Chapter 8.                                 (continued) 

In furthering our goal of constructing a moral code that is founded on our best understanding of reality, these last three chapters have served only one purpose. They have left us with a model of the mind—and what it does as it thinks and “knows”—called Bayesianism.

   

The most paralyzing confusion in my mind about how to best realize my prime directive occurs when I am trying to decide between the preservation of myself and that of others outside myself. Even deeper than our minds is the basic programming of sex and reproduction. We’re built to love our kids, and since we want them to survive so much, we learn to be motivated about the survival of our tribe. Gradually, as we mature, we learn to expand this circle of moral consideration to our nation. Our most interesting literature dramatizes situations that portray heroes trying to sort through choices between their own survival and that of their families, nations, etc. We find such stories challenging and fascinating. In such literature, we are seeking models to guide us through possible future situations in which we may have to choose between saving ourselves and saving our children, our nation, or our species. I, like all my fellow humans, want to live. But I want my kids and my country and its way of life to survive too. Bayesian decision processes get confused in such dilemmas. We feel this confusion as what we call “anxiety”. What outranks what?   

   

Shakespeare’s Hamlet still holds the stage for exactly this reason. Hamlet can’t see any point in this life of treachery in which the bad succeed by being bad. But in the end, he realizes he is willing to die for the restoring of order in his beloved country, Denmark. The rest he will leave for God to sort out.

There are, of course, no neat, simple answers to such questions, no unfailingly reliable guides. Reality is uncertain, subtle, complex, and frightening. No sets of programs we can devise will ever enable us to live in reality without running into anxious challenges and rude surprises. Still, the bottom line is that reality is where we must live. Therefore, in our universe, it is sad but true that a moderate but constant anxiety is the natural human condition. Anxiety is the downside for us of surviving in the probabilistic real world. The upside is freedom. If we are brave enough, we learn to relish life as challenge.

As far as this book is concerned, the important point to be made about Bayesianism is that the Bayesian model of the human mind is the one on which this book is founded. For each of the further points I argue in this book, I will try to show that they currently appear to have the best odds of working in the future, not that any one of them is irrefutably logical. To aim for logically irrefutable conclusions is to violate the spirit of Bayesianism—and to waste one’s time. In this life, any search for perfect confidence in any belief is either deluded or doomed to cycle after cycle of circularity, frustration, and failure.

Therefore, we must aim to adopt beliefs that, when they are used to construct arguments, make our conclusions look increasingly probable the more we check those conclusions against wider observations of physical evidence. Higher levels of probability are what we want, probabilities that appear to keep climbing the more of the real world we explore and successfully cognize.

Over two hundred years ago, David Hume spotted a major problem with the whole method of reasoning by induction. Deductive reasoning begins from some general rule that we trust totally. We then apply the rule to a problem in front of us. Inductive reasoning begins by looking at a whole lot of examples of a problem and trying to find a common pattern among them. Then we formulate a rule about how these kinds of situations turn out, a rule based on the pattern we think we have spotted. Then we test the rule in new situations, over and over, until we really sharpen and deepen our understanding of it. Inductive reasoning is the reasoning method that empiricism and science depend on.³

However, Hume said that if we draw generalizations from our masses of experience of the real world, no matter how careful we are in how we observe reality, formulate our generalizations, or conduct research to further test, refine, and bolster these generalizations, we still can’t say with certainty that any of them is true. To do so would be to posit that the events of the future will be like the events of the past. We can’t make that larger claim because we haven’t been to the future.

Bayesianism slips out of the problem of induction. It simply says we are always gambling, checking the generalizations that inform our gambling—even our most basic ones, the ones we need in order to see reality and form generalizations at all—against real-world data constantly. By choosing to live in this state of permanent tentativeness, we are gambling on alert, rational gambling as being our best gamble.

But we aren’t putting all our eggs in the single basket of any one model of any part of reality. Rationalists end in doing that, as they attempt to reason their way from sets of concepts they say they just know to premises they won’t question to policies they won’t analyze, no matter how ineffective or destructive the consequences of those policies may appear to be.

With Bayesianism, we also don’t get stuck like the empiricists, stopping in a stymied funk in our progress toward a kinder, wiser world, which is what happens if we keep staring at the problem of induction and refuse to get on with life until that problem is solved. It isn’t going to be solved. Bayesianism gives us a viable way out.

Thus, we can get on with it—the task of formulating a moral code based on our best current models of the real world. In the coming chapters, the Bayesian view of the human mind, combined with two of the most basic ideas in physics and a model of cultural evolution, will enable us to build a modern moral system. And then, finally, we may be able to make a case for theism, a belief in the existence of God.

Notes

1. Douglas R. Hofstadter, I Am a Strange Loop, (New York, NY: Basic Books, 2007).

2. Plato, The Phaedrus, Perseus Digital Library. Accessed April 17, 2015. http://www.perseus.tufts.edu/hopper/text?doc=plat.+phaedrus+265e.

3. John Vickers, “The Problem of Induction,” Stanford Encyclopedia of Philosophy, March 14, 2014. http://plato.stanford.edu/entries/induction-problem/.