2) Complexity Science

Complexity is perceived by many to be a scientific concept, far removed from everyday life and routine, when in fact it is a phenomenon that not only influences every person externally, but is also present in our physical composition.  Examples of these occurrences are the global climate, ecosystems and the human brain.  Complexity can basically be defined as a parameter or a measurement of a system.  It measures for example the number of elements in a system, the degree to which these elements are connected, the level of diversity among elements also how they may adapt and/or how they self-organize (Systems Academy).

Additionally, the definition of complexity also varies among scientific fields.  In computer science computational complexity is broadly defined as the measurement of the level of difficulty of mathematical problems, describing the requirements of a computer to solve problems.  In Network Theory complexity is a measurement of the intensity of connections between the components of a system, as mentioned above.  In physical systems, complexity is the measurement of characteristics in the state of a quantum system.  In biological sciences complexity also serves as a measurement of the structural intricacy of cells.

Complex Network (Copyright © 2012-2016 33rd Square)

At this stage it is worth noting the difference between ‘complex’ and ‘complicated’.  The Harvard Business Review provides a good example of both.  Complicated systems are defined as systems with many parts or procedural steps, but which “operate in a patterned way”.  Hence, a certain set path of functionality exists.  In contrast, a complex system reflects elements and interactions that constantly change.  The characteristics of complex systems will be discussed at a later stage and will shed more light on how it varies from complicated phenomena.


Additional Complexity text in Further Reading