Overview of how various USG agencies use CAS concepts for analysis of international security problems. Presented as a university seminar to graduate students in international security policy studies at University of Maryland
Complex Adaptive Systems and International Security Analysis
1. Understanding WMD Proliferation: Applying Complex Adaptive Systems Theory Nancy K. Hayden [email_address] [email_address] December 1, 2011
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6. Social Complexity Creates “ Wicked Problems” for Policy Analysts A wicked problem is one for which each attempt to create a solution changes the understanding of the problem. Wicked problems cannot be solved in a traditional linear fashion, because the problem definition evolves as new possible solutions are considered and/or implemented.
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9. Definitions II Structure: Simple, Complex, Random Innovation Surprise Unpredictable Structural Complexity Randomness 0 1
12. 2. States change over time through predictable mechanisms… … affecting structural form, function, and behaviors. 1. Systems in different states should be analyzed and managed differently Two Key Points
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14. Network Structures Enable Different Types of Behaviors and Outcomes Weak Links Ring Connected Ring Trees Giant Star High School Friendships High School Dating Web Sites Yeast Proteins TB Contagion Small Worlds Cliques Books on Politics Freshwater Food Web
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17. Network Structures State System Predict Adaptive Adversary Behaviors and Most Effective Policy OSD Solution: Use network metrics to anticipate and disrupt potential innovation paths Policy Strategies
18. Policy Analysis Example 2: IC efforts to Prevent Terrorism The key is to better understand the future—plan to change it, and change it Develop Understanding Logistics/ Infrastructure Social/ psychological Simulation Gaming, Statistics, Modeling MOADB indications & warnings increase hope warn first responders manipulate - deceive - control - dissuade - deter - destroy enhanced collection scenario driven hypothesis Policy decisions Reality mitigate
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22. Causal Loop Diagram with Feedback System Dynamics modeling yields non-intuitive insights into relationships between stocks, flows, and agent interactions.
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26. SUBMODULE A : Resource Mobilization and Public Well-being
30. Putting it all together: Frame the Problem Forecast Question Epistemology Information Density/unit time System Complexity Describe Explore Interpret Infer Suggest Analysis approach depends on what question is being asked, in what timeframe Predict
31. Systems Thinking and National Security Observation Table Top Exercises Forecast Question Epistemology Information Density/unit time System Complexity Describe Explore Interpret Infer Predict Law Enforcement Explain Case Studies Field Surveys Statistical Analysis Social Network Analysis Academic emphasis Remote Sensing Evidentiary Reasoning Red Teaming Gaming Network Analysis Modeling & Simulation Intelligence/security Analysts
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Notas del editor
WMD proliferation has become complex involving understanding of social systems beyond traditional models of political-military strategy SNL is systems engineering lab. We do lots of development of systems models for policy makers.
CAS thinking provides a framework for understanding the ‘systematic patterns of thought” that remain after a particular government or its capabilities have been “torn down”. This is key to countering proliferation of WMD. What motivates governments or non-state actors to proliferate WMD? How do socio-cultural, economic, and political systems constrain those decisions?
The questions that are asked for WMD proliferation policy analysis are much the same, in the abstract, as other issues in international security. The same framework of Complex Adaptive Systems can be used. This aids in looking at the linkage between issue areas.
Ky characteristics of CAS are 1) purposeful agents; 2) self-organizing and adaptive; and 3) emergent behaviors. Structures provide architecture (topology) through which resources are transmitted. They can change over time. They lead to specfic, measurable metrics for predicting network behaviors. Dynamics - the observed network behaviors; are related to structure.
The term was originally coined by Horst Rittel in early 70’s when studying civil engineering problems for traffic systems in northern california. Wicked problems always occur in a social context -- the wickedness of the problem reflects the diversity among the stakeholders in the problem. Because the group or team's understanding of the wicked problem is evolving, productive movement toward a solution requires powerful mechanisms for getting everyone on the same page. There will be volumes facts, data, studies and reports about a wicked problem, but the shared commitment needed to create durable solution will not live in information or knowledge. Understanding a wicked problem is about collectively making sense of the situation and coming to shared understanding about who wants what.
The problem is ill-structured, an evolving set of interlocking issues and constraints. Since there is no definitive "The Problem", there is also no definitive "The Solution." The problem solving process ends when you run out of resources. simply "better," "worse," "good enough," or "not good enough." There are so many factors and conditions, all embedded in a dynamic social context, that no two wicked problems are alike, and the solutions to them will always be custom designed and fitted.
The “rules” that self-organizing, purposeful elements in a systems are guided by are often referred to as “schema” in complexity literature.
From the Cynefin framework for organization theory and sense-making http://www.cognitive-edge.com/articledetails.php?articleid=14
Murray Gelman points out that adaptation can take place on one of three very different levels. One is a response to changes in the environment, but does not require a change in the way the elements of the system think about themselves, their functions, or their relationships to each other and the environment. A second occurs when there is competition among the way that various elements function, with winners and losers. The performance of the winner is learned and copied. . The third is the familiar evolutionary process. Stephen Jay Gould; Ernst Mayer
From Cynefin Framework
While globalization is making the world “smaller”, we will continue to live in a world of increasing cultural, economic, and technological divides that have the potential to fuel the fires of hate and resentment against the west. In the studies done since September 11, including our own study within the ACG, one repeatedly sees calls for understanding and addressing “root causes” of terrorism, as well as understanding and protecting against our vulnerabilities. A key part of security will be understand what this means, and find ways to deal with these root causes, drawing on communication and cooperation across these divides. Current administration recognizes these factors and is engaged in proactive research partnerships globally. One such initiative is the US – Mexico Cooperation.
System dynamics was created during the mid-1950s[3] by Professor Jay Forrester of the Massachusetts Institute of Technology. Forrester's insights into the common foundations that underlie engineering, which led to the creation of system dynamics, were triggered, to a large degree, by his involvement with managers at General Electric (GE) during the mid-1950s. At that time, the managers at GE were perplexed because employment at their appliance plants in Kentucky exhibited a significant three-year cycle. The business cycle was judged to be an insufficient explanation for the employment instability. From hand simulations (or calculations) of the stock-flow-feedback structure of the GE plants, which included the existing corporate decision-making structure for hiring and layoffs, Forrester was able to show how the instability in GE employment was due to the internal structure of the firm and not to an external force such as the business cycle.
Convenient GUI system dynamics software developed into user friendly versions by the 1990s and have been applied to diverse systems. SD models solve the problem of simultaneity (mutual causation) by updating all variables in small time increments with positive and negative feedbacks and time delays structuring the interactions and control.
Complexity: Order from disorder – what does system structure look like? Random? Centralized? Growing? Directed? Degree of connectivity? Embedded? Timescale of Processes and decision making: Evolutionary dynamics look at functional role of network and how fitness functions evolve. Robustness can be examined with respect to how systems adapt, evolve in response to environmental perturbations – Self-aware? Here it is key to look at the immediate needs and threats, versus long term. Key will be timeframe of these – punctuated equilibria? Epochal? Diffusive? Function role for analysis (human or machine) -
Complexity: Order from disorder – what does system structure look like? Random? Centralized? Growing? Directed? Degree of connectivity? Embedded? Timescale of Processes and decision making: Evolutionary dynamics look at functional role of network and how fitness functions evolve. Robustness can be examined with respect to how systems adapt, evolve in response to environmental perturbations – Self-aware? Here it is key to look at the immediate needs and threats, versus long term. Key will be timeframe of these – punctuated equilibria? Epochal? Diffusive? Function role for analysis (human or machine) -