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:

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When is a Model Not a Model?

Ross Ashby, one of the pioneers of Cybernetics, started an essay with the following question:

I would like to start not at: How can we make a model?, but at the even more primitive question: Why make a model at all?

He came up with the following answer:

I would like then to start from the basic fact that every model of a real system is in one sense second-rate. Nothing can exceed, or even equal, the truth and accuracy of the real system itself. Every model is inferior, a distortion, a lie. Why then do we bother with models? Ultimately, I propose. we make models for their convenience.

To go further on this idea, we make models to come up with a way to describe “how things work?” This is done for us to also answer the question – what happens when… If there is no predictive or explanatory power, there is no use for the model. From a cybernetics standpoint, we are not interested in the “What is this thing?”, but the “What does this thing do?” We never try to completely understand a “system”. We understand it in chunks, the chunks that we are interested in. We construct a model in our heads that we call a “system” to make sense of how we think things work out in the world. We only care about certain specific interactions and its outcomes.

One of the main ideas that Ashby proposed was the idea of variety. Loosely put, variety is the number of available states a system has. For example, a switch has a variety of two – ON or OFF. A stop light has a variety of three (generally) – Red, Yellow or Green. As we increase the complexity, the variety also increases. The variety is dependent on the ability of the observer to discern them. A keen-eyed observer can discern a higher number of states for a phenomenon than another observer. Take the example of the great fictional characters, Sherlock Holmes and John Watson. Holmes is able to discern more variety than Watson, when they come upon a stranger. Holmes is able to tell the most amazing details about the stranger that Watson cannot. When we construct a model, the model lacks the original variety of the phenomenon we are modeling. This is important to keep in mind. The external variety is always much larger than the internal variety of the observer. The observer simply lacks the ability to tackle the extremely high amount of variety. To address this, the observer removes or attenuates the unwanted variety of the phenomenon and constructs a simpler model. For example, when we talk about a healthcare system, the model in our mind is pretty simple. One hospital, some doctors and patients etc. It does not include the millions of patients, the computer system, the cafeteria, the janitorial service etc. We only look at the variables that we are interested in.

Ashby explained this very well:

Another common aim that will have to be given up is that of attempting to “understand” the complex system; for if “understanding” a system means having available a model that is isomorphic with it, perhaps in one’s head, then when the complexity of the system exceeds the finite capacity of the scientist, the scientist can no longer understand the system—not in the sense in which he understands, say, the plumbing of his house, or some of the simple models that used to be described in elementary economics.

A crude depiction of model-making is shown below. The observer has chosen certain variables that are of interest, and created a similar “looking” version as the model.

Ashby elaborated on this idea as:

We transfer from system to model to lose information. When the quantity of information is small, we usually try to conserve it; but when faced with the excessively large quantities so readily offered by complex systems, we have to learn how to be skillful in shedding it. Here, of course, model-makes are only following in the footsteps of the statisticians, who developed their techniques precisely to make comprehensible the vast quantities of information that might be provided by, say, a national census. “The object of statistical methods, said R. A. Fisher, “is the reduction of data.”

There is an important saying from Alfred Korzybski – the map is not the territory. His point was that we should take the map to be the real thing. An important corollary to this, as a model-maker is:

If the model is the same as the phenomenon it models, it fails to serve its purpose. 

The usefulness of the model is in it being an abstraction. This is mainly due to the observer not being able to handle the excess variety thrown at them. This also answers one part of the question posed in the title of this post – A model ceases to be a model when it is the same as the phenomenon it models. The second part of the answer is that the model has to have some similarities to the phenomenon, and this is entirely dependent on the observer and what they want.

This brings me to the next important point – We can only manage models. We don’t manage the actual phenomenon; we only manage the models of the phenomenon in our heads. The reason being again that we lack the ability to manage the variety thrown at us.

The eminent management cybernetician, Stafford Beer, has the following words of wisdom for us:

Instead of trying to specify it in full detail, you specify it only somewhat. You then ride on the dynamics of the system in the direction you want to go.

To paraphrase Ashby, we need not collect more information than is necessary for the job. We do not need to attempt to trace the whole chain of causes and effects in all its richness, but attempt only to relate controllable causes with ultimate effects.

The final aspect of model-making is to take into consideration the temporary nature of the model. Again, paraphrasing Ashby – We should not assume the system to be absolutely unchanging. We should accept frankly that our models are valid merely until such time as they become obsolete.

Final Words:

We need a model of the phenomenon to manage the phenomenon. And how we model the phenomenon depends upon our ability as the observer to manage variety. We only need to choose certain specific variables that we want. Perhaps, I can explain this further with the deep philosophical question – If a tree falls in a forest and no one is around to hear it, does it make a sound? The answer to a cybernetician should be obvious at this point. Whether there is sound or not depends on the model you have, and if you have any value in the tree falling having a sound.

Please maintain social distance and wear masks. Stay safe and Always keep on learning…

In case you missed it, my last post was The Maximum Entropy Principle:

Storytelling at the Gemba:

In today’s post, I am looking at storytelling. We are sometimes referred to as Homo Narrans or humans who tell stories. Storytelling, oral or otherwise, is part of our culture, and part of who we are. Joseph Campbell, the American literary professor, talks about the universal nature of all stories in his famous book, The Hero with a Thousand Faces.  Campbell’s thesis, like those of the ancients—and as put forth also, but in different ways, by Freud, Jung, and others—is that by entering and transforming the personal psyche, the surrounding culture, the life of the family, one’s relational work, and other matters of life can be transformed too. Campbell’s ideas have been distilled into the famous Hero’s Journey. Loosely put, this story structure describes a hero who starts off as ordinary, faces adversities, goes through a transformation, and in the end becomes triumphant. I am inspired by Campbell’s work, but I am looking at the ideas I learned in Cybernetics.

Variety:

One of the most important ideas in Cybernetics is that of variety, a brainchild of the brilliant Ross Ashby. Ashby described variety as:

Given a set of elements, its variety is the number of elements that can be distinguished.

For example, if we consider a set of elements in {g b c g g c}, the variety is 3. Another easy example to consider is that of a light switch. A light switch has a variety of two (ON or OFF). Ashby created his most famous Law of Requisite Variety from this simple idea. The Law of Requisite Variety can be simply stated as “only variety can destroy variety.” If the regulatory agency of a system does not have the requisite variety to match the variety of its environment, it will not be able to adapt and survive. Ashby explained this using the example of a fencer:

If a fencer faces an opponent who has various modes of attack available, the fencer must be provided with at least an equal number of modes of defense if the outcome is to have the single value: attacked parried.

How does this come into play with stories? Stories are interesting only if there are conflicts. The villain is shown to have more variety than the hero. This puts the villain in control of the situation because to be in control means to have the appropriate amount of variety over the situation. The hero has to somehow overcome the lack of variety he has. In a superhero movie, if the superhero has more variety than the supervillain, then the story is not at all interesting. Per the Hero’s Journey structure, the superhero has to face adversities to make the story more interesting. This brings up the idea of variety engineering, proposed by another brilliant mind, Stafford Beer.

We can depict the varieties as below. The supervillain has much more variety than the superhero. This is shown by the larger font size for “v” depicting the variety. We can see that the variety of the supervillain is much more (>>) than that of the superhero. This is the major adversity that the superhero must overcome. This conflict makes the story interesting.

As Stafford Beer might say, the superhero has to find ways to attenuate or reduce the variety of the supervillain, and at the same time find ways to amplify his own variety. This allows him to have the requisite variety to overcome the supervillain. The squiggly line towards right in the schematic below shows the attenuation of the variety coming from the supervillain, while the curved line with the triangle on it shows the amplification of the variety from the superhero. In the below schematic, the varieties are shown to match, as indicated by the same font size for “v” in the middle. This also is an important part of the story since the final fight should not be easy for the superhero. Now we have a good superhero story. The attenuation of the variety may be achieved by not getting scared by the antics shown by the villain. The amplification may be achieved by the use of valuable information that the villain does not have access to, or by coming up with a plan that allows the hero to use his special skill.

The same structure can be seen across many of the blockbuster movies or TV shows. The interesting part is always how the variety engineering is done, and how the requisite variety is achieved by the hero, whether it is a Marvel superhero movie or “The Last Kingdom” or “Rick and Morty.”

Role of the Observer:

Ross Ashby gives further insight into this. He brings in the importance of the observer. He noted:

If two observers differ in the distinctions they can make, then they will differ in their estimates of the variety.

An easy example is to consider the set, {b a c c C a B a}. Depending on the observer, the variety of the set can be said as 3 (3 letters) or 5 (3 lowercase letters and 2 uppercase letters). The idea is easily illustrated in a Sherlock Holmes story, where the same crime scene is witnessed by Holmes and Watson. Holmes is able to make more distinctions than Watson, allowing him to achieve the requisite variety needed to solve the crime. One of the most important definitions of information in the light of distinctions come from Gregory Bateson, who described information as the difference that makes the difference. Bateson noted:

What gets onto the map, in fact, is difference, be it a difference in altitude, a difference in vegetation, a difference in population structure, difference in surface, or whatever. Differences are the things that get onto a map.

Bateson’s idea of difference that makes a difference was possibly introduced as part of an Alfred Korzybski lecture. And of course, the observer determines which differences are meaningful to be selected, and which selected differences must be further amplified. Uncertainty can be described as the lack of useful information. With this idea, the observer can reduce uncertainty by making useful distinctions.

Abstractions, an act of attenuating variety, allow an observer to identify that two things are similar, or that the two same things are different. There is no contradiction here because abstractions are not equivalencies. All we have and can have access to are abstractions. Thus, two observers can come to two different conclusions while witnessing the same phenomenon. Both may have some access to the same phenomenon but not to each other’s abstractions. This is exemplified in the Alfred Korzybski’s quote – “The map is not the territory” or the Alan Watts’ quote – “The menu is not the meal.”

We can use a great piece of advice from the German philosopher Hans-Georg Gadamer to further understand variety and uncertainty:

“Reality” always stands in a horizon of desired or feared or, at any rate, still undecided future possibilities. Hence it is always the case that mutually exclusive expectations are aroused, not all of which can be fulfilled. The undecidedness of the future permits such a superfluity of expectations that reality necessarily lags behind them.

From the observer’s standpoint, we realize that the most powerful tool to manage variety becomes the control of information. If one is able to not allow or hinder the other person’s ability to make distinctions, he can control the narrative and be in charge. We see this played out in real life too often.

People Principle:

Another important idea that comes from all of this is that the requisite variety always come from the people on the front, in the midst of facing adversities. We can notate this as:

People Principle: In any organization, the requisite variety always come from the people.

The organizational structures lack the variety needed. The requisite variety is provided as needed by the front-end employees, if they are able to.

Final Words:

“Story can mend, and story can heal.” (Joseph Campbell – The Hero with a Thousand Faces)

We are storytellers. We live and live on in stories. Make yours a good one.

I will finish with excellent advice on tackling writer’s block from one of my favorite storytellers, O. Henry (William Sydney Porter). He puts a nice “Go to the Gemba” touch:

Yes, I get dry spells. Sometimes I can’t turn out a thing for three months. When one of those spells comes on, I quit trying to work and go out and see something of life. You can’t write a story that’s got any life in it by sitting at a writing table and thinking. You’ve got to get out into the streets, into the crowds, talk with people, and feel the rush and throb of real life–that’s the stimulant for a story writer.

For those interested, I have shared some of my really short stories or Flash fiction here.

I also welcome the readers to check out the following posts that are applicable to the topic on hand:

Purpose of a System in Light of VSM:

Exploring The Ashby Space:

OODA Loop at the Gemba: (OODA loop also looks at how preventing the adversary to generate new useful information puts you in control)

Stay safe and Always keep on learning…

In case you missed it, my last post was Hermeneutics at the Gemba: