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If engineers build kluges mostly to save money or to save time, why does nature build them? Evolution is neither clever nor penny-pinching. There’s no money involved, no foresight, and if it takes a billion years, who’s going to complain? Yet a careful look at biology reveals kluge after kluge. The human spine, for example, is a lousy solution to the problem of supporting the load in an upright, two-legged creature. It would have made a lot more sense to distribute our weight across four equal cross-braced columns. Instead, all our weight is borne by a single column, putting enormous stress on the spine. We manage to survive upright (freeing our hands), but the cost for many people is agonizing back pain. We are stuck with this barely adequate solution not because it is the best possible way to support the weight of a biped, but because the spine’s structure evolved from that of four-legged creatures, and standing up poorly is (for creatures like us, who use tools) better than not standing up at all.

Meanwhile, the light-sensitive part of our eye (the retina) is installed backward, facing the back of the head rather than the front. As a result, all kinds of stuff gets in its way, including a bunch of wiring that passes through the eye and leaves us with a pair of blind spots, one in each eye.

Another well-known example of an evolutionary kluge comes from a rather intimate detail of male anatomy. The tubing that runs from the testis to the urethra (the vas deferens) is much longer than necessary: it runs back to front, loops around, and does a 180-degree turn back to the penis. A parsimonious designer interested in conserving materials (or in efficiency of delivery) would have connected the testis directly to the penis with just a short length of tubing; only because biology builds on what has come before is the system set up so haphazardly. In the words of one scientist, “The [human] body is a bundle of imperfections, with… useless protuberances above the nostrils, rotting teeth with trouble-prone third molars, aching feet…, easily strained backs, and naked tender skin, subject to cuts, bites, and, for many, sunburn. We are poor runners and are only about a third as strong as chimpanzees smaller than ourselves.”

To this litany of human-specific imperfections, we might add dozens more that are widely shared across the animal world, such as the byzantine system by which DNA strands are separated prior to DNA replication (a key process in allowing one cell to become two). One molecule of DNA polymerase does its job in a perfectly straightforward fashion, but the other does so in a back-and-forth, herkyjerky way that would drive any rational engineer insane.

Nature is prone to making kluges because it doesn’t “care” whether its products are perfect or elegant. If something works, it spreads. If it doesn’t work, it dies out. Genes that lead to successful outcomes tend to propagate; genes that produce creatures that can’t cut it tend to fade away; all else is metaphor. Adequacy, not beauty, is the name of the game.

Nobody would doubt this when it comes to the body, but somehow, when it comes to the mind, many people draw the line. Sure, my spine is a kluge, maybe my retina too, but my mind? It’s one thing to accept that our body is flawed, quite another to accept that our mind is too.

Indeed, there is a long tradition in thinking otherwise. Aristotle saw man as “the rational animal,” and economists going back to John Stuart Mill and Adam Smith have supposed that people make decisions based on their own self-interest, preferring wherever possible to buy low and sell high, maximizing their “utility” wherever they can.

In the past decade, a number of academics have started to argue that humans reason in a “Bayesian”[2] fashion, which is mathematically optimal. One prestigious journal recently devoted an entire issue to this possibility, with a trio of prominent cognitive scientists from MIT, UCLA, and University College London arguing that “it seems increasingly plausible that human cognition may be explicable in rational probabilistic terms… in core domains, human cognition approaches an optimal level of performance.”

The notion of optimality is also a recurrent theme in the increasingly popular field of evolutionary psychology. For example, John Tooby and Leda Cosmides, the cofounders of the field, have written that “because natural selection is a hill-climbing process that tends to choose the best of the variant designs that actually appear, and because of the immense numbers of alternatives that appear over the vast expanse of evolutionary time, natural selection tends to cause the accumulation of superlatively well engineered functional designs.”

In the same vein, Steven Pinker has argued that “the parts of the mind that allow us to see are indeed well engineered, and there is no reason to think that the quality of engineering progressively deteriorates as the information flows upstream to the faculties that interpret and act on what we see.”

This book will present a rather different view. Although no reasonable scholar would doubt the fact that natural selection can produce superlatively well engineered functional designs, it is also clear that superlative engineering is by no means guaranteed. What I will argue, in contrast to most economists, Bayesians, and evolutionary psychologists, is that the human mind is no less of a kluge than the body. And if that’s true, our very understanding of ourselves — of human nature — must be reconsidered.

In the extensive literature on evolutionary psychology, I know of only a few aspects of the human mind that have been attributed to genuine quirks. Although most evolutionary psychologists recognize the possibility of suboptimal evolution in principle, in practice, when human errors are discussed, it’s almost always to explain why something apparently nonadaptive actually turns out to be well engineered.

Take, for example, infanticide. Nobody would argue that infanticide is morally justifiable, but why does it happen at all? From the perspective of evolution, infanticide is not just immoral, but puzzling. If we exist essentially as gene-propagating vessels (as Richard Dawkins has argued), why would any parent murder his or her own child? Martin Daly and Margo Wilson have argued that from the gene’s-eye view, infanticide makes sense only in a very limited set of circumstances: when the parent is not actually related by blood to the child (stepparents, for example), when a male parent is in doubt about paternity, or when a mother is not currently in a position to take good care of the child, yet has prospects for taking better care of some future child (say, because the current infant was born hopelessly unhealthy). As Daly and Wilson have shown, patterns of murder and child abuse fit well with these hypotheses.

Or consider the somewhat unsurprising fact that men (but not women) systematically tend to overinterpret the sexual intentions of potential mates.[3] Is this simply a matter of wishful thinking? Not at all, argue the evolutionary psychologists Martie Haselton and David Buss. Instead, it’s a highly efficient strategy shaped by natural selection, a cognitive error reinforced by nature. Strategies that lead to greater reproductive success spread (by definition) widely throughout the population, and ancestral males who tended to read too much into the signals given by possible partners would have more opportunities to reproduce than would their more cautious counterparts, who likely failed to identify bona fide opportunities. From the gene’s-eye view, it was well worth it for our male ancestors to take the risk of overinterpretation because gaining an extra reproductive opportunity far outweighs the downside, such as damage to self-esteem or reputation, of perceiving opportunity where there is none. What looks like a bug, a systematic bias in interpreting the motives of other human beings, might in this case actually be a positive feature.

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2

The term Bayesian comes from a particular mathematical theorem stemming from the work of the Reverend Thomas Bayes (1702–1761), although he himself did not propose it as a model for human reasoning. In rough terms, the theorem states that the probability of some event is proportional to the product of the likelihood of that event and its prior probability. For a clear (though somewhat technical) introduction, point your browser to http://en.wikipedia.org/wiki/Bayesian_statistics.

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3

Except, tellingly, those of their sisters.