A Crude Look at the Whole: A Simple Guide to Complexity for National Security Professionals
In the summer of 2010, turbid clouds of ochre-colored smoke wafted low across the iron-grey Muscovite sky, obscuring the Kremlin in a miasmic haze so thick it could be worn like a coat according to eyewitnesses. During hot summers in Russia, peat bogs often catch fire and billow noxious fumes across the East European Plain that cling to clothing and sting eyes. That year, several hundred fires burned continuously. The heat was so severe—a fact attributed to climate change—that it resulted in an estimated 56,000 deaths. But there was worse to come.
Resulting crop failures reduced the expected Russian wheat harvest by more than a third. The Russian Federation implemented severe export controls on grain in response, creating a market shortage with effects rippling across countries around the world. Those relying on Russian food exports to feed their population—most notably, the already fragile states of North Africa—were squeezed hardest.
In Tunisia, a twenty-six-year-old food vendor named Mohamed Bouazizi became the literal match that sparked the Jasmine Revolution, a flame that became a conflagration named the Arab Spring. Soaring inflation forced Bouazizi, already destitute before the grain shortage, to contract a loan to acquire the produce he then sold on the street. When a corrupt Sidi Bouzid police officer instead confiscated these wares, Bouazizi saw no other recourse and set himself on fire in protest in front of the town’s police station on December 17, 2010. Bouazizi died of his wounds on January 4, 2011.
Tunisian protesters, primed by disclosures from Wikileaks that revealed high-level government corruption, were outraged by Bouazizi’s story. The resulting mass mobilization overthrew the government in a mere 28 days, and President Zine El Abidine Ben Ali, who had ruled the country for nearly a quarter-century, resigned on January 11, 2011.
Just 36 days later in Egypt, the thirty-year rule of Hosni Mubarak came to an end as its people occupied Tahrir Square. Egypt normally receives more than half of its total grain imports from Russia, but in 2010 were sent 1.2 million tons less, a serious shortage in a country where most people receive one-third of their daily caloric intake from bread. Food prices in Egypt doubled between June 2010 and February 2011.
Within a month of Bouazizi’s death in a Tunisian hospital, protests erupted in at least 14 countries including neighboring Libya—whose dictator Muammar Gaddafi proved more stubborn than Ben Ali, spawning instability that lasts to this day. The violence later spread to Syria, which devolved into a brutal sectarian civil war that to date has resulted in the deaths of over half a million people. This ensuing instability has also led to other problems, including the rise of the Islamic State, increased military tensions between the United States and Russia, and an ever more truculent relationship with Turkey.
The point of recounting the events surrounding the Arab Spring is not that any of them were the cause of the others. Asking why the cascade of popular movements occurred when it did is the wrong question, because it assumes ultimate causation is even knowable in complex systems. This is known as the fallacy of the single cause or causal reductionism. Causal reductionism attempts to draw linear relationships from cause to effect.
But there was no single proximate cause that ignited the wave of protests across the Middle East and North Africa in the spring of 2011. If it were possible to rearrange the players and pieces and replay the scenario over, the results would very likely be different.
Rather, the Arab Spring is a powerful example of an outcome from multiple causal paths, or complex causality. The ingredients for revolution had been in place for decades. Food prices had fluctuated before, and the region’s regimes consistently repressed their citizens. But a combination of factors in late 2010 and early 2011 pushed this escalating tension past the point of criticality, what Malcolm Gladwell famously called the tipping point.
Because complex causality involves a combination of multiple interdependent variables, a change in the value of one can change the effect of another, resulting in different effects on the dependent variable—that is, the result. Events resulting from such complex causal paths are practically impossible to forecast because of the contingency inherent in any number of the many interdependent variables.
Unforeseen contingencies aren’t new, of course. National security has always abounded with problems that are clearer than their solutions, and most solutions also create their own new problems. What is new is the dramatically increased level of global interaction.
Leaders often describe the world as interconnected and complex. The National Defense Strategy focuses on “an increasingly complex global security environment.” Former Secretary of Defense James Mattis has said “the international situation is the most complex and demanding that I have seen in all my years.” Chairman of the Joint Chiefs of Staff General Joseph Dunford has similarly quoted Henry Kissinger, who said that we are living in the “most complex and volatile security environment since World War Two,” and he frequently refers to “today’s extraordinarily dynamic and complex world.”
Unfortunately, like another overused word—strategy—its meaning has been diluted. Complexity is often—incorrectly—thought of as a synonym for complicated. Both are derived from Latin but are subtly distinct. The Latin verb plicare means to fold. Complicare is to fold together. The Proto-Indo-European plek refers to a strand of hair. Over time this morphed into the Latin past participle plexus, which can mean to weave, braided, or entwined. From these derives complexus or braided together. The difference one of layering and braiding. Complication denotes layers, one atop another. Complexity takes this further, merging discrete strands into a single, braided whole. Complexity is the intertwining—or interconnectedness—of elements within a system.
Etymology is nice to know. But what does it mean? More importantly, why does it matter?
Complexity science matters to national security professionals because it is quickly displacing deterministic Newtonian mechanics as the most useful mental model for interpreting our connected world. Like the problems we face today, the study of complexity is cross-disciplinary and holistic, incorporating elements from physics, biology, sociology, and information sciences to approximate a crude look at the whole.
When a problem is complex, it is intertwined with other problems, and taking an action to remedy one may have unpredictable effects on others it influences. An apt metaphor for complexity then might be uncertainty, and that makes it important to the realm of national security. But complexity is much more than a metaphor; it is the fundamental phenomenon of our world, one that we are just beginning to understand.
Complexity is hard to understand; its technical consideration involves a lot of math. Like quantum mechanics, it is often counterintuitive, because our brains are not wired for it. Where complicated systems are straightforward and observable, complex systems often interact in unobservable ways that lead to unexpected results. For national security practitioners who aren’t mathematicians, there are four building block concepts to grasp complexity: systems, agents, interdependence, and feedback. Together they create conditions in which, a fifth concept, emergence occurs.
A system is a collection of various actors that form a network subject to rules, but is not beholden to any central authority. Systems can be open—liable to be influenced by actors outside the system—or closed. Complex systems are almost always open. In the example above, the system of North Africa was open to influence from faraway Russia and entities like Wikileaks.
Agents are the irreducible actors within a system. Agents can be almost anything: cells, insects, people, terrorist organizations, or states. Systems are composed of agents, and agents act within a given system. In Tunisia, from the opening vignette, a much-simplified list of agents would include the protestors, the government, and external actors like Wikileaks or other media outlets. The number and diversity of agents is a measure of a given system’s multiplicity.
Agents tend to be self-organizing—that is, over time, local pockets of order emerge within the system between individual agents, and even hierarchies can develop as agents interact with one another. The self-organization of agents often follow power laws because of a concept from network science called preferential attachment—that is, agents with more interactions are likelier to attract still more agents with which to interact. This effect is demonstrated across a variety of complex systems: millions of army ants work together to accomplish diverse tasks; individual cells organize themselves into organs like hearts and lungs, popular websites are placed higher on search engine results, the rich get richer. Numerous individual agents in Tunis and across North Africa independently shared social media posts of outrage towards their regimes, amplifying that message and spreading more outrage. No one had to tell them to; it was self-organized.
Interdependence is the degree of interaction between actors within the system, which is closely related to the composition and scale of the networks they create. This is why complexity science deals closely with network dynamics, since the world is increasingly interconnected through vast, overlapping networks. The more connections made, the more interdependent a system becomes. For national security purposes, consider every new internet user, every new connected device, every new gas pipeline, and every new financial transfer as increasing global interdependence. In the example of the Arab Spring, countries like Tunisia were dependent upon normally reliable food imports from countries like Russia. The Russian wheat harvest was in turn dependent upon favorable weather conditions, and so on.
Think of feedback as an exchange between agents. Feedback is something new that prompts agents to take action or change their behavior. Just as ants respond to stimuli on the ground and release pheromones to signal other ants to change their order of march, humans respond to a video of a brutal act of violence on YouTube, inspiring some to share or mimic it and other to be repulsed and condemn it. The Tunisian revolt was widely-touted as the Facebook Revolution at the time, because of the unprecedented ability of the protestors to share information (feedback) with one another on the social media platform.
Feedback is more familiar to military theorists than they realize. Consider Clausewitz’s concept of friction. The Prussian taught “everything in war is very simple, but the simplest thing is difficult. The difficulties accumulate and, in the end, produce a kind of friction that is inconceivable unless one has experienced war.” Clausewitz went to great lengths to employ the scientific language of his day—friction, force, gravity. Feedback, like Clausewitzian friction, accumulates.
The concept of feedback was popularized by meteorologist and mathematician Edward Lorenz’s discovery of the butterfly effect in 1962. While working as a meteorologist at Massachusetts Institute of Technology, Lorenz ran equations on his computer to determine patterns in weather formation. Running a particular equation multiple times, he expected to replicate the same results and was shocked to find the computer consistently generated wildly divergent predictions. He stumbled quite by accident on an observation made by Henri Poincare, who might be considered the father of chaos theory, nearly a hundred years earlier. Poincare called it “sensitive dependence upon initial conditions.”
Infinitesimally small differences in the measurements were causing profound differences in Lorenz’s forecast. Standard mechanics wouldn’t expect differences this tiny to make a difference, but here was evidence they did. Lorenz demonstrated that as weather develops, tiny interactions feedback upon themselves, influencing the emerging pattern. He concluded that even a theoretically perfect sensor will miss fluctuations which calculations cannot account. Before long, minuscule errors compound, making even marginally accurate prediction impossible.
National security affairs are easily as complex as any weather pattern. People, the agents who comprise nations, are inherently unpredictable, because feedback takes the form of information, which is often intangible and intrinsic—but its effects nonetheless manifest in myriad ways. The more information—that is, feedback—flowing through a system, the likelier it is a critical state will be reached, and emergent behavior will occur. So while we might be able to forecast the immediate future with some success, what look like clear skies can turn dark rapidly, and sometimes storms emerge with unexpected force and intensity, like during the Arab Spring.
Emergence is the spontaneous result of the interaction of simple bits through feedback. Examples of emergence include the formation of fractal patterns in snowflakes, the towering dirt cathedrals built by termite colonies, the collaboration of ants forming living bridges to cross chasms, and the spark of human consciousness that emerges from the billions of interacting neurons in our brains. In Tunisia, the immolation of Mohamed Bouazizi was where feedback within the system reached a critical state, sparking the emergent behaviour of a self-organizing revolution which took down a dictatorial regime.
National security professionals don’t need to completely understand how complexity works. But they can better understand how systems, agents, interdependence, and feedback coalesce in emergent outcomes when analyzing foreign affairs. Even a cursory familiarity with these core dynamics should give analysts and policymakers pause as they consider the unintended second- and third-order effects from their actions in a world woven together.
The standard model of cause and effect bequeathed to us by Copernicus, Newton, and Laplace, with simple laws of motion that govern everything, in which a system is no more than the sum of its parts, is outmoded at the strategic level of analysis an era of unprecedented multiplicity and ubiquitous connectivity. While the standard model is suitable for simple systems, and thus still has some utility, there are very few simple systems left today.
Laplace’s clockwork universe, in which forecasting future outcomes was possible given perfect knowledge and powerful enough measuring tools, is now widely recognized as fantasy. In the real world, human agency and a seemingly unlimited capacity for innovation creates new blossoms of adjacent possibilities from which emerge still others, perhaps without limit.
The digital revolution sparked a historic transfer of power from once-dominant institutions to new actors and models of organization. People everywhere, from Silicon Valley to the Ferghana Valley, are more mobile and more empowered than ever before because they are more connected. Now, every problem is becoming more intertwined with every other because the principal condition of contemporary global competition is that very connectivity.
Familiar boundaries are eroding and systems that were once seemingly separate are now entangled. States, which could once be conceptualized as bounded geographic entities, are now more like vast and growing networks that exist above, below, and through imaginary lines on a map. In an interconnected world, a preference to demarcate issues by clear geographic or functional boundaries, or by placing them into topical bins, often hinders rather than help. Old concepts, such as the idea of merely regional conflicts, are becoming outdated as even local wars can now have global effects.
The interdependence of security affairs undermines the strengths of traditional analysis which breaks apart problems to examine their pieces. Doing so, however, makes it difficult to put them back together to see the big picture. In increasingly complex systems, the whole often equals much more than the sum of individual parts, and thus, we are surprised.
It is not that the older ideas aren’t helpful; they are simply insufficient. Security communities need thinkers who are comfortable in both complicated and complex environments, who can study the trees but still grasp the shape of the forest.
Zachery Tyson Brown is an intelligence consultant for the Department of Defense. The views expressed in this article do not reflect the position of the Defense Intelligence Agency, Department of Defense, or the U.S. Government.
This article appeared originally at Strategy Bridge.
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