September 19, 2017

Bringing order to chaos – Part 1

A cybernetic approach to the study of society and ecosystems. From Towards a Unified Science.

Cybernetics is the science of control. The term was first used in this sense by Norbert Weiner in 1948 and it derives from the Greek word for a helmsman. Cyberneticians assume that things which act as autonomous units of adaptive behaviour do so because they possess a control mechanism. Whether they be molecules, amoebas, human beings, machines or business enterprises, the control mechanism must have certain things in common. It is these things that are studied by cybernetics. The control mechanism, together with what it actually controls, are best regarded as constituting a system. Systems must also have certain things in common, and these are usually studied by an allied discipline called General Systems, associated with the name of Ludwig von Bertalanffy. Since a control mechanism is an integral part of a system, it is very difficult to study the one without the other. I shall therefore regard them as different aspects of the same thing, and refer to them both as cybernetics.

Cybernetics has been made use of to study all sorts of very different behavioural processes. Its best-known application is in the design of computers, but it has also been particularly useful in the field of psychology. One of the main advantages of using the cybernetic approach to study human behaviour is that it becomes possible to view it in objective and functional terms, not the usual subjective ones. Thus the process normally termed perception is broken up into its functional components: isolation of data relevant to the system’s behaviour pattern, its transduction into the information medium of the brain, and its organization into information. Seen in this way, this process is a very different one from the perception of the Empiricists. Similarly, what we refer to subjectively as the mind can be regarded as a specialized type of control mechanism in use at the level of the individual human being. Thinking simply becomes the process of organizing information in the brain which, if fruitful, serves to increase its value, while the memory is seen as a hierarchical organization of information. There is no reason why the same method should not be applicable to the study of societies and ecosystems, and I am equally certain that this must be the most fruitful approach.

In this article, I shall examine what are the principal characteristics of systems in order to show how our view of society and of the ecosystem would be modified if they were to be studied in this light.

Interrelationship

The parts of a system are all closely interrelated. We cannot alter the value of any one of them without affecting that of the others. What is important is that cause and effect relationships between any two sub-systems can therefore never be examined in isolation, but only in terms of the system of which they are part. It must follow that to determine the effect of any local change, we must build a model of the system, which first involves carefully establishing the interrelationship between each of the variables used. We are then in a position to simulate the system by calculating the effect which the change in the value of any one of the variables will have on that of all the others, and hence on the model as a whole. We can then predict the effect of a corresponding change in any of its parts on the system as a whole. This method is known as systems analysis. It must be the only scientific method for working out cause and effect relationships in natural systems.

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Vertical structure

The concept of levels of organization, mainly made use of in biology, is applicable to all systems. Take the case of an atom. It cannot grow indefinitely. A point is reached where development is only possible by associating with other atoms, thereby forming a molecule. Similarly with a molecule. When it reaches its maximum size it must associate with others to form a cell. A biological organism is thus made up of cells, which are in turn made up of molecules, which are in turn made up of atoms, and it is not possible to move from an atom to a biological organism without passing through the intermediary stages. This is as true of societies and ecosystems as it is of biological organisms and cells. Every system must be taken as having an optimum structure, deviation from which must reduce stability, and major deviations from which can only lead to total breakdown. Thus one cannot pass from the individual to a society, nor to an ecosystem, without passing through equally essential intermediary stages, of which two are undoubtedly the family and the small community. The implications are far-reaching. For instance, growth cannot occur at a rate inconsistent with the maintenance of the correct structure. Nor can systems get too big—they all have an optimum size. This points to the fallacy of the present-day worship of size and craving for vast centralized corporations or political units.

In biology, cancer is an example of the growth of tissue that no longer displays the correct structure. In society a modern city is an equally good example.

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Horizontal structure

A system must also have an optimum horizontal structure: thus the correct ratio must be maintained between all the differentiated cells making up a biological organism; or between the different members of an ant colony; or between the different specialists—accountants, salesmen, clerks, etc.—that make up a business enterprise. If this optimum structure is not maintained there will be unintegrated parts that will behave in a random manner—noise or distortion in a machine—which can seriously compromise the correct functioning of the system.

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Law of the optimum value

Assuming that all the parts of the system can be quantified, we can then formulate the essential principle of all systems, which we can refer to as the law of optimum value. There must be an optimum value for every part of the system, which is determined by that of the other parts. To allow one of these values to increase without reference to the others is to destroy the essential structure of the system, and bring about its breakdown. So if we regard the United Kingdom as a system, there is an optimum population at any given moment. There is an optimum number of houses, an optimum number of cars; there is also an optimum standard of living, an optimum differential between the wages paid to different people; there is an optimum longevity and even an optimum amount of social deviation. It must follow that there is no conceivable variable whose value can be increased or decreased indefinitely without bringing about the breakdown of the system. Nothing is good or bad per se.

Things cannot be judged against an absolute standard of values, but by their ability to fulfil their specific function within the system of which they are part. The implications of this principle are colossal and affect practically all our most cherished values. For instance, it reveals the illusory nature of the conventionally accepted idea of progress which provides us with a justification for the havoc we are wreaking today on our environment.

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Goal

Science consists in the organization of data into information that can be made use of for making predictions. If it is possible to organize data in this way it is because the world displays order. Order is the opposite of randomness. Systems come into being and behave in an ordered way, not in a random one. This implies that they are goal-seeking. This principle is of the utmost importance. If one does not accept that processes are goal-seeking, one must also deny the possibility of studying them scientifically. Scientific method in such conditions would then be limited to the study of purely static things, and since these do not exist, one would be denying the possibility of science. Since a cultural pattern can only be regarded as a system, it must also be goal-seeking. The cultural traits it must follow cannot be regarded as having come into being at random. They all have precise functions within their specific cultural system, and are goal-seeking, like all other parts of a system. They can therefore be examined scientifically, in terms of measurable variables, like any other aspect of behaviour. The same is true of any of the differentiated parts of the total ecosystem. This principle is totally incompatible with the Empiricist approach and in particular with Hume’s law of causality. Its methodological implications are crucial, since it allows us to deduce from the very existence of any system that it has some function to fulfil within the larger one of which it is part. It also allows us to use this information for mediating its future behaviour, and also to judge it according to how far it fulfils this function.

Such a teleonomic or a posteriori approach is in fact constantly used by scientists in the physical sciences, regardless of accepted notions of scientific method—but is frowned upon in the sciences dealing with human behaviour.

It is, in fact, simply another form of deduction which, as we have seen, is the correct means of acquiring information.

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Stability

Incomplete man-made systems have been created to fulfil a specific goal. Once achieved, their raison d’etre has gone. An example is a guided missile. Natural or complete systems do not have a goal that can be pinpointed in space and in time. It is more like a carrot held in front of a donkey’s nose, i.e., it will never be attained. It is, in fact, best described in terms of a trajectory in which disequilibria and hence corresponding corrections or rejections will be ever further reduced. In this way, the system will become more and more stable, or homeostatic. This can be achieved in two ways, either by modifying the environment in such a way that disequilibria will be reduced—by increasing environmental order, or else by increasing the system’s ability to deal with environmental disequilibria—by increasing cybernismic order.

If one accepts that this is the goal of all systems, including societies and ecosystems, one is then in a position to make use of the deductive method in building up a science of behaviour.

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Complexity

If there is a tendency for systems to become more and more complex, it is because complexity renders them more stable. Another way of looking at complexity is in terms of variety, assuming that the variants do not occur at random, but together constitute an integrated system—though in the case of a population or gene-pool, the degree of integration is not very high. The greater the variety, the greater the system’s ability to deal with improbable changes. Serious disruption of its basic structure also becomes less likely.

A reduction in variety, resulting in simplification, will thus lead to a reduction in stability. It is worth noting that the destruction of the numerous cultures of primitive people throughout the world, and the absorption of their cultures, has produced a radical and dangerous simplification at the cultural level of organization—reducing our stability and rendering our species vulnerable to changes or accidents that would normally affect only a small section of it. In agriculture, monoculture is a drastic simplification of plant life. Antibiotics and insecticides are drastic simplifications in that they are replacing complex controls that normally keep insects in check by indiscriminate killers.

Technological processes, when used to replace natural ones, are further simplifications. In all these cases, stability is being reduced and vulnerability increased. We are forced to accept the unpleasant fact that practically all man’s efforts today are tending towards the simplification of the total ecosystem and that we are becoming ever more vulnerable to environmental changes.

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Order

Another way of increasing stability is by increasing order. This can be defined as the influence of the whole over the parts. It is also defined as limitation of choice, for the greater the influence of the whole over the parts, the greater must be the constraints imposed on them to ensure that they behave in a way that will further the interests of the whole.

Every system owes its existence to the operation of a specific set of constraints. As it increases order so as to increase its ability to face a given challenge, there is an increase in the constraints applied, and hence a reduction in the range of choices open to the parts of the system. As the system develops and achieves new levels of organization, e.g. as molecules join together to form cells, or as families join together to form small communities, and small communities to form larger ones, new constraints are imposed. Each system possesses an organization of information which we can refer to as a cybernism which constitutes a model of the environment and at the same time provides the system with a goal-structure and its corresponding constraints. That set of beliefs cherished by every ordered society constitutes its cybernism, in terms of which it interprets environmental data and mediates responses to them.

We can best understand such a cybernism as part of a control-mechanism that applies the constraints that will ensure that each member of the society behaves as a differentiated part of it. Once these constraints are no longer observed, the society will disintegrate.

One of the implications of this principle which we might not be too happy to accept is that permissiveness can only be regarded as another word for disorder—as the inevitable sign of social disintegration.

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Economy

Systems tend towards increasing their order so as to increase stability, or homeostasis. They will not do so indefinitely because of the law of optimum value, which will favour the optimum stability or homeostasis of the larger system of which it is part. This value will be the minimum that will enable it to fulfil this function, in accordance with the law of economy. In this way the complexity and order of a system will only increase when there is a need for it, or, in other words, systems will display the minimum complexity and order. This means that adaptive systems are as small and decentralized as possible. This is of urgent relevance to present-day society with its seemingly uncheckable tendency towards ever greater size and centralization.

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Differentiation

A system grows in order to become more complex, not simply in order to get bigger. In becoming more complex, it does not develop new basic goals, it simply becomes capable of satisfying pre-existing goals more satisfactorily in a way that will ensure higher homeostasis. The mechanisms ensuring the achievement of these goals become more differentiated. Feedback mechanisms ensure the development of parts of a system adapted to varied environmental requirements. When feedback development breaks down, differentiation ceases to occur. Instead, parts come into being by multiplication. The system therefore gets bigger but not more complex, and unintegrated parts come into being. These constitute surplus capacity—noise in a machine or disorder in society—which may lead to the eventual collapse of the system.

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Integrity

A system, as we have seen, has an optimum structure, no surplus capacity, and the parts are all differentiated. It is an integral whole, and the destruction of any of its parts can lead to total breakdown.

This is a point which has rarely been taken into account at a cultural level. Colonialist powers have constantly interfered in the most irresponsible way with the cultures of the societies they controlled. Missionaries and colonial administrators have tampered with the delicately adjusted cultural systems of highly stable and ecologically sound societies which they regarded as “primitive” or “barbarous” and brought about their breakdown in most instances. The consequences for the inhabitants of these societies has been disastrous. They usually become rootless members of a depressed proletariat in the shantytowns we are thereby methodically creating. The consequences for the ecosystem as a whole have been equally disastrous. By reducing order as well as cultural variety or complexity, we have seriously reduced the stability or homeostasis of the world’s human population.

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