Models are frequently used as a way to understand, explain, and design representations of what we observe in the world around us. We assume that we can reduce the complexity of whatever we are studying into a coherent, meaningful, and simple enough representation so we can use it as a tool to explain what we see and perhaps even help us create software systems that can solve problems for us. The thing is, though, that complexity will not submit to our wish to control it, regardless of how beautiful and clever our models of it are.

In this talk, we will take a closer look at what problems we can run into if we think we can manage or even subdue complexity in our attempt to model it. Using systems thinking we will learn that the approach to framing reality in a model so we can grasp it will be wildly different to the model we will need to design to reduce reality to fit into the mechanics of software systems. Thinking in systems is not the same as designing them; conflating these destroys both what we seek to understand and what we wish to create.