Reply to comment

Every good model should provide a diagram or illustration of an idea about how something in the physical world functions. While the thing illustrated can be somewhat intangible or even abstract, such as ideas about the emergence of life or randomness, the designer should pick a single, coherent and concise phenomenon from the physical world. The purpose of the model is then to provide a diagram of a mechanism that could be creating the phenomenon.

For example, a designer who is interested in the phenomenon of traffic jams might design a model to illustrate a possible mechanism of why jams emerge. The model would not replace emperical evidence, which would necessitate looking at cars and drivers in the real world, but could serve to test certain theories and assumptions derived from real world observation to see what would happen if they were true. For example you could use an emergent model to examine how focusing on the distance before the next car might affect a driver’s speed. Essentially, this kind of model (which starts with a theory and forms an instance) works in the opposite direction as scientific observation (which starts with an instance in the physical world and forms a theory) and enables a more effective, cyclical development process.

It’s important to remember that the model doesn’t prove the cause of the phenomenon as different causes may have the same effect. In other words, knowing that A could cause B does not prove that A does cause B because B could be caused by C independently of A. However, we never really know what’s going on in nature; rather, we take observations and tell the best story that we can. Emergent models offer a way to test how good that story is.