We prefer simple models to complicated ones. Circles to ellipses, a single ancestor to a soup. But is that really because the simple explanation is more likely?
The value of keeping assumptions to a minimum is cognitive.
Philip Ball, The Tyranny of Simple Explanations
Simpler theories are more useful because we can think about them more easily. We can pass them from person to person.
But now we have software, which can encapsulate complicated theories almost as easily as simple ones. We can package them up into products and make use of them, without taking up brainspace with all those complications.
Maybe you still find simple models most likely in physics. Simple models are not accurate in biology – much less in human interactions.
In biology, everything going on had some reason it got that way (might be randomness) and many reasons that it stays that way. Most adaptations are exaptive — used for some purpose other than their original purpose. Most have many purposes, the proteins participate in multiple pathways, the fur is warm and also distinguishing, the brain anticipates danger and builds social structure.
In our own lives, every action has multiple stories. I’m playing this game to relax, I’m playing this game to avoid writing, I’m playing this game to learn from it.
We choose based on probability spaces from many models, stacked on top of each other. I buy this dress because I feel powerful in it, because I deserve it, because my date will like it, because I am sloppy with money. I value this relationship because I don’t know how to be alone, because they’re a kind person, because we belong together, because he reminds me of the father figure from my childhood.
This is right, this is healthy, to have all these stories. In real life, the simple explanation is never complete. Taking action for exactly one reason is unnatural. Like gaming a metric, it fails to account for the whole rest of the system.
Everything we do in a complex system has many effects, so it is right that we have many overlapping reasons. This doesn’t make life easy, only real.
When I started in software I loved that it was simple and predictable. Now I love that it is complex and messy, because that’s where I learn the important stuff.