The complexity of terrorism: considering surprise and deceit
Sandia National Laboratories
Institute for Complex Adaptive Systems, New Mexico Technical University
Last modified: April 25, 2006
Terrorism can be viewed as an emergent phenomenon of complex, dynamically interacting social, technological, and institutional systems, with behaviors characterized by surprise, adaptation, and strategic deception to maintain robust positions of advantage in asymmetric conditions. Considering terrorism through this lens has significant implications for security and policy analyses, made possible by advances in understanding complex systems over the past twenty years. First, the universal principles that govern the behavior of complex systems provide a framework based on evolutionary dynamics and structural abstractions that transcends traditional academic boundaries and allows synergistic consideration of knowledge from diverse conceptual domains, multiple cultural perspectives, and a wide range of behavioral scales. Second, technical advances in analytic methods derived from complexity science – such as multi-scale, interactive network analysis, evolutionary computing algorithms, hybrid dynamical agent based modeling and simulation, and multi-dimensional pattern analysis and signature detection – provide means for heterogeneous data assimilation, linkage analysis, and alternative competing hypothesis generation and testing that have been computationally intractable in the past. Third, new paradigms for sense-making in situations of high complexity and ambiguity provide security and policy analysts means to explicitly consider complex, interdependent social, technical, and behavioral phenomena such as emergence, innovation, adaptation, self-organization, and surprise in developing counter terrorism strategies. This paper provides an analytic framework based on the principles of complex systems analysis; and describes a new analytic method for deception detection and surprise within that framework; thereby providing new paradigms for sense-making.