Finding Our Way Through Complexity and Uncertainty

The last post looked at Michael Ben-Eli’s paper, ”Understanding Systems”, a part of Sustainability Laboratory’s online course on Systems Thinking and Systems Modeling. This should have been said then, the Understanding Systems paper needs to be read, even more so than this blog post series. This is only my interpretation, far more likely subject to error, jumbled with alternative and added thoughts to tie it to New Community Paradigms. The paper by Ben-Eli has far more insights from Stafford Beer, Ross Ashby, and others not included here.

The previous post was able to fully define the concept of ”system”, based on the insights in ”Understanding Systems”, solely through mutually supporting abstract concepts without referring to anything physical. There wasn't any need for the particularity of specific instances. ”Organization” could be seen as a concept without the need for reference to a specific organization or particular type. Self-organization arose from the further internal interactions of mutually supporting concepts. There was an inference, with the mention of patterns, to our more immediate sensory world but that world is a veil behind which the concept of patterns lay.

That conceptual reality, however, is not the one that we have to survive, strive, and succeed in. Even if the interactions within such conceptual reality are constrained seamlessly, weaving together effortlessly, they are hidden from our own hard-knock reality by a veil of complexity, uncertainty, and randomness and must be divined from the clues made apparent when we look for them.

The key to piercing the veil, so as to glimpse at a system’s internal workings, is to see the same logic found in the circuitry in man-made, automatic, error-control mechanisms as being analogous to the homeostatic logic found in physiological structures that work to maintain specific physiological values such as body temperature, body fluid composition, blood pressure, blood sugar level, etc., by triggering an appropriate corrective action when deviations occur from a norm. 

Cybernetics focuses specifically on understanding the often obscured dynamics of a systems’ internal structures and the mechanisms that maintain its dynamic organization invariant.  The term “cybernetics” denotes the role of feedback mechanisms in processes of regulation and control. The number of possible distinctions related to a system’s internal states in cybernetics is termed “variety”. 

Norbert Wiener, the first pioneer in the field, and his colleagues established I am going to say the immutable connection between the observable behavior of a system or its output and the internal structure of a system in a 1943 paper, Behavior Purpose, and Teleology. 

First, by clarifying the question of purposive behavior by tying a system’s behavior to its specific internal structure which helped to remove the need for “vitalism,” or as in the last post ”vital force”, to explain the special qualities of living systems. Second, by making it clear that to modify a system’s behavior change must be made to the system’s core structure rather than being directed at the behavior of the system. 

Wiener defined cybernetics as “the science of control and communication in the animal and the machine,” highlighting two key ideas. One is establishing the validity of the theory for both man-made devices and living systems. Two, classifying  “control” and “communication” as one, signifying the role of information in processes of control and regulation. 

What then are the structures and mechanisms of a system by which it mediates its operation, viability, performance, and by which it determines how the system can regulate itself? How it can self-organize and how it can adapt and evolve?

Regulatory processes mediate between the factors interacting for particular outcomes or behaviors binding a system together to preserve (constrain) its singular identity. ”Control” then is not meant to be considered as a restricting concept.

Regulation in the cybernetic model is expressed in the context of a system’s capacity to maintain equilibrium states in the face of disturbances from an environment with which it interacts. Regulation can then be regarded as the manifestation of a system’s adaptive capacity.

Cybernetics extents the concept of regulation to evolutionary processes, by which a system can actually transform into a new entity with a higher regulation potency. Amplifying potential variety by processes such as coalition formation, highlighting the importance of cooperation in evolution as has been demonstrated by anthropologists looking at the work of Elinor Ostrom.

The number of different states that a system in the real world can assume or its potential internal variety can be considered a measurement of complexity. Complexity then can be thought of as the number of possible distinctions by which information can be known or that can be determined about a given system, independent of its size. A human cell can be more complex than a large distribution warehouse.

The number of possible states or a variety of a system increases both rapidly and exponentially when the numbers of elements it contains get larger along with the number of interactions or connections between them, as well as the possibility for each interaction to assume more than a single value.

A quantity of variety, however, also produces a measure of uncertainty. Uncertainty or randomness relates to our perception of order or information about the different states of a system although contrariwise to the way order relates to the more deterministic regularities in a system’s behavior produced by a sequence of a system’s changing states which are detectable. 

The concepts of information and uncertainty are closely related having similar mathematical expressions but opposite signs. If uncertainty is at a maximum then all events in a given universe can occur with equal probability which means that no information is available and variety is at zero. Uncertainty then is a measure of disorder in a system or the level of entropy. 

The process of conveying an amount of information concerning one state out of the variety of all the possible states of a system removes some uncertainty but never all of it, some of it is irreducible as Donella Meadows has pointed out. Too much information can be as bad as too little, making distinguishing relevant information from background noise impossible.

The behavior of whole systems, presumably those of sufficient complexity to require multiple subcomponents to achieve a high degree of internal variety, cannot be predicted from the behavior of the system’s parts alone due to the emergence of new, often unexpected properties. This perspective of an entire or whole system is termed synergy in Cybernetics. This ought to be assumed in all cases of social systems design and addressed as they will find inevitable expression in social interactions. 

The concept of variety, along with the concepts of organization, entropy, and order, and I would add synergy, are at the nexus of our ideas involving physics, information theory, and the philosophy of science. Such regularities that can be found within a system are produced by constraints imposed on that system’s potential variety or its internal structure as discussed in the last post. This the Understanding Systems paper asserts is profound.

The far more prevalent traditional reductionist analytical process, according to Ludwig von Bertalanffy, as cited by the Understanding Systems paper, sees interactions between elements being non-existent, or negligible in that they can supposedly be ignored for the purpose of analysis. According to a strictly reductionist perspective, understanding the world should be possible from constructing a picture of it by simply adding up detailed descriptions of its parts.  There is no need but to precisely measure what is immediately before us and sum it up. Ignoring the internal state of systems is to our peril as we are assailed with a world of complexity, uncertainty, and randomness by which the reductionist perspective can be seen as myopic.

The gross deficiencies of currently prevailing top-down hierarchical command and control structures, including an inability to effectively address complexity, have been highlighted by many including Dee Hock, founder and CEO emeritus of VISA International, who advocated instead for a creative combination of “order” and “chaos” or what he termed “chaordic”. A more versatile and dynamic, but also more complex form of organization that allows for the ability to innovate and experiment. 

Switching from a mechanistic, reductionistic perspective of the world to a system view of the world opens one up hopefully but also understandably hesitantly to a variable, dynamic and interdependent reality, which demonstrates not only the need for a transformative shift in values, attitude, and actions in the world but also to pathways able to achieve them. 

Personally, I doubt that this would actually force acknowledgment of such a reality, as Ben-Eli asserts. We, humans, are far more resilient in our mental models than that, persuasion is still required. As he says elsewhere, individual observers can either keep or change their frame of reference. Even if they do change, they will likely have to come together with others in some manner to change their collective conclusions to change the system. Regardless, the implications of switching are still profound.