The Cybernetics of Complexity:

In today’s post, I am looking the second order view of complexity. While I was thinking of a good title for this post, I went from “A constructivist walks into a Complexity bar” to “The Chernobyl model of Complexity”. Finally, I settled with “The Cybernetics of Complexity.” What I am looking at is not new by any means. I am inspired by the ideas of Ross Ashby, Stafford Beer, Heinz von Foerster, Haridimos Tsoukas, Mary Jo Hatch and Ralph Stacey.

I start from the basic premise that complexity is a description rather than a property of a phenomenon. This would indicate that the complexity is dependent on the one doing the describing, i.e., the observer. Complexity is a description, which means it needs someone describing it. This is the observer. The same thing can be perceived as complex and complicated by two different people. Tsoukas and Hatch explain this further:

in order for cognitive beings to be able to act effectively in the world we must organize our thinking… one way of viewing organizations as complex systems is to explore complex ways of thinking about organizations-as complex systems; which we call second order complexity. We further note that entering the domain of second-order complexity – the domain of the thinker thinking about complexity – raises issues of interpretation (and, we argue, narration) that have heretofore been ignored by complexity theorists.

What is complexity? It is our contention that the puzzle of defining the complexity of a system leads directly to concern with description and interpretation and therefore to the issue of second-order complexity.

Tsoukas and Hatch references Jim Casti to explain this further:

complexity is, in effect, in the eye of the beholder: ‘system complexity is a contingent property arising out of the interaction I between a system S and an observer/decision-maker O’. To put it more formally, the complexity of a system, as seen by an observer, is directly proportional to the number of inequivalent descriptions of the system that the observer can generate. The more inequivalent descriptions an observer can produce, the more complex the system will be taken to be.

Casti’s definition of complexity is an interesting one for it admits that the complexity of a system is not an intrinsic property of that system; it is observer-dependent, that is, it depends upon how the system is described and interpreted. Consequently, if an observer’s language is complex enough (namely, the more inequivalent descriptions it can contain) the system at hand will be described in a complex way and thus will be interpreted as a complex system. What complexity science has done is to draw our attention to certain features of systems’ behaviors which were hitherto unremarked, such as nonlinearity, scale-dependence, recursiveness, sensitivity to initial conditions, emergence. It is not that those features could not have been described before, but that they now have been brought into focus and given meaning. To put it another way, physics has discovered complexity by complicating its own language of description.

Here, the language of description comes from the observer. One of the best examples that I have to provide some clarity is a scene from HBO’s wonderful show Chernobyl, adapted from the Chernobyl tragedy. In the scene, Anatoly Dyatlov, the deputy chief Engineer was alerted of things going wrong by the other engineers taking part in a test. Dyatlov stubbornly refused to acknowledge that anything was wrong. He asked the engineer, “What does the dosimeter say?” The response was. “3.6 Roentgen, but that’s as high as the meter..” Dyatlov, in the show cut him off midsentence and famously state, “3.6. Not great, not terrible.

Dyatlov firmly believed that the reactor could not explode. Even though he was informed that the meter can go only as high as 3.6 roentgen, he found the situation to be manageable. Later it is revealed using a different gage with higher range, the actual rate was 15,000 roentgen per hour. This scene is truly remarkable because there were different people looking at a phenomenon and coming to different conclusions with terrible consequences.

In philosophy, we talk about ontology and epistemology. Ontology is about what exists and epistemology is about how you come to know things. We are all born with a set of “gages” (to loosely put). But each one of our gages have different ranges. The set of gages is unique to our species. For example, we can only see a small part of the light spectrum. We can only hear only a small part of the sound spectrum. We are informationally closed. This means that we generate meaning within a closed interpretative framework/mechanism. Information cannot come in directly. Rather, we are perturbed by the environment and we generate meaning from it. It might make it easier if we can come up with a way to quantify complexity.

A loose way to do this is to view complexity in terms of the number of possible interactions the phenomenon can have. This in turn is related to the number of states of the phenomenon. In cybernetics, complexity is viewed in terms of variety. Variety is the number of states of a phenomenon. I have discussed this concept at length before. To explain it loosely with an example, the variety of a simple light switch is two, the two states being ON and OFF. A variable light switch on the other hand has a whole lot more variety. The other insight regarding variety is that it is dependent on the observer since the observer is the one describing the number of “possible” states. Now this is where the possible rub comes in for some people. I see complexity as dependent upon the observer. Do I reject that there is nothing out there that is not in my head? That is a question about ontology. I am not very keen on just looking at ontology. I am looking at this from an epistemological viewpoint. Going back to the Chernobyl show, if my gage is inadequate, then that determines my reality which determines my action. If I have a better gage, then I can better understand what is going on. If I have others around me with more gages, then I can do a comparison and come to a general consensus on what is going on so that our general viability is maintained.

We have learned through evolution as a species to cut down on the high variety thrown at us so that we can remain viable. As noted earlier, we have evolved to see only a narrow band of the light spectrum, same with the sound and other natural phenomena. This has led to us having a set of “gages” unique to our species so that we can continue being viable. When these gages become inadequate, then our viability is in question. The purpose of gages is to make sense of what is happening so that we can act or not act. We don’t register everything that is coming in because we don’t need to. Our genetic makeup has become tuned to just what we need.

When I say complexity is in the eyes of the beholder, I mean that our range of gages are different dependent upon the observer. What we sense directly impacts how we act. Some of us can manage situations better because they are able to make sense better. Whether a situation is complex or complicated changes based on who is doing the observing. The term observer here means the person interacting with the situation. You can call him an actor or an agent, if needed.

Tsoukas and Hatch expand on this:

If practitioners are to increase their effectiveness in managing paradoxical social systems, they should, as Weick recommends, ‘complicate’ themselves. But complicate themselves in what way? By generating and accommodating multiple inequivalent descriptions, practitioners will increase the complexity of their understanding and, therefore, will be more likely, in logico-scientific terms, to match the complexity of the situation they attempt to manage, or, in narrative terms, to enact it.

In Cybernetics, this aligns with Ross Ashby’s law of requisite variety. This law states that only variety can absorb variety. To simply put, we have to cut down excess external variety coming in and find ways to amplify our internal variety so that the internal variety matches the external variety. A good way to cut down the external variety is to focus on only what matters/values to us. A good way to amplify our internal variety is to keep on learning and to be open to other perspectives. Of course, there are a lot of other ways to do this. A specific procedure cannot be made because everything is dependent upon the context. The phenomenon itself is changing with time, and so are we as the observers.

We have to welcome how the other practitioners describe the phenomenon. We have to engage with them so that we can come to a stable narrative of the phenomenon. This is not possible if we see ourselves as external to the phenomenon and if we believe that we all experience a single objective phenomenon. As Tsoukas and Hatch note – Expanding the focus from the system itself (first-order complexity) to also include those who describe the system as complex (second-order complexity) exposes the interpretive-cum-narrative dimensions of complexity. A complex system is said to have many specific characteristics including non-linearity, feedback loops, etc. But these are all descriptions of an observer describing the phenomenon. As Tsoukas and Hatch note:

Although you may call non-linearity, scale dependence, recursiveness, sensitivity to initial conditions and emergence properties of the system, they are actually your descriptive terms – they are part of a vocabulary, a way of talking about a system. Why use such a vocabulary? Is it because it corresponds to how the system really is? Not quite. Because the system cannot speak for itself, you do not know what the system really is. Rather, you use such a vocabulary because of its suspected utility – it may enable you to do certain things with it. A new vocabulary, notes Rorty, ‘is a tool for doing something which could not have been envisaged prior to the development of a particular set of descriptions, those which it itself helps to provide’.

What we have to then do is to understand that seeing complexity as a description of a phenomenon helps us in understanding how we understand the phenomenon. This is a second-order act, a cognitive act. We need to be aware of our blind spots (realization that we have inadequate gages). We need to improve our vocabulary so that we can better describe what we experience. Some models of complexity recommend bringing in experts for complicated phenomenon. Complicated phenomenon are cases where the complexity is slightly higher, but a cause-and-effect relationship still exists. The reason for bringing in the experts is because they are able to describe the phenomenon differently than a layperson. This again shows that complexity is dependent on the observer. It also indicates that we can improve our sensemaking capabilities by improving our vocabulary by keeping on learning. I will try to loosely explain my ideas based on a one-dimensional depiction of complexity. I am not saying that this is a correct model. I am providing this only for clarity’s sake. The chart below shows the complexity in terms of variety. The green line starts at 0 and ends at 100 to show complexity on a spectrum. Depending upon the capability of the observer to distinguish possible varieties, two observers perceive and understand complexity as shown below. The observer 2 in this case is able to manage complexity better than observer 1. Please note that to manage complexity means to cut down on the excess external variety and amplify internal variety. The other point to keep in mind is that the observer is informationally closed, so the observer is able to generate meaning of only those characteristics that perturbs the observer. In other words, the observer can distinguish only those characteristics that the observer’s interpretative mechanism can afford.  

When we look at a phenomenon and try to make sense of it, we try to do it in terms of a whole narrative, one that makes sense to us. This adds a uniqueness to how each one of the practitioners approach the phenomenon. The same complex phenomenon can have different contexts for different people. For example, the same Covid pandemic can be a problem of health crisis for one person, while for another it could be about freedom and government regulation. A stable social reality is achieved through continuous interaction. The environment changes, so we have to continuously interact with each other and the environment and continue to reframe reality. This social stability is an ongoing activity.

Final Words:

I had indicated that this post is about a second order view of complexity. In order to improve our understanding of complexity, we have to understand how we understand – how we come to know about things that we can describe. I do not propose that there is an objective reality out there that we all experience equally. All we can say is that we each experience a reality and through ongoing interaction we come to a stable version of reality. One of the criticisms to this approach is that this leads to solipsism. The main version of Solipsism is that others may not really exist and that only one’s mind is sure to exist. This is a no-win argument that I find no appeal in. I am happy that other smarter people exist because my life is better because of them. Another criticism to this approach is that it supports relativism. Relativism is the idea that all perspectives are equally valid. This also is a terrible idea in my view. I support the idea of pluralism. I have written about this before here.  Pluralism does not agree that all belief systems are equally valid. In a cybernetic explanatory manner, a pluralist believes that what is more important is to be less wrong. At the same time, a pluralist is open to understanding other people’s belief systems.

What I am hoping to achieve from this constructivist view is epistemic humility. This is the stance that what we know is incomplete, and that it may also be inadequate. We have to keep on learning, and be open to other viewpoints.

I will finish with a wonderful quote from Heinz von Foerster:

properties that apparently are associated with things are indeed properties that belong to the observer. So, that means the properties which are thought to reside in things turn out to be properties of the observer. I’ll give you immediately an example. A good example, for instance, is obscenity. You know that there is a tremendous effort even going up to the Supreme Court which is almost a comedy worthy to be written by Aristophanes. Who wants to establish what is obscene? Now it’s perfectly clear that “obscene” is, of course, a property which resides in the observer, because if you take a picture and show it to Mr. X, and Mr. X says, “This picture is obscene,” you know something about Mr. X, but nothing about the picture.

This post is also available as a podcast – https://anchor.fm/harish-jose/episodes/The-Cybernetics-of-Complexity-e15v5v9

Please maintain social distance and wear masks. Please take vaccination, if able. Stay safe and Always keep on learning… In case you missed it, my last post was Observations on Observing, The Case Continues:

4 thoughts on “The Cybernetics of Complexity:

  1. Again well written. Thanks.
    The word “gages” triggers me. Smith and Berg describe in their Paradoxes of Group Life four paradoxes – a paradox is also in the eye of the beholder – called engagement (I prefer the verb “engaging”). Very interesting, because “complexity” results from engaging of systems with complex systems – Ashby’s Law. Very simply put: structural coupled natural or organic “systems” induce organically complexity in structurally coupled systems (or the other way around). The “gages” of living systems engage themselves.

    They’re calling the four paradoxes paradox of disclosure (disclosing – as a verb), trust (trusting), intimacy (intimating – to communicate delicately and indirectly), regression (regressing). This are intergroup paradoxes: the paradox of living in groups consist of our resistance with disclosing ‘secrets’, like (dis)trusting other members in certain situations, with which we are close and then “regress” – act implicitly more childishly (angry, dissatisfied, saddened, … You can see how these complications will lead to complex situations, where we say one thing while meaning another thing.

    They – Smith and Berg – connect this paradox with the intergroup paradox of what they call perception (perceiving). We see members from other groups through the lenses – templates – of our group. .Sometimes called “projecting”.
    In my view, ;-), life itself is paradoxical. So I can project the intergroup paradoxes on my organs – members of my body-as-a-group; they are engaged, trust each other and – in the long run – regress. My perceptual organs – skin, eyes, ears, nose, … – perceive while projecting their “inner views” on the outside. These processes process themselves in my brain, thereby structurally coupling body with mind, sensing with acting.

    The problems we’re having with understanding (non-)linearity come from using a linear structured tool in engaging with our domains (the word I prefer over environment): language. I’m sure we fully understand complexity when we’re engaged in engaging – we’re able to absorb complexity when driving a car, gathering food, building buildings, …. When engaged with each other in conversations using language, we run into trouble, because we have been instructed that words carry meaning (conduit metaphor https://en.wikipedia.org/wiki/Conduit_metaphor)

    I’m currently developing a model based on a double metaphor: one generated by our senses – metaphor-in-use – and one induced by the group we’re being adopted by – metaphor-espoused. The metaphor-in-use we’re realizing when we’re (inter)acting (“when you want to perceive, learn to act”), while we cannot realize ourselves the processes of realizing. The metaphor-espoused we can “hear” when we’re referring (in language) to a metaphor-in-use as perceived through the lenses (templates) of our group. I suppose we’re still thinking that spoken words can control reality, like using spells.

    Like

  2. Thinking about this reply, I noticed your remark: “I have discussed this concept at length before.” This is a kind of “recursing”, referring to what has been said or done before.

    You also wrote:”complexity science has done is to draw our attention to certain features of systems’ behaviours which were hitherto unremarked, such as nonlinearity, scale-dependence, recursiveness, sensitivity to initial conditions, emergence “. Nothing in behaviour of systems has changed, except for our not unmarking, or “perceiving”.

    “Complexity is not an option”.
    Ashby’s Law states that only complexity – complex systems – can absorb complexity – complex systems. So complexity induces – produces, invents, projects – complexity in itself – recursively – as well as in other “systems” – pro-cursively. Complexity – like paradox – is self-propagating, self producing, autopoietic, autonomous … . In this way, I can explain why what we’re calling complexity cannot be exclusive and has to be included in any (complex) system . (With the general exception of systems of thought, theories, *-ism’s, because we need them to be general, accurate, complete and (preferably) simple)

    “Complexity produces one-self, here and now”
    For instance, any animal “absorbs” – abducts – complexity from its “environment”, (I like the French milieu, as it refers to being in the middle of the place (lieu)) while producing complex products, like its environment of ‘milieu’. Any animal both produces and is being produced, shaped by its so-called environment. (this is why I like to call “environment” domain. Domain comes from “domus”, house. One build one’s house oneself).

    “machine are not complex, their complex is”
    Because we build our machines – and theories – ourselves, still, they can only be complicated and will never become complex. However, the system of machines and theories becomes complex, as these domains induce each other. Emerging economical, social, cultural and political systems – as complexes inducing, producing, evolving each other – from technical – https://www.etymonline.com/word/technology – inventions in reproducing text facilitated “itself”. Interestingly, text comes from textile, weaving. We’re weaving patterns of language.

    Extending Ahby’s Law: only ambiguity begets ambiguity; only volatility becomes volatile and only uncertainty remain uncertain.

    Liked by 1 person

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