A Perspective of Human Social Complexity

By Gerrit Van Wyk.

The law of requisite complexity.

Boisot and McKelvey modified Ashby’s law of requisite variety, and stated that to adapt effectively, the internal complexity of a system must match the external complexity it confronts. I take that to imply your understanding of complexity must match the complexity of the phenomenon you confront.

No theory or approach I know of meets that requirement. Most theories about complexity are not complex.

The reason for that is, all theories about complexity I know of, for example the Cynefin grid, takes complexity as a subcategory of reality, as opposed to the idea complexity is the default; in other words, reality is complex, and simple, complex, and chaotic is simply ways of looking at aspects of that complexity.

The reason we are blinkered is we are all indoctrinated in the dominant perspective of reality as machine-like. Which is the basis of science, which so far has been the most successful method for approaching reality and its complexity. The problem is we’ve become so used to the dominance of science, we are incapable of seeing its impotence when faced with complex issues, many created by science and the worldview it is founded on.

One of the most complex phenomena we deal with daily is humans and human society. No matter how hard sociologists, anthropologists, and others try, using scientific methods, by simplifying complex phenomena, they break the law of requisite complexity, which is why we spin tires on the subject.

We can learn a lot from science and scientific methods, in fact, a lot of what we know about complex phenomena come from that, but to break from the past, we must use that knowledge differently, because complex phenomena don’t follow natural laws, it has its own set of rules.

The degree of complexity we face depends on the way we look at it. The more parts and interactions we include, the more complex the phenomenon, the more we take away, the simpler we make it, which is a design choice coming at a cost. Complex phenomena consist of networks of interconnected, interrelated components constantly exchanging information, and reacting and adapting to it, leaving traces in memory, which is constantly updated. From the connections and interactions, properties emerge that are a function of the entity, not the parts, which self-organize around it unpredictably and without planning or control. Similar outcomes may emerge from different arrangements of components, and different outcomes from similar arrangements. All components affect outcomes, even if in small ways, small actions can have major consequences far removed from where they happened and in time (the butterfly effect), effects are non-linear, and initial conditions matter. Because there are so many components and interactions, one cannot accurately predict how they may interact and behave in future. Finally, complex phenomena can develop a dynamic internal order trending to chaos and order at the same time.

Based on the assumption of machine-like predictability, one can plan for simple or complex entities, but not for complex ones. Initial conditions inevitably change, which means the gap between a plan and reality constantly grows bigger. It means you are obliged to adopt a complex understanding of complexity, must adapt to, and learn from how things change, and be prepared to respond to unpredictable unplanned events by making sense of them as they happen. Like a steersman, you can set a course to a desired destination, but you have no idea ahead of time how that journey may go.

My interest is in human complexity, which requires a complex model of human society that cannot fit in an elevator pitch. What follows is a very simplified, anemic version of it.

Human cells consist of a handful of components emerging from chemical interactions, the chemicals consist of atomic particles, and their interactions create a palette of immense complexity. The human body consists of billions of cells, increasing the complexity to a staggering level, which, in turn, contain trillions of bacteria and viruses interacting symbiotically. In the medical tradition, the human body and what happens in it is isolated from its social world, but, as can be expected, such a complex organism constantly interacting with, adapting to, and learning from the physical world, creates very complex behavior patterns, which become part of the human social world.

You don’t need language to communicate, and we communicated through our bodies in very complex ways before we had language. Modern mechanistic perspectives of communication disregard this fact, which eliminates around 80% of human communication. Language emerged as a tool once our voice apparatus evolved to the point where we can manipulate sound at a much higher level of complexity than other animals, giving us a range of options, including the ability to communicate symbols and symbolic concepts.

Like complex adaptive systems, we act towards and react to those around us, and adapt to and learn from that. We act not only with our bodies, but also through language. From these actions and reactions, patterns emerge that remain stable as long as they are useful, but which constantly change incrementally, and sometimes hugely. As we act and react, simple rules spontaneously emerge governing actions and reactions, and, in addition, language is governed by its own simple rules. When we look at entities like banks, schools, political parties, etc., we are looking at emergent patterns , and no two are ever the same, even though they may appear similar.

There are advantages to cooperation, hence we naturally form groups, of which there are many kinds. Groups in turn develop their own simple rules and norms about what they value, and to keep belonging you must agree to the norms and follow the rules. From this a strong sense of collective identity arises, as well as one of them and us; who belong to us and who don’t.

We are born with a potential, but the identity we take on emerges from the interaction between this potential and those around us, which means an identity is not stable and is under constant revision. Our personal identities merge with our social collective identities.

There are different roles in groups, and expectations attached to those roles. Those roles also become part of how we see ourselves. We unconsciously rank the roles, from which a hierarchy emerges, giving access to valued resources. Hence, we compete in groups to improve our hierarchical standing, and cooperate at the same time.

Collectives, or groups, form hierarchies as well based on valued resources they collectively control, of which there are many. Groups are also distributed in competing hierarchies, and we try to jump groups to improve our personal standings. Groups develop habits including dress codes, ways of speaking, perspectives of things, ideologies, things they value, etc., which differentiates them.

Both cooperation and competition depend on the distribution of social power. Power is not a thing, such as in physics, it emerges from the interactions and interrelationships of people and groups. People not only cooperate and compete, they also resist in many subtle and not so subtle ways; where there is power, there is resistance. What one person or group does causes a response, to which the person or groups respond back and forth in an ongoing cycle.

The behavior of groups is socially controlled internally by multiple invisible mechanisms including gossip, shaming, fear, and morality, but above all trust. Again, trust is not a thing, it emerges from interrelationships and interactions, and once destroyed, groups come apart and competition increases.

Organizations technically consist of small to very large groups, in which the dynamics described above play out in complex ways. Many, today, are designed, hence all we see is our design, which ignores human social complexity, which therefore recedes into the background. We think the visible game and the rules we make is real, but the reality is, what goes on in the background and in the wings determines the outcome of the game. We ignore that fact at our own peril.

What I describe here is bare-bones to the extreme, and each of the multiple components of the argument contain many other components cascading into further complex phenomena, thereby multiplying the complexity. The model is based on evidence, but as the evidence changes, becomes obsolete, or proves to be wrong, the model must adapt and learn, which it does all the time. Adapting and learning is a hallmark of complexity, and any model or theory that cannot, or does not do so, cannot be sufficiently complex to meet the requirements of the law of requisite complexity, and that is a problem planners, leaders, mentors, coaches, policy makers, etc., face with existing approaches.