Technosocial Predictive Analytics Initiative
The Technosocial Predictive Analytics Initiative (TPAI) is taking the next steps to addressing complex, interwoven issues with highly integrated, innovative models to help analysts and policy makers identify and counter strategic surprise.
Technosocial Predictive Analytics supports a multi-perspective approach to predictive analysis through integrated reasoning, drawing knowledge insights from both the natural and social sciences. More specifically, Technosocial Predictive Analytics defines, develops, and evaluates novel modeling algorithms that integrate domain knowledge about interacting physical and human factors. In so doing, Technosocial Predictive Analytics enables its modeling algorithms with ancillary capabilities aimed at acquiring knowledge inputs and enhancing cognitive access.
Knowledge inputs inform technosocial modeling with subject matter expertise and evidence about natural, technical, individual and organizational factors germane to the application domains of interest. This conceptualization recognizes that issues of interest—such as counter-terrorism, nuclear non-proliferation, and global environmental change—comprise dynamic and interdependent human and physical components. Cognitive enhancement enables the user to interact with the outcomes of the modeling process (i.e., predictions) so as to determine what matters and what can be influenced productively.
Several challenges face our nation including:
- Social and political unrest leading to acts of violence
- Weapons of mass destruction development by rogue countries
- Natural and man-made disasters
- Energy shortages
- Global climate change
Call for Papers: Security Informatics
Special issue on Technosocial Predictive Analytics For Security Informatics
Security Informatics is now accepting papers for a special issue on Technosocial Predictive Analytics For Security Informatics. The special issue, guest edited by PNNL's Antonio Sanfilippo, will focus on all aspects of technosocial, sociotechnical, and complex-system approaches to predictive analytics. EXTENDED: Submissions are due October 10, 2011.