U.S. Air Force Strategic Deterrence Analytic Capabilities An Assessment of Tools, Methods, and Approaches for the 21st Century Security Environment (2014) / Chapter Skim
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3 Selected Discussion of Tools, Methods, and Approaches for Deterrence and Assurance
3 Selected Discussion of Tools, Methods, and Approaches for Deterrence and Assurance
Pages 51-87
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2. The value of analysis depends primarily on the talent, education, and experience of the analysts and their work environments.
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The leftmost column groups the methods in three major classes: those that help to collect, organize, or analyze data; those that involve knowledge structuring, model building, and theory building; and those for analysis to aid decision making. The committee did not include methods regarded as simply part of the baseline (e.g., operations research, statistics, quantitative po litical science, simulation, standard game theory, and standard decision analysis)
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Selected Discussion of Tools, Methods, and A pp r o a c h e s 53 TABLE 3-1 Selected Methods to Address Issues in Analysis of Deterrence and Assurance Safe, Test Beyond Planning Anticipating Secure, General Cases for Rational Under the and Methods Deterrence Planning Actor UncertaintyUnexpected Effective Empirical and quasiempirical Data collection •• •• •• •• •• Crowdsourcing Data mining Social science analytics •••• •• •••• •• •• Case studies and narratives Content analysis and profiling Social network analysis Gaming and computational •••• •• •••• •• •• experimentation Human gaming Computational experimentation Knowledge organization, modeling, and theory Frameworks and qualitative modeling •••• •••• •••• •••• •• •• Broadened framework of decision making Complex adaptive systems Causal system depictions Qualitative system modeling System diagrams Factor trees, cognitive maps and models Qualitative game theory Computational modeling •• •• •• System dynamics, Bayesian nets, influence nets Game-structured agent-based modeling Modeling of limited rationality Analysis Analysis methods •••• •••• •••• •••• •••• •••• Leadership profiling Analyzing receptivity issues Exploratory analysis and robust decision making Strategic portfolio analysis •••• •••• •••• •••• •••• Synergy across methods NOTE: Number of bullets indicates subjectively assessed relative applicability.
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For this or other reasons, private companies can sometimes do better in this regard.1 Big Data Mining Experiments, observations, and numerical simulations in science and business are currently generating terabytes of data, verging on petabytes and beyond.2 In contrast to traditional isolated analysis, the paradigm for "big data" is often for 1 Companies offering crowd sourcing analyses include Monitor 360 and Wikistrat. RAND researchers have also developed a system Called ExpertLens (Dalal et al., 2011)
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The potential of the big data approach is undeniable. At the time of its study, however, the committee did not yet see successful unclassified applica tions clearly relevant to deterrence and assurance, although it noted opportunities as mentioned in the later section on Content Analysis.
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Narrative analysis includes thematic, structural, interactional, and performative aspects. Thematic analysis focuses on the "what" -- that is, on the meaning rather than the language used.
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. As discussed later in this chapter under "Analysis Methods" and in much more detail in Appendix E, modern quantitative content analysis can be a powerful tool in developing and updating leadership profiles directly useful for deterrence and assurance.
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It is now possible to conduct a huge quantitative content analysis of electronic text quickly. Table 3-2 illustrates a scale stemming from such work.
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Centrality measures characterize the relative importance of a node in a network -- for example, "degree centrality" which calculates the num ber of direct ties to a node; "betweenness centrality," which measures the relative importance of a particular node by how many other nodes it connects to; and 5 To play the Kevin Bacon game, players search for the shortest connections between a chosen individual and the actor. For example, an individual's Bacon number would be 6 if his or her second cousin was Anne Bancroft, Anne Bancroft was in Waking Ned with Ian Bannen; Ian Bannen was in Braveheart with Mel Gibson; Mel Gibson was in Bird on a Wire with Goldie Hawn; Goldie Hawn was in Housesitter with Steve Martin; and Steve Martin was in Novocain with Kevin Bacon.
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S . A i r F o r c e S t r at e g i c D e t e r r e n c e A n a ly t i c C a pa b i l i t i e s Louise 2 2 Ada 2 Lena 1 1 1 2 Adele Marion 1 1 1 2 Jane 2 2 Cora 1 1 Frances 1 2 2 Maxine 2 Mary 1 2 2 1 2 Eva 2 1 Edna 1 Ruth 1 1 Anna 1 Martha 1 Betty 2 2 Robin 1 1 Jean 2 2 2 2 2 1 2 1 Alice Laura 1 2 1 Hazel 2 Helen Hilda Ellen 1 2 1 2 1 Ella Irene FIGURE 3-1 Nodes and edges in a social network.
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This suggests that war games dealing with strategic nuclear deterrence should col lect data and information from adjudication teams as from traditional player cells. This is not usually possible because it would mean additional and time-consuming overhead, making it difficult to have an effective game within the usual one-week time period allocated by major commands for a war game.
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This may have communi cated the wrong lessons on WMD play because of artificial restraints. War games involving nuclear exchanges conducted by AFGSC may err in the opposite direction.
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. Computational modeling will be discussed primarily in later sections relating to knowledge and theory development, but its data-generating role has become important with the advent of new technology, computer power, and conceptual approaches to analysis.
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If the models have sufficient structural validity and uncer tainties can be bounded, exploratory analysis can yield nontrivial insights. Those, however, must then be assessed separately, as are, for example, potential insights from war gaming or experience.
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systemic-, social-, and individual-level considerations. Here "social" includes type of regime and political system, standard operating pro cedures, factional interests, and related social psychology.
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Individuals of Individuals of Actor A Actor B FIGURE 3-2 A broad framework for thinking about human decision making. response based on available information rather than on motivational, affective, or cognitive biases in a deterrence or assurance situation.
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. Doing so should also be part of the basic education of analysts seeking to describe or understand phenomena such as deterrence.16 Com plexity thinking affects many of the other sections of this report, including that on computational modeling.
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System Diagrams of System Dynamics, Bayesian Nets, and Influence Nets MIT-style system dynamics is more fully described in a later section under computational modeling, but a key element is its use of causal-loop and stock flow diagrams that convey a "system map" or "system view."18 Somewhat analo gous "influence diagrams" stemming from Carnegie Mellon research by Granger Morgan and Max Henrion serve similar purposes.19 System Dynamics is especially good at representing dynamical developments in systems with feedback loops. The Morgan-Henrion style has advantages for uncertainty analysis, multiresolution modeling, and decision aiding.
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Factor trees can be turned into modular computational models that exploit more social science knowledge. However, because of uncertainties, they should be used for exploratory analysis, as described in the later section by that name, rather than forecasting.23An example, Figure 3-3, shows a factor tree for public support for insurgency and terrorism.
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• Cultural and historical factors. FIGURE 3-3 Factor tree for public support of insurgency and terrorism.
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Considerable knowledge and sophistication are necessary, even though some of the methods appear simple. Qualitative Game Theory Game theory has long been important background for strategic thinking and practice with the basic concepts providing insights and language, such as Prisoner's Dilemma or Chicken.
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It follows that game outcomes include some worrisome situa tions that are not the familiar Nash equilibria of static game theory: they reflect dilemmas analogous in significance to, say, the Prisoner's Dilemma or the game of Chicken. Game theoretic methods are valuable not only because of their insights but because, despite their simplicity and unpretentiousness, they add important aspects of realism that can readily be communicated and learned.
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Game-Structured, Agent-Based Modeling Example from the 1980s Lessons can be learned from a game-structured simulation that was developed in the Cold War as the RAND Strategy Assessment System (RSAS) .32 This was a global analytic war game covering conventional war through general nuclear war.
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war games conducted in the 1980s (Bracken, 2012)
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Modeling of Limited Rationality A cross-cutting issue in computational modeling (and, also in the qualitative modeling described earlier) is the type of reasoning assumed.
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. 40 Examples include operations research, systems analysis, statistics, and classic game theory as described in, for example, Powell (2005)
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strategic portfolio analysis. The method of sequential ordinal games discussed earlier (under qualitative game theory)
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The methods of content analysis and leader ship profiling in conjunction with other methods have the potential to help meet requirements of actor-specific knowledge for a strategy of tailored deterrence. An alliance among content analysis, leadership profiling, abstract modeling, and gam ing and simulations as a suite of methods is possible in order to solve the complex problems associated with studying the decision-making dynamics of single groups and multiple autonomous actors as decision units.
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The methods are highly relevant to deterrence, assurance, and related matters where uncertainties loom large. The concept of exploratory analysis is seemingly straightforward.
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confronting deep uncertainty and, often, disagreement among policy makers, when establishing strategy and allocating resources. It has a metaphorical relationship to financial portfolio analysis and is logi cally just another example of multiple-criteria decision analysis.
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In the corporate world, this is sometimes ac complished with outside strategic consultant companies enlisted by top corporate officials. OPPORTUNITIES FOR SYNERGY ACROSS TOOLS, METHODS, AND APPROACHES Opportunities exist for synergy among, for example, human gaming, qualitative and computational modeling, historical studies, and game theory -- raditionally t separate activities.
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An initial qualitative model is constructed drawing on the best social sci ence, using both qualitative and quantitative methods and reflecting lessons from gaming and game theory.
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Fostering Cross-Domain Collaboration. Perhaps the most im portant next step in methods relevant to deterrence and assurance would be orga nized support for cross-cutting work drawing on the tentative insights and analysis from such disparate domains as human war-gaming, qualitative sequential games, simple cognitive modeling, leadership profiling, computational modeling, history, and other sources.
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1972. Content Analysis; A Technique for Systematic Inference from Communications.
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1969. Content Analysis for the Social Sciences and Humanities.
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2011a. Applications of game theory in support of intelligence analysis.
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1994. Social Network Analysis: Methods and Applications.
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