Chapter 6.                            (continued) 

The answer to this critique is disturbing. The problem is not that the Bayesian model doesn’t work as an explanation of human behaviour and thinking. The problem is rather that the Bayesian model of human thinking and the behaviours driven by that thinking works too well. The irrational behaviours individual humans engage in are not proof of Bayesianism’s inadequacy, but rather proof of how it applies to the thinking, learning, and behaviour of individuals and also to the thinking, learning, and behaviour of whole communities and even whole nations.

Societies evolve and change because they each contain some people who are naturally curious. These curious people constantly imagine and test new ideas and new ways of doing things like obtaining food, raising kids, fighting off invaders, healing the sick—any of the things the society must do in order to carry on. Often, other subgroups in society view any new idea or way of doing things as threatening to their most deeply held beliefs. If the adherents of the new idea keep demonstrating that their idea works and that the more intransigent group’s old ways are obsolete, then the larger society will usually marginalize the less effectual members and their system of ideas. In this way, a society mirrors what an individual does when he finds a better way of growing onions or teaching kids or easing Papa’s arthritic pain. In this way, we adapt—as individuals, but more profoundly, as societies—to new lands and markets and to new technologies such as vaccinations, cars, televisions, computers, and so on. Farmers, teachers, and healers who cling to obsolete methods are simply passed by, eventually even by their own grandchildren.

But then there are the more disturbing cases, the ones that caused me to write nearly always above. Sometimes large minorities or even majorities of citizens hang on to obsolete concepts and ways.

The Bayesian model of human thinking works well, most of the time, to explain how individuals form and evolve their basic idea systems. Most of the time, it also can explain how a whole community, tribe, or nation can grow and change its sets of beliefs, thinking styles, customs, and practices. But can it account for the times when majorities in a society do not embrace a new way in spite of the Bayesian calculations showing the idea is sound and useful? In short, can the Bayesian model explain the dark side of tribalism?

  

                                                   Nazi party rally, 1938. Tribalism at its worst.

As we saw in our last chapter, for the most part, individuals become willing to drop a set of ideas that seems to be losing its effectiveness when they encounter a new set of ideas that looks more promising. They embrace the new ideas that perform well, that guide the individual well through the hazards of real life. Similarly, at the tribal level, whole societies usually drop paradigms, and the ways of thinking and living based on those paradigms, when citizens repeatedly see that the old ideas are no longer working and that a set of new ideas is getting better results. Sometimes, on the level of radical social change, this mechanism can cause societies to marginalize or ostracize subcultures that refuse to let go of the old ways. Cars and car people marginalized the horse culture within a generation. Assembly line factories brought the unit cost of goods down until millions who had once accepted that they would never have a car or a t.v. bought one on payments and owned it in a year. The old small-scale shop in which sixteen men made whole cars, one at a time, was obsolete.

The point is that when a new subculture with new beliefs and ways keeps getting good results, and the old subculture keeps proving ineffectual by comparison, the majority usually do make the switch to the new way—of chipping flint, growing corn, spearing fish, making arrows, weaving cloth, building ships, forging gun barrels, dispersing capital to the enterprises with the best growth potential, or connecting a computer to the Internet.