Cyber-social learning systems (CSLS) are purposeful socio-technical systems that learn. They learn how to perform much better over time, as manifested in continuous progress toward, and ultimately in the achievement and maintenance of, extraordinary levels of fitness for purpose. Learning in this sense is more like learning how to play the piano than learning that a proposition is true or learning what function generated given data. CSLSs are systems that learn to, and that then do, perform at virtuoso levels of quality. Many of today’s most critical systems — for defense, healthcare, education, community services, transportation, energy and environment, etc. — are archaic, vastly under-performing, and unsustainable. The challenge is to put them on a path to becoming CSLSs. An audacious goal is to transform them into CSLS that exhibit dramatic improvements in performance within at most a decade or two. The results would include great reductions in cost and environmental impact while vastly improving the security, health, wellbeing, and quality of life of billions of people the U.S. and around the globe. The question of how to achieve the transformation of today’s systems into cyber-social learning systems of the future was the subject of a series of workshops sponsored by the Computing Community Consortium, advisory to the National Science Foundation and other policy makers. In this talk, I will introduce the concept of cyber-social learning systems; the need for new scientific, engineering, and design foundations to enable their development; and a path toward such foundations based on convergent research that integrates computing, complex systems studies, the social, behavioral, and economic sciences, and other disciplines, along with test and evaluation in diverse domains of practice, to realize the vision of a world of interconnected cyber-social learning systems at scale.

Kevin Sullivan joined the SERC as a researcher through the University of Virginia, where he serves as an Associate Professor of Computer Science in the School of Engineering and Applied Science. He received his undergraduate degree from Tufts University in 1987 and the MS and his Ph.D. in Computer Science from the University of Washington in Seattle, Washington in 1994. His Ph.D. advisor was David Notkin. Dr. Sullivan received an NSF Career Award in 1995, the (first) ACM Computer Science Professor of the Year Award from undergraduate students in 1998, a University Teaching Fellowship in 1999, the Harold Morton Jr. Teaching Prize in 2000, and a Virginia Engineering Foundation Endowed Faculty Fellowship in 2003. Dr. Sullivan’s research interests are in software-intensive systems, in general, and in software engineering and languages. He recently served as associate editor for the Journal of Empirical Software Engineering and the ACM Transactions on Software Engineering & Methodology, and on the program and executive committees of conferences including the ACM SIGSOFT Symposium on the Foundations of Software Engineering (FSE), the International Conference on Software Engineering (ICSE), Aspect-Oriented Software Development (AOSD) and ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages (POPL). In addition, Dr. Sullivan is currently serving as a member of the SERC Research Council, providing guidance and insight for SERC’s growth of the Trusted Systems research area.