This dictionary introduces the most important (physical) concepts to understand self-organisation and transformation processes.<\/p>\n\n\n\n\n\n\n\n
Contrary to how we use the term chaos in our daily language, chaos in physics does not denote complete disorder, but actually requires some state of order!<\/strong> \u201cChaos is a self-organising<\/a> process\u201d, which results from the non-linear interactions of many different elements[1: p.304]<\/sup>. Non-linearity<\/em> results from the system\u2019s complexity<\/a><\/em><\/strong> \u2013 it\u2019s plurality of parts and large number of possible dynamics amongst them.<\/p>\n\n\n\n Chaos theory is more commonly known as the “butterfly effect”; a stroke of a butterfly\u2019s wing may cause a tornado on the other side of the globe. This illustration emphasises one of the most important characteristics of chaos: a minor change in the root cause (wing flap), may lead to a major impact (tornado). Therefore, we observe a non-linear relationship between input and output.<\/p>\n\n\n\n Contrary to our linear understanding of causality of our mechanistic image of the world \u2013 a certain input causes certain output \u2013 a property of chaos is that the output is not that easily predictable. Chaotic processes are only contingently predictable<\/em>, because small deviations in a process may lead to large differences in the further course of events. Contrary to our intuition, however, chaotic processes are generally deterministic<\/em>, which means that they are \u2013 at least theoretically \u2013 fully explainable. Except, of course, if quantum mechanical randomness<\/a> is at play (strong emergence<\/a>). Chaos arises from the non-linear interactions happening in complex systems. Our brains, social interactions and organisations are all examples of such \u201cchaotic\u201d systems.<\/p>\n\n\n\n