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How the Mind Works

STEVEN PINKER

Director, McDonnell-Pew Center for Cognitive Neuroscience, Massachusetts Institute of
Technology, Cambridge, Massachusetts 02139, USA

The human mind is a remarkable organ. It has allowed us to walk on the moon, to
discover the physical basis of life and the universe, and to play chess almost as well
as a computer. But the brain raises a paradox. On the one hand, many tasks that we
take for granted—walking around a room, picking up an object, recognizing a face,
remembering information—are feats that scientists and engineers have been unable
to duplicate in robots and computers. Nonetheless, these feats can be accomplished
by any four-year-old, and we tend to be blasé about them. On the other hand, for all
its engineering excellence, the mind has many apparent quirks. For example, why is
the thought of eating worms disgusting when worms are perfectly safe and nutri-
tious? Why do men do insane things like challenge each other to duels and murder
their ex-wives? Why do fools fall in love? Why do people believe in ghosts and
spirits?

Recently, I have been foolhardy enough to try to answer questions like this in a

book called How the Mind Works. What I will be talking about today comes from
that book, which is based on three key ideas: computation, evolution, and
specialization.

The first idea is that the function of the brain is information processing, or com-

putation. Computation involves an age-old problem, one that was raised by Profes-
sor Edelman, namely, Descartes’s problem of the causation of behavior. If I were to
ask you, “Why did Bill just get on the bus?” to answer that question you wouldn’t
run a neural network simulation and you wouldn’t need to put Bill’s head in a scan-
ner. You could just ask Bill, and you might discover that the explanation for his be-
havior is that he wants to visit his grandmother, and he knows that the bus will take
him to his grandmother’s house. No science of the future is likely to provide an ex-
planation with greater predictive power than that. If Bill hated the sight of his grand-
mother or if he knew the route had changed, his body would not be on that bus. But
this excellent theory raises a puzzle. The beliefs and desires that cause Bill’s behav-
ior are colorless, odorless, tasteless, and weightless. Nevertheless, they are as potent
a cause of action as any billiard ball clacking into another billiard ball.

How do we explain this seeming paradox? One part of the solution, I believe, is

that beliefs and desires are information. Information is another commodity that is
colorless, odorless, tasteless, and weightless yet can have physical effects without
resorting to any occult or mysterious process. Information consists of patterns in
matter or energy, namely symbols, that correlate with states of the world. That’s
what we mean when we say that something carries information. A second part of the
solution is that beliefs and desires have their effects in computation—where compu-
tation is defined, roughly, as a process that takes place when a device is arranged so
that information (namely, patterns in matter or energy inside the device) causes
changes in the patterns of other bits of matter or energy, and the process mirrors the

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laws of logic, probability, or cause and effect in the world. The result is that if the
old patterns are accurate or true, or correlate with some aspect of reality, the new ar-
rangements of matter or energy will as well. The cascade gives the device an ability
to deduce new truths from old truths, which is not a bad definition of thinking. In
fact, the computational theory of mind is the only theory that I know of that can ex-
plain how it is that patterns of physical change in a device—be it a computer or a
brain, or, for that matter, some extraterrestrial intelligent life—might accomplish
something we would dignify with the term “thinking.” It’s the only explanation we
have for how physical changes actually do something we would be willing to call
intelligent. It is an explanation of where intelligence comes from.

A few comments must be added to this claim. One is that the computational the-

ory of mind is very different from the computer metaphor that Professor Edelman
has alluded to in his presentation. As he pointed out, there are many ways in which
commercially available computers are radically different from brains. Computers are
serial; brains are parallel. Computers are fast; brains are slow. Computers have de-
terministic components; brains have noisy components. Computers are assembled
by an external agent; brains have to assemble themselves. Computers display screen-
savers with flying toasters; brains do not. But the claim is not that commercially
available computers are a good model for the brain. Rather, the claim is that the an-
swer to the question “What makes brains intelligent?” may overlap with the question
“What makes computers intelligent?” The common feature, I suggest, is informa-
tion-processing, or computation. An analogy is that when we want to understand
how birds fly, we invoke principles of aerodynamics that also apply to airplanes. But
that doesn’t mean that we are committed to an airplane metaphor for birds and
should ask whether birds have complimentary beverage service. It’s a question of
isolating the key component of the best explanation.

Another comment is that the computational theory of mind, explicitly or not, has

set the agenda for brain science for decades. An old example from introductory neu-
roscience classes describes the naive person who asks, “Since the image on the retina
is upside-down but we see the world right-side up, is there some part of the brain that
turns the image right-side up?” We all realize that this question rests on a fallacy, that
there is no such process in the brain, and that there doesn’t need to be any such pro-
cess. Why is it a fallacy? Because the orientation of the image on the retina makes
no difference to how the brain processes information. Since information-processing
is the relevant aspect of what goes on in the brain, the orientation on the retina—and,
for that matter, on the visual cortex—is irrelevant; that is why the above is a
pseudoquestion. Similarly, the search for the neural basis of psychological functions
is guided, from beginning to end, by invoking information-processing. As you know,
one of the great frontiers of science is the search for the molecular basis of learning
and memory. Well, of the hundreds or thousands of metabolic processes in the brain,
how will we know when we’ve identified the one that corresponds to memory? We
will know we have it when the process meets the requirements of the storage and re-
trieval of information. So again, it is information that sets the interesting questions
in neuroscience.

A third comment is that the computational theory of mind is a radical challenge

to our everyday way of thinking about the mind, because the theory says that the life-
blood of thought is information. That goes against our folk notion that the lifeblood

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of thought is energy or pressure. Why did the disgruntled postal worker shoot up the
post office? Well, for many years, we say, pressure had been building up until he fi-
nally burst; if only he had had an alternative outlet to which to divert all of that en-
ergy, he could have released it in more constructive ways. The metaphor is that
thought and emotion are animated by some superheated fluid or gas under pressure.
Now, there is no doubt that this hydraulic metaphor captures something about our
experience. But we know that it is not literally how the brain works: there is no con-
tainer full of fluid and channels through which the fluid flows. And that raises an im-
portant scientific question: Why is the brain going to so much trouble to simulate
energy and pressure, given that it doesn’t literally work that way? I will return to that
question later.

Let me continue with the second key idea: evolution. How do we understand a

complex device? Imagine that you are rummaging through an antique store and you
come across a contraption bristling with gears and springs and a handle and hinges
and blades. You have no idea how to explain it until someone tells you what it’s for
—say, an olive-pitter. Once you realize what the device is for—what its function is—
suddenly all the parts and their arrangements become clear in a satisfying rush of in-
sight. This is an activity called “reverse engineering.” In forward engineering, you
start off with an idea for what you want a device to do and you go and build the de-
vice. In reverse engineering, you stumble across a device and try to figure out what
it was designed to do. Reverse engineering is what the technicians at Panasonic do
when Sony comes out with a new product. They go to the store, buy one, bring it
back to the lab, take a screwdriver to it, and try to figure out what all the little widgets
and gizmos are for.

For the last few hundred years, the science of physiology has been a kind of re-

verse engineering. Living bodies are complex devices and pose questions like “Why,
in the eye, do we find the most transparent tissue in the body that just happens to be
shaped like a lens, behind the lens an iris that expands and contracts in response to
light, and a layer of light-sensitive tissue that happens to be at the focal plane of the
lens?” Questions like these can be answered only by the idea that the eye was in
some sense “designed” to form an image. We analyze it just as if it were a machine.
For centuries, the complexity of the eye and other organs was taken as conclusive
proof of the existence of God. If the eye shows signs of design, it must have a de-
signer—namely, God. Darwin’s great accomplishment was to explain signs of engi-
neering in the natural world through a purely physical force, namely, the differential
replication rates among replicators competing for resources in a finite environment,
iterated over hundreds and thousands of generations.

Of course, the eye doesn’t just sit by itself, isolated in the skull. Rather, the eye

is connected to the brain. In fact, the eye can validly be considered to be an extension
of the brain. And that naturally leads us to treat the mind as a complex natural device
—in this case, a complex computational device—which makes the science of psy-
chology a kind of reverse engineering. Just as in the case of the olive-pitter, we can
understand the brain only once we have correctly identified its function. If we
thought that the olive-pitter was a wrist-exerciser, we would have a very different ex-
planation for what the parts are for. The crucial place to begin explaining the mind,
therefore, is to understand its function. Since the mind is a product of natural selec-
tion, not of a conscious engineer, we have an answer to that question: the ultimate

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function of the mind is survival and reproduction in the environment in which the
mind evolved—that is, the environment of hunting and gathering tribes in which we
have spent more than 99% of our evolutionary history, before the recent invention of
agriculture and civilizations only 10,000 years ago.

The third key idea is specialization. The mind is designed to solve many kinds of

problems, such as seeing in three dimensions, moving arms and legs, understanding
the physical world, finding and keeping mates, securing allies, and many others.
These are very different kinds of problems, and the tools for solving them are bound
to be different as well. We know that specialization is ubiquitous in biology. The
body is not made of Spam, but is divided into systems and organs and tissues, each
designed to perform a special function or functions. The heart has a different struc-
ture from the kidney because a device that pumps blood has to be different from a
device that filters blood. This specialization continues all the way down: to the dif-
ferent tissues that the heart and the kidney are made from, all the way down to dif-
ferences in the molecules that they are made from. The mind, like the body is
organized into mental systems and organs and tissues—a kind of hierarchical differ-
entiation that was beautifully displayed in the functional neuroimaging experiments
that Professor Raichle has shown.

I concur fully in a point that has been made several times during this session—

namely, that the mind will not be explained in terms of some special essence or won-
der tissue or almighty mathematical principle. Rather, the mind is a system of com-
putational organs that allowed our ancestors to understand and outsmart objects,
animals, plants, and each other. I will try to give you a glimpse of how three of these
organs of computation might be dissected. I will present examples of seeing, think-
ing, and emotions about people.

Let’s begin with seeing. The problem of vision can be made vivid by imagining

what the world looks like from the brain’s point of view. It is not what we whole,
functioning human beings experience, namely, a showcase of three-dimensional ob-
jects arrayed in space. Rather, the brain “sees” a million activation levels corre-
sponding to the brightnesses of tiny patches on the retina; the retinal image as a
whole is a two-dimensional projection of the three-dimensional world. The task for
the visual system of the brain is to recover information about three-dimensional
shapes and their arrangements from the pattern of intensities on the retinal image.
The brain has evolved a number of tricks for solving this problem, and I am going to
talk about one of them—sometimes called “shape-from-shading.” Each of these
tricks exploits a regularity of optics that is true by virtue of physical law, and the
brain can, in a sense, run these laws “backwards” to try to make intelligent guesses
about what is out there in the world based on the information that is coming in from
the retina.

One important bit of physics is (roughly) that the steeper the angle formed by a

surface with respect to a light source, the less light the surface reflects. So as I shine
a flashlight perpendicularly to a card, it projects a concentrated, bright spot of light.
But when I rotate the card, the beam is smeared across a large area, and any partic-
ular part of the area must be dimmer. Now, the shape-from-shading algorithm—a bit
of psychology—more or less runs the law backwards and says that the dimmer a
patch on the retina, the steeper the angle of the surface in the world. And with that
algorithm, the brain can reconstruct the shape of an object by estimating the angles
of the thousands of tiny facets or tangent planes that make up the surface.

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This process works reasonably well, but it depends on a key assumption. Since it

interprets differences in brightness as coming from differences in surface angle, it
implicitly assumes a uniformly colored world, or at least a randomly colored world.
That means that the process is vulnerable, because surfaces that are colored in clever
ways should fool the shape-from-shading module and cause us to see things that
aren’t there. In fact, it does happen: two striking examples are television and make-
up. If alien anthropologists visited this planet, they would be puzzled by the fact that
the average American spends four hours a day staring at a piece of glass on the front
of a box. Why do we do this? Because the television set has been arranged to violate
the assumption of uniform or random coloration. It has been engineered to display a
highly nonrandom pattern that fools the shape-from-shading module of the brain
into hallucinating a three-dimensional world behind the pane of glass.

Another example is makeup. A person who is skilled at applying makeup might

put a little blush on the sides of the nose, because the eye of the beholder is attached
to a shape-from-shading module that interprets darker surfaces as steeper angles,
making the sides of the nose look more parallel and the nose smaller and more at-
tractive. Conversely, if you put light powder on the upper lip, the brain says that
lighter equals a flatter angle, which makes the lip look fuller, giving that desirable
pouty look that models strive so hard to attain.

More generally, these examples offer an explanation for many of the seemingly

inexplicable quirks of modern human thought and behavior. Many illusions, falla-
cies, and maladaptive behaviors may come not from some inherent defect or design
flaw but from a mismatch: a mismatch between assumptions about an ancestral
world that were built into our mental modules over millions of years and the struc-
ture of the current world (which we have turned topsy-turvy by technology in our
recent history). It has long been a puzzle for biologists why people do maladaptive
things like eat junk food, use contraception (which, when you think of it, is a kind
of Darwinian suicide), or gamble. But if you posit that our mental modules assume
a world in which sweet foods are nutritious (namely, ripe fruit), in which sex leads
to babies (as it tended to do until the invention of reliable contraceptives), and in
which statistical patterns have underlying causes, then these activities no longer
seem quite so mysterious.

Next, let us turn to the problem of thinking. There is an old puzzle that has wor-

ried philosophers and biologists ever since it was pointed out by Alfred Russel Wal-
lace, the co-discoverer, with Darwin, of natural selection. What do illiterate,
technologically primitive hunter-gatherers do with their capacity for abstract intelli-
gence? In fact, this question might be more justly asked by hunter-gatherers about
modern American couch potatoes. After all, life for hunters and gatherers was like a
camping trip that never ended, but without Swiss army knives and tents and freeze-
dried pasta. Our ancestors had to live by their wits and eke out a living from an eco-
system in which most of the plants and animals whose bodies we consume as food
would just as soon keep their bodies for themselves.

Our species succeeded by entering what a biologist might call the “cognitive

niche”: the ability to overtake the fixed defenses of other organisms by cause-and-
effect reasoning. In all human societies, no matter how supposedly primitive, people
use a variety of tools; traps; poisons; various ways of detoxifying plants by cooking,
soaking, and leaching; methods of extracting medicines from plants to combat par-
asites and pathogens; and an ability to act cooperatively to accomplish what a single

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person acting alone could not achieve. These accomplishments show that the mind
must be equipped with ways of grasping the causally significant parts of the world.
The world is a heterogeneous place, and it is likely that we have several different in-
tuitive theories or varieties of common sense that are adapted to figure out the causal
structure of different aspects of the world. We can think of them as a kind of intuitive
physics, intuitive biology, intuitive engineering, and intuitive psychology, each
based on a core intuition.

The most basic is intuitive physics, an appreciation of how objects fall, roll, and

bounce. The core intuition behind our intuitive physics is the existence of stable ob-
jects that obey some kind of physical laws. This is not a banal claim. William James
said that the world of the infant is a “blooming, buzzing confusion”—a kaleidoscope
of shimmering pixels—and that knowledge of stable objects is an achievement only
of late infancy. Yet one of the first things we learn in introductory courses in philos-
ophy is that unless one has an assumption that the multitude of sensory impressions
is caused by an underlying stable object, one could experience the blooming and
buzzing confusion all of one’s life. Indeed, the more we know about the world of the
infant, the more we see that William James, at least in this case, didn’t have it quite
right. The youngest infants that can be tested (about three months old) already are
expecting a world that contains stable objects, and they are surprised when an exper-
imenter rigs up a display in which an object vanishes, passes through another object,
flies apart, or moves without an external push. As one psychologist summed up the
literature: A “blooming, buzzing confusion” is a better description of the world of
the parents of an infant than of the world of the infant.

But there are many objects that we encounter that seem to violate our intuitive

physics. As the biologist Richard Dawkins has pointed out, if you throw a dead bird
in the air, it will describe a graceful parabola and come to rest on the ground, just
like the physics books say it should. But if you throw a live bird in the air, it won’t
describe a graceful parabola, and it might not touch land this side of the county
boundary. In other words, we interpret living things such as birds not through our
intuitive physics but through an intuitive biology. We do not assume that birds are
some kind of weird, springy object that violates the laws of physics; we assume,
rather, that birds follow a different kind of law altogether—the laws of biology. The
core intuition of folk biology is that plants and animals have an internal essence that
contains a renewable supply of energy or oomph, that gives the animal or plant its
form, that drives its growth, and that orchestrates its bodily functions. This deep-
rooted intuition is found in all peoples and explains why hunter-gatherers are such
excellent amateur biologists. Botanists and zoologists who do field work with hunt-
er-gatherers are often astonished to learn that hunter-gatherers have remarkably de-
tailed knowledge about local plants and animals and that their names for these plants
and animals usually match the Linnaean genus or species of the professional biolo-
gists. These categorizations often involve lumping animals that, from surface ap-
pearance, look very different—for example, a caterpillar and a butterfly, or a male
and a female bird with different plumage. Hunter-gatherers, using their intuitions
about the hidden essences in animals or plants, predict their future behavior. They
may, from a set of tracks, deduce the kind of animal and where it is likely to be head-
ing so that they can surprise it at a resting place; or they might notice a flower in the
spring and return to it in the fall to dig out a hidden tuber that the flower portends.

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They extract juices and powders of living things and try them out as medicines, poi-
sons, and food additives.

The third kind of intuition, different from the first two, is an intuitive engineering.

Our species is famous for exploiting and using tools or artifacts, and the core intu-
ition behind tools is their function. If I ask you to define a “chair,” you might say it
is a stable horizontal surface supported by four legs. But that will not work for bean-
bags, cubes, severed elephant’s feet, and other objects that we can call chairs. The
only thing that chairs have in common is that someone intended them to hold up a
human behind. The core intuition behind our faculty to appreciate tools involves
their function, or the intention of a designer. Young children, before they’ve entered
school, sharply distinguish artifacts from living things. For example, in one experi-
ment, children were told that doctors took a raccoon, spray-painted it black with a
white stripe down its back, and implanted into it a sack of smelly stuff. The children
were then shown a picture of a skunk and asked what it was. Most of them said that
it was still a raccoon. But if they were told that doctors took a coffee pot, sawed off
its handle, cut a hole through it, and filled it with birdseed, and then are shown a pic-
ture of a bird feeder and asked what it is, they say it’s a bird feeder. This experiment
shows that even young children appreciate that an artifact such as a bird feeder is
anything that feeds birds, but a natural object such as a raccoon has an internal con-
stitution that cannot be changed by superficial manipulations.

And finally, people have an intuitive version of psychology. I mentioned earlier

that all of us explained Bill’s behavior in getting on the bus not by assuming there is
some kind of magnetic force that pulls him aboard or that he is a kind of artifact like
a windup doll, but that he acts out of beliefs and desires, a kind of entity we cannot
help but posit even though it is not directly observable. Again, this ability is dis-
played early by young children, who can, for example, deduce what an adult knows
and wants just from observing what the adult is looking at.

There is evidence, apart from developmental psychology, that our reasoning abil-

ity really is divided into these intuitive theories or ways of thinking. For example,
the technique of functional neuroimaging, which has been described by Dr. Raichle,
has shown that different parts of the brain are active when people think about tools
or about living things. Moreover the presumably genetic syndrome of autism can be
pretty well characterized by saying that it impairs a person’s intuitive psychology:
Autistic children really do interpret humans as if they were windup dolls, and have
no concept that other people have beliefs and desires.

Misapplications of the four forms of thinking, or a shift from one way of thinking

to another, can also explain certain puzzling behaviors and beliefs. One example is
slapstick humor. We laugh when someone slips on a banana peel because of the sud-
den shift from thinking of the person in the usual way (using our intuitive psychol-
ogy and thinking of him as a locus of beliefs and desires) to thinking of him as an
object ignominiously obeying the laws of physics. Belief in souls and ghosts consists
of taking our intuitive psychology and divorcing it from our intuitive biology, so that
we think of minds that have an existence independent of bodies. And animistic be-
liefs do the opposite: They marry our intuitive psychology to our intuitive biology,
physics, or engineering and allow us to think of trees, mountains, or idols as having
minds.

I will now proceed to my final example: emotions about people. The main puzzle

about our feelings toward other people is why they are often so passionate and seem-

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ingly irrational. Why do people pursue vengeance past the point of any value to
themselves? Why do people defend their honor in crazy ways such as challenging
each other to duels? Why do people fall head over heels in love? The most common
theory, among both scientists and lay people, is the “romantic theory”—the idea that
the emotions come from a vestigial force (part of our heritage from nature), and that
they are maladaptive and dangerous unless they are channeled into art and creativity.
I’m going to explain a very different alternative, the “strategic theory,” which pro-
poses that passion is a “paradoxical tactic” wired into us. The basic idea is that a sac-
rifice of freedom and rationality can actually give one a strategic advantage when
one is interacting with others whose interests are partly competing and partly over-
lapping with one’s own. The theory applies particularly well to instances of promis-
es, threats, and bargains. Just to show how unromantic this theory is, I am going to
illustrate it by reverse-engineering romantic love.

Cynical social scientists and veterans of the dating scene agree on one thing: that

love is a marketplace. There is a certain rationality to love—smart shopping. All of
us at some point in our lives have to search for the nicest, smartest, richest, stablest,
funniest, best-looking person who will settle for us. But that person is a needle in a
haystack, and we might die single if we held out indefinitely for him or her. So we
trade off value against time, and after a certain period set up house with the best per-
son we have found up to that point. Good evidence for this sequence of events is the
phenomenon called “assortative mating” by mate value: the overall desirabilities of
a husband and a wife or a boyfriend and a girlfriend are approximately equally
matched, as if each was trying to get the best partner he or she could.

Needless to say, that does not explain all there is to falling in love. There is an

irrational part of love, an involuntariness and caprice to it. You cannot will yourself
to fall in love. Many people can recall being fixed up with a person who looked per-
fect on paper, but when they met, they just didn’t hit it off. Cupid’s arrow didn’t
strike; the earth didn’t move. It isn’t a list of desirable traits that steals the heart; it’s
often something capricious like the way a person walks, talks, or laughs.

Is this any way to design a rational organism? As a matter of fact, it might be.

Entering a partnership through totally “rational” shopping poses a problem. If you
have set up house with the best person you have found up to a certain point, then by
the law of averages, sooner or later someone even better will come along. At that
point a rational agent would be tempted to drop a wife or husband like a hot potato.
But now think of it from the spouse’s point of view. Entering a partnership requires
sacrifices—forgone opportunities with other potential partners and the time and en-
ergy put into child-rearing, among many other things. Rational spouses could antic-
ipate that their partner would drop them when someone better came along, and they
would be foolish to enter the relationship in the first place. Thus we would have the
paradoxical situation in which what is in the interest of both parties—that they stick
with each other—cannot be effected because neither one can trust the other if the
other is acting as a rational, smart shopper.

Here is one solution to the problem. If we are wired so that we don’t fall in love

for rational reasons, perhaps we are less likely to decide to fall out of love for rational
reasons. When Cupid strikes, it makes one’s promise credible in the eyes of the ob-
ject of desire. Romantic love is a guarantor of the implicit promise one makes in
starting a romantic relationship, in the face of the problem that it may be rational to
break that promise in the future.

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Romantic love is an example of a concept from game theory called “paradoxical

tactics,” in which a lack of freedom and rationality can be an advantage. An analogy
from a nonpsychological domain is the rationale for laws and contracts. When we
apply for a mortgage from a bank, the law states that if we default on our payments,
the bank has the power to foreclose on the mortgage and seize our house. It is only
this law that makes it worth the bank’s while to lend us the money, and therefore the
law, paradoxically, works to the advantage of the borrower as well as the lender.
Likewise, leases work to both the tenant’s and the landlord’s advantage by constrain-
ing the freedom of each. In this sense, many passions, such as romantic love, could
be viewed as the neural equivalents of laws and contracts. Moreover, by symmetrical
logic, if passionate love and loyalty are guarantors that our promises are not double-
crosses, so passionate vengeance and honor serve as guarantors that our threats are
not bluffs. The problem with issuing a threat, such as “If you steal my goats, I will
beat you up,” is that carrying out a threat can be dangerous: you could get hurt beat-
ing someone up. The only value of the threat is as a deterrent; once it has to be car-
ried out, it serves no one’s purposes. Since the target of the threat is aware of that
fact, he can threaten the threatener right back by calling his bluff and daring him to
go through with the vengeance. How does one prevent one’s bluff from being called?
By being forced to carry out the threat. If we are wired to interpret defiance or tres-
pass as an intolerable insult for which we demand vengeance regardless of the cost
to ourselves, that emotion serves as a credible deterrent. One gets the reputation of
being someone that people don’t want to mess with.

Let me conclude. Earlier I pointed out that the mind seems to be equipped with a

certain number of ways of conceptualizing reality, which I called “intuitive theo-
ries.” How do we go from our everyday “intuitive theories” to the real article in gen-
uine scientific reasoning? I suspect that this unnatural activity called science is
another way of misapplying our intuitive theories. In medicine and physiology, we
avoid thinking of living things in the usual way—as being driven by a hidden essence
or substance, some kind of juice or gel or a quivering mass—and instead think of
them as a kind of machinery. That is, we take our faculty of intuitive engineering and
apply it to a domain that ordinarily we think of by our intuitive biology. I would like
to suggest that a challenge of the next century is going to be doing the same thing
for our own minds. As scientists, we will learn to treat our mind not with the faculty
of intuitive psychology that we apply every day—as a product of immaterial, inex-
plicable forces—but, as with the body, as composed of complex machinery that we
can reverse-engineer. This prospect is exciting because it will be a realization of the
age-old injunction: Know thyself.