The Believing Brain - Michael Shermer [30]
If you assume that the rustle in the grass is just the wind but it turns out that it is a dangerous predator, you have made what is called a Type II error in cognition, also known as a false negative, or believing something is not real when it is. That is, you have missed a real pattern. You failed to connect (A) a rustle in the grass to (B) a dangerous predator, and in this case A was connected to B. You’re lunch. Congratulations, you have won a Darwin Award. You are no longer a member of the hominid gene pool.
Our brains are belief engines, evolved pattern-recognition machines that connect the dots and create meaning out of the patterns that we think we see in nature. Sometimes A really is connected to B; sometimes it is not. The baseball player who (A) doesn’t shave and (B) hits a home run forms a false association between A and B, but it is a relatively harmless one. When the association is real, however, we have learned something valuable about the environment from which we can make predictions that aid in survival and reproduction. We are the descendants of those who were most successful at finding patterns. This process is called association learning and is fundamental to all animal behavior, from C. elegans to H. sapiens. I call this process patternicity, or the tendency to find meaningful patterns in both meaningful and meaningless noise.
Unfortunately, we did not evolve a baloney-detection network in the brain to distinguish between true and false patterns. We have no error-detection governor to modulate the pattern-recognition engine. The reason has to do with the relative costs of making Type I and Type II errors in cognition, which I describe in the following formula:
P = CTI < CTII
Patternicity (P) will occur whenever the cost (C) of making a Type I error (TI) is less than the cost (C) of making a Type II error (TII).
The problem is that assessing the difference between a Type I and Type II error is highly problematic—especially in the split-second timing that often determined the difference between life and death in our ancestral environments—so the default position is to assume that all patterns are real; that is, assume that all rustles in the grass are dangerous predators and not the wind.
This is the basis for the evolution of all forms of patternicity, including superstition and magical thinking. There was a natural selection for the cognitive process of assuming that all patterns are real and that all patternicities represent real and important phenomena. We are the descendants of the primates who most successfully employed patternicity.
Note what I am arguing here. This is not just a theory to explain why people believe weird things. It is a theory to explain why people believe things. Full stop. Patternicity is the process of seeking and finding patterns, connecting the dots, linking A to B. Again, this is nothing more than association learning, and all animals do it. It is how organisms adapt to their ever-changing environments when evolution is too slow. Genes are selected for and against in changing environments, but this takes time—generations of time. Brains learn, and they can learn almost instantaneously—time is not an issue.
In a 2008 paper entitled “The Evolution of Superstitious and Superstition-Like Behaviour,”1 Harvard biologist Kevin R. Foster and University of Helsinki biologist Hanna Kokko tested an earlier version of my theory through evolutionary modeling, a tool used to assess the relative costs and benefits of different relationships between organisms. For example, to whom should you offer help? In evolutionary theory, altruistically helping others seems problematic because