Johannes B. Schmidt – KA703 1/49 Knowledge Area 703 System Theory and Mystical Kabbalah Johannes B. Schmidt Ph.D. – Program School of Human and Organization Development Fielding Graduate University, Santa Barbara, CA December, 2007 To help soul and psyche experience reality, spirituality is required. Swami Chandrasekharanand Saraswati If you know the answer, you’re only part of the problem. Snowden Johannes B. Schmidt – KA703 2/49 Abstract This paper outlines two different wholistic approaches, namely systemic theory and mystical Kabbalah. Both theories describe wholeness, as opposed to dissectional analysis, and the abstract totality of diverse realities. Key ideas of systemic theory, complexity theory and chaos theory, as well as the Universal Mystical Heritage of Humankind, the Kabbalah, are being explored. This exploration helps to reveal resemblances and differences. The comparison of the two approaches deepens our understanding of the interconnectedness and wholistic nature of reality. It challenges our perception and habitual heuristic to relate to the internal and external world. It requires that we incorporate and experience reality rather than think about. Finally, the comparison helps us to integrate seemingly disparate points of view. Johannes B. Schmidt – KA703 3/49 Content: Part A: Overview Introduction into a scientific (r)evolution ........................................................................ 4 System Theory .................................................................................................................. 6 Cybernetics ....................................................................................................................... 8 Chaos Theory ................................................................................................................. 10 Properties of living systems ........................................................................................... 12 Introduction into enlistment of Kabbalah ....................................................................... 16 Kabbalah ......................................................................................................................... 18 Kabbalistic Cosmology .................................................................................................. 26 Part B: In-Depth Juxtaposition of Systemic Theory and Mystical Kabbalah ............................................ 28 Immaterial organizational structure ............................................................................... 31 Boundaries and the in-between ...................................................................................... 32 Emergence ...................................................................................................................... 35 Arising questions for further inquiry .............................................................................. 35 Part C: Applied Practical Consequences .................................................................................................. 38 Appendix: The function of text in early oral cultures ................................................... 39 Reference List ............................................................................................................... 45 Johannes B. Schmidt – KA703 4/49 Part A: Overview Introduction into a scientific (r)evolution Systemic thinking arose from a need for understanding and integrating assemblages of divergent components in interdependent, unified structural arrangements. The need to align a host of interacting, reciprocal and iterative factors, to create coordinated, systematic, and coherent output in highly interactive, reciprocal systems, exceeded the then known scientific possibilities. In rocket science, for example, chemical, electrical and physical components needed to be integrated in one aligned and stratified process. Ecological problems, including air and water pollution, traffic congestion and weather forecast, defied simple, few-dimensional cause-and- effect chain analysis. Social problems, like organized crime, juvenile delinquency, or city planning, required a grand synthesis of diverse interdisciplinary approaches for their resolution. The generation of these solutions needed to be embedded in a unifying, overarching theory that allowed an effective understanding of the reciprocities and effects involved. In the 1940s, evolving new disciplines of what became later known as information theory, cybernetics, gamble theory, decision theory, molecular biology, cognitive science, biophysics, or thermodynamics, all ran into challenges whose structures were astoundingly similar. In each field, the complexity of the abstract and practical issues defied uni-dimensional solutions as offered by common positivistic, dissectional scientific thinking. The required integration of diverse variables and the interconnectedness and reciprocity of the phenomena exceeded the contemporary understanding of mechanistic clockwork interaction. Various scientists, whose interest and attitude precluded them from staying within the confinement of positivistic thinking, strove to find a new theory for understanding complex and highly interconnected problems. People, including Walter Cannon (1871 – 1945, physiologist, homeostasis), Ludwig van Bertalanffy (1901 – 1972, organismic theorist, General System Theory), Ilya Prigogine (1917 – 2003, physical chemist, dissipative structures), Franciso Varela (1946 – 2001, neurobiologist, autopoiesis, constructivism), Humberto Maturana (1928 - present, neurobiologist, autopoiesis, constructivism), Heinz von Foerster (1911 – 2002, physicist, radical constructivism), Norbert Wiener (1894 – 1964, mathematician, cybernetics), Anatol Rapoport (1911 – 2007, biomathematician, systems and Johannes B. Schmidt – KA703 5/49 game theory), Gregory Bateson (1904 – 1980, anthropologist, epistemology), Kurt Lewin (1890 – 1947, psychologist, group dynamics), Warren McCulloch (1899 – 1969, neurophysiologist, neural network), Margaret Mead (1901 – 1978, anthropologist), Claude Shannon (1916 – 2001, information theorist, information theory), and Max Delbrück (1906 – 1981, geneticist, molecular biology) strove to elaborate a Grand Unified Theory. The interdisciplinary Macy conferences, hosted by The Josiah Macy Jr. Foundation from 1946 – 1953 in New York City, provided a cauldron for sharing and developing ideas that evolved into cybernetics and systems theory. In this context, a “third form of science” (Waldrop, 1992, p. 63) established itself which stood between the common alternatives of theory and experiment. This new form of science profited from increasing computational capacity, which allowed the computation and modelling of non-linear and iterative equations on computers. According to Heylighen, professor of a transdisciplinary research group at the Free University of Brussels, the information capacity from pre-industrial times (200 years ago) till today multiplied 100 billion times (!) (Francis Heylighen, 2002, p. 3). Consequently, this (r)evolution of abstract modelling finally sped up new forms of thinking which became known as chaos theory, systems theory and cybernetics. Heylighen, Cilliers and Gershenson (2007) show to what extend these new ideas challenged Newtonian science and thus the habitual way of thinking. The foundational principles of science at this time were reductionism, determinism, and assumed objective knowledge. The traditional methods were analysis and isolation of variables in combination with gaining full understanding and gathering of complete information about a phenomenon. Concepts of matter, absolute space, time, and nomothetic law, which govern movement in a clockwork world, reigned absolute. The underlying materialistic ontology sees all phenomena as constituted of matter and excludes possible alternatives for ephemeral phenomena, such as biological, mental, social or spiritual realities. Heylighen et al. (2007) identify the corresponding Newtonian thinking as “reflection- correspondence view.” The objective reality outside creates a corresponding inner experience.. Science strives to make this correspondence a perfect match - a perfect objective representation where our internal cognitive reality reflects accurately the external material reality. The net result of this approach to reality is “the principle of distinction conservation” Johannes B. Schmidt – KA703 6/49 (Francis Heylighen, 1990). Whoever looks at the objective reality in the world, makes the same dissecting distinctions to understand the phenomena. As these distinctions remain stable there is no change in the fundamental components that create reality. No new distinctions, initial states, or intermittent variations come into being. Heylighen et al. conclude that Newtonian science is simplistic, as “it is merely an ‘uncovering’ of distinctions that were waiting to be observed” (p. 4). They refer to Prigogine and Stengers (1984) who support the view that the Newtonian approach does not allow for novelty or creation. Taking into account that Newtonian thinking forms the background for an interdisciplinary, evolving, new paradigm, the foregoing description may make clear that this evolution had characteristics of a (r)evolution. The common beliefs were turned upside down, as will be outlined in the following paragraphs. System Theory van Bertalanffy sets out to formulate a General System Theory as the “scientific exploration of ‘wholes’ and ‘wholeness’” (1969, p. xx). A system can be broadly defined as an assemblage of things - sets or units which share a particular, characteristic interaction. James Grier Miller gives a general definition of system saying that it “is a set of interacting units with relationships among them” (1978, p. 16). In Fritjof Capra’s view, the term “systemic” can be used interchangeably with “holistic”, “organismic”, or “ecological” and refers to the basic tension between “the parts and the whole”. (Capra, 1996, p. 17). The different definitions of systems usually stress existence of a number of components which mostly create a tangible structure in combination with a particular organization. It is this interactional organization, independent of the physical structure, that is the major focus of systemic theory. According to the neurobiologists Maturana and Varela (1987), living systems coordinate their behavior (communicate) along autopoietic (self-made) autonomous and self-referential interactions in a structure-determined way. It is not yet fully clear in what way this is true for social systems. The interaction in systems is considered to be non-trivial, which means non- linear (Bertalanffy, 1969, p. 19). The particular quality of the interrelatedness produces emergent phenomena which cannot be derived from the quality of the constituent components. Emergent qualities cannot be researched by a dissecting, reductionist, scientific approach that is interested in the properties of parts. The enormity of this statement becomes clear when “on closer scrutiny practically all Johannes B. Schmidt – KA703 7/49 of the properties that matter to us in everyday life, such as beauty, life, status, intelligence…, turn out to be emergent” (Francis Heylighen et al., 2007, p. 6). Love is an emergent quality that is based on a particular quality of relationship. This relationship may be based on diverse structural components, including baby - mother, husband - wife, person - spiritual source, human being – human being, human being - animal. It is a particular quality of relationship in the context of bonding, attachment or interrelatedness that brings about the emergent phenomenon of love. This perception of love reciprocally and iteratively feeds back into the relationship and into communication. It may express in diverse and unpredictable forms as behavior, emotion, rituals, communication, physical proximity, spiritual practice, etc. The systemic approach adds to the traditional Cartesian view of the world, which is confined to the non-emergent, linear, and often mechanical. Nevertheless, technical systems can certainly have emergent and non-emergent properties at the same time. The weight of a car is a non-emergent property and depends on the sum of the weight of all its parts. Speed, however, critically depends on a particular interaction and thus functional relationship among the parts and can be seen as an emergent property. The irreducibility of emergent phenomena opened the view on new research questions that had been excluded from science so far. The inclusion of questions like order, organisation, reciprocity, wholeness, or teleology changed the understanding of living systems. Moreover, although systemic approaches never resulted in a consistent mathematical theory that is applicable in a universal way, “they created a certain way of thinking, a new language, new concepts, and a whole intellectual climate that has led to significant scientific advances in the recent years” (Capra, 1996, p. 79). The Chilean neurobiologists, Maturana and Varela, developed a systemic understanding of human epistemological processes. They expounded a biologically-based theory of living systems that reaches into the arena of human reflective consciousness and knowledge generation. Gregory Bateson (2002), Margaret Mead, and the German sociologist Niklas Luhmann (1999; Luhmann, 2002) set out to transfer the sometimes highly abstract and technical systemic ideas to social and sociological systems. Luhmann tried creating a universal theory of society as, in his view, current sociological theories fell short of offering a satisfactory global theory for the understanding of a diversified modern society (Luhmann, 1999). Luhmann replaced the physical and organizational boundary of Maturana and Varela’s Johannes B. Schmidt – KA703 8/49 autopoeisis by a symbolic social boundary. This social boundary is self-made by sets of expectations, loyalties, confidentialities, and coordinative acts. However, Luhmann’s endeavor resulted in an extremely abstract language that makes acquisition and application of his theory difficult. We will come back to the issue of increasing abstractness later, when looking at different Kabbalistic descriptions. Cybernetics The word “cybernetic” is rooted in the Greek kybernetes, which is commonly translated as “steersman”, “pilot” or “rudder”. The term denotes the science and art of directing highly complex systems and thus deals with issues of communication and control. The mathematician, Norbert Wiener, together with Ross Ashby is one of the originators of the discipline. According to Wiener, the necessity for control was greatly enhanced in the wake of the mechanization of the World Wars. He considered the eighteenth century as the “age of the clock”, the nineteenth century as the “age of the steam engine”, and the twentieth century as “the age of the ‘servomechanisms’” with the “need of handling the extremely dangerous energy of the atom …” (Wiener, 1948/1961, p. 43). He writes in the preface to the second edition of his foundational book Cybernetics: or Control and Communication in the Animal and the Machine, that “the role of information and the technique of measuring and transmitting information constitute a whole discipline for the engineer, for the physiologist, for the psychologist and for the sociologist” (Wiener, 1948/1961, p. vii). This statement makes clear that cybernetics deals not just with weaponry or technical issues but with the interdisciplinary problem of communicative patterns in any form of organization. Heinz von Foerster clarifies that cybernetic theories use the term “information” in the sense of “signal” rather than in the common sense of “news” (Capra, 1996, p. 64). Heylighen explains that cybernetics (Ashby, 1962; F. Heylighen & Joslyn, 2001) is the science that studies how goal-directed systems can succeed in a complex, variable environment, by counteracting any perturbations that make them deviate from their preferred course. Adopting a more modern terminology, we will call such systems that try to reach their goal by acting upon their environment agents. Agents can be people, organisations, cells, robots, or any living organisms” (2007, p. 2). Johannes B. Schmidt – KA703 9/49 Cybernetics had an impact on several newly emerging sciences including control theory, computer science, information theory, automata theory, artificial intelligence, artificial neural networks, cognitive science, computer modelling, simulation science, dynamical systems and artificial life. Although partly rooted in the understanding of technical systems, mathematical machines, and abstract language, cybernetics contributed to a new view on the basic processes of life – the self-regulatory processes of feedback loops. The idea of feedback loops sparked a process of thinking in circular processes rather than linear progression. The idea of circular causality was described as a self-balancing (negative) or self-reinforcing (positive) circle that has an impact on its own starting point – it feeds back on itself. It is an iterative process for regulating temperature, steering trajectories of ships, airplanes, missiles or keeping the blood sugar at a particular level. Negative feedback loops correct any deviation from equilibrium, and preserve a homeostatic state in living organisms. Any registered variation from a set value is nullified by a corresponding counter-regulation. Positive feedback loops add more of the same and thus make for increasing effect in the cycle and ensuing instability due to a state far from equilibrium. In economics, this principle was dubbed “increasing returns” by Brian Arthur (Waldrop, 1992, p. 17) and shows how those who come first on the market have an advantage that multiplies. Positive behavioral feedback loops are described in common parlance as a vicious circle or self-fulfilling prophecy where the engagement in a particular kind of practice inevitably self-perpetuates until a final point of collapse of the system is attained. In order to prevent the often disquieting effects of a positive feedback loop from gaining full momentum, one has to break the cycle or balance it by the interconnection with a negative feedback loop. Nature, for example, keeps the growth of a population in check through an ongoing scarcity of food. In this way, different contextual conditions interlock and create a self-regulating whole. Capra notes that circular causality is not equal to an actual circular physical arrangement of the constituent parts of a system. He points out that “for the first time in the history of systems thinking, the cyberneticists clearly distinguished the pattern of organization of a system from its physical structure – a distinction that is crucial in the contemporary theory of living systems” (1996, p. 64). Consequently, this insight stimulated a search for pattern recognition in systems that finally deepened the understanding of concepts like self-organization, autonomy, and autopoiesis of living systems (Humbert R. Maturana & Varela, 1980; Johannes B. Schmidt – KA703 10/49 Humberto R. Maturana & Varela, 1987; Varela, 2002). Dealing with patterns of organization became one major focus of cybernetics. Another merit of cybernetic thinking is the recognition that system observers are cybernetic systems themselves (“second-order cybernetics”). This inclusion of the observer evolved with a shift from mechanical systems to organic or social systems in the early 1970s. Heinz von Foerster’s catchphrase, “objectivism is the delusion that ideas can be made without a maker (and can be enacted without an actor)” (cited in Pask, 1996, p. 351), is indicative of the inclusion of the observer as a part of the system. Interaction is needed to understand a system and the particular intention and quality of interaction makes the observer part of the system. Cybernetic systems observation becomes the connection of two self-regulating systems that construct their own internal reality. The inner structure of one system changes according to the interconnection with the environmental system. This point of view shifted the focus from objective systems “out there” to the cognitive and social processes involved. Heinz von Foerster, Humberto Maturana, Gordon Pask, Ranulp Glanville, and Paul Pangaro explored the implications of this observer inclusion. Although Heylighen, Cilliers and Gershenson (2007, p. 2) summarize that “complexity science is little more than an amalgam of methods, models and metaphors from a variety of disciplines rather than an integrated science,” they admit that it can claim “a unified focus”. Despite its mostly formalized language of network clustering algorithms, computer simulations, and non-linear differential equations, or ambiguous ideas and metaphors, its main characteristic is its idiosyncratic way of conceptualizing. It replaces reductionism by a “scientifically-based holism” (p.1). Pask holds the view that cybernetics “permeates all science” (1996, p. 352) although it lacks a clear body of identity. Heylighen & Joslyn (2001) point out that the ubiquitous use of the prefix “cyber-“, which shows the shift in system understanding to “relations, functions and information flows” (p. 5), has become part of a common culture that, more often than not, lacks depth of understanding of the often highly abstract theories involved. Chaos Theory Dynamical systems theory, the mathematical branch of system theory, evolved into an abstract body of descriptive mathematics, which laid the foundations for chaos theory. The non-linear interconnectedness of a wide range of phenomena required a mathematic which