Systems thinking and its implications

The principle of interdependence

The systems thinking
The systems thinking
29 JAN 2016

The basis of systems thinking derives from the consideration that most of the complex systems around us—be they living entities, social systems, cities, or insect colonies—are constructed as assemblages of many parts, or components, and that the properties of the system stem from the interaction and interdependence of all the parts.

This idea of the importance of the interdependence of parts is not new. It can, in fact, be traced back to the Vedanta tradition. Buddhism is based essentially on the principle of interdependence: nothing makes sense as a single, isolated entity. However, to say just this would not be very helpful in the present world. We need to reinterpret this thinking in view of modern science, social behavior, and ecology.

This is the central purpose of the recent book by Capra and Luisi, The Systems View of Life—a Unified Vision, published by Cambridge University Press in 2014 [1]. The book restates in an updated form the principle of systems thinking applied to the four main aspects of life—biology, social life, cognitive sciences, and ecology—taking into account modern achievements in science and epistemology.

The Systems View of Life is divided into five parts. The first two parts address the history of philosophical thinking, and how systems thinking—beginning with the 1968 pioneer work of von Bartalanffy—came about. It shows how this new paradigm represented a sharp turn of perspective with respect to the analytical/reductionist mechanical way of thinking that had permeated western thought for the two preceding centuries. Although each expressed it in a different way, the writings of Galileo, Newton, and Descartes explored the idea that knowing the fundamental building blocks of reality and their properties would lead to an understanding of the world. Systems thinking suggests the opposite. It holds that one cannot understand reality by looking at single components, but only by taking into account the whole, and the mutual interaction of all its components. It is the emphasis on the network of interactions, on what keeps the parts together, that structures modern thought more than a focus on the individual parts.

Let’s see here, briefly, how this view is consistent with the other epistemic principles of modern science, starting with the notion of self-organization. The term “self” is much in use in the modern theory of complexity, where one talks about self-maintenance, self-autonomy, self-reproduction, and so on. Self-organization is seen as a form of high order, although “order” in this context does not necessarily imply symmetry, or periodicity, but rather a configuration of elements in a precisely determined way. In essence, self-organization embodies the notion of “aperiodic order,” which is a higher degree of order.

Self-organization generally implies another important notion, which is central to the modern, anti-reductionist view of life: the notion of emergent properties. Emergent properties are those novel properties that arise when parts interact with each other—novel in the sense that they cannot be found in the single components of a whole. Thus, one can say that the properties of water—a chemical combination of hydrogen and oxygen—are emergent properties, because they are not present in the isolated atoms. Or one can say that the properties of a family, or of a tribe, cannot be found in the single individual. Likewise, one can say that cellular life (and life in general) is an emergent property, which arises from the interaction of all cell components, and is not present in the single, isolated components, such as DNA, or proteins, or sugars, or lipids.

A very important aspect of emergent properties is that they cannot be predicted or understood on the basis of the properties of the constituent parts. They then represent the innovation, the surprise, that complexity can bring about. Examples of this phenomenon would be semiconductors, or even earlier, batteries. What we are talking about are properties due to the mutual interaction of the constituent parts, a kind of collective behavior (some call this “collective intelligence,” a term I find problematic). Further, these systems function without a center of command, without a center of localization.

This is quite an important concept in the modern view of science. It’s possible to find many examples at all scales of reality. If you consider, say, a beehive, or an ant or termite nest, you may observe the complexity of the whole structure, but also observe that there is no central point where this complexity is being localized. The same can be said for the “swarm intelligence” of flying birds, and, jumping from one dimension to another, the same can be said for the notion of “self” in cognitive science: there is not a point in any of us where the “self” can be localized. For a more mundane example, think about the possible localization of the city of New York. It cannot be isolated into a single point that represents the whole. New York is the whole New York.

Another important modern concept, in large part coming out of the school of Prigogine and his colleagues, is that these complex systems are often not static entities, quietly resting in their equilibrium. They are instead dynamic systems that are out of equilibrium, which—and this is the beauty of it—although being out of equilibrium, maintain a high degree of self-organization. Think of tornadoes, or the whirlpool at the drain of a sink. A candle is another good example because it demonstrates more clearly the idea that we may be looking at dissipative structures, structures which, in order to maintain their organizational continuity, have to use—to dissipate—energy.

To this part of the complexity field also belong those examples in which order comes unexpectedly out of chaos—as in the examples of the famous Belousov-Zabotinsky reaction, or in the Benard cells. But the best examples of systems that are out of equilibrium are living organisms—which are discussed in detail in the third part of Capra and Luisi’s book. Each of these living systems is thermodynamically open, in the sense that it exchanges energy/molecular components with the environment. The interaction of the living with the environment, in Capra and Luisis’ book, is viewed in terms of the cognition theory of Maturana and Varela. These authors also make the point that living systems are characterized by operational closure. An ant, although a thermodynamically open system, does not need any information from outside in order to be an ant; it is all self-contained. And the same is true for an elephant.

Characteristic of some of the complex systems is non-linearity. This means that their growth, for example, does not proceed 1, 2, 3, 4, but rather 2, 4, 8, 16, with extreme consequences in the amplification mechanisms. At this point, one might well ask what the difference is between a living system and a machine. A machine, after all, works via an elaborate system of parts interaction, just as living systems do. An airplane and a robot are the result of highly complex systems of interacting parts, and no single part can be said to be equivalent to the whole.

Yet there is a fundamental difference between a living system and a machine. A living system is capable of self-maintenance by regenerating all components from the inside, i.e., from within a boundary of its own creation. A machine is not. Each cell of a living being constantly undergoes thousands of transformations, and despite this, a liver cell remains always a liver cell, an amoeba remains always an amoeba—at least for the period of homeostasis—and, likewise, an elephant always remains an elephant.

How is this apparent contradiction between self-maintenance and internal continuous changes possible? It is possible because all components that are going to be destroyed in the transformative process—sugar burned, proteins hydrolysed, blood cells eliminated—are reproduced within the cell itself. The living cell, and each living organism in general, is a factory that remakes itself from within. The tree loses its fruits and leaves in winter, but it makes them again in the spring—from within. My hemoglobin molecules are eliminated every few days, but they are reconstructed from within my body. A machine does not have that capability; it does not repair or re-make itself from within. And this is the basic difference. This self-generation from within is the central tenet of autopoiesis, (“self-production”) as Maturana and Varela state in their important book, The Tree of Knowledge [2].

The theme of cognition extends to the thorny trilogy of brain-mind-consciousness, which brings us to the concepts of spirituality and religiosity. There is a chapter in The Systems View of Life that discusses health and alternative medicine, and the final part of the book addresses ecology, climate change, and the disturbing social and economic problems of our generation—always in the framework of systems thinking. The book concludes by positing that solutions to our world problems are possible when approached via the framework of systems thinking. To quote Ludwig von Bartalanffy, who says, “perhaps seeing the world as a large organization can be helpful in reinforcing the sense of reverential respect towards the living, a sense that we have almost completely lost during the most recent bloody period of human history.” [3]

[1] F. Capra and P.L. Luisi, The systems view of life, Cambridge Univ. Press, 2014, italian edition Vita e natura. Una visione sistemica, Aboca Museum

[2] H. Maturana and F. Varela, The Tree of Knowledge, 1980, Shambala
[3] L. von Bartalanffy, General System Theory: Foundations, Development, Applications, New York: George Braziller, 1968, revised edition 1976.