Roundtable: Ethics in AI

Francesca Rossi, IBM Research; University of Padova, Maya Gupta, Google, Eric Horvitz, Microsoft Research, and Pedro Domingos, University of Washington

An update from industry leaders at the forefront of examining the societal impact of AI and the efforts to ensure the development of ethical machines.

Francesca Rossi, Distinguished Research Staff Member; Professor of Computer Science, IBM Research; University of Padova

Francesca Rossi is a research scientist at the IBM T.J. Watson Research Center and a professor of computer science at the University of Padova, Italy, currently on leave. Her research interests focus on artificial intelligence, specifically constraint reasoning, preferences, multi-agent systems, computational social choice, and collective decision making. She is also interested in ethical issues in the development and behavior of AI systems. She has published over 170 scientific articles in journals and conference proceedings, and as book chapters. She is editor in chief of the Journal of Artificial Intelligence Research, co-chairs the AAAI committee on AI and ethics, and is a member of the scientific advisory board of the Future of Life Institute. She is on the executive committee of the IEEE global initiative on ethical considerations in the development of autonomous and intelligent systems, and she belongs to the World Economic Forum Council on AI and robotics. She has given several media interviews about the future of AI and AI ethics to the Wall Street Journal, the Washington Post, Motherboard, Science, the Economist, CNBC, Eurovision, Corriere della Sera, and La Repubblica and has delivered three TEDx talks on these topics.

Maya Gupta, Machine Learning Researcher, Google

Gupta joined Google Research in 2012. Before Google, Gupta was an Associate Professor of Electrical Engineering at the University of Washington (2003-2012), tenured in 2009. Her research group focused on statistical learning algorithms for signal processing and color image processing. In 2007, Gupta received the PECASE award from Pres. George Bush for her work in classifying uncertain (e.g. random) signals, and received the 2007 Office of Naval Research YIP Award. Gupta graduated 9 Ph.D. students and 7 M.S students. Her Ph.D. in Electrical Engineering is from Stanford University (2003), where she was a National Science Foundation Graduate Fellow and worked with Bob Gray, Rob Tibshirani, and Richard Olshen. Before 2003, Gupta worked for Ricoh Research, NATO's Undersea Research Center, HP R&D, AT&T Labs, and Microsoft. Gupta also runs Artifact Puzzles, the second largest US maker of wooden jigsaw puzzles, a company she founded in 2009.

Eric Horvitz, Technical Fellow and Managing Director, Microsoft Research

Eric is a technical fellow and the managing director of the Microsoft Research lab at Redmond, balancing lab-wide responsibilities with ongoing research on machine intelligence and on opportunities to leverage the complementarities of human and machine intelligence. Eric’s ongoing research builds on representations of probability and utility, focusing on identifying ideal actions under conditions of uncertainty and bounded informational, computational, and cognitive resources. Beyond curiosity-driven research on foundations of machine perception, learning, and reasoning, he is excited about building real-world systems that provide value to people, organizations, and society, working in areas including human-computer interaction, information retrieval, health care, transportation, operating systems, and aerospace. Microsoft is a founding member of the Partnership on Artificial Intelligence to Benefit People and Society. Eric serves as its interim co-chair.

Pedro Domingos, Professor, University of Washington

Pedro Domingos is a professor of computer science at the University of Washington and the author of The Master Algorithm. He is a winner of the SIGKDD Innovation Award, the highest honor in data science, and a fellow of the Association for the Advancement of Artificial Intelligence. He has received a Fulbright Scholarship, a Sloan Fellowship, the National Science Foundation’s CAREER Award, and numerous best-paper awards. His research spans a wide variety of topics in machine learning, artificial intelligence, and data science, including scaling learning algorithms to big data, maximizing word of mouth in social networks, unifying logic and probability, and deep learning.


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