Complexity (Becoming, Part 4)

In the summer of 2009, my wife Sadie was accepted into the prestigious Hudson River Fellowship, a group of classical artists who meet annually to paint the landscapes of the Hudson River Valley in upstate New York, in the traditions of the original Hudson River School painters who worked there nearly a century and a half ago. This was not an opportunity to be passed up, so of course she happily made plans to travel to the East Coast in July and participate in what would be a month-long landscape painting extravaganza, alongside her new artist Fellows.

The question was, what exactly was I going to do with myself for a month without Sadie? I sure wasn't going to stay home alone in San Francisco during what is regularly the most dead month of the visual effects project cycle. Since spouses of the HRF artists were not invited to share their living quarters during their studies, I was forced to do the next best thing- to hang out with Mom and Dad at their house, in my home town of Blue Bell, Pennsylvania, a four hour drive from Hunter, New York where Sadie would be staying, driving up to visit her whenever possible.

While I missed Sadie enormously, I actually had a pretty great time in Pennsylvania. It was the longest I'd spent away from Sadie, but it was also the longest stretch I'd spent with my parents since I went to college nearly twelve years earlier. During the day I digitized family videos and met up with old friends. At night my dad and I took to watching episodes from the first season of the original Star Trek on Blu Ray. I spent several of my weekends up in New York City, hanging out with friends and drinking far too much. I also took full advantage of the top-notch East Coast cuisine I'd been missing for so many years, including Italian hoagies, cheesesteaks, pastrami sandwiches, meatball subs, scrapple, etc. I think I gained about 10 pounds.

However, among all of the socializing and gorging on fabulous foods, in the background I grasped desperately for a new path in my academic studies. At that point I was more or less completely lost. I was still recoiling from my frustrating encounters with both Quantum Mechanics and the Hard Problem of Consciousness within Philosophy of Mind. Neither had managed to satisfactorily describe my harmonic city encounters that had started over a year and a half before. So I figured the best approach from here was to cast my net wide, branching out and studying a variety of subjects simultaneously. This multi-disciplined mindset provoked the broad consumption of courses from The Teaching Company, covering the works of existentialist philosopher Friedrich Nietzsche, the essays of Ralph Waldo Emerson and others representing the American Transcendentalist movement, a pan-historical perspective on the various types of political leadership called Power Over People, and finally a small set of lectures I bought on a whim called Understanding Complexity.

Out of the myriad of subjects I was studying, I didn't think for a second that it would be complexity that might tie into the grand scheme of things. I had meant for the course to be a fun little side-study that I snacked on while in bed every night before I went to sleep, while during the day I continued my real research within realms located squarely outside of the sciences. At only twelve lectures, each clocking in at a mere half hour in length, the series seemed less than daunting, as it was much smaller than any of the previous TTC classes I had taken. I was surprised to find not only my expectations exceeded, but also my ass thoroughly kicked. Short as they were, the complexity lectures packed the intellectual density of a granite mountain. After completing the course and repeating many of the lectures for maximum absorption, I found myself blazing a decidedly different path back into science that was completely exhilarating, infusing my efforts with a new sense of purpose and vigor.

So what exactly is complexity, and why should it matter to us in our day to day lives? To begin with, complex systems are much more common than you might imagine. The word "complexity" in the context of scientific analysis refers to the intricate configuration of different parts that serve as a functional layer within a given system. At first glance, this might seem like the most vanilla definition possible, but it makes a few very important points.

First, it states that complexity is defined by configurations of parts within a living system, rather than the nature of the parts themselves. So instead of zooming down to the microscopic level to view specific actions of component parts within a system, studies of complexity focus on the the interactions of component parts and the macroscopic properties that result. Such properties are often referred to as "emergent" phenomena, which I discussed in detail in the previous essay while describing consciousness as an emergent property of higher functions within the human brain. Therefore complexity studies of consciousness are not interested in the functions of individual neurons within the brain per-se, but the properties that arise wholesale as a result of the interactions between the neurons.

Second, the above definition also identifies complexity in terms of "layers", which is crucial to the understanding of how larger complex systems fit together. I also touched on this notion of layered systems in the previous essay when I discussed "emergent layers" within a system, and how a complex system (like a tree) could be entirely described by the functions of each of its separate layers. This is exactly the kind of thing that complexity researchers love to sink their teeth into. They endeavor to create functional computer models that simulate complex behaviors using simple mathematical rules, giving them insight into how a system's component parts interact with one another and how these interactions ultimately serve to build superseding layers of complexity. Researchers can then study the various layers hierarchically, building a more solid understanding of how the system operates as a whole.

Complexity researchers are also interested in the commonalities between vast arrays of living systems. These can range from colonies of bacteria to entire ecosystems- from the cellular functions of the human immune system to the inner workings of much larger social systems, including economies, international political systems and the internet. As researchers discover more and more underlying principles and mathematical algorithms that are held in common between these various systems, a entire new science of complexity starts to emerge. As it stands, the research of complex systems is a formidable movement that only continues to grow in relevance.

So what is it exactly that makes a system complex? Possibly the most important point to understand about complex systems is that by nature, they build themselves automatically from the bottom-up. By this I mean that each component part (or "agent") within a complex system carries within itself a set of instructions that gives it the ability to collaborate with others like itself to create discernible, entirely new structures. These novel configurations cannot be traced to the actions of a single agent; it is only through the flurry of interaction among many different agents that larger patterns emerge and a purposeful, functioning system is created.

The opposing view, that systems are "top-down", sees a system organized with a single authority at the center, which hands instructions directly down to each and every agent of the system. This basically means there is one master entity that runs the whole show, and that lesser agents of the system act as slaves to its every whim. While a top-down view of systems has been common within classical schools of thought for the last several hundred years, whether it's science, politics, or economics, this model doesn't accurately describe any system in nature.

For example, the queen in a bee colony, unlike her nominal counterparts in traditional human aristocracies, does not dictate how worker bees should interact with one other, or how they should react to threats and conditions outside of the hive. The queen's sole purpose is to reproduce en masse, providing the colony with its next generations of bees. So instead of awaiting instructions from the queen bee, worker bees communicate with one another using pheromones and body language. Through these simple chemical and bodily-linguistic interactions, the operations of the hive emerge naturally.

Say an outside force, such as a bear or a skunk, is threatening a hive. Only a few bees might initially notice the attacker and take flight, but this small action might be just enough to catalyze a formidable response. Other workers that see and receive pheromone signals from their local constituents will join in the effort to defend the hive. As more workers take flight, an ever-increasing number of their counterparts also begin to mobilize, creating a cascading response that quickly forms a swarm- a wholly new complex system, that has a much better chance of taking on the attacker than any single bee ever could. The swarm phenomenon is the result of what's called a self-reinforced positive feedback loop.

Feedback in a complex system works very similarly to audio feedback, which might remind you of a botched high school theater performance, where an actor carried his microphone a bit too close to the auditorium speakers. In this situation, the amplified voice of the performer was continually looped from the speakers back into the microphone, making the sound louder with each pass through the system and turning a single word of dialogue into giant roar-causing audience members to clap their hands over their ears in agony.

In the case of the beehive, feedback takes the form of reinforced body language and pheromone signals (as opposed to sound waves) which serve to recruit more and more bees, quickly transforming a hive's nectar-gathering operations into a furious swarm. In both the theater scenario and the beehive, a small signal becomes amplified, pushing outward and then looping back in upon itself. The signal is reinforced again and again until it reaches a massive critical state in which it is capable of causing a large shift within the system.

Another great example of a system that spontaneously emerges due to feedback can be found in sports stadiums around the world. This is the phenomenon known as The Wave. The Wave is formed when spectators spontaneously stand up in succession, section by section, forming a wave-like motion of synchronized crowd movement that ripples in a circular pattern around the the stadium. As it continues, it picks up more and more participants until it reaches a critical mass, where nearly the entire audience is involved in the effort. While they are formed for completely different purposes (entertainment vs survival), the driving principles behind both The Wave and the swarm of bees are identical. Participants in The Wave reinforce the social behavior of their fellow spectators by mimicking their movements, just as bees reinforce each others' actions in a swarm.

Feedback and cascading behavior in the case of The Wave and swarms of bees are generally favorable outcomes of a system (with the exception of some countries where The Wave is illegal). In other systems however, positive feedback loops are not quite so favorable. The word "positive" when referring to feedback within complex systems simply indicates cumulative, compounding actions. It is not necessarily expressive of an amicable outcome for any parties observing or involved. In fact, feedback responses can be downright detrimental to the system.

For instance, in economics, a stock market is created by corporations and individuals who invest in shares of various different companies. The investing entities, through incredibly simple transactions, have the ability to create and sustain the operations of the market. Like the bees in our swarm or spectators participating in The Wave, investors act as the agents within this particular type of economic system. As long as the agents continue to do their jobs (buy and sell stocks in this case) the system continues to propagate.

However, if large factions of investors change their behavior due to shaky external economic conditions and sell all of their holdings in the market, a feedback loop is thus created which could - if conditions were right - trigger a panicked cascade of sell-offs by thousands of additional investors, causing the entire market value to plunge. This is precisely the behavior that ripped through world financial markets in late 2008 and early 2009. It was certainly not a favorable outcome for most of us who were invested in the market, but it was nevertheless the inevitable result of a devastated real estate market and frivolous practices by lending institutions, combined with the natural sensitivity that comes along with every complex economic system.

This is the two-sided coin of complex systems. While a system can yield serious benefits to agents inside and outside of itself, it also has built into it the seeds of its own destruction. It is for this same reason that the cells within the human immune system can quickly change from protecting the body from pathogens, to attacking healthy cells, as is the case with autoimmune diseases like diabetes and multiple sclerosis. It is also why human beings can nationalize and choose to go to war against other nations, while under different circumstances they can choose to defect and revolt against their own governments. The stock market could just as easily have gone the other way and rallied in early 2009, were economic news astoundingly good. This is why we invest in the market at all- the possibility to grow our capital based on the success of the world economic system as a whole. It is however, always a gamble. The success or failure of a system is always subject to external conditions that can turn on a dime.

The general volatility of economic systems is an excellent illustration of the implicit sensitivity and dynamic behavior inherent within all complex systems. The tendency of a system to shift due to feedback loops and cascades, whether beneficial or detrimental to the system, is only possible with a substantial amount of flexibility built into the system, allowing it to adapt to large scale changes. Researchers describe this necessary state of complex systems as the edge of chaos. It is the state where a system is ordered enough to survive a fair amount of damage without collapsing, yet is fluid enough to adapt itself to shifting circumstances.

rival queen beesIn fact, the adaptive, decentralized nature of bottom-up complex systems is so robust that it can tolerate the removal of many agents without failing, even if that agent is one of the most critical players in the system. Let's look again into our beehive. If the queen bee is removed from the hive or is killed, worker bees immediately prepare several chambers already containing new larvae with royal jelly, effectively transforming the newborns into queens. When the multiple queens emerge from their pupal states, they fight each other to the death. The sole-surviving queen becomes the new reproductive center of the hive.

Similarly, human governments (while largely man-made structures) also have complex adaptive components that are set up in such a way that the operations of a given state can continue, even if the most powerful positions within the government are suddenly vacated. In the United States, if the president were to resign or be assassinated, there is a long line of successors set up to retain continuity of government. While shocks would inevitably ripple through the government's constituency - a socially disruptive response to such a drastic change in the nation's political power structure - the basic functions of the government would remain intact. For free democratic nations like the US, which are governed entirely by its own people, the government as a whole could technically be re-elected and re-formed overnight. The only thing that could effectively cause a democratic government to collapse would have to be a large scale popular revolution, a coup d'etat or a crushing military invasion by an external force.

And then there is the internet- a massive global network of computers and users that runs 24 hours a day, 7 days a week. If one or even several of these systems, whether home computers, mobile phones, or massive commercial servers were to go offline, chances are that barely anyone would even notice. Each machine on the net is a separate, independent entity, each generally drawing from a separate power source and many times participating from a vastly different geographical location. Only after the loss of a major web-based service or telecommunications network would users really start to notice. Because of this fact, the internet remains one of the most robust and powerful complex adaptive systems of its size and scale on the planet. It is highly decentralized, dynamic, densely interconnected, adaptable to major failures and most importantly of all, it is built on the backs of a multitude of some of the most able complex systems in existence: human beings. The internet is an immaculate expression of human cooperation and solidarity.

Human beings and most other purely natural systems arose over millions of years out of the processes of evolution and natural selection. Evolution is perhaps the clearest example of how natural systems emerge from the bottom up, and how they are able to grow in complexity over time. It is partly the layered nature of complex organisms that allows them to survive and persist through difficult times. However, the organisms who are able to persist the longest are not necessarily the most rigidly built, but are rather the most versatile. Our versatility combined with our ability to participate in and influence other complex systems leaves us with enough flexibility to constantly adapt and to deal with the inevitable change and upset that random natural events constantly provide for us. Thus the innate complexity of our organic human structure - courtesy of evolution and natural selection - is in essence, who we are. It's the reason we are here at all.

It's difficult to view the immense structural complexity of the human organism and not feel awed at its magnificence. We were all once just a few molecules, that through simple interactions managed to coordinate and gradually build ourselves into incredibly complex, self-sustained organic systems. Our bodily systems are a marvel of the complexifying processes of evolution, woven intricately together and acting with enough synchrony to keep our lungs breathing, our blood pumping, our brains thinking and our hands creating.

Yet at the same time we are a complete mess. We fight with one another, we steal, we cheat, we disrupt everything around us. In fact, we're probably the most destructive species to ever walk the face of the Earth. But this all comes with the territory. We are each our own complex adaptive system, and we walk through life on a thin line between order and chaos, constantly brushing up against and trudging directly through other complex systems. If we take any action on the planet at all, we can't help but disrupt it. And at any moment, any number of these other systems could shift drastically, leading to great fortune or an even greater catastrophe for us. Such are the complex lives we bear.

I think what struck me the most during my foray into complexity was the exposure to the idea that we live in a world of sheer dynamism- one where configurations and circumstances, as stable as they may seem, are shifting constantly. When I started my Becoming journey back in January of 2008, many monumental transformations were taking place. There was a large shift in political power occurring within the US government, fuel prices were skyrocketing due to feared supply shortages from the rapid growth of newly industrializing nations, and a massive economic crisis was just getting revved up.

So you might imagine why the rationalist philosophical ideal of a fundamental harmony within a mathematically discernible, stable universe seemed completely absurd, in light of the unpredictable morass I saw rife throughout the world around me. It wasn't until I'd studied complexity that I could effectively banish any remaining hints of the mythical notion of some kind of innate stability and equilibrium within nature from my explorations. I never expected that I could actually be comfortable, let alone be at peace with a world that was fundamentally in flux. This was most likely the reason why rationalism and scientific exactitude was so appealing to me at the beginning of my journey. But with a little help from quantum physics, philosophy of mind and complexity, I could now view the world from a wholly different and much more realistic platform.

So where to go from here? First and foremost I needed to address the implications of a reality that is ceaselessly shifting and fundamentally amorphous. Unfortunately the Ancient Greeks didn't have a whole lot to say on this type of natural configuration, save a few surviving Fragments from my old pal Heraclitus, who was abruptly sidelined early on when I decided to follow Pythagoras and the long procession of rationalists that succeeded him instead. While Heraclitus's works were vindicated by these new discoveries of mine, there wasn't enough depth within The Fragments to form any kind of coherent world view- that is, without supplementing them with a serious amount of speculation.

Luckily there was another entirely different group of philosophers who spoke authoritatively on the subject of a constantly changing, unpredictable, even paradoxical reality, just around the same time as Heraclitus, whose works - quite unlike Heraclitus's - were celebrated and revered in their time, and remain well-preserved to this day. But in order to explore such philosophies, we must leave the Greeks behind and look East- to the thinkers of Ancient China.

Bibliography:

Hofstadter, Douglas R. I Am A Strange Loop Basic Books, 2008

Miller, John H. and Scott E. Page Complex Adaptive Systems: An Introduction to Computational Models of Social Life Princeton University Press, 2007

Mitchell, Melanie Complexity: A Guided Tour Oxford University Press, 2009

Simon, Herbert A "The Architecture of Complexity" from Proceedings of the American Philosophical Society, Vol 106, No. 6. (Dec 12, 1962) p. 467-482

Waldrop, M. Mitchell Complexity: The Emerging Science at the Edge of Order and Chaos Simon and Shuster, 1992