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JudyGoldsmith.pdfAI Ethics Education and the Moral Imagination
Tuesday, May 21, 2019, 9:00 - 10:00, Royal Palm BallroomJudy Goldsmith
University of KentuckyAbstract: Imagine a world of private jet packs; mind-to-mind communication; personalized weather; personalized VR landscapes; reconfigurable bodies and endocrine systems. Science fiction writers imagine these for us, and show us some of the challenges that such technology may create, but we cannot just depend on the imagination of science fiction writers to bring all the consequences of our work to our attention. AI ethics education must go beyond the snatched-from-the-headlines case studies; students must develop the capacity to imagine the challenges and dysfunctions around AI technology before the technologies begin to exert influence in the wider world. This morally-charged imaginative capacity will help us prevent or forestall the dysfunctions, and think sensitively and concretely about how to confront and navigate the inevitable challenges. This capacity for moral imagination can also help us think about the ways in which our sense of what is normal, valuable or possible will be transformed once AI becomes more deeply integrated into the fabric of daily life. In this talk, we argue that (a) it is crucial for the creators and theorizers of new technology to creatively and imaginatively consider the impacts of their work on society and the world; (b) it is thus necessary for educators to prepare our students to imagine the ramifications of their work, and (c) we must help them develop their moral imagination, namely the capacity to cultivate ethical perception and judgment through images, stories, and metaphors.
Bio: Dr. Judy Goldsmith received degrees in Mathematics from Princeton University and the University of Wisconsin-Madison. She held post-docs at Dartmouth College and Boston University, an assistant professorship at the University of Manitoba, and has been in the Computer Science Department of the University of Kentucky since 1993. She is a full professor. Goldsmith has been active in the AI community since 1996, and has published heavily cited and award winning papers. Her research areas include decision making under uncertainty; computational social choice; preference elicitation, representation, and aggregation; computational learning theory, computational complexity, computer ethics and ethics pedagogy. She was recognised in 2014 as a Senior Member of AAAI, the Association for the Advancement of Artificial Intelligence.In 2015, Goldsmith received an Undergraduate Research Mentor award from the Computing Research Association. She has received teaching awards at the department, college, and university level at the University of Kentucky. In 1998, Goldsmith was recognized by the AAAS for her mentoring of members of underrepresented groups in the STEM disciplines.
Bio: Dr. Judy Goldsmith received degrees in Mathematics from Princeton University and the University of Wisconsin-Madison. She held post-docs at Dartmouth College and Boston University, an assistant professorship at the University of Manitoba, and has been in the Computer Science Department of the University of Kentucky since 1993. She is a full professor. Goldsmith has been active in the AI community since 1996, and has published heavily cited and award winning papers. Her research areas include decision making under uncertainty; computational social choice; preference elicitation, representation, and aggregation; computational learning theory, computational complexity, computer ethics and ethics pedagogy. She was recognised in 2014 as a Senior Member of AAAI, the Association for the Advancement of Artificial Intelligence.In 2015, Goldsmith received an Undergraduate Research Mentor award from the Computing Research Association. She has received teaching awards at the department, college, and university level at the University of Kentucky. In 1998, Goldsmith was recognized by the AAAS for her mentoring of members of underrepresented groups in the STEM disciplines.
TuomasSandholm.pdfNew Results for Solving Imperfect-Information Games
Wednesday, May 22, 2019, 9:00 - 10:00, Royal Palm BallroomTuomas Sandholm
Carnegie Mellon UniversityAbstract: Most real-world settings are imperfect-information games. They present challenges beyond those in perfect-information games. In 2017, our AI Libratus beat top humans in the main benchmark, heads-up no-limit Texas hold’em. In this talk I will discuss some of our more recent work on imperfect-information games. Topics include a unified framework for abstracting games with bounds on solution quality [Kroer & Sandholm, NeurIPS-18], a sound depth-limited search framework [Brown et al., NeurIPS-18], the fastest equilibrium-finding algorithms [Brown & Sandholm, AAAI-19], deep learning as an alternative to abstraction [Brown et al., Deep RL Workshop-18], a general framework for online convex optimization for sequential decision processes and extensive-form games [Farina et al., AAAI-19], the first scalable algorithm for trembling-hand equilibrium refinements [Farina et al., NeurIPS-18], and trembling-hand refinement of Stackelberg equilibria [Farina et al., IJCAI-18; Marchesi et al. AAAI-19].
Bio: Tuomas Sandholm is Angel Jordan Professor of Computer Science at Carnegie Mellon University. He is Co-Director of CMU AI. He is Founder and Director of the Electronic Marketplaces Laboratory. He is Founder and CEO of Optimized Markets, Strategic Machine, and Strategy Robot. He has designed and fielded $60 billion of combinatorial auctions. His algorithms run the national kidney exchange for UNOS. Optimized Markets is bringing new optimization-powered paradigms to advertising campaign sales, scheduling, and pricing—in TV, streaming, display, mobile, game, radio, and cross-media advertising. Strategic Machine and Strategy Robot are bringing computational game solving to business, military, gaming, and sports applications. Among Prof. Sandholm's many honors are the Minsky Medal, IJCAI Computers and Thought Award, inaugural ACM Autonomous Agents Research Award, Allen Newell Award for Research Excellence, Sloan Fellowship, Carnegie Science Center Award for Excellence, Edelman Laureateship, and NSF Career Award. He is Fellow of the ACM, AAAI, and INFORMS. He holds an honorary doctorate from the University of Zurich.
Bio: Tuomas Sandholm is Angel Jordan Professor of Computer Science at Carnegie Mellon University. He is Co-Director of CMU AI. He is Founder and Director of the Electronic Marketplaces Laboratory. He is Founder and CEO of Optimized Markets, Strategic Machine, and Strategy Robot. He has designed and fielded $60 billion of combinatorial auctions. His algorithms run the national kidney exchange for UNOS. Optimized Markets is bringing new optimization-powered paradigms to advertising campaign sales, scheduling, and pricing—in TV, streaming, display, mobile, game, radio, and cross-media advertising. Strategic Machine and Strategy Robot are bringing computational game solving to business, military, gaming, and sports applications. Among Prof. Sandholm's many honors are the Minsky Medal, IJCAI Computers and Thought Award, inaugural ACM Autonomous Agents Research Award, Allen Newell Award for Research Excellence, Sloan Fellowship, Carnegie Science Center Award for Excellence, Edelman Laureateship, and NSF Career Award. He is Fellow of the ACM, AAAI, and INFORMS. He holds an honorary doctorate from the University of Zurich.
Autonomous Systems with Humans-in-the-Loop
Monday, May 20, 2019, 9:00 - 10:00, Royal Palm BallroomMaarten Sierhuis
Nissan Research CenterAbstract: Advances in artificial intelligence are making systems smarter, more responsive, and better at making decisions in a variety of environments. But we are still not at a point where autonomous systems can know exactly how to handle unpredictable situations. This is one of the roadblocks to realizing a fully autonomous future. Autonomous systems need a human-in-the-loop. In this talk, I will discuss the limitations of today’s autonomous systems with the example of fully autonomous vehicles, also known as driverless vehicles, and autonomous systems in healthcare.
Bio: Dr. Maarten Sierhuis is Chief Technology Director of the Alliance Innovation Lab Silicon Valley. In this role he oversees the technical innovation with responsibility to connect Silicon Valley internal research outcomes and external technology intelligence to the Alliance research & advanced engineering functions. Previously, as Director of the Nissan Research Center Silicon Valley, Sierhuis led a team of researchers tasked with developing Artificial Intelligence (AI) technologies for autonomous vehicles, connected vehicles and Human-Machine Interaction and Interfaces (HMI²) to help shape the future of intelligent cars capable of driving themselves.
Prior to Nissan, he spent 12 years at NASA where he created the Brahms agent language that was used to develop an intelligent agent system for communication between Mission Control and the International Space Station. He also developed an autonomous system for human-robot collaboration, and monitor and give advice to astronauts during extra-vehicular activities.
He is a co-founder of Ejenta, a San Francisco-based healthcare company that enables health providers to monitor chronically-ill patients in their homes in real time. Personalized intelligent agents detect abnormalities, predict health deterioration in advance, and present actionable data to keep care teams connected.
Bio: Dr. Maarten Sierhuis is Chief Technology Director of the Alliance Innovation Lab Silicon Valley. In this role he oversees the technical innovation with responsibility to connect Silicon Valley internal research outcomes and external technology intelligence to the Alliance research & advanced engineering functions. Previously, as Director of the Nissan Research Center Silicon Valley, Sierhuis led a team of researchers tasked with developing Artificial Intelligence (AI) technologies for autonomous vehicles, connected vehicles and Human-Machine Interaction and Interfaces (HMI²) to help shape the future of intelligent cars capable of driving themselves.
Prior to Nissan, he spent 12 years at NASA where he created the Brahms agent language that was used to develop an intelligent agent system for communication between Mission Control and the International Space Station. He also developed an autonomous system for human-robot collaboration, and monitor and give advice to astronauts during extra-vehicular activities.
He is a co-founder of Ejenta, a San Francisco-based healthcare company that enables health providers to monitor chronically-ill patients in their homes in real time. Personalized intelligent agents detect abnormalities, predict health deterioration in advance, and present actionable data to keep care teams connected.
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