AXIOM: A1 of impelling purpose
WHAT: A system, discriminated from its surroundings, is a set of models of our reality created by people for reasons which give meaning to and determine the purpose of the system
WHY: We identify a system because we are curious and want to understand (science), or wish to modify the world around us to improve the human condition (engineering, medicine) or express our emotions (art, religion). Our purpose in identifying the system is our highest goal. That goal provides us with meaning and motivates us to put in effort to add value. Identifying purpose draws on our emotional intelligence to help us reflect on and understand WHY we think and act, what we value and how we can improve how we work together.
Axiom: A2 of appropriate layers
WHAT: Systems models are holons i.e. they are both parts and wholes and hence are layered according to levels of detail and abstraction.
WHY: Thinking of a system in layers helps us cope with size, scale and dimensionality. Models of holons at different levels can be different but still be inter- dependent.
AXIOM: A3 of complex interdependency
WHAT: Holons are connected to certain other holons with which they exchange messages.
WHY: In a complex world everything seems to be interconnected and hence inter- dependent. Outcomes are often unintended. We can simplify by focussing on local connections in a manner similar to the internet of connected computers.
WHAT: A4 of the ubiquity of change
WHAT: Systems models change at varying rates but none are permanent and invariable. Some changes may be unforeseen. Some changes may be small but some may be ‘revolutionary paradigm shifts’ involving new ways of thinking.
WHY: Most of us think of matter or substance as the permanent stuff of which something is composed and form as the way that stuff is put together. Interestingly eastern traditions emphasise flow and change as things come into being and cease to be. This view ties in with the spontaneous random fluctuations of energy in a quantum space.
AXIOM: A5 of evolutionary learning
WHAT: Complex systems often cannot be ‘solved’ rather they have to be managed to desirable outcomes.
WHY: Learning reduces uncertainty. Learning is too often seen as rote learning of facts and techniques and ‘how to do something’. Learning to learn or ‘learning power’ has much to offer in finding our way through uncertainty.