Chapter 12                       The Mechanism of Cultural Evolution

 

               

             Customs: Geisha Dancers (credit: Joi Ito, via Wikimedia Commons)

 

In order to begin to build a universal moral code, we must now create a model of cultural evolution, one that is reasonable and testable, as theories in Science are supposed to be. In order to set up our model, first, we’ll describe some data, i.e. describe how a number of different beliefs and morés have worked in the real lives of the tribes/nations of the West, and how they changed over time. 

Second, we’ll infer from our observations of the data, a theory/model of how moral codes work: how a moral code shapes behavior, how new parts are sometimes added to that code, and how, sometimes, old parts are dropped.

Finally, to complete this part of our overall case, we’ll test the theory against more data.

 

                     

  A recent custom: dabbing (credit: Gokudabbing, via Wikimedia Commons) 

 

The testing of our theory will have to be ex post facto. That is, we could never intentionally program a new code of behavior into a test population even of a few hundred people just to see how, over a dozen generations or so, that code would affect their survival rate. That would be morally forbidden under the code of ethics we now live by in the West. We can’t purposely, consciously usurp the freedom and dignity of other people for reasons of research or any other reasons. But we can examine the records we have of human tribes – their stated beliefs and values, the less well-explained, but vitally important acts people in those tribes performed in real life, and the social measures of what was going on in their culture. In short, via a study of History, we should be able to put together a model that tentatively explains why humans in groups do the things they do and what the material effects of their values are. 

Most of us are conditioned to be fiercely loyal to the way of life that we grew up with so we can expect that analyzing the roots of morality will be hard. Powerful programming steers us away from any such analyzing. Instead, we are steered toward affirming the values/morés we grew up with. On the other hand, we do have a lot of evidence in historical records of life as it has been lived by real people in many eras and lands from which to infer our tentative theory/model.

 To begin with, we can observe the everyday actions of the people around us. Why does this man rise when his clock radio beeps? Why does he even own a clock radio? Why do men in some cultures shave off their beards? Why have women in so many cultures been so oppressed? Why is honoring elders such a widespread custom?

 In similar ways, dozens of mundane questions may be posed about everyday life in our society or any society. While these actions and the motives behind them may seem obvious to people who live in the society where the customs are practiced, to people from other cultures, the reasons for foreigners’ ways aren’t so much confusing as inscrutable. All nations have at least some “ways” in their daily lives that visitors from other lands see as being not normal. Even bizarre.

 

 

          

          Dancers from West Africa (credit: Eric Draper, via Wikimedia Commons)

 

An interesting example of a custom that is commonplace in some societies but not in others is the one that trains men to shave their beards. In some cultures, clean-shaven men are seen as being presentable, neat, and attractive. Socially acceptable. In other cultures, a man without a beard is seen as being weak.  

The fascinating questions come when we ask “Why?” Why is shaving done? Is there a survival advantage in some environments for men who learned from their fathers to shave off their beards? For example, do men who shave daily appear more attractive to women? Do they reproduce more prolifically and thus pass their shaving behavior on to more progeny, i.e. sons who watch their fathers shave and then, when they grow up, do the same themselves?

Research on shaving is sparse and inconclusive. However, what’s important for now is to see that asking these kinds of questions about cultural morés and customs in terms of their possible advantages in the survival game entails thinking scientifically about morés. Under this view, no human customs are trivial. They all have significance in the larger design of a culture. Under this view, we also can compare cultures. Mundane customs become fascinating.

If we keep asking "Why?" about our "ways of life", the answers seem to spread further and further from one another into a variety of human morés and then whole cultures; human morés vary widely within any given society and then much more so from society to society. But if we persist in analyzing our observations, patterns begin to emerge. Based on these patterns, we can make some general statements about people and their ways, i.e. ways of life.

For the most part, people act in the ways that they do because they have been programmed to act in those ways – by parents, teachers, and the media (in very early times, storytellers) in their cultures. Humans don’t acquire most of their “ways” by genetic coding. We are not born to adopt shaving our beards or speaking English or spicing our food with curry because innate forces push us to do these things. The behaviors are learned from those around us as we develop in childhood. 

For example, close observation shows that the vast majority of humans early on in their development learn to urinate and defecate in ways considered socially acceptable in their particular culture. The urge to “go”, as we say in English, sometimes gets urgent to the point of being irrepressible. But where we “go” is very specifically defined by our cultural programming.

                 

                                        Balut (soft-boiled fetal duck, Vietnam)

                             (credit: Marshall Astor, via Wikimedia Commons)

 

In this category of mundane morés, we also find the morés that govern how we eat. I prefer to eat dishes I find familiar, ones I ate during my upbringing. And in my culture, I wash my hands before eating in order to remove disease-causing microbes that I might otherwise ingest with my food if I ate it with dirty hands. I have never seen these tiny animals, but I have been trained to be wary of them. Therefore, I take measures to neutralize the danger I believe they pose to my health. For similar reasons, if I possibly can, I try to urinate and defecate only in places deemed acceptable in my society, no matter how acute my natural urges may at times become.

It is useful to note here the profound way in which human behavior patterns differ from those of nearly all other animals. A turtle doesn’t need ever to see another turtle, from hatching to dying of old age, in order to be turtlish. A turtle that was the last of its species would be unable to perform its genetically driven reproductive behavior each mating season, but for a few days it would still try to find a mate. The rest of the time, it would live in ways normal for turtles, with all its behaviors being directed by its genetic code. 

Creatures like ants, crabs, and fish that came early in evolutionary history clearly are more fully programmed by their genetic codes than later ones like cats, dogs, apes, and humans. But even large mammals learn only some of their behaviors. Most of their behaviors are still acquired via their genetic programing. Kittens, in time, will stalk balls and then mice and birds, even if they are taken from their mothers still blind and helpless. Pups are genetically programmed to bury bones. As they mature, dogs mate, then have pups, even if they were taken from their mothers at one week old, blind and helpless, and raised entirely by human owners.

Humans, by contrast, if  they even survive, if raised without adults to model ourselves on, demonstrate few if any of our society’s “human” behaviors. We humans – unlike turtles, apes, and kittens – learn our society’s way of being human by “enculturation”, i.e. almost entirely from other, older humans.^{1. ,2.}

The knowledge base that you consult most of the time in order to respond to real-life situations is called your culture, and it is learned, not innate. Put a dead fish in the earth with each corn seed you plant; wear your tuxedo and black tie to the opera. These are customs, not innate ways.

 

                   A widespread custom: mom teaching daughter how to cook

                       (credit: Sgt. Sinthia Rosario, via Wikimedia Commons) 

 

But if humans act as they do mostly because of social programming, then we must ask why or how some behavior patterns ever became established at all in the earliest human societies, and why many behaviors possible for humans died out or never got tried. Why don’t most people on this planet eat holly berries or make their children into slaves? The answer is clear: such practices would reduce the chances of our children surviving to have and raise children of their own and so reduce the chances of our culture surviving. We keep concepts, values, and morés that help us, and even more, our culture, to survive. We drop ones that don’t. In this picture, my loyalty to my “way of life” is programmed into me because that programming is my culture’s way of protecting itself. 

We keep alive concepts, values, and morés that, in the past, have kept us alive.

Behavior patterns get established in a society and passed on generation to generation if they enable the people who use them to live – as individuals and as tribes – to survive, reproduce, and then program the behaviors into their young. If new morés or behavior patterns are to last, then they must achieve these results at levels of efficiency at least as high as those the community knew before its people began to try out the new behavior patterns. When an old moré no longer serves any of its carrier society’s needs, or when it in fact is getting in the way of serving survival needs, over generations, it dies out. This is the theory around which the model of sociocultural evolution is built.^3.

                                 Chapter 11     Summing Up the Case so Far

 

How do we know things? Or, worse yet, do we ever really know anything? What is an individual who is sincerely straining after truth to conclude at the end of a careful analysis of the problem of epistemology? The pattern is there; records of centuries of fruitless seeking for a model of knowing are there; the conclusion is clear: Rationalism and Empiricism are both hopeless projects.

 

Whatever else human minds may successfully cognize and manipulate – in abstract forms like arguments in Philosophy or in more tangible forms like computer programs – the mind will never rigorously define itself.

 

A human mind is much larger and more complex than any of the systems it can devise, including systems of ideas that it uses to try to explain itself. From within itself, it can make systems of symbols for labelling, organizing, and expressing its thoughts: the symbol systems cannot make or contain it.

 

                 

 

             IBM supercomputer Blue Gene/P (credit: Wikimedia Commons)

 

 

 

But the model of the mind called Bayesianism is workable enough to allow us to get on with building the further philosophical structures we need in order to devise a modern moral code. The Bayesian model of knowing contains some hard parts, but it doesn’t crash like Rationalism and Empiricism do.

 

Yes, it will be a gamble. No, there isn’t a way to avoid that. And we have to gamble. In every culture currently on earth, we can’t stay where we are. So let’s take the smartest gamble we can. 

 

Bayesianism doesn’t attempt to justify itself as being infallibly true, but it offers itself as a smart gamble, very likely to be true. And it will do what we need it to do.  It will serve as a base upon which we may construct a universal moral code. It just requires of us that we gamble on rational gambling as being our best, and likely our only, way of getting on with life.

 

And I stress again: we must have a moral code. We have to see, grasp, plan, and act in order to get on with life. A moral code tells us the answers to: “What matters here?” and “What should I do about it?”   

 

Alternative models of thinking and knowing usually are variations of either Empiricism or Rationalism. For example, Marxism was an original form of Rationalism. It built a theoretical model of how human society could be, then attempted to cram millions of real, often uncooperative, humans into the state plan it had devised. It didn’t work. The evidence is clear. Centrally planned economies wither. Marxism also makes citizens corrupt, lazy, and resentful.

 

Scientism is a form of Empiricism. It too let its adherents down. Too many scientists during WW2 found their life philosophy silent on what the Nazis, the Fascists, and the leaders of Imperial Japan were doing in the world. For them, Science did not take moral positions. A few even accepted the Nazis’ version of Evolution, and ultimately regretted this choice of life philosophy.

 

On the other hand, religious leaders all over the world still claim knowledge can be gained by other means, namely from holy texts or revelation. But as we saw in our early chapters, this model of thinking based on revelation, and/or scriptures, in the past has led people into some painful mistakes. Given its history, we’d be wise not to trust this way of thinking again.  

 

And, finally, a few ways of explaining human thinking are merely ways of completely dodging the issue of how human thinking works. In this early twenty-first century, the worldview called “postmodernism” is such a dodge. It basically tells its adherents that because our human views are so hopelessly biased by our cultural conditioning, we can’t ever trust any of our judgements about anything, not even facts millions of us have seen with our own eyes.

 

And let’s be even clearer. We get on with living every day in our lives now. Therefore, we must already be using some way of thinking and acting. Attending to sense data and responding to them effectively. A mind that can’t recognize, organize, prioritize, and respond to the sensory details being fed into it moment by moment is going to go catatonic. Anyone reading these words and making sense of them already has some program in place for simply handling daily life.

 

It is also true that many people do not want to look at how they do the thinking they actually do in order to handle their lives. But this book is for the person who does want to understand herself and the world around her. The person who has not resigned and given up.

 

The case argued in the book so far, then, makes these claims:

 

1. Our role in this world is in deep trouble. Overpopulation, global warming, and nuclear arms proliferation all threaten our survival. We must act to counter these threats.

 

2. All the moral codes and the morés that humans have used in the past have shown themselves to be inadequate for dealing with the world we have now.

 

3.  We must build a new moral code, a code of behavior that can work, ideally, for all of us. We must enable team action on a global scale. We can’t just let our situation drift and hope for the best. That is tantamount to relying on old moral codes that overwhelming evidence is telling us are rapidly going bankrupt.

 

4. In order to do the reasoning that we need to do to build this new code, we need to begin with a new way of understanding how it is that we think, form conclusions, and act on them. Bayesianism looks like the best candidate for a new epistemology on which to build the new moral code we need.

 

5. At this point in our project of building a new moral code, we can begin to study the data of our human history in order to then propose a theory/model of how our history works. Look for patterns. Form a theory. Test that theory against more data. The theory I will now propose is called cultural evolution.

 

Thus, from here on, I am going to trust my Bayesian way of thinking and use it to build a theory that describes how humans got to their present ways of life and how we could update them so that we may live with more health and joy and less pain and misery in the future.

 

Please notice again that this theory will not claim to be logically airtight. There is no such theory. But it is the best gamble, the most likely looking of the options we have before us.

 

Here we pause for a short rest. 

 

 

 

 

                                Labrador Retriever  (credit: Wikipedia) 

 

 

 

 

 

 

Oyama Morning

 

The restful sleep of boyish innocence

Awakens, stretches, smiles through dreamy eyes,

Looks over sunlit window ledge and spies

His Labrador, Black Queen, fixed, pointing, tense,

Below the dewy grass and picket fence,

Stock still, as now the air her black nose tries,

Then delicate with stealth, she steps ... Surprise!!

A pheasant cock splits dawn light rays' suspense

And arcing, flapping, squalling, climbs the skies,

Squawks window-by, a boyish reach away;

Flinch-startle back, now pause, now hear him bray;

Lean out and see the blue-red-golden glide

Fade into drifting dust of breaking day,

The flowing tail and wings’ defiant pride,

Through fresh, rose-saffron Canada, immense.

 

 

    

   Pheasant in flight  (credit: Archibald Thorburn, via Wikimedia Commons) 

 

So we’ve had a rest and looked back over how far we’ve come. Let’s take up our task again and press on toward the summit of our mountain, Moral Realism. The next step in the logic is to study the data of a segment of our own history, propose a model of human social change, and test it against more data. Then, we can use that model to reason our way to a universal moral code.   

 

 

                                     Chapter 10.                     (conclusion)  

The response in defense of Bayesianism is complex, but not that complex. What the critics seem not to grasp is the spirit of Bayesianism. In the Bayesian way of seeing reality and our relationship to it, everything in the human mind is morphing and floating. The Bayesian picture of the mind sees us as testing, reassessing, and updating all our ways of understanding reality all the time.

 

In the formula above, the term for my degree of confidence in the evidence, when I take only my background beliefs as true – i.e. Pr(E/B) – is never 100%. Not even for very familiar old evidence. Nor is the term for my degree of confidence in the evidence if I include the hypothesis in my set of mental assumptions – Pr(E/H&B) – ever equal to 100%. I am never perfectly certain of anything, not of my background assumptions and not even physical evidence I have seen repeatedly with my own eyes.

 

To closely consider this situation in which a hypothesis is used to try to explain old evidence, we need to examine the kinds of things that occur in the mind of a researcher in both the situation in which the new hypothesis does fit the old evidence and the one in which it doesn’t.

 

When a hypothesis explains some old evidence, what the researcher affirms is that, in the term Pr(E/H&B), the evidence fits the hypothesis, the hypothesis fits the evidence, and the background assumptions can be integrated with the hypothesis in a comprehensive way. The researcher is delighted to see that committing to this hypothesis, and the theory underlying it, will provide reassurance that the old evidence did happen in the way in which the researcher and her colleagues observed it. In short, they can feel reassured that they did the work well. The researcher did not make any mistakes. The researcher really did see what she thought she did. 

 

Fear of making an observation mistake haunts scientists. It's reassuring for them when they more confidently can tell themselves that they didn't mess up. All these logical and psychological factors raise the researcher’s confidence that this new hypothesis, and the theory behind it, must be right when he sees it explain problematic old evidence.

 

This insight into the workings of Bayesian confirmation theory becomes even clearer when we consider what the researcher does when she finds that a hypothesis does not successfully account for the old evidence. In research, only rarely does a researcher in this situation simply drop the new hypothesis. Instead, the researcher usually examines the hypothesis, the old evidence, and her background assumptions to see whether any of them may be adjusted, using new concepts involving newly proposed variables or closer observations of the old evidence, so that all the elements in the Bayesian equation may be brought into harmony again. The researcher gives the hypothesis thorough consideration. Every chance to prove itself.

 

When the old evidence is examined in light of the new hypothesis, if the hypothesis successfully explains that old evidence, the researcher’s confidence in the hypothesis and confidence in that old evidence both go up. Even if prior confidence in that old evidence was really high, the researcher can now feel more confident that she and her colleagues – even ones in the distant past – did observe that old evidence correctly and did record their observations well.

 

The value of this successful application of the new hypothesis to the old evidence may be small. Perhaps it raises the E in the term Pr(E/H&B) only a fraction of 1 percent. But that is still a positive increase in the value of the whole term, and therefore it supports the hypothesis/theory being considered.

 

Meanwhile, Pr(H/E&B), i.e. the scientist’s degree of confidence in the truth of the new hypothesis, also goes up another notch as a result of the increase in her confidence in the old evidence. A scientist, like all of us, finds reassurance in the feeling of mental harmony that comes when more of her perceptions, memories, and concepts about reality are brought into consonance with each other. (She feels relieved whenever her cognitive dissonance drops a bit.)

 

A human mind experiences cognitive dissonance when it keeps observing evidence that does not fit any of its models. A person attempting to explain old evidence that is inconsistent with his worldview sometimes clings to his background beliefs and shuts out the new theory his colleagues are discussing. He keeps insisting that this new evidence can’t be correct. Some systemic error must be leading other researchers to think they have observed E, but they must be mistaken. E is not what they say it is. “That can’t be right,” he says.

 

In the meantime, his subversive colleague down the hall, even if only in her own mind, is arguing “I know what I saw. I know how careful I’ve been. E is right. Thus, the probability of H, at least in my mind, has grown. It’s such a relief to see a way out of the cognitive dissonance I’ve been experiencing for the last few months. I get it now. Wow, this feels good!” Settling a score with a stubborn bit of old evidence that refused to fit into any of a scientist’s models of reality is a bit like finally whipping a bully who picked on her in elementary school – not really logical, but still very satisfying.

 

Normally, testing a new theory involves devising a hypothesis based on that theory and then doing an experiment that will test the hypothesis. If the experiment delivers the evidence that was predicted by the hypothesis, but not predicted by my background concepts, then the theory that the hypothesis is based on seems to me more likely to be true.

 

But I may also decide to try to use a hypothesis and the theory it is based on to explain some problematic old evidence. If I find that the theory does explain that problematic old evidence, what I’m confirming is not just the hypothesis and its base theory. I have also found a consistency between the old evidence, the new theory/hypothesis, and all or nearly all of my background concepts. (Sadly, at least some of the time, it is likely that I will have to drop a few of my old ways of thinking to make room for the new theory.)

 

This is why a new theory/hypothesis explaining some problematic old evidence so deeply affects how much we believe in the new theory. Our human feelings are engaged and reassured when the new theory relieves some of our cognitive dissonance. The exhilaration we feel mostly isn’t logical. But it is human.

 

And no, it is not obvious that evidence seen with my own eyes is ever 100% reliable, not even if I’ve seen a particular phenomenon repeated many times. Neither my familiar background concepts nor the sense data I see in everyday experiences are trusted that much. If they were, then I and anyone who trusts gravity, light, and human anatomy would be unable to watch a good magic show without having a nervous breakdown. Elephants disappear, men float, and women get sawn in half. If my most basic concepts were believed at the 100% level, then either I’d have to gouge my eyes out or go mad. 

 

But I know the magic is a trick of some kind. And I choose, for the duration of the show, to suspend my desire to harmonize all my sense data with my set of background concepts. It is supposed to be a performance of fun and wonder. If I figure out and explain how the trick is done, I ruin my grandkids’ fun …and my own.

 

It’s important to point out here that the idea behind H&B, the set of the new hypothesis/theory plus my background concepts, is also more complex than the equation can capture. This part of the formula should be read: “If I integrate the hypothesis into my whole background concept set.” The formula attempts to capture in symbols something that is almost not capturable. This is because the point of positing a hypothesis, H, is that it doesn’t fit neatly into my background set of beliefs. It is built around a new way of comprehending reality and thus, it will only be fully integrated into my old background set of concepts and beliefs if some of those old concepts are adjusted by careful, gradual tinkering, and some are removed entirely.

 

Similarly, in the term Pr(H/E&B), E&B is trying to capture something no math term can capture. E&B is trying to say: “If I take both the evidence and my set of background beliefs to be 100% reliable.” 

 

But that way of stating the E&B part of the term merely highlights the issue of problematic old evidence. This evidence is problematic because I can’t make it consistent with all of my background concepts and beliefs, no matter how I tinker with them.

 

All the whole formula really does is try to capture the gist of human thinking and learning. It is a useful metaphor; but we can’t become complacent about this formula for the Bayesian model of human thinking and learning any more than we can become complacent about any of our concepts. And that thought is consistent with the spirit of Bayesianism. It tells us not to become too blindly attached to any of our concepts, not even how we think about how we think. Any of them may have to be updated and revised at any time.

 

For all these reasons, the criticism of Bayesianism which says it can’t explain why we find a fit between a hypothesis and some problematic old evidence reassuring turns out not to be a fatal criticism at all. It is more a useful mental tool, one that we may use to deepen our understanding of the Bayesian model. 

 

The Bayesian model tells us to accept that all the patterns of neuron firings in the brain – i. e. all the hypotheses, bits of evidence, and background concepts – are forming, reforming, aligning, realigning, and floating in and out of one another all the time – even concepts as basic as the ones we have about gravity, matter, space, and time. This whole view of “Bayesianism” arises if we simply apply Bayesianism to itself.

 

In short, Bayesianism says we keep adjusting our thinking until we die. 

 

The Bayesian way of thinking about our own thinking requires us to be willing to float all our concepts, even our most deeply held ones. Some are more central, and we use them more often with more confidence. A few we may believe almost absolutely. But none of our concepts is irreplaceable.

 

For humans, the mind is our means of surviving. Thus, it will adapt to almost anything. Let war, famine, plague, economics, and technology do what they will. Rattle our living styles and ways until they tumble. We adjust. We go on.

 

We gamble heavily on the concepts we routinely use to organize our sense data and memories of sense data. I use my concepts to organize the memories already stored in my brain, and the new sense data that are flooding into my brain, all the time. I keep trying to learn more concepts – including concepts for organizing other concepts – that will enable me to utilize my memories more efficiently to make faster, better decisions and to act more and more effectively. In this constant, restless, searching mental life of mine, I never trust anything absolutely.

 

But I choose to stand by my most basic concepts even at a magic show, not because I am certain they’re right, but because they’ve been tested and found effective over so many trials for so long that I’m willing to keep gambling on them. At least until someone proposes something even more promising to me. I don’t know for certain that the theories of the real world that my culture has programmed into me are sure bets; they just seem very likely to be the most promising options available to me now. And I need some theories about space, matter, etc. every day. I have to see and act. I can’t live by sitting catatonic.

 

 

                                 

    

                             

                              Harry Houdini with his “disappearing” elephant, Jennie 

                                             (credit: Wikimedia Commons)

 

Life is constantly making demands on me to move and keep moving. I have to gamble on some models of reality just to live my life; I go with my best horses, my most successful and trusted concepts. And sometimes I change my mind.

 

This flexibility on my part is not weakness or lack of discipline; it is just life. Bayesianism tells us Kuhn’s thesis in The Structure of Scientific Revolutions. Sometimes as individuals, and sometimes as whole tribes, we are constantly adjusting all our concepts as we try to make our ways of dealing with reality more effective.

 

And when a researcher begins to grasp a new hypothesis and the theory it is based on, the resulting experience is like a religious “awakening” – profound, even life-altering. Everything changes when we accept a new model or theory because we change. How we perceive and think changes. In order to “get it”, we have to change. We have to eliminate some old beliefs from our familiar background belief set and literally see in a new way.

 

And what of the shifting nature of our view of reality and the gambling spirit that is implicit in the Bayesian model? The general tone of all our experiences tells us this overall view of our world and ourselves – though it may seem scary, or maybe, for confident individuals, exhilarating – is just life.

 

We have now arrived at a point where we can feel confident that Bayesianism gives us a good base on which to build further reasoning. 100% reliable? No. But solid enough to use and so to get on with all the other thinking that must be done. It can answer its critics – both those who attack it with real-world counterexamples and those who attack it with pure logic. And it outperforms both Rationalism and Empiricism every time.

 

Bayesianism is not logically unshakable. But in a sensible view of our world and ourselves, Bayesianism serves well. First, because it makes sense when it is applied to our real problem-solving behavior; second, because it works even when it is applied to itself; third, because we must have a foundational belief of some kind in place in order to get on with building a universal moral code; and fourth, because – as was shown earlier – we have to build that new code. That task is crucial. Without a new moral code, we aren’t going to survive.

 

We are now at a good place to pause to summarize our case so far. The next chapter is devoted to that summing up.

 

 

 

Notes

 

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