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Waldrop, M. Mitchell, Complexity (1992)

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M. Mitchell Waldrop, Complexity (1992)Edit

Context: Waldrop has a PhD in elementary particle physics at the University of Wisconsin. He has become a scientific journalist and author. At Science magazine he has been a senior writer.


Thesis: This book describes the Santa Fe Institute’s attempts to understanding emergence, life, adaptation, and complexity through a multi-disciplinary approach. It follows the development of the Santa Fe institute (http://www.santafe.edu/) which still exists today. It contends that complexity in life (and in a variety of systems) is due to spontaneous self-organization.


Argument:

1. Spontaneous self-organization

1.1. Causes its components to transcend themselves and acquire collective properties
1.1.1. Everything is interrelated. Nothing can be considered in complete isolation.
1.2. This can only happen at a certain threshold, a place that is sufficiently complex: the edge of chaos.
1.2.1. The edge of chaos is the constantly shifting situation between stagnation and anarchy. It exists between order and chaos.
1.3. These self-organizing systems are adaptive and dynamic
1.4. Positive feedback causes increasing returns :
1.4.1. Early momentum can create additional momentum that ultimately results in a given course of action being the standard (Lock-in) – VHS vs. Beta.
1.5. Collective behavior and self-organization have patterns of behavior; random things don’t always stay random

2. Non-linear thinking:

2.1. The whole can be greater than the sum of its parts
2.2. Best fostered by an accommodating, innovative, reflective, and unique environment
2.2.1. A multi-disciplinary approach allows people to see connections between their fields/ideas and others
2.2.2. Foster differing opinions and dissent
2.2.3. The Santa Fe Institute is such an organization
2.2.4. Such a process breaks down barriers to allow an organization to become spontaneously self-organizing.

3. The balance of centralized and decentralized control:

3.1. Top-level rules cannot cover everything
3.2. Let behavior emerge from the bottom up by channeling it appropriately
3.3. Learning is a process, not an end in itself


Implications for Strategy:

  • Non-linear thinking suggests the need to consider multiple perspectives and/or theories in order to develop a more solid analysis of the given situation. This concept is critical to strategists as they seek to examine a scenario in order to develop recommended actions.
  • Encourage a multi-disciplinary approach with differing opinions.
  • War is undoubtedly a complex system characterized by chaos; as strategists we must find the framework for adaptation within the complexity of war and recognize that connections exist that we may at first not recognize.

Sugar's Tips on Waldrop

This book is one of many popular ones today that deals with the fact that not all organization comes from the top down, but also from the bottom up. Based on a number of various disciplines, scientists are trying to explain everything from how cells multiply into complex organisms, how ants seem to be able to self organize without anyone seeming to give directions, and even how human cities evolve into working communities in the absence of central management. This is called emergence, and it can be used for many different purposes, whether it’s to explain the communal behaviors of slime molds, all the way to explaining the Sunni awakening. The big idea is despite the fact that we tend to believe that things become more disorganized unless someone is consciously acting to organize them (work fighting entropy), things tend to find higher levels of organization even when no one is calling the shots. These scientists seek to answer why this happens.

Another valuable insight from studies of complexity is that at times, meaning in complex systems (especially social ones) is best gained by looking at the aggregate, rather than breaking down the system into individual parts (the implied method we normally prefer to use as evidenced by our inclusion of COG analysis/Strange model in doctrine). Here’s an example that works for me getting this close to dinner – I can describe strawberries, pound cake, and ice cream, but I can’t even get close to understanding why I should save room for strawberry shortcake unless I’ve had the experience of mixing them all together. Works for the components of Martinis even better….

We tend to break things down into meaningful parts, and then try to synthesize meaning by recombining the insights we get from the parts. If you could also look at things from the total first, you might be able to gain additional insights on why the system works the way it does –we don’t just want to understand the nodes of the system, we also want to understand the links which define the relationships between them. Using both, you can make predictions of future behavior, and then also guess about how your proposed actions will influence the system, for better or worse, towards a status quo that you prefer. If you can’t affect the way the system is going, then at least you can anticipate it, and “ride the wave”. We’ll get to this concept later when we read Julien’s “Treatise on Efficacy”. Trying to understand and work within complex systems is the primary driver of “Design”, the system we discussed yesterday.

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