The Mating Mind: How Sexual Choice Shaped the Evolution of Human Nature (59 page)

One might think that a group of individuals playing a science equilibrium would out-compete a group playing a Scheherazade equilibrium, because science brings survival benefits. Wouldn't group competition favor sexual displays concerning falsifiable hypotheses and empirical facts, rather than sexual displays concerning Aladdin and his genie? The science-displayers would develop useful theories about the world as a side-effect of their sexual status games. The Scheherazades would not. The science-displaying groups should have had competitive advantages.

Indeed they have, but only in the last five hundred years. For all of human evolution we muddled along playing half-fact, half-fantasy games with our language. We learned useful words, certainly, but then immediately invented as many useless synonyms as possible so we could display our vocabulary sizes. We learned useful facts about other individuals through gossip, and then immediately embellished and distorted those facts to make more entertaining stories. We revealed our life stories, but only the good bits, and only as if we were always the protagonist, and never the chorus.

Language evolved as much to display our fitness as to communicate useful information. To many language researchers and philosophers, this is a scandalous idea. They regard altruistic communication as the norm, from which our self-serving fantasies might sometimes deviate. But to biologists, fitness advertisement is the norm, and language is an exceptional form of it. We are the

only species in the evolutionary history of our planet to have discovered ft system of fitness indicators and sexual ornaments that also happens to transmit ideas from one head to another with telepathy's efficiency, Cyrano's panache, and Scheherazade's delight.

11

The Wit to Woo

To many people, "evolutionary psychology" implies "genetic determinism." This common error makes it hard to understand how there could be an evolutionary account of human creativity. Darwin proposed his theory of natural selection to account for the existence of complex order, such as the structure of the eye. Yet creativity implies the generation of novel, unpredictable, non-deterministic behavior—apparently the opposite of order. Whereas the eye's structure makes parallel light-rays converge to a point, creativity makes ideas diverge in all directions. Creativity seems too chaotic, both in its mental processes and its cultural products, to count as a biological adaptation in the traditional sense. So how could it have evolved?

This chapter reviews how evolution favors unpredictable behavior in many animals, and suggests that these capacities for randomness may have been amplified into human creativity through sexual and social selection. We shall see that behaviors are often randomized by evolutionary design, not by accident. Creativity is not just a side-effect of chaotic neural activity in large brains: it evolved for a reason, partly as an indicator of intelligence and youthfulness, and partly as a way of playing upon our attraction to novelty. By understanding how natural selection can favor unpredictable strategies in competitive situations, we may better understand how sexual selection could favor the benign unpredictability of creativity and humor in courtship.

striving to overcome "genetic determinism"—the direct coding of behaviors in genes. No scientist believes that genes preprogram every single behavior demonstrated by an organism during its lifetime. Evolution avoids such preprogramming by endowing animals with senses for registering what is going on in the environment, and reflexes for letting those senses influence movements. These senses and reflexes allow behavior to track environmental variables faster than genetic evolution can. One key variable is the location of food. A flatworm's eyes can notice that food is available in a certain location, without having to wait for the flatworm species to evolve the belief that food is there. If you believe in the existence of senses and nervous systems, you are not a genetic determinist in the strict sense.

Evolution did not stop with eyes and simple nervous systems. It took perfectly good simply nervous systems and expanded their first several segments into great bastions of antideterminism called brains, then added layer upon layer of thinking and feeling between sensory input and motor output. The job of evolutionary psychology is to analyze how evolution constructs these mental adaptations that turn environmental cues into fitness-promoting behaviors. The larger the brain, the more sophisticated the environmental cues it can use to guide behavior, and the more sophisticated that behavior. Into the grand, generation-long cycle of genetic evolution, brains insert millions of faster feedback loops. On a second-by-second basis, senses and brains track new opportunities to promote survival and reproduction. Their whole reason for existence is to keep genes from having to change every time the environment does.

Genes rarely determine specific behaviors, but they often determine the ways in which environmental cues activate behaviors. Many behaviors are fairly predictable if you know what an organism is perceiving at the moment. This predictability comes from the demands of optimality: for any given environmental situation, there is often one best thing to do. Animals that do the right thing survive and reproduce better; animals that deviate from optimal behavior tend to die. This pressure for

optimal behavior makes many behaviors predictable.

However, there are situations in which it is a very bad idea to be predictable. If another organism is trying to predict what you will do in order to catch you and eat you, you had better behave a bit more randomly. Selection may favor brain circuits that randomize responses, to produce adaptively unpredictable behavior. The benefits of randomization were first understood in a deep way by game theorists. What they said about randomization will help us understand human creativity later.

Matching Pennies

John von Neumann had an astonishingly creative mind, even compared with other Hungarian mathematicians. By the age of 30 in 1933, he had developed the modern definition of ordinal numbers, specified an axiomatic foundation of set theory, and written a standard textbook on quantum physics. When he worked on the Manhattan Project, he had a key insight about how to make the atomic bomb work, and he also originated a fundamental concept of computer science, the "Von Neumann architecture." But these were just warm-up exercises for his work on the theory of games, which became the foundation of both modern economics and modern evolutionary biology

Von Neumann realized that many games are best played by randomizing what you do at each step. Consider a game called "Matching Pennies." In this game, there are two players, and they each have a penny. At each turn, each player secretly picks heads or tails: they turn their pennies heads-up or tails-up under their hands. Then the coins are revealed. If the first player, in the role of "matcher," has turned up the same side as the opponent (e.g. if both coins are heads), then the matcher wins the opponent's penny. If the coins don't match (e.g. if one is heads, the other tails), then the matcher must give a penny to the opponent. The first play is not so interesting, but as the game is repeated, one can form predictions about the opponent's behavior. The possibility of prediction makes Matching Pennies a strategically intricate game.

The roles of "matcher" and "non-matcher" seem different, but their goals are fundamentally the same: predict what the

opponent will do, and then do whatever is appropriate (matching

or not matching) to win the turn. All that matters is to find out the
opponent's intentions. The ideal offensive strategy is to be the

perfect predictor: figure out what the opponent is doing based on

his or her past behavior, extrapolate that strategy to the next move,
make the prediction, and win the money. But there is an easy way

to defeat this prediction strategy: play unpredictably. Von

Neumann remarked, "In playing Matching Pennies against an at
least moderately intelligent opponent, the player will not attempt

to find out the opponent's intentions, but will concentrate on avoiding having his own intentions found out, by playing irregularly heads and tails in successive games."

In particular, if a player picks heads half the time and tails half

the time, then no opponent, no matter how good a predictor he or
she is, can do better than break even in this game. This half-heads,

half-tails strategy is an example of what game theorists call a "mixed strategy," because it mixes moves unpredictably. In their seminal 1944 book
The Theory of Games and Economic Behavior
, John

von Neumann and Oskar Morgenstern proved an important theorem. Roughly speaking, they showed that in every

competitive game between two players that has more than one

equilibrium, the best strategy is mixed. We have already seen in the chapters on morality and language that many important

games have more than one equilibrium. We know from evolution

how important competition is. The theorem implies that when any two animals are interacting and they have a conflict of

interest, they would often do well to randomize their behaviors at some level. When being predictable can make you lose a penny, unpredictability is recommended. When being predictable can make you lose your life to a predator, unpredictability is highly recommended.

The importance of randomness has long been appreciated in military strategy, competitive sports, and poker. In World War II, submarine captains sometimes threw dice to determine their patrol routes, generating a zigzagging course that would not be

predictable to enemy ships. Some modern fighter aircraft are equipped with "electronic jinking" systems that can automatically randomize their evasion maneuvers when guided missiles try to intercept them ("jinking" means zigzagging very abruptly and randomly). Professional tennis players are coached to "mix it up" when they serve and return shots. Plays in American football are carefully randomized to be unpredictable. Random drug tests make it harder for Olympic athletes to predict when they can abuse steroids. These are all "mixed strategies" that work by being unpredictable. Game theory showed the common rationale for randomness in many situations like these, where players have conflicts of interest and benefit from predicting each other's behavior.

Strategic Randomness in Biology

In 1930, Sir Ronald Fisher showed that animals play a game similar to Matching Pennies. They must evolve a strategy to determine whether to produce male or female offspring. If an animal could predict which sex will be in higher demand in the next generation, it could gain an advantage by producing the rarer, more sought-after sex. In an all-female population, a single male could do very well, spreading his genes through the entire gene pool in one generation. Likewise for a female in an all-male population. So, should animals try to out-predict their evolutionary opponents? Fisher said no. As in Matching Pennies, the best they can do is to randomize, by producing half males and half females. The sex ratio is balanced strategically, not because there is some biological law that says it has to be a 50/50 split. (As W. D. Hamilton showed, in some parasites with unusual mating systems, the optimal strategy is some other ratio, such as 3 males to 11 females, and such species duly evolve that biased sex ratio.)

At the level of behavior, biologists were slower to recognize the uses of randomness. In 1957 Michael Chance published a minor classic tided "The role of convulsions in behavior." Researchers had long been puzzled by the fact that laboratory rats sometimes go into strange convulsions when lab technicians

accidentally jangle their keys. Why should certain sounds induce seizures that look so maladaptive, resulting in rats injuring themselves against the cage walls? Chance found that the rats were responding to the key-jangles as if they indicated the approach of a dangerous predator. If provided with hiding places (little rat-huts) in their cages, they simply ran and hid when keys were jangled. Only if they had nowhere to hide did they go into convulsions. The convulsions may therefore have evolved as last-ditch defensive behaviors rather than pathologies. Wild convulsions, including "death throes," would make it harder for predators to catch and hold the convulser. The aptly named Dr. Chance argued that rats evolved defensive strategies that exploit randomness.

Shortly after Chance's work on rats, Kenneth Roeder found that bat sounds can induce similarly randomized behavior in moths. Bats eat moths, locating them at night by chirping and listening for ultrasonic echoes. If you're a moth, and you suddenly get hit by a blast of ultrasound, you can be pretty sure a gaping bat-mouth is close behind. Roeder found that moths in this situation produce an extraordinarily unpredictable range of evasive movements, including tumbling, looping, and power dives. Moth genes for predictable behavior usually got digested in bat stomachs rather than passed on to baby moths.

Protean Behavior

In 1970, British ethologists P. M. Driver and D. A. Humphries suggested that these rat and moth behaviors were examples of "protean behavior." They named this kind of adaptive unpredictable behavior after the mythical Greek river-god Proteus. Many enemies tried to capture Proteus, but he eluded capture by continually, unpredictably changing from one form into another— animal to plant to cloud to tree. Driver and Humphries's 1988 book
Protean Behaviour: The Biology of Unpredictability
presented a detailed theory of randomized behavior, supported by a wide range of field observations. Unfortunately they did not make the connection to mixed strategies in game theory, so these prophets