Approaches and Aims in Systems Science

When, some 40 years ago, I started my life as a scientist, biology was involved in the mechanism-vitalism controversy. The mechanistic procedure essentially was to resolve the living organism into parts and partial processes: the organism was an aggregate of cells, the cell one of colloids and organic molecules, behavior a sum of unconditional and conditioned reflexes, and so forth. The problems of organization of these parts in the service of maintenance of the organism, of regulation after disturbances and the like were either by-passed or, according to the theory known as vitalism, explainable only by the action of soul-like factors— little hobgoblins as it were—hovering in the cell or the organism—which obviously was nothing less than a declaration of the bankruptcy of science. In this situation, I and others were led to the so-called organismic viewpoint. In one brief sentence, it means that organisms are organized things and, as biologists, we have to find out about it. I tried to implement this organismic program in various studies on metabolism, growth, and the bio-physics of the organism. One step in this direction was the so- called theory of open systems and steady states which essentially is an expansion of conventional physical chemistry, kinetics and thermodynamics. It appeared, however, that I could not stop on the way once taken and so I was led to a still further generalization which I called “General System Theory.” The idea goes back some considerable time: I presented it first in 1957 in Charles Morris’ philosophy seminar at the University of Chicago. However, at that time theory was in bad repute in biology, and I was afraid of what Gauss, the mathematician, called the “clamor of the Boeotians.” So I left my drafts in the drawer, and it was only after the war that my first publications on the subject appeared.

Then, however, something interesting and surprising happened. It turned out that a change in intellectual climate had taken place, making model building and abstract generalizations fashionable. Even more: quite a number of scientists had followed similar lines of thought. So general system theory, after all, was not isolated, not a personal idiosyncrasy as I had believed, but corresponded to a trend in modern thinking.

There are quite a number of novel developments intended to meet the needs of a general theory of systems. We may enumerate them in a brief survey:

  1. Cybernetics, based upon the principle of feedback or circular causal trains providing mechanisms for goal-seeking and self-controlling behavior.
  2. Information theory, introducing the concept of information as a quantity measurable by an expression isomorphic to negative entropy in physics, and developing the principles of its transmission.
  3. Game theory analyzing, in a novel mathematical framework, rational competition between two or more antagonists for maximum gain and minimum loss.
  4. Decision theory, similarly analyzing rational choices, within human organizations, based upon examination of a given situation and its possible outcomes.
  5. Topology or relational mathematics, including non-metrical fields such as network and graph theory.
  6. Factor analysis, i.e., isolation, by way of mathematical analysis, of factors in multivariable phenomena in psychology and other fields.
  7. General system theory in the narrower sense (G.S.T.), trying to derive, from a general definition of “system” as a complex of interacting components, concepts characteristic of organized wholes such as interaction, sum, mechanization, centralization, competition, finality, etc., and to apply them to concrete nomena.

While systems theory in the broad sense has the character of a basic science, it has its correlate in applied science, sometimes subsumed under the general name of Systems Science. This development is closely connected with modern automation. Broadly speaking, the following fields can be distinguished (Ackoff, 1960; A.D. Hall, 1962):

Systems Engineering, i.e., scientific planning, design, evaluation, and construction of man-machine systems;

Operations research, i.e., scientific control of existing systems of men, machines, materials, money, etc.;

Human Engineering, i.e., scientific adaptation of systems and especially machines in order to obtain maximum efficiency with minimum cost in money and other expenses.

A very simple example for the necessity of study of “man- machine systems” is air travel. Anybody crossing continents by jet with incredible speed and having to spend endless hours waiting, queuing, being herded in airports, can easily realize that the physical techniques in air travel are at their best, while “organizational” techniques still are on a most primitive level.

Although there is considerable overlapping, different conceptual tools are predominant in the individual fields. In systems engineering, cybernetics and information theory and also general system theory in the narrower sense are used. Operations research uses tools such as linear programming and game theory. Human engineering, concerned with the abilities, physiological limitations and variabilities of human beings, includes biomechanics, engineering psychology, human factors, etc., among its tools.

The present survey is not concerned with applied systems science; the reader is referred to Hall’s book as an excellent textbook of systems engineering (1962). However it is well to keep in mind that the systems approach as a novel concept in science has a close parallel in technology.

The motives leading to the postulate of a general theory of systems can be summarized under a few headings.

  1. Up to recent times the field of science as a nomothetic endeavor, e., trying to establish an explanatory and predictive system of laws, was practically identical with theoretical physics. Consequently, physical reality appeared to be the only one vouchsafed by science. The consequence was the postulate of reduc- tionism, i.e. the principle that biology, behavior and the social sciences are to be handled according to the paragon of physics, and eventually should be reduced to concepts and entities of the physical level. Owing to developments in physics itself, the physicalistic and reductionist theses became problematic, and indeed appeared as metaphysical prejudices. The entities about which physics is talking—atoms, elementary particles and the like —have turned out to be much more ambiguous than previously supposed: not metaphysical building blocks of the universe, but rather complicated conceptual models invented to take account of certain phenomena of observation. On the other hand, the biological, behavioral and social sciences have come into their own. Owing to the concern with these fields on the one hand, and the exigencies of a new technology, a generalization of scientific concepts and models became necessary which resulted in the emergence of new fields beyond the traditional system of physics.
  2. In the biological, behavioral and sociological fields, there exist predominant problems which were neglected in classical science or rather which did not enter its considerations. If we look at a living organism, we observe an amazing order, organization, maintenance in continuous change, regulation and apparent teleology. Similarly, in human behavior goal-seeking and purposiveness cannot be overlooked, even if we accept a strictly behavioristic However, concepts like organization, directiveness, teleology, etc., just do not appear in the classic system of science. As a matter of fact, in the so-called mechanistic world view based upon classical physics, they were considered as illusory or metaphysical. This means, for example, to the biologist that just the specific problems of living nature appeared to lie beyond the legitimate field of science. The appearance of models—conceptual and in some cases even material— representing such aspects of multivariable interaction, organization, self- maintenance, directiveness, etc., implies introduction of new categories in scientific thought and research.
  3. Classical science was essentially concerned with two-variable problems, linear causal trains, one cause and one effect, or with few variables at the most. The classical example is mechanics. It gives perfect solutions for the attraction between two celestial bodies, a sun and a planet, and hence permits exact prediction of future constellations and even the existence of still undetected planets. However, already the three- body problem of mechanics is insoluble in principle and can only be approached by approximations. A similar situation exists in the more modern field of atomic physics (Zacharias, 1957). Here also two-body problems such as that of one proton and electron are solvable, but trouble arises with the many-body Many problems, particularly in biology and the behavioral and social sciences, are essentially multivariable problems for which new conceptual tools are needed. Warren Weaver (1948), co-founder of information theory, has expressed this in an often-quoted statement. Classical science, he stated, was concerned either with linear causal trains, that is, two-variable problems; or else with unorganized complexity. The latter can be handled with statistical methods and ultimately stems from the second principle of thermodynamics. However, in modern physics and biology, problems of organized complexity, i.e., interaction of a large but not infinite number of variables, are popping up everywhere and demand new conceptual tools.
  4. What has been said are not metaphysical or philosophic We are not erecting a barrier between inorganic and living nature which obviously would be inappropriate in view of intermediates such as viruses, nucleo-proteins and self-duplicating units. Nor do we protest that biology is in principle “irreducible to physics” which also would be out of place in view of the tremendous advances of physical and chemical explanation of life processes. Similarly, no barrier between biology and the behavioral and social sciences is intended. This, however, does not obviate the fact that in the fields mentioned we do not have appropriate conceptual tools serving for explanation and prediction as we have in physics and its various fields of application.
  5. It therefore appears that an expansion of science is required to deal with those aspects which are left out in physics and happen to concern the specific characteristics of biological, behavioral, and social phenomena. This amounts to new conceptual models to be introduced.
  6. These expanded and generalized theoretical constructs or models are interdisciplinary—e., they transcend the conventional departments of science, and are applicable to phenomena in various fields. This results in the isomorphism of models, general principles and even special laws appearing in various fields.

In summary: Inclusion of the biological, behavioral and social, sciences and modern technology necessitate generalization of basic concepts in science; this implies new categories of scientific thinking compared to those in traditional physics; and models introduced for such purpose are of an interdisciplinary nature.

An important consideration is that the various approaches enumerated are not, and should not be considered to be monopolistic. One of the important aspects of the modern changes in scientific thought is that there is no unique and all-embracing “world system.” All scientific constructs are models representing certain aspects or perspectives of reality. This even applies to theoretical physics: far from being a metaphysical presentation of ultimate reality (as the materialism of the past proclaimed and modern positivism still implies), it is but one of these models and, as recent developments show, neither exhaustive nor unique. The various “systems theories” also are models that mirror different aspects. They are not mutually exclusive and are often combined in application. For example, certain phenomena may be amenable to scientific exploration by way of cybernetics, others by way of general system theory in the narrower sense; or even in the same phenomenon, certain aspects may be describable in the one or the other way. This, of course, does not preclude but rather implies the hope for further synthesis in which the various approaches of the present toward a theory of “wholeness” and “organization” may be integrated and unified. Actually, such further syntheses, e.g., between irreversible thermodynamics and information theory, are slowly developing.

Source: Bertalanffy Ludwig Von (1969), General System Theory: Foundations, Development, Applications, George Braziller Inc.; Revised edition.

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