The Reality of Informationally Closed Entities:

In today’s post, I am looking at the idea of “informationally closed”. The idea of informational closure was first proposed by Ross Ashby. Ashby defined Cybernetics as a study of systems that are informationally tight. Ashby wanted cyberneticians to look at all the possibilities that a system can be in. Here the system refers to a selection of variables that the observer has chosen. Ashby noted that we should not look at what individual act a system produces ‘here and now’, but at all the possible behaviors it can produce. For example, he asked why does the ovum grows into a rabbit, and not a dog or a fish? Ashby noted that this is strictly related to information, and not energy:

Growth of some form there will be; cybernetics asks “why should the changes be to the rabbit-form, and not to a dog-form, a fish-form or even to a teratoma-form?” Cybernetics envisages a set of possibilities much wider than the actual, and then asks why the particular case should conform to its usual particular restriction. In this discussion, questions of energy play almost no part – the energy is simply taken for granted. Even whether the system is closed to energy or open is often irrelevant; what is important is the extent to which the system is subject to determining and controlling factors. So, no information or signal or determining factor may pass from part to part without its being recorded as a significant event. Cybernetics might, in fact, be defined as the study of systems that are open to energy by closed to information and control – systems that are information-tight.

Ashby’s main point regarding this is that the machine or the system under observation selects its actions from a set of possible actions, and this will remain the same until there is a significant event that causes it to alter the set of possible actions. The action of the system is entirely based on its structure, and not because an external agent is choosing that action for the system. The external agent is only triggering or perturbing the system, and the system in turn reacts. This idea of informational closure was further taken up by Humberto Maturana and Francisco Varela. The idea of “informationally closed” is a strong premise for constructivism – the idea that all knowledge is constructed rather than perceived through senses. They noted that as cognizant beings, we are informationally closed. We do not have information enter us externally. We are instead perturbed by the environment, and we react in ways that we are accustomed to. Jonathan D. Raskin expands on this further:

People are informationally closed systems only in touch with their own processes. What an organism knows is personal and private. In adhering to such a view, constructivism does not conceptualize knowledge in the traditional manner, as something moving from “outside” to “inside” a person. Instead, what is outside sets off, triggers, or disrupts a person’s internal processes, which then generate experiences that the person treats as reflective of what is outside. Sensory data and what we make of it are indirect reflections of a presumed outside world. This is why different organisms experience things quite differently. How Jack’s backyard smells to his dog is different from how it smells to him because he and his dog have qualitatively different olfactory systems. Of course, how Jack’s backyard smells to him may also differ from how it smells to Sara because not only is each of them biologically distinct but each has a unique history that informs the things to which they attend and attribute meaning. The world does not dictate what it “smells” like; it merely triggers biological and psychological processes within organisms, which then react to these triggers in their own ways. The kinds of experiences an organism has depend on its structure and history. Therefore, what is known is always a private and personal product of one’s own processes.

Raskin gives an example of a toaster or a washing machine to provide more clarity on the informational closure.

Maturana asserts that from the point of view of a biologist living systems are informationally closed–that is, things don’t get in and they don’t get out. From the outside, you can trigger a change, but you cannot directly instruct. Think of it as having a toaster and a washing machine. And, the toaster is going to toast no matter what you do. And, the washing machine is going to wash no matter what you do. And they both can be triggered by electricity. But the electricity doesn’t tell the toaster what to do. The toaster’s structure tells the toaster what to do. So similarly, we trigger organisms, but what they do has to do with their internal structure–including their nervous system–and the way it responds to various perturbations.

The idea of informational closure forces us to bring a new perspective to how we view the world. How are we able to know about reality? From a constructivism standpoint, we do not have a direct access to the external reality. What we can truly say is how we experience the world, not how the world really is. We do not construct a representation of the external world. This is not possible, if we are informationally closed. What we do is actually construct how we experience the world. As Raskin points out, the world is not a construction; only our experience of it is. Distinguishing experiential reality from external reality (even a hypothetical, impossible-to-prove-for-sure external reality) is important in maintaining a coherent constructivist stance.

All knowledge from this standpoint is personal, and cannot be passed on as a commodity. In constructivism, there is an idea called as the myth of instructive interaction. This means that we cannot be directly instructed. A teacher cannot teach a student with a direct and exact impact. All the teacher can do is to perturb the student so that the student can construct their personal knowledge based on their internal structure. Raskin notes – once people’s internal systems are triggered, they organize their experiential responses into something meaningful and coherent. That is to say, they actively construe. Events alone do not dictate what people know; constructive processes play a central role as people impose meaning and order on sensory data. 

The more interactions we have with a phenomenon, the better we can experience the phenomenon, and it aids in our construction of the stable experiential reality of that phenomenon. Repetition is an important ingredient for this. Ernst von Glasersfeld notes:

Without repetition there would be no reason to claim that a given experiential item has some kind of permanence. Only if we consider an experience to be the second instance of the self-same item we have experienced before, does the notion of permanence arise.

From this point, I will try to look at some questions that might help to further our understanding of constructivism.

What is the point of constructivism if it means that we cannot have an accurate representation of the real world? The ultimate point about constructivism is not about an ontological stance, it is about viability. It is about being able to continue to survive. All organisms are informationally closed, and they continue to stay viable. The goal is to fit into the real world. Raskin explains – the purpose of this knowledge is not to replicate a presumed outside world but to help the organism survive. In Cybernetics, we say that we need to have a model of what we are trying to manage or control. This “model” does not have to be an exact representation of the “system” we are trying to control. We can treat it as a black box where we have no idea about the inner workings of the system. As long as we are able to come up with a set of possibilities and possible triggers for possible outcomes, we can manage the system. A true representation is not needed.

How would one account for a social realm if we are informationally closed? If each of us are informationally closed, and our knowledge are personal, how we do account for the social realm, where we all acknowledge a version of stable social reality. Raskin provides some clarity on this. He notes:

Von Glasersfeld held that people create a subjective internal environment that they populate with “repeatable objects.” These repeatable objects are experienced as “external and independent” by the person constructing internal representations of them. Certain repeatable objects–those we identify as sentient, primarily other people–are treated as if they have the same active meaning-making abilities that we attribute to ourselves. Consequently, we are able to experience an intersubjective reality whenever other people respond to us in ways that we interpret as indicating they experience things the same way we do. Once again, this alleviates concerns about constructivism being solipsistic because people do relationally coordinate with one another in confirming and maintaining their constructions. 

For von Glasersfeld, it means that people construe one another as active meaning makers and consequently treat their personal understandings as communally shared when others’ behavior is interpreted as affirming those understandings. As I stated elsewhere, “when experiencing sociality or an intersubjective reality, we come to experience our constructions as socially shared to the extent that they appear to be (and, for all functional purposes, can be treated as if they are) also held by others”.

Each one of us construct an experiential reality of the external world. This external world includes other people in it. Our ongoing interaction with these people enhances and updates our own experiential world. We come to see the external world as a social construction. Our personal construction gets triggered in a social setting resulting in a social version of that construction. The more frequent and diverse interactions we get, the more viable this construction becomes. The other people are part of this experiential reality and thereby become cocreators of the social reality. In many regards, what we construct are not representations of the external world, but more a domain of constraints and possibilities. Making sense of the external world is a question about viability. If it does not affect viability, one may very well believe in a God or think that the world is flat. The moment, the viability is impacted, the constructions of the reality will have to adjusted/modified.

The image I have chosen for the post is an artwork by the Japanese Zen master, Nakahara Nantenbō (1839 – 1925). The artwork is a depiction of ensō (circle). The caption reads:

Born within the ensō (circle) of the world, the human heart must also become an ensō (circle).

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 Ghost in the System:

This post is also available as a podcast – https://anchor.fm/harish-jose/episodes/The-Reality-of-Informationally-Closed-Entities-e16ke0d

References:

  1. An Introduction to Cybernetics, Ross Ashby (1956)
  2. An introductory perturbation: what is constructivism and is there a future in it?, Raskin, Jonathan D. (2015)

The Truth About True Models:

I recently came across Dr. Donald Hoffman’s idea of Fitness-Beats-Truth or FBT Theorem. This is the idea that evolution stamps out true perceptions. In other words, an organism is more likely to survive if it does not have a true and accurate perception. As Hoffman explains it:

Suppose there is an objective reality of some kind. Then the FBT Theorem says that natural selection does not shape us to perceive the structure of that reality. It shapes us to perceive fitness points, and how to get them… The FBT Theorem has been tested and confirmed in many simulations. They reveal that Truth often goes extinct even if Fitness is far less complex.

Hoffman suggests that natural selection did not shape us to perceive the structure of an objective reality. Evolution gave us a less complex but efficient perceptual network that takes shortcuts to perceive “fitness points.” Evolution by natural selection does not favor true perceptions—it routinely drives them to extinction. Instead, natural selection favors perceptions that hide the truth and guide useful action.

An easy to way to digest this idea is to consider our ancient ancestors. If they heard a rustling sound in the grass, it benefitted them to not analyze and capture the entire surrounding to get an accurate and true model of the reality. Instead, they would survive only if they got a “quick and dirty” or good-enough model of the surrounding. They did not gain anything by having an elaborate and accurate perception. Their quick and dirty heuristics such as “if you hear a rustling on the grass, then flee” allowed them to survive and pass of their genes. In other words, their fitter perception did not comprise of a true and accurate perception of the world around them. They gained (they survived) based on fitness rather than truth. As Hoffman noted, having true perception would have been detrimental because it avoided shortcuts and heuristics that saved time. As complexity increases, heuristics work much better.

The idea of FBT aligns pretty well with the ideas of second order cybernetics (SOC) and radical constructivism. From an SOC standpoint, the emphasis for the representation of the world is not that of a model of causality, but of a model of constraints. As Ernst von Glasersfeld explains this:

In the biological theory of evolution, we speak of variability and selection, of environmental constraints and of survival. If an organism survives individually or as a species it means that, so far at least, it has been viable in the environment in which it happens to live. To survive, however, does not mean that the organism must in any sense reflect the character or the qualities of his environment. Gregory Bateson (1967) was the first who noticed that this theory of evolution, Darwin’s theory, is really a cybernetic theory because it is based on the concept of constraint rather than on the concept of causation.

In order to remain among the survivors, an organism has to ‘‘get by” the constraints which the environment poses. It has to squeeze between the bars of the constraints, to coin a metaphor. The environment does not determine how that might he achieved. It does not cause certain organisms to have certain characteristics or capabilities or to be a certain way. The environment merely eliminates those organisms that knock against its constraints. Anyone who by any means manages to get by the constraints, survives… All the environment contributes is constraints that knock out some of the changed organisms while others are left to survive. Thus, we can say that the only indication we may get of the ‘‘real” structure of the environment is through the organisms and the species that have been extinguished; the viable ones that survive merely constitute a selection of solutions among an infinity of potential solutions that might be equally viable.

Nature prefers efficient solutions that does the work most of the time, rather than effective solutions that work all of the time – solutions that prefer least energy expenditure, least number of parts etc. This approach also resonates with Occam’s razor. It is always advisable to have the least number of assumptions in your model. Another way to look at this is – the design with the least number of moving parts is always preferred.

The idea that true perceptions are not always advantageous may be counterintuitive. As complexity increases, we lack the perceptual network to truly comprehend the complexity. How we perceive our world around us depends a lot on our perceptual network, which is unique to our species. Our reality consists of omitting most of the attributes of the world around us. As Hoffman explains – the reality becomes simply a species-specific representation of fitness points on offer, and how we can act to get those points. Evolution has shaped us with perceptions that allow us to survive. But part of that involves hiding from us the stuff we don’t need to know.

Complexity also favors this approach of viable solutions/fitter perceptions. Hoffman notes:

We find that increasing the complexity of objective reality, or perceptual systems, or the temporal dynamics of fitness functions, increases the selection pressures against veridical perceptions.

I will add more thoughts on the FBT theorem at a later time. I encourage the readers to check out Hoffman’s book, The Case Against Reality.

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

In case you missed it, my last post was Talking about Constraints in Cybernetics:

Talking about Constraints in Cybernetics:

In today’s post, I am looking at constraints with respect to Cybernetics. I am looking mainly at the ideas from Ross Ashby, one of the pioneers of Cybernetics. Ashby wrote one of the best introductions to Cybernetics, aptly titled An Introduction to Cybernetics. Ashby described constraints in terms of variety. Variety is the number of distinct elements that an observer is capable of making. For example, consider the following set of elements:

{a, b, b, B, c, C}

Someone could say that the variety of this set is 3 since there are three letters. Some other person could say that the variety is actually 5 if the lower and upper cases are distinguished. A very common example to explain variety is a traffic stop light. Generally, the stop light in the US has 3 states (Red, Yellow and Green). Sometimes, additional states are possible such as blinking Red (indicating a STOP sign) or no light. Thus, the variety of a stop light can vary from 3 to 4 to 5.

Ashby explained constraints as – when there are two related sets and one set has less variety than the other, we can determine that a constraint is present in the set of elements with less variety. Let’s consider the stop light again. If all the lights were independent, we can have 8 possible states. This is shown below, where “X” means OFF and “O” means ON.

Figure 1 – The Eight States of a Stop Light

Per our discussion above, we utilize mainly 3 of these states to control traffic (ignoring the blinking states). These are identified in the blue shaded cells {2, 6, 7}. Thus, we can say that there is a constraint applied on the stop light since the actual variety the stop light possesses is 3 instead of 8. Ashby distinguishes slight and severe constraints. The example that Ashby gives is applying a constraint on a squad of soldiers in a single rank. The soldiers can be made to stand in numerous ways. For example, if the constraint to be applied is that no one soldier is to stand next to another soldier who shares the same birthday, the variety achieved is high. This is an example of a slight constraint. It is highly unlikely that two soldiers share the same birthday in a small group. However, if the constraint to be applied is that the soldiers should arrange themselves in the order of their height, the variety is then highly reduced. This is an example of a severe constraint.

Another example that Ashby gives is that of a chair. A chair taken as a whole has six degrees of freedom for movement. However, when the chair is disassembled into its parts, the freedom for movement increases. Ashby said:

A chair is a thing because it has coherence, because we can put it on this side of a table or that, because we can carry it around or sit on it. The chair is also a collection of parts. Now any free object in our three-dimensional world has six degrees of freedom for movement. Were the parts of the chair unconnected each would have its own six degrees of freedom; and this is in fact the amount of mobility available to the parts in the workshop before they are assembled. Thus, the four legs, when separate, have 24 degrees of freedom. After they are joined, however, they have only the six degrees of freedom of the single object. That there is a constraint is obvious when one realizes that if the positions of three legs of an assembled chair are known, then that of the fourth follows necessarily—it has no freedom.

Thus, the change from four separate and free legs to one chair corresponds precisely to the change from the set’s having 24 degrees of freedom to its having only 6. Thus, the essence of the chair’s being a “thing”, a unity, rather than a collection of independent parts corresponds to the presence of the constraint.

Ashby continued:

Seen from this point of view, the world around us is extremely rich in constraints. We are so familiar with them that we take most of them for granted, and are often not even aware that they exist. To see what the world would be like without its usual constraints we have to turn to fairy tales or to a “crazy” film, and even these remove only a fraction of all the constraints.

There are several takeaways we can have from Ashby’s explanation of constraints.

  1. The effect of the observer: The observer is king when it comes to cybernetics. The variety of an observed system is dependent on the observer. This means that the observation is subject to the constraints that the observer applies knowingly or unknowingly in the form of biases, beliefs, etc. The observer brings and applies internal constraints on the external world. Taking this a step further, our experiential reality is a result of our limited perceptual network. For example, we can see only a small section of the light spectrum. We can hear only a small section of the sound spectrum. We have cognitive blind-spots that we are not aware of. And yet we claim access to an objective reality and we are surprised when people don’t understand our point of view. We should not force our own views such that we come up with false dichotomies. This is sadly all very prevalent in today’s politics where almost every matter has been turned into a political viewpoint.
  2. Constraints are not a bad thing: Ashby’s great insight was that when a constraint exists, we can take advantage of it. We can make reasonably good predictions when constraints exist. Constraints help us to understand how things work. Ashby said that every law of nature is a constraint. We are able to estimate the variety that would exist if total independence occurred. We are able to minimize this variety by understanding the existing variety and adding further constraints as possible to produce results that we want. Adding constraints is about reducing unwanted variety. Design Engineering takes full use of this. On a similar note, Ashby also pointed out that learning is possible only to the extent that a sequence shows constraint. Learning is only possible when there is a constraint. If we are to learn a language, we learn it by learning the constraints that exists in the language in the form of syntax, meanings of the words, grammar etc.
  3. Law of Requisite Variety: Ross Ashby came up with the Law of Requisite Variety. This law simply can be explained as variety destroys (compensates) variety. For example, a good swordsman is able to fend off an opponent, if they are able to block and counter-attack every move of the opponent. The swordsman has to match the variety of the opponent (the set of attacks and blocks). To take our previous example, the stop light has to have a requisite variety to control traffic. If the 3 states identified in Figure 1 are not enough, the “system” will absorb the variety in the form of a traffic jam. When we think in terms of constraints, the requisite variety should be aligned with the identified constraints. We should minimize bringing in our internal constraints, and watch for the external constraints existing. The variety that we need to match must be aligned to the constraints already existing.
  4. Constraints do not need to be Objects: Similar to point 1, what we tell ourselves in terms of narratives and stories are also constraints. We are Homo Narrans – storytellers. We make sense of the world in terms of the stories we share and tell ourselves and others. We control ourselves and others with the stories we tell. We limit ourselves with what we believe. If we can understand the stories, we tell ourselves or others are telling us, we can better ourselves.
  5. Adaptation or Fit: Ashby realized that an organism can adapt just so far as the real world is constrained, and no further. Evolution is about fit. It is about supporting those factors that allow the organism to match the constraint in order to survive. The organism evolves to match the changing constraints present in the changing environment. This often happens through finding use for what is already existing. There is a great example that Cybernetician and Radical Constructivist, Ernst von Glasersfeld gives – the way the key fits a lock that it is able to open:

The fit describes a capacity of the key, not a property of the lock. When we face a novel problem, we are in much the same position as the burglar who wishes to enter a house. The “key” with which he successfully opens the door might be a paper clip, a bobby pin, a credit card, or a skillfully crafted skeleton key. All that matters is that it fits within the constraints of the particular lock and allows the burglar to get in.

I will finish with Ernst von Galsersfeld’s description of Cybernetics in terms of constraints:

Cybernetics is not interested in causality but constraints. Cybernetics is the art of maintaining equilibrium in a world of constraints and possibilities.

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

In case you missed it, my last post was Deconstructing Systems – There is Nothing Outside the Text:

Cybernetics Ideas from a Thermostat:

The thermostat is a simple device that is often used to describe the basic ideas of Cybernetics. Cybernetics is the art of steering. Simply put, a goal is identified and the “system” acts to get closer to the goal. In the example of the thermostat, the user specifies the setpoint for the thermostat such that when the temperature goes below the setpoint, it kicks on the furnace and stops when the internal temperature of the house meets the desired temperature. In a similar fashion, when the temperature goes above a setpoint, the thermostat kicks on the air conditioner to bring down the internal temperature. The thermostat acts as a medium for achieving a constant temperature inside the house. This is also the idea of homeostasis. In order to achieve what the thermostat does, it needs to have a closed loop. It needs to read the internal temperature at specified frequencies, and act as needed depending upon this information. If it was an open loop, no information is fed back into the system, and thus no homeostasis is achieved. An example of an open loop is a campfire without anyone to manage it. The fire continues to burn until it goes out.

Ernst von Glasersfeld, the father of radical constructivism, talked about these ideas in his short paper, Reflections on Cybernetics (2000):

The good old thermostat, the favorite example in the early literature of cybernetics, is still a useful explanatory tool. In it a temperature is set as the goal-state the user desires for the room. The thermostat knows nothing of the room or of desirable temperatures. It is designed to eliminate any discrepancy between a set reference value and the feedback it receives from its sensory organ, namely the value indicated by its thermometer. If the sensed value is too low, it switches on the heater, if it is too high, it switches on the cooling system. Employing Gordon Pask’s clever distinction (Pask, 1969, p.23–24): from the user’s point of view, the thermostat has a purpose for, i.e. to maintain a desired temperature, whereas the purpose in the device is to eliminate a difference.

The idea that the thermostat’s purpose is simply to eliminate a difference is most important here. I have written about this here.

Von Galsersfeld continues:

This example may also help to clarify a second cybernetic feature that is rarely stressed. Imagine a thermostat that has an extremely sensitive thermometer. If it senses a temperature that is a fraction below the reference value, it switches on the heater. The moment the temperature begins to rise above the reference, it switches on the cooling system –and thus it enters into an interminable oscillation. This would hardly be desirable. Therefore, it is important to design the device so that it has an area of inaction around the reference value where neither the one nor the other response is triggered. In other words, rather than a single switching point, there have to be two, with some space for equilibrium in between.

Homeostasis does not refer to a fine line it needs to maintain. It is often a band or a range. The wider the band, the easier it is to maintain homeostasis. It is more efficient to define the “stable conditions” to be between a range of values. A good example for this is a bicycle lane. It is not easy, if not impossible, to ride a bicycle in a straight line. However, it is easy to ride a bicycle in a somewhat wider lane. With the thermostat, this region is sometimes referred to as a “deadband.” This is the range of the temperature, within which the thermostat does not act (stays OFF). Below the lower limit, the thermostat will kick on the furnace, and above the upper limit, the thermostat will kick on the air conditioner.

Another important lesson from a thermostat is that if you want to change the room temperature, there is no point in moving the thermostat value to an extreme setpoint. Let’s say that you want to cool the room down. It is of no use if you put the thermostat value at 40 degrees F (4.44 degrees C). The house will not get colder faster with this approach. The thermostat controls the temperature inside the house, but not the speed with which it achieves this.  

To be economically efficient, the thermostat must be aligned with the external temperature. For example, in colder weather conditions, the heat setpoint should be reduced (for example 67 degrees F or 19.4 degrees C), and similarly during warmer weather conditions the cool set point should be raised. Even though, the thermostat is the regulator, the user determines how this regulation is achieved. The thermostat as a regulator must also follow the Good Regulator Theorem. All good regulators must be a model of the system that it tries to regulate. The model of how to maintain the internal temperature constant (within the deadband) is programmed into the thermostat. It also follows the law of Requisite Variety. The thermostat must have the requisite variety to adjust the internal temperature based on the external perturbations. The thermostat must be able to differentiate the states of “below the setpoint temperature” or “above the setpoint temperature” to achieve the requisite variety and maintain the internal temperature. Both the Good Regulator Theorem and the Law of Requisite Variety are at utmost importance in Cybernetics, and they are both the contributions of one of the pioneers of Cybernetics, Ross Ashby.

I will finish this with some great aphorisms from Ross Ashby:

The drive to equilibrium forces the emergence of intelligence.

That the brain matches its environment is no more surprising than the matching of the two ends of a broken stick.

Every piece of wisdom is the worst folly in the opposite environment. Change the environment to its opposite and every piece of wisdom becomes the worst of folly.

The rule for decision is: Use what you know to narrow the field as far as possible: after that, do as you please.

Any system that achieves appropriate selection (to a degree better than chance) does so as a consequence of information received.

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

In case you missed it, my last post was The Toyota House – Why Jidoka and JIT?