Sex, Murder, and the Meaning of Life (24 page)

What counts as evolutionary rationality varies with the species. Elephants take decades to reach sexual maturity; some small mammals can successfully reproduce after only a few months. What counts as an evolutionarily rational strategy also varies within a species and depends on the animal's sex as well as on his or her phase of the life span. And at any given time for any given animal, the immediate environment may offer certain opportunities (or threats) and not others. As I discussed in previous chapters, our minds are equipped with a set of subprograms designed to focus our attention and our mental abilities on the current most-important set of opportunities and threats. The result is that rather than having brains with a single “rational” information processor crunching information, we have a set of different subprograms in there, each crunching information in a way designed to solve the most immediately important problems. Remember one of the key messages from the fusion of evolutionary psychology and cognitive science: The human mind is not a massive information-crunching computer but a multitude of miniminds, a collection of independent mental adaptations specifically designed to solve particular adaptive problems by crunching different kinds of information in very different ways. This has important implications for economic decision-making; what counts as a good decision about allocating resources to solve one problem may count as a very bad decision for solving another problem.

Extending the logic of Chapter 6, we can say that each individual decision-maker has several different economic subselves, and
which subself is in charge right now depends on what adaptive threats and opportunities are currently prominent in the environment. What looks like irrationality to one subself may be deeply rational to another. Your marketplace subself, which is dominated by the question, “What's in it for
moi
?,” would be aghast at the exorbitant bill your parental subself has run up sending junior through college, for example.

The implications of the evolutionary multiple-mind viewpoint for everyday economic decision-making are thus far largely unexplored. But in this book, we have already covered evidence suggesting that the decision rules a woman uses when thinking about how to negotiate with a stranger in the marketplace will not follow the same math as the mental rules she would use in deciding how to exchange resources with her son, who shares half her genes, and is dependent on her generosity if he is himself to survive to reproductive age. Besides the different mental rules for dealing with strangers and close kin, everyday people need yet another set of decision biases for interacting with friends, to whom they are linked not by shared genes but by trust-based reciprocal exchanges. And romantic partners do business according to still another set of decision rules.

In studies I discussed in earlier chapters, my colleagues and I found that whether or not a person chooses to conspicuously and wastefully throw around his or her wealth, to display his or her benevolence and nurturance, to risk a fight, or to go against group opinion will ebb and flow in predictable ways depending on whether that person is a she or a he and on whether he or she is in a mating frame of mind, as opposed to thinking about status or worrying about life and limb.

The logic of deep rationality suggests that fundamental biological motives such as mating and self-protection should drastically change all the traditional behavioral economic biases, such as temporal discounting (the tendency to value small immediate payoffs over larger delayed ones) and probability discounting (the tendency to prefer a
smaller payoff now over a larger one later). The same motives should also change what a person regards as luxury versus necessity, and they should do so very differently for men and women. A series of experiments by Norm Li and his colleagues found profound differences between men and women in distinguishing between luxuries and necessities in different aspects of social decision-making. For example, if people are given an abundant budget of “mate dollars,” both men and women choose similar partners: They want someone who is physically attractive, funny, warm, and high status. But most of us are not like a wealthy movie actor who can “have it all”; instead, we have to prioritize. When men are put on a more limited budget of mate dollars, they spend first on physical attractiveness, indicating that that is a high priority. Women on a limited budget make different choices, placing higher priority on getting a partner with sufficient wealth or status and treating good looks as an expendable luxury.

Let's reconsider the classic case of “loss aversion” in light of the notion of deep rationality. As I mentioned earlier, the Kahneman and Tversky loss aversion function simply indicates that a loss of a given size (say $100) has more psychological impact than a gain of the same size. This function has now made its way into introductory economics textbooks and has been amply supported by research. Indeed, one recent review concludes, “There has been so much research on loss aversion that we can say with some certainty that people are impacted twice as much by losses as they are by gains.” But why the bias, and is it the same for every type of gain and loss?

Evolutionary theorists, including E. O. Wilson, have suggested a possible answer to the “why” question: Ancestral humans would have survived better if they put a higher priority on avoiding losses than on acquiring gains because they frequently lived close to the margin of
survival (extra food would be nice, but insufficient food could mean death). Consistent with this idea, loss aversion has been found not only in humans but also in other species (whose ancestors, like ours, would have suffered more from falling below the line of subsistence than they would have profited from an overabundance of resources). This is a plausible functional hypothesis about past conditions, but it does not fully exploit the scientific strengths of the modern evolutionary approach, which we can use to generate specific new hypotheses about when and how loss aversion should ebb and flow with functionally important motivations.

For example, the usual inclination toward loss aversion should be erased or even reversed when a mating motive is activated. Furthermore, this erasure should occur only for males, and not for females. Why? As I noted earlier, women, as female mammals, have an intrinsically high minimum investment in their young, and this inspires them to be relatively more selective in choosing mates. As a consequence, males must compete to be chosen as mates. I talked about various ways for a male to say, “Pick me! Pick me!” One is to flash a noticeably wasteful display (such as a peacock's feathers or a Porsche Carrera GT); another is to directly outcompete the other males (butting them with antlers or winning a fight for a well-appointed executive office). To beat out the competition, it helps to take risks, and as noted in Chapter 9, male mammals indeed become especially risky during the mating season. It follows that men primed to think about mating should act like bighorn sheep during the rutting season, when too great an aversion to losses would prevent the kind of risky competition that can beat out the other males.

If our logic is correct, though, the shape of that famous function should change in predictable ways for men under the influence of a mating motive. Men primed to think about mating ought to shift their attention toward gains and away from losses. Along with Jessica Li, Vlad Griskevicius, and Steve Neuberg—and funded by a generous
grant from the National Science Foundation—I set out to test this hypothesis. In one experiment, we had some people (in the mating condition) think about a romantic first encounter with someone they found very attractive, whereas others (in the control condition) thought simply about organizing their desk.

After the motive manipulation, all our subjects answered a series of questions like this: Imagine that you are at the 50th percentile of financial assets (in other words, half the population makes less money than you, and the other half makes more). How happy or unhappy would you be if you dropped to the 40th percentile? (Imagine an 11-point scale, with 1 being extremely unhappy, and 11 being extremely happy.) What about if you went up to the 60th percentile? How happy or unhappy would that make you?

The results came out exactly as we had expected: In the control condition people were inclined to be loss averse—that is, they expected their happiness level to change more after a loss than after a gain. A mating motive had no effect on women's responses, but it did have an impact on men's judgments. Men in a mating frame of mind focused more on the gains, and reduced their normal oversensitivity to losses. That is, their psychological evaluations changed in a way that would encourage them to be more risky. This finding was not just a general effect of becoming more physiologically aroused, either. In a later study, we also put some people in a self-protective frame of mind by having them imagine a scenario in which someone was breaking into their house. When their night watchman self was thus activated, men, like women, became even more loss averse.

By integrating behavioral economics with evolutionary psychology, I believe we are moving toward a totally new way of thinking about economic rationality. Behavioral economist Dan Ariely has eloquently
argued that we are “predictably irrational.” But this depiction captures only half of the truth. It is certainly true that people do not systematically calculate all the potential costs and benefits of various alternative choices and then reliably choose the one most likely to maximize their future gains. The behavioral economists are correct in pointing out that we instead use simple heuristics, ignoring a great deal of relevant information and thus making biased decisions that do not incorporate all the available options. At a deeper level, however, our biases reflect the influence of profoundly important functionally relevant motivations. Furthermore, our failures to make simplistically “selfish” choices reflect the powerful influence of a deeper rationality. Rather than being designed to maximize immediate personal reward, many of our choices seem designed to maximize our long-term genetic success.

So far, we have focused mainly on the psychology of the individual. Of course, all the individual biases inside your head and mine are designed to produce effects on the social world—to attract mates, to gain status, to protect ourselves from harm, and so on. And as illustrated by the case of the prisoner's dilemma, your individual decisions and mine are intrinsically dependent on and sensitively responsive to decisions made by the people around us. The implications of this dynamic connection between different people's decisions go way beyond two people negotiating a check in a restaurant or trying to avoid a fistfight, though. In fact, your personal decisions link you into a vast network with strangers halfway around the world, including dairy farmers in the Netherlands, financiers in New York, and world leaders in Washington, Moscow, and Beijing. In the next chapter, we'll explore how all that works.

E
very day before school, my little brother and I donned identical blue pants, white shirts, and blue ties. The uniform marked us as students at St. Joseph's, the Catholic elementary school on the corner. There was also a public school on our block, P.S. 70, but our mother didn't even like us playing in the schoolyard there. What troubled her was not just that the un-uniformed public school kids were rowdier than the nun-fearing youngsters at St. Joseph's, but also that the schoolyard was a hangout for the Garrisons, a gang of teenage hooligans who wore leather jackets and tight jeans held up with thick leather Garrison belts (the source of the gang's name). The Garrisons upset the respectable citizens on the block by fighting, drinking, cursing, and having sex in the schoolyard. As a boy growing up in the 1950s, of course, I thought these James Dean–like characters, with their greased pompadour haircuts and Lucky Strikes dangling from sneering mouths, were kind of cool.

By the time I started high school, the Garrisons were gone, several to prison. But there was a new generation of public school hoodlums
hanging out in P.S. 70's urine-stinking schoolyard. Besides drinking and fighting, the new troublemakers were reputed to be taking drugs, which included popping “downers,” and sniffing glue. Although several members of the new generation of rowdies had been my playmates as children, I joined a different crowd. I started hanging out at a nearby city park with a group of teenagers who had graduated from St. Joseph's and had mostly gone on to Catholic high schools.

Although my parents should have been relieved that I had not fallen in with the glue-sniffers in P.S. 70's schoolyard, they nevertheless disapproved of my new crowd. They had hoped I would hang out instead with my fellow students at Regis, an elite Jesuit school in Manhattan where all the students were supported by scholarships. My new associates, however, who called themselves the Forty-sixth Street Boys, were not Regis intellectuals but mostly students from lower-tier Catholic high schools like Power Memorial and Mater Christi. Some of the Forty-sixth Street Boys had even dropped out of the Catholic school system to attend Bryant High, a city school where students sniffed glue in the restrooms and where a full-time policeman was assigned to roam the grounds. Rather than spending their time in the library and dressing in preppie Brooks Brothers–style outfits, like the budding young scholars at Regis, the Forty-sixth Street Boys dressed in tight sharkskin pants and greaser-style half-boots while they hung around the park smoking cigarettes, flirting with girls, and listening to doo-wop music on transistor radios. I was, as my parents observed, hanging out with the “wrong crowd.”