The whole is greater than the sum of the parts.
This is the essence of a complex adaptive system. Any system that is straightforward enough to be a simple adding up of the effects of each part really isn’t worth contemplating as a system. It’s a collection of independent agents. A stack of checkers of different thicknesses are such a linear system. Stack them up and the height simply adds up in a linear way.
Once the components start acting on each other and themselves, behavior becomes complex and increasingly difficult to predict based on knowledge of the components and their connections. This is not due to ignorance. Collection of more and more data doesn’t help at all. There is some aspect of the whole that is not just the linear addition of the parts.
Once a system is made of connected components that have inputs and outputs, that are processing information, its behavior can become difficult to predict with precision. It could be a mechanical system like a thermostat connected to a heating system, a computer program with subroutines, nerve cells connected in brain circuits, stock traders in a market, the atmosphere are all complex adaptive systems. The mechanical and computer level examples are the most useful for study because they are clearly in the mechanistic, Newtonian, deterministic world and yet their future state cannot be known.
The difference between an additive system and a complex system is in the relationships. Negative and positive feedback create unexpected behaviors in the system. Small effects in one component produce large effects elsewhere because of the nature of the connections which are not simply proportional but non-linear instead.
We’re surrounded by complex systems.Arguably simple linear systems are exceptions and may be idealized simple models rather than real functioning systems out in the world. As thinkers, we study simple systems or simplify the complex into idealized simple systems because they are easy to deal with in a deterministic and reductionistic manner.
We are ignorant of the state of the past and the future. That creates uncertainty. Because of complexity, even if we had perfect knowledge, we’d still be unable to know the future.