There have long been discussions about whether systems are “real.” Some take the position that the universe we know is comprised of systems which we discover through recognition. Others claim that systems are only a way of seeing things – a particular set of concepts by which we describe reality, but which are arbitrary and completely subject to the interpretation of each observer.
This is actually only an extension of the more general question, “what is real?” While most people would agree that we experience a “real” world, it’s also true that we only experience it based upon our individual interpretations of the sensations that we have. What we “see” is the result of how our brains interpret the neuronal impulses which our eyes produce in response to the light which stimulates them. We assume that what we see is real (therefore the adage, “seeing is believing”) but we can easily be fooled through simple manipulations such as visual illusions. Similarly, we assume that our experience of the world is directly connected with the actuality of the world until we find ourselves in an altered state. This can happen in dreams that seem so real that we don’t know whether they were dreams or not. (At the neurological level, it was equally an “experience.”) It can also occur as result of almost any alteration to our brain chemistry, be it from chemicals that we ingest (e.g. drugs), or injury, or excessive fatigue, or conditions such as dementia or schizophrenia. It can even happen simply through suggestive states of consciousness such as from watching a really scary movie and becoming hypersensitive to “things that go bump in the night.”
One aim of science has been to overcome these problems by eliminating human bias from research. Observations are made using tools and measurements which are to be verified by other observes, and ultimately through controlled experiments which can test the veracity of any claims. For better or worse, though, science is a human activity which is always subject to human interpretation and understanding.
Because our experiences happen individually inside each of our brains, we can only compare and coordinate those with others. We can never know for certain the actual experience of another. At the same time, what we do – individually and collectively – affects the real, tangible world in which we live, just as we are a part of that world and are affected by it.
One aspect of the question in relation to systems is the choice of things on which to focus. Ultimately, everything is connected in one way or another, even if just at the most elemental (e.g. quantum) levels. And yet as humans there is no way by which we can focus on the entirety of the universe all at once. We have to make choices. As explained by Ashby (1956):
At this point, we must be clear about how a “system” is to be defined. Our first impulse is to point at the pendulum and to say “the system is that thing there.” This method, however, has a fundamental disadvantage: every material object contains no less than an infinity of variables, and therefore of possible systems. The real pendulum, for instance, has not only length and position; it has also mass, temperature, electric conductivity, crystalline structure, chemical impurities, some radioactivity, velocity, reflecting power, tensile strength, a surface film of moisture, bacterial contamination, an optical absorption, elasticity, shape, specific gravity, and so on and on. Any suggestion that we should study “all” the facts is unrealistic, and actually the attempt is never made. What is necessary is that we should pick out and study the facts that are relevant to some main interest that is already given (p. 39-40).
What Ashby describes is what is often called the “system of interest.” It is that entity or phenomenon on which one focuses. It is that part of reality that we separate from the rest in order to understand it independently, or “as it is.” In Gestalt work, it is what comes into the “foreground.” In science it is the subject, and in engineering and other disciplines it is defined by what is included in a particular model.
From this perspective it’s easy to see why there is often confusion about the concept of systems. The systems with which we work are bounded by choices of our interests or focus. But that does not mean that they do not reflect aspects of reality. (In fact, if they did not, there would be little value in having them at all.) Robert Rosen made the distinction between formal systems (or models) and natural systems, or the entities in the real world which they represented. As he explained it: “Now the whole point of making models, i.e. of encoding natural systems into formal ones, is to enable us to make specific predictions (particularly temporal or dynamical predictions) about natural systems, utilizing the inferential structure of the model as an image of the processes occurring in the natural system itself ” (Rosen, 1985, p. 215).
Andras Angyal (1941) offers a perspective which suggests that there are systems in the world, and that we can discover ways to study them with some accuracy. As he describes this:
Some state that wholes, as such, cannot be studied since scientific investigation presupposes that analysis of the whole into parts, which then makes possible the study of the interrelationships among parts.
It is, however, a misconception that the holistic type of study excludes analysis. Analysis consists in a concrete or abstractive division of an object into smaller units. One can, however, make divisions in many different ways, depending upon the principle according to which the division is made. It is true that such division may destroy the whole, but there is a method of analysis which is perfectly adapted to the study of wholes, a method which does not destroy the object studied but, on the contrary, brings its structure into clearer relief. Let us clarify this point.
Suppose one wishes to study a given whole, be it an animal, a plant, or even an inanimate object which exhibits some of the characteristics of wholes, for example, a building. One can divide such wholes in at least four different ways. 1) One can “cut” the object into pieces at random. The result of such division will be a number of fragments. 2) One can divide the whole according to a certain previously fixed principle which does not take into account the intrinsic nature of that given whole but is extraneous to it. An illustration of this type of division would be the division of a tree into cubes. 3) One can “divide” by abstraction, by which is meant the resolution of objects into a number of distinguishable properties, for example, color, weight, consistency, etc. The result of such analysis will be a number of features. 4) One can divide the whole according to its structural articulation. Wholes, in the technical sense of the word, are never entirely undifferentiated, but are always structured and articulated into parts. This characteristic distinguishes them from homogenous masses and from chaotic aggregations. The multiplicity of parts is just as characteristic of wholes as the unity which holds them together. The whole is never structureless but is a true unitas multiplex, as the philosopher would say. The division of the whole into smaller units can be made, therefore, in such a way that the line of division coincides with the structural articulation of the whole itself, and thus the lines of division are prescribed by the structure of the whole itself (pp. 12-13)
References:
Angyal, A. (1941). Foundations for a science of personality. New York: The Commonwealth Fund.
Ashby, W. R. (1956). An introduction to cybernetics. London, UK: Chapman and Hall Ltd.
Rosen, R. (1985). Anticipatory Systems. Oxford: Pergamon Press.