Science Policy Professionals in the Era of Big Data: In Honor of Stephen D. Nelson

Sunday, 15 February 2015: 10:00 AM-11:30 AM
Room LL21C (San Jose Convention Center)
As science and technology become increasingly influential in national and global affairs, the world of policy needs leaders and analysts who can define and resolve issues at the interfaces between science and society. Where will these leaders come from, and how will they develop the knowledge and wisdom they need? What will their information and communication sources and networks look like? Steve Nelson was centrally concerned with these issues in his career at AAAS, including his time as the longest-serving director of the Science and Technology (S&T) Policy Fellowship Program. This session is organized in his honor. The panel uses big data as an example of an area where S&T policy analysis is likely to be quite different for future generations. Datasets relevant to a wide range of policy problems are growing quickly, and techniques for their analysis are emerging. But does the data address the most important questions from a policy perspective? Can the sophisticated techniques produce results that policy audiences can understand and absorb? What role does visualization play in communicating these large-scale insights, with what loss or grain of understanding of the underlying data and analysis? In this session, current AAAS Policy Fellows describe how big data creates special challenges in their jobs and how they address them. The panel also includes the perspective of policy users, drawing from earlier generations of S&T policy analysts who have served at various government agencies.
Susan E. Cozzens, Georgia Institute of Technology
Norine Noonan, University of South Florida
Edward G. Derrick, AAAS Center for Science, Policy, and Society Programs
Beth Russell, University of Chicago
Big Data in Health Policy
Meredith M. Lee, AAAS Science and Technology Policy Fellow, Homeland Security Advanced Research Projects Agency
Big Data and Homeland Security
Kaye Fealing, University of Minnesota
Big Data for Science and Innovation Policy
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