AI and Robotics Task Force

Chairs: Greg Hager and Eric Horvitz

Gregory HagerGregory Hager

Johns Hopkins University

Bio

Gregory Hager   Website


Gregory D. Hager is a Professor and former Chair of Computer Science at Johns Hopkins University. He received his BA from Luther College and his MSE and PhD from the University of Pennsylvania in 1986 and 1988, respectively. After a year as a Fulbright scholar at the University of Karlsruhe, he joined the faculty of Yale University in 1990. He moved to Johns Hopkins in 1999. His research interests include image-guided robotics, human-machine collaboration, and medical applications of image analysis and robotics. He has served as the Deputy Director of the NSF Engineering Research Center for Computer Integrated Surgical Systems and Technology, he serves on board of the International Federation of Robotics Research, and he is a fellow of the IEEE for his contributions in vision-based robotics. He serves as Chair of the Computing Community Consortium.

Eric HorvitzEric Horvitz

Microsoft Research

Bio

Eric Horvitz   Website


Eric Horvitz is a Technical Fellow at Microsoft Research. He is pursuing research on principles of machine intelligence and on leveraging the complementarities of human and machine reasoning. He is passionate about harnessing the latest computing advances to provide valuable services. He has long been curious about the computational foundations of intelligence: How do our minds work? What computational principles and architectures underly thinking and intelligent behavior? A key focus of his work has been on opportunities to leverage the complementarities of human and machine intelligence. Related interests include machine learning and decision making for crowdsourcing and human computation, information triage and alerting that takes human attention into consideration, spanning work on notification systems, surprise modeling, multitasking, and psychological studies of interruption and recovery.

Current Members:
Randy BryantRandy Bryant

Carnegie Mellon University

Bio

Randy Bryant Website


Randal E. Bryant has been on the faculty at Carnegie Mellon since 1984, starting as an Assistant Professor and progressing to his current rank of University Professor of Computer Science. He also holds a courtesy appointment in the Electrical and Computer Engineering Department. Dr. Bryant’s research focuses on methods for formally verifying digital hardware, and more recently some forms of software. His 1986 paper on symbolic Boolean manipulation using Ordered Binary Decision Diagrams (BDDs) has the highest citation count of any publication in the Citeseer database of computer science literature. In addition, he has developed several techniques to verify circuits by symbolic simulation, with levels of abstraction ranging from transistors to very high-level representations.

Vasant HonavarVasant Honavar

Pennsylvania State University

Bio

Vasant Honavar Website


Vasant Honavar is a Professor and Edward Frymoyer Chair of Information Sciences and Technology and Professor of Bioinformatics and Genomics and of Neuroscience at Pennsylvania State University where he currently leads the Artificial Intelligence Research Laboratory and the Big Data Analytics and Discovery Informatics Initiative. Honavar has served as a Program Director in the Information and Intelligent Systems Division at the National Science Foundation (during 2010-2013) where he contributed to multiple programs including Information Integration and Informatics, Smart and Connected Health, and led the Big Data Science and Engineering Program. Prior to joining Pennsylvania State University, Honavar was Professor of Computer Science and of Bioinformatics and Computational Biology and Director of the Artificial Intelligence Research Laboratory (during 1990-2013), and Chair of the Bioinformatics and Computational Biology Ph.D. program (during 2003-2005) at Iowa State University. He served on the National Institutes of Health study section on Biological Data Management and Analysis during 2002-2007. Honavar’s current research and teaching interests span Artificial Intelligence, Machine Learning, Bioinformatics, Big Data Analytics, Computational Molecular Biology, Data Mining, Discovery Informatics, Information Integration, Knowledge Representation and Inference, Semantic Technologies, Health Informatics, Neuroinformatics, Social Informatics and Security Informatics. His research (documented in over 250 peer-reviewed publications) has contributed scalable approaches to learning predictive models from “big data” – including in particular, very large, distributed, semantically disparate, richly structured data (including tabular, sequence, network, relational, time series data); knowledge-based, statistical and network-based approaches to integrating information, Eliciting causal information from multiple sources of observational and experimental data; Selective sharing of knowledge across disparate knowledge bases; Representing and reasoning about preferences; Composing complex services from components; and applications in bioinformatics and computational molecular and systems biology. Honavar has graduated over 30 PhD students, many of whom are leaders in academia and industry. Honavar currently serves on the editorial boards of several journals including IEEE/ACM Transactions on Computational Biology and Bioinformatics. He has served as a general co-chair of the IEEE International Conference on Big Data (2014). Honavar earned his Ph.D. degree from the University of Wisconsin-Madison in 1990.

Maja MatarićMaja Matarić

University of Southern California

Bio

Maja Matarić Website


Maja Matarić is professor and Chan Soon-Shiong chair in Computer Science Department, Neuroscience Program, and the Department of Pediatrics at the University of Southern California, founding director of the USC Robotics and Autonomous Systems Center (RASC), co-director of the USC Robotics Research Lab and Vice Dean for Research in the USC Viterbi School of Engineering. She received her PhD in Computer Science and Artificial Intelligence from MIT in 1994, MS in Computer Science from MIT in 1990, and BS in Computer Science from the University of Kansas in 1987. Prof. Matarić is the author of a popular introductory robotics textbook, “The Robotics Primer” (MIT Press 2007), an associate editor of three major journals and has published extensively. She serves or has recently served on a number of advisory boards, including the National Science Foundation Computing and Information Sciences and Engineering (CISE) Division Advisory Committee, and the Willow Garage and Evolution Robotics Scientific Advisory Boards. Prof. Matarić is actively involved in K-12 educational outreach, having obtained federal and corporate grants to develop free open-source curricular materials for elementary and middle-school robotics courses in order to engage student interest in science, technology, engineering, and math (STEM) topics. This is Maja’s first year on the CCC Council.

Dramatic advances in the power and practicality of Artificial Intelligence (AI) have broad us to a point where the potential impact of AI on society and economy are far-reaching and profound. Yet, we are just at beginnings of understanding the possibilities for AI-related technologies, and at the same time are struggling to understand and advance beyond the substantial limitations of current state-of-the art systems.

The role of this task force is to provide a mechanism for articulating both the state of the art and technical limitations of AI, to help develop forward-looking research agendas for the field, and to better understand the potential of AI to provide tremendous social good in the future, including but not limited to urban computing, health, environmental sustainability, and public welfare.

CCC materials produced and curated for this task force include:

Science and Policy Materials on AI:

NITRD –  In October 2016, the Networking and Information Technology Research and Development (NITRD) Program released the The National Artificial Intelligence Research and Development Strategic Plan which identifies the strategies and priorities for Federally-funded AI research.

OSTP – In October 2016,the White House Office of Science and Technology Policy (OSTP) published the Preparing for the Future of Artificial Intelligence report, which “surveys the current state of AI, its existing and potential applications, and the questions that are raised for society and public policy by progress in AI. The report also makes recommendations for specific further actions by Federal agencies and other actors.”

White House OSTP Request for Information (RFI) for AI – In June 2016, OSTP announced a new Request for Information (RFI) on Artificial Intelligence (AI), to solicit feedback on how the United States can best prepare for the future of AI. According to the OSTP Blog, they “received 161 responses from a range of stakeholders, including individuals, academics and researchers, non-profit organizations, and industry.” All of the responses are now public and can be found here. The CCC’s response can be found here.

AI-related Events:

OSTP Workshop Series – In May, 2016 OSTP announced four workshops (later a fifth was added) surrounding the future of artificial intelligence to explore the opportunities and challenges that AI presents.

  • Artificial Intelligence for Social Good – The CCC co-hosted the second OSTP AI Workshop, Artificial Intelligence for Social Goodwith OSTP and AAAI. In this workshop, we discussed the successful deployments and the potential use of AI in various topics that are essential for social good, including but not limited to urban computing, health, environmental sustainability, and public welfare. You can learn more about the workshop here.
  • Artificial Intelligence: Law and PolicyThe first workshop in the series was co-hosted by the University of Washington School of Law, the White House, and UW’s Tech Policy Lab, “the event places leading artificial intelligence experts from academia and industry in conversation with government officials interested in developing a wise and effective policy framework for this increasingly important technology.”
  • The Future of Artificial Intelligence – The third workshop, co-hosted by Stanford University and OSTP, featured “leading artificial intelligence (AI) researchers will discuss the most impactful research topics in AI and highlight the challenges and potentials of artificial intelligence.”
  • Workshop on Safety and Control for Artificial Intelligence – The fourth workshop was co-hosted by Carnegie Mellon University and OSTP and included “keynote talks and panel discussions that explore the potential future of AI and AI applications, the emerging technical means for constructing safe and secure systems, how safety might be assured, and how we can make progress on the challenges of safety and control for AI.”
  • The Social and Economic Implications of Artificial Intelligence Technologies in the Near-Term – The fifth workshop in the series was co-hosted by the NYU Information Law Institute and the White House generated “a foundational discussion about the role of AI in social and economic systems.”

One Hundred Year Study on AI – “The One Hundred Year Study on Artificial Intelligence, or AI100, is a 100-year effort to study and anticipate how the effects of artificial intelligence will ripple through every aspect of how people work, live and play” and is the brainchild of task force co-chair Eric Horvitz. Learn more about the One Hundred Year Study here and view the 2016 report here.

Other Resources:

Partnership on AI – In September, 2016 Amazon, DeepMind/Google, Facebook, IBM, and Microsoft “announced that they will create a non-profit organization that will work to advance public understanding of artificial intelligence technologies (AI) and formulate best practices on the challenges and opportunities within the field. Academics, non-profits, and specialists in policy and ethics will be invited to join the Board of the organization, named the Partnership on Artificial Intelligence to Benefit People and Society (Partnership on AI).” You can read the full press release here.

2016 Robotics Roadmap – In 2009, the CCC released A Roadmap for US Robotics, From Internet to Robotics (Robotics Roadmap). The Robotics Roadmap explored the capacity of robotics to act as a key economic enabler, specifically in the areas of manufacturing, healthcare, and in the service industry, 5, 10, and 15 years into the future and was influential in developing 2011’s National Robotics Initiative (NRI). An updated version of the Robotics Roadmap was released in November, 2016 and it expands on the topics discussed in the 2009 roadmap as well as addressing the areas of public safety, earth science, and workforce develop. You can read the full 2016 roadmap here.