COMPUTATIONAL SOCIAL SCIENCE – Complex Intelligence Preparation of the Battlefield: An Effort to Operationalize the Integration of Political Theory to Improve Analysis Across the Intelligence Enterprise – Thomas Pike

When:
April 14, 2017 @ 3:00 pm – 4:30 pm
2017-04-14T15:00:00-04:00
2017-04-14T16:30:00-04:00
Where:
Center for Social Complexity Suite 3rd Floor, Research Hall, Fairfax Campus
Cost:
Free
Contact:
Karen Underwood
703-993-9298

COMPUTATIONAL SOCIAL SCIENCE FRIDAY SEMINAR

Thomas Pike, PhD Student
Computational Social Science
Department of Computational and Data Sciences
George Mason University

Complex Intelligence Preparation of the Battlefield:
An Effort to Operationalize the Integration of Political Theory to Improve Analysis Across the Intelligence Enterprise 

Friday, April 14, 2017,  3:00 p.m.
Center for Social Complexity Suite
3rd Floor, Research Hall

Fifteen years of conflict have shown severe limitations in the United States’ ability to influence foreign populations in pursuit of national objectives. Intertwined within these challenges is the difficulty the U.S. Intelligence Enterprise has in integrating recent research to more effectively analyze foreign populations and support decision makers. The introduction of a Complex Adaptive Systems based meta-framework for intelligence analysts, supported by an agent based model can reduce the cost of analysts learning and applying new research. As a first attempt we adopt the Army’s current framework Intelligence Preparation of the Battlefield (IPB) and begin to formulate one possible meta-perspective Complex Intelligence Preparation of the Battlefield. Complex IPB has the potential to be a constantly improving model that integrates new and emerging theories from economics, communication, politics, demography, game theory and social network analysis to analyze the emergence and contagion of civil conflict in local populations. Complex IPB can assist in identifying regions of potential instability before escalation. Finally, a quasi-global sensitivity analysis identifies effective and efficient policy levers in the face of limited resources.