Chapter 8.                     How Pervasive Is Bayesianism? 

                      Girls Learning Sign Language, a code for communicating  

                              (credit: David Fulmer via Wikimedia Commons) 

The idea behind Bayesianism is straightforward enough to be grasped by nearly all adults in all lands. But radical Bayesianism escapes us. The radical form of Bayesianism says all we do fits inside the Bayesian model. But it is very human to dread such a view of ourselves and then to slip into thinking Bayesianism must be wrong. We want desperately to believe that at least a few of our ideas are unshakable. Too often, unfortunately, people think they have found such an idea. But a true Bayesian knows that probably the only absolute truth is the one that says there are no absolute truths. In reality, even though we suspect that our familiar ideas and beliefs are not perfectly certain, we still use them to interpret, reason, and act in the world. Why? Because we have to. We have to move through the day. We can’t sit catatonic. We gamble that smart gambling is the best of our choices for ways to get through the decade and the day.

An idea is a mental tool that enables you to sort and respond to sensory experiences – single ones or whole categories of them. ("Balsamroot! Tasty.”) (“Poison ivy here. Stay away.") ("That’s a clip of Martin Luther King in Selma. That’s real courage.")

 

When you find an idea that enables quick, accurate sorting, you keep it. What can confuse and confound this whole picture is the way that, in the case of many of your most deeply held, deeply programmed ideas, you didn’t find them. They came by trial-and-error to some of your ancestors, who found the ideas so useful that they then did their best to program these ideas into their children. Then, the ideas were passed down the generations to you.

 

Many ideas you acquire are added to your mental toolkit after Bayesian analysis by the process of your own noticing, considering, and testing them. But you pick up many more ideas from your family and tribe. This cultural programming is being instilled in you because people of your tribe acquired, tested, and affirmed those ideas by the first process. Furthermore, those ideas worked. Your forbears survived well enough to pass those ideas down the generations to you partly because they had adopted and used those ideas.

 

Observe, hypothesize, test, adjust, test some more: these are the marks of Bayesianism, the model by which we grow and move forward, individually and as nations. And a Bayesian never concludes about any of his ideas that the idea is final.

 

Culture, consciousness, even sanity, are constantly evolving for all humans all the time. All of us keep updating our ideas/beliefs. This is true for ideas as complex as justice and love and as basic as up and down. (Individual minds can indeed be made to reprogram their notions of up and down.¹) And in this picture, “I” is a dynamic, self-referencing system that is constantly checking its perceptions of the evidence in reality against ideas, models, and concepts of what it believes reality should be, then updating itself.

 

Admittedly, a few very general ideas are not acquired by humans via either of the above methods of individual learning or social programming. They are hardwired into us by our genetic code. They don’t fit into either of the categories just described. But they fit inside the Bayesian model because they can be studied by scientists using Bayesian methods.

 

Some of the genes that cause a language center to develop in a fetus’ brain are still being located. The brain areas holding them also are only partly understood. But they’re being studied in physical reality (e.g. Broca’s area). They are not nebulous Rationalist concepts about concepts.  

 

In our present discussion, we can pass these innate concepts by. They are biological rather than philosophical – hardware rather than software – so they are outside of our present scope. These genes, and the brain structures that are built from the information coded into them, may even be manipulated one day, for a whole range of possible ends, by behavior modification, genetic engineering, drugs, surgery, or other technologies we today can’t imagine.

 

But for our purposes here, in our search for a universal code of moral values, Neurophysiology’s usefulness runs out. Whether techniques for manipulating the brain/mind will be judged right or wrong and whether they will be allowed in our society will still depend on values already programmed as “software” into future tribes of humans. Values like freedom and dignity. These values, as we have already seen, are going to need something more in the code at their core than what is offered by our current Science.

 

Empiricism, as a moral guide, has proved unreliable in theory and practice. In short, so far, Science has failed at being its own moral guide.

 

Even in Neurophysiology, knowing the structure of the brain cannot tell us how brains should be used. Bodies and brains are hardware; moral codes are software. How we should program hardware is not revealed by studying hardware. What ideas we should put into brains is not made clear by studying brains.  

 

Figuring out what we should be programming into human minds requires that we examine the fit between our software – including our moral codes – and reality, i.e. the world. Do our morals work? Do they lead us to live wiser, healthier lives and, most of all, to survive? In the end, that is the crucial test of any moral code. This thought returns us to our project of finding a foundation for some new core software – i.e. a new moral code – and so to Bayesianism. 

 

The Bayesian model of how we think is so radical that at first it eludes us. To each individual, the idea that he must continually adjust his entire mindset, and that no parts of it, not even the most deeply held ideas of who he is or how reality works, can ever be fully trusted, is disturbing to say the least. Doubting our most basic concepts is like flirting with mental illness. Even considering the possibility is upsetting. But this radical Bayesian view is certainly the one I arrive at when I look back honestly over the changes I have undergone in my own life. The Bayesian model of how a “self” is formed, and how it evolves as the organism ages, fits the set of memories that I call my “self” exactly.

 

Thomas Kuhn is the most famous of the philosophers who have examined the processes by which people adopt a new theory, model, or way of knowing. His works focus on how scientists adopt a new scientific model, but his conclusions can be applied to all thinking. His most famous book implies that all our ways of knowing, even our most cherished ones, are tentative.² Human knowledge grows and changes as humans advance, by paradigm shifts, from obsolete ideas to newer, more effective ones – i.e. by leaps, rather than in a steady march of gradually growing understanding. We “get” a new theory by a kind of experience that is like a religious conversion.

 

Thus, Kuhn confirms what Bayesianism tells us about our ways of growing our thinking: real growth is always surprising; it always moves into newer, better ways of thinking by a revolution inside our sets of beliefs. In this book, the moral code we are aiming to write for future generations of humans round the world is going to have to take this evolving nature of human culture into account. Our new code is going to have to provide for its own constant updating.

 

Caution and vigilance seem to be the only rational attitudes to take under such a view of the universe and the human place in it. To many people, the idea that all the mind’s routines, perhaps even the mind’s operating system – i.e. its sanity – are tentative and subject to constant revision seems absurd. 

But then again, cognitive dissonance theory leads us to predict that we would dismiss such a scary picture of ourselves. We don’t want to see ourselves as incapable of forming any unshakeable beliefs. But history and experience both show that we’re almost completely devoid of any unshakable concepts. (Why I say almost completely will become clear shortly.) 

 

Ultimately, our way of thinking, learning, and evolving in all matters is either Bayesian or doomed. On the tribal scale, tribes either evolve or die out. That’s a rule of living. In real existence, real survival, there is no other way.

 

At this point in the discussion, opponents of Bayesianism begin to marshal their forces. Critics give many reasons for disagreeing with Bayesianism. I will deal with the two most telling – one is practical and evidence-based, and the other is theoretical. We’ll disarm the evidence-based attack in the next chapter, the theoretical one in the chapter after that.

 

 

 

Notes

 

1. Jan Degenaar, “Through the Inverting Glass: First-Person Observations on Spatial Vision and Imagery”

Phenomenology and the Cognitive Sciences 12, No. 1 (March 2013).

 

2. Thomas Kuhn, The Structure of Scientific Revolutions (Chicago: University of Chicago Press, 3rd ed., 1996).