AI Seminar & Natural Language Processing Seminar|
Can Robots Behave Well as Members of Society? & Natural Language Processing for Collective Discourse
Benjamin Kuipers & Dragomir Radev
Professors of Computer Science
University of Michigan
Tuesday, November 17, 2015|
4:00pm - 5:15pm
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About the Event
Kuipers: Robots and other AIs are becoming increasingly numerous, and they are increasingly acting as members of our society. They drive cars autonomously on our roads, help care for children and the elderly, and run complex distributed systems in the infrastructures of our world. These tasks sometimes present difficult and time-critical choices. How should robots and AIs make morally and ethically significant choices? By considering how robots should act in society, we ask what are the pragmatic benefits to individuals, and to society as a whole, of acting morally and ethically. How should effective moral and ethical reasoning be done, to obtain these benefits? Recent results in the cognitive sciences shed light on how humans make moral and ethical decisions. Humans expect themselves and others to act in ways that benefit the entire society, not just themselves. Following ethical and moral constraints often leads both the individual and the society as a whole to reap greater benefits than would be available to self-interested reward-maximizers. As robots and AIs take a larger role in our society, should they be considered as members of society, along with humans, rather than simply as tools for use by humans? How should they behave, to act well as members of society?
Kuipers: Benjamin Kuipers is a Professor of Computer Science and Engineering at the University of Michigan. He previously held an endowed Professorship in Computer Sciences at the University of Texas at Austin. He received his B.A. from Swarthmore College, and his Ph.D. from MIT. He investigates the representation of commonsense and expert knowledge, with particular emphasis on the effective use of incomplete knowledge. His research accomplishments include developing the TOUR model of spatial knowledge in the cognitive map, the QSIM algorithm for qualitative simulation, the Algernon system for knowledge representation, and the Spatial Semantic Hierarchy models of knowledge for robot exploration and mapping. He has served as Department Chair at UT Austin, and is a Fellow of AAAI, IEEE, and AAAS.
Open to: Public