Cyber Social Learning Systems
Over the last decade, we have made great progress establishing scientific and engineering principles for cyber-physical systems (CPS). We are thus now on the threshold of a world of physical systems that are computational and connected at all scales, yielding radical improvements in function and performance.
The next major frontier in research and development is the integration of cyber-physical with complex human and social systems and phenomena at scale. Progress will catalyze the transformation of major existing systems into cyber-social learning systems (CSLS) that continually and rapidly improve in their function and performance in complex, evolving environments. Progress in the science and application of CSLS theory, technology, and practice has the potential to drive revolutionary advances across all sectors of our society, including health, healthcare, transportation, education, housing, justice, defense, and more.
The CCC convened three workshops in order to develop and validate the propositions that there is a compelling opportunity and need for basic and applied research in cyber-social learning systems; there are communities that can be formed now to conduct this research; and success would enable dramatic improvements in the function and performance of the systems of the future on which our society will rely.
Goals of these three workshops included:
Develop detailed examples of cyber-social learning systems, including overall cyber-social system architectures, system properties and enforcement, and performance improvements.
Ground and validate this vision in the challenges faced in several major sectors, including health, education, and communities, which have histories of chronic underperformance.
Articulate basic research challenges in cyber-social learning systems, and potential approaches, generalizing across scales and sectors, including open questions, measures of progress, and characteristics of multi-disciplinary teams and methods (including in situ testbeds), required to fully develop and evaluate cyber-social learning system theories, methods, and tools.
Articulate challenges and opportunities for applied research and development in cyber-social learning systems within specific sectors, and project the potential for broader impacts on system function and performance, on economic and workforce development, and on quality of life broadly.
Define capabilities that a combined basic and applied research community could demonstrate in 1, 3, and 5 years, with a view to a 10-20 year time frame for national impact, with measures of success for each phase.
Formulate and communicate a vision of how the NSF, other national, state and municipal agencies, academic and industrial researchers, and industry broadly can form a coalition to advance the science, engineering, design, and impact of cyber-social learning systems.
August 2016 – Workshop 1
November 2016 – Workshop 2
January, 2017 – Workshop 3
Members of the Executive Committee plus General Planning Committee
- Annie Anton, Georgia Tech
- Elizabeth Churchill, Google
- Ann Drobnis, CCC Director
- Charles Friedman, University of Michigan, co-chair
- William Rouse, Stevens Institute
- Joshua C. Rubin, University of Michigan
- Ben Shneiderman, University of Maryland
- Kevin Sullivan, University of Virginia, co-chair
General Planning Committee
- Charlie Catlett, Argonne National Laboratory
- Lori Clarke, University of Massachusetts
- William Griswold, University of California, San Diego
- Deborah Johnson, University of Virginia
- Beth Mynatt, CCC and Georgia Tech
- Jonathan Silverstein, Northshore University HealthSystem
- William Stead, Vanderbilt University
- William Scherlis, CMU
- Stephanie Teasley, University of Michigan