Adapted from Creative Systems Theory
The twentieth century witnessed a sequence of efforts to develop not just systems perspectives for particular realms of inquiry, but to elucidate underlying systemic principles. Below I’ve listed chronologically the most important contributions to this history and ended by comparing and contrasting Creative Systems Theory.
Science’s glaring inability to define life drove the first efforts.
Biologists, in the early part of the last century, buoyed by how relativity and quantum mechanics had successfully stepped beyond classical models, began to talk of organisms having “emergent” properties, properties that were a function of the organism as a whole—life being the most pivotal. A radical new approach to biological thought, called organicism, challenged and stepped beyond the two prevailing (and warring) schools of biological thought—mechanism (that made it all just anatomy and physiology) and vitalism (that proposed some separate animating force). Organicism’s most influential early thinkers were H.B.S Haldane and E.S. Russel—and later with the 1920’s, Ludwig von Bertalanffy. In the words of Russel, an organismic perspective “allows us to look on the living thing as a functional unity … and to realize all its activities … subserve in cooperation with one another the primary end of development, maintenance and reproduction.”
Research in embryology provided important support for the organismic perspective. Early embryologists discovered that when you divide an embryo during its very early stages the result is not two incomplete organism as you might expect. Rather it is two fully healthy and whole organisms. They concluded that cells differentiate not just according to predefined instructions, but as an expression of their position in the developing embryo. The content of development was directly linked to its organismic context.
From these beginnings, von Bertalanffy developed a more formal and expansive formulation—applicable to social as well as biological systems—that he called General Systems Theory. General Systems Theory argued that “certain general principles apply to systems irrespective of their domain.” It replaced Newton’s picture of existence as a great machine with the idea that reality is, in Bertalanffy’s words, more accurately a “great organization.” General Systems Theory specifically addressed the question of emergent properties. And von Bertalanffy offered that because “certain general principles apply to systems irrespective of their domain,” systems understanding presented a way to link thinking from diverse fields. General Systems Theory, in successfully bridging mechanism and vitalism, succeeds at being systemic in the deep sense. (Bertalanffy thought of organization in terms of generative dialectics. “The world as a whole, and each of its individual entities, is a unity of opposites, which, in their opposition and struggle, constitutes and maintains a greater whole.” He struggled—unsuccessfully—to generalize his systems ideas into a formal mathematics of living systems.)
Cybernetics, a second major contribution to systems understanding, arose from mathematics, engineering, and the social sciences. (One of its contributions was its strong advocacy of multi-disciplinary inquiry.) Norbert Wiener was its primary architect. Cybernetics hoped to model the kind of feedback and self-regulation found in living systems. It strongly influenced later thinking in organizational development and systems engineering and played a major role in the beginnings of computer science. (Interest in mathematically-based systems thinking has been rekindled of late by the advent of high-speed computers—the complex computations needed to address multi-variable equations have become much less a problem.)
Cybernetic formulations are ultimately of the connect-the-dots sort—how the thermostat in your house regulates temperature through a simple feedback loop is an example of a cybernetic system—which helps explain both their strengths and their failings. Their machine assumptions make them conceptually accessible (no great shift in paradigm was needed) and of immediate practical application. But while they engaged the bridging project (the concept of “information” helped link structure and process) and attempted to address change (for example with the ideas of positive and negative feedback), cybernetic formulations are ultimately deterministic and homeostatic. Their mechanistic underpinnings leave them limited when it comes to systems for which machine principles are not enough—and dangerous if those limitations are not recognized—cybernetic concepts are highly vulnerable to being exploited as tools for social control. (Some of these failings have been addressed with later attempts at a “second order” cybernetics that brings new attention to the reflective aspect of perception.)
Much of systems thinking in sociology, psychology, and anthropology is similarly of a connect-the-dots sort and open to the same criticisms. (Systems thinking in the social sciences is commonly associated with the “positivist” perspectives of Auguste Compte and Emile Durkheim. Postivist social science argues that the functioning of human systems can be fully explained with the methods and assumptions of classical science.) But there are important, more integrative exceptions. I think of the Structuralism of linguist Ferdinand Saussue and anthropologist Claude Le’vi-Strauss with its emphasis on underlying pattern and self-organization. The best of Structuralism links complexity and change. Jean Piaget (often referred to as a Structuralist) defines structure as a “system of transformations.” The Gestalt Psychology of Wolfgang Köhler and Kurt Lewin saw the perception of form as a unitary and evolutionary process. Earlier I mentioned family systems concepts.
Systems ideas went in and out of favor through the twentieth century. Organismic, General Systems, and Structuralist ideas receded in importance as the biological and social sciences strove to mimic the final objectivity of the harder sciences (ironically, just as the harder sciences were questioning past mechanistic assumptions). Systems thinking as a whole went out of favor with the ascendancy of post-modernism with its basic mistrust of meta-theory (systems thinking is ultimate meta-theory—though, at its best, ultimately of a different sort than post-modern theorists imagine it). Today, with the growing visibility of challenges that require systemic perspective, increasing recognition of the limitations of both mechanistic and post-modern understanding, and the advent of high speed computers able to better model complexity, the project of developing mature systemic formulations is gaining fresh attention.
The body of scientific inquiry most associated with the word complexity is more recent. Know collectively as the Mathematics of Complexity (Chaos Theory and fractal geometry are the two most celebrated examples), it is not formally systemic and is again ultimately mechanistic. But it does offer intriguing insights into life’s intricacies and how those intricacies may be coded. Its formulations demonstrate how simple equations can produce results that mimic highly complex phenomena—from cloud formations to the serrated edge of a leaf (a recognition with fascinating implications, for among other things, the question of how living structures may develop). In addition, by illustrating how fully deterministic equations can produce unpredictable results—not just complicated, but fundamentally unpredictable—they demonstrate another way uncertainty and order need not be at odds.
Related is the study of open systems—systems such as a tornado or the vortex in one’s tub (or ourselves) whose structure is dependent on inflow and outflow. (An engine requires inflow and outflow to run, but in their absence retains its structure.) Bertlanffy’s work emphasized the important difference between open and closed systems. Ilya Prigogine’s elucidation of generation mechanism in non-equilibrium thermodynamics processes (see footnote in Chapter Four) comprises the most well-known application of this distinction. The study of open systems has made major contributed to our understanding of emergent properties and self-organization.
A more recent inclusion is the study of “complex adaptive systems.” Complex adaptive systems evolve through mechanisms analogous to those of natural selection. Much of this work is based on computer modeling. (At such modeling’s extreme we find computer programs designed to design themselves through “mutation” and selection.) It is a fertile field with broad potential application.
Two further contributions from the life sciences are worth noting both because they take on directly the task of deep systemic conception and because of their particular pertinence to foundational principles in Creative Systems Theory. The work of Gregory Bateson in the 1970s and the more recent efforts of biologist Humberto Maturana, each in different ways, returned to systems theory’s original quandary—the question of life. They arrived at similar—and similarly provocative—highly systemic answers. Bateson and Maturana were each concerned with the relationship between cognition—how organisms process their internal and external worlds—and the phenomenon of life. Both concluded that cognition, if understood in its full complexity—in terms of an organism’s capacity to self-maintain, self-organize, learn, and interrelate—was not just a characteristic of life; it was what defined life.
The result is fully non-dualistic conception—an achievement of major philosophical significance. (It successfully bridges mind and matter—as apposed to vitalistic concepts that postulate a separate animating force or mechanistic views that create the appearance of non-duality by ignoring the offending pole.) In the thinking of both Bateson and Maturana, cognition—here used to refer to the entirety of an organism’s generative responsiveness—becomes the fundamental architecture of animate existence. Cognition, understood in its full systemic implication, becomes, in the words of Bateson, “the pattern which connects.” (Bateson enjoyed highlighting that quandary of life when teaching students. He would put, say a crab, in front of them on a table and ask them how they knew it was alive. He’d then leave the room while they struggled for an answer. Do we know a crab is alive because it moves? So do trains and buses.) Do we know it because a crab reproduces? So do crystals. The conversations the followed focuses on how any answer which even came close somehow involved cognition in the broad sense.)
Also worthy of acknowledgment are efforts through the later half of the twentieth century to integrate various systems approaches. I think first of the formulations of Eric Jantsch, Erwin Laszlo, Fritjof Capra, and Stuart Kauffman. Each of these thinkers focused more effectively on the physical and the biological than the human. But eac—with varying degrees of success—strove for systems understanding of a dynamics sort and succeeded in bringing ideas about here-and-now complexity together with theories of change.
The focus of Creative Systems Theory is human systems. It is unusual in how broadly it addresses them (most systemic perspective in the human sphere address one particular systemic scale—individual, family, organization, culture). It is also unusual how explicit it is in addressing them from a deep systemic perspective. It is unique in its use of cognition (as manifest in conscious systems) as its fulcrum for understanding (a conceptual leap that lets it address not just life, conscious process non-dualistically). It is also unique in how is uses creative/formative process as its model for differentiation (and through the application of this model, how it links temporal and here and not differences).
Creative Systems Theory shares certain characteristics with each of these formulations. Like the ideas of Bertalanffy it makes its starting point an emergent property (here two of them, conscious awareness along with life). Like cybernetics, it gives as much attention to pattern as structure. Like the sciences of complexity, it delineates how simple dynamics can generate highly complex phenomena. Like the work of Bateson and Maturana, it expands usual notions of cognition (here for human cognition) and makes intelligence the fundamental mechanism through which we organize experience. And like family systems theory, it emphasizes that human identity is always as much a product of systems we are a part of as who we are as individuals. (And it goes further to delineate how relationships between self as self and self as larger systems creatively evolve and differ from place to place.)