Predictive Societal Indicators of Radicalism

From MilcordWiki

The Decision Modeler is a tool that supports commanders in modeling the operational environment to understand what-if type planning and resource allocation questions.
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Overview

DoD Directive 3000.05 defines Stability Operations as, “civilian and military activities to shape and restore order, ” with the goal to ‘win the peace’. The Predictive Societal Indicators of Radicalism Decision Modeler is a campaign planning and management tool to support commanders in making strategic decisions across various lines of effort such as security, economic, governance, and resource allocation.

Need

The Decision Modeler supports commanders in modeling the operational environment to answer what-if type planning and resource allocation questions. Decision Modeler assists operators and analysts in better understanding the root causes driving instability in a region for the purposes of developing more targeted and effective operations that address the cycle of conditions and behaviors that sustain criminal activity and Improvised Explosive Devices (IED) networks.

Approach

The Decision Modeler instantiates multi-criteria decision analysis for campaign design, planning, and management in complex operations that enables a commander to design decision models for better understanding the tradeoffs associated with various courses of action. As part of our research into identifying data sources for input into the Decision Modeler, we determined that there was a multitude of field collected data available for use in a decision modeling environment, however the data was located in disparate knowledge silos and was not being effectively utilized in analysis and reporting. Additionally, we identified a significant amount of open-source population sentiment data to be applied to data-driven stability operations.

The Decision Modeler is built on decision science principles, multi-criteria decision analysis, a discipline for solving complex problems that involve a set of alternatives evaluated on various metrics. Our tool is pre-populated with data and sample models to provide a starting point for users to conduct course of action forecasting for determining the optimal decision based on costs and benefits, while providing a way to visualize the uncertainty associated with socio-cultural data collected in conflict environments. The tool supports project management by tracking progress along metrics for continual course of action assessment. The Decision Modeler also fosters collaboration through shared model building to create a data repository for ongoing projects in support of knowledge transfer while recording successes and failures for lessons learned analysis.

Our approach consists of:

• Using a process model based on Counterinsurgency and Stability Operations Field Manuals
• Deriving key stability indicators from the multitude of global databases built over decades on governance, economics, and grievances using our course of action knowledge management framework
• Finding the causality between pre-indicators and low-intensity insurgency and civil war onset using by CIRI Human Rights Data Project, Global Terrorism Database, ITERATE, Minorities at Risk (MAR), Political Instability Task Force, Uppsala Conflict Data Program, World Development Indicators and several other datasets.

Benefits

• More effective allocation of CERP (Commander’s Emergency Response Program) and PRT (Provincial Reconstruction Team) budgets
• Risk based operational planning of contingency operations at the Unified Commands

Applications

• Stability, Security, Transition, and Reconstruction (SSTR) operations

References

• Cassani, L., Caglayan, A., Amanda, M., and Bell, S. (2012) Predictive Societal Indicators of Radicalism - Forecasting Political Violence, 2nd International Conference on Cross-Cultural Decision Making in 4th International Conference on Applied Human Factors and Ergonomics 2012 (AHFE 2012), San Francisco, California, USA, July 21-25, 2012. abstract
• Alavedra, J., Stroh, L., Caglayan, A., and Das, S. (2011)Bayesian Analysis of Sentiment Surveys, Fusion 2011, 14th International Conference on Information Fusion, Chicago, IL, July 5-8, 2011.
• Murdie, A. and Bhasin, T. (2011) Aiding and Abetting? Human Rights INGOs and Domestic Anti- Government Protest, Journal of Conflict Resolution. 55(2): 163-191. abstract
• Murdie, A. (2011) Coercion, Capacity, and Coordination: A Risk Assessment Model of the Determinants of Political Violence, Forecasting Political Instability Workshop, Council on Foreign Relations, Washington, DC, March 31, 2011.
• Cingranelli, D., Bell, S., Murdie, A. , Caglayan, A., Stroh, L. and Burke, D. (2011) Predictive Societal Indicators of Radicalism - Forecasting Political Violence, HSCB Focus 2011 Conference, Chantilly, VA, February 8-10, 2011. abstract
• Caglayan, A., Stroh, L. Burke, D. and Morgan, W. (2011) Decision Modeling for Sociocultural Data, HSCB Focus 2011 Conference, Chantilly, VA, February 8-10, 2011. abstract
• Caglayan, A. Increased political violence in store for Italy and Czech Republic? milcord blog. November 28, 2010.
• Stroh, L. Multi Criteria Decision Modeling for Complex Operations milcord blog. July 8, 2010.
• Stroh, L., Caglayan, A., Rashed, T., Burke, D., and Eaton, G., (2010) Geospatial Campaign Management for Complex Operations, 1st International Conference on Cross-Cultural Decision Making, 3rd International Conference on Applied Human Factors and Ergonomics (AHFE), Miami, FL, July 17-20, 2010. abstract
• Dustin, B. (2010) Shuffling methodology for sanitizing Afghanistan TCAPF microdata: a working paper, milcord blog. June 30, 2010.
• Rashed, T. (2010) Geospatial Campaign Design for COIN Civil Affairs, First GeoDesign Summit, ESRI, Redlands, CA, January 6-8, 2010.
• Stroh, L. M., Burke, D., Zhao, Y. T., Caglayan, A. (2009) A System Dynamics Model of Counterinsurgency in Southern Afghanistan, 2009 NAACSOS (North American Association for Computational Social and Organizational Sciences) Annual Conference, Arizona State University, Tempe, AZ, October 23-24, 2009. abstract blog
• Cingranelli, D. L. and David L. R. (2009) The Quantitative Study of Human Rights, In The Encyclopedia of Human Rights, ed. David P. Forsythe. Oxford University Press, 2009.
• Stroh, L.M. (2009) The Inheritance, milcord blog. June 18, 2009.
• Regan, P. M. and Bell, S. R. Changing Lanes or Stuck in the Middle: Why are Anocracies More Prone to Civil Wars? Political Research Quarterly, May 20, 2009. abstract
• Caglayan, A., Burke, D., Eaton, G., Qamar, S., Caglayan, J., and Cingranelli, D., Regan, P., Bell, S., Frank, R. (2009) Predictive Societal Indicators of Radicalism (PSIR), AFRL/RIEA Final Report, Rome, NY, January 2009.
• Guttieri, K. (2006) Unlearning War: U.S. Military Experience with Stability Operations, In Organizational Learning in the Global Context, eds. Leann Brown, Michael Kenney and Michael Zarkin. London: Ashgate, September 2006.
• Cingranelli, D. L., and D. L. Richards. (1999) Measuring the Pattern, Level, and Sequence of Government Respect for Human Rights, International Studies Quarterly 43: 407-417.