EVOLVED BRAINS - UNCONSCIOUS INTELLIGENCE - Gut Feelings: The Intelligence of the Unconscious - Gerd Gigerenzer

Gut Feelings: The Intelligence of the Unconscious - Gerd Gigerenzer (2007)

Part 1. UNCONSCIOUS INTELLIGENCE

If we stopped doing everything for which we do not know the reason, or for which we cannot provide a justification…we would probably soon be dead.

—Friedrich A. Hayek1

4. EVOLVED BRAINS

We tend to smile when hearing that former first lady Barbara Bush is reported to have said, “I married the first man I ever kissed. When I tell this to my children, they just about throw up.” Should she have looked at more suitors? Barbara Bush is not the only one; a third of Americans born even as recently as the 1960s and early 1970s married their first partner.2 Marriage consultants often disapprove of people who marry the first or second partner they are engaged with, rather than looking systematically for more alternatives and experience in making such an important decision. Likewise, economists complain about the limited rationality in partner choice. When I hear similar criticisms, I ask the narrator how he found a partner. “Oh, that was different!” he tells me, and relates a story of an accidental meeting at a party or in a cafeteria, a first sensation of excitement, the anxiety of being rejected, how life focused on only that person, and a gut feeling that he or she was the right one. These stories have little in common with the deliberate process of choosing among a set of alternatives, as we tend to do when choosing digital cameras or refrigerators.

To date I have met only one man, an economist, who responded that he followed the Benjamin Franklin method to choose a partner. He sat down with a pencil and listed all the possible partners he could think of and all possible consequences he could imagine (such as whether she would still listen to him after being married, take care of the children, and let him work in peace). Next he put a number on the utilities of each consequence and then estimated the probabilities that each might come true. Finally, he multiplied the utilities with the probabilities and added them up. The woman he proposed to and married was the one with the highest expected utility, though he didn’t tell her about his strategy. By the way, he is now divorced.

My point is that important decisions—whom to marry, which job to accept, what to do with the rest of your life—are not only a matter of our imagined pros and cons. Something else weighs in the decision process, something literally quite heavy: our evolved brain. It supplies us with capacities that have developed over millennia but are largely ignored by standard texts on decision making. It also supplies us with human culture, which evolves much faster than genes. These evolved capacities are indispensable for many important decisions and can prevent us from making crude errors in important affairs. They include the ability to trust, to imitate, and to experience emotions such as love. That is not to say that without trust and love, living beings would not function. In many reptiles, there is no mother love; newborn youngsters need to hide to prevent being eaten by their parents. That works too, but it’s not how we humans behave. In order to understand human behavior, we need to understand that there is an evolved human brain that allows us to solve problems in our own way—different from that of reptiles or computer chips. Our infants don’t need to hide after they are born but can draw on other abilities to grow up—smiling, imitating, looking cute, and having the capacity to listen and to learn to speak. Consider a thought experiment.

The Fable of Robot Love

In the year 2525, engineers finally managed to build robots that looked like humans, acted like humans, and were ready to reproduce. Ten thousand robots of various types had been built, all of them female. A research team set out to design a male robot who would be able to find a good mate, found a family, and take care of the little robots until they were able to take care of themselves. They called their first model Maximizer, M-1 for short. Programmed to find the best mate, M-1 proceeded to identify a thousand female robots that fit his goal of not marrying a model older than himself. He detected five hundred features on which individual female robots varied, such as energy consumption, computing speed, and frame elasticity. Regrettably, the females did not have their individual feature values printed on their foreheads; some even hid them, trying to fool M-1. He had to infer these values from samples of behavior. After three months passed, he had succeeded in getting reliable measures on the first feature he tested, memory size, from each female robot. The research team made a quick calculation of when M-1 would be ready to pick the best and discovered that no one in the team would still be alive at that point—nor would the best female robot. The thousand females were upset that M-1 could not make up his mind, and, as he began recording the second feature, the serial number, they pulled out his batteries and dumped him in a scrap yard. The team went back to the drawing board. M-2 was designed to focus on the most important features and to stop looking for more when the costs of collecting further information exceeded its benefits. After three months, M-2 was exactly where M-1 was, and in addition was busy measuring the benefits and costs of each feature so that he could know what to ignore. The impatient females ripped out his wires and got rid of him, too.

The team now adopted the proverb that the best is the enemy of the good and designed G-1, a robot who looked for a mate that was good enough. G-1 had an aspiration level built in. When he encountered the first female who met his aspiration level, he would propose to her—and ignore the rest. To make sure that he found a mate if his aspirations were too high, he was equipped with a feedback loop that lowered the aspiration level if none of the females were good enough for him over too long a period. G-1 showed no interest in the first six females he met, but then proposed to number seven. Short of alternatives, she accepted. Three months later, to everyone’s pleasure, G-1 was married and had two small kids. While writing the final report, however, the team learned that G-1 had left his wife for another robot. Nothing in his brain had prevented him from running off to what looked to him like a better deal. One team member pointed out that M-1 would never have left his wife, because he would only have accepted the best in the first place. That’s true, responded the others, but G-1 at least found one. The team discussed the problem for a while and then came up with GE-1. He was happy with a good-enough female, just like G-1, but was additionally equipped with an emotional glue that was released when he met a good-enough robot and adhered more strongly with each physical contact. Just to be sure, they inserted a second form of emotional glue into his brain that discharged when a baby was born and tightened after each physical contact with the baby. GE-1 proposed to a female as quickly as G-1 did, married, and fathered three babies. He was still with them when the team finished their report. He was somewhat clingy, but dependable. Ever since, GE-1 robots have conquered the earth.

In the fable, M-1 failed because he tried to find the best, as did M-2, both of them running out of time. G-1 was fast by going for a good-enough choice, but was also fast in dropping it. However, the capacity for love, the glue, provided a powerful stopping rule that ended GE-1’s search for a partner and strengthened his commitment to his loved ones. Similarly, feelings of parental love, triggered by an infant’s presence or smile, free parents from having to decide every morning whether they should invest their resources in their children or in some other business. The question of whether it is worthwhile to endure all the sleepless nights and other frustrations associated with baby care simply does not arise, and our memory ensures that we forget these tribulations soon. The evolved brain keeps us from looking too long and thinking too much. The culture it is embedded in influences what the object of love or trust can be, or what makes us upset and feel hurt.

Consider how a deliberate search for the best can conflict with pride and honor in real humans. The astronomer Johannes Kepler was short, unhealthy, and the son of a poor mercenary. Yet, famous for his astounding discoveries, he was considered a good catch. In 1611, after an arranged and unhappy first marriage, Kepler began a methodical search for a second wife. Unlike Barbara Bush, he investigated eleven possible replacements within two years. Friends urged him to marry candidate number four, a lady of high status and a tempting dowry, but he persisted with his investigation. Insulted, this suitable match rejected him for toying with her.

EVOLVED CAPACITIES

Evolved capacities, including language, recognition memory, object tracking, imitation, and emotions such as love, are acquired through natural selection, cultural transmission, or other mechanisms. The capacity for language, for instance, has evolved through natural selection, but knowing what words refer to what objects is a matter of cultural learning. I use the term evolved capacities in a broad sense, since capacities of the brain are always functions of both our genes and our learning environment. Historically, they evolved in tandem with the environment in which our ancestors lived and are shaped by the environment in which a child grows up. The human ability to imitate the behavior of others, for instance, is a precondition for the evolution of culture. One of Darwin’s rare blunders was his belief that the ability to imitate was a common adaptation in animal species.3 In no other species do individuals imitate as generally, carefully, and spontaneously as we do, allowing for the cumulative growth of a body of skills and knowledge that we call culture.

The psychologist Michael Tomasello and his coworkers conducted experiments wherein juvenile and adult chimpanzees and two-year-old children watched adult human demonstrators use a rakelike tool to obtain food that was out of arms’ reach.4 Chimps learned that the tool could somehow be used, but they didn’t pay attention to the details of how it was used, whereas children paid close attention to the details and imitated them faithfully. A child may be weaker and slower than a chimp but learns culture faster using, in this case, imitation.

Yet if we all relied on imitation alone, our behavior would be decoupled from the environment. Flexible rules of thumb allow us to use imitation in an environmentally sensitive way. Imitate if the world is only slowly changing, otherwise learn from your own experience (or imitate those who are smarter than you and have adapted more quickly to a new situation).

Because many of our evolved capacities are not well understood, we can’t endow machines with the same abilities. For instance, artificial face and voice recognition does not yet match that of humans, and emotional capacities, such as love, hope, and desire, are far from being part of machine intelligence. Of course, the opposite is also true. One can speak of the “evolved” capacities of modern computers, such as their immense combinatorial power unmatched by the human mind. The differences in the hardware of computer and that of mind have an important consequence. Humans and machines rely on different types of rules of thumb in order to take advantage of their respective capacities. Therefore, their intuitions are likely disparate.

Capacities build on each other. The ability to track objects is based on the physical and mental mechanisms involved in exploring one’s environment. The ability to gather information by observing others is in turn based on the ability to track individuals across time and space. The capacities for cooperation and imitation are in turn based on the ability to observe others. If individuals have the ability to cooperate, in order to exchange goods for example, they’ll also need to develop a radar for cheating in order to avoid being exploited.5 Similarly, recognition memory is a precondition for reputation; for institutions to achieve good reputation, people must recognize their names and at least faintly recall why they deserve respect. An institution with a good reputation in turn increases trust, enhances group identification, and promotes the spread of the values it embodies.

THE ADAPTIVE TOOLBOX

Enlightenment philosophers compared the mind to a kingdom ruled by reason. At the turn of the twentieth century, William James compared consciousness to a river and the self to a fortress; and, in response to the latest technologies, the mind has been alternately portrayed as a telephone switchboard, a digital computer, and a neural network. The analogy I use is that of a toolbox that contains instruments adapted to the spectrum of problems confronting humankind (Figure 4-1). The adaptive toolbox has three layers: evolved capacities, building blocks that make use of capacities, and rules of thumb composed of building blocks. The relationship between these three layers can be compared to that between the atomic particles, the chemical elements in the periodic table, and the molecules built from combinations of the elements. There are many molecules and rules of thumb, fewer elements and building blocks, and even fewer particles and capacities.

image

Figure 4-1: Like a maintenance worker with a box of tools, intuition draws on an adaptive toolbox of rules of thumb.

Consider the gaze heuristic again. It has three building blocks:


(1) Fix your gaze on the ball, (2) start running, and (3) adjust your running speed so that the angle of gaze remains constant.


Each of these building blocks is anchored in evolved capacities. The first makes use of the human capacity to track objects, the second the capacity to maintain balance while running, and the third the capacity for fine-tuned vision-motor adjustments. These allow an original solution to the problem of catching a ball that is entirely different from estimating its trajectory. The gaze heuristic is fast and frugal because the complex capacities it relies on are hardwired. Note that the standard mathematical solution—computing the trajectory—does not take advantage of this potential.

Next consider the tit-for-tat strategy introduced in the previous chapter. It applies to situations in which two people or institutions exchange products, favors, emotional support, or other goods. Each of the two partners can be either nice (cooperate) or nasty (not cooperate). Tit for tat can also be divided into three building blocks:


(1) Cooperate first, (2) keep a memory of size one, and (3) imitate your partner’s last behavior.


Assume both partners meet repeatedly over time. Thus, in the first encounter, a person who uses tit for tat would be nice to the other, then remember how the other acted, and in the second encounter would imitate the partner’s behavior in the first move, and so on. If the partner also uses tit for tat, both will cooperate from the beginning to the end; if the other is nasty and never cooperates, however, the tit-for-tat player will also finish by not cooperating with him. Note that although the resulting behavior is different, nice or nasty, the rule of thumb remains the same. An explanation of the tit-for-tat player’s behavior in terms of traits or attitudes would miss this crucial difference between process (tit for tat) and resulting behavior (cooperate or not).

The first building block involves cooperation, the second involves the ability to forget, which, just like forgiving, is helpful for maintaining stable social relationships. My flash drive, by contrast, cannot forget, and from time to time I have to delete a number of files so that it remains useful. The third building block makes use of the ability to imitate, at which humans excel. Reciprocation between unrelated members of the same species is known as reciprocal altruism: I help you now, and you return the favor later. It is exceptionally rare in the animal world, as is tit for tat.6 Animals may reciprocate if they are genetically related. By contrast, large human societies, which emerged only some ten thousand years ago, consist of mostly unrelated members who practice both nepotism and reciprocal altruism, as in agriculture and trade.

The adaptive toolbox consists of evolved capacities, including capacities to learn, that form the basis for building blocks that can construct efficient rules of thumb. Evolved capacities are the metal from which the tools are made. A gut feeling is like a drill, a simple instrument whose force lies in the quality of its material.

ADAPTIVE GOALS

An evolved capacity can be drawn upon to solve a wide spectrum of adaptive problems. Consider tracking. The original adaptive goals were probably predation and navigation: for example, intercepting prey by keeping the angle of gaze constant. As we have seen in chapter 1, tracking enables simple solutions to such complex modern problems as catching a baseball or avoiding a collision in sailing and flying. It provides ingenious solutions to social problems as well. In human societies as well as in hierarchically organized primate ones, a newcomer can quickly figure out the social status of individual group members by tracking who is looking at whom. Careful tracking allows a new group member to know whom to respect, avoiding conflicts that would upset the existing hierarchy. Children are sensitive to eye gaze from birth and seem to know when someone is looking at them. When infants are about one year old, they begin to use adults’ gaze to learn language. When Mommy says computer while the child is looking at the goldfish tank, the child does not conclude that the new word refers to the tank or the fish but follows Mommy’s gaze to infer which of the many objects in the room she means. At about the age of two, children begin to read others’ gazes to figure out their mental states, such as their desires, and three-year-olds begin to use gaze as a cue to uncover deception.7 Both children and adults trace not only the direction of a gaze, but also that of others’ bodily movements to infer their intentions. Even the movements of virtual bugs on a computer screen can suggest to us that they might have intentions to flirt or help or hurt.8

An evolved capacity is necessary for solving adaptive problems, but it is not sufficient on its own—just as a 200-horsepower motor is designed for moving fast, but cannot do so without a steering wheel and tires. Only with those parts in place is it possible for a driver to move the car by a simple sequence of acts, such as turning on the engine, pushing the gas pedal, and switching gears accordingly. Similarly, the ability to track other people’s eye gaze is not sufficient for inferring their intentions, as the case of autism illustrates. It is the rule of thumb that goes beyond the information given and forms our intuitions.

HUMAN AND MACHINE INTUITIONS

In 1945, the British mathematician Alan Turing (1912-54) predicted that computers would one day play excellent chess. Others have since hoped that chess programming would contribute to the understanding of how humans think. Though Turing was correct—in 1997, the IBM chess program Deep Blue beat the world champion Garry Kasparov—advances in programming have not led to a deeper understanding of human thought. Why is this? Human chess-playing strategies exploit the unique capacities of the human organism. Both Kasparov and Deep Blue had to rely on rules of thumb—even the fastest computer cannot determine the optimal strategy for chess, that is, the strategy that always wins, or at least never loses. Deep Blue can foresee as many as fourteen turns of play but has to use a quick rule of thumb in order to evaluate the quality of billions of possible positions generated. Kasparov, by contrast, is reported to have said that he thinks only four to five moves ahead. Deep Blue’s capacities include its brute-force combinatorial power, whereas those of a grand master include spatial pattern recognition. Because these capacities are fundamentally different, understanding computer “thought processes” does not necessarily help to understand human ones.

In the initial wake of the computer revolution, the idea of disembodied cognition became very popular. Turing himself emphasized that differences in hardware were ultimately of little importance.9 The new rhetoric was of cognitive systems that described the thought processes of “everything from man to mouse to microchip.”10 This led to great hopes for computer programs that would reproduce human creativity. A number of years ago, there was great enthusiasm about computer programs for composing music and improvising jazz, and anticipation that we could soon have a program that matched a Bach, if not a Beethoven. But nobody seriously talks anymore about simulating the great composers of the past. Unlike computer-generated music, human composition is embodied. It is based on an oral tradition of singing—wherein breath structures the phrasing and the length of tunes—and on the morphology of our hands, which structures the range and the flow of harmonies. And it is based on an emotional brain. Without the turbulent emotions Mozart faced as he wrote his Ave Verum Corpus on the eve of an early death, it is difficult to mimic his composition. Composition, like cognition, is based on capacities that vary from man to mouse to microchip.

HUMAN AND CHIMPANZEE INTUITIONS

Chimpanzee Intuitions

Humans are motivated, at least in part, by empathy and concern for the welfare of others. We donate blood for strangers, contribute to charity, and punish violators of social norms. Chimpanzees are, together with bonobos, our closest relatives, and they similarly engage in cooperative hunting, comfort victims of aggression, and perform other collective activities. Would they show concern for the welfare of unrelated, familiar chimps if the benefits were at no cost to themselves?

Primatologist Joan Silk and her collaborators conducted an experiment with chimps that had lived together for fifteen years or more.11 Eighteen chimps were studied, from two different populations with different life histories and exposures to experiments. Pairs of chimps faced each other in opposing enclosures or sat side by side, and could see and hear each other. One chimp, the actor, was given the choice to pull one of two handles: if the actor pulled the “nice” handle, both the actor and the other chimp got food, and exactly the same portion. If the actor pulled the “nasty” handle, only the actor received food, and the other chimp got nothing. In a control test, only the actor was present. Which handle did the chimps pull?

When no other chimp was present, the actors chose both options about equally frequently. The chimps didn’t care, and why should they? Yet even when a second chimp arrived, the chimps didn’t choose the “nice” option more often. Although they could clearly see the other one displaying desperate begging gestures, or happily eating the food when it was dispensed, the chimps showed no sign of empathy. It should be noted that they showed no spitefulness either. What mattered to the actors more than the other chimp was whether the handle for the nice option was placed on their right or left side. They had a much stronger preference for the right side than for the happiness of their partner. Chimps simply did not seem to care about the welfare of unrelated group members.

Human Intuitions

What would children do in this situation? In a very similar study, three-to five-year-old children were asked whether they would prefer to have one sticker for themselves and one for a young female experimenter, or just a sticker for themselves.12 Most children went with the prosocial alternative, and some were even willing to give up their own stickers to the experimenter.

In contrast to other primates, we humans not only give and share outside our families or when sharing proves costly, but we can get angry if someone does not. Consider the ultimatum game, which was invented by the economist Werner Güth, one of my colleagues at the Max Planck Society. In the game’s classic version, two people who have never met before and never will are seated in different rooms. They cannot see or hear each other. A coin is flipped that assigns to them the role of the Proposer or the Responder. Both are told the rules of the game:

The Proposer receives $10 (in ten single bills) and offers any part of this to the Responder, that is, any amount from $0 to $10. The Responder then decides whether to accept the amount. If the Responder accepts, both players keep what they have; if the Responder rejects, both players receive nothing.

If you were the Proposer, how much would you offer? According to the logic of self-interest, both players will aim at maximizing their gain. Since the Proposer moves first, he should offer the Responder a single dollar bill and not more, because that maximizes the Proposer’s gain. The Responder should subsequently accept the offer, because one dollar is obviously more than none. This logical norm is called a Nash equilibrium, after the Nobel laureate John Nash. But neither Proposer nor Responder tends to respond this way. The most frequent offer is not $1, but $5 or $4. Thus, people seem to be concerned with equity, sharing roughly the same amount—here we meet the 1/N rule in a different context. Even more surprising to the logic of self-interest, about half of those who were offered only one or two dollars rejected the money and preferred to take home nothing. They were annoyed and angry for being treated unfairly.

One might object that a few dollars are just peanuts, and that people would turn selfish as soon as there was more at stake. Imagine, for instance, a Proposer with $1,000 at his disposal. Yet when the game was played in other cultures with amounts that corresponded to the earnings of a week or even a month, little changed.13 If the Proposer was a computer, humans were less likely to reject a small offer. Yet could the Proposer’s concern for the other’s welfare simply be calculated selfishness, that is, not wanting to take the risk of being rejected? Would people still give away money if the Responder could not reject? This version of the ultimatum game is called the dictator game, in which the Proposer simply dictates whether or not to give money and how much. Yet even when the other party has no possibility to reject, a substantial number of people give away some of their money. University students in the United States, Europe, and Japan playing the dictator game typically keep 80 percent and give 20 percent, whereas adults in the general population give more, sometimes an even split. German children’s most frequent offer was an equal split in both games.14 Nor could pure selfishness be found in a cross-cultural study with fifteen small-scale societies in the tropical forests of South America, the savanna-woodlands of Africa, the high-latitude deserts in Mongolia, and other remote places.15 These experimental results illustrate that even in an extreme situation where the other person is unfamiliar, the situation anonymous, and there is a cost to themselves, people tend to be concerned with others’ welfare. This general capacity for altruism divides us from other primates, even chimpanzees.

MALE AND FEMALE INTUITIONS

There is much talk about female intuition but comparatively little about that of males. One might suspect that this is because women have better intuitions than men, yet history suggests a different reason. Since the Enlightenment, intuition has been seen as inferior to reason, and long before that, women as inferior to men. Polarizing males and females in terms of both intelligence and character goes back to Aristotle, who wrote,

The female is softer in disposition, is more mischievous, less simple, more impulsive, and more attentive to the nurture of the young; the male, on the other hand, is more spirited, more savage, more simple and less cunning…. The fact is, the nature of man is the most rounded off and complete, and consequently in man the qualities above referred to are found most clearly. Hence woman is more compassionate than man, more easily moved to tears, at the same time is more jealous, more querulous, more apt to scold and to strike. She is, furthermore, more prone to despondency and less hopeful than the man, more void of shame, more false of speech, more deceptive, and of more retentive memory.16

This passage echoed through millennia of European debate about the difference between the genders and structured early modern views about moral values in Christianity. Violating the passive virtues, particularly chastity, was a cardinal sin for women but not for men, whereas timidity was easily excused in women but not in men. Memory, imagination, and sociability were traits clustered around the female pole, to be contrasted with male discursive and speculative reason. For Kant, this contrast condensed into the male mastery of abstract principles, as opposed to the female grasp of concrete detail, which in his view was incompatible with abstract speculations or knowledge: “Her philosophy is not to reason, but to sense.”17 He thought that the few flesh-and-blood counterexamples—learned ladies—were worse than useless, and freakish to boot: women with beards. A century later, Darwin similarly opposed male energy and genius to female compassion and powers of intuition. His identification of female faculties with “the lower races” was a characteristic nineteenth-century addition.

Modern psychology absorbed this opposition between male logic and female feeling into its initial concepts. Stanley Hall, the founder and first president of the American Psychological Association, described women as different from men in every organ and tissue:

She works by intuition and feeling; fear, anger, pity, love, and most of the emotions have a wider range and greater intensity. If she abandons her natural naiveté and takes up the burden of guiding and accounting for her life by consciousness, she is likely to lose more than she gains, according to the old saw that she who deliberates is lost.18

This short history reveals that the association between intuition and women has been, for much of the time, one between what were viewed as a lesser virtue and a lesser sex. Unlike the contrast between humans, chimpanzees, and machines, there is little firm evidence that men and women differ in any striking way in their cognitive capacities, except for characteristics associated with reproductive functioning and the cultures into which they are born. Given two millennia of beliefs in polar oppositions, however, it is not surprising that people believe that the differences between male and female intuition are larger than they really are. Psychologists tested the intuitive powers of more than fifteen thousand men and women in distinguishing a real smile from a false one.19 They were shown ten pairs of photographs of smiling faces, one a genuine smile, the other a fake. Before studying the faces, the participants were asked to rate their intuitive abilities. Seventy-seven percent of the women said they were highly intuitive, compared to only 58 percent of the men. Yet women’s intuitive judgments were not better than men’s; they identified the real smile correctly in 71 percent of cases, whereas men did so in 72 percent. Interestingly, men could better judge women’s genuine smiles than those of other men, whereas women were less adept at judging the sincerity of the opposite sex. Thus, if there are differences between male and female intuition, they are much more specific than the old idea that women are more intuitive than men.

For instance, according to the selectivity hypothesis, men tend to base their intuitive judgments on only one reason, good or bad, whereas women are sensitive to multiple reasons.20 This difference has been attributed to societies in which girls are encouraged to consider others’ views, whereas boys are motivated to take a more selfish, single-minded approach to mastering their world. Advertisers seem to assume this difference when they design ads for men and women. Researchers on consumer studies concluded that when targeting men, advertisers should associate the product with a single compelling message and feature it at the beginning of the ad. In contrast, when targeting women, they concluded that the ads should make use of ample cues that evoke positive associations and images. An automobile advertisement shows a Saab intently pursuing a straight path at a junction where large white arrows painted on the road point right and left. The headline reads: “Does popular acceptance require abandoning the very principles that got you where you are?” According to the ad, while other car manufacturers may compromise their design to win popular acceptance, Saab NEVER will! Never compromise is the single reason presented to buy a Saab. On the other hand, an ad by Clairol that introduced a new line of seven shampoos provided rich visual images meant to appeal to the female’s powers of associative processing and subtle discriminations. Within a single ad, one shampoo was placed on a Hawaiian beach replete with luscious coconuts, another in a landscape of Egyptian pyramids near a desert oasis, and so on, for each of the seven products.

In 1910, seven years after she received the Nobel Prize in physics and a year before she became the first person ever to win a second Nobel Prize, this time in chemistry, Marie Curie was recommended for election to the prestigious French Academy of Sciences. In a tumultuous atmosphere, the members of the Academy voted and rejected her by a narrow margin. Despite her exceptional brilliance, prejudice against women prevailed; women, seen as inferior to men since the ancient world, were not meant to triumph in science. Today, though the polarity “male = reason, female = intuition” has been largely dissolved in our culture, and men are allowed to have intuitions, too, we still hear that women have much better intuition than men. Even now that intuition is seen as generally positive, this distinction sustains the old prejudice. Contrary to common belief, however, men and women share the same adaptive toolbox.