The Edge of Chaos: Using Systems Theory to Rock The World

These days, it may feel like we’re living on the edge of chaos. That’s not exactly breaking news. But what may surprise you is, we’re never not on the edge of chaos! Being on this edge is the default state of all complex systems. Complex systems, those in which the whole is greater than all of its many parts, are everywhere- inside of us and all around us. Everything from the simplest life forms to vast ecosystems, from village markets to entire civilizations, all are examples of complex systems. Incredibly, every complex system has arisen from chaotic upheavals of previous systems. Every fresh adaptation, every breakthrough, every revolution and burst of evolution is a gift from chaos. And you, gentle reader, are on the front lines where all the magic of chaos unfolds.

Why Do Complex Systems Operate on The Edge?

The scientific term for the edge of chaos is “far from equilibrium.” In this state, a system isn’t rigidly ordered and stabilized. But neither is it dissolving completely into disorder and decay. It’s operating somewhere in between the two extremes, where tiny shifts in the behavior of elements within the system can have enormous consequences.

Because complex systems are not rigidly stable, they’re fluid and dynamic, in a constant state of flux. This makes them nimble, responsive and adaptive. Newton’s good old Second Law of Thermodynamics says a closed system, over time, descends into a state of ever-increasing disorder and entropy. The operative word here is “closed.” Complex systems have dodged The Second Law by staying wide open.

Systems strive to maintain equilibrium and stability by resisting and exporting chaos or entropy. Complex systems do this by creating barriers between themselves and mayhem. Whether it’s cell walls, international borders, rules of law, firewalls or personal boundaries, barriers to chaos are essential to maintaining the structure and functionality of a system.

For example, cell walls only allow in molecules with very precise configurations which act as keys, if you will, allowing them entry. Any other molecules or organisms will be blocked and sent on their way. Inside the cell, waste is a natural byproduct of metabolism. But waste is nothing but decay and chaos! It’s escorted out, thank you very much, and one less bit of chaos is around to cause trouble!

As long as barriers to chaos are permeable- and they have to be in order to be “open systems”- chaos plays at the edges, disrupting, disorganizing, and wrecking havoc. Whether its viruses or drug smugglers; noisy neighbors or computer hackers, carriers of disorder and chaos lurk everywhere.

But permeable barriers aren’t the only means by which chaos can pull a complex system far from equilibrium. Individual elements within a system are instigators of disorder in their own right. And they can go rogue without any warning, as we’ll see.

Interactions Between Autonomous Agents: The Emergence of Complex Systems

Complex systems, by definition, are made up of numerous individual elements, autonomous agents. Autonomous agents act in their own self interest making the system quite unpredictable and extraordinarily fluid! The agents themselves create the system to which they belong and have more influence on the whole than you might imagine.

The structure of a complex system is created by the patterns of interactions between autonomous agents.

Let that sink in a moment.

The interactions between individual agents form the actual structure of a complex system. Those interactions create patterns of greater complexity than exist within the agents themselves.

Exquisite patterns of complexity formed by these interactions abound in nature. For example, organelles are quite advanced biological systems, and when working in concert, they produce cells, which are of a much higher order of complexity. And though cells are amazing living components, when synchronized to form biological systems, individual cells can’t compare to the complexity of, say, an entire plant or animal.

How can patterns of interaction form structure? It’s possible because every individual agent within a complex system is connected to, and dependent on, every other agent in the system, if only indirectly. The way this interconnection and interdependence expresses itself become the pattern of the structure.

This interconnection and interdependence is happening inside you at this very moment with every breath you take!

Every cell in your body, those tiny autonomous agents of the system that is you, requires oxygen to function and is completely dependent on other cells to receive it. Every cell in your body is dependent on the alveoli cells in your lungs to absorb oxygen from the air. Every cell is dependent on blood cells to deliver oxygen to them. Every cell is dependent on cardiac cells to fire with perfect synchronization to send blood cells to their vicinity. And that’s just the interdependence for the circulation of oxygen! All cells need nutrients from the GI tract. Cells require regulation by myriad chemicals of the endocrine system. And the entire shebang is coordinated into a seamless whole by the cells of the nervous system. Our bodies are examples of a staggering degree of interdependence and complexity!

The more interconnectivity between agents, the greater the complexity of a system.

The more interdependence of the agents, the greater the complexity of a system.

And, as you may have inferred, the higher the number and the broader the diversification of agents, the greater the complexity of a system.

Here’s the kicker: the farther from equilibrium a system is, that is, the closer to chaos it operates, the greater its complexity also! It’s more complex because it’s impossible to precisely predict what any one agent will do, or exactly how other agents will then respond.

That’s not to say autonomous agents behave randomly. They don’t. They weigh possible actions in terms of the cost of some behaviors and the benefit of others. The decision is the agent’s alone and there can be a wide spectrum of possible responses available. In fact, the broader the range of possible behaviors, the greater the flexibility, creativity, adaptation, evolution, and even revolution, possible within a system, as we’ll soon see.

And all breakthroughs start with individual agents and their interactions within their immediate vicinity.

Autonomous Agents and Feedback Loops: Instruments of Stability and Chaos

On a winter morning in 2010, a poor street vendor in Tunis set himself on fire in an act of despair and protest. It was a lone deed, which no one could have foreseen would spark revolutions across North Africa and the Middle East. The waves of unrest that resulted from this lone act came to be know as “The Arab Spring.” It lead to the civil war in Syria, 2400 miles away, that still rages today.

How did this single act lead to widespread consequences that never could have been imagined, much less predicted? The answer is it  triggered feedback loops, the mechanism by which agents in a complex system communicate and interact.

A feedback loop occurs when an individual agent is perturbed by something in its environment, a tiny bit of personal chaos, if you will. These environmental disturbances are called, fittingly, perturbations. An autonomous agent responds to the perturbation by doing something to relieve its own disequilibrium. That response then impacts the environment, which now responds in a slightly altered way, and so on, in a loop feeding information back and forth from agent to environment.

Feedback loops come in two varieties: negative and positive. The designation of negative or positive has nothing to do with a judgement on the quality of loops, but rather the direction agents move in response to a perturbation. Negative feedback loops cause an agent to move away from a perturbation. Positive feedback loops bring an agent to it. Regardless of how an individual agent reacts, that response impacts the entire system, again, if only indirectly.

Most of us are familiar with the feedback loops of traffic jams and our efforts to avoid them. When we’re zipping along the freeway and suddenly see nothing but red brake lights for miles ahead, we’re receiving information from our environment that our travels are about to come to a halt. A perturbation has occurred. Our equilibrium is disturbed. As autonomous agents, we use our wits, or our traffic app, to find an alternative route. We take the next exit which sends us moving along on a different path. We have responded to the traffic jam by moving away from it and taking a new route.

What we seldom think about is once we exit the freeway, there is one less car in traffic. Our response to the traffic jam has lessened its congestion, if only by one vehicle. Chances are high we’re not the only one who got out of traffic and took another route. If enough vehicles get off the freeway, the flow of traffic will stabilize and eventually return to a normal, orderly flow.

So negative feedback loops tend to stabilize and bring more order to a complex system.

If negative feedback loops create greater equilibrium, do positive feedback loops tend to destabilize a system? Oh, yes! Big time! Positive feedback loops have an attractor agent or a strongly attractive quality. They can spread quickly and disrupt the stability of systems in the most unpredictable ways. The poor street vendor in Tunis who unwittingly launched “The Arab Spring” is a perfect example.

Mohmad Bouazizi couldn’t find work, nor could he afford a permit to be a street vendor. Because he illegally sold his wares, he was constantly hauled off to jail and charged fines he couldn’t possibly pay. The perturbation Bouazizi experienced was so intense, his despair so great, he ended his own life in protest.

Bouazizi’s death was a purely local event, noticed only by his family, friends, and neighbors. But his small community was strongly moved by his plight. They, too, had lived with economic and social injustice- enormous perturbations in their environment. His local community took to the streets in solidarity with Bouazizi, taking up the protest he had begun.

Soon the protests spread across the city of Tunis, then all over Tunisia, then blazing through Algeria, Libya and Egypt. The speed with which revolt spread reflects the degree of perturbation of social and economic unrest simmering just under the surface.

Bouazizi’s action became the attractor in a positive feedback loop. It drew people in. Individual agents weighed the cost of joining the protest- possibly being arrested and jailed- against the benefit- releasing years of pent up frustration and rage, and the desire to change the system.

Now, if just a single person protests, she takes a great risk that she’ll be arrested. But when more people synchronize their actions with that of the attractor agent, two things happen. First, the more people who protest, the less likely any one person will go to jail. The risk of protesting becomes less as greater numbers of agents participate. Numbers are a powerful buffer from harm.

Secondly, there is a local synchronization of the feedback loop. That is, agents drawn toward the attractor agent now behave in a similar manner. The more agents who participate, the greater the likelihood nearby agents synchronize their responses with them. This is the phenomenon behind herds of cattle stampeding, investors fleeing a stock market in panic, and mobs suddenly becoming violent when the individuals would normally never engage in a fight. It is a snowball effect. With each roll, the numbers of synchronized agents grows.

When the number of synchronized individual agents within a system reaches a critical mass, it has reached a transition phase known by the scientific term of “regime change.”

Regime change for a heated molecule of water is as simple as changing from liquid to gas. For complex systems, what a regime change will look like is nearly impossible to predict. But it’ll be the result of different kinds of interactions between agents, starting in their own vicinity.

Self-Organization: Autonomous Agents Can’t Not Get Themselves Together

Regardless of the mayhem that ensues when a system enters a transition phase or regime change, it cannot and will not last indefinitely. This is because the agents of the old system are themselves complex systems. Complex systems can’t not be somewhat organized! How the regime change proceeds will take one of two routes, though the details of either can’t be predicted.

The first possible route is the vestiges of the former system will devolve and reconstitute itself into a lower level of complexity. The number and diversity of the elements may decrease as the system shrinks and exports agents of chaos to restore order. The interconnection and interdependence of the agents may be reduced when communication between them is lessened. The autonomy of the agents may be reduced. The outcome is one of regression but not of dissolution and chaos. Order will resume, one way or another.

The second possible route is, as the system collapses, an entirely new paradigm of greater complexity will emerge. The emerging system will be one inconceivable prior to the disruption.

For example, illiterate peasants in feudal systems could not have conceived of liberal democracies prior to the revolutions of the 18th century. Or, sixty-six million years ago, tiny, furry, mice-like critters evolving into humans that would come to dominate the globe could not have been anticipated when enormous dinosaurs ruled the world. In both these instances, enormous perturbations occurred in the environment first, creating the fall of one regime and the rise of a new, unimagined, more complex replacement.

What is required for a phase transition to begin and a new, more complex system to arise is sufficient chaos! Chaos is needed to destabilize the old patterns of interactions between agents, enabling them to explore other possibilities.

Chaos is also required to generate randomness, which increases the range of possibilities to be explored. That exploration will bring together new ways of interacting never before imagined.

Interactions that are adaptive and beneficial to individual agents will begin to synchronize locally. These interactions don’t have to be perfect to succeed; only better than the ones before. As local agents begin to synchronize their interactions, those synchronizations will spread around the edges, creating a new network, a new structure, a paradigm of greater complexity, unimaginable prior to its inception. When new responses arise and synchronize, unimaginable reconfigurations develop. Breakthroughs happen. Evolution occurs.

Go Rock Your World!

All advances in complex systems happen first between individual agents in close proximity- agents like you and me. In conversation and communion with our friends, families and neighbors, we change the atmosphere of our world every time we question, explore and make small changes in our lives. Every shift we make alters slightly the currents of feedback loops in our environment.

We cannot know how or to what degree these ripples will effect change as they silently flutter through the complex networks of our world. Nor can we intentionally shape the systems to come because what emerges next cannot yet be imagined.

But we needn’t fear or turn away from this great chaos we’re experiencing, though by its very nature it’s unsettling and perturbing! We can, instead, embrace the opportunity chaos affords us to explore new ideas, try something completely different, and allow our own curiosity and wisdom to rock our world.




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