Abstract
Events occur daily that challenge the security, health and sustainable growth of our nation, and often find our government agencies unprepared for the catastrophic outcomes. These events involve the interaction of complex processes such as climate change, energy reliability, terrorism, nuclear proliferation, natural and man-made disasters, social/political and economic vulnerability. If we are to help our nation to meet the challenges that emerge from these events, we must develop novel methods for predictive analysis that support a concerted decision-making effort by analyst and policymakers to anticipate and counter strategic surprise. There is now increased awareness among subject-matter experts, analysts, and decision makers that a combined understanding of interacting physical and human factors is essential in addressing strategic surprise proactively. The Technosocial Predictive Analytics (TPA) framework provides an operational advancement of this insight through the development of new methods for anticipatory analysis and response that implement a multi-perspective approach to predictive modeling through the integration of human and physical models facilitate the achievement of knowledge/evidence inputs to support the modeling task and promote inferential transparency enable analysts and policymakers to stress-test the quality of their intelligence products and planned responses without waiting for history to prove them right or wrong. Human Language Technologies (HLT) play an important role in the realization of this framework with specific reference to evidence extraction, but must be augmented to support TPA’s knowledge requirements properly. In presenting TPA, I will discuss an approach which provides such an extension of HLT through the integration of insights from specific domains of expertise and content analysis processes.
Biography
Dr. Antonio Sanfilippo is Chief Scientist in the Computational and Statistical Analytics Division at Pacific Northwest National Laboratory (PNNL). His research focus is on Computational Linguistics, Content Analysis, Knowledge Technologies and Predictive Analytics with reference to Cognitive, Social, Behavioral and Biomedical Sciences. Dr. Sanfilippo holds a Laurea degree in Foreign Modern Languages awarded cum laude from the University of Palermo in Italy, M.A. and M. Phil. degrees in Anthropological Linguistics from Columbia University, and a Ph.D. in Cognitive Science from the University of Edinburgh (UK). Dr. Sanfilippo is the recipient of the 2008 Laboratory Director’s Award for Exceptional Scientific Achievement at PNNL. For more about Antonio please visit: http://www.linkedin.com/in/antoniosanfilippo