Social Self-Organization

Social Self-Organization

Self-organization is a type of pattern formation, a means through which some form of order or coordination is developed. There are essentially just two basic methods through which social coordination and order can occur. Within linear systems, it may be imposed in a top-down fashion from some centralized global authority or within nonlinear systems, it may emerge from the interaction of the agents on the local level in a bottom-up fashion and this is social self-organization. As such self-organization is a nonlinear process of pattern formation.1

Top-Down Order

Within a linear system where there is a low level of connectivity and relatively few components interacting in a well-defined linear fashion, it is possible to control and coordinate that system through some centralized regulatory mechanism. We can use this centralized governance mechanism to impose or maintain order within the system, that is to say by influencing or controlling the agent’s choices towards a coordinated outcome we can get some state of order within the system. We can only have this form of centralized top-down coordination when a relatively large percentage of the interactions are being routed through some centralized coordination mechanism. But this top-down form of regulation and control is only possible within linear systems, as we turn up the distributed connectivity, the number of components and their capacity for autonomous decision making, the system will become more and more difficult to coordinate from a centralized location and it will become easier and easier for patterns to form on the local level through this high level of distributed interaction. Above some theoretical point where we have more nonlinear distributed interactions than centrally controlled connections, we are starting to get a significantly large enough space that is unregulated and it is in this unregulated space that has sufficient density of nonlinear interactions that self-organization can take hold as a significant mechanism for coordination.2


Centralized models to social order have their limitations as they will always have to use hierarchy in order to manage the system. This is because a centralized model means that very few people are trying to regulate very many, one can only do that by using abstraction, a president of a country with 1.3 billion people cannot go around telling each one what to do there has to be many layers of bureaucracy between them, and information has to flow in a linear fashion out from the center to the periphery, the further we go out the more people we have and the greater possible cross links we can have between them, each one of these peer-to-peer links is a possibility for a local pattern to form. Thus self-organization often happens out at the fringes where the chain of command is weak and there are many local interactions, we can call this state an unregulated environment and it is the condition or ground on which self-organization takes hold.


Self-organization is then a form of distributed nonlinear pattern formation, all patterns, forms of order, or organization are going to involve some correlation between the states of the system’s constituent elements, this is essentially what organization is when there is no correlation we have randomness, the absence of order. We have randomness and order which is some form of correlation between states, like two people dancing together, a change in the state of one’s motion will be correlated with that of a change in another. The dancers on a fundamental level can really only do two different things, they can move together in the same direction, which is a positive correlation or they can move in the opposite direction, which is a negative correlation. A positive correlation means the two elements states are synchronized, they move together in the same direction, a negative correlation means they are desynchronized they move in the opposite direction. In applying this to social systems then, we are talking about agents and thus we are talking about correlations between the choices of agents, do they choose to do the same thing, opposing things or is there no correlation between their choices, this is the very basics of what we are dealing with when talking about self-organization within social systems.3

Feedback Loops

Self-organization is then a process that is going to change the correlation between agent’s states within the system, it is going to coordinate them and this is done through what are called feedback loops. Positive feedback loops have been identified as playing a central role in the process of self-organization, we will be talking more about feedback loops in a future video but a positive feedback loop is one that is self-reinforcing, more begets more, the more products a business sells the more it can invest in its business, meaning it can produce better, cheaper products, meaning it will sell more, meaning it can reinvest more and so on, this is an example of a positive feedback loop, it is a nonlinear process of change, through it the business can grow in an exponential fashion. Feedback loops are the mechanisms through which some local small event, which is often random in nature, can get amplified into a new macro level pattern of organization and this is the heart of the whole process of self-organization.4 To give an illustration of this let’s think about a beach of people sunbathing on their holidays. Now let’s add some initial random event, we have someone with headphones on listening to their favorite music and they get so excited that they jump up and start dancing around, what happens now depends on the state of the other agents around them, typically these random events will get dampened down and die out, everyone will look at this guy like he is weird. But by this person occupying this differentiated state we have already created a feedback loop, it is now much easier for anyone else with a propensity for dancing to jump up and join him, and when they do we now have some distinct pattern, two people occupying the same state and although they are still a significant minority the positive feedback has got stronger, it is now even easier for the next person to join, and with every new person that joins it becomes more attractive for anyone else to do likewise.5


As this positive feedback process of change continues we will get to some point where there are more people dancing than not dancing, at this point dancing has become what we would call an attractor, you will be considered more normal if you are dancing rather than not dancing. If we add a new agent to this system who just wants to be normal and follow the course of least resistance then he or she will end up dancing. And thus through this process of change driven by positive feedback we now have an attractor, a default set of states within the system, this attractor is the pattern of organization, all these agents dancing have correlated their states in some way.6 As another example of an attractor we might think about the languages and cultures within different regions, within any different region there will be a strong attractor towards speaking the same language and adopting the same culture and behind the creation of these cultural attractors was a positive feedback loop, the same as with our people on the beach. But as we know there are many different languages and cultures in our world representing many different attractors, because if the system is large enough this process of self-organization through positive feedback may take hold around many different components within the system at different locations and grow out from there until it reaches another pattern at which point we get a boundary condition, like the national boards in Europe marking the limits to the different cultural attractors that have formed over a prolonged period of time. At this point where all the elements in the system are aligned within local level attractors positive feedback will die out and negative feedback will take hold as the different attractors balance each other out to create a semi-stable configuration.7


Different attractors then have to compete or cooperate in order to enable some form of global coordination. This type of interaction will largely be a product of how the attractors were created in the first place, i.e. were these different local attractors created out of exclusive or inclusive conditions. We can create social organization by the individuals overcoming their differences to find common ground, common purpose, and identity or we can create this organization by defining our difference and degrading others, what is called out-group derogation, which is a form of negative externality. We are creating the pattern of organization by simply exporting the entropy outside of the system’s boundary to some other system. For example, the Nazis created their sense of identity around the Aryan race through a systematic derogation of other out-groups, including the Jews among others, this exporting of social entropy creates division and conflict. By the individual attractors exporting entropy this will create a state of disorder within the overall system, any group that is dependent upon the exporting of entropy in order to define and maintain its internal state of order, will not be able to integrate within the overall state space and conflict will be the primary type of interaction between the different patterns of organization.8


This process of social self-organization can also be created out of positive externalities, the net result being emergence as the different local attractions overcome their differences and we get the emergence of some global pattern of organization. Emergence is a process whereby larger entities, patterns, and regularities arise through interactions among smaller or simpler entities that themselves do not exhibit such properties as such it is very much analogous to self-organization but subtly different. Emergence is a distinctly nonlinear phenomenon in that it can not be derived from any one component within the system, it is the produce of many distributed interactions across the system. An example of this might be a wave at a football match, this is an emergent self-organizing phenomenon, no one is coordinating it, some small initial event takes hold and gets amplified into a large macro phenomenon, it emerges out of the synchronized states of the members. People crossing on a street is another example of pattern emergence through self-organization, we have dense interactions as people going in either direction try to pass each other, those who meet first have to coordinate their activity, but once they do this will create an attractor for others to follow as we get the emergence of some pattern to the crowd, streams of people going in different directions.9

Cause & Effect

In these nonlinear systems, there is a breakdown of linear cause and effect. When all the components come to be aligned within a similar configuration, all the agents come to adopt a similar perspective then some small event can gain traction and propagate through the whole system. For example we might think about some oppressive political regime, for every act of oppression from the ruler this may not have a direct consequence, but it creates resentment among the people, this resentment builds up until we have some critical state, all the people are synchronized in their discontent, at this point some small random phenomena, that had happened many times before, can now propagate through the system rapidly, the system has self-organized into a critical state, this critical state is systemic it is distributed out across all the elements in the system, thus no one cause created the effect, it emerged out of the overall state of the system and the feedback loops that drove it over time. This type of nonlinear pattern formation is then unpredictable, there are many small fluctuations and it can not be determined in advance which one will gain hold thus we cannot know where they will come from because the actual event emerges out of the state of the system and through the feedback loops, but those feedback loops play out over time after the event has happened, that is to say, the outcome does not exist at inception, it is not determined by the initial cause but instead it is created along the way.10

Systems Innovation

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