Biomimicry 104 – Complex Adaptive Systems

In continuation on my journey of developing the skills necessary to see the extraordinary from the ordinary in nature, I learnt about fractals and the patterns which it creates. THe next thing I came across was the concept of designing and understanding complexity through systems thinking. This lead me to learn more about Complex Adaptive Systems – which are very different from the linear systems we are often used to.

I read a few articles about this;

  • Redesigning Health Care with Insights from the Science of Complex Adaptive Systems by Paul Plsek
  • Embracing Chaos and Complexity: A Quantum Change for Public Health by Kenneth Resnicow and Scott E. Page

“What we call chaos is just patterns we haven’t recognized. What we call random is just patterns we can’t decipher. What we can’t understand we call nonsense. What we can’t read we call gibberish”
Chuck Palahniuk

Complex Adaptive Systems are made of many parts with their own behavior and rules. There are several hallmarks of this system which in its chaos and complexity, can still breed innovation and creativity. Several features of the Complex Adaptive System includes;

  • Adaptable Elements
  • Simple Rules
  • Non-linearity
  • Emergent Behaviour
  • Context & Embededness
  • Co-evolution

We find it difficult to comprehend or create such systems because of our “scientific” method of learning which dates back to the reinsurance period whereby the “further study of the parts of systems will lead to deeper understanding and predictability”. We were trained to think of the “one best way” to answer problems, questions and difficulties in our lives. Such thinking cannot bring us into the future where complex and multi-factorial, multi-stakeholder problems plaque us. In a chaotic situation, we find that creating more rules to restrict and reach a desired outcome is almost innate.

Its kind of like the old computer simulation, Game of Life, where you enter points and you watch how it randomly simulates life. The rules of this program were simply;

  1. Any live cell with fewer than two live neighbours dies, as if caused by under-population.
  2. Any live cell with two or three live neighbours lives on to the next generation.
  3. Any live cell with more than three live neighbours dies, as if by overcrowding.
  4. Any dead cell with exactly three live neighbours becomes a live cell, as if by reproduction.

In moving forward, we must learn to live with complexity and appreciate the individual and its place in the entire scheme of things. We must believe that our individual actions amount to larger things beyond our sight. And as leaders and creators of systems, we have to learn to let go to let come. Create simple rules and let the future emerge from it.

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