Complex Systems: A Motorcycle Tour Through the Museum

This is the first of a series of posts adapted from an article originally published on Kurt Cagle's XML Today blog.

In the articles I write, some key piece of reasoning usually depends on the properties and behavior of Complex Systems.

Partly it’s me (I find Systems Theory increasingly indispensable as an investigative, analytic, and descriptive model); but partly it’s that we live in a changing world. Systems are looming larger in human affairs.

In fact, it all seems to be coming together in a spectacular crunch, and that’s not coincidental: this global trend is driven by the increasing interconnection and scale of human activity. Systems behavior can, and does, occur in very simple contexts, but its occurrence increases nonlinearly as things get more numerous and interconnected. Bottom line: It’s getting harder and harder to ignore, or defer responding to, Systems-driven global phenomena that have real near-term consequences.

Which sucks, all things considered, because we’re just no damn good at Systems. Thinking in systems is not something that our species does well. 

More than that, though, our contemporary culture is especially bad at it. Really, and c’mon: we’ve mostly been taught to think in Systems as little as possible. It's understandable: analytical, reductionist, linear thinking was much more profitable and effective during most of the thousands of years in which our primary intellectual traditions developed.

Problem is, we've changed the world. Now we really need to get a lot better at Systems thinking, fairly quickly—a hard thing to ask of people who’ve been trained against it. But if we can’t manage it, we’re facing worse times.

A Physics professor of mine once used the phrase “motorcycle tour through a museum” as a rueful lament about how small a glimpse, of how vast a subject, undergraduate Physics courses could actually provide. I’ve stolen this from him, and I hope he’d approve.

In that spirit, here’s a basic overview of the general nature, shape, and implications of Complex Systems. Don’t expect theoretical precision. I’ll just try to make things conceptually accessible at a pretty high level.

Now you probably know enough to decide whether to read further. If you do, grab your boots, jacket, do-rag, assless chaps, mirrorshades, whatever you think you need for the road; and let’s roll.

A note on terminology

The words “Complex” and “System” have specific technical meanings in the field of Systems Theory. They also, however, have different meanings in everyday speech. Complex and complicated mean the same thing in casual conversation; the Dewey Decimal System is certainly “systematic” in the way most people understand the word, but it’s got nothing to do with Systems Theory. 

In order to emphasize the distinction, I am capitalizing the formal terms and any derived forms (e.g. “Complexity”) in this series of articles.

What's Complexity, eh Precious?

Any discussion of Complexity runs into the fish-can't-describe-water problem. Complexity is such a pervasive part of, well, everything, that it's hard to stand aside and talk about it.

We ourselves are, as individuals, biologically Complex organisms and psychologically Complex personalities. We work for Complex organizations, exchange information across Complex networks, buy and sell goods and services through Complex markets within Complex economies. We live in highly Complex societies governed by Complex political systems and sustained by Complex infrastructures. Our global civilization itself is Complex, immensely so.

That’s only the beginning, though. We are only a small fraction of the living organisms on the planet, and the ecologies of mutual interdependence in which those organisms live are always Complex—orders of magnitude more so than any of those human artifacts.

The planet itself is Complex in its responses to energy throughput, most especially its meteorological and oceanic systems. (It’s awfully hard to have anything that flows, be it a material gas or liquid; energy such as heat or electricity; or nonphysical quantities such as money, celebrity, or memetic content; that does not exhibit Complexity. Engineers work pretty hard to prevent, or reduce, or at least ride on top of, Complex behavior in any flow system.)

Personally and professionally, you yourself are a Complex System immersed in other Complex Systems. You are likely to behave in weird and unexpected ways; and so is just about everyone and everything else.

Welcome to the world of Systems thinking, you beautiful freaks.

What’s a System?

There are a lot of deep and technical descriptions of the nature of Systems. I will goose the throttle right by those, and just give some broad ideas and rules of thumb.

• A System is any grouping of identifiable components that interact meaningfully, in reasonably consistent ways.
• Components act on each other, usually altering one another’s state as they do; these changes in state kick off other interactions, and so on. In other words, interactions propagate from component to component, working changes as they go.
• A System is dynamic. If there’s no motion, if there’s no change, then the components can never interact. A static structure like that is not a System—not the kind Systems Theory studies, anyway, no matter what people call it.
• Very importantly: these dynamic interactions are not instantaneous. Systems act over time. This is particularly weird to those of us in IT, because we have gotten overwhelmingly accustomed to the logic of discrete states, i.e. the logically instantaneous execution of instructions in sequence.
• If state changes can cause interactions which lead to state changes which cause interactions which... then it’s usually the case that an interaction will sooner or later come around, full circle, and have a significant effect on the originating component. This is called a feedback loop. The presence of feedback loops is the fundamental characteristic of Complex Systems, and it leads to some very basic general behaviors:
• Oscillation
• Emergent behavior
• Self-organization
• Self-regulation.
• As a result, it’s usually the case that Complex Systems are behavior-dense: you get a lot of different behaviors out of a fairly modest set of components and defined interactions. And, as mentioned, the behaviors explode in profuse differentiation as the System’s size increased.

These points are all somewhat fuzzy. Don’t worry about it: in Systems thinking, fuzziness is a feature not a bug.

There’s a learning point to make here. This list has a remarkable defect, which is instructive to ponder: it's got its precedence of expression wrong.

We normally expect, given a sequence of assertions, that the first is the most fundamental, the most significant. Look at this list: the first point in this list is to define a System in terms of components. This tempts you, dear reader, to use that to frame the entire concept as you traverse the list. 

You would be wrong to do that, though. The structure of the System is mostly defined by its internal interactions, especially feedback loops. In Systems thinking, component parts matter not because of what they are, but because of what they do.

To start the list with something like “A System is a set of mutual cyclic interactions” would have been more correct, but much less accessible. Leaving the concept of feedback loops to near the end of the list makes a much easier progression to grok.

This has some important lessons about the nature of Systems, not least of which is that entry points in Systems discussions are chosen for convenience. Ordered lists do not reflect System nature, nor structure, worth a damn. Which is inconvenient for us, who by nature (and much more by nurture and training) think in terms of linear sequences.

How do Systems behave, and how do we work with them?

Systems are things that buzz and wriggle and vibrate, things that don't hold still, things subject to damping and stoking of motion, things that try to get beck to business as usual, things that can suddenly collapse or fly into bits.

Systems are things that just can't be reasoned about with the tools we know best.

Systems are a source of bafflement and surprise. They cause us wonder and delight, and they cause us frustration and bafflement. Sometimes at the same time.

Systems teach a salutary intellectual humility.

If you want to think in Systems, you have a lot of unlearning to do.

If you want to think in Systems, you have to learn to see with different eyes. Or, ahem, through a different lens.

There are five things about Systems that deserve a bit more discussion to round out this introductory description:

• Feedback
• Emergent behavior and self-regulation
• Stocks and flows
• Modeling vs. analysis
• Complex System representation in data and computation

So I will talk about those. But not today. Each of these topics can stand on its own.

Hey! I think I see a roadhouse up ahead. I can use a break. Maybe a drink too… Systems Theory gives me a thirst. You?