulted for international bodies such as the United Nations and the European Commission. His career has intersected with initiatives tied to companies like Amazon (company), Apple Inc., and Intel in advancing AI research and deployment.
Horvitz's research spans probabilistic reasoning, decision theory, machine learning, and human-computer interaction, connecting to trajectories visible in work from Judea Pearl, Geoffrey Hinton, Yoshua Bengio, and Yann LeCun. He contributed to advances in Bayesian networks, linking to foundations from Alan Turing-era probabilistic ideas and developments at University of Edinburgh and University College London. His work on utility-directed sensing and anytime algorithms relates to concepts used at SRI International and in projects influenced by Herbert A. Simon and Allen Newell. He has published on AI safety, aligning with research themes explored at Center for Human-Compatible AI and policy dialogues involving Future of Life Institute and Bletchley Park-connected histories. Horvitz has explored human-AI collaboration in healthcare settings, engaging topics relevant to institutions like Mayo Clinic, Johns Hopkins University, and Cleveland Clinic. His contributions influenced applied systems deployed in contexts similar to work at Siemens and Philips in decision-support technologies.
Horvitz served in senior leadership roles at Microsoft Corporation, participating in cross-industry collaborations with National Institutes of Health, Defense Advanced Research Projects Agency, and the National Institute of Standards and Technology. He has been a member of advisory panels to the White House Office of Science and Technology Policy and engaged with legislative bodies such as the United States Congress on AI policy. Internationally, he has given expert testimony and briefings for entities including the European Parliament and the Organisation for Economic Co-operation and Development. Horvitz has participated in multidisciplinary efforts with scholars from Harvard University, Princeton University, and Yale University to shape norms for responsible AI and safety, and has collaborated with ethicists linked to Georgetown University and Oxford University.
Horvitz has been recognized with honors from professional societies such as the Association for Computing Machinery and the Institute of Electrical and Electronics Engineers. His awards parallel distinctions conferred at gatherings like the NeurIPS conference, the AAAI symposiums, and accolades that echo prizes from foundations such as the MacArthur Foundation and the Royal Society fellowship traditions. He has been invited to deliver named lectures at institutions including Columbia University, University of Oxford, and California Institute of Technology, and has received distinctions from national academies comparable to National Academy of Sciences and National Academy of Engineering membership honors.
Horvitz's publications include influential papers in venues such as Journal of Artificial Intelligence Research, Communications of the ACM, and proceedings of NeurIPS, ICML, and AAAI. He has authored work on Bayesian networks, decision-making under uncertainty, and mixed-initiative interaction, which appear alongside contributions from scholars at MIT Press and Springer. His portfolio includes patents in areas of decision support, context-aware computing, and predictive interfaces, resonating with patented innovations from Bell Labs and Xerox PARC.
Category:American computer scientists Category:Artificial intelligence researchers