An Introduction to Complexity Theory


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As part of the highly successful lunchtime talk series, the contemporary Tavistock Institute of Human Relations (TIHR) food-for-thought programme, Eliat Aram, the Institute’s CEO introduced staff and guests to some key concepts and philosophical underpinning of Complexity theory and its implications to understanding organisational praxis.

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  • Prigogine: definition of dissipative structures in thermodynamics systems and far from equilibrium for which he won the Nobel prize in Chemistry in 1977. He has shown how nonlinear systems develop unpredictable forms of behaviour when they operate far from equilibrium. In 1997 he wrote “The End of Certainty” where he departs from determinism (Einstein, Newton, Schrodinger (quantum physics; the thought cat experiment) saying that determinism loses its explanatory power in the face of irreversibility and instability (= a ball at the top of the hill is an unstable situation). Murray Gell-Mann, a Nobel price winning physicist from the Santa Fe institute in Mexico, his book is called ‘adventures in the simple and the complex’ and the title is taken from an Arthur Sze (chineseamerican poet) poem: “"The world of the quark has everything to do with a jaguar circling in the night." Goodwin, a biologist, wrote about the Heart and its beat and how a healthy heart beat is paradoxical, both stable and unstable at the same time.
  • A theory of connections = nonlinear connections
  • With the developing capacity to compute difficult mathematical equations, it has become possible to investigate formula containing both positive and negative feedback. Mathematical chaos reveals patterns in phenomena previously thought to be random. The patterns are paradoxically regular and irregular, stable and unstable.
  • This more complex structure is called dissipative structure because it takes energy to sustain the system in that new mode.
  • 1. For example, a living cell is made up of huge numbers of interacting proteins, lipids, and nucleic acids and the human brain is a network of billions of interconnected neurones. Organisations too were thought of as complex adaptive systems consisting of many interacting individuals with their ideas and beliefs.2.This means that their evolution cannot be traced back to simple explanations of cause and effect. ‘The genes in a developing embryo organise themselves in one way to make a liver cell, and in another way to make a muscle cell’ (Waldrop, 1992:12). 3. means that agents interact locally and that it is in this local interaction that global patterns emerge without any global blueprint, design or programme. The systems evolve in an intrinsically unpredictable manner into an undetermined future. They are interdependent, with local action at one scale having unpredictable consequences at all scales through complex relationships over time. They co-create their future.4. taking the form of both positive and negative feedback, can, broadly speaking, display three dynamics:stable to the point of rigidity;unstable to the point of disintegration; paradoxically, patterns that are both stable and unstable simultaneously – edge of chaos / bounded instability Although the dynamic at the edge of chaos is required for novelty to emerge it is not a guarantee for survival. In addition to the emergence of New there may be some big extinction events. 5. Diversity: is a pre-requisite for the system of the new. A system displays the internal capacity to change spontaneously only when agents comprising it are DIFFERENT from one another – microdiversity.
  • When the agents in a complex adaptive system differ from each other, the system displays the capacity to transform itself. It is only at a critical level of diversity that a system can produce novelty (Allen, 1998 a & b). Such systems are adaptive in that they do not simply respond to events, but evolve or learn. Each agent is guided by its own schema, or rules of behaviour, and also by schema shared with other agents. Interpreted in the organisation literature, single-loop learning occurs when schema remain unchanged, while double-loop learning involves changes in current schema, so producing more fundamental changes of kind (Argyris & Schon, 1978). Through double-loop learning 'species evolve for better survival in a changing environment - and so do corporations and industries' (Waldrop, 1992: 11). 'Competition and conflict emerge and the evolution of the system is driven by agents who are trying to exploit each other, but the game can go on only if neither side succeeds completely or for long in that exploitation' (Stacey, 1996b: 340).
  • The philosophical underpinnings of our thinking about the nature of causality are relevant for understanding the nature of stability and instability, continuity and novelty, especially to one type of cause, namely teleological or ‘final’ cause. Teleological cause attempts to answer the ‘why’ question. Why does a particular phenomenon becomes what it becomes? What is the purpose that causes the phenomenon to do what it does or to become what it becomes?5 of those:
  • Secular natural law teleology: Newtonian way; if-then; efficient causality; phenomena as mechanism; future is a predictable repetition of the pastBased on Kant, 2 causalities: Formative : the system through its formative process unfolds a future already enfolded in it. The identity of the system is predetermined and therefore “known”. Organisation then is continuity of form with only small variations and no true novelty is possible. Rationalist: Humans as autonomous individuals who are free to make ethical choices. Are able to act on the basis of reason, to set their own goals and design the actions required to achieve them. This is a causality of freedom. This is the basis of systems thinking. Adaptionist – Neo Darwinian way of thinking about evolution as the emergence of the novel but driven by chance and competitive selectionTransformative – here the future is under perpetual construction in the ongoing interaction between individual human beings (agents). Individual and collective identities emerge in these interactions as continuity (the experience of) as well as potential transformation. The transformation is unpredictable. The process of construction is that of forming and being formed at the same time. First 3 assume movement towards a knowable future last 2 assume movement towards an unknowable future.
  • An Introduction to Complexity Theory

    1. 1. Complexity: An Introduction<br />Eliat Aram<br />The TIHR Lunchtime Talks Series<br />June 2011<br />
    2. 2. The complexity sciences originated in mathematics, physics, chemistry and biology:<br />Prigogine & Stengers, 1984: Order out of Chaos <br />Gleick, 1987: Chaos: Making a New Science<br />Waldrop, 1992: Complexity: The Emerging Science at the Edge of Chaos<br />Gell-Mann, 1994: The Quark and the Jaguar <br />Kauffman, 1995: At Home in the Universe<br />Coveney& Highfield, 1995: Frontiers of Complexity <br />Goodwin, 1995: How the Leopard Changed its Spots <br />
    3. 3. Ideas from these new sciences were taken into theorising about organisations and management during the 1990s<br />Allen, 1998: Modelling Complex Economic Evolution; Evolving Complexity in Social Science in Systems: New Paradigms for the Human Sciences <br />Whitley, 1992: Leadership & the New Science: Learning about Organisations from an Orderly Universe <br />Stacey, 1991: The Chaos Frontier; 1992: Managing the Unknowable; 1993: Strategic Management & Organisational Dynamics; 1996: Complexity & Creativity in Organisations; - to name a few<br />Stacey, Griffin & Shaw: Complexity & Management: Fad or Radical Challenge to Systems Thinking? <br />
    4. 4. Chaos Theory <br />The dynamic of Mathematical Chaos:<br />Bifurcation points?<br />Strange attractor?<br />State of non-equilibrium ?<br /> non-linearity?<br />= PARADOX : stable and unstable; predictable and unpredictable, at the same time <br />
    5. 5. Chaos in Nature:<br />The weather system:<br /> Comprises patterns in interdependent forces such as pressure, temperature, humidity and wind speed that are related to each other by nonlinear relationships<br />
    6. 6. The Edge of Chaos <br />The paradoxical dynamic has become known as the “edge of chaos”, a dynamic where order and disorder co-exist. <br />‘The edge of chaos is where life has enough stability to sustain itself and enough creativity to deserve the name of life. It is the constantly shifting battle zone between stagnation and anarchy, the one place where a complex system can be spontaneous, adaptive, and alive’ <br />(Waldrop, 1992: 12).<br />
    7. 7. Dissipative Structures: <br />Chaos performs the important task of amplifying small changes, or fluctuations, in the environment, causing the instability necessary to shatter an existing behaviour pattern and make way for a different one. <br /> Systems may pass through states of instability and reach critical points where they may spontaneously self-organise to produce a different structure or behaviour that cannot be predicted from a knowledge of the previous state. <br />
    8. 8. What if? <br />We LIVE at the edge of chaos?<br />Our lives characterised by a state of paradoxical <br />Existence?<br /> Order and chaos – planning and emergence –predictability and unpredictability – all always at the same time? <br />
    9. 9. Complex Adaptive Systems: <br />Organisms can be understood as complex adaptive systems made up of many interacting agents. <br />Complex adaptive systems are nonlinear and self organising with emergent futures. <br />Self organisation? <br />emergence?<br />Criterion of diversity<br />
    10. 10. Complex? Adaptive? <br />Capacity for Learning<br />Single and double loop learning (Argyris & Schon, 1978). <br />Through double-loop learning 'species evolve for better survival in a changing environment - and so do corporations and industries' (Waldrop, 1992: 11). <br />'Competition and conflict emerge and the evolution of the system is driven by agents who are trying to exploit each other, but the game can go on only if neither side succeeds completely or for long in that exploitation' (Stacey, 1996b: 340).<br />
    11. 11. Self organising process:<br /> A complex adaptive system is capable of self organise, i.e., produce emergent novelty when it operates in the dynamic at the edge of chaos<br /> This capacity consists of iterative non linear interactions<br /> These interactions are heterogeneous and hence take on a life of their own which means they are characterised by transformative rather than formative causality <br />
    12. 12. Profound and contentious implications: <br />Life in the universe and life in organisations arises from a dialectic between competition and cooperation, not from an unconstrained competition => emerging order which is unpredictable<br />Through an internal process of self organisation the system produces both parasites and something like predator-prey dynamic => potential for tidiness and harmony of cooperation together with dissonance, destruction and messy competition<br />Evolution: not an incrementally progressive affair but a rather stumbling sort of journey in which a system moves both forwards and backwards and that- <br /> – is the most effective way to proceed! <br />
    13. 13. More profound and contentious implications: <br />Identity – personal and organisational – is based in transformative causality<br />Life in organisation – strategic management, leadership, consultancy, research, design – operates at the edge of chaos and is hence<br />Paradoxical <br /> Unpredictable <br />nonlinear and conversational<br />
    14. 14. Teleological Causalities:<br />Secular law teleology<br />Formative teleology<br />Rationalist teleology<br />Adaptionist teleology<br />Transformative teleology <br />
    15. 15. So ... ?<br />What happens to order and hierarchy?<br />What about our sense of control?<br />What does ‘knowledge’ mean? <br />Implications for our work? <br />Who am I? How to understand self, mind and identity ? <br />Any other questions? <br />