By Gerrit Van Wyk.
The following is a series of propositions about complexity, social complexity, and the complexity behind how I arrived at these propositions.
Introduction
- My interest is human social dynamics, interactions, and behavior.
- Human social interactions, dynamics, and behavior confuse me.
- My question is, how to explain human interaction, social dynamics, and behavior in a way that makes sense in practice?
- What theory or argument pragmatically explains it, and what evidence is there supporting the theory, or argument?
- The test for whether such an evidence-based argument is true is does it work in practice?
- From what I observe, human social interaction, dynamics, and behavior is complex.
- If that is the case, do the sciences of complexity offer a reasonable explanation of it, and do the observed ways complex phenomena behave apply to human social interaction, dynamics, and behavior?
- There is evidence supporting the argument human interactions, behavior, and dynamics is complex.
- Evidence for assuming human social behavior and interactions is complex by itself is not sufficient for explaining those interactions and behaviors, and specifically what operates outside consciousness.
- We are unconscious of most interactions in our bodies, and what triggers our interactions and behaviors, which significantly influences the outcomes of interacting with others. In the same way, we are unconscious of most human interactions and interrelationships as they play out.
- The traditional social sciences assume human interactions, dynamics, and behavior may be explained scientifically.
- I do not find anything in the traditional social sciences satisfactorily explaining the complexity of human interactions, dynamics, and behavior, and specifically the unconscious part.
Complexity
- Complexity is not a feature of an entity of interest, it depends on how we describe it.
- Entities are things of interest to us, and exist because we name them after artificially creating a border around it.
- The more components and interactions one add to a description, the more interconnected they are and the more they interact, and the more you leave out, the simpler the entity appears.
- Components are emergent patterns which we put into categories and give names.
- Patterns emerge from components, how they are arranged, and how they are interrelated and interact with each other.
- Components affect an entity of interest through their connections to and interactions with other components, and no components have no effect on the entity.
- Components effect other components by exchanging matter, energy, or information.
- Components react to other components’ actions, and act on that.
- Components do not act randomly; their actions depend on simple rules and a memory of past experience, constraining how they may act.
- The actions of components change the rules, as well as memory, which affects future actions.
- Effects ripple through an entity as a network effect.
- The more densely networked components are, the more it may affect the entity.
- Effects ripple through entities in a nonlinear fashion; the further removed in space and time from the original interaction, the less predictable the outcome.
- Rare effects occur more commonly in complex environments than expected.
- Some effects only become noticeable some distance from the original interaction (the butterfly effect).
- Complex phenomena are deterministic; what happened before influences what happens next.
- Complex phenomena retain a memory of what happened before, which influences what happens now, and what will happen in the future, while at the same time, changing the memory.
- Patterns show a cloud effect; their ongoing interactions create constant incremental change which appears imperceptible to us, and sometimes big ones, which come to our attention.
- Entities of interest are never stable: stability is a cognitive illusion.
- It is difficult understanding patterns outside the context from which they emerge.
- Patterns and associated properties emerge from the interconnections and interactions of the parts without being planned or controlled.
- Basins of attraction; properties are maintained for as long as the interconnections and interactions of its components remain relatively undisturbed and stable.
- Patterns are not discrete entities or components, they represent multi-dimensional distributions within which what is closer to the core is more representative of the entity, and what is further away, less.
- Differently interrelated and interacting components can give rise to similar patterns, and similarly arranged components interacting in the same way to different ones.
- Complex phenomena appear both stable and chaotic to us at the same time. Aspects of complex phenomena appear chaotic to us because we lack the capability to understand and explain them; once we can, they no longer appear chaotic, therefore chaos is not a property of complex phenomena.
Social complexity
- Human interactions and interrelationships are complex.
- The propositions about complexity applies equally and proportionally to human behaviour.
- Human behavior and social interaction are constrained by thousands of physical, biological, cognitive, social, linguistic, and other simple rules, all in play at the same time, and playing out unconsciously.
- The human body, human behavior, and human social world is an inseparable complex entity.
- Phenomena such as mind, consciousness, thinking, emotions, etc., are constantly changing complex patterns emerging from interacting human biology, behavior, and social interactions.
- Behavioral phenomena such as a self, me, personality, etc., are constantly changing patterns emerging from the interaction between individuals and their social and physical environments. The idea of a stable self, me, personality, etc., is an illusion.
- Collective phenomena such as groups, organizations, power interactions, etc., are constantly changing emergent complex patterns.
- Social artifacts such as a nation, economics, academia, politics, etc., are emergent constantly changing complex patterns.
- The interacting biological, cognitive, and social complexity of humans escalate the level of human complexity non-linearly and exponentially.
- Humans communicate through complex biological and linguistic patterns, based on generalized predictions about how others may interpret it and respond.
- Like all complex phenomena, humans react to each other’s actions and react to that, while at the same time adapting and learning from it.
- Humans react to and act on others based on predictions of how people on average act and respond, which is robust, but inevitably inaccurate to some degree.
- We react to and act in response to the inaccuracy, and learn from it by retaining a memory of the interaction, which affects how we perceive and react to similar conditions in the future.
- To meet Boisot and McKelvey’s Law of Requisite Complexity, which requires an explanation of complexity to match the complex it attempts to describe, the propositions above are interconnected and interrelated, and all operate together at the same time.
- The propositions satisfactorily explain both observed and unconscious human behavior, interrelationships, and interactions, which meets the requirement of pragmatic utility.