Complexity Science

"We cannot solve our problems with the same thinking we used when we created them."
- Albert Einstein


We're all familiar with the idea of using the right tool for the job.  When your job is to understand a Complex Adaptive System, we believe that Complexity Science is that tool.  Here's why:

  • Complex Adaptive Systems usually involve living organisms.  They feature many connected and interdependent elements that have the capacity to change, and the ability to learn from experience.

  • Linear scientific methods would seek to fully understand each individual element of the system, and the cause and effect relationship between the elements.  If you're trying to understand a more mechanical, non-living system, these methods work nicely.  For example, if you want to understand  how and why a clock works, go with the linear scientific method.

  • Non-linear scientific methods also seek to understand the individual elements of a system, but in addition, they examine patterns of relationships, how they are sustained, how they self-organize, and how outcomes emerge.  If you're trying to understand how and why societies, financial markets, or biological systems function, we prefer the non-linear approach.

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