Complexity 101. Robert M. Pirsig Zen and the Art of Motorcycle Maintenance (1974) IBM 10th April 2007 COGNITIVEEDGE

Transcription

1 COGNITIVEEDGE Complexity 101 IBM 10th April 2007 Traditional scientific method has always been at the very best hindsight. It s good for seeing where you ve been. It s good for testing the truth of what you think you know, but it can t tell you where you ought to go Robert M. Pirsig Zen and the Art of Motorcycle Maintenance (1974) Copyright 2007 Cognitive Edge. All Rights Reserved. 2

2 Joining up the dots... Boisot Omnipedia issue 6 Sept/Oct 2004 Dots Number of dots Number of possible links Number of possible patterns N=4 L=6 P=64 Links Patterns N=10 L=45 P=3.5 trillion N=12 L=66 P=4,700 quadrillion L= N(N-1)/2 P=2L Copyright 2007 Cognitive Edge. All Rights Reserved. 3 For to say that, assuming the earth moves and the sun stands still, all the appearances are saved better than with eccentrics and epicycles, is to speak well; there is no danger in this, and it is sufficient for mathematicians. But to want to affirm that the sun really is fixed in the center of the heavens and only revolves around itself (i. e., turns upon its axis ) without travelling from east to west, and that the earth is situated in the third sphere and revolves with great speed around the sun, is a very dangerous thing Cardinal Bellarmine Letter to Foscarini April 12th 1615 Copyright 2007 Cognitive Edge. All Rights Reserved. 4

3 A brief history (1) Complexity is about two very simple ideas: The sensitivity of a system to its starting conditions & feedback (but that is rather like saying DNA is about four chemicals) Science made progress by ignoring complexities (to great effect): the laws of motions and of thermodynamics Poincaré: gravity can behave in a chaotic and unpredictable fashion Phase space and the idea of a landscape (Hamilton) Copyright 2007 Cognitive Edge. All Rights Reserved. 5 A brief history (2) Richardson & then Lorenz: weather forecasting: Does the flap of a Butterfly s Wings in Brazil set of a Tornado in Texas Washington 1972 Period doubling, bifurcations (May 1976) leading to Feigenbaum & Mandelbrot From Chaos to complexity: Onsager & Priogogine (hexagonal convection cells) Kauffmann & the importance of networks, evolution as phase transformation, fitness landscapes and the Red Queen problem Arthur challenged neo-classical economics and equibrium thinking Stacy in management & others Copyright 2007 Cognitive Edge. All Rights Reserved. 6

4 Attractors Point Strange Limit Cycle Copyright 2007 Cognitive Edge. All Rights Reserved. 7 Cillier s list Complex systems consist of a large number of elements A large number of elements is necessary but not sufficient The interaction is rich and diverse The interactions are non-linear & small causes can have large consequences & vice versa The interactions usually have a fairly short range There are loops in the interactions (enhancing/stimulating or detracting/inhibiting) Complex systems are usually open systems Complex systems operate under conditions far from equilibrium (equilibrium equals death) Complex systems have history, the past is co-responsible for present Each element in the system is ignorant of the behaviour of the system as a whole, it responds only to local information Copyright 2007 Cognitive Edge. All Rights Reserved. 8

5 Axelrod & Cohen model Strategy, a conditional action pattern that indicates what to do in which circumstances Artefact, a material resource that has definite location and can respond to the action of agents Agent, a collection of properties (especially location), strategies and capabilities for interacting with artefacts and other agents Population, a collection of agents, or, in some situations, collections of strategies System, a larger collection, including one or more populations of agents and possibly also artefacts. Type, all the agents (or strategies) in a population that have some characteristic in common Variety, the diversity of types within a population or system Interaction pattern, the recurring regularities of contact among types within a system Space (physical), the location in geographical space and time of agents and artefacts Space (conceptual), the location in a set of categories structured so that nearby agents will tend to interact Selection, processes that lead to an increase or decrease in the frequency of various types of agent or strategies Success criteria or performance measures, a score used by an agent or designer in attributing credit in the selection of relatively successful (or unsuccessful) strategies or agents. Copyright 2007 Cognitive Edge. All Rights Reserved. 9 Self Organisation (Cilliers) Structure is not the result of an a priori design, nor is it determined directly by external conditions. It is a result of interaction between the system and its environment The internal structure of the system can adapt dynamically to change, even if change is not regular Not merely the result of processes, involves higher order non-linear process It is an emergent property of the system as a whole Increase in complexity over time Cannot happen without some form of memory Cannot be driven by function Reductionist descriptions cannot be used Copyright 2007 Cognitive Edge. All Rights Reserved. 10

6 In the idealistic approach, the leaders of an organisation set out an ideal future state that they wish to achieve, identify the gap between the ideal and their perception of the present, and seek to close it. This is common not only to process-based theory but also to practice that follows the general heading of the learning organisation. Naturalistic approaches, by contrast, seek to understand a sufficiency of the present in order to act to stimulate evolution of the system. Once such stimulation is made, monitoring of emergent patterns becomes a critical activity so that desired patterns can be supported and undesired patterns disrupted. The organisation thus evolves to a future that was unknowable in advance, but is more contextually appropriate when discovered Kurtz & Snowden Bramble Bushes in a Thicket Copyright 2007 Cognitive Edge. All Rights Reserved. 11 Human complexity The pattern basis of human intelligence & decision making Pliocene hunter gatherers The role of language The question of identity The ability to create order The role of technology & tools in general (e.g. blogs as a form of distributed cognition) Distributed consciousness Natural numbers: 5, 15, 150 & 5m Complex P-S-R Monitor Chaotic A-S-R Innovate Complicated S-A-R Analysis Simple S-C-R Doctrine Copyright 2007 Cognitive Edge. All Rights Reserved. 12

7 Sensemaking Framework TECHNO-FABULISTS NATURALISTIC EVOLUTIONARY ART-LUDDITIES NATURE OF THE SYSTEM Ordered Complex Chaotic HOW WE PERCEIVE Information processors Pattern processing Ideology & power THE WAY WE KNOW Explicit Narrative Experiential Copyright 2007 Cognitive Edge. All Rights Reserved. 13 The landscape of management Complex Output Computational Complexity a simulation Naturalistic Sense making an ecology Simple Output Process Engineering a machine Systems Dynamics an organism Simple Input Complex Input Copyright 2007 Cognitive Edge. All Rights Reserved. 14

8 Antonyms Efficiency Stability Exploitation Rules Categorisation Taxonomic Effectiveness Resilience Exploration Heuristics Relationships Serendipitous Copyright 2007 Cognitive Edge. All Rights Reserved. 15 Thank You! Copyright 2007 Cognitive Edge. All Rights Reserved. 16