The Stories We Live By:

In today’s post, I am inspired by the idea of Metanarratives from the French philosopher, Jean-François Lyotard. Lyotard’s most famous work is The Postmodern Condition: A Report on Knowledge. He presented the term “postmodern” in this book. He defined postmodern as:

Simplifying to the extreme, I define postmodern as incredulity toward metanarratives.

A metanarrative or a grand narrative is a larger scale narrative that a group of people hold on to, to make sense of how the world is progressing around them. There is a teleological aspect to it such that the “progression” of the society can be explained. Leotard viewed this as a grand narrative of modernity, one where the society is progressing towards a future where all our problems are solved and where we all live happily ever after. The postmodern view distrusts any such grand narratives. The grand narrative is how we find meaning in the world around us.

The New World Encyclopedia defines metanarratives as follows:

Metanarrative or grand narrative or mater narrative is a term developed by Jean-François Lyotard to mean a theory that tries to give a totalizing, comprehensive account to various historical events, experiences, and social, cultural phenomena based upon the appeal to universal truth or universal values. In this context, the narrative is a story that functions to legitimize power, authority, and social customs. A grand narrative or metanarrative is one that claims to explain various events in history, gives meaning by connecting disperse events and phenomena by appealing to some kind of universal knowledge or schema. The term grand narratives can be applied to a wide range of thoughts which includes Marxism, religious doctrines, belief in progress, universal reason, and others.

Perhaps, it is because the world has grown closer together and more exposed to the different cultures that the postmodernists believe that we have lost faith in the grand narratives. Instead of grand narratives, what we have are localized small narratives that are often intertwined. Lyotard uses the Wittgenstein’s language games to explain this. Wittgenstein noted that the meaning of a word is in how we use the word. The words themselves are invariant; their meanings are not. The words are not fixed labels of things, but something we come together to agree upon while engaged in language games. As Simon Malpas notes:

 Like normal games, there are a variety of language games that may not always have rules in common. For example, in chess there are rules that allow us to move the pieces in certain ways, set out our objectives for victory and make certain moves illegal. In the same way, in science certain types of statement can be made about the world and certain aims and rules are involved in scientific enquiry and experimentation. The success or failure of a given statement is thus determined by how well it works within the rules of the language game in which it occurs.

Located in a multiplicity of language games that no longer follow a single metanarrative, an individual’s identity becomes dispersed… As language games are linked to identity, Lyotard argues that the wider range of different language games that are considered legitimate within society, the more open and pluralist that society can become. The main threat facing postmodern society is the reduction of knowledge to a single system whose only criterion is efficiency… Once the grand narratives have fallen away, we are left only with the diverse range of language games, and the aim of postmodern criticism should be to do justice to them by allowing them to be heard in their own terms.

It is easy to be mesmerized by a grand narrative. This could be a political slogan about making a country great again. It could also be the belief that the whole is always greater than sum of its parts. We might be told that we should be willing to sacrifice for the benefit of the whole. These grand narratives often lack the variety to sustain itself. The idea of the whole being greater than some of its parts is often taught in Systems Thinking. This posits the view that there is indeed an objective whole. As David M. Boje notes, a system is a fiction of the whole. The most important piece that is often ignored is the question – to whom? All systems are mental constructs that an observer or a group of observer constructs. The keyword here is the observer. The grand narrative that “the whole is greater” is based on an observer. This does not mean that another observer will see the system identically. To a patient, the healthcare system has specific needs such as affordable healthcare and this may be entirely different than the CEO managing a hospital. If we are able to answer the following questions, then we might be able to better understand the “whole” – who does the summation? From whose perspective is the whole and parts determined? For whose purpose?

Lyotard noted that no self is an island; each exists in a fabric of relations that is now more complex and mobile than ever before.

The social subject itself seems to dissolve in the dissemination of language games. The social bond is linguistic, but is not woven with a single thread. It is a fabric formed by the intersection of at least two (and in reality an indeterminate number) of language games, obeying different rules.

One single grand narrative cannot explain away the multitude of human experiences. Our role as a systems thinker is to welcome the multiple local narratives and engage in the different language games. We should challenge the rules that govern images and narratives. We should understand that the different language games may not always work together. We should welcome pluralism – the idea that multiple perspectives may be equally meaningful and valid.

It may be difficult at first to digest the postmodernist ideas. The realization that there is no singular objective reality may not be easy to accept. This realization however makes us more acceptable to welcome other perspectives of the world, the social realm. Socrates was declared wise by the oracle of Delphi because one thing Socrates knew was that he did not know anything. This type of self-reflection is possible when we give upon the metanarrative of an objective knowledge.

Please maintain social distance and wear masks. Please take vaccination, if able. Stay safe and Always keep on learning…

A podcast version of this post is available here – https://anchor.fm/harish-jose/episodes/The-Stories-We-Live-By-e11uctl

In case you missed it, my last post was Hermeneutics in Systems Thinking:

Hermeneutics in Systems Thinking:

In today’s post, I am carrying on some of the ideas from Heidegger. See the last post for more details. I have written about Hermeneutics before here.  Heidegger was a student of the great German philosopher, Edmund Husserl. Husserl pioneered the school of phenomenology. Phenomenology is the study of how things appear to us experientially. The objects we experience are the phenomena. As Susan Laverty notes:

Phenomenology is essentially the study of lived experience or the life world (van Manen, 1997). Its emphasis is on the world as lived by a person, not the world or reality as something separate from the person (Valle et al., 1989). This inquiry asks “What is this experience like?” as it attempts to unfold meanings as they are lived in everyday existence. Polkinghorne (1983) identified this focus as trying to understand or comprehend meanings of human experience as it is lived. The ‘life world’ is understood as what we experience pre-reflectively, without resorting to categorization or conceptualization, and quite often includes what is taken for granted or those things that are common sense (Husserl, 1970). The study of these phenomena intends to return and re-examine these taken for granted experiences and perhaps uncover new and/or forgotten meanings.

Husserl taught that to understand things around us, we have to go back to the things themselves. He gave a detailed methodology to make phenomenology happen. He wanted a structured approach just like in science or mathematics. Husserl believed that how we experience things can be affected by our biases about things. So, he proposed that we “bracket” our presuppositions, biases etc. and approach the thing at hand. This suspension of our presuppositions is a phenomenological reduction. It is said that Husserl would spend days with his class analyzing a trivial object such as a mailbox. His version of phenomenology was free of social, cultural and historical “grasps” on the object. The object was a standalone entity waiting to be experienced, and through this experience an understanding of the entity was possible. He suggested with his method, we are able to come to a descriptive presentation of the phenomena.

Heidegger, as Husserl’s student was very taken by the idea of phenomenology. However, Heidegger realized that we cannot be separated from our presuppositions. We can understand existence only through our existing; the way we are. Heidegger realized that the experience of a phenomenon is a personal activity, and therefore we may come up with multiple descriptions of the phenomenon. Most importantly, the process of coming up with a description is an interpretive process. We make sense of the phenomenon as an interpretive process. Heidegger’s version of phenomenology is thus termed as “hermeneutic phenomenology”, whereas Husserl’s version is termed as “transcendental phenomenology”. Heidegger realized that the knowledge we achieve at any point in time is incomplete, and is contingent on our existence at that point in time. Our relationship to the phenomenon is affected by who we are, where we are, when we are and how we are experiencing the phenomenon.

A key point in hermeneutics is the hermeneutic circle. This circle is actually a recursion. Hermeneutics is generally associated with interpreting a text. Generally, when we start to read a part of the text, we get an idea of what the whole of the text stands for. As we get more into the text, we get a better understanding of the part, which helps with a better understanding of the whole text, and so on. This can be viewed as a recursive function. The uniqueness of our worldview comes from the recursive nature of our experiential living. We keep updating our worldview based on the current worldview which is impacted by our past worldview. And round and round we go.

Heidegger’s view that we cannot assume freedom from our presuppositions is an important thing to keep in mind in Systems Thinking. This reaffirms the idea that we are not able to experience a singularly objective reality. Reality is multidimensional, and have many variations contingent on many social factors. The circularity of hermeneutics is explained well by M. N. Babu:

The most important consequence of the circularity of understanding for hermeneutics that there is no pure starting point for understanding because every act of understanding takes place within a finite historically conditioned horizon, within an already understood frame of reference. It is no longer a question of how we are to enter the hermeneutical circle, because human consciousness is always already in it. We understand only by constant reference to what we have already understood, namely, our past and anticipated experience. The experiencing and reflecting subject is never a tabula rasa upon which the understanding of raw experience inscribes its objective character, rather, all experience and reflection are the result of a confrontation between one’s pre-understanding or even prejudice and new or perhaps strange objects. The inevitable presence of pre-understanding or prejudice is not necessarily the distortion of the meaning of an object by an arbitrary subject, rather, it is the very condition for any understanding of all. Heidegger, however, contends that presuppositions are the very condition for any reception of the object whatsoever. His notions of the ontological character of understanding and the primordial connection of subject and object in their pre- understanding and the primordial connection of subject and object in their pre-reflective relational whole provides the foundation for this contention. For him, all interpretation is a derivative form of a prior understanding, in which the prior relationship between subject and object is brought to explication.

How does one proceed when we realize that we cannot be free of our presuppositions? Heidegger advises that we need to get into the circle in the right way. Hans-Georg Gadamer provides clarity on this. As Jean Grondin notes:

Gadamer takes up Heidegger’s suggestion that the important thing is to get into the circle in the right way, but for him this mainly means that the “prejudiced” nature of our understanding should be recognized as that which makes understanding possible in the first place. This is what he calls the “ontological” and positive aspect of the hermeneutical circle. He emphasizes the ontological nature of the circle to fight against the false ideal of a presupposition‐less type of knowledge which would have been imposed upon the humanities by the objectivity requirement of exact science. His aim in highlighting the hermeneutical circle is to liberate the humanities from this alienating model. But does this mean that all presuppositions, prejudices, and anticipations are valid? Obviously not, since this would call into question the very idea of truth, which a book entitled Truth and Method surely wants to defend. Gadamer does maintain the distinction between adequate and inadequate anticipations. According to his best account of this key critical difference, it is through temporal distance and the work of history that we are able to make this distinction.

The most important thing in the process of making sense of a phenomenon is to understand the context. If the context is not understood, we fall into the trap of relativism. Relativism is the idea that all views are equally valid. A better nuanced version of this is pluralism. Pluralism is the idea that there are multiple views of a phenomenon that are different but equally valid. The difference between pluralism and relativism is in understanding the context. As we have been discussing, this understanding requires hermeneutical phenomenology. When we are aware that our understanding is always incomplete and imperfect, we are more open to going through the self-correcting hermeneutic cycle. We are open to challenge what we think we know, and we welcome scrutiny of our ideas. We put our assumptions open for all to see. Rather than being stuck with the realization that our views are imperfect and incomplete, we learn to cope with the world.

The great Systems Thinker, C. West Churchman said that the systems approach begins when first you see the world through the eyes of another.

We can only know things in terms of things we already know. From this standpoint, when we are looking at a new phenomenon, we have to look at it in terms of things we already know. If we are looking at a social “system”, then we have to always start from things that are common. The basis of all that is common in a social realm is the humanity in us all, and that is a good place to start. This is my takeaway from Churchman’s advice.

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 The Being-Question in Systems Thinking:

The Being-Question in Systems Thinking:

In today’s post, I am looking at the Being-question from Martin Heidegger. Heidegger is a philosopher I put off studying mainly because he was a Nazi sympathizer. His ideas are said to be of utmost importance for the twentieth century and he influenced many of the post-modern philosophers such as Sartre, Foucault, Derrida, Rorty etc. Heidegger’s main philosophical work is “Being and Time”.

At that time, the prevalent view about how we view the world was based on the distinction between the subject and the object. The subject, let’s say an observer, is able to stand outside and observe the world. The world is independent of the observer. The observer is able to study the world and using their rational mind to come to meaningful conclusions. This view was made famous by the French philosopher, René Descartes. Descartes emphasized the difference between the subject and the object. The observer themselves are not part of the observation. What is observed (the object) is part of an objective reality that is readily accessible to everyone. From this standpoint, we come to see systems as physical entities of the world that is waiting there to be objectively observed and understood by everyone.

Heidegger wanted to turn this view upside down. He viewed the idea of trying to prove an objective reality as a scandalous activity. He did not deny the subject and the object. However, he viewed the subject as being a part of the world; an embedded being in the world. Heidegger thought that the question of “what exists?” is a useless activity. He realized that the question – “what does it mean to be existing?” was more meaningful.

Michael Gelven, who authored one of the most accessible books on Heidegger notes:

Descartes not only asks whether such a thing as material substance exists, he actually tells us what it means for such a thing to exist: if it takes up space it is a material thing that exists. Heidegger, however, argues there is an even more fundamental question that can be asked: What does it mean to exist at all?  The question is not whether something does exist or how to characterize the existence of particular kinds of things, like material things or mental things, but simply to ask about the very meaning of Being.

To ask what it means to exist or simply to be is to engage in the most fundamental kind of questioning possible. Heidegger calls this die Frage nach den Sinn von Sein, “to question what it means to be,” or simply, “the Being-question.”

Here the word “Being” is capitalized to reflect how it was written by Heidegger and it does not stand for a Supreme Being. The Being is basically us in the world interacting with the world.

Gelven gives a great example to further the idea of the “Being-question”:

Suppose I ask “What is a jail? ” You answer, “The jail is that red-brick building down the street with bars on the windows and locks on the cells. ” In this case, the question is about an entity, and the answer provides one with characteristics that describe or identify the entity. Suppose I ask, “What does it mean to be in jail? ” In response, you say, “To be in jail is to be guilty of a crime and to be punished for it by suffering the loss of liberty. To be in jail thus is to be punished, to feel reprimanded, to suffer, possibly to be afraid, to be lonely, to feel outcast, etc. ” The second question is answered by reference to what it means to exist in various ways, such as being guilty or being unfree. The question What is a jail? is answered by the description of other entities, bars in the windows, locks, unsavory patrons; but the question of the meaning of anything is answered by reference to other meanings. In this we simply recognize there must be a parallel between the kind of question asked and the kind of answers given.

But suppose I press this distinction and ask Which question is prior? A moment’s reflection will assure us that what it means to be in jail is the reason or the ground for the jail being built the way it is. In other words, what it means to be in jail is prior to what kind of thing a jail is, for the meaning determines the entity. If I understand what it means to be in jail, I will know what is required to make a jail. So, in the formal sense of what explains what, meaning precedes entity. The inquiry into what it means to be in jail is not only different from the question about what kind of thing is a jail, it is also prior to it, for the meaning ultimately explains the entity.

The problem with believing that there is an objective reality ready for everyone to access is that we take others for granted and also view them as part of the “objective” reality. We don’t realize that most of what we see and believe are contingent on our past experiences, biases, worldviews etc. These are not necessities. It would be a categorical error to assume that the conditions of contingencies are actually conditions of necessities. An easy way to explain the difference between contingency and necessity is to think of a red triangle. The color “red” is contingent on the direction I gave you. I could have said blue instead of red or any other color for that matter. However, it is necessary that you have three sides to the triangle. You cannot have two sides or four sides for the triangle since then it ceases to be a triangle.

When we assume that systems are physical entities of the world, we fall into the categorical error. We bring in our biases and worldviews and impose them on others. Similar to the jail example above, if we simply ask “what is a hospital and how can we improve the hospital?”, we get answers that go nowhere. If instead, we try to ask the question – “what is it like to be a patient in the hospital?”, and try to see this from another person’s viewpoint, we might be able to make some headway. The world as we see it, is our construction of our being in the world. We are in a social realm, and we cope with the world by being part of it, rather than being apart from it.

Gelven also gives another example:

I ask: What is the mind? This question is the traditional metaphysical one; it asks for classification and identification. I also ask: Do I have a mind that is anything more than the physical brain? Here the question is one of whether something exists. Let us now re-ask this all-important question in terms of Heidegger’s revolution. What kind of question could we ask? What does it mean to think? Notice what happens when we rephrase the question in this way. By asking What does it mean to think? I avoid completely the metaphysical questions of whether something exists or what kind of thing it is. Yet, at the same time, the question probes just as deeply into what I want to know.

How we are in the world depends on our affordances to be in this world. As the great Cybernetician/Enactivist Francesco Varela pointed out – Our cognition is directed toward the world in a certain way: it is directed toward the world as we experience it. For example, we perceive the world to be three/ dimensional, macroscopic, colored, etc.: we do not perceive it as composed of subatomic particles. To this, I will also add Cybernetician Bruce Clarke’s quote- We still have a hard time taking for real that all knowledge of the environment depends upon the specific realities of the systems that observe it. The systemic reality of the environment is to be both the precondition and the product of an observing system.

The next time when someone asks you to improve the system, remember to use the Being-question. I will finish with a quote from Heidegger:

In order to be who we are, we human beings remain committed to and within the being of language, and can never step out of it and look at it from somewhere else. Thus, we always see the nature of language only to the extent to which language itself has us in view, has appropriated us to itself. That we cannot know the nature of language—know it according to the traditional concept of knowledge defined in terms of cognition as representation—is not a defect, however, but rather an advantage by which we are favored with a special realm, that realm where we, who are needed and used to speak language, dwell as mortals.

Please maintain social distance and wear masks. Stay safe and Always keep on learning… In case you missed it, my last post was Round and Round We Go:

Round and Round We Go:

In today’s post, I am looking at a simple idea – Loops, and will follow it up with Heinz von Foerster’s ideas on second order Cybernetics. A famous example of a loop is “PDCA”. The PDCA loop is generally represented as a loop – Plan-Do-Check-Act-Plan-Do…, and the loop is represented as an iterative process where it goes on and on. To me, this is a misnomer and misrepresentation. These should be viewed as recursions. First, I will briefly explain the difference between iteration and recursion. I am using the definitions of Klaus Krippendorff:

Iteration – A process for computing something by repeating a cycle of operations.

Recursion – The attribute of a program or rule which can be applied on its results indefinitely often.

In other words, iteration is simply repetition. In a program, I can say to print the word “Iteration” 5 times. There is no feedback here, other than to keep count of the times the word was printed on screen. On the other hand, in recursion, the value of the first cycle is fed back into the second cycle, the output of which is fed into the third cycle and so on. Here circular feedback is going on. A great example of a recursive function is the Fibonnaci sequence. The Fibonacci sequence is expressed as follows:

Fn = Fn-1 + Fn-2, for n > 1

Fn = 1, for n = 0 or 1

Here, we can see that the previous value is fed into the equation to create a new value, and this is an example of recursion.

From the complexity science standpoint, recursions lead to interesting phenomenon. This is not an iterative non-feedback loop any longer, where you come back to the same point again and again. With recursion, you get to circular causality with each loop, and you enter a new state altogether. Each loop is directly impacted by the previous loop. Anything that leads back to its original starting point doesn’t lead to emergence and can actually lead to a paradox. A great example is the liar paradox. In a version of this, a card has a statement written on both sides of a card. They are as follows:

  1. The statement on the other side of this card is FALSE.
  2. The statement on the other side of this card is TRUE.  

This obviously leads to a paradox when you follow it along a loop. You do not get to a new state with each iteration. Douglas Hofstadter wonderfully explained this as a mirror mirroring itself. However, with recursion, a wonderful emergence can happen, as we see in complexity science. Circular causality and recursion are ideas that have strong footing in Second Order Cybernetics. A great example of this is to look at the question – how do we make sense of the world around us? Heinz von Foerster, the Socrates of Cybernetics, has a lot to say about this. As Bernard Scott notes:

For Heinz von Foerster, the goal of second-order cybernetics is to explain the observer to himself, that is, it is the cybernetics of the cybernetician. The Greek root of cybernetics, kubernetes, means governor or steersman. The questions asked are; who or what steers the steersman, how is the steersman steered and, ethically, how does it behoove the steersman to steer himself? Von Foerster begins his epistemology, in traditional manner, by asking, “How do we know?” The answers he provides-and the further questions he raises-have consequences for the other great question of epistemology, “What may be known?” He reveals the creative, open-ended nature of the observer’s knowledge of himself and his world.

Scott uses von Foerster’s idea of undifferentiated coding to explore this further. I have written about this before here.

Undifferentiated coding is explained as below:

The response of a nerve cell encodes only the magnitude of its perturbation and not the physical nature of the perturbing agent.

Scott continues:

Put more specifically, there is no difference between the type of signal transmitted from eye to brain or from ear to brain. This raises the question of how it is we come to experience a world that is differentiated, that has “qualia”, sights, sounds, smells. The answer is that our experience is the product of a process of computation: encodings or “representations” are interpreted as being meaningful or conveying information in the context of the actions that give rise to them. What differentiates sight from hearing is the proprioceptive information that locates the source of the signal and places it in a particular action context.

Von Foerster explained the circular relationship between sense data and experiences as below:

The motorium (M) provides the interpretation for the sensorium (S) and the sensorium provides the interpretation for the motorium.

How we make sense depends on how we experience, and how we experience depends upon how we make sense. As Scott notes, we can explain the above relationship as follows:

S = F(M). Sensorium, S, is a function of motorium, M.

M = G(S). Motorium, M, is a function of sensorium, S.

Von Foerster pointed out that this is an open recursive loop, since we can replace M with G(S).

S=F(G(S))

With more replacements for the “S”, this equation becomes an open recursive loop as follows:

S=F(G(F(G(F(G(…………G(S)))))……

Scott continues:

Fortunately, the circularity is not vicious, as in the statement “I am a liar”. Rather, it is virtuous or, as von Foerster calls it, it is a creative circle, which allows us to “transcend into another domain”. The indefinite series is a description of processes taking place in sequence, in “time”, with steps t, t+1, t+2 and so on. (I put “time” in quotes as a forward marker for discussion to come). In such indefinite recursive expressions, solutions are those values of the expression which, when entered into the expression as a base, produce themselves. These are known as Eigen values (self-values). Here we have the emergence of stabilities, invariances. The “objects” that we experience are “tokens” for the behaviors that give rise to those experiences. There is an “ultimate” base to these recursions: once upon a “time”, the observer came into being. As von Foerster neatly puts it, “an observer is his own ultimate object”.

The computations that give rise to the experience of a stable world of “objects” are adaptations to constraints on possible behaviors. Whatever else, the organism, qua system, must continue to compute itself, as a product. “Objects” are anything else it may compute (and recompute) as a unitary aspect of experience: things, events, all kinds of abstraction. The possible set of “objects” it may come to know are limited only by the organism’s current anatomy and the culture into which she is born.

I have written about this further here – Consistency over Completeness.

Heinz von Foerster said – The environment contains no information; it is as it is. We are informationally closed entities, which means that information cannot come from outside to inside. We make meanings out of the perturbations and we construct a reality that our interpretative framework can afford.

I will finish with a great observation from the Cybernetist philosopher Yuk Hui:

Recursivity is a general term for looping. This is not mere repetition, but rather more like a spiral, where every loop is different as the process moves generally towards an end, whether a closed one or an open one.

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

In case you missed it, my last post was Observing with Your Hands:

References:

  1. M. C. Escher Spiral
  2. Second Order Cybernetics as Cognitive Methodology. Bernard Scott
  3. A Dictionary of Cybernetics. Klaus Krippendorff

Observing with Your Hands:

In today’s post, I am looking at the ideas inspired by mirror neurons. Mirror neurons are a class of neurons that activate when someone engages in an activity or when they observe the same activity being performed by someone else. It was first identified by a group of Italian neurophysiologists led by Giacomo Rizzolatti in the 1980s. They were studying macaque monkeys. As part of their research, they placed electrodes in the monkeys’ brains to study hand and mouth motions. The story goes that the electrodes sent signals when the monkeys observed the scientists eating peanuts. The same neurons that fired when the monkeys were eating peanuts fired when they merely observed the same action. Several additional studies indicate that the mirror neurons are activated to respond to goal-oriented actions. For example, when the scientist covered the peanut bowl, and performed the action of picking a peanut and eating, the mirror neurons still fired even though the monkeys could not see the peanut bowl. However, when the scientist simply mimicked the action of taking a peanut without a peanut bowl, the neurons did not fire. There have been several hypotheses regarding the mirror neurons such as they facilitate learning by copying, and that they are the source for empathy.

The most profound idea about mirror neurons is that action execution and action observation are tightly coupled. Our ability to interpret or comprehend other’s actions involve our own motor system. For example, when we observe someone doing an action, depending upon whether we have performed the action adds depth to how we can observe the action being performed. If I am watching a ballet and the ballerina performs a difficult move, I may not fully grasp what I have seen since I do not know ballet and because I have never performed it. However, if I watch a spin bowler in Cricket throwing an off-spin, I will be able to grasp it better and possibly tell how the ball is going to spin. This is because I have played a lot of Cricket as a youth. The same with a magician performing a sleight of hand.

The idea of mirror neurons brings an extra depth to the meaning of going to the gemba. Going to gemba is a key tenet of Toyota Production System. We go to the gemba, where the action is, to grasp the current situation. We go there to observe. Gemba, it is said, is our best teacher. When we go there to observe the work being performed, we may get a different experience depending upon whether we ourselves have performed the work or not. Heinz von Foerster, the Socrates of Cybernetics, said – if you want to see, learn how to act. He was talking about the circular loop of sensorium and motorium. In order to see, there has to be interaction between the sensorium and motorium.

In a similar way, Kiichiro Toyoda, the founder of Toyota Motor Corporation is said to have remarked that engineers would never amount to anything unless they had to wash their hands at least three times a day; the evidence they were getting their hands dirty from real work.

I will finish with a great advice from Taiichi Ohno:

Don’t look with your eyes, look with your feet. Don’t think with your head, think with your hands.

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

In case you missed it, my last post was The Extended Form of the Law of Requisite Variety:

Image Reference – Now You See It. Now You Don’t (Bill Tarr)

The Extended Form of the Law of Requisite Variety:

This is a follow-up to my last week’s post – Notes on Regulation: In today’s post, I am looking at the Arvid Aulin-Ahmavaara’s extended form of the law of requisite variety (using Francis Heylighen’s version). As I have noted previously, Ross Ashby, the great mind and pioneer of Cybernetics came up with the law of requisite variety (LRV). The law can be stated as only variety can absorb variety. Here variety is the number of possible states available for a system. This is equivalent to statistical entropy. For example, a coin can be shown to have a variety of two – Heads and Tails. Thus, if a user wants a way to randomly choose one of two outcomes, the coin can be used. The user can toss the coin to randomly choose one of two options. However, if the user has 6 choices, they cannot use the coin to randomly choose one of six outcomes efficiently. In this case, a six-sided die can be used. A six-sided die has a variety of six. This is a simple explanation of variety absorbing variety.

The controller can find ways to amplify variety to still meet the external variety thrown upon the system. Let’s take the example of the coin and six choices again. It is possible for the user to toss the coin three times or use three coins, and use the three coin-toss results to make a choice (the variety for three coin-tosses is 8). This is a means to amplify variety in order to acquire requisite variety. From a cybernetics standpoint, the goal of regulation is to ensure that the external disturbances do not reach the essential variables. The essential variables are important for a system’s viability. If we take the example of an animal, some of the essential variables are the blood pressure, body temperature etc. The essential variables must be kept within a specific range to ensure that the animal continues to survive. The external disturbances are denoted by D, the essential variables by E and the actions available to the regulator as A. As noted, variety is expressed as statistical entropy for the variable. As Aulin-Ahmavaara notes – If A is a variable of any kind, the entropy H(A) is a measure of its variety.

With this background, we can note the extended form of the Law of Requisite Variety as:

H(E) ≥ H(D) – H(A) + H(A|D) – B

The H portions of the term represents the statistical entropy for the term. For example, H(E) is the statistical entropy for the essential variables. The larger the value for H, the more the uncertainty around the variable. The goal for the controller is to keep the H(E) as low as possible since a larger value for the entropy for the essential variables indicate a larger range of values for the essential variables. If the essential variables are not kept to a small range of values, the viability of the organism is compromised. We can now look at the other terms of the equation and see how the value for H(E) can be maintained at a lower value.

Heylighen notes:

This means that H(E) should preferably be kept as small as possible. In other words, any deviations from the ideal values must be efficiently suppressed by the control mechanism. The inequality expresses a lower bound for H(E): it cannot be smaller than the sum on the right-hand side. That means that if we want to make H(E) smaller, we must try to make the right-hand side of the inequality smaller. This side consists of four terms, expressing respectively the variety of disturbances H(D), the variety of compensatory actions H(A), the lack of requisite knowledge H(A|D) and the buffering capability B.

As noted, D represents the external disturbances, and H(D) is the variety of disturbances coming in. If H(D) is large, then it also increases the value generally for H(E). Thus, an organism in a complex environment is more likely to face some adversities that might drive the essential variables outside the safe range. For example, you are less likely to die while sitting in your armchair than while trekking through the Amazonian rain forest or wandering through the concrete jungle of a megacity. A good rule of thumb for survivability would be to avoid environments that have a larger variety for disturbances.

The term H(A) represents the variety of actions available to counter the disturbances. The more variety you have for your actions, the more likely you are able to counteract the disturbances. At least one of them will be able to solve the problem, escape the danger, or restore you to a safe, healthy state. Thus, the Amazonian jungle may not be so dangerous for an explorer having a gun to shoot dangerous animals, medicines to treat disease or snakebite, filters to purify water, and the physical condition to run fast or climb in trees if threatened. The term H(A) enters the inequality with a minus (–) sign, because a wider range of actions allows you to maintain a smaller range of deviations in the essential variables H(E).

The term H(A|D) represents a conditional state. It is also called the lack of requisite knowledge. It has a plus sign since it indicates a “lack”. It is not enough that you have a wide range of actions, you have to know which action will be effective. If you have minimal knowledge, then your best strategy is to try out each action at random, and this is highly inefficient and ineffective if time is not on your side. For example, there is little use in having a variety of antidotes for different types of snakebites if you do not know which snake bit you. H(A|D) expresses your uncertainty about performing an action A (e.g., taking a particular antidote) for a given disturbance D (e.g., being bitten by a particular snake). The larger your uncertainty, the larger the probability that you would choose a wrong action, and thus fail to reduce the deviation H(E). Therefore, this term has a “+” sign in the inequality: more uncertainty (= less knowledge) produces more potentially lethal variation in your essential variables.

The final term B stands for buffering (passive regulation). It expresses your amount of protective reserves or buffering capacity. Better even than applying the right antidote after a snake bite is to wear protective clothing thick enough to stop any snake poison from entering your blood stream. The term is negative because higher capacity means less deviation in the essential variables.

The law of requisite variety expresses in an abstract form what is needed for an organism to prevent or repair the damage caused by disturbances. If this regulation is insufficient, damage will accumulate, including damage to the regulation mechanisms themselves. This produces an acceleration in the accumulation of damage, because more damage implies less prevention or repair of further damage, and therefore a higher rate of additional damage.

The optimal formation for the Law of Requisite Variety occurs when the minimum value for H(E) is achieved, and when there is no lack of requisite knowledge. The essence of regulation is that disturbances happen all the time, but that their effects are neutralized before they have irreparably damaged the organism. This optimal result of regulation is represented as:

H(E)min = H(D) – H(A) – B

I encourage the reader to check out my previous posts on the LRV.

Getting Out of the Dark Room – Staying Curious:

Notes on Regulation:

Storytelling at the Gemba:

Exploring The Ashby Space:

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

In case you missed it, my last post was Notes on Regulation:

References:

[1] Cybernetic Principles of Aging and Rejuvenation: the buffering-challenging strategy for life extension – Francis Heylighen

[2] The Law of Requisite Hierarchy – A. Y. Aulin-Ahmavaara

Notes on Regulation:

In today’s post, I am looking at the idea of regulation. I talked about direct and indirect regulation in my previous post. In today’s post, I will look at passive and active regulation.

Ashby viewed a system as a selection of variables chosen by an observer for the purpose of sensemaking and control. The observer is looking not at what the system is (what the variables are), but at what the system does. In other words, the observer is interested in the behavior of the system. The observer is interested in influencing the behavior so that the system is maintained in certain desirable states. Of all possible states, the system can be in, the observer would like to keep the system in a chosen few states. To achieve this, the observer has to model the behavior of the system. As J. Achterbergh and D. Vriens note:

we should “model” the behavior of this entity (system) in such a way that we can understand how it behaves in the first place, and how this behavior reacts to “influences.” One could say that (at least) two kinds of influences on behavior (input) can be discerned: “disturbances” – causing the concrete entity to behave “improperly,” and “regulatory actions” – causing “proper” behavior (by preventing or dealing with disturbances).

The general understanding is that the environmental disturbances cause the system to behave improperly. The role of the regulator is to prevent the disturbances from reaching the essential variables of the system. The controller sets the target for the system, while the regulator acts on realizing the target. An easy example to distinguish the controller and the regulator is with a thermostat. The homeowner in this case is the controller, while the thermostat is the regulator. The homeowner decides the range for the thermostat, and all the thermostat can do is turn on or off depending upon the temperature inside the house. The regulator is not able to change the target; only the controller can change the target.

The goal of the regulator, as noted above, is to ensure that the disturbances from outside do not impact the essential variables of the system. Ashby noted:

An essential feature of the good regulator is that it blocks the flow of variety from disturbances to essential variables.

J. Achterbergh and D. Vriens expand this further:

Regulators block variety flowing from disturbances to essential variables. The more variety they block, the more effective the regulator. The most effective regulator is the one that blocks all the variety flowing from disturbances to essential variables… We can now also define regulation as the activity performed by the regulator. That is, regulation is “blocking the flow of variety from disturbances to essential variables.” If the more general description of essential variables is used (i.e., those variables that must be kept within limits to achieve some goal) then the purpose of regulation is that it enables the realization of this goal. If the goal is the survival of some concrete system, then the purpose of regulation is trying to keep the values of its essential variables within the limits needed for survival, in spite of the values of disturbances.

This is a good place to introduce the main law of Cybernetics – the law of requisite variety (LRV). LRV is the brainchild of Ross Ashby, the most prolific thinker and pioneer of Cybernetics. LRV states that only variety can absorb variety. Here variety is the number of possible states. For example, a light switch has a variety of two – ON or OFF. If the user just wants the light to be turned on or off, then the light switch can meet that variety. However, if the user wants the light to be dimmed down or up, then the situation calls for a lot more variety than two. Here, a light switch with a variety of two cannot absorb the variety “thrown” at it. However, a dimmer switch with an indefinite amount of variety can achieve this.

Ashby was inspired by Claude Shannon’s tenth theorem. There is an upper limit for the amount of variety the regulator can absorb. The controller will need to find ways to attenuate variety (filter out unwanted variety thrown at the system) and amplify internal variety such that the requisite variety is achieved. A simple example of attenuating variety is the big sign on the front of a fast-food place. The customer should not go into the fast-food place and ask to buy a car. Since there is an upper limit to a single regulator, the controller has to use multiple regulators linked to achieve amplification of variety. The fast-food place can use more employees during rush-hour to meet with the extra variety thrown at it. This is an example of amplifying variety.

Ashby talked about two types of regulation. This has been explained as Passive and Active regulation by J. Achterbergh and D. Vriens. Passive regulation does not make any selection. We can state that passive regulation is always working. An easy example to explain this is the shell of a turtle. It does not make any selections. J. Achterbergh and D. Vriens explained this as follows:

In the case of passive regulation there exists a passive block between the disturbances and the essential variables. This passive block, for instance the shell of a turtle, separates the essential variables from a variety of disturbances. It is characteristic of passive regulation that it does not involve selection… the regulator does not select a regulatory move dependent on the occurrence of a possibly disturbing event, for the block is given independent of disturbances. Because no selection is involved, the passive “regulator” does not need information about changes in the state of the essential variable or about disturbances causing such changes to perform its regulatory activity.

Francis Heylighen explained passive regulation as buffering:

 Buffering—at least in the cybernetic sense—is a passive form of regulation: the system dampens or absorbs the disturbances through its sheer bulk of protective material. Examples of buffers are shock absorbers in a car, water reservoirs or holding basins dampening fluctuations in rainfall, and the fur that protects a warm-blooded animal from variations in outside temperature. The advantage is that no energy, knowledge or information is needed for active intervention. The disadvantage is that buffering is not sufficient for reaching goals that are not equilibrium states in themselves, because moving away from equilibrium requires active intervention. For example, while a reservoir makes the flow of water more even, it cannot provide water in regions where it never rains. Similarly, fur alone cannot maintain a mammal body at a temperature higher than the average temperature of the surroundings: that requires active heat production.

Active regulation requires a selection of activity and requires information. J. Achterbergh and D. Vriens explained active regulation as follows:

In the case of active regulation, the regulator needs to select a regulatory move. Dependent on either the occurrence of a change of the state of the essential variable or of a disturbance, the regulator selects the regulatory move to block the flow of variety to the essential variables. Because it has to select a regulatory move, the active regulator either needs information about changes in the state of the essential variable or about the disturbances causing such changes in order to perform its regulatory function.

There are two forms of active regulation – feedforward (cause-controlled) and feedback (error-controlled). In feedforward regulation, the regulator anticipates and acts when it senses the disturbances prior to having any impact on the essential variable. Heylighen explained this as:

In feedforward regulation, the system acts on the disturbance before it has affected the system, in order to prevent a deviation from happening. For example, if you perceive a sudden movement in the vicinity of your face, you will close your eyelids before any projectile can hit it, so as to prevent potential damage to your eyeball. The disadvantage that it is not always possible to act in time, and that the anticipation may turn out to be incorrect, so that the action does not have the desired result. For example, the projectile may not have been directed at your eyes, but at a different part of your face. By shutting your eyes, you make it more difficult to avoid the actual impact.

In feedback regulation, the regulator acts only after the essential variable is impacted.

In feedback regulation, the system neutralizes or compensates the deviation after the disturbance has pushed the system away from its goal, by performing an appropriate repair action. For example, a thermostat compensates for a fall in temperature by switching on the heating, but only after it detected a lower than desired temperature. For effective regulation, it suffices that the feedback is negative—i.e. reducing the deviation—because a sustained sequence of corrections will eventually suppress any deviation. The advantage is that there is no need to rely on a complex, error-prone process of anticipation on the basis of imperfect perceptions: only the direction of the actual deviation has to be sensed. The disadvantage is that the counteraction may come too late, allowing the deviation to cause irreversible damage before it was effectively suppressed.

Ashby viewed feedforward as reacting to threat, and feedback as reacting to disaster. Feedforward control (cause controlled) generally comes from feedback control (error controlled). We should have a somewhat good knowledge of the situation’s behavior and this comes from previous feedback experiences.

In next week’s post, I will look at the extended form of the Law of Requisite Variety. I will finish this post with an example from J. Achterbergh and D. Vriens to further explain the three forms of regulation with an example of a medieval knight:

To illustrate these different modes of regulation, imagine a medieval knight on a battlefield. One of the essential variables might be “pain,” with the norm value “none.” In combat, the knight will encounter many opponents with different weapons all potentially threatening this essential variable. To deal with these disturbances, he might wear suitable armor: a passive block. If a sword hits him nevertheless (e.g., somewhere, not covered by the armor), he might withdraw from the fight, treat his wounds and try to recover: an error-controlled regulatory activity, directed at dealing with the pain. A cause-controlled regulatory activity might be to actively parry the attacks of an opponent, with the effect that these attacks cannot harm him.

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

In case you missed it, my last post was Getting Out of the Dark Room – Staying Curious:

References:

[1] Cybernetic Principles of Aging and Rejuvenation:the buffering-challenging strategy for life extension – Francis Heylighen

[2] Social Systems Conducting Experiments – Jan Achterbergh, Dirk Vriens

Getting Out of the Dark Room – Staying Curious:

In today’s post I am looking at the importance of staying curious in the light of Karl Friston’s “Free Energy Principle” (FEP) and Ross Ashby’s ideas on indirect regulation. I have discussed Free Energy Principle here. The FEP basically states that in order to resist the natural tendency to disorder, adaptive agents must minimize surprise.

Karl Friston, the brilliant mind behind FEP noted:

the whole point of the free-energy principle is to unify all adaptive autopoietic and self-organizing behavior under one simple imperative; avoid surprises and you will last longer.

Avoiding surprises means that one has to model and anticipate a changing and itinerant world. This implies that the models used to quantify surprise must themselves embody itinerant wandering through sensory states (because they have been selected by exposure to an inconstant world): Under the free-energy principle, the agent will become an optimal (if approximate) model of its environment. This is because, mathematically, surprise is also the negative log-evidence for the model entailed by the agent. This means minimizing surprise maximizes the evidence for the agent (model). Put simply, the agent becomes a model of the environment in which it is immersed. This is exactly consistent with the Good Regulator theorem of Conant and Ashby (1970). This theorem, which is central to cybernetics, states that “every Good Regulator of a system must be a model of that system.” .. Like adaptive fitness, the free-energy formulation is not a mechanism or magic recipe for life; it is just a characterization of biological systems that exist. In fact, adaptive fitness and (negative) free energy are considered by some to be the same thing.

This idea of the agent having a model of its environment is quite important in Cybernetics. In fact, the idea of FEP can be traced back to Ashby’s ideas on Cybernetics. For an organism to survive, it needs to keep certain internal variables such as blood pressure, internal temperature etc. in a certain range. Ashby called these as essential variables, depicted by “E”. Ashby noted that the goal of regulation is to keep these essential variables in range, in the light of disturbances coming from the environment. In other words, the goal of regulation is to minimize the effect of disturbances coming in. A perfect regulation will result in no disturbances reaching the essential variables. The organism will be completely ignorant of what is going on outside in this case. When the regulation succeeds, we say that the regulator has requisite variety. It is able to counter the variety coming in from the environment. Ashby called this “the law of Requisite Variety”, and explained it succinctly as “only variety can absorb variety.” Ashby explained the direct and indirect regulation as follows:

Direct and indirect regulation occur as follows. Suppose an essential variable X has to be kept between limits x’ and x”. Whatever acts directly on X to keep it within the limits is regulating directly. It may happen, however, that there is a mechanism M available that affects X, and that will act as a regulator to keep X within the limits x’ and x” provided that a certain parameter P (parameter to M) is kept within the limits p’ and p”. If, now, any selective agent acts on P so as to keep it between p’ and p”, the end result, after M has acted, will be that X is kept between x’ and x”.

Now, in general, the quantities of regulation required to keep P in p’ and p” and to keep X in x’ to x” are independent. The law of requisite variety does not link them. Thus, it may happen that a small amount of regulation supplied to P may result in a much larger amount of regulation being shown by X.

When the regulation is direct, the amount of regulation that can be shown by X is absolutely limited to what can be supplied to it (by the law of requisite variety); when it is indirect, however, more regulation may be shown by X than is supplied to P. Indirect regulation thus permits the possibility of amplifying the amount of regulation; hence its importance.

Ashby explained the direct and indirect regulation with the following example:

Living organisms came across this possibility eons ago, for the gene-pattern is a channel of communication from parent to offspring: ‘Grow a pair of eyes,’ it says, ‘ they’ll probably come in useful; and better put hemoglobin into your veins — carbon monoxide is rare and oxygen common.’ As a channel of communication, it has a definite, finite capacity, Q say. If this capacity is used directly, then, by the law of requisite variety, the amount of regulation that the organism can use as defense against the environment cannot exceed Q. To this limit, the non-learning organisms must conform. If, however, the regulation is done indirectly, then the quantity Q, used appropriately, may enable the organism to achieve, against its environment, an amount of regulation much greater than Q. Thus, the learning organisms are no longer restricted by the limit.

A lower cognitive capacity organism may be able to survive with just relying on its gene-pattern, while a higher cognitive capacity organism has to supplement the basic gene-patterns with a learning behavior. In order to do this, it has to learn from its environment. Ashby continued:

In the same way the gene-pattern, when it determines the growth of a learning animal, expends part of its resources in forming a brain that is adapted not only by details in the gene-pattern but also by details in the environment… dictionary. While the hunting wasp, as it attacks its prey, is guided in detail by its genetic inheritance, the kitten is taught how to catch mice by the mice themselves. Thus, in the learning organism the information that comes to it by the gene-pattern is much supplemented by information supplied by the environment; so, the total adaptation possible, after learning, can exceed the quantity transmitted directly through the gene-pattern.

It is important to note that the environment does not input information into the organism. Instead, the organism perceives the environment through its action on the environment. The environment also acts on the organism, just like the organism acts on the environment. Perception is possible only through this circular causal cycle. As Ashby noted, the gene pattern for learning allows for the organism to model its environment, and this allows for the indirect regulation. Ashby explains this point further:

This is the learning mechanism. Its peculiarity is that the gene-pattern delegates part of its control over the organism to the environment. Thus, it does not specify in detail how a kitten shall catch a mouse, but provides a learning mechanism and a tendency to play, so that it is the mouse which teaches the kitten the finer points of how to catch mice. This is regulation, or adaptation, by the indirect method. The gene-pattern does not, as it were, dictate, but puts the kitten into the way of being able to form its own adaptation, guided in detail by the environment.

The Dark Room:

At this point, we can look at the idea of the dark room. This is a thought experiment in FEP. We can try to explain this also using Ashby’s ideas. If the goal of the regulator is to minimize the impact of disturbances on the essential variables, one strategy is to then go to an environment with minimum disturbances. In FEP, this thought experiment is explained similarly as – if the goal of the agent is to minimize surprise, why wouldn’t the agent find a dark room and stay in it indefinitely?

A recurrent puzzle raised by critics of these models (FEP) is that biological systems do not seem to avoid surprises. We do not simply seek a dark, unchanging chamber, and stay there. This is the “Dark-Room Problem.” 

Karl Friston offers an answer to this question:

Technically, the resolution of the Dark-Room Problem rests on the fact that average surprise or entropy H(s|m) is a function of sensations and the agent (model) predicting them. Conversely, the entropy H(s) minimized in dark rooms is only a function of sensory information. The distinction is crucial and reflects the fact that surprise only exists in relation to model-based expectations. The free-energy principle says that we harvest sensory signals that we can predict (cf., emulation theory; Grush, 2004); ensuring we keep to well-trodden paths in the space of all the physical and physiological variables that underwrite our existence. In this sense, every organism (from viruses to vegans) can be regarded as a model of its econiche, which has been optimized to predict and sample from that econiche. Interestingly, free energy is used explicitly for model optimization in statistics (e.g., Yedidia et al., 2005) using exactly the same principles.

This means that a dark room will afford low levels of surprise if, and only if, the agent has been optimized by evolution (or neurodevelopment) to predict and inhabit it. Agents that predict rich stimulating environments will find the “dark room” surprising and will leave at the earliest opportunity. This would be a bit like arriving at the football match and finding the ground empty. Although the ambient sensory signals will have low entropy in the absence of any expectations (model), you will be surprised until you find a rational explanation or a new model (like turning up a day early). Notice that average surprise depends on, and only on, sensations and the model used to explain them. This means an agent can compare the surprise under different models and select the best model; thereby eluding any “circular explanation” for the sensations at hand.

We are born with a gene pattern that allows for learning. The basic pattern is to learn, and our survival mainly comes from this. We are able to get out of the dark room because of this. We are born curious and this allows us to keep on learning. We have an inner ability to keep looking for answers and not be satisfied with status quo.

I am sure there is an important lesson for us all here with the idea of the dark room and the indirect regulation. I could simply say – stay curious and keep on learning. Or I can have you come to that conclusion on your own. As famous Spanish philosopher, José Ortega y Gasset noted – He who wants to teach a truth should place us in the position to discover it ourselves.

I will finish with a great lesson from Ashby to explain the idea of the indirect regulation:

If a child wanted to discover the meanings of English words, and his father had only ten minutes available for instruction, the father would have two possible modes of action. One is to use the ten minutes in telling the child the meanings of as many words as can be described in that time. Clearly there is a limit to the number of words that can be so explained. This is the direct method. The indirect method is for the father to spend the ten minutes showing the child how to use a dictionary. At the end of the ten minutes the child is, in one sense, no better off; for not a single word has been added to his vocabulary. Nevertheless, the second method has a fundamental advantage; for in the future the number of words that the child can understand is no longer bounded by the limit imposed by the ten minutes. The reason is that if the information about meanings has to come through the father directly, it is limited to ten-minutes’ worth; in the indirect method the information comes partly through the father and partly through another channel (the dictionary) that the father’s ten-minute act has made available.

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

In case you missed it, my last post was The Cybernetics of Ohno’s Production System:

The Cybernetics of Ohno’s Production System:

In today’s post, I am looking at the cybernetics of Ohno’s Production System. For this I will start with the ideas of ultrastability from one of the pioneers of Cybernetics, Ross Ashby. It should be noted that I am definitely inspired by Ashby’s ideas and thus may take some liberty with them.

Ashby defined a system as a collection of variables chosen by an observer. “Ultrastability” can be defined as the ability of a system to change its internal organization or structure in response to environmental conditions that threaten to disturb a desired behavior or value of an essential variable (Klaus Krippendorff). Ashby identified that when a system is in a state of stability (equilibrium), and when disturbed by the environment, it is able to get back to the state of equilibrium. This is the feature of an ultrastable system. Let’s look at the example of an organism and its environment. The organism is able to survive or stay viable by making sure that certain variables, such as internal temperature, blood pressure etc. stays in a specific range. Ashby referred to these variables as essential variables. When the essential variables go outside a specific range, the viability of the organism is compromised. Ashby noted:

That an animal should remain ‘alive’, certain variables must remain without certain ‘physiological’ limits. What these variables are, and what the limits, are fixed when the species is fixed. In practice one does not experiment on animals in general, one experiments on one of a particular species. In each species the many physiological variables differ widely in their relevance to survival. Thus, if a man’s hair is shortened from 4 inches to 1 inch, the change is trivial; if his systolic blood pressure drops from 120 mm. of mercury to 30, the change will quickly be fatal.

Ashby noted that the organism affects the environment, and the environment affects the organism: such a system is said to have a feedback. Here the environment does not simply mean the space around the organism. Ashby had a specific definition for environment. Given an organism, its environment is defined as those variables whose changes affect the organism, and those variables which are then changed by the organism’s behavior. It is thus defined in a purely functional, not a material sense. The reactionary part is the sensory-motor framework of the organism. The feedback between the reactionary part (R) of an organism (Orgm) and the environment (Envt.) is depicted below:

Ashby explains this using an example of a kitten resting near a fire. The kitten settles at a safe distance from the fire. If a lump of hot coal falls near the kitten, the environment is threatening to have a direct affect on the essential variables. It the kitten’s brain does nothing; the kitten will get burned. The kitten being the ultrastable system is able to use the correct mechanism – move away from the hot coal and maintain its essential variables in check. Ashby proposed that an ultrastable system has two feedbacks. One feedback that operates frequently while the other feedback that operates infrequently when the essential variables are threatened. The two feedback loops are needed for a system to get back into equilibrium. This is also how the system can learn and adapt. Paul Pangaro and Michael C. Geoghegan note:

What are the minimum conditions of possibility that must exist such that a system can learn and adapt for the better, that is, to increase its chance of survival? Ashby concludes via rigorous argument that the system must have minimally two feedback loops, or double feedback… The first feedback loop, shown on the left side and indicated via up/down arrows, ‘plays its part within each reaction/behavior.’ As Ashby describes, this loop is about the sensory and motor channels between the system and the environment, such as a kitten that adjusts its distance from a fire to maintain warmth but not burn up. The second feedback loop encompasses both the left and right sides of the diagram, and is indicated via long black arrows. Feedback from the environment is shown coming into an icon for a meter in the form of a round dial, signifying that this feedback is measurable insofar as it impinges on the ‘essential variables.’

Ashby depicted his ultrastable system as below:

The first feedback loop can be thought as a mechanism that cannot change itself. It is static, while the second feedback loop is able to operate some parameters so that the structure can change resulting in a new behavior. The second feedback loop acts only when the essential variables are challenged or when the system is not in equilibrium. It must be noted that there are no decisions being made with the first feedback loop. It is simply an action mechanism. It keeps doing what was working before, while the second feedback loop alters the action mechanism to result in a new behavior. If the new behavior is successful in maintaining the essential variables, the new action is continued until it is not effective any longer. When the system is able to counter the threatening situation posed by the environment, it is said to have requisite variety. The law of requisite variety was proposed by Ashby as – only variety can absorb variety. The system must be able to have the requisite variety (in terms of available actions) to counter the variety thrown upon it by the environment. The environment always possesses far more variety than the system. The system must find ways to attenuate the variety coming in, and amplify its own variety to maintain the essential variables.

Let’s look at this with an easy example of a baby. When the baby experiences any sort of discomfort, it starts crying. The crying is the behavior that helps put it back into equilibrium (removal of discomfort) since it gets the attention from its mother or other family members. As the baby grows, its desired variables also get specific (food, water, love, etc.) The action of crying does not always get it what it is looking for. Here the second feedback loop comes in, and it tries a new behavior and see if it results in a better outcome. This behavior could be to point at something or even learning and using words. The new action is kept and used, as long as it becomes successful. The baby/child learns and adapts as needed to meet its own wants and desires.

Pangaro and Geoghegan note that the idea of an ultrastable system is applicable in social realms also. To evoke the social arena, we call the parameters ‘behavior fields.’ When learning by trial-and-error, a behavior field is selected at random by the system, actions are taken by the system that result in observable behaviors, and the consequences of these actions in the environment are in turn registered by the second feedback loop. If the system is approaching the danger zone, and the essential variables begin to go outside their acceptable limits, the step function says, ‘try something else’—repeatedly, if necessary—until the essential variables are stabilized and equilibrium is reached. This new equilibrium is the learned state, the adapted state, and the system locks-in.

It is important to note that the first feedback loop is the overt behavior that is locked in. The system cannot change this unless the second feedback loop is engaged. Stuart Umpleby cites Ashby’s example of an autopilot to explain this further:

In his theory of adaptation two feedback loops are required for a machine to be considered adaptive (Ashby 1960).  The first feedback loop operates frequently and makes small corrections.  The second feedback loop operates infrequently and changes the structure of the system, when the “essential variables” go outside the bounds required for survival.  As an example, Ashby proposed an autopilot.  The usual autopilot simply maintains the stability of an aircraft.  But what if a mechanic miswires the autopilot?  This could cause the plane to crash.  An “ultrastable” autopilot, on the other hand, would detect that essential variables had gone outside their limits and would begin to rewire itself until stability returned, or the plane crashed, depending on which occurred first. The first feedback loop enables an organism or organization to learn a pattern of behavior that is appropriate for a particular environment.  The second feedback loop enables the organism to perceive that the environment has changed and that learning a new pattern of behavior is required.

Ohno’s Production System:

Once I saw that the idea of an ultrastable system may be applied to the social realm, I wanted to see how it can be applied to Ohno’s Production System. Taiichi Ohno is regarded as the father of the famous Toyota Production System. Before it was “Toyota Production System”, it was Ohno’s Production System. Taiichi Ohno was inspired by the challenge issued by Kiichiro Toyoda, the founder of Toyota Motor Corporation. The challenge was to catch up with America in 3 years in order to survive.  Ohno built his ideas with inspirations from Sakichi Toyoda, Kiichiro Toyoda, Henry Ford and the supermarket system. Ohno did a lot of trial and error. And the ideas he implemented, he made sure were followed. Ohno was called “Mr. Mustache”. The operators thought of Ohno as an eccentric. They used to joke that military men used to wear mustaches during World War II, and that it was rare to see a Japanese man with facial hair afterward. “What’s Mustache up to now?” became a common refrain at the plant as Ohno carried out his studies. (Source: Against All Odds, Togo and Wartman)

His ideas were not easily understood by others. He had to tell others that he will take responsibility for the outcomes, in order to convince them to follow his ideas. Ohno could not completely make others understand his vision since his ideas were novel and not always the norm. Ohno was persistent, and he made improvements slowly and steadily. He would later talk about the idea of Toyota being slow and steady like the tortoise. Ohno loved what he did, and he had tremendous passion pushing him forward with his vision. As noted, his ideas were based on trial and error, and were thus perceived as counter-intuitive by others.

Ohno can be viewed as part of the second feedback loop and the assembly line as part of the first feedback loop, while the survivability of the company via the metrics of cost, quality, productivity etc. can be viewed as the “essential variables”. Ohno implemented the ideas of kanban, jidoka etc. on the line, and they were followed. The assembly line could not change the mechanisms established as part of Ohno’s production system. Ohno’s production system can be viewed as a closed system in that the framework is static. Ohno watched how the interactions with the environment went, and how the essential variables were being impacted. Based on this, the existing behaviors were either changed slightly, or changed out all the way until the desired equilibrium was achieved.

Here the production system framework is static because it cannot change itself. The assembly line where it is implemented is closed to changes at a given time. It is “action oriented” without decision powers to make changes to itself. There is no point in copying the framework unless you have the same problems that Ohno faced.

Umpleby also describes the idea of the double feedback loop in terms of quality improvement similar to what we have discussed:

The basic idea of quality improvement is that an organization can be thought of as a collection of processes. The people who work IN each process should also work ON the process, in order to improve it. That is, their day-to-day work involves working IN the process (the first, frequent feedback loop). And about once a week they meet as a quality improvement team to consider suggestions and to design experiments on how to improve the process itself. This is the second, less frequent feedback loop that leads to structural changes in the process. Hence, process improvement methods, which have been so influential in business, are an illustration of Ashby’s theory of adaptation.

This follows the idea of kairyo and kaizen in the Toyota Production System.

Final Words:

It is important to note that Ohno’s Production System is not Toyota Production System is not Toyota’s Production System is not Lean. Ohno’s Production System evolved into Toyota Production System. Toyota’s production system is emergent while Toyota Production System is not. Toyota Production System’s framework can be viewed as a closed system, in the sense that the framework is static. At the same time, the different plants implementing the framework are dynamic due to the simple fact that they exist in an everchanging environment. For an organization to adapt to an everchanging environment, it needs to be ultrastable. An organization can have several ultrastable systems connected with each other resulting in a homeostasis. I will finish with an excellent quote from Mike Jackson.

The organization should have the best possible model of the environment relevant to its purposes… the organization’s structure and information flows should reflect the nature of that environment so that the organization is responsive to it.

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

In case you missed it, my last post was The Cybernetics of a Society:

The Cybernetics of a Society:

In today’s post, I will be following the thoughts from my previous post, Consistency over Completeness. We were looking at each one of us being informationally closed, and computing a stable reality. The stability comes from the recursive computations of what is being observed. I hope to expand the idea of stability from an individual to a society in today’s post.

Humberto Maturana, the cybernetician biologist (or biologist cybernetician) said – anything said is said by an observer. Heinz von Foerster, one of my heroes in cybernetics, expanded this and said – everything said is said to an observer. Von Foerster’s thinking was that language is not monologic but always dialogic. He noted:

The observer as a strange singularity in the universe does not attract me… I am fascinated by images of duality, by binary metaphors like dance and dialogue where only a duality creates a unity. Therefore, the statement.. – “Anything said is said by an observer” – is floating freely, in a sense. It exists in a vacuum as long as it Is not embedded in a social structure because speaking is meaningless, and dialogue is impossible, if no one is listening. So, I have added a corollary to that theorem, which I named with all due modesty Heinz von Foerster’s Corollary Nr. 1: “Everything said is said to an observer.” Language is not monologic but always dialogic. Whenever I say or describe something, I am after all not doing it for myself but to make someone else know and understand what I am thinking of intending to do.

Heinz von Foerster’s great insight was perhaps inspired by the works of his distant relative and the brilliant philosopher, Ludwig Wittgenstein. Wittgenstein proposed that language is a very public matter, and that a private language is not possible. The meaning of a word, such as “apple” does not inherently come from the word “apple”. The meaning of the word comes from how it is used. The meaning comes from repeat usage of the word in a public setting. Thus, even though the experience of an apple may be private to the individual, how we can describe it is by using a public language. Von Foerster continues:

When other observers are involved… we get a triad consisting of the observers, the languages, and the relations constituting a social unit. The addition produces the nucleus and the core structure of society, which consists of two people using language. Due to the recursive nature of their interactions, stabilities arise, they generate observers and their worlds, who recursively create other stable worlds through interacting in language. Therefore, we can call a funny experience apple because other people also call it apple. Nobody knows, however, whether the green color of the apple you perceive, is the same experience as the one I am referring to with the word green. In other words, observers, languages, and societies are constituted through recursive linguistic interaction, although it is impossible to say which of these components came first and which were last – remember the comparable case of hen, egg and cock – we need all three in order to have all three.

Klaus Krippendorff defined closure as follows – A system is closed if it provides its own explanation and no references to an input are required. With closures, recursions are a good and perhaps the only way to interact. As organizationally closed entities, we are able to stay viable only as part of a social realm. When we are part of a social realm, we have to construct reality with reference to an external reference. Understanding is still generated internally, but with an external point of reference. This adds to the reality of the social realm as a collective. If the society has to have an identity that is sustained over time, its viability must come from its members. Like a set of nested dolls, society’s structure comes from participating individuals who themselves are embedded recursively in the societal realm. The structure of the societal or social realm is not designed, but emergent from the interactions, desires, goals etc. of the individuals. The society is able to live on while the individuals come and go.

I am part of someone else’s environment, and I add to the variety of their environment with my decisions and actions (sometimes inactions). This is an important reminder for us to hold onto in light of recent world events including a devastating pandemic. I will finish with some wise words from Heinz von Foerster:

A human being is a human being together with another human being; this is what a human being is. I exist through another “I”, I see myself through the eyes of the Other, and I shall not tolerate that this relationship is destroyed by the idea of the objective knowledge of an independent reality, which tears us apart and makes the Other as object which is distinct from me. This world of ideas has nothing to do with proof, it is a world one must experience, see, or simply be. When one suddenly experiences this sort of communality, one begins to dance together, one senses the next common step and one’s movements fuse with those of the other into one and the same person, into a being that can see with four eyes. Reality becomes communality and community. When the partners are in harmony, twoness flows like oneness, and the distinction between leading and being led has become meaningless.

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

In case you missed it, my last post was Consistency over Completeness:

Source – The Certainty of Uncertainty: Dialogues Introducing Constructivism By Bernhard Poerksen