The Thrill of Creating Complexity

I’m fascinated with this idea that simple things can interact to create complex results. Think about that for a moment. Sometimes you can combine things in such a way as to create properties that are greater than the properties of the things being combined. They adopt heightened characteristics when they interact.

Nature is full of such examples. Complex cloud formations emerge when water vapor and tiny water droplets are suspended in the atmosphere. Ocean waves form when wind interacts with the water’s surface. Clouds and waves, despite being just water in the right atmospheric conditions, exhibit all manner of unpredictable shapes, patterns, and formations.

In situations where simplicity creates complexity, the key principle on display is: emergence. The term emergence refers to a dynamic where complex attributes, characteristics, patterns, or behaviors develop when simple constituents interact.

A good example of emergence is the ant colony. Ants communicate with each other individually, using antennae and pheromones to share information. All communication is local. Each ant carries out its individual task on its individual path. Yet collectively, the colony behaves with a certain order as if governed by a central control system.

Ants build complex cities, launch collective defense strategies against predators, harvest food to feed their population, build bridges and rafts using their own bodies to help the colony to survive flooding, and exhibit vast organizational complexity. Yet the colony doesn’t have a military-style hierarchy of commanders barking orders at the troops, “Divert resources to reinforce our defenses in the Alpha quadrant!” Rather, each ant learns from its neighbors about what local task is needed, and then it executes that local task, contributing to the colony’s complex order.

Social networks like Facebook, Instagram, and X can also resemble ant colonies with their own emergent characteristics. Individuals in the network interact by sharing content and responding to the content of others. Yet from these simple interactions emerge larger trends, collective behaviors, organizations, rallies, clubs, and social movements. As ants and Facebook accounts attest, constituents in complex systems often possess the quality of self-organization.

Neural networks in the brain provide another good example. Neurons themselves are simple cells, yet their collective interactions create the complex cognitive functions of learning, understanding, memory formation and retrieval, language processing, decision making, and consciousness.

Although interactions may be complex, that doesn’t necessarily mean they are complicated. Complex systems create emergent properties that may not be known in advance. By contrast, complicated systems typically have many constituent parts creating outcomes that are more predictable.

Think of a domino chain reaction where someone erects row upon row of dominos and begins an extensive wave-like sequence by tipping just one domino. The system is complicated, involving hundreds or even thousands of carefully placed dominos, but the outcome is predictable. It is complicated but it isn’t complex in the sense of unpredictability.

Complicated situations can be comical when taken to extremes, as shown by the Rube Goldberg machine, named after the American cartoonist. Goldberg’s machines were contraptions that involved unnecessarily complicated systems to accomplish simple tasks. In one example, “Professor Butts and the Self-Operating Napkin,” the Professor is sitting for dinner. He raises a spoon to his mouth to set off a chain reaction: it jerks a ladle which throws a cracker in the air, causing a bird to jump after the cracker, tilting its perch which spills seeds into a bucket which weighs against a chord that lights a lighter flame that ignites a skyrocket that causes a blade to cut a string that releases a pendulum with a napkin on the end that wipes the chin of Professor Butts. Of course, the Professor could have more easily wiped his own chin with the napkin, but then it wouldn’t be a Rube Goldberg machine.

The system uses exaggerated complexity, but its outcome is known in advance. In fact, the cartoon derives its humor from the predictability of the outcome. Each of the machine’s components has a small, specific role to play. If every component executes its small task as expected, the machine will achieve its predictable result.

Complex interactions, on the other hand, often create unpredictable results. Their results are often non-linear, meaning, their outcomes are not proportional to their inputs. In complex ecosystems, a small change in one factor can lead to a large change in the entire system. In the example of the wave, increasing the wind by just one mile per hour could create a compounding effect to result in tremendously larger waves.

Non-linearity is captured in the idea of the snowball effect. A tiny snowball at the top of a hill gathers more snow as it rolls down, resulting in a snow boulder at the bottom of the hill. How large will the boulder become by the time it reaches the bottom? It’s hard to predict exactly because the process is non-linear. At the top of one hill, a small amount of snow that gets displaced may simply come to rest without further activity. At the top of a different hill, however, the same small displacement could trigger a giant cliff-like avalanche. The effects are non-linear.

In epidemiology, minuscule differences in transmission rates can cause one virus to die off harmlessly, while another one leaps from host to host to spread across the global population. The world learned this lesson in non-linearity during the COVID-19 epidemic.

Complex interactions often create feedback loops, so the results of interactions influence the behavior of the individuals interacting. The product of one interaction becomes the input for the next interaction.

Think of a sporting event where the home crowd begins spontaneously taunting one of the visiting-team players, mockingly repeating his name in unison after he makes a mistake. The group behavior influences the group behavior. Or think of a musical concert when the audience settles into a rhythmic clapping and whistling and shouting, “En-CORE! En-CORE! En-CORE!” in unison until the performers return to the stage to resume their performance. These are examples of feedback loops evident in complex environments.

It can be thrilling to watch complexity emerge from simple interactions. And it can be even more thrilling to actually create that complexity through skillful combinations.

The process of combining elements releases the inherent potential of the elements being combined. It is the act of creation in its pure form, the creation of new characteristics that were not present previously. The process brings into being new potential, new information, new behavior, new patterns, new characteristics.

There are only 12 notes in the musical scale, but you can combine them into a melodic piece to deliver an emotional charge to listeners. When you create this music, you create a new energy that can animate and excite your listeners.

And that is exactly what happens when you create complexity: you create energy that didn’t exist prior to your activities. The process can be incredibly gratifying, both to you and to the people who experience it.