by Steven Pinker
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Last annotated on December 21, 2015
PREFACE
Any book called How the Mind Works had better begin on a note of humility, and I will begin with two. First, we don’t understand how the mind works—not nearly as well as we understand how the body works, and certainly not well enough to design utopia or to cure unhappiness. Then why the audacious title? The linguist Noam Chomsky once suggested that our ignorance can be divided into problems and mysteries. When we face a problem, we may not know its solution, but we have insight, increasing knowledge, and an inkling of what we are looking for. When we face a mystery, however, we can only stare in wonder and bewilderment, not knowing what an explanation would even look like. I wrote this book because dozens of mysteries of the mind, from mental images to romantic love, have recently been upgraded to problems (though there are still some mysteries, too!). Read more at location 48
The linguist Noam Chomsky once suggested that our ignorance can be divided into problems and mysteries. When we face a problem, we may not know its solution, but we have insight, increasing knowledge, and an inkling of what we are looking for. When we face a mystery, however, we can only stare in wonder and bewilderment, not knowing what an explanation would even look like. I wrote this book because dozens of mysteries of the mind, from mental images to romantic love, have recently been upgraded to problems (though there are still some mysteries, too!). Every idea in the book may turn out to be wrong, but that would be progress, because our old ideas were too vapid to be wrong. Read more at location 52
My goal was to weave the ideas into a cohesive picture using two even bigger ideas that are not mine: the computational theory of mind and the theory of the natural selection of replicators. Read more at location 60
HOW THE MIND WORKS
1 STANDARD EQUIPMENT
But the gap between robots in imagination and in reality is my starting point, for it shows the first step we must take in knowing ourselves: appreciating the fantastically complex design behind feats of mental life we take for granted. The reason there are no humanlike robots is not that the very idea of a mechanical mind is misguided. It is that the engineering problems that we humans solve as we see and walk and plan and make it through the day are far more challenging than landing on the moon or sequencing the human genome. Nature, once again, has found ingenious solutions that human engineers cannot yet duplicate. Read more at location 123
The faculty with which we ponder the world has no ability to peer inside itself or our other faculties to see what makes them tick. That makes us the victims of an illusion: that our own psychology comes from some divine force or mysterious essence or almighty principle. Read more at location 131
First, a visual system must locate where an object ends and the backdrop begins. But the world is not a coloring book, with black outlines around solid regions. The world as it is projected into our eyes is a mosaic of tiny shaded patches.
..The amount of light hitting a spot on the retina depends not only on how pale or dark the object is but also on how bright or dim the light illuminating the object is.
...The harmony between how the world looks and how the world is must be an achievement of our neural wizardry, because black and white don’t simply announce themselves on the retina. Read more at location 184
The next problem is seeing in depth. Our eyes squash the three-dimensional world into a pair of two-dimensional retinal images, and the third dimension must be reconstituted by the brain. Read more at location 190
Let’s take a look at another everyday miracle: getting a body from place to place. When we want a machine to move, we put it on wheels. The invention of the wheel is often held up as the proudest accomplishment of civilization. Many textbooks point out that no animal has evolved wheels and cite the fact as an example of how evolution is often incapable of finding the optimal solution to an engineering problem. But it is not a good example at all. Even if nature could have evolved a moose on wheels, it surely would have opted not to. Wheels are good only in a world with roads and rails. They bog down in any terrain that is soft, slippery, steep, or uneven. Legs are better. Read more at location 219
But legs come with a high price: the software to control them. A wheel, merely by turning, changes its point of support gradually and can bear weight the whole time. A leg has to change its point of support all at once, and the weight has to be unloaded to do so. Read more at location 227
as one engineer has put it, “the upright two-footed locomotion of the human being seems almost a recipe for disaster in itself, and demands a remarkable control to make it practicable.” When we walk, we repeatedly tip over and break our fall in the nick of time. When we run, we take off in bursts of flight. These aerobatics allow us to plant our feet on widely or erratically spaced footholds that would not prop us up at rest, and to squeeze along narrow paths and jump over obstacles. But no one has yet figured out how we do it. Read more at location 236
an arm presents a new challenge. ..The trigonometry is frightfully complicated. But your arm is an architect’s lamp, and your brain effortlessly solves the equations every time you point. Read more at location 245
A still more remarkable feat is controlling the hand. Nearly two thousand years ago, the Greek physician Galen pointed out the exquisite natural engineering behind the human hand. It is a single tool that manipulates objects of an astonishing range of sizes, shapes, and weights, from a log to a millet seed. “Man handles them all,” Galen noted, “as well as if his hands had been made for the sake of each one of them alone.” The hand can be configured into a hook grip (to lift a pail), a scissors grip (to hold a cigarette), a five-jaw chuck (to lift a coaster), a three-jaw chuck (to hold a pencil), a two-jaw pad-to-pad chuck (to thread a needle), a two-jaw pad-to-side chuck (to turn a key), a squeeze grip (to hold a hammer), a disc grip (to open a jar), and a spherical grip (to hold a ball). Each grip needs a precise combination of muscle tensions that mold the hand into the right shape and keep it there as the load tries to bend it back. Read more at location 249
“A common man marvels at uncommon things; a wise man marvels at the commonplace.” Keeping Confucius’ dictum in mind, let’s continue to look at commonplace human acts with the fresh eye of a robot designer seeking to duplicate them. Pretend that we have somehow built a robot that can see and move. Read more at location 260
**** (Note: Wittgenstein ish) An intelligent being cannot treat every object it sees as a unique entity unlike anything else in the universe. It has to put objects in categories so that it may apply its hard-won knowledge about similar objects, encountered in the past, to the object at hand. But whenever one tries to program a set of criteria to capture the members of a category, the category disintegrates.
...common sense is not simply an almanac about life that can be dictated by a teacher or downloaded like an enormous database. No database could list all the facts we tacitly know, and no one ever taught them to us. Read more at location 287
An intelligent system, then, cannot be stuffed with trillions of facts. It must be equipped with a smaller list of core truths and a set of rules to deduce their implications. But the rules of common sense, like the categories of common sense, are frustratingly hard to set down. Even the most straightforward ones fail to capture our everyday reasoning. Read more at location 294
A thinker has to compute not just the direct effects of an action but the side effects as well. But a thinker cannot crank out predictions about all the side effects, either. Read more at location 304
**** An intelligent being has to deduce the implications of what it knows, but only the relevant implications. Dennett points out that this requirement poses a deep problem not only for robot design but for epistemology, the analysis of how we know. The problem escaped the notice of generations of philosophers, who were left complacent by the illusory effortlessness of their own common sense. Only when artificial intelligence researchers tried to duplicate common sense in computers, the ultimate blank slate, did the conundrum, now called “the frame problem,” come to light. Yet somehow we all solve the frame problem whenever we use our common sense. Read more at location 313
When the visual areas of the brain are damaged, for example, the visual world is not simply blurred or riddled with holes. Selected aspects of visual experience are removed while others are left intact. Read more at location 406
These syndromes are caused by an injury, usually a stroke, to one or more of the thirty brain areas that compose the primate visual system. Some areas specialize in color and form, others in where an object is, others in what an object is, still others in how it moves. A seeing robot cannot be built with just the fish-eye viewfinder of the movies, and it is no surprise to discover that humans were not built that way either. When we gaze at the world, we do not fathom the many layers of apparatus that underlie our unified visual experience, until neurological disease dissects them for us. Read more at location 419
**** the startling similarities between identical twins, who share the genetic recipes that build the mind. Their minds are astonishingly alike, and not just in gross measures like IQ and personality traits like neuroticism and introversion. They are alike in talents such as spelling and mathematics, in opinions on questions such as apartheid, the death penalty, and working mothers, and in their career choices, hobbies, vices, religious commitments, and tastes in dating. Identical twins are far more alike than fraternal twins, who share only half their genetic recipes, and most strikingly, they are almost as alike when they are reared apart as when they are reared together. Read more at location 424
The far-reaching effects of the genes have been documented in scores of studies and show up no matter how one tests for them: by comparing twins reared apart and reared together, by comparing identical and fraternal twins, or by comparing adopted and biological children. And despite what critics sometimes claim, the effects are not products of coincidence, fraud, or subtle similarities in the family environments (such as adoption agencies striving to place identical twins in homes that both encourage walking into the ocean backwards). Read more at location 435
REVERSE-ENGINEERING THE PSYCHE
**** (Note: premise) The mind is a system of organs of computation, designed by natural selection to solve the kinds of problems our ancestors faced in their foraging way of life, in particular, understanding and outmaneuvering objects, animals, plants, and other people. The summary can be unpacked into several claims. The mind is what the brain does; specifically, the brain processes information, and thinking is a kind of computation. The mind is organized into modules or mental organs, each with a specialized design that makes it an expert in one arena of interaction with the world. The modules’ basic logic is specified by our genetic program. Read more at location 444
The various problems for our ancestors were subtasks of one big problem for their genes, maximizing the number of copies that made it into the next generation. On this view, psychology is engineering in reverse. In forward-engineering, one designs a machine to do something; in reverse-engineering, one figures out what a machine was designed to do. Read more at location 450
Darwin insisted that his theory explained not just the complexity of an animal’s body but the complexity of its mind. “Psychology will be based on a new foundation,” he famously predicted at the end of The Origin of Species. But Darwin’s prophecy has not yet been fulfilled. More than a century after he wrote those words, the study of the mind is still mostly Darwin-free, often defiantly so. Read more at location 472
Evolutionary thinking is indispensable, not in the form that many people think of—dreaming up missing links or narrating stories about the stages of Man—but in the form of careful reverse-engineering. Read more at location 478
Thinking is computation, I claim, but that does not mean that the computer is a good metaphor for the mind. The mind is a set of modules, but the modules are not encapsulated boxes or circumscribed swatches on the surface of the brain. The organization of our mental modules comes from our genetic program, but that does not mean that there is a gene for every trait or that learning is less important than we used to think. The mind is an adaptation designed by natural selection, but that does not mean that everything we think, feel, and do is biologically adaptive. We evolved from apes, but that does not mean we have the same minds as apes. And the ultimate goal of natural selection is to propagate genes, but that does not mean that the ultimate goal of people is to propagate genes. Read more at location 491
********** Information and computation reside in patterns of data and in relations of logic that are independent of the physical medium that carries them. Read more at location 503
This insight, first expressed by the mathematician Alan Turing, the computer scientists Alan Newell, Herbert Simon, and Marvin Minsky, and the philosophers Hilary Putnam and Jerry Fodor, is now called the computational theory of mind. It is one of the great ideas in intellectual history, for it solves one of the puzzles that make up the “mind-body problem”: how to connect the ethereal world of meaning and intention, the stuff of our mental lives, with a physical hunk of matter like the brain. Read more at location 510
******* The computational theory of mind resolves the paradox. It says that beliefs and desires are information, incarnated as configurations of symbols. The symbols are the physical states of bits of matter, like chips in a computer or neurons in the brain. Read more at location 518
Neuroscientists like to point out that all parts of the cerebral cortex look pretty much alike—not only the different parts of the human brain, but the brains of different animals. One could draw the conclusion that all mental activity in all animals is the same. But a better conclusion is that we cannot simply look at a patch of brain and read out the logic in the intricate pattern of connectivity that makes each part do its separate thing. Read more at location 526
The content of a book or a movie lies in the pattern of ink marks or magnetic charges, and is apparent only when the piece is read or seen. Similarly, the content of brain activity lies in the patterns of connections and patterns of activity among the neurons. Read more at location 531
As Tooby and Cosmides have written, There are birds that migrate by the stars, bats that echolocate, bees that compute the variance of flower patches, spiders that spin webs, humans that speak, ants that farm, lions that hunt in teams, cheetahs that hunt alone, monogamous gibbons, polyandrous seahorses, polygynous gorillas. . . . There are millions of animal species on earth, each with a different set of cognitive programs. The same basic neural tissue embodies all of these programs, and it could support many others as well. Facts about the properties of neurons, neurotransmitters, and cellular development cannot tell you which of these millions of programs the human mind contains. Even if all neural activity is the expression of a uniform process at the cellular level, it is the arrangement of neurons—into bird song templates or web-spinning programs—that matters. Read more at location 534
What those microcircuits can do depends only on what they are made of. Circuits made from neurons cannot do exactly the same things as circuits made from silicon, and vice versa. For example, a silicon circuit is faster than a neural circuit, but a neural circuit can match a larger pattern than a silicon one. These differences ripple up through the programs built from the circuits and affect how quickly and easily the programs do various things, even if they do not determine exactly which things they do. My point is not that prodding brain tissue is irrelevant to understanding the mind, only that it is not enough. Psychology, the analysis of mental software, will have to burrow a considerable way into the mountain before meeting the neurobiologists tunneling through from the other side. Read more at location 545
**** Human thought and behavior, no matter how subtle and flexible, could be the product of a very complicated program, and that program may have been our endowment from natural selection. The typical imperative from biology is not “Thou shalt . . . ,” but “If . . . then . . . else.” Read more at location 566
****** (Note: loops within loops) The mind, I claim, is not a single organ but a system of organs, which we can think of as psychological faculties or mental modules. The entities now commonly evoked to explain the mind—such as general intelligence, a capacity to form culture, and multipurpose learning strategies—will surely go the way of protoplasm in biology and of earth, air, fire, and water in physics. These entities are so formless, compared to the exacting phenomena they are meant to explain, that they must be granted near-magical powers. When the phenomena are put under the microscope, we discover that the complex texture of the everyday world is supported not by a single substance but by many layers of elaborate machinery. Read more at location 570
Take our first problem, the sense of sight. A seeing machine must solve a problem called inverse optics.
...The input is the retinal image, and the output is a specification of the objects in the world and what they are made of—that is, what we know we are seeing. And there’s the rub. Inverse optics is what engineers call an “ill-posed problem.” It literally has no solution. Just as it is easy to multiply some numbers and announce the product but impossible to take a product and announce the numbers that were multiplied to get it, optics is easy but inverse optics impossible. Yet your brain does it every time you open the refrigerator and pull out a jar. Read more at location 586
**** (Note: As Wittgenstein and noted, at root is an assumption, a paradigmatic premise) The answer is that the brain supplies the missing information, information about the world we evolved in and how it reflects light. If the visual brain “assumes” that it is living in a certain kind of world—an evenly lit world made mostly of rigid parts with smooth, uniformly colored surfaces—it can make good guesses about what is out there. Read more at location 590
it’s impossible to distinguish coal from snow by examining the brightnesses of their retinal projections. But say there is a module for perceiving the properties of surfaces, and built into it is the following assumption: “The world is smoothly and uniformly lit.”
...Since Planet Earth has, more or less, met the even-illumination assumption for eons, natural selection would have done well by building the assumption in. Read more at location 599
The module has been unmasked; it does not apprehend the nature of things but relies on a cheat-sheet. That cheat-sheet is so deeply embedded in the operation of our visual brain that we cannot erase the assumptions written on it. Even in a lifelong couch potato, the visual system never “learns” that television is a pane of glowing phosphor dots, and the person never loses the illusion that there is a world behind the pane. Read more at location 607
other mental modules need their own cheat-sheets to solve their unsolvable problems. A physicist who wants to figure out how the body moves when muscles are contracted has to solve problems in kinematics (the geometry of motion) and dynamics (the effects of forces). But a brain that has to figure out how to contract muscles to get the body to move has to solve problems in inverse kinematics and inverse dynamics—what forces to apply to an object to get it to move in a certain trajectory. Like inverse optics, inverse kinematics and dynamics are ill-posed problems. Our motor modules solve them by making extraneous but reasonable assumptions—not assumptions about illumination, of course, but assumptions about bodies in motion. Read more at location 611
****** (Note: ungrounded root) we mortals have to make fallible guesses from fragmentary information. Each of our mental modules solves its unsolvable problem by a leap of faith about how the world works, by making assumptions that are indispensable but indefensible—the only defense being that the assumptions worked well enough in the world of our ancestors. Read more at location 629
(Note: Biological unity) An organ of the body is a specialized structure tailored to carry out a particular function. But our organs do not come in a bag like chicken giblets; they are integrated into a complex whole. The body is composed of systems divided into organs assembled from tissues built out of cells. Some kinds of tissues, like the epithelium, are used, with modifications, in many organs. Some organs, like the blood and the skin, interact with the rest of the body across a widespread, convoluted interface, and cannot be encircled by a dotted line. Sometimes it is unclear where one organ leaves off and another begins, or how big a chunk of the body we want to call an organ. Read more at location 643
Our physical organs owe their complex design to the information in the human genome, and so, I believe, do our mental organs. We do not learn to have a pancreas, and we do not learn to have a visual system, language acquisition, common sense, or feelings of love, friendship, and fairness. No single discovery proves the claim (just as no single discovery proves that the pancreas is innately structured), but many lines of evidence converge on it. The one that most impresses me is the Robot Challenge. Read more at location 652
I predict that no one will ever build a humanlike robot—and I mean a really humanlike robot—unless they pack it with computational systems tailored to different problems. Throughout the book we will run into other lines of evidence that our mental organs owe their basic design to our genetic program. I have already mentioned that much of the fine structure of our personality and intelligence is shared by identical twins reared apart and hence charted by the genes. Infants and young children, when tested with ingenious methods, show a precocious grasp of the fundamental categories of the physical and social world, and sometimes command information that was never presented to them. Read more at location 660
Framing the issue in such a way that innate structure and learning are pitted against each other, either as alternatives or, almost as bad, as complementary ingredients or interacting forces, is a colossal mistake. It’s not that the claim that there is an interaction between innate structure and learning (or between heredity and environment, nature and nurture, biology and culture) is literally wrong. Rather, it falls into the category of ideas that are so bad they are not even wrong. Read more at location 669
The idea that heredity and environment interact is not always meaningless, but I think it confuses two issues: what all minds have in common, and how minds can differ. Read more at location 701
Complex mental organs, like complex physical organs, surely are built by complex genetic recipes, with many genes cooperating in as yet unfathomable ways. Read more at location 725
The brain and all the other organs differentiate in embryonic development from a ball of identical cells. Every part of the body, from the toenails to the cerebral cortex, takes on its particular shape and substance when its cells respond to some kind of information in its neighborhood that unlocks a different part of the genetic program. The information may come from the taste of the chemical soup that a cell finds itself in, from the shapes of the molecular locks and keys that the cell engages, from mechanical tugs and shoves from neighboring cells, and other cues still poorly understood. The families of neurons that will form the different mental organs, all descendants of a homogeneous stretch of embryonic tissue, must be designed to be opportunistic as the brain assembles itself, seizing any available information to differentiate from one another. Read more at location 730
Our organs of computation are a product of natural selection. The biologist Richard Dawkins called natural selection the Blind Watchmaker; in the case of the mind, we can call it the Blind Programmer. Our mental programs work as well as they do because they were shaped by selection to allow our ancestors to master rocks, tools, plants, animals, and each other, ultimately in the service of survival and reproduction. Natural selection is not the only cause of evolutionary change. Organisms also change over the eons because of statistical accidents in who lives and who dies, environmental catastrophes that wipe out whole families of creatures, and the unavoidable by-products of changes that are the product of selection. But natural selection is the only evolutionary force that acts like an engineer, “designing” organs that accomplish improbable but adaptive outcomes (a point that has been made forcefully by the biologist George Williams and by Dawkins). Read more at location 751
the old joke about sadomasochism (Masochist: “Hit me!” Sadist: “No!”). Read more at location 791
The logic of reverse-engineering has guided researchers in visual perception for over a century, and that may be why we understand vision better than we understand any other part of the mind. There is no reason that reverse-engineering guided by evolutionary theory should not bring insight about the rest of the mind. Read more at location 803
First, selection operates over thousands of generations. For ninety-nine percent of human existence, people lived as foragers in small nomadic bands. Our brains are adapted to that long-vanished way of life, not to brand-new agricultural and industrial civilizations. Read more at location 862
Second, natural selection is not a puppetmaster that pulls the strings of behavior directly. It acts by designing the generator of behavior: the package of information-processing and goal-pursuing mechanisms called the mind. Read more at location 870
Behavior itself did not evolve; what evolved was the mind. Read more at location 878
**** The ultimate goal that the mind was designed to attain is maximizing the number of copies of the genes that created it. Natural selection cares only about the long-term fate of entities that replicate, that is, entities that retain a stable identity across many generations of copying. It predicts only that replicators whose effects tend to enhance the probability of their own replication come to predominate. Read more at location 887
Though there are some holdouts (such as Gould himself), the gene’s-eye view predominates in evolutionary biology and has been a stunning success. It has asked, and is finding answers to, the deepest questions about life, such as how life arose, why there are cells, why there are bodies, why there is sex, how the genome is structured, why animals interact socially, and why there is communication. It is as indispensable to researchers in animal behavior as Newton’s laws are to mechanical engineers. But almost everyone misunderstands the theory. Contrary to popular belief, the gene-centered theory of evolution does not imply that the point of all human striving is to spread our genes. Read more at location 896
**** Dawkins explained the theory in a book called The Selfish Gene, and the metaphor was chosen carefully. People don’t selfishly spread their genes; genes selfishly spread themselves. They do it by the way they build our brains. By making us enjoy life, health, sex, friends, and children, the genes buy a lottery ticket for representation in the next generation, with odds that were favorable in the environment in which we evolved. Our goals are subgoals of the ultimate goal of the genes, replicating themselves. But the two are different. As far as we are concerned, our goals, conscious or unconscious, are not about genes at all, but about health and lovers and children and friends. Read more at location 903
PSYCHOLOGICAL CORRECTNESS
The evolutionary psychology of this book is a departure from the dominant view of the human mind in our intellectual tradition, which Tooby and Cosmides have dubbed the Standard Social Science Model (SSSM). The SSSM proposes a fundamental division between biology and culture. Biology endows humans with the five senses, a few drives like hunger and fear, and a general capacity to learn. But biological evolution, according to the SSSM, has been superseded by cultural evolution. Culture is an autonomous entity that carries out a desire to perpetuate itself by setting up expectations and assigning roles, which can vary arbitrarily from society to society. Even the reformers of the SSSM have accepted its framing of the issues. Biology is “just as important as” culture, say the reformers; biology imposes “constraints” on behavior, and all behavior is a mixture of the two. The SSSM not only has become an intellectual orthodoxy but has acquired a moral authority. Read more at location 918
****** A denial of human nature, no less than an emphasis on it, can be warped to serve harmful ends. We should expose whatever ends are harmful and whatever ideas are false, and not confuse the two. Read more at location 1002
So what about the three supposed implications of an innate human nature? The first “implication”—that an innate human nature implies innate human differences—is no implication at all. The mental machinery I argue for is installed in every neurologically normal human being. The differences among people may have nothing to do with the design of that machinery. They could very well come from random variations in the assembly process or from different life histories. Even if the differences were innate, they could be quantitative variations and minor quirks in equipment present in all of us (how fast a module works, which module prevails in a competition inside the head) and are not necessarily any more pernicious than the kinds of innate differences allowed in the Standard Social Science Model (a faster general-purpose learning process, a stronger sex drive). Read more at location 1005
The fallacy of the second supposed implication of a human nature—that if our ignoble motives are innate, they can’t be so bad after all—is so obvious it has been given a name: the naturalistic fallacy, that what happens in nature is right. Read more at location 1039
Any cause of behavior, not just the genes, raises the question of free will and responsibility. The difference between explaining behavior and excusing it is an ancient theme of moral reasoning, captured in the saw “To understand is not to forgive.” In this scientific age, “to understand” means to try to explain behavior as a complex interaction among (1) the genes, (2) the anatomy of the brain, (3) its biochemical state, (4) the person’s family upbringing, (5) the way society has treated him or her, and (6) the stimuli that impinge upon the person. Sure enough, every one of these factors, not just the stars or the genes, has been inappropriately invoked as the source of our faults and a claim that we are not masters of our fates. Read more at location 1088
Without a clearer moral philosophy, any cause of behavior could be taken to undermine free will and hence moral responsibility. Science is guaranteed to appear to eat away at the will, regardless of what it finds, because the scientific mode of explanation cannot accommodate the mysterious notion of uncaused causation that underlies the will. Read more at location 1121
Either we dispense with all morality as an unscientific superstition, or we find a way to reconcile causation (genetic or otherwise) with responsibility and free will. I doubt that our puzzlement will ever be completely assuaged, but we can surely reconcile them in part. Like many philosophers, I believe that science and ethics are two self-contained systems played out among the same entities in the world, just as poker and bridge are different games played with the same fifty-two-card deck. The science game treats people as material objects, and its rules are the physical processes that cause behavior through natural selection and neurophysiology. The ethics game treats people as equivalent, sentient, rational, free-willed agents, and its rules are the calculus that assigns moral value to behavior through the behavior’s inherent nature or its consequences. Free will is an idealization of human beings that makes the ethics game playable. Read more at location 1130
ethical theory requires idealizations like free, sentient, rational, equivalent agents whose behavior is uncaused, and its conclusions can be sound and useful even though the world, as seen by science, does not really have uncaused events. As long as there is no outright coercion or gross malfunction of reasoning, the world is close enough to the idealization of free will that moral theory can meaningfully be applied to it. Science and morality are separate spheres of reasoning. Only by recognizing them as separate can we have them both. Read more at location 1140
A human being is simultaneously a machine and a sentient free agent, depending on the purpose of the discussion, just as he is also a taxpayer, an insurance salesman, a dental patient, and two hundred pounds of ballast on a commuter airplane, depending on the purpose of the discussion. The mechanistic stance allows us to understand what makes us tick and how we fit into the physical universe. When those discussions wind down for the day, we go back to talking about each other as free and dignified human beings. Read more at location 1162
2 THINKING MACHINES
Intelligence, then, is the ability to attain goals in the face of obstacles by means of decisions based on rational (truth-obeying) rules. The computer scientists Allen Newell and Herbert Simon fleshed this idea out further by noting that intelligence consists of specifying a goal, assessing the current situation to see how it differs from the goal, and applying a set of operations that reduce the difference. Read more at location 1256
We have desires, and we pursue them using beliefs, which, when all goes well, are at least approximately or probabilistically true. Read more at location 1259
As the famous behaviorist B. F. Skinner said, “The question is not whether machines think, but whether men do.” Of course, men and women do think; the stimulus-response theory turned out to be wrong. Read more at location 1265
The chasm between what can be measured by a physicist and what can cause behavior is the reason we must credit people with beliefs and desires. In our daily lives we all predict and explain other people’s behavior from what we think they know and what we think they want. Beliefs and desires are the explanatory tools of our own intuitive psychology, and intuitive psychology is still the most useful and complete science of behavior there is. Read more at location 1285
No, intelligence does not come from a special kind of spirit or matter or energy but from a different commodity, information. Information is a correlation between two things that is produced by a lawful process (as opposed to coming about by sheer chance). Read more at location 1332
effects. What is special is information processing. We can regard a piece of matter that carries information about some state of affairs as a symbol; it can “stand for” that state of affairs. Read more at location 1338
Alan Turing. He designed a hypothetical machine whose input symbols and output symbols could correspond, depending on the details of the machine, to any one of a vast number of sensible interpretations. The machine consists of a tape divided into squares, a read-write head that can print or read a symbol on a square and move the tape in either direction, a pointer that can point to a fixed number of tickmarks on the machine, and a set of mechanical reflexes. Each reflex is triggered by the symbol being read and the current position of the pointer, and it prints a symbol on the tape, moves the tape, and/or shifts the pointer. The machine is allowed as much tape as it needs. This design is called a Turing machine. Read more at location 1366
What does this mean? It means that to the extent that the world obeys mathematical equations that can be solved step by step, a machine can be built that simulates the world and makes predictions about it. To the extent that rational thought corresponds to the rules of logic, a machine can be built that carries out rational thought. To the extent that a language can be captured by a set of grammatical rules, a machine can be built that produces grammatical sentences. To the extent that thought consists of applying any set of well-specified rules, a machine can be built that, in some sense, thinks. Turing showed that rational machines—machines that use the physical properties of symbols to crank out new symbols that make some kind of sense—are buildable, indeed, easily buildable. Read more at location 1379
There are no Turing machines in use anywhere, let alone in our heads. They are useless in practice: too clumsy, too hard to program, too big, and too slow. But it does not matter. Turing merely wanted to prove that some arrangement of gadgets could function as an intelligent symbol-processor. Not long after his discovery, more practical symbol-processors were designed, some of which became IBM and Univac mainframes and, later, Macintoshes and PCs. But all of them were equivalent to Turing’s universal machine. Read more at location 1390
According to the computational theory of mind, that information is embodied in symbols: a collection of physical marks that correlate with the state of the world as it is captured in the propositions. These symbols cannot be English words and sentences, notwithstanding the popular misconception that we think in our mother tongue. As I showed in The Language Instinct, sentences in a spoken language like English or Japanese are designed for vocal communication between impatient, intelligent social beings. They achieve brevity by leaving out any information that the listener can mentally fill in from the context. In contrast, the “language of thought” in which knowledge is couched can leave nothing to the imagination, because it is the imagination. Read more at location 1417
the statements in a knowledge system are not sentences in English but rather inscriptions in a richer language of thought, “mentalese.” Read more at location 1428
(Note: This is exactly as Godel did to principia Mathematica) To hammer home my explanation of the trick—that symbols both stand for some concept and mechanically cause things to happen—I will step through the activity of our production system and describe everything twice: conceptually, in terms of the content of the problem and the logic that solves it, and mechanically, in terms of the brute sensing and marking motions of the system. The system is intelligent because the two correspond exactly, idea-for-mark, logical-step-for-motion. Read more at location 1442
The computational theory thus embraces an alternative kind of computer with many elements that are active to a degree corresponding to the probability that some statement is true or false, and in which the activity levels change smoothly to register new and roughly accurate probabilities. Read more at location 1845
computation has finally demystified mentalistic terms. Beliefs are inscriptions in memory, desires are goal inscriptions, thinking is computation, perceptions are inscriptions triggered by sensors, trying is executing operations triggered by a goal. Read more at location 1877
a representation is a set of symbols corresponding to aspects of the world, and each homunculus is required only to react in a few circumscribed ways to some of the symbols, a feat far simpler than what the system as a whole does. The intelligence of the system emerges from the activities of the not-so-intelligent mechanical demons inside it. Read more at location 1891
Suppose that someday we discovered that cats are not animals after all, but lifelike robots controlled from Mars. Any inference rule that computed “If it’s a cat, then it must be an animal” would be inoperative. The inferential role of our mental symbol cat would have changed almost beyond recognition. But surely the meaning of cat would be unchanged: you’d still be thinking “cat” when Felix the Robot slunk by. Score two points for the causal theory. Read more at location 1931
Another sign that the computational theory of mind is on the right track is the existence of artificial intelligence: computers that perform humanlike intellectual tasks. Read more at location 1947
The debate seems to come right out of the pages of Christopher Cerf and Victor Navasky’s The Experts Speak: Well-informed people know it is impossible to transmit the voice over wires and that were it possible to do so, the thing would be of no practical value. —Editorial, The Boston Post, 1865 Fifty years hence . . . [w]e shall escape the absurdity of growing a whole chicken in order to eat the breast or wing, by growing these parts separately under a suitable medium. —Winston Churchill, 1932 Heavier-than-air flying machines are impossible. —Lord Kelvin, pioneer in thermodynamics and electricity, 1895 [By 1965] the deluxe open-road car will probably be 20 feet long, powered by a gas turbine engine, little brother of the jet engine. —Leo Cherne, editor-publisher of The Research Institute of America, 1955 Man will never reach the moon, regardless of all future scientific advances. —Lee Deforest, inventor of the vacuum tube, 1957 Nuclear powered vacuum cleaners will probably be a reality within 10 years. —Alex Lewyt, manufacturer of vacuum cleaners, 1955 Read more at location 1958
Scientific understanding and technological achievement are only loosely connected. For some time we have understood much about the hip and the heart, but artificial hips are commonplace while artificial hearts are elusive. The pitfalls between theory and application must be kept in mind when we look to artificial intelligence for clues about computers and minds. The proper label for the study of the mind informed by computers is not Artificial Intelligence but Natural Computation. Read more at location 1982
No corner of the field is untouched by the idea that information processing is the fundamental activity of the brain. Information processing is what makes neuroscientists more interested in neurons than in glial cells, even though the glia take up more room in the brain. The axon (the long output fiber) of a neuron is designed, down to the molecule, to propagate information with high fidelity across long separations, and when its electrical signal is transduced to a chemical one at the synapse (the junction between neurons), the physical format of the information changes while the information itself remains the same. And as we shall see, the tree of dendrites (input fibers) on each neuron appears to perform the basic logical and statistical operations underlying computation. Read more at location 1987
The blossoming came from a central agenda for psychology set by the computational theory: discovering the form of mental representations (the symbol inscriptions used by the mind) and the processes (the demons) that access them. Read more at location 2009
Research in cognitive psychology has tried to triangulate on the mind’s internal representations by measuring people’s reports, reaction times, and errors as they remember, solve problems, recognize objects, and generalize from experience. The way people generalize is perhaps the most telltale sign that the mind uses mental representations, and lots of them. Read more at location 2034
Your knowledge about the word elk could not have been connected directly to the physical shapes of printed letters. If it had, then when new letters were introduced, your knowledge would have no connection to them and would be unavailable until you learned the connections anew. In reality, your knowledge must have been connected to a node, a number, an address in memory, or an entry in a mental dictionary representing the abstract word elk, and that entry must be neutral with respect to how it is printed or pronounced. When you learned the new typeface, you created a new visual trigger for the letters of the alphabet, which in turn triggered the old elk entry, and everything hooked up to the entry was instantly available, without your having to reconnect, piece by piece, everything you know about elks to the new way of printing elk. This is how we know that your mind contains mental representations specific to abstract entries for words, not just the shapes of the words when they are printed. These leaps, and the inventory of internal representations they hint at, are the hallmark of human cognition. If you learned that wapiti was another name for an elk, you could take all the facts connected to the word elk and instantly transfer them to wapiti, without having to solder new connections to the word one at a time. Read more at location 2041
**** (Note: **** vastness of thought expressible as language) The combinatorics of mentalese, and of other representations composed of parts, explain the inexhaustible repertoire of human thought and action. A few elements and a few rules that combine them can generate an unfathomably vast number of different representations, because the number of possible representations grows exponentially with their size. Language is an obvious example. Say you have ten choices for the word to begin a sentence, ten choices for the second word (yielding a hundred two-word beginnings), ten choices for the third word (yielding a thousand three-word beginnings), and so on. (Ten is in fact the approximate geometric mean of the number of word choices available at each point in assembling a grammatical and sensible sentence.) A little arithmetic shows that the number of sentences of twenty words or less (not an unusual length) is about 1020: a one followed by twenty zeros, or a hundred million trillion, or a hundred times the number of seconds since the birth of the universe. I bring up the example to impress you not with the vastness of language but with the vastness of thought. Read more at location 2073
the human brain uses at least four major formats of representation. One format is the visual image, which is like a template in a two-dimensional, picturelike mosaic. (Visual images are discussed in Chapter 4.) Another is a phonological representation, a stretch of syllables that we play in our minds like a tape loop, planning out the mouth movements and imagining what the syllables sound like. This stringlike representation is an important component of our short-term memory, as when we look up a phone number and silently repeat it to ourselves just long enough to dial the number. Phonological short-term memory lasts between one and five seconds and can hold from four to seven “chunks.” (Short-term memory is measured in chunks rather than sounds because each item can be a label that points to a much bigger information structure in long-term memory, such as the content of a phrase or sentence.) A third format is the grammatical representation: nouns and verbs, phrases and clauses, stems and roots, phonemes and syllables, all arranged into hierarchical trees. In The Language Instinct I explained how these representations determine what goes into a sentence and how people communicate and play with language. The fourth format is mentalese, the language of thought in which our conceptual knowledge is couched. When you put down a book, you forget almost everything about the wording and typeface of the sentences and where they sat on the page. What you take away is their content or gist. (In memory tests, people confidently “recognize” sentences they never saw if they are paraphrases of the sentences they did see.) Mentalese is the medium in which content or gist is captured; Read more at location 2107
The modular organization of mental software, with its packaging of knowledge into separate formats, is a nice example of how evolution and engineering converge on similar solutions. Read more at location 2129
our modular, multiformat minds: Modularize. Use subroutines. Each module should do one thing well. Make sure every module hides something. Localize input and output in subroutines. A second principle is captured in the maxim Choose the data representation that makes the program simple. Read more at location 2139
if you like the intellectual stratosphere in which “complex systems” of all kinds are lumped together, you might be receptive to Herbert Simon’s argument that modular design in computers and minds is a special case of modular, hierarchical design in all complex systems. Bodies contain tissues made of cells containing organelles; armed forces comprise armies which contain divisions broken into battalions and eventually platoons; books contain chapters divided into sections, subsections, paragraphs, and sentences; empires are assembled out of countries, provinces, and territories. These “nearly decomposable” systems are defined by rich interactions among the elements belonging to the same component and few interactions among elements belonging to different components. Complex systems are hierarchies of modules because only elements that hang together in modules can remain stable long enough to be assembled into larger and larger modules. Read more at location 2152
**** We don’t need spirits or occult forces to explain intelligence. Nor, in an effort to look scientific, do we have to ignore the evidence of our own eyes and claim that human beings are bundles of conditioned associations, puppets of the genes, or followers of brutish instincts. We can have both the agility and discernment of human thought and a mechanistic framework in which to explain it. Read more at location 2173
The first attack comes from the philosopher John Searle. Searle believes that he refuted the computational theory of mind in 1980 with a thought experiment he adapted from another philosopher, Ned Block (who, ironically, is a major proponent of the computational theory). Searle’s version has become famous as the Chinese Room.
...Searle’s tactic is to appeal over and over to our common sense.
...But the history of science has not been kind to the simple intuitions of common sense, to put it mildly. The philosophers Patricia and Paul Churchland ask us to imagine how Searle’s argument might have been used against Maxwell’s theory that light consists of electromagnetic waves. A guy holds a magnet in his hand and waves it up and down. The guy is creating electromagnetic radiation, but no light comes out; therefore, light is not an electromagnetic wave.
...Similarly, Searle has slowed down the mental computation to a range in which we humans no longer think of it as understanding (since understanding is ordinarily much faster). By trusting our intuitions in the thought experiment, we falsely conclude that rapid computation cannot be understanding, either. Read more at location 2214
The other attack on the computational theory of mind comes from the mathematical physicist Roger Penrose, in a best-seller called The Emperor’s New Mind (how’s that for an in-your-face impugnment!). Penrose draws not on common sense but on abstruse issues in logic and physics. He argues that Gödel’s famous theorem implies that mathematicians—and, by extension, all humans—are not computer programs. Read more at location 2270
Gödel proved that any formal system (such as a computer program or a set of axioms and rules of inference in mathematics) that is even moderately powerful (powerful enough to state the truths of arithmetic) and consistent (it does not generate contradictory statements) can generate statements that are true but that the system cannot prove to be true. Since we human mathematicians can just see that those statements are true, we are not formal systems like computers. Penrose believes that the mathematician’s ability comes from an aspect of consciousness that cannot be explained as computation. Read more at location 2273
Penrose’s mathematical argument has been dismissed as fallacious by logicians, and his other claims have been reviewed unkindly by experts in the relevant disciplines. One big problem is that the gifts Penrose attributes to his idealized mathematician are not possessed by real-life mathematicians, such as the certainty that the system of rules being relied on is consistent. Another is that quantum effects almost surely cancel out in nervous tissue. A third is that microtubules are ubiquitous among cells and appear to play no role in how the brain achieves intelligence. A fourth is that there is not even a hint as to how consciousness might arise from quantum mechanics.
....The computational theory fits so well into our understanding of the world that, in trying to overthrow it, Penrose had to reject most of contemporary neuroscience, evolutionary biology, and physics!
REPLACED BY A MACHINE
no inference system follows explicit rules all the way down. At some point the system must, as Jerry Rubin (and later the Nike Corporation) said, just do it. That is, the rule must simply be executed by the reflexive, brute-force operation of the system, no more questions asked. At that point the system, if implemented as a machine, would not be following rules but obeying the laws of physics. Similarly, if representations are read and written by demons (rules for replacing symbols with symbols), and the demons have smaller (and stupider) demons inside them, eventually you have to call Ghost-busters and replace the smallest and stupidest demons with machines—in the case of people and animals, machines built from neurons: neural networks. Read more at location 2325
Neurons, in effect, add up a set of quantities, compare the sum to a threshold, and indicate whether the threshold is exceeded. That is a conceptual description of what they do; the corresponding physical description is that a firing neuron is active to varying degrees, and its activity level is influenced by the activity levels of the incoming axons from other neurons attached at synapses to the neuron’s dendrites (input structures). A synapse has a strength ranging from positive (excitatory) through zero (no effect) to negative (inhibitory). The activation level of each incoming axon is multiplied by the strength of the synapse. The neuron sums these incoming levels; if the total exceeds a threshold, the neuron will become more active, sending a signal in turn to any neuron connected to it. Read more at location 2334
psychologists and artificial intelligence researchers have been using everything-connected-to-everything networks to model many examples of simple pattern recognition. Read more at location 2399
We do not need predefined retrieval tags for items in memory; almost any aspect of an object can bring the entire object to mind. For example, we can recall “vegetable” upon thinking about things that are green and leafy or green and crunchy or leafy and crunchy.
...“Pritn” would activate the more familiar pattern “print”; “gub” would be warped to “gun,” “HELF” to “HELP.” Similarly, a computer with a single bad bit on its disk, a smidgen of corrosion in one of its sockets, or a brief dip in its supply of power can lock up and crash. But a human being who is tired, hung over, or brain-damaged does not lock up and crash; usually he or she is slower and less accurate but can muster an intelligible response. A third advantage is that auto-associators can do a simple version of the kind of computation called constraint satisfaction. Read more at location 2427
These problems abound in perception, language, and common-sense reasoning. Am I looking at a fold or at an edge? Am I hearing the vowel [I] (as in pin) or the vowel [ε] (as in pen) with a southern accent? Was I the victim of an act of malice or an act of stupidity? These ambiguities can sometimes be resolved by choosing the interpretation that is consistent with the greatest number of interpretations of other ambiguous events, if they could all be resolved at once. Read more at location 2435
Conceptually speaking, a pattern associator captures the idea that if two objects are similar in some ways, they are probably similar in other ways. Mechanically speaking, similar objects are represented by some of the very same units, so any piece of information connected to the units for one object will ipso facto be connected to many of the units for the other. Moreover, classes of different degrees of inclusiveness are superimposed in the same network, because any subset of the units implicitly defines a class. The fewer the units, the larger the class. Read more at location 2473
We have reached what many psychologists treat as the height of the neural-network modeler’s art. In a way, we have come full circle, because a hidden-layer network is like the arbitrary road map of logic gates that McCulloch and Pitts proposed as their neuro-logical computer. Conceptually speaking, a hidden-layer network is a way to compose a set of propositions, which can be true or false, into a complicated logical function held together by ands, ors, and nots—though with two twists. One is that the values can be continuous rather than on or off, and hence they can represent the degree of truth or the probability of truth of some statement rather than dealing only with statements that are absolutely true or absolutely false. The second twist is that the network can, in many cases, be trained to take on the right weights by being fed with inputs and their correct outputs. On top of these twists there is an attitude: to take inspiration from the many connections among neurons in the brain and feel no guilt about going crazy with the number of gates and connections put into a network. That ethic allows one to design networks that compute many probabilities and hence that exploit the statistical redundancies among the features of the world. And that, in turn, allows neural networks to generalize from one input to similar inputs without further training, as long as the problem is one in which similar inputs yield similar outputs. Those are a few ideas on how to implement our smallest demons and their bulletin boards as vaguely neural machines. The ideas serve as a bridge, rickety for now, along the path of explanation that begins in the conceptual realm (Grandma’s intuitive psychology and the varieties of knowledge, logic, and probability theory that underlie it), continues on to rules and representations (demons and symbols), and eventually arrives at real neurons. Read more at location 2526
CONNECTOPLASM
Where do the rules and representations in mentalese leave off and the neural networks begin? Most cognitive scientists agree on the extremes. At the highest levels of cognition, where we consciously plod through steps and invoke rules we learned in school or discovered ourselves, the mind is something like a production system, with symbolic inscriptions in memory and demons that carry out procedures. At a lower level, the inscriptions and rules are implemented in something like neural networks, which respond to familiar patterns and associate them with other patterns. But the boundary is in dispute. Read more at location 2544
A school called connectionism, led by the psychologists David Rumelhart and James McClelland, argues that simple networks by themselves can account for most of human intelligence. In its extreme form, connectionism says that the mind is one big hidden-layer back-propagation network, Read more at location 2552
The other view—which I favor—is that those neural networks alone cannot do the job. It is the structuring of networks into programs for manipulating symbols that explains much of human intelligence. In particular, symbol manipulation underlies human language and the parts of reasoning that interact with it. That’s not all of cognition, but it’s a lot of it; it’s everything we can talk about to ourselves and others. In my day job as a psycholinguist I have gathered evidence that even the simplest of talents that go into speaking English, such as forming the past tense of verbs (walk into walked, come into came), is too computationally sophisticated to be handled in a single neural network. Read more at location 2559
Raw connectoplasm has trouble with five feats of everyday thinking. The feats appear to be subtle at first, and were not even suspected of existing until logicians, linguists, and computer scientists began to put the meanings of sentences under a microscope. But the feats give human thought its distinctive precision and power and are, I think, an important part of the answer to the question, How does the mind work? One feat is entertaining the concept of an individual.
...Your knowledge of the properties of two objects can be identical and still you can know they are distinct. Read more at location 2621
when we reverse-engineer the sense of justice and the emotion of romantic love, we will see that the mental act of registering individual persons is at the heart of their design. Read more at location 2660
A second problem for associationism is called compositionality: the ability of a representation to be built out of parts and to have a meaning that comes from the meanings of the parts and from the way they are combined. Compositionality is the quintessential property of all human languages. Read more at location 2674
the combinatorics of thought can overwhelm the number of neurons in the brain. A hundred million trillion sentence meanings cannot be squeezed into a brain with a hundred billion neurons if each meaning must have its own neuron. Read more at location 2698
the human mind must represent propositions with something more sophisticated than a set of concept-to-concept or concept-to-role associations. The mind needs a representation for the proposition itself. Read more at location 2740
The bank of “proposition” units light up in arbitrary patterns, a bit like serial numbers, that label complete thoughts. It acts as a superstructure keeping the concepts in each proposition in their proper slots. Note how closely the architecture of the network implements standard, language-like mentalese! There have been other suggestions for compositional networks that aren’t such obvious mimics, but they all have to have some specially engineered parts that separate concepts from their roles and that bind each concept to its role properly. The ingredients of logic such as predicate, argument, and proposition, and the computational machinery to handle them, have to be snuck back in to get a model to do mindlike things; association-stuff by itself is not enough. Read more at location 2745
Another mental talent that you may never have realized you have is called quantification, or variable-binding. It arises from a combination of the first problem, individuals, with the second, compositionality. Our compositional thoughts are, after all, often about individuals, and it makes a difference how those individuals are linked to the various parts of the thought. Read more at location 2752
David Sherry and Dan Schacter have pushed this line of reasoning farther. They note that the different engineering demands on a memory system are often at cross-purposes. Natural selection, they argue, responded by giving organisms specialized memory systems. Each has a computational structure optimized for the demands of one of the tasks the mind of the animal must fulfill. For example, birds that cache seeds to retrieve in leaner times have evolved a capacious memory for the hiding places (ten thousand places, in the case of the Clark’s Nutcracker). Read more at location 2787
**** (Note: memory) We humans place two very different demands on our memory system at the same time. We have to remember individual episodes of who did what to whom, when, where, and why, and that requires stamping each episode with a time, a date, and a serial number. But we also must extract generic knowledge about how people work and how the world works. Sherry and Schacter suggest that nature gave us one memory system for each requirement: an “episodic” or autobiographical memory, and a “semantic” or generic-knowledge memory, following a distinction first made by the psychologist Endel Tulving. Read more at location 2793
The trick that multiplies human thoughts into truly astronomical numbers is Read more at location 2798
**** (Note: self referencing, recursive) a kind of mental fecundity called recursion. A fixed set of units for each role is not enough. We humans can take an entire proposition and give it a role in some larger proposition. Then we can take the larger proposition and embed it in a still-larger one, creating a hierarchical tree structure of propositions inside propositions. Read more at location 2799
Each simple structure (for a person, an action, a proposition, and so on) is represented in long-term memory once, and a processor shuttles its attention from one structure to another, storing the itinerary of visits in short-term memory to thread the proposition together. This dynamic processor, called a recursive transition network, is especially plausible for sentence understanding, because we hear and read words one at a time rather than inhaling an entire sentence at once. We also seem to chew our complex thoughts piece by piece rather swallowing or regurgitating them whole, and that suggests that the mind is equipped with a recursive proposition-cruncher for thoughts, not just for sentences. Read more at location 2813
Neural networks easily implement a fuzzy logic in which everything is a kind-of something to some degree. To be sure, many common-sense concepts really are fuzzy at their edges and have no clear definitions. The philosopher Ludwig Wittgenstein offered the example of “a game,” whose exemplars (jigsaw puzzles, roller derby, curling, Dungeons and Dragons, cockfighting, and so on) have nothing in common, Read more at location 2825
Experiments in cognitive psychology have shown that people are bigots about birds, other animals, vegetables, and tools. People share a stereotype, project it to all the members of a category, recognize the stereotype more quickly than the nonconformists, and even claim to have seen the stereotype when all they really saw were examples similar to it. These responses can be predicted by tallying up the properties that a member shares with other members of the category: the more birdy properties, the better the bird. Read more at location 2835
**** (Note: fuzzy versus crisp) In fact, fuzzy and crisp versions of the same category can live side by side in a single head. The psychologists Sharon Armstrong, Henry Gleitman, and Lila Gleitman mischievously gave the standard tests for fuzzy categories to university students but asked them about knife-edged categories like “odd number” and “female.” The subjects happily agreed to daft statements such as that 13 is a better example of an odd number than 23 is, and that a mother is a better example of a female than a comedienne is. Moments later the subjects also claimed that a number either is odd or is even, and that a person either is female or is male, with no gray areas. People think in two modes. Read more at location 2850
neural networks don’t perform miracles, only some logical and statistical operations. The choices of an input representation, of the number of networks, of the wiring diagram chosen for each one, and of the data pathways and control structures that interconnect them explain more about what makes a system smart than do the generic powers of the component connectoplasm. But my main intent is not to show what certain kinds of models cannot do but what the mind can do. The point of this chapter is to give you a feel for the stuff our minds are made of. Thoughts and thinking are no longer ghostly enigmas but mechanical processes that can be studied, and the strengths and weaknesses of different theories can be examined and debated. I find it particularly illuminating to see the shortcomings of the venerable doctrine of the association of ideas, because they highlight the precision, subtlety, complexity, and open-endedness of our everyday thinking. Read more at location 2935
ALADDIN’S LAMP What about consciousness? What makes us actually suffer the pain of a toothache or see the blue of the sky as blue? The computational theory of mind, even with complete neural underpinnings, offers no clear answer. The symbol blue is inscribed, goal states change, some neurons fire; so what? Consciousness has struck many thinkers as not just a problem but almost a miracle: Read more at location 2946
How it is that anything so remarkable as a state of consciousness comes about as a result of irritating nervous tissue, is just as unaccountable as the appearance of the Djin, when Aladdin rubbed his lamp. —Thomas Huxley Read more at location 2955
Consciousness presents us with puzzle after puzzle. How can a neural event cause consciousness to happen? What good is consciousness? That is, what does the raw sensation of redness add to the train of billiard-ball events taking place in our neural computers? Read more at location 2962
Gould has denied consciousness to all nonhuman animals; other scientists grant it to some animals but not all. Many test for consciousness by seeing whether an animal recognizes that the image in a mirror is itself and not another animal. By this standard, monkeys, young chimpanzees, old chimpanzees, elephants, and human toddlers are unconscious. The only conscious animals are gorillas, orangutans, chimpanzees in their prime, and, according to Skinner and his student Robert Epstein, properly trained pigeons. Others are even more restrictive than Gould: not even all people are conscious. Julian Jaynes claimed that consciousness is a recent invention. Read more at location 2976
Verbal humor sets readers up with one meaning of an ambiguous word and surprises them with another. Theoreticians also trade on the ambiguity of the word consciousness, not as a joke but as a bait-and-switch: the reader is led to expect a theory for one sense of the word, the hardest to explain, and is given a theory for another sense, the easiest to explain.
...Sometimes “consciousness” is just used as a lofty synonym for “intelligence.”
...there are three more-specialized meanings, nicely distinguished by the linguist Ray Jackendoff and the philosopher Ned Block. Read more at location 3000
One is self-knowledge. Among the various people and objects that an intelligent being can have information about is the being itself.
...Self-knowledge, including the ability to use a mirror, is no more mysterious than any other topic in perception and memory. If I have a mental database for people, what’s to prevent it from containing an entry for myself? Read more at location 3007
A second sense is access to information. I ask, “A penny for your thoughts?” You reply by telling me the content of your daydreams, your plans for the day, your aches and itches, and the colors, shapes, and sounds in front of you.
...the mass of information processing in the nervous system falls into two pools. One pool, which includes the products of vision and the contents of short-term memory, can be accessed by the systems underlying verbal reports, rational thought, and deliberate decision making. The other pool, which includes autonomic (gut-level) responses, the internal calculations behind vision, language, and movement, and repressed desires or memories (if there are any), cannot be accessed by those systems. Sometimes information can pass from the first pool to the second or vice versa. Read more at location 3019
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Finally, we come to the most interesting sense of all, sentience: subjective experience, phenomenal awareness, raw feels, first-person present tense, “what it is like” to be or do something, if you have to ask you’ll never know. Woody Read more at location 3033
The engineering specs of information access, and thus the selection pressures that probably gave rise to it, are also becoming clearer. The general principle is that any information processor must be given limited access to information because information has costs as well as benefits. One cost is space: the hardware to hold the information. Read more at location 3063
**** (Note: vastness of thoughtscape) Simple calculations show that the number of humanly graspable sentences, sentence meanings, chess games, melodies, seeable objects, and so on can exceed the number of particles in the universe. For example, there are thirty to thirty-five possible moves at each point in a chess game, each of which can be followed by thirty to thirty-five responses, defining about a thousand complete turns. A typical chess game lasts forty turns, yielding 10120 different chess games. There are about 1070 particles in the visible universe. Read more at location 3070
A second cost of information is time. Just as one couldn’t store all the chess games in a brain less than the size of the universe, one can’t mentally play out all the chess games in a lifetime less than the age of the universe (1018 seconds). Solving a problem in a hundred years is, practically speaking, the same as not solving it at all. In fact, the requirements on an intelligent agent are even more stringent. Life is a series of deadlines. Perception and behavior take place in real time, such as in hunting an animal or keeping up one’s end of a conversation. And since computation itself takes time, information processing can be part of the problem rather than part of the solution. Read more at location 3078
A third cost is resources. Information processing requires energy. That is obvious to anyone who has stretched out the battery life of a laptop computer by slowing down the processor and restricting its access to information on the disk. Thinking, too, is expensive. The technique of functional imaging of brain activity (PET and MRI) depends on the fact that working brain tissue calls more blood its way and consumes more glucose. Read more at location 3084
**** Access-consciousness has four obvious features. First, we are aware, to varying degrees, of a rich field of sensation: the colors and shapes of the world in front of us, the sounds and smells we are bathed in, the pressures and aches of our skin, bone, and muscles. Second, portions of this information can fall under the spotlight of attention, get rotated into and out of short-term memory, and feed our deliberative cogitation. Third, sensations and thoughts come with an emotional flavoring: pleasant or unpleasant, interesting or repellent, exciting or soothing. Finally, an executive, the “I,” appears to make choices and pull the levers of behavior. Each of these features discards some information in the nervous system, defining the highways of access-consciousness. And each has a clear role in the adaptive organization of thought and perception to serve rational decision making and action. Read more at location 3095
Jackendoff observed that access-consciousness seems to tap the intermediate levels. People are unaware of the lowest levels of sensation. Read more at location 3106
What we “see” is a highly processed product: the surfaces of objects, their intrinsic colors and textures, and their depths, slants, and tilts. In the sound wave arriving at our ears, syllables and words are warped and smeared together, but we don’t hear that seamless acoustic ribbon; we “hear” a chain of well-demarcated words. Our immediate awareness does not exclusively tap the highest level of representation, either. The highest levels—the contents of the world, or the gist of a message—tend to stick in long-term memory days and years after an experience, but as the experience is unfolding, we are aware of the sights and sounds. Read more at location 3109
Why is visual computation divided into an unconscious parallel stage and a conscious serial stage? Conjunctions are combinatorial. It would be impossible to sprinkle conjunction detectors at every location in the visual field because there are too many kinds of conjunctions. There are a million visual locations, so the number of processors needed would be a million multiplied by the number of logically possible conjunctions: the number of colors we can discriminate times the number of contours times the number of depths times the number of directions of motion times the number of velocities, and so on, an astronomical number. Parallel, unconscious computation stops after it labels each location with a color, contour, depth, and motion; the combinations then have to be computed, consciously, at one location at a time. Read more at location 3148
There are bottlenecks constricting the flow of information from inside the person as well as from outside. When we try to retrieve a memory, the items drip into awareness one at a time, often with agonizing delays if the information is old or uncommon.
...The psychologist John Anderson has reverse-engineered human memory retrieval, and has shown that the limits of memory are not a by-product of a mushy storage medium. As programmers like to say, “It’s not a bug, it’s a feature.” In an optimally designed information-retrieval system, an item should be recovered only when the relevance of the item outweighs the cost of retrieving it. Read more at location 3170
A piece of information that has been requested many times in the past is more likely to be needed now than a piece that has been requested only rarely. A piece that has been requested recently is more likely to be needed now than a piece that has not been requested for a while. An optimal information-retrieval system should therefore be biased to fetch frequently and recently encountered items. Anderson notes that that is exactly what human memory retrieval does: we remember common and recent events better than rare and long-past events. Read more at location 3180
A third notable feature of access-consciousness is the emotional coloring of experience. We not only register events but register them as pleasurable or painful. That makes us take steps to have more of the former and less of the latter, now and in the future. Read more at location 3186
The things that become objects of desire are the kinds of things that led, on average, to enhanced odds of survival and reproduction in the environment in which we evolved: water, food, safety, sex, status, mastery over the environment, and the well-being of children, friends, and kin. Read more at location 3191
fourth feature of consciousness is the funneling of control to an executive process: something we experience as the self, the will, the “I.” Read more at location 3193
The agents of the brain might very well be organized hierarchically into nested subroutines with a set of master decision rules, a computational demon or agent or good-kind-of-homunculus, sitting at the top of the chain of command. It would not be a ghost in the machine, just another set of if-then rules or a neural network that shunts control to the loudest, fastest, or strongest agent one level down. Read more at location 3199
**** (Note: self) for many decades neurologists have known that exercising the will—forming and carrying out plans—is a job of the frontal lobes. A sad but typical example came to me from a man who called about his fifteen-year-old son, who had suffered an injury to his frontal lobes in a car accident. The boy would stay in the shower for hours at a time, unable to decide when to get out, and could not leave the house because he kept looping back to his room to check whether he had turned off the lights. Why would a society of mental agents need an executive at the top? The reason is as clear as the old Yiddish expression “You can’t dance at two weddings with only one tuches.” No matter how many agents we have in our minds, we each have exactly one body. Read more at location 3205
An example of access without sentience might be found in the strange syndrome called blindsight. When a person has a large blind spot because of damage to his visual cortex, he will adamantly deny that he can see a thing there, but when forced to guess where an object is, he performs well above chance. One interpretation is that the blindsighter has access to the objects but is not sentient of them. Read more at location 3224
**** The philosopher Georges Rey once told me that he has no sentient experiences. He lost them after a bicycle accident when he was fifteen. Since then, he insists, he has been a zombie. I assume he is speaking tongue-in-cheek, but of course I have no way of knowing, and that is his point. The qualia-debunkers do have a point. At least for now, we have no scientific purchase on the special extra ingredient that gives rise to sentience. As far as scientific explanation goes, it might as well not exist. Read more at location 3268
To reconstruct human evolution, we need physical anthropology to find the bones, archeology to understand the tools, molecular biology to date the split from chimpanzees, and paleobotany to reconstruct the environment from fossil pollen. When any part of the puzzle is blank, such as a lack of chimpanzee fossils or an uncertainty about whether the climate was wet or dry, the gap is sorely felt and everyone waits impatiently for it to be filled. But in the study of the mind, sentience floats in its own plane, high above the causal chains of psychology and neuroscience. Read more at location 3275
If you bear with me to the end of the book, you will learn my own hunch about the mystery of sentience. But the mystery remains a mystery, a topic not for science but for ethics, for late-night dorm-room bull sessions, Read more at location 3289
3 REVENGE OF THE NERDS
At a famous conference in 1961, the astronomer and SETI enthusiast Frank Drake noted that the number of extraterrestrial civilizations that might contact us can be estimated with the following formula: (1) (The number of stars in the galaxy) × (2) (The fraction of stars with planets) × (3) (The number of planets per solar system with a life-supporting environment) × (4) (The fraction of these planets on which life actually appears) × (5) (The fraction of life-bearing planets on which intelligence emerges) × (6) (The fraction of intelligent societies willing and able to communicate with other worlds) × (7) (The longevity of each technology in the communicative state). The astronomers, physicists, and engineers at the conference felt unable to estimate factor (6) without a sociologist or a historian. But they felt confident in estimating factor (5), the proportion of life-bearing planets on which intelligence emerges. They decided it was one hundred percent. Read more at location 3325
We are chauvinistic about our brains, thinking them to be the goal of evolution. And that makes no sense, for reasons articulated over the years by Stephen Jay Gould. First, natural selection does nothing even close to striving for intelligence. The process is driven by differences in the survival and reproduction rates of replicating organisms in a particular environment. Over time the organisms acquire designs that adapt them for survival and reproduction in that environment, period; nothing pulls them in any direction other than success there and then. Read more at location 3378
**** (Note: no hierarchy of life forms) is a densely branching bush, not a scale or a ladder, and living organisms are at the tips of the branches, not on lower rungs. Every organism alive today has had the same amount of time to evolve since the origin of life—the amoeba, the platypus, the rhesus macaque, and, yes, Larry on the answering machine asking for another date. Read more at location 3383
Organisms don’t evolve toward every imaginable advantage. If they did, every creature would be faster than a speeding bullet, more powerful than a locomotive, and able to leap tall buildings in a single bound. An organism that devotes some of its matter and energy to one organ must take it away from another. It must have thinner bones or less muscle or fewer eggs. Organs evolve only when their benefits outweigh their costs. Read more at location 3399
The same disadvantages would face any creature pondering whether to evolve a humanlike brain. First, the brain is bulky. The female pelvis barely accommodates a baby’s outsize head. That design compromise kills many women during childbirth and requires a pivoting gait that makes women biomechanically less efficient walkers than men. Also, a heavy head bobbing around on a neck makes us more vulnerable to fatal injuries in accidents such as falls. Second, the brain needs energy. Neural tissue is metabolically greedy; our brains take up only two percent of our body weight but consume twenty percent of our energy and nutrients. Third, brains take time to learn to use. We spend much of our lives either being children or caring for children. Fourth, simple tasks can be slow. My first graduate advisor was a mathematical psychologist who wanted to model the transmission of information in the brain by measuring reaction times to loud tones. Theoretically, the neuron-to-neuron transmission times should have added up to a few milliseconds. But there were seventy-five milliseconds unaccounted for between stimulus and response—“There’s all this cogitation going on, and we just want him to push his finger down,” my advisor grumbled. Lower-tech animals can be much quicker; some insects can bite in less than a millisecond. Read more at location 3407
**** (Note: reductionism) fallacy that intelligence is some exalted ambition of evolution is part of the same fallacy that treats it as a divine essence or wonder tissue or all-encompassing mathematical principle. The mind is an organ, a biological gadget. Read more at location 3420
LIFE’S DESIGNER
What else but the plans of God could effect the teleology (goal-directedness) of life on earth? Darwin showed what else. He identified a forward-causation physical process that mimics the paradoxical appearance of backward causation or teleology. The trick is replication. A replicator is something that can make a copy of itself, with most of its traits duplicated in the copy, including the ability to replicate in turn. Read more at location 3452
In the beginning was a replicator. This molecule or crystal was a product not of natural selection but of the laws of physics and chemistry. (If it were a product of selection, we would have an infinite regress.) Replicators are wont to multiply, and a single one multiplying unchecked would fill the universe with its great-great-great-. . .-great-grandcopies. But replicators use up materials to make their copies and energy to power the replication. The world is finite, so the replicators will compete for its resources. Because no copying process is one hundred percent perfect, errors will crop up, and not all of the daughters will be exact duplicates. Most of the copying errors will be changes for the worse, causing a less efficient uptake of energy and materials or a slower rate or lower probability of replication. But by dumb luck a few errors will be changes for the better, and the replicators bearing them will proliferate over the generations. Their descendants will accumulate any subsequent errors that are changes for the better, including ones that assemble protective covers and supports, manipulators, catalysts for useful chemical reactions, and other features of what we call bodies. The resulting replicator with its apparently well-engineered body is what we call an organism. Read more at location 3474
Natural selection is not the only process that changes organisms over time. But it is the only process that seemingly designs organisms over time. Read more at location 3484
(Note: Opposite is true for neurological habits: wire together, fire together. Habit effect new RNA, affe t child DNA? I think this will be shown as present to a nontrivial degree.) First, using an organ does not, by itself, make the organ function better. The photons passing through a lens do not somehow wash it clear, and using a machine does not improve it but wears it out. Read more at location 3494
Complexity theory raises interesting issues. Natural selection presupposes that a replicator arose somehow, and complexity theory might help explain the “somehow.” Complexity theory might also pitch in to explain other assumptions. Each body has to hang together long enough to function rather than fly apart or melt into a puddle. And for evolution to happen at all, mutations have to change a body enough to make a difference in its functioning but not so much as to bring it to a chaotic crash. If there are abstract principles that govern whether a web of interacting parts (molecules, genes, cells) has such properties, natural selection would have to work within those principles, just as it works within other constraints of physics and mathematics like the Pythagorean theorem and the law of gravitation. Read more at location 3534
The “complexity” that so impresses biologists is not just any old order or stability. Organisms are not just cohesive blobs or pretty spirals or orderly grids. They are machines, and their “complexity” is functional, adaptive design: complexity in the service of accomplishing some interesting outcome. The digestive tract is not just patterned; it is patterned as a factory line for extracting nutrients from ingested tissues. No set of equations applicable to everything from galaxies to Bosnia can explain why teeth are found in the mouth rather than in the ear. And since organisms are collections of digestive tracts, eyes, and other systems organized to attain goals, general laws of complex systems will not suffice. Matter simply does not have an innate tendency to organize itself into broccoli, wombats, and ladybugs. Natural selection remains the only theory that explains how adaptive complexity, not just any old complexity, can arise, because it is the only nonmiraculous, forward-direction theory in which how well something works plays a causal role in how it came to be. Read more at location 3551
the evidence is overwhelming. I don’t just mean evidence that life evolved (which is way beyond reasonable doubt, creationists notwithstanding), but that it evolved by natural selection. Read more at location 3561
Natural selection is also readily observable in the wild. In a classic example, the white peppered moth gave way in nineteenth-century Manchester to a dark mutant form after industrial soot covered the lichen on which the moth rested, making the white form conspicuous to birds. When air pollution laws lightened the lichen in the 1950s, the then-rare white form reasserted itself. There are many other examples, perhaps the most pleasing coming from the work of Peter and Rosemary Grant. Darwin was inspired to the theory of natural selection in part by the thirteen species of finches on the Galápagos islands.
...The Grants painstakingly measured the size and toughness of the seeds in different parts of the Galápagos at different times of the year, the length of the finches’ beaks, the time they took to crack the seeds, the numbers and ages of the finches in different parts of the islands, and so on—every variable relevant to natural selection. Their measurements showed the beaks evolving to track changes in the availability of different kinds of seeds, a frame-by-frame analysis of the movie that Darwin could only imagine. Selection in action is even more dramatic among faster-breeding organisms, as the world is discovering to its peril in the case of pesticide-resistant insects, drug-resistant bacteria, and the AIDS virus in a single patient. And two of the prerequisites of natural selection—enough variation and enough time—are there for the having. Populations of naturally living organisms maintain an enormous reservoir of genetic variation that can serve as the raw material for natural selection. Read more at location 3576
what better demonstration than everyone’s favorite example of a complex adaptation, the eye? The computer scientists Dan Nilsson and Susanne Pelger simulated a three-layer slab of virtual skin resembling a light-sensitive spot on a primitive organism.
...Satisfyingly, the model evolved into a complex eye right on the computer screen. The slab indented and then deepened into a cup; the transparent layer thickened to fill the cup and bulged out to form a cornea. Inside the clear filling, a spherical lens with a higher refractive index emerged in just the right place, resembling in many subtle details the excellent optical design of a fish’s eye. To estimate how long it would take in real time, rather than in computer time, for an eye to unfold, Nilsson and Pelger built in pessimistic assumptions about heritability, variation in the population, and the size of the selective advantage, and even forced the mutations to take place in only one part of the “eye” each generation. Nonetheless, the entire sequence in which flat skin became a complex eye took only four hundred thousand generations, a geological instant. Read more at location 3606
the seminal ducts in men do not lead directly from the testicles to the penis but snake up into the body and pass over the ureter before coming back down. That is because the testes of our reptilian ancestors were inside their bodies. The bodies of mammals are too hot for the production of sperm, so the testes gradually descended into a scrotum. Like a gardener who snags a hose around a tree, natural selection did not have the foresight to plan the shortest route. Read more at location 3638
From the shape of an organism’s body to the shape of its protein molecules, everything we have learned in biology has come from an understanding, implicit or explicit, that the organized complexity of an organism is in the service of its survival and reproduction. Read more at location 3655
Guided only by what works, selection can home in on brilliant, creative solutions. For millennia, biologists have discovered to their astonishment and delight the ingenious contrivances of the living world: the biomechanical perfection of cheetahs, the infrared pinhole cameras of snakes, the sonar of bats, the superglue of barnacles, the steel-strong silk of spiders, the dozens of grips of the human hand, the DNA repair machinery in all complex organisms. After all, entropy and more malevolent forces like predators and parasites are constantly gnawing at an organism’s right to life and do not forgive slapdash engineering. Read more at location 3666
Even in the living world, the molecules of life are asymmetrical, as are livers, hearts, stomachs, flounders, snails, lobsters, oak trees, and so on. Symmetry has everything to do with selection. Organisms that move in straight lines have bilaterally symmetrical external forms because otherwise they would go in circles. Symmetry is so improbable and difficult to achieve that any disease or defect can disrupt it, and many animals size up the health of prospective mates by checking for minute asymmetries. Gould has emphasized that natural selection has only limited freedom to alter basic body plans. Much of the plumbing, wiring, and architecture of the vertebrates, for example, has been unchanged for hundreds of millions of years. Presumably they come from embryological recipes that cannot easily be tinkered with. But the vertebrate body plan accommodates eels, cows, hummingbirds, aardvarks, ostriches, toads, gerbils, seahorses, giraffes, and blue whales. The similarities are important, but the differences are important, too! Read more at location 3690
Selection versus constraints is a phony dichotomy, as crippling to clear thinking as the dichotomy between innateness and learning. Selection can only select from alternatives that are growable as carbon-based living stuff, but in the absence of selection that stuff could just as easily grow into scar tissue, scum, tumors, warts, tissue cultures, and quivering amorphous protoplasm as into functioning organs. Thus selection and constraints are both important but are answers to different questions. The question “Why does this creature have such-and-such an organ?” by itself is meaningless. It can only be asked when followed by a compared-to-what phrase. Read more at location 3704
Many organs that we see today have maintained their original function. The eye was always an eye, from light-sensitive spot to image-focusing eyeball. Others changed their function. That is not a new discovery. Darwin gave many examples, such as the pectoral fins of fishes becoming the forelimbs of horses, the flippers of whales, the wings of birds, the digging claws of moles, and the arms of humans. In Darwin’s day the similarities were powerful evidence for the fact of evolution, and they still are. Darwin also cited changes in function to explain the problem of “the incipient stages of useful structures,” perennially popular among creationists. How could a complex organ gradually evolve when only the final form is usable? Most often the premise of unusability is just wrong. For example, partial eyes have partial sight, which is better than no sight at all. Read more at location 3721
The delicate chain of middle-ear bones in mammals (hammer, anvil, stirrup) began as parts of the jaw hinge of reptiles. Reptiles often sense vibrations by lowering their jaws to the ground. Certain bones served both as jaw hinges and as vibration transmitters. That set the stage for the bones to specialize more and more as sound transmitters, causing them to shrink and move into their current shape and role. Read more at location 3728
Selection is not invoked to explain mere usefulness; it’s invoked to explain improbable usefulness. Read more at location 3773
THE BLIND PROGRAMMER
Why did brains evolve to start with? The answer lies in the value of information, which brains have been designed to process. Read more at location 3819
information confers a benefit that is worth paying for. Life is a choice among gambles. Read more at location 3823
Most organisms don’t buy lottery tickets, but they all choose between gambles every time their bodies can move in more than one way. They should be willing to “pay” for information—in tissue, energy, and time—if the cost is lower than the expected payoff in food, safety, mating opportunities, and other resources, all ultimately valuated in the expected number of surviving offspring. In multicellular animals the information is gathered and translated into profitable decisions by the nervous system. Often, more information brings a greater reward and earns back its extra cost. Read more at location 3831
Genetic algorithms are programs that are duplicated to make multiple copies, though with random mutations that make each one a tiny bit different. All the copies have a go at solving a problem, and the ones that do best are allowed to reproduce to furnish the copies for the next round. But first, parts of each program are randomly mutated again, and pairs of programs have sex: each is split in two, and the halves are exchanged. After many cycles of computation, selection, mutation, and reproduction, the surviving programs are often better than anything a human programmer could have designed. Read more at location 3861
a population of networks that is allowed to evolve innate connection weights often does better than a single neural network that is allowed to learn them. That is especially true for networks with multiple hidden layers, which complex animals, especially humans, surely have. If a network can only learn, not evolve, the environmental teaching signal gets diluted as it is propagated backward to the hidden layers and can only nudge the connection weights up and down by minuscule amounts. But if a population of networks can evolve, even if they cannot learn, mutations and recombinations can reprogram the hidden layers directly, and can catapult the network into a combination of innate connections that is much closer to the optimum. Innate structure is selected for. Evolution and learning can also go on simultaneously, with innate structure evolving in an animal that also learns. Read more at location 3871
Each animal, as it lives its life, tries out settings for the learnable connections at random until it hits upon the magic combination. In real life this might be figuring out how to catch prey or crack a nut; whatever it is, the animal senses its good fortune and retains those settings, ceasing the trial and error. From then on it enjoys a higher rate of reproduction. The earlier in life the animal acquires the right settings, the longer it will have to reproduce at the higher rate. Read more at location 3893
**** (Note: panpsychism of sorts) The Baldwin effect probably played a large role in the evolution of brains. Contrary to standard social science assumptions, learning is not some pinnacle of evolution attained only recently by humans. All but the simplest animals learn. That is why mentally uncomplicated creatures like fruit flies and sea slugs have been convenient subjects for neuroscientists searching for the neural incarnation of learning. If the ability to learn was in place in an early ancestor of the multicellular animals, it could have guided the evolution of nervous systems toward their specialized circuits even when the circuits are so intricate that natural selection could not have found them on its own. Read more at location 3911
There are dozens of comparable examples. Many species compute how much time to forage at each patch so as to optimize their rate of return of calories per energy expended in foraging. Some birds learn the emphemeris function, the path of the sun above the horizon over the course of the day and the year, necessary for navigating by the sun. The barn owl uses sub-millisecond discrepancies between the arrival times of a sound at its two ears to swoop down on a rustling mouse in pitch blackness. Cacheing species place nuts and seeds in unpredictable hiding places to foil thieves, but months later must recall them all. I mentioned in the preceding chapter that the Clark’s Nutcracker can remember ten thousand hiding places. Even Pavlovian and operant conditioning, the textbook cases of learning by association, turn out to be not a general stickiness of coinciding stimuli and responses in the brain, but complex algorithms for multivariate, nonstationary time series analysis (predicting when events will occur, based on their history of occurrences). The moral of this animal show is that animals’ brains are just as specialized and well engineered as their bodies. A brain is a precision instrument that allows a creature to use information to solve the problems presented by its lifestyle. Read more at location 3966
**** Whatever is special about the human mind cannot be just more, or better, or more flexible animal intelligence, because there is no such thing as generic animal intelligence. Each animal has evolved information-processing machinery to solve its problems, and we evolved machinery to solve ours. Read more at location 3977
Our brains are about three times too big for a generic monkey or ape of our body size. The inflation is accomplished by prolonging fetal brain growth for a year after birth. If our bodies grew proportionally during that period, we would be ten feet tall and weigh half a ton. The major lobes and patches of the brain have been revamped as well. The olfactory bulbs, which underlie the sense of smell, have shriveled to a third of the expected primate size (already puny by mammalian standards), and the main cortical areas for vision and movement have shrunk proportionally as well. Within the visual system, the first stop for information, the primary visual cortex, takes up a smaller proportion of the whole brain, while the later areas for complex-form processing expand, as do the temporo-parietal areas that shunt visual information to the language and conceptual regions. The areas for hearing, especially for understanding speech, have grown, and the prefrontal lobes, the seat of deliberate thought and planning, have ballooned to twice what a primate our size should have. While the brains of monkeys and apes are subtly asymmetrical, the human brain, especially in the areas devoted to language, is so lopsided that the two hemispheres can be distinguished by shape in the jar. Read more at location 3992
William James pressed the point:
...Nothing more can be said than that these are human ways, and that every creature likes its own ways, and takes to the following them as a matter of course. Science may come and consider these ways, and find that most of them are useful. But it is not for the sake of their utility that they are followed, but because at the moment of following them we feel that that is the only appropriate and natural thing to do. Not one man in a billion, when taking his dinner, ever thinks of utility. He eats because the food tastes good and makes him want more. If you ask him why he should want to eat more of what tastes like that, instead of revering you as a philosopher we will probably laugh at you for a fool. . . . And so, probably, does each animal feel about the particular things it tends to do in presence of particular objects. Read more at location 4024
****** (Note: Wittgenstein: belief ungrounded) Remember what the tortoise said to Achilles. No rational creature can consult rules all the way down; that way infinite regress lies. At some point a thinker must execute a rule, because he just can’t help it: it’s the human way, a matter of course, the only appropriate and natural thing to do—in short, an instinct. Read more at location 4036
because selection is driven by the fate of the whole individual, it is not enough to explain the evolution of a brain in a vat. A good theory has to connect all the parts of the human lifestyle—all ages, both sexes, anatomy, diet, habitat, and social life. That is, it has to characterize the ecological niche that humans entered. The only theory that has risen to this challenge comes from John Tooby and the anthropologist Irven DeVore. Tooby and DeVore begin by noting that species evolve at one another’s expense. Read more at location 4080
Humans analyze the world using intuitive theories of objects, forces, paths, places, manners, states, substances, hidden biochemical essences, and, for other animals and people, beliefs and desires. (These intuitive theories are the topic of Chapter 5.) People compose new knowledge and plans by mentally playing out combinatorial interactions among these laws in their mind’s eye. Read more at location 4094
The cognitive niche embraces many of the zoologically unusual features of our species. Tool manufacture and use is the application of knowledge about causes and effects among objects in the effort to bring about goals. Language is a means of exchanging knowledge. It multiplies the benefit of knowledge, which can not only be used but exchanged for other resources, and lowers its cost, because knowledge can be acquired from the hard-won wisdom, strokes of genius, and trial and error of others rather than only from risky exploration and experimentation. Information can be shared at a negligible cost: Read more at location 4129
WHY US?
I would guess that our ancestors had four traits that made it especially easy and worth their while to evolve better powers of causal reasoning. First, primates are visual animals.
...Why would the vision thing make such a difference? Depth perception defines a three-dimensional space filled with movable solid objects. Color makes objects pop out from their backgrounds, and gives us a sensation that corresponds to the stuff an object is made of, distinct from our perception of the shape of the stuff. Together they have pushed the primate brain into splitting the flow of visual information into two streams: a “what” system, for objects and their shapes and compositions, and a “where” system, for their locations and motions. It can’t be a coincidence that the human mind grasps the world—even the most abstract, ethereal concepts—as a space filled with movable things and stuff Read more at location 4148
A second possible prerequisite, this one found in the common ancestor of humans, chimpanzees, and gorillas, is group living. Most apes and monkeys are gregarious, though most mammals are not.
...Group living could have set the stage for the evolution of humanlike intelligence in two ways. With a group already in place, the value of having better information is multiplied, because information is the one commodity that can be given away and kept at the same time. Therefore a smarter animal living in a group enjoys a double advantage: the benefit of the knowledge and the benefit of whatever it can get in trade for the knowledge. The other way in which a group can be a crucible of intelligence is that group living itself poses new cognitive challenges.
...In many kinds of animals, the largest-brained and smartest-behaving species are social: bees, parrots, dolphins, elephants, wolves, sea lions, and, of course, monkeys, gorillas, and chimpanzees. (The orangutan, smart but almost solitary, is a puzzling exception.) Social animals send and receive signals to coordinate predation, defense, foraging, and collective sexual access. They exchange favors, repay and enforce debts, punish cheaters, and join coalitions. Read more at location 4185
A third pilot of intelligence, alongside good vision and big groups, is the hand.
...Hands are levers of influence on the world that make intelligence worth having. Precision hands and precision intelligence co-evolved in the human lineage, and the fossil record shows that hands led the way. Finely tooled hands are useless if you have to walk on them all the time, and they could not have evolved by themselves. Every bone in our bodies has been reshaped to give us our upright posture, which frees the hands for carrying and manipulating. Read more at location 4210
A final usher of intelligence was hunting. Hunting, tool use, and bipedalism were for Darwin the special trinity that powered human evolution.
...Across the mammals, carnivores have larger brains for their body size than herbivores, partly because of the greater skill it takes to subdue a rabbit than to subdue grass, and partly because meat can better feed ravenous brain tissue. Even in the most conservative estimates, meat makes up a far greater proportion of foraging humans’ diet than of any other primate’s. That may have been one of the reasons we could afford our expensive brains. Read more at location 4234
THE MODERN STONE AGE FAMILY
The stepwise growth of the brain, propelled by hands and feet and manifested in tools, butchered bones, and increased range, is good evidence, if evidence were needed, that intelligence is a product of natural selection for exploitation of the cognitive niche. The package was not an inexorable unfolding of hominid potential. Read more at location 4301
According to the standard timetable in paleoanthropology, the human brain evolved to its modern form in a window that began with the appearance of Homo habilis two million years ago and ended with the appearance of “anatomically modern humans,” Homo sapiens sapiens, between 200,000 and 100,000 years ago. I suspect that our ancestors were penetrating the cognitive niche for far longer than that. Read more at location 4311
Modern humans (us) are said to have first arisen between 200,000 and 100,000 years ago in Africa. One kind of evidence is that the mitochondrial DNA (mDNA) of everyone on the planet (which is inherited only from one’s mother) can be traced back to an African woman living sometime in that period. (The claim is controversial, but the evidence is growing.) Another is that anatomically modern fossils first appear in Africa more than 100,000 years ago and in the Middle East shortly afterward, around 90,000 years ago. The assumption is that human biological evolution had pretty much stopped then. This leaves an anomaly in the timeline. The anatomically modern early humans had the same toolkit and lifestyle as their doomed Neanderthal neighbors. The most dramatic change in the archeological record, the Upper Paleolithic transition—also called the Great Leap Forward and the Human Revolution—had to wait another 50,000 years. Therefore, it is said, the human revolution must have been a cultural change. Read more at location 4333
Ways of life certainly can shoot off without any biological change, as in the more recent agricultural, industrial, and information revolutions. That is especially true when populations grow to a point where the insights of thousands of inventors can be pooled. But the first human revolution was not a cascade of changes set off by a few key inventions. Ingenuity itself was the invention, manifested in hundreds of innovations tens of thousands of miles and years apart. I find it hard to believe that the people of 100,000 years ago had the same minds as those of the Upper Paleolithic revolutionaries to come—indeed, the same minds as ours—and sat around for 50,000 years without it dawning on a single one of them that you could carve a tool out of bone, or without a single one feeling the urge to make anything look pretty. And there is no need to believe it—the 50,000-year gap is an illusion. Read more at location 4349
the revolution probably began well before the commonly cited watershed of 40,000 years ago. That’s when fancy artifacts begin to appear in European caves, but Europe has always attracted more attention than it deserves, because it has lots of caves and lots of archeologists. France alone has three hundred well-excavated paleolithic sites, including one whose cave paintings were scrubbed off by an overenthusiastic boy scout troop that mistook them for graffiti. The entire continent of Africa has only two dozen. Read more at location 4364
if someone were to guess the degree of relatedness between you and your cousin based on your most recent ancestor, he would say you were closely related. But if he could check only the most recent all-female-line ancestor, he might guess that you are not related at all! Similarly, the birthday of humanity’s most recent common all-female-line ancestor, mitochondrial Eve, overestimates how long ago all of humanity was still interbreeding. Read more at location 4388
some geneticists think, our ancestors passed through a population bottleneck. According to their scenario, which is based on the remarkable sameness of genes across modern human populations, around 65,000 years ago our ancestors dwindled to a mere ten thousand people, perhaps because of a global cooling triggered by a volcano in Sumatra. The human race was as endangered as mountain gorillas are today. The population then exploded in Africa and spun off small bands that moved to other corners of the world, possibly mating now and again with other early humans in their path. Read more at location 4392
what about the Darwinian imperative to survive and reproduce? As far as day-to-day behavior is concerned, there is no such imperative. People watch pornography when they could be seeking a mate, forgo food to buy heroin, sell their blood to buy movie tickets (in India), postpone childbearing to climb the corporate ladder, and eat themselves into an early grave. Human vice is proof that biological adaptation is, speaking literally, a thing of the past. Our minds are adapted to the small foraging bands in which our family spent ninety-nine percent of its existence, not to the topsy-turvy contingencies we have created since the agricultural and industrial revolutions. Read more at location 4442
**** People do not divine what is adaptive for them or their genes; their genes give them thoughts and feelings that were adaptive in the environment in which the genes were selected. Read more at location 4452
Richard Dawkins has drawn the clearest analogy between the selection of genes and the selection of bits of culture, which he dubbed memes. Memes such as tunes, ideas, and stories spread from brain to brain and sometimes mutate in the transmission. New features of a meme that make its recipients more likely to retain and disseminate it, such as being catchy, seductive, funny, or irrefutable, will lead to the meme’s becoming more common in the meme pool. In subsequent rounds of retelling, the most spreadworthy memes will spread the most and will eventually take over the population. Ideas will therefore evolve to become better adapted to spreading themselves. Note that we are talking about ideas evolving to become more spreadable, not people evolving to become more knowledgeable. Dawkins himself used the analogy to illustrate how natural selection pertains to anything that can replicate, not just DNA. Others treat it as a genuine theory of cultural evolution. Read more at location 4463
The geneticist Theodosius Dobzhansky famously wrote that nothing in biology makes sense except in the light of evolution. We can add that nothing in culture makes sense except in the light of psychology. Evolution created psychology, and that is how it explains culture. Read more at location 4505
4 THE MIND’S EYE
Illusions are no mere curiosities; they set the intellectual agenda for centuries of Western thought. Skeptical philosophy, as old as philosophy itself, impugns our ability to know anything by rubbing our faces in illusions: the oar in the water that appears bent, the round tower that from a distance looks flat, the cold finger that perceives tepid water as hot while the hot finger perceives it as cold. Many of the great ideas of the Enlightenment were escape hatches from the depressing conclusions skeptical philosophers drew from illusions. We can know by faith, we can know by science, we can know by reason, we can know that we think and therefore that we are. Perception scientists take a lighter view. Vision may not work all the time, but we should marvel that it works at all. Read more at location 4526
real organisms don’t have these luxuries. When they apprehend the world by sight, they have to use the splash of light reflected off its objects, projected as a two-dimensional kaleidoscope of throbbing, heaving streaks on each retina. The brain somehow analyzes the moving collages and arrives at an impressively accurate sense of the objects out there that gave rise to them. The accuracy is impressive because the problems the brain is solving are literally unsolvable. Recall from Chapter 1 that inverse optics, the deduction of an object’s shape and substance from its projection, is an “ill-posed problem,” a problem that, as stated, has no unique solution. An elliptical shape on the retina could have come from an oval viewed head-on or a circle viewed at a slant. A patch of gray could have come from a snowball in the shade or a lump of coal in the sun. Vision has evolved to convert these ill-posed problems into solvable ones by adding premises: assumptions about how the world we evolved in is, on average, put together. Read more at location 4536
**** When the current world resembles the average ancestral environment, we see the world as it is. When we land in an exotic world where the assumptions are violated—because of a chain of unlucky coincidences or because a sneaky psychologist concocted the world to violate the assumptions—we fall prey to an illusion. That is why psychologists are obsessed with illusions. They unmask the assumptions that natural selection installed to allow us to solve unsolvable problems and know, much of the time, what is out there. Read more at location 4545
This chapter explores how vision turns retinal depictions into mental descriptions. Read more at location 4575
DEEP EYE
Autostereograms exploit not one but four discoveries on how to trick the eye. The first, strange to say, is the picture. We are so jaded by photographs, drawings, television, and movies that we forget that they are a benign illusion. Smears of ink or flickering phosphor dots can make us laugh, cry, even become sexually aroused. Read more at location 4583
Vision begins when a photon (unit of light energy) is reflected off a surface and zips along a line through the pupil to stimulate one of the photoreceptors (rods and cones) lining the curved inner surface of the eyeball. The receptor passes a neural signal up to the brain, and the brain’s first task is to figure out where in the world that photon came from. Unfortunately, the ray defining the photon’s path extends out to infinity, and all the brain knows is that the originating patch lies somewhere along the ray. For all the brain knows, it could be a foot away, a mile away, or many light-years away; information about the third dimension, distance from the eye, has been lost in the process of projection. Read more at location 4591
The visual system hates coincidences: it assumes that a regular image comes from something that really is regular and that it doesn’t just look that way because of the fortuitous alignment of an irregular shape. Read more at location 4608
one can use the difference in an object’s projection in the two eyes, together with the angle formed by the two eyes’ gaze and their separation in the skull, to calculate how far away the object is. If natural selection could wire up a neural computer to do the trig, a two-eyed creature could shatter Leonardo’s window and sense an object’s depth. The mechanism is called stereoscopic vision, stereo for short. Incredibly, for thousands of years no one noticed. Read more at location 4661
Stereo vision was not discovered until 1838, by Charles Wheatstone, a physicist and inventor Read more at location 4670
The closer the object, the more the rays have to be bent for them to converge to a point rather than to a blurry disk, and the fatter the lens of the eye has to be. Muscles inside the eyeball have to thicken the lens to focus nearby objects and flatten it to focus distant objects.
...The second physical adjustment is to aim the two eyes, which are about two and a half inches apart, at the same spot in the world. The closer the object, the more the eyes must be crossed. Read more at location 4703
Until recently, everyone thought that the brain solved the correspondence problem in everyday scenes by first recognizing the objects in each eye and then matching up images of the same object. Read more at location 4825
Stereo vision does not come free with the two eyes; the circuitry has to be wired into the brain. We know this because about two percent of the population can see perfectly well out of each eyeball but not with the cyclopean eye; random-dot stereograms remain flat. Another four percent can see stereo only poorly. An even larger minority has more selective deficits. Some can’t see stereo depth behind the point of fixation; others can’t see it in front. Whitman Richards, who discovered these forms of stereoblindness, hypothesized that the brain has three pools of neurons that detect differences in the position of a spot in the two eyes. One pool is for pairs of spots that coincide exactly or almost exactly, for fine-grained depth perception at the point of focus. Another is for pairs of spots flanking the nose, for farther objects. A third is for pairs of spots approaching the temples, for nearer objects. Neurons with all these properties have since been found in the brains of monkeys and cats. The different kinds of stereoblindness appear to be genetically determined, Read more at location 4974
Stereo vision appears abruptly in infants. When newborns are brought into a lab at regular intervals, for week after week they are unimpressed by stereograms, and then suddenly they are captivated. Close to that epochal week, usually around three or four months of age, the babies converge their eyes properly for the first time (for example, they smoothly track a toy brought up to their nose), and they find rivalrous displays—a different pattern in each eye—annoying, whereas before they had found them interesting. It is not that babies “learn to see in stereo,” whatever that would mean. The psychologist Richard Held has a simpler explanation. When infants are born, every neuron in the receiving layer of the visual cortex adds up the inputs from corresponding locations in the two eyes rather than keeping them separate. The brain can’t tell which eye a given bit of pattern came from, and simply melts one eye’s view on top of the other’s in a 2-D overlay. Without information about which eye a squiggle came from, stereo vision, convergence, and rivalry are logically impossible. Around the three-month mark each neuron settles on a favorite eye to respond to. The neurons lying one connection downstream can now know when a mark falls on one spot in one eye and on the same spot, or a slightly shifted-over spot, in the other eye—the grist for stereo vision. In cats and monkeys, whose brains have been studied directly, this is indeed what happens. Read more at location 4988
Once the brain has segregated the left eye’s image from the right eye’s, subsequent layers of neurons can compare them for the minute disparities that signal depth. Read more at location 5022
the face keeps growing after birth, and the eyes get pushed farther apart. Their relative vantage points change, and the neurons must keep up by retuning the range of intereye disparities they detect. Genes cannot anticipate the degree of spreading of the vantage points, because it depends on other genes, nutrition, and various accidents. So the neurons track the drifting eyes during the window of growth. When the eyes arrive at their grownup separation in the skull, the need disappears, and that is when the critical period ends. Read more at location 5038
I think stereo vision is one of the glories of nature and a paradigm of how other parts of the mind might work. Stereo vision is information processing that we experience as a particular flavor of consciousness, a connection between mental computation and awareness that is so lawful that computer programmers can manipulate it to enchant millions. It is a module in several senses: it works without the rest of the mind (not needing recognizable objects), the rest of the mind works without it (getting by, if it has to, with other depth analyzers), it imposes particular demands on the wiring of the brain, and it depends on principles specific to its problem (the geometry of binocular parallax). Read more at location 5053
Stereo vision shows off the engineering acumen of natural selection, exploiting subtle theorems in optics rediscovered millions of years later by the likes of Leonardo da Vinci, Kepler, Wheatstone, and aerial reconnaissance engineers. It evolved in response to identifiable selection pressures in the ecology of our ancestors. And it solves unsolvable problems by making tacit assumptions about the world Read more at location 5060
LIGHTING, SHADING, SHAPING
How can a visual system calculate the most probable state of the world from the evidence on the retina? Probability theory offers a simple answer: Bayes’ theorem, the most straightforward way of assigning a probability to a hypothesis based on some evidence. Bayes’ theorem says that the odds favoring one hypothesis over another can be calculated from just two numbers for each hypothesis. One is the prior probability: how confident are you in the hypothesis before you even look at the evidence? The other is the likelihood: if the hypothesis were true, what is the probability that the evidence as you are seeing it now would have appeared? Multiply the prior probability of Hypothesis 1 by the likelihood of the evidence under Hypothesis 1. Multiply the prior probability of Hypothesis 2 by the likelihood of the evidence under Hypothesis 2. Take the ratio of the two numbers. You now have the odds in favor of the first hypothesis. How does our 3-D line analyzer use Bayes’ theorem? It puts its money on the object that has the greatest likelihood of producing those lines if it were really in the scene, and that has a good chance of being in scenes in general. It assumes, as Einstein once said about God, that the world is subtle but not malicious. Read more at location 5086
(Note: Semantic, but I think we near disagreement,. I think Pinker views matter as real; more than information... the stuff of the universe...) Surfaces are not just bounded by lines; they are composed of material.
...Surfaces with glosses, patinas, fuzz, pits, and prickles do other, stranger things with light, and they can fool the eye. A famous example is the full moon. It looks like a flat disk, but of course it is a sphere.
...The center of the full moon faces the viewer flat-on, so it should be brightest, but it has little nooks and crannies whose walls are seen edge-on from the viewer’s earthly vantage point, making the center of the moon look darker. The surfaces near the perimeter of the moon graze the line of sight and should look darker, but they present their canyon walls face-on and reflect back lots of light, making the perimeter look lighter. Over the whole moon, the angle of its surface and the angles of the facets of its craters cancel out. All portions reflect back the same amount of light, and the eye sees it as a disk. Read more at location 5206
The moral is that the specialists must be coordinated, not necessarily by a homunculus or demon, but by some arrangement that minimizes the costs, where cheap equals simple equals probable. In the parable, simple operations are easier to perform; in the visual system, simpler descriptions correspond to likelier arrangements in the world. Read more at location 5317
**** the mind is a collection of modules, a system of organs, or a society of experts. Experts are needed because expertise is needed: the mind’s problems are too technical and specialized to be solved by a jack-of-all-trades. And most of the information needed by one expert is irrelevant to another and would only interfere with its job. But working in isolation, an expert can consider too many solutions or doggedly pursue an unlikely one; at some point the experts must confer. The many experts are trying to make sense of a single world, and that world is indifferent to their travails, neither offering easy solutions nor going out of its way to befuddle. So a supervisory scheme should aim to keep the experts within a budget in which improbable guesses are more expensive. That forces them to cooperate in assembling the most likely overall guess about the state of the world. SEEING IN TWO AND A HALF DIMENSIONS Read more at location 5360
First, vision is not a theater in the round. We vividly experience only what is in front of our eyes; the world beyond the perimeter Read more at location 5397
Second, we don’t have x-ray vision. We see surfaces, not volumes. Read more at location 5405
Third, we see in perspective. Read more at location 5409
Fourth, in a strict geometric sense we see in two dimensions, not three. Read more at location 5416
Fifth, we don’t immediately see “objects,” the movable hunks of matter that we count, classify, and label with nouns. As far as vision is concerned, it’s not even clear what an object is. Read more at location 5425
The most famous illusions in psychology come from the brain’s unflagging struggle to carve the visual field into surfaces and to decide which is in front of the other. Read more at location 5434
(Note: I think Eagleman's work is much newer, so I would guess Pinker is wrong here) We perceive surfaces involuntarily, impelled by information surging up from our retinas; contrary to popular belief, we do not see what we expect to see. Read more at location 5444
FRAMES OF REFERENCE
The key to using visual information is not to remold it but to access it properly, and that calls for a useful reference frame or coordinate system. Reference frames are inextricable from the very idea of location. How do you answer the question “Where is it?” By naming an object that the asker already knows—the frame of reference—and describing how far and in what direction the “it” is, relative to the frame. Read more at location 5485
As the head pitches, rolls, and yaws, fluid in the canals sloshes around and triggers neural signals registering the motion. A heavy mass of grit pressing down on other membranes registers linear motion and the direction of gravity. These signals can be used to rotate the mental crosshairs so they are always correctly pointing “up.” That is why the world does not seem to list even though people’s heads are seldom plumb perpendicular. Read more at location 5525
if you are moving inside a container like a car, a boat, or a sedan chair—evolutionarily unprecedented ways to get around—the inner ear says, “You’re moving,” but the walls and floor say, “You’re staying put.” Motion sickness is triggered by this mismatch, Read more at location 5535
ANIMAL CRACKERS
How do people recognize shapes? An average adult knows names for about ten thousand things, most of them distinguished by shape. Read more at location 5593
The key idea is that a shape memory is not a copy of the 2½-D sketch but rather is stored in a format that differs from it in two ways. First, the coordinate system is centered on the object—not, as in the 2½-D sketch, on the viewer. To recognize an object, the brain aligns a reference frame on its axes of elongation and symmetry and measures the positions and angles of the parts in that reference frame. Only then are vision and memory matched. The second difference is that the matcher does not compare vision and memory pixel by pixel, as if placing a jigsaw puzzle piece in a gap. Read more at location 5612
The psychologist Irv Biederman has fleshed out Marr’s two ideas with an inventory of simple geometric parts that he calls “geons” (by analogy to the protons and electrons making up atoms). Read more at location 5621
Biederman proposes twenty-four geons altogether, including a cone, a megaphone, a football, a tube, a cube, and a piece of elbow macaroni. (Technically, they are all just different kinds of cones. Read more at location 5624
Geons are combinatorial, like grammar. Obviously we don’t describe shapes to ourselves in words, but geon assemblies are a kind of internal language, a dialect of mentalese. Elements from a fixed vocabulary are fitted together into larger structures, like words in a phrase or sentence. Read more at location 5631
Language and complex shapes even seem to be neighbors in the brain. The left hemisphere is not only the seat of language but also the seat of the ability to recognize and imagine shapes defined by arrangements of parts. A neurological patient who had suffered a stroke to his left hemisphere reported, “When I try to imagine a plant, an animal, an object, I can recall but one part. My inner vision is fleeting, fragmented; if I’m asked to imagine the head of a cow, I know it has ears and horns, but I can’t revisualize their places.” The right hemisphere, in contrast, is good for measuring whole shapes; it can easily judge whether a rectangle is taller than it is wide or whether a dot lies more or less than an inch from an object. Read more at location 5641
(Note: Platonic) The geon theory says that at the highest levels of perception the mind “sees” objects and parts as idealized geometric solids. That would explain a curious and long-noted fact about human visual aesthetics. Anyone who has been to a figure-drawing class or a nude beach quickly learns that real human bodies do not live up to our sweet imaginations. Read more at location 5651
Many psychologists believe that face recognition is special. In a social species like ours, faces are so important that natural selection gave us a processor that registers the kinds of geometric contours and ratios needed to tell them apart. Read more at location 5669
Face recognition may even use distinct parts of the brain. An inability to recognize faces is called prosopagnosia. Read more at location 5673
A fundamental discovery of twentieth-century physics is that the universe has a handedness, too. At first that sounds absurd. For any object and event in the cosmos, you have no way of knowing whether you are seeing the actual event or its reflection in a mirror. You may protest that organic molecules and human-made objects like letters of the alphabet are an exception. The standard versions are all over the place and familiar; the mirror images are rare and can easily be recognized. But for a physicist, they don’t count, because their handedness is a historical accident, not something ruled out by the laws of physics. On another planet, or on this one if we could rewind the tape of evolution and let it happen again, they could just as easily go the other way. Physicists used to think that this was true for everything in the universe. Wolfgang Pauli wrote, “I do not believe that the Lord is a weak left-hander,” and Richard Feynman bet fifty dollars to one (he was unwilling to bet a hundred) that no experiment would ever reveal a law of nature that looked different through the looking glass. He lost. The cobalt 60 nucleus is said to spin counterclockwise if you look down on its north pole, but that description by itself is circular because “north pole” is simply what we call the end of the axis from which a rotation looks counterclockwise. The logical circle would be broken if something else differentiated the so-called north pole from the so-called south pole. Here is the something else: when the atom decays, electrons are more likely to be flung out of the end we call south. “North” versus “south” and “clockwise” versus “counterclockwise” are no longer arbitrary labels but can be distinguished relative to the electron spurt. The decay, hence the universe, would look different in the mirror. God is not ambidextrous after all. Read more at location 5748
The envelope, please. And the winner is . . . All of the above. People definitely stored several views: when a shape appeared in one of its habitual orientations, people were very quick to identify it. And people definitely rotate shapes in their minds. When a shape appeared at a new, unfamiliar orientation, the farther it would have to be rotated to be aligned with the nearest familiar view, the more time people took. And at least for some shapes, people use an object-centered reference frame, as in the geon theory. Tarr and I ran a variant of the experiment in which the shapes had simpler geometries: Read more at location 5829
One can even make an educated guess about the anatomy of mental imagery. The incarnation of a 2½-D sketch in neurons is called a topographically organized cortical map: a patch of cortex in which each neuron responds to contours in one part of the visual field, and in which neighboring neurons respond to neighboring parts. The primate brain has at least fifteen of these maps, and in a very real sense they are pictures in the head. Neuroscientists can inject a monkey with a radioactive isotope of glucose while it stares at a bull’s-eye. The glucose is taken up by the active neurons, and one can literally develop the monkey’s brain as if it were a piece of film. It comes out of the darkroom with a distorted bull’s-eye laid out over the visual cortex. Read more at location 5947
The brain is also ready for the second computational demand of an imagery system, information flowing down from memory instead of up from the eyes. The fiber pathways to the visual areas of the brain are two-way. They carry as much information down from the higher, conceptual levels as up from the lower, sensory levels. No one knows what these top-down connections are for, but they could be there to download memory images into visual maps. Read more at location 5957
the Perky effect: holding a mental image interferes with seeing faint and fine visual details. Imagery can affect perception in gross ways, too. When people answer questions about shapes from memory, like counting off the right angles in a block letter, their visual-motor coordination suffers. (Since learning about these experiments I try not to get too caught up in a hockey game on the radio while I am driving.) Mental images of lines can affect perception just as real lines do: they make it easier to judge alignment and can even induce visual illusions. When people see some shapes and imagine others, later they sometimes have trouble remembering which was which. Read more at location 5976
The visual cortex is topographically mapped—it forms a picture, if you will. In some runs, the subjects visualized large letters, in others, small letters. Pondering large letters activated the parts of the cortex representing the periphery of the visual field; pondering small letters activated the parts representing the fovea. Images really do seem to be laid across the cortical surface. Read more at location 5995
**** (Note: mental imagery as topographic within brain!) Mental images live in the visual cortex; indeed, parts of images take up parts of cortex, just as parts of scenes take up parts of pictures. Read more at location 6001
Images are fragmentary. We recall glimpses of parts, arrange them in a mental tableau, and then do a juggling act to refresh each part as it fades. Worse, each glimpse records only the surfaces visible from one vantage point, distorted by perspective. Read more at location 6086
Memory images must be labeled and organized within a propositional superstructure, perhaps a bit like hypermedia, where graphics files are linked to attachment points within a large text or database. Visual thinking is often driven more strongly by the conceptual knowledge we use to organize our images than by the contents of the images themselves. Read more at location 6102
When vision leaves off and thought begins, there’s no getting around the need for abstract symbols and propositions that pick out aspects of an object for the mind to manipulate. Read more at location 6170
5 GOOD IDEAS
Wallace’s paradox, the apparent evolutionary uselessness of human intelligence, is a central problem of psychology, biology, and the scientific worldview. Even today, scientists such as the astronomer Paul Davies think that the “overkill” of human intelligence refutes Darwinism and calls for some other agent of a “progressive evolutionary trend,” perhaps a self-organizing process that will be explained someday by complexity theory. Unfortunately this is barely more satisfying than Wallace’s idea of a superior intelligence guiding the development of man in a definite direction. Much of this book, and this chapter in particular, is aimed at demoting Wallace’s paradox from a foundation-shaking mystery to a challenging but otherwise ordinary research problem in the human sciences. Read more at location 6210
ECOLOGICAL INTELLIGENCE
A ground rule when you solve a problem at school is to base your reasoning on the premises mentioned in a question, ignoring everything else you know. The attitude is important in modern schooling. In the few thousand years since the emergence of civilizations, a division of labor has allowed a class of knowledge professionals to develop methods of inference that are widely applicable and can be disseminated by writing and formal instruction. These methods literally have no content. Long division can calculate miles per gallon, or it can calculate income per capita. Read more at location 6273
our brains were shaped for fitness, not for truth. Sometimes the truth is adaptive, but sometimes it is not. Read more at location 6307
The philosopher Hilary Putnam confesses that, like most people, he has no idea how an elm differs from a beech. But the words aren’t synonyms for him or for us; we all know that they refer to different kinds of trees, and that there are experts out there who could tell us which is which if we ever had to know. Experts are invaluable and are usually rewarded in esteem and wealth. But our reliance on experts puts temptation in their path. The experts can allude to a world of wonders—occult forces, angry gods, magical potions—that is inscrutable to mere mortals but reachable through their services.
...In a complex society, a dependence on experts leaves us even more vulnerable to quacks, from carnival snake-oil salesmen to the mandarins who advise governments to adopt programs implemented by mandarins. Modern scientific practices like peer review, competitive funding, and open mutual criticism are meant to minimize scientists’ conflicts of interest in principle, and sometimes do so in practice. Read more at location 6319
Donald Brown was puzzled to learn that over the millennia the Hindus of India produced virtually no histories, while the neighboring Chinese had produced libraries full. He suspected that the potentates of a hereditary caste society realized that no good could come from a scholar nosing around in records of the past where he might stumble upon evidence undermining their claims to have descended from heroes and gods. Brown looked at twenty-five civilizations and compared the ones organized by hereditary castes with the others. None of the caste societies had developed a tradition of writing accurate depictions of the past; instead of history they had myth and legend. The caste societies were also distinguished by an absence of political science, social science, natural science, biography, realistic portraiture, and uniform education. Read more at location 6324
LITTLE BOXES
the mind has to get something out of forming categories, and that something is inference. Obviously we can’t know everything about every object. But we can observe some of its properties, assign it to a category, and from the category predict properties that we have not observed. Read more at location 6354
****** (Note: inductive vs deductive categories of thought) treat games and vegetables as categories that have stereotypes, fuzzy boundaries, and family-like resemblances. That kind of category falls naturally out of pattern-associator neural networks. We treat odd numbers and females as categories that have definitions, in-or-out boundaries, and common threads running through the members. That kind of category is naturally computed by systems of rules. We put some things into both kinds of mental categories—we think of “a grandmother” as a gray-haired muffin dispenser; we also think of “a grandmother” as the female parent of a parent. Now we can explain what these two ways of thinking are for. Fuzzy categories come from examining objects and uninsightfully recording the correlations among their features. Their predictive power comes from similarity: if A shares some features with B, it probably shares others. They work by recording the clusters in reality. Well-defined categories, in contrast, work by ferreting out the laws that put the clusters there. They fall out of the intuitive theories that capture people’s best guess about what makes the world tick. Their predictive power comes from deduction: if A implies B, and A is true, then B is true. Read more at location 6382
science is famous for transcending fuzzy feelings of similarity and getting at underlying laws. Read more at location 6392
similarity-defying guesses come from intuitive theories about aging, weather, economic exchange, biology, and social coalitions. They belong to larger systems of tacit assumptions about kinds of things and the laws governing them. The laws can be played out combinatorially in the mind to get predictions and inferences about events unseen. Read more at location 6404
Sometimes the descendants of a species diverge so unevenly that some of their scions are almost unrecognizable. Those branchlets have to be hacked off to keep the category as we know it, and the main branch is disfigured by jagged stumps. It turns into a fuzzy category whose boundaries are defined by similarity, without a crisp scientific definition. Fish, for example, do not occupy one branch in the tree of life. One of their kind, a lungfish, begot the amphibians, whose descendants embrace the reptiles, whose descendants embrace the birds and the mammals. There is no definition that picks out all and only the fish, no branch of the tree of life that includes salmon and lungfish but excludes lizards and cows. Taxonomists fiercely debate what to do with categories like fish that are obvious to any child but have no scientific definition because they are neither species nor clades. Read more at location 6426
Classification is particularly fuzzy at the stump where a branch was hacked off, that is, the extinct species that became the inauspicious ancestor of a new group. The fossil Archaeopteryx, thought to be the ancestor of the birds, has been described by one paleontologist as “a piss-poor reptile, and not very much of a bird.” The anachronistic shoehorning of extinct animals into the modern categories they spawned was a bad habit of early paleontologists, dramatically recounted in Gould’s Wonderful Life. Read more at location 6436
****** In his book Women, Fire, and Dangerous Things, named after a fuzzy grammatical category in an Australian language, the linguist George Lakoff argues that pristine categories are fictions. They are artifacts of the bad habit of seeking definitions, a habit that we inherited from Aristotle and now must shake off. He defies his readers to find a sharp-edged category in the world. Crank up the microscope, and the boundaries turn to fuzz. Read more at location 6444
**** Systems of rules are idealizations that abstract away from complicating aspects of reality. They are never visible in pure form, but are no less real for all that. No one has ever actually sighted a triangle without thickness, a frictionless plane, a point mass, an ideal gas, or an infinite, randomly interbreeding population. That is not because they are useless figments but because they are masked by the complexity and finiteness of the world and by many layers of noise. Read more at location 6453
Goals and values are one of the vocabularies in which we mentally couch our experiences. They cannot be built out of simpler concepts from our physical knowledge the way “momentum” can be built out of mass and velocity or “power” can be built out of energy and time. They are primitive or irreducible, and higher-level concepts are defined in terms of them. Read more at location 6519
apparently infants have an idea of objecthood early in life, and it is the core of the adult concept: parts moving together. When two sticks peeking out from behind the screen moved back and forth in tandem, babies saw them as a single object and were surprised if the raised screen revealed two. When they didn’t move, babies did not expect them to be a single object, even though the visible pieces had the same color and texture. When a stick peeked out from behind the top edge and a red jagged polygon peeked out from behind the bottom edge, and they moved back and forth in tandem, babies expected them to be connected, even though they had nothing in common but motion. The child is parent to the adult in other principles of intuitive physics. One is that an object cannot pass through another object like a ghost.
...A second principle is that objects move along continuous trajectories: they cannot disappear from one place and materialize in another,
.A third principle is that objects are cohesive. Infants are surprised when a hand picks up what looks like an object but part of the object stays behind. A fourth principle is that objects move each other by contact only—no action at a distance. Read more at location 6588
three- to four-month-old infants see objects, remember them, and expect them to obey the laws of continuity, cohesion, and contact as they move. Babies are not as stoned as James, Piaget, Freud, and others thought. As the psychologist David Geary has said, James’ “blooming, buzzing confusion” is a good description of the parents’ life, not the infant’s. Read more at location 6593
If children did not carve the world into objects, or if they were prepared to believe that objects could magically disappear and reappear anywhere, they would have no pegs on which to hang their discoveries of stickiness, fluffiness, squishiness, and so on. Read more at location 6639
People construe certain objects as animate agents. Agents are recognized by their ability to violate intuitive physics by starting, stopping, swerving, or speeding up without an external nudge, especially when they persistently approach or avoid some other object. The agents are thought to have an internal and renewable source of energy, force, impetus, or oomph, which they use to propel themselves, usually in service of a goal. These agents are animals, of course, including humans. Read more at location 6652
Infants divide the world into the animate and the inert early in life. Three-month-olds are upset by a face that suddenly goes still but not by an object that suddenly stops moving. They try to bring objects toward them by pushing things, but try to bring people toward them by making noise. By six or seven months, babies distinguish between how hands act upon objects and how other objects act upon objects. They have opposite expectations about what makes people move and what makes objects move: objects launch each other by collisions; people start and stop on their own. By twelve months, babies interpret cartoons of moving dots as if the dots were seeking goals. Read more at location 6658
Philosophers say that the meaning of a natural-kind term comes from an intuition of a hidden trait or essence that the members share with one another and with the first examples dubbed with the term. People don’t need to know what the essence is, just that there is one. Read more at location 6685
If the driving intuition behind folk physics is the continuous solid object, and the driving intuition behind animacy is an internal and renewable source of oomph, then the driving intuition behind natural kinds is a hidden essence. Read more at location 6694
One of Darwin’s best arguments for evolution was that it explained why living things are hierarchically grouped. The tree of life is a family tree. The members of a species seem to share an essence because they are descendants of a common ancestor that passed it on. Species fall into groups within groups because they diverged from even earlier common ancestors. Embryonic and internal features are more sensible criteria than surface appearance because they better reflect degree of relatedness. Darwin had to fight his contemporaries’ intuitive essentialism because, taken to an extreme, it implied that species could not change. A reptile has a reptilian essence and can no more evolve into a bird than the number seven can evolve into an even number. Read more at location 6713
Today we have gone to the other extreme, and in modern academic life “essentialist” is just about the worst thing you can call someone. In the sciences, essentialism is tantamount to creationism. In the humanities, the label implies that the person subscribes to insane beliefs such as that the sexes are not socially constructed, there are universal human emotions, a real world exists, and so on. And in the social sciences, “essentialism” has joined “reductionism,” “determinism,” and “reification” as a term of abuse hurled at anyone who tries to explain human thought and behavior rather than redescribe it. I think it is unfortunate that “essentialism” has become an epithet, because at heart it is just the ordinary human curiosity to find out what makes natural things work. Read more at location 6722
Daniel Dennett proposes that the mind adopts a “design stance” when dealing with artifacts, complementing its “physical stance” for objects like rocks and its “intentional stance” for minds. Read more at location 6785
We are all psychologists. We analyze minds not just to follow soap-opera connivings but to understand the simplest human actions. Read more at location 6794
The skills behind mind reading are first exercised in the crib. Two-month-olds stare at eyes; six-month-olds know when they’re staring back; one-year-olds look at what a parent is staring at, and check a parent’s eyes when they are uncertain why the parent is doing something. Between eighteen and twenty-four months, children begin to separate the contents of other people’s minds from their own beliefs. They show that ability off in a deceptively simple feat: pretending. When a toddler plays along with his mother who tells him the phone is ringing and hands him a banana, he is separating the contents of their pretense (the banana is a telephone) from the contents of his own belief (the banana is a banana). Two-year-olds use mental verbs like see and want, and three-year-olds use verbs like think, know, and remember. Read more at location 6818
A TRIVIUM
The medieval curriculum comprised seven liberal arts, divided into the lower-level trivium (grammar, logic, and rhetoric) and the upper-level quadrivium (geometry, astronomy, arithmetic, and music). Trivium originally meant three roads, then it meant crossroads, then commonplace (since common people hang around crossroads), and finally trifling or immaterial. The etymology is, in a sense, apt: with the exception of astronomy, none of the liberal arts is about anything. Read more at location 6880
Logic, in the technical sense, refers not to rationality in general but to inferring the truth of one statement from the truth of other statements based only on their form, not their content. Read more at location 6889
People surely do use some kind of logic. All languages have logical terms like not, and, same, equivalent, and opposite. Children use and, not, or, and if appropriately before they turn three, not only in English but in half a dozen other languages that have been studied. Logical inferences are ubiquitous in human thought, particularly when we understand language. Read more at location 6904
One reason is that logical words in everyday languages like English are ambiguous, often denoting several formal logical concepts. The English word or can sometimes mean the logical connective OR (A or B or both) and can sometimes mean the logical connective XOR (exclusive or: A or B but not both). The context often makes it clear which one the speaker intended, but in bare puzzles coming out of the blue, readers can make the wrong guess. Read more at location 6925
So is the mind logical in the logician’s sense? Sometimes yes, sometimes no. A better question is, Is the mind well-designed in the biologist’s sense? Here the “yes” can be a bit stronger. Logic by itself can spin off trivial truths and miss consequential ones. The mind does seem to use logical rules, but they are recruited by the processes of language understanding, mixed with world knowledge, and supplemented or superseded by special inference rules appropriate to the content. Read more at location 6981
Mathematics is part of our birthright. One-week-old babies perk up when a scene changes from two to three items or vice versa. Infants in their first ten months notice how many items (up to four) are in a display, and it doesn’t matter whether the items are homogeneous or heterogeneous, bunched together or spread out, dots or household objects, even whether they are objects or sounds. According to recent experiments by the psychologist Karen Wynn, five-month-old infants even do simple arithmetic. Read more at location 6986
Human adults use several mental representations of quantity. One is analogue—a sense of “how much”—which can be translated into mental images such as an image of a number line. But we also assign number words to quantities and use the words and the concepts to measure, to count more accurately, and to count, add, and subtract larger numbers. Read more at location 7000
Mac Lane suggests that “mathematics starts from a variety of human activities, disentangles from them a number of notions which are generic and not arbitrary, then formalizes these notions and their manifold interrelations.” The power of mathematics is that the formal rule systems can then “codify deeper and nonobvious properties of the various originating human activities.” Read more at location 7051
Mathematics is ruthlessly cumulative, all the way back to counting to ten. Evolutionary psychology has implications for pedagogy which are particularly clear in the teaching of mathematics. American children are among the worst performers in the industrialized world on tests of mathematical achievement. They are not born dunces; the problem is that the educational establishment is ignorant of evolution. Read more at location 7083
Setting our mental modules to work on material they were not designed for is hard. Children do not spontaneously see a string of beads as elements in a set, or points on a line as numbers. If you give them a bunch of blocks and tell them to do something together, they will exercise their intuitive physics and intuitive psychology for all they’re worth, but not necessarily their intuitive sense of number. Read more at location 7096
Mastery of mathematics is deeply satisfying, but it is a reward for hard work that is not itself always pleasurable. Without the esteem for hard-won mathematical skills that is common in other cultures, the mastery is unlikely to blossom. Sadly, the same story is being played out in American reading instruction. In the dominant technique, called “whole language,” the insight that language is a naturally developing human instinct has been garbled into the evolutionarily improbable claim that reading is a naturally developing human instinct. Old-fashioned practice at connecting letters to sounds is replaced by immersion in a text-rich social environment, and the children don’t learn to read. Read more at location 7103
**** The brain can process limited amounts of information, so instead of computing theorems it uses crude rules of thumb. One rule is: the more memorable an event, the more likely it is to happen. Read more at location 7150
The sad history of human folly and prejudice is explained by our ineptness as intuitive statisticians. Tversky and Kahneman’s demonstrations are among the most thought-provoking in psychology, and the research has drawn attention to the depressingly low intellectual quality of our public discourse about societal and personal risk. Read more at location 7155
Many events work like that. They have a characteristic life history, a changing probability of occurring over time which statisticians call a hazard function. An astute observer should commit the gambler’s fallacy and try to predict the next occurrence of an event from its history so far, a kind of statistics called time-series analysis. There is one exception: devices that are designed to deliver events independently of their history. Read more at location 7180
Indeed, calling our intuitive predictions fallacious because they fail on gambling devices is backwards. A gambling device is, by definition, a machine designed to defeat our intuitive predictions. Read more at location 7188
Our ancestors’ usable probabilities must have come from their own experience, and that means they were frequencies: over the years, five out of the eight people who came down with a purple rash died the following day. Gigerenzer, Cosmides, Tooby, and the psychologist Klaus Fiedler noticed that the medical decision problem and the Linda problem ask for single-event probabilities: how likely is that this patient is sick, how likely is it that Linda is a bankteller. A probability instinct that worked in relative frequencies might find the questions beyond its ken. There’s only one Linda, and either she is a bankteller or she isn’t. “The probability that she is a bankteller” is uncomputable. So they gave people the vexing problems but stated them in terms of frequencies, not single-event probabilities. Read more at location 7206
Many probability theorists conclude that the probability of a single event cannot be computed; the whole business is meaningless. Single-event probabilities are “utter nonsense,” said one mathematician. They should be handled “by psychoanalysis, not probability theory,” sniffed another. Read more at location 7265
A final mind-bending ingredient of the concept of probability is the belief in a stable world. A probabilistic inference is a prediction today based on frequencies gathered yesterday. But that was then; this is now. How do you know that the world hasn’t changed in the interim? Philosophers of probability debate whether any beliefs in probabilities are truly rational in a changing world. Read more at location 7281
a species that had no instinct for probability could not learn the subject, let alone invent it. And when people are given information in a format that meshes with the way they naturally think about probability, they can be remarkably accurate. The claim that our species is blind to chance is, as they say, unlikely to be true. THE METAPHORICAL MIND Read more at location 7292
The human mind, we see, is not equipped with an evolutionarily frivolous faculty for doing Western science, mathematics, chess, or other diversions. It is equipped with faculties to master the local environment and outwit its denizens. People form concepts that find the clumps in the correlational texture of the world. They have several ways of knowing, or intuitive theories, adapted to the major kinds of entities in human experience: objects, animate things, natural kinds, artifacts, minds, and the social bonds and forces we will explore in the next two chapters. They wield inferential tools like the elements of logic, arithmetic, and probability. Read more at location 7296
The spatial metaphor is found not only in talk about changes but in talk about unchanging states. Belonging, being, and scheduling are construed as if they were landmarks situated at a place: Read more at location 7317
******* Location in space is one of the two fundamental metaphors in language, used for thousands of meanings. The other is force, agency, and causation. Read more at location 7350
Space and force pervade language. Many cognitive scientists (including me) have concluded from their research on language that a handful of concepts about places, paths, motions, agency, and causation underlie the literal or figurative meanings of tens of thousands of words and constructions, not only in English but in every other language that has been studied. Read more at location 7386
These concepts and relations appear to be the vocabulary and syntax of mentalese, the language of thought. Because the language of thought is combinatorial, these elementary concepts may be combined into more and more complex ideas. Read more at location 7389
The psychologist Melissa Bowerman discovered that preschool children spontaneously coin their own metaphors in which space and motion symbolize possession, circumstance, time, and causation: Read more at location 7415
Space and force are so basic to language that they are hardly metaphors at all, at least not in the sense of the literary devices used in poetry and prose. There is no way to talk about possession, circumstance, and time in ordinary conversation without using words like going, keeping, and being at. And the words don’t trigger the sense of incongruity that drives a genuine literary metaphor. Read more at location 7435
Once you begin to notice this pedestrian poetry, you find it everywhere. Ideas are not only food but buildings, people, plants, products, commodities, money, tools, and fashions. Love is a force, madness, magic, and war. The visual field is a container, self-esteem is a brittle object, time is money, life is a game of chance. Read more at location 7478
********** (Note: recursive mind) Educated understanding is an enormous contraption of parts within parts. Each part is built out of basic mental models or ways of knowing that are copied, bleached of their original content, connected to other models, and packaged into larger parts, which can be packaged into still larger parts without limit. Because human thoughts are combinatorial (simple parts combine) and recursive (parts can be embedded within parts), breathtaking expanses of knowledge can be explored with a finite inventory of mental tools. Read more at location 7508
6 HOTHEADS
the following summary of the amok mind-set, composed in 1968 by a psychiatrist who had interviewed seven hospitalized amoks in Papua New Guinea, is an apt description of the thoughts of mass murderers continents and decades away: I am not an important or “big man.” I possess only my personal sense of dignity. My life has been reduced to nothing by an intolerable insult. Therefore, I have nothing to lose except my life, which is nothing, so I trade my life for yours, as your life is favoured. The exchange is in my favour, so I shall not only kill you, but I shall kill many of you, and at the same time rehabilitate myself in the eyes of the group of which I am a member, even though I might be killed in the process. Read more at location 7570
Allegedly the Utku-Inuit Eskimos have no word for anger and do not feel the emotion. Tahitians supposedly do not recognize guilt, sadness, longing, or loneliness; they describe what we would call grief as fatigue, sickness, or bodily distress. Spartan mothers were said to smile upon hearing that their sons died in combat. In Latin cultures, machismo reigns, whereas the Japanese are driven by a fear of shaming the family. In interviews on language I have been asked, Who but the Jews would have a word, naches, for luminous pride in a child’s accomplishments? And does it not say something profound about the Teutonic psyche that the German language has the word Schadenfreude, pleasure in another’s misfortunes? Cultures surely differ in how often their members express, talk about, and act on various emotions. But that says nothing about what their people feel. The evidence suggests that the emotions of all normal members of our species are played on the same keyboard. Read more at location 7583
The expressions in the photographs are unmistakable. When Ekman began to present his findings at a meeting of anthropologists in the late 1960s, he met with outrage. One prominent anthropologist rose from the audience shouting that Ekman should not be allowed to continue to speak because his claims were fascist. On another occasion an African American activist called him a racist for saying that black facial expressions were no different from white ones. Ekman was bewildered because he had thought that if the work had any political moral it was unity and brotherhood. In any case, the conclusions have been replicated and are now widely accepted in some form (though there are controversies over which expressions belong on the universal list, how much context is needed to interpret them, and how reflexively they are tied to each emotion). And another observation by Darwin has been corroborated: children who are blind and deaf from birth display virtually the full gamut of emotions on their faces. Read more at location 7612
In The Language Instinct I argued that the influence of language on thought has been exaggerated, and that is all the more true for the influence of language on feeling. Read more at location 7624
**** G. K. Chesterton wrote, Man knows that there are in the soul tints more bewildering, more numberless, and more nameless than the colours of an autumn forest; . . . Yet he seriously believes that these things can every one of them, in all their tones and semitones, in all their blends and unions, be accurately represented by an arbitrary system of grunts and squeals. He believes that an ordinary civilized stockbroker can really produce out of his own inside noises which denote all the mysteries of memory and all the agonies of desire. Read more at location 7630
FEELING MACHINES
The Romantic movement in philosophy, literature, and art began about two hundred years ago, and since then the emotions and the intellect have been assigned to different realms. The emotions come from nature and live in the body. They are hot, irrational impulses and intuitions, which follow the imperatives of biology. The intellect comes from civilization and lives in the mind. It is a cool deliberator that follows the interests of self and society by keeping the emotions in check. Romantics believe that the emotions are the source of wisdom, innocence, authenticity, and creativity, and should not be repressed by individuals or society. Read more at location 7683
Most scientists tacitly accept the premises of Romanticism even when they disagree with its morals. The irrational emotions and the repressing intellect keep reappearing in scientific guises: the id and the superego, biological drives and cultural norms, the right hemisphere and the left hemisphere, the limbic system and the cerebral cortex, the evolutionary baggage of our animal ancestors and the general intelligence that propelled us to civilization. Read more at location 7692
******** I present a distinctly unromantic theory of the emotions. It combines the computational theory of mind, which says that the lifeblood of the psyche is information rather than energy, with the modern theory of evolution, which calls for reverse-engineering the complex design of biological systems. I will show that the emotions are adaptations, well-engineered software modules that work in harmony with the intellect and are indispensable to the functioning of the whole mind. The problem with the emotions is not that they are untamed forces or vestiges of our animal past; it is that they were designed to propagate copies of the genes that built them rather than to promote happiness, wisdom, or moral values. Read more at location 7696
**** The emotions are mechanisms that set the brain’s highest-level goals. Once triggered by a propitious moment, an emotion triggers the cascade of subgoals and sub-subgoals that we call thinking and acting. Because the goals and means are woven into a multiply nested control structure of subgoals within subgoals within subgoals, no sharp line divides thinking from feeling, nor does thinking inevitably precede feeling or vice versa (notwithstanding the century of debate within psychology over which comes first). Read more at location 7765
Each human emotion mobilizes the mind and body to meet one of the challenges of living and reproducing in the cognitive niche. Some challenges are posed by physical things, and the emotions that deal with them, like disgust, fear, and appreciation of natural beauty, work in straightforward ways. Others are posed by people. The problem in dealing with people is that people can deal back. The emotions that evolved in response to other people’s emotions, like anger, gratitude, shame, and romantic love, are played on a complicated chessboard, and they spawn the passion and intrigue that misleads the Romantic. Read more at location 7779
THE SUBURBAN SAVANNA
every animal is adapted to a habitat. Humans are no exception. We tend to think that animals just go where they belong, like heat-seeking missiles, but the animals must experience these drives as emotions not unlike ours. Some places are inviting, calming, or beautiful; others are depressing or scary. The topic in biology called “habitat selection” is, in the case of Homo sapiens, the same as the topic in geography and architecture called “environmental aesthetics”: what kinds of places we enjoy being in. Read more at location 7786
Homo sapiens is adapted to two habitats. One is the African savanna, in which most of our evolution took place. For an omnivore like our ancestors, the savanna is a hospitable place compared with other ecosystems. Deserts have little biomass because they have little water. Temperate forests lock up much of their biomass in wood. Rainforests—or, as they used to be called, jungles—place it high in the canopy, relegating omnivores on the ground to being scavengers who gather the bits that fall from above. But the savanna—grasslands dotted with clumps of trees—is rich in biomass, much of it in the flesh of large animals, because grass replenishes itself quickly when grazed. And most of the biomass is conveniently placed a meter or two from the ground. Savannas also offer expansive views, so predators, water, and paths can be spotted from afar. Its trees provide shade and an escape from carnivores. Our second-choice habitat is the rest of the world. Read more at location 7801
The biologist Gordon Orians, an expert on the behavioral ecology of birds, recently turned his eye to the behavioral ecology of humans. With Judith Heerwagen, Stephen Kaplan, Rachel Kaplan, and others, he argues that our sense of natural beauty is the mechanism that drove our ancestors into suitable habitats. We innately find savannas beautiful, but we also like a landscape that is easy to explore and remember, and that we have lived in long enough to know its ins and outs. In experiments on human habitat preference, American children and adults are shown slides of landscapes and asked how much they would like to visit or live in them. The children prefer savannas, even though they have never been to one. Read more at location 7816
FOOD FOR THOUGHT
Disgust is a universal human emotion, signaled with its own facial expression and codified everywhere in food taboos. Like all the emotions, disgust has profound effects on human affairs. Read more at location 7864
Judged by the standards of modern science, disgust is manifestly irrational. People who are sickened by the thought of eating a disgusting object will say it is unsanitary or harmful. But they find a sterilized cockroach every bit as revolting as one fresh from the cupboard, and if the sterilized roach is briefly dunked into a beverage, they will refuse to drink it. People won’t drink juice that has been stored in a brand-new urine collection bottle; hospital kitchens have found this an excellent way to stop pilferage. People won’t eat soup if it is served in a brand-new bedpan or if it has been stirred with a new comb or flyswatter. You can’t pay most people to eat fudge baked in the shape of dog feces or to hold rubber vomit from a novelty store between their lips. One’s own saliva is not disgusting as long as it is in one’s mouth, but most people won’t eat from a bowl of soup into which they have spat. Read more at location 7868
Most Westerners cannot stomach the thought of eating insects, worms, toads, maggots, caterpillars, or grubs, but these are all highly nutritious and have been eaten by the majority of peoples throughout history. None of our rationalizations makes sense. You say that insects are contaminated because they touch feces or garbage? But many insects are quite sanitary. Termites, for example, just munch wood, but Westerners feel no better about eating them. Compare them with chickens, the epitome of palatability (“Try it—it tastes like chicken!”), which commonly eat garbage and feces. And we all savor tomatoes made plump and juicy from being fertilized with manure. Insects carry disease? So does all animal flesh. Just do what the rest of the world does—cook them. Insects have indigestible wings and legs? Pull them off, as you do with peel-and-eat shrimp, or stick to grubs and maggots. Insects taste bad? Here is a report from a British entomologist who was studying Laotian foodways and acquired a firsthand knowledge of his subject matter: None distasteful, a few quite palatable, notably the giant waterbug. For the most part they were insipid, with a faint vegetable flavour, but would not anyone tasting bread, for instance, for the first time, wonder why we eat such a flavourless food? A toasted dungbeetle or soft-bodied spider has a nice crisp exterior and soft interior of soufflé consistency which is by no means unpleasant. Salt is usually added, sometimes chili or the leaves of scented herbs, and sometimes they are eaten with rice or added to sauces or curry. Flavour is exceptionally hard to define, but lettuce would, I think, best describe the taste of termites, cicadas, and crickets; lettuce and raw potato that of the giant Nephila spider, and concentrated Gorgonzola cheese that of the giant waterbug (Lethocerus indicus). I suffered no ill effects from the eating of these insects. Read more at location 7875
Though disgust is universal, the list of nondisgusting animals differs from culture to culture, and that implies a learning process. As every parent knows, children younger than two put everything in their mouths, and psychoanalysts have had a field day interpreting their lack of revulsion for feces. Read more at location 7918
Rozin ventured that disgust is an adaptation that deterred our ancestors from eating dangerous animal stuff. Feces, carrion, and soft, wet animal parts are home to harmful microorganisms and ought to be kept outside the body. Read more at location 7946
What about our feeling that disgusting things contaminate everything they touch? It is a straightforward adaptation to a basic fact about the living world: germs multiply. Read more at location 7956
The anthropologist Marvin Harris has shown that cultures avoid animalitos when larger animals are available, and eat them when they are not. The explanation has nothing to do with sanitation, since bugs are safer than meat. It comes from optimal foraging theory, the analysis of how animals ought to—and usually do—allocate their time to maximize the rate of nutrients they consume. Read more at location 7963
Harris observes that food taboos often make ecological and economic sense. The Hebrews and the Muslims were desert tribes, and pigs are animals of the forest. They compete with people for water and nutritious foods like nuts, fruits, and vegetables. Kosher animals, in contrast, are ruminants like sheep, cattle, and goats, which can live off scraggly desert plants. In India, cattle are too precious to slaughter because they are used for milk, manure, and pulling plows. Harris’ theory is as ingenious as the rabbis’ and far more plausible, though he admits that it can’t explain everything. Ancient tribes wandering the parched Judaean sands were hardly in danger of squandering their resources by herding shrimp and oysters, and it is unclear why the inhabitants of a Polish shtetl or a Brooklyn neighborhood should obsess over the feeding habits of desert ruminants. Read more at location 8001
Food taboos often prohibit a favorite food of a neighboring tribe; that is true, for example, of many of the Jewish dietary laws. That suggests that they are weapons to keep potential defectors in. First, they make the merest prelude to cooperation with outsiders—breaking bread together—an unmistakable act of defiance. Even better, they exploit the psychology of disgust. Taboo foods are absent during the sensitive period for learning food preferences, and that is enough to make children grow up to find them disgusting. That deters them from becoming intimate with the enemy Read more at location 8014
THE SMELL OF FEAR
Fears and phobias fall into a short and universal list. Snakes and spiders are always scary. They are the most common objects of fear and loathing in studies of college students’ phobias, and have been so for a long time in our evolutionary history. D. O. Hebb found that chimpanzees born in captivity scream in terror when they first see a snake, and the primatologist Marc Hauser found that his laboratory-bred cotton-top tamarins (a South American monkey) screamed out alarm calls when they saw a piece of plastic tubing on the floor. The reaction of foraging peoples is succinctly put by Irven DeVore: “Hunter-gatherers will not suffer a snake to live.” In cultures that revere snakes, people still treat them with great wariness. Even Indiana Jones was afraid of them! The other common fears are of heights, storms, large carnivores, darkness, blood, strangers, confinement, deep water, social scrutiny, and leaving home alone. The common thread is obvious. These are the situations that put our evolutionary ancestors in danger. Spiders and snakes are often venomous, especially in Africa, and most of the others are obvious hazards to a forager’s health, or, in the case of social scrutiny, status. Read more at location 8033
The psychiatrist Isaac Marks has shown that people react in different ways to different frightening things, each reaction appropriate to the hazard. An animal triggers an urge to flee, but a precipice causes one to freeze. Social threats lead to shyness and gestures of appeasement. People really do faint at the sight of blood, because their blood pressure drops, presumably a response that would minimize the further loss of one’s own blood. The best evidence that fears are adaptations and not just bugs in the nervous system is that animals that have evolved on islands without predators lose their fear and are sitting ducks for any invader—hence the expression “dead as a dodo.” Read more at location 8045
creatures cannot be conditioned to fear just any old thing. Children are nervous about rats, and rats are nervous about bright rooms, before any conditioning begins, and they easily associate them with danger. Change the white rat to some arbitrary object, like opera glasses, and the child never learns to fear it. Read more at location 8061
THE HAPPINESS TREADMILL
People do come to feel the same across an astonishing range of good and bad fortunes. But the baseline that people adapt to, on average, is not misery but satisfaction. (The exact baseline differs from person to person and is largely inherited.) The psychologists David Myers and Ed Diener have found that about eighty percent of people in the industrialized world report that they are at least “fairly satisfied with life,” and about thirty percent say they are “very happy.” (As far as we can tell, the reports are sincere.) The percentages are the same for all ages, for both sexes, for blacks and whites, and over four decades of economic growth. Read more at location 8155
Within an industrialized country, money buys only a little happiness: the correlation between wealth and satisfaction is positive but small. Lottery winners, after their jolt of happiness has subsided, return to their former emotional state. On the brighter side, so do people who have suffered terrible losses, such as paraplegics and survivors of the Holocaust. Read more at location 8162
There are twice as many negative emotions (fear, grief, anxiety, and so on) as positive ones, and losses are more keenly felt than equivalent gains. The tennis star Jimmy Connors once summed up the human condition: “I hate to lose more than I like to win.” The asymmetry has been confirmed in the lab by showing that people will take a bigger gamble to avoid a sure loss than to improve on a sure gain, and by showing that people’s mood plummets more when imagining a loss in their lives (for example, in course grades, or in relationships with the opposite sex) than it rises when imagining an equivalent gain. Read more at location 8170
**** the study of happiness often sounds like a sermon for traditional values. The numbers show that it is not the rich, privileged, robust, or good-looking who are happy; it is those who have spouses, friends, religion, and challenging, meaningful work. The findings can be overstated, because they apply to averages, not individuals, and because cause and effect are hard to tease apart: being married might make you happy, but being happy might help you get and stay married. But Campbell echoed millennia of wise men and women when he summed up the research: “The direct pursuit of happiness is a recipe for an unhappy life.” Read more at location 8181
I AND THOU
Biologists often describe these acts as self-interested behavior, but what causes behavior is the activity of the brain, especially the circuitry for emotions and other feelings. Animals behave selfishly because of how their emotion circuits are wired. My full stomach, my warmth, my orgasms, feel better to me than yours do, and I want mine, and will seek mine, more than yours. Read more at location 8288
When an animal behaves to benefit another animal at a cost to itself, biologists call it altruism. When altruism evolves because the altruist is related to the beneficiary so the altruism-causing gene benefits itself, they call it kin selection. But when we look into the psychology of the animal doing the behaving, we can give the phenomenon another name: love. The essence of love is feeling pleasure in another’s well-being and pain in its harm. These feelings motivate acts that benefit the loved one, like nurturing, feeding, and protecting. We now understand why many animals, including humans, love their children, parents, grandparents, grandchildren, siblings, aunts, uncles, nephews, nieces, and cousins: people helping relatives equals genes helping themselves. The sacrifices made for love are modulated by the degree of relatedness: people make more sacrifices for their children than for their nephews and nieces. Read more at location 8327
Many people think that the theory of the selfish gene says that “animals try to spread their genes.” That misstates the facts and it misstates the theory. Animals, including most people, know nothing about genetics and care even less. People love their children not because they want to spread their genes (consciously or unconsciously) but because they can’t help it. That love makes them try to keep their children warm, fed, and safe. What is selfish is not the real motives of the person but the metaphorical motives of the genes that built the person. Genes “try” to spread themselves by wiring animals’ brains so the animals love their kin and try to keep warm, fed, and safe. Read more at location 8339
Humans are, of course, a brainy species, and are zoologically unusual in how often they help unrelated individuals (Chapter 3). Our lifestyles and our minds are particularly adapted to the demands of reciprocal altruism. People have food, tools, help, and information to trade. With language, information is an ideal trade good because its cost to the giver—a few seconds of breath—is minuscule compared with the benefit to the recipient. Read more at location 8385
the human mind is equipped with goal-setting demons that regulate the doling out of favors; as with kin-directed altruism, reciprocal altruism is behaviorist shorthand for a set of thoughts and emotions. Trivers and the biologist Richard Alexander have shown how the demands of reciprocal altruism are probably the source of many human emotions. Collectively they make up a large part of the moral sense. The minimal equipment is a cheater-detector and a tit-for-tat strategy that begrudges a gross cheater further help. A gross cheater is one who refuses to reciprocate at all, or who returns so little that the altruist gets back less than the cost of the initial favor. Read more at location 8390
Here is how Trivers reverse-engineered the moralistic emotions as strategies in the reciprocity game. (His assumptions about the causes and consequences of each emotion are well supported by the literature in experimental social psychology and by studies of other cultures, though they are hardly necessary, as real-life examples no doubt will flood into mind.) Liking is the emotion that initiates and maintains an altruistic partnership. It is, roughly, a willingness to offer someone a favor, and is directed to those who appear willing to offer favors back. We like people who are nice to us, and we are nice to people whom we like. Anger protects a person whose niceness has left her vulnerable to being cheated. When the exploitation is discovered, the person classifies the offending act as unjust and experiences indignation and a desire to respond with moralistic aggression: punishing the cheater by severing the relationship and sometimes by hurting him. Many psychologists have remarked that anger has moral overtones; almost all anger is righteous anger. Furious people feel they are aggrieved and must redress an injustice. Gratitude calibrates the desire to reciprocate according to the costs and benefits of the original act. We are grateful to people when their favor helps us a lot and has cost them a lot. Sympathy, the desire to help those in need, may be an emotion for earning gratitude. If people are most grateful when they most need the favor, a person in need is an opportunity to make an altruistic act go farthest. Guilt can rack a cheater who is in danger of being found out. H. L. Mencken defined conscience as “the inner voice which warns us that someone might be looking.” If the victim responds by cutting off all future aid, the cheater will have paid dearly. He has an interest in preventing the rupture by making up for the misdeed and keeping it from happening again. People feel guilty about private transgressions because they may become public; confessing a sin before it is discovered is evidence of sincerity and gives the victim better grounds to maintain the relationship. Shame, the reaction to a transgression after it has been discovered, evokes a public display of contrition, no doubt for the same reason. Lily Tomlin said, “I try to be cynical, but it’s hard to keep up.” Trivers notes that once these emotions evolved, people had an incentive to mimic them to take advantage of other people’s reactions to the real thing. Read more at location 8406
The next round in this evolutionary contest is, of course, developing an ability to discriminate between real emotions and sham emotions. We get the evolution of trust and distrust. When we see someone going through the motions of generosity, guilt, sympathy, or gratitude rather than showing signs of the genuine emotion, we lose the desire to cooperate. Read more at location 8433
Perhaps we should rejoice that people’s emotions aren’t designed for the good of the group. Often the best way to benefit one’s group is to displace, subjugate, or annihilate the group next door. Ants in a colony are closely related, and each is a paragon of unselfishness. That’s why ants are one of the few kinds of animal that wage war and take slaves. When human leaders have manipulated or coerced people into submerging their interests into the group’s, the outcomes are some of history’s worst atrocities. Read more at location 8458
To defend yourself against threats, make it impossible for the threatener to make you an offer you can’t refuse. Again, freedom, information, and rationality are handicaps. Read more at location 8563
The passions are no vestige of an animal past, no wellspring of creativity, no enemy of the intellect. The intellect is designed to relinquish control to the passions so that they may serve as guarantors of its offers, promises, and threats against suspicions that they are lowballs, double-crosses, and bluffs. The apparent firewall between passion and reason is not an ineluctable part of the architecture of the brain; it has been programmed in deliberately, because only if the passions are in control can they be credible guarantors. Read more at location 8590
The lust for revenge is a particularly terrifying emotion. All over the world, relatives of the slain fantasize day and night about the bittersweet moment when they might avenge a life with a life and find peace at last. The emotion strikes us as primitive and dreadful because we have contracted the government to settle our scores for us. But in many societies an irresistible thirst for vengeance is one’s only protection against deadly raids. Individuals may differ in the resolve with which they will suffer costs to carry out vengeance. Since that resolve is an effective deterrent only if it is advertised, it is accompanied by the emotion traditionally referred to as honor: the desire to publicly avenge even minor trespasses and insults. Read more at location 8603
Facial expressions are useful only if they are hard to fake. As a matter of fact, they are hard to fake. People don’t really believe that the grinning flight attendant is happy to see them. That is because a social smile is formed with a different configuration of muscles from the genuine smile of pleasure. A social smile is executed by circuits in the cerebral cortex that are under voluntary control; a smile of pleasure is executed by circuits in the limbic system and other brain systems and is involuntary. Anger, fear, and sadness, too, recruit muscles that can’t be controlled voluntarily, and the genuine expressions are hard to fake, though we can pantomime an approximation. Read more at location 8635
FOOLS FOR LOVE
Unsentimental social scientists and veterans of the singles scene agree that dating is a marketplace. People differ in their value as potential marriage partners. Almost everyone agrees that Mr. or Ms. Right should be good-looking, smart, kind, stable, funny, and rich. People shop for the most desirable person who will accept them, and that is why most marriages pair a bride and a groom of approximately equal desirability. Mate-shopping, however, is only part of the psychology of romance; it explains the statistics of mate choice, but not the final pick. Read more at location 8678
THE SOCIETY OF FEELINGS
the whole person has many goals, like food, sex, and safety, and that requires a division of labor among mental agents with different priorities and kinds of expertise. The agents are bound by an entente that benefits the whole person over a lifetime, but over the short term the agents may outwit one another with devious tactics. Self-control is unmistakably a tactical battle between parts of the mind. Schelling observes that the tactics people use to control themselves are interchangeable with the tactics they use to control others. Read more at location 8730
**** (Note: interesting, true) The self that wants a trim body outwits the self that wants dessert by throwing out the brownies at the opportune moment when it is in control. So we do seem to use paradoxical tactics against ourselves. The agent in control at one time makes a voluntary but irreversible sacrifice of freedom of choice for the whole body, and gets its way in the long run. Read more at location 8736
One more speculation on the battle inside the head. No one knows what, if anything, grief is for. Obviously the loss of a loved one is unpleasant, but why should it be devastating? Why the debilitating pain that stops people from eating, sleeping, resisting diseases, and getting on with life? Jane Goodall describes a young chimp, Flint, who after the death of his beloved mother became depressed and died himself as if of a broken heart. Some have suggested that grief is an enforced interlude for reassessment. Read more at location 8744
grief is the other side of love. And there may lie the answer. Perhaps grief is an internal doomsday machine, pointless once it goes off, useful only as a deterrent. Read more at location 8756
KIDDING OURSELVES
Our confabulations, not coincidentally, present us in the best light. Literally hundreds of experiments in social psychology say so. The humorist Garrison Keillor describes the fictitious community of Lake Wobegon, “where the women are strong, the men are good-looking, and all the children are above average.” Indeed, most people claim they are above average in any positive trait you name: leadership, sophistication, athletic prowess, managerial ability, even driving skill. They rationalize the boast by searching for an aspect of the trait that they might in fact be good at. The slow drivers say they are above average in safety, the fast ones that they are above average in reflexes. More generally, we delude ourselves about how benevolent and how effective we are, a combination that social psychologists call beneffectance. When subjects play games that are rigged by the experimenter, they attribute their successes to their own skill and their failures to the luck of the draw. When they are fooled in a fake experiment into thinking they have delivered shocks to another subject, they derogate the victim, implying that he deserved the punishment. Everyone has heard of “reducing cognitive dissonance,” in which people invent a new opinion to resolve a contradiction in their minds. Read more at location 8783
**** When does a negative remark sting, cut deep, hit a nerve? When some part of us knows it is true. If every part knew it was true, the remark would not sting; it would be old news. If no part thought it was true, the remark would roll off; we could dismiss it as false. Read more at location 8800
Trivers writes, Consider an argument between two closely bound people, say, husband and wife. Both parties believe that one is an altruist—of long standing, relatively pure in motive, and much abused—while the other is characterized by a pattern of selfishness spread over hundreds of incidents. They only disagree over who is altruistic and who selfish. It is noteworthy that the argument may appear to burst forth spontaneously, with little or no preview, yet as it rolls along, two whole landscapes of information processing appear to lie already organized, waiting only for the lightning of anger to show themselves. Read more at location 8826
Note: **** Edit
thanks to the complexity of our minds, we need not be perpetual dupes of our own chicanery. The mind has many parts, some designed for virtue, some designed for reason, some clever enough to outwit the parts that are neither. One self may deceive another, but every now and then a third self sees the truth. Read more at location 8837
7 FAMILY VALUES
Universal harmony was a style as ephemeral as the bell-bottoms, a status symbol that distanced them from rednecks, jocks, and the less hip preppies. As the post-60s rock musician Elvis Costello asked, “Was it a millionaire who said ‘Imagine no possessions’?” The Woodstock Nation was not the first utopian dream to be shattered. The free-love communes of nineteenth-century America collapsed from sexual jealousy and the resentment of both sexes over the leaders’ habit of accumulating young mistresses. The socialist utopias of the twentieth century became repressive empires led by men who collected Cadillacs and concubines. Read more at location 8867
In Human Universals, the anthropologist Donald Brown has assembled the traits that as far as we know are found in all human cultures. They include prestige and status, inequality of power and wealth, property, inheritance, reciprocity, punishment, sexual modesty, sexual regulations, sexual jealousy, a male preference for young women as sexual partners, a division of labor by sex (including more child care by women and greater public political dominance by men), hostility to other groups, and conflict within the group, including violence, rape, and murder. The list should come as no surprise to anyone familiar with history, current events, or literature. There are a small number of plots in the world’s fiction and drama, Read more at location 8876
it is genes, not organisms, that must compete or die; sometimes the genes’ best strategy is to design organisms that cooperate, and yes, even smile on their brother and love one another. Natural selection does not forbid cooperation and generosity; it just makes them difficult engineering problems, like stereoscopic vision. Read more at location 8897
The observation that conflict is part of the human condition, banal though it is, contradicts fashionable beliefs. One is expressed in the gluey metaphor of social relations as attachment, bonding, and cohesion. Another is the assumption that we unthinkingly play out the roles society assigns to us, and that social reform is a matter of rewriting the roles. I suspect that if you pressed many academics and social critics you would find views no less utopian than those of Charles Reich. If the mind is an organ of computation engineered by natural selection, our social motives should be strategies that are tailored to the tournaments we play in. People should have distinct kinds of thoughts and feelings about kin and non-kin, and about parents, children, siblings, dates, spouses, acquaintances, friends, rivals, allies, and enemies. Read more at location 8918
KITH AND KIN
The kinship metaphors have a simple message: treat certain people as kindly as you treat your blood relatives. We all understand the presupposition. The love of kin comes naturally; the love of non-kin does not. That is the fundamental fact of the social world, steering everything from how we grow up to the rise and fall of empires and religions. The explanation is straightforward. Relatives share genes to a greater extent than nonrelatives, so if a gene makes an organism benefit a relative (say, by feeding or protecting it), it has a good chance of benefiting a copy of itself. With that advantage, genes for helping relatives will increase in a population over the generations. The vast majority of altruistic acts in the animal kingdom benefit the actor’s kin. Read more at location 8931
Homo sapiens is obsessed with kinship. All over the world, when people are asked to talk about themselves, they begin with their parentage and family ties, and in many societies, especially foraging groups, people rattle off endless genealogies. For adoptees, childhood refugees, or descendants of slaves, curiosity about biological kin can drive a lifelong quest. Read more at location 8953
Families are important in all societies, and their core is a mother and her biological children. All societies have marriage. A man and a woman enter a publicly acknowledged alliance whose primary goal is children; the man has a “right” of exclusive sexual access to the woman; and they both are obligated to invest in their children. The details vary, often according to the patterns of blood relationships in the society. Read more at location 8979
In one study of emotionally healthy middle-class families in the United States, only half of the stepfathers and a quarter of the stepmothers claimed to have “parental feeling” toward their stepchildren, and fewer still claimed to “love” them. The enormous pop-psychology literature on reconstituted families is dominated by one theme: coping with antagonisms. Many professionals now advise warring families to give up the ideal of duplicating a biological family. Daly and Wilson found that stepparenthood is the strongest risk factor for child abuse ever identified. In the case of the worst abuse, homicide, a stepparent is forty to a hundred times more likely than a biological parent to kill a young child, even when confounding factors—poverty, the mother’s age, the traits of people who tend to remarry—are taken into account. Stepparents are surely no more cruel than anyone else. Parenthood is unique among human relationships in its one-sidedness. Parents give; children take. For obvious evolutionary reasons, people are wired to want to make these sacrifices for their own children but not for anyone else. Read more at location 9020
The indifference, even antagonism, of stepparents to stepchildren is simply the standard reaction of a human to another human. It is the endless patience and generosity of a biological parent that is special. This point should not diminish our appreciation of the many benevolent stepparents; if anything, it should enhance it, for they are especially kind and self-sacrificing people. Read more at location 9031
Relatives are natural allies, and before the invention of agriculture and cities, societies were organized around clans of them. One of the fundamental questions of anthropology is how foraging people divide themselves into bands or villages, typically with about fifty members though varying with the time and place. Napoleon Chagnon amassed meticulous genealogies that link thousands of members of the Yanomamö, the foraging and horticultural people of the Amazon rainforest whom he has studied for thirty years. He showed how kinship is the cement that keeps villages together. Close kin fight each other less often and come to each other’s aid in fights more often. Read more at location 9055
The journalist Ferdinand Mount has documented how every political and religious movement in history has sought to undermine the family. The reasons are obvious. Not only is the family a rival coalition competing for a person’s loyalties, but it is a rival with an unfair advantage: relatives innately care for one another more than comrades do. They bestow nepotistic benefits, forgive the daily frictions that strain other organizations, and stop at nothing to avenge wrongs against a member. Leninism, Nazism, and other totalitarian ideologies always demand a new loyalty “higher” than, and contrary to, family ties. So have religions from early Christianity to the Moonies (“We’re your family now!”). In Matthew 10:34–37, Jesus says: Think not that I am come to send peace on earth: I came not to send peace, but a sword. For I am come to set a man at variance against his father, and the daughter against her mother, and the daughter in law against her mother in law. And a man’s foes shall be they of his own household. He that loveth father or mother more than me is not worthy of me: and he that loveth son or daughter more than me is not worthy of me. When Jesus said “Suffer the little children to come unto me,” he was saying that they should not go unto their parents. Read more at location 9126
PARENTS AND CHILDREN
the first child sees it differently. He shares fifty percent of his genes with his younger sibling, but he shares one hundred percent of his genes with himself. As far as he is concerned, the parent should continue to invest in him until the benefit to a younger sibling is greater than twice the cost to him. The genetic interests of the parent and the child diverge. Each child should want more parental care than the parent is willing to give, because parents want to invest in all of their offspring equally (relative to their needs), whereas each child wants more of the investment for himself. The tension is called parent-offspring conflict. In essence it is sibling rivalry: siblings compete among themselves for their parents’ investment, whereas the parents would be happiest if each accepted a share proportional to his or her needs. Read more at location 9172
The ethologist Konrad Lorenz pointed out that the geometry of babies—a large head, a bulbous cranium, large eyes low in the face, pudgy cheeks, and short limbs—elicits tenderness and affection. The geometry comes from the baby-assembly process. The head end grows fastest in the womb, and the other end catches up after birth; babies grow into their brain and their eyes. Lorenz showed that animals with that geometry, such as ducks and rabbits, strike people as cute. Read more at location 9240
**** The idea that parents shape their children is so ingrained that most people don’t even realize it is a testable hypothesis and not a self-evident truth. The hypothesis has now been tested, and the outcome is one of the most surprising in the history of psychology. Personalities differ in at least five major ways: whether a person is sociable or retiring (extroversion-introversion), whether a person worries constantly or is calm and self-satisfied (neuroticism-stability), whether the person is courteous and trusting or rude and suspicious (agreeableness-antagonism), whether a person is careful or careless (conscientiousness-undirectedness), and whether a person is daring or conforming (openness-nonopenness). Read more at location 9305
**** (Note: genetic determinism of sorts) Where do these traits come from? If they are genetic, identical twins should share them, even if they were separated at birth, and biological siblings should share them more than adoptive siblings do. If they are a product of socialization by parents, adoptive siblings should share them, and twins and biological siblings should share them more when they grow up in the same home than when they grow up in different homes. Dozens of studies have tested these kinds of predictions on thousands of people in many countries. The studies have looked not only at these personality traits but at actual outcomes in life such as divorce and alcoholism. The results are clear and replicable, and they contain two shockers. One result has become well known. Much of the variation in personality—about fifty percent—has genetic causes. Identical twins separated at birth are alike; biological siblings raised together are more alike than adopted siblings. That means that the other fifty percent must come from the parents and the home, right? Wrong! Being brought up in one home versus another accounts, at most, for five percent of the differences among people in personality. Identical twins separated at birth are not only similar; they are virtually as similar as identical twins raised together. Adoptive siblings in the same home are not just different; they are about as different as two children plucked from the population at random. The biggest influence that parents have on their children is at the moment of conception. (I hasten to add that parents are unimportant only when it comes to differences among them and differences among their grown children. Anything that all normal parents do that affects all children is not measured in these studies. Read more at location 9310
No one knows where the other forty-five percent of the variation comes from. Perhaps personality is shaped by unique events impinging on the growing brain: Read more at location 9326
Judith Harris has amassed evidence that children everywhere are socialized by their peer group, not by their parents. At all ages children join various play groups, circles, gangs, packs, cliques, and salons, and they jockey for status within them. Each is a culture that absorbs some customs from the outside and generates many of its own. Children’s cultural heritage—the rules of Ringolevio, the melody and lyrics of the nyah-nyah song, the belief that if you kill someone you legally have to pay for his gravestone—is passed from child to child, sometimes for thousands of years. As children grow up they graduate from group to group and eventually join adult groups. Prestige at one level gives one a leg up at the next; most significantly, the leaders of young adolescent cliques are the first to date. At all ages children are driven to figure out what it takes to succeed among their peers and to give these strategies precedence over anything their parents foist on them. Weary parents know they are no match for a child’s peers, and rightly obsess over the best neighborhood in which to bring their children up. Read more at location 9335
Evolutionary thinking is often put down as a “reductionistic approach” that aims to redefine all social and political issues as technical problems of biology. The criticism has it backwards. The evolution-free discourse that has prevailed for decades has treated childrearing as a technological problem of determining which practices grow the best children. Trivers’ insight is that decisions about childrearing are inherently about how to allocate a scarce resource—the parents’ time and effort—to which several parties have a legitimate claim. As such, childrearing will always be partly a question of ethics and politics, not just of psychology and biology.
BROTHERS AND SISTERS
Children are exquisitely sensitive to favoritism, right through adulthood and after the parents’ deaths. They should calculate how to make the best of the hand that nature dealt them and of the dynamics of the poker game they were born into. The historian Frank Sulloway has argued that the elusive nongenetic component of personality is a set of strategies to compete with siblings for parental investment, and that is why children in the same family are so different. Each child develops in a different family ecology and forms a different plan for getting out of childhood alive. Read more at location 9409
the first-born sees the newcomer as a usurper. Thus he (or she) should identify with his parents, who have aligned their interests with his, and should resist changes to the status quo, which has always served him well. He should also learn how best to wield the power that fate has granted him. In sum, a first-born should be a conservative and a bully. Second-born children have to cope in a world that contains this obsequious martinet. Since they cannot get their way with thuggery and toadyism, they must cultivate the opposite strategies. They should become appeasers and cooperators. And with less at stake in the status quo, they should be receptive to change. (These dynamics depend, too, on the innate components of the personalities of the siblings and on their sex, size, and spacing; your mileage may vary.) Later-borns have to be flexible for another reason. Parents invest in the children who show the most promise of success in the world. The first-born has staked a claim in whatever personal and technical skills she is best at. There’s no point in a later-born competing on that turf; any success would have to come at the expense of the older and more experienced sibling, and he (or she) would be forcing his parents to pick a winner, with daunting odds against him. Instead, he should find a different niche in which to excel. That gives his parents an opportunity to diversify their investments, because he complements his older sibling’s skills in competition outside the family. Siblings in a family exaggerate their differences for the same reason that species in an ecosystem evolve into different forms: each niche supports a single occupant. Read more at location 9417
Sulloway analyzed data on 120,000 people from 196 adequately controlled studies of birth order and personality. As he predicted, first-borns are less open (more conforming, traditional, and closely identified with parents), more conscientious (more responsible, achievement-oriented, serious, and organized), more antagonistic (less agreeable, approachable, popular, and easygoing), and more neurotic (less well-adjusted, more anxious). They are also more extroverted (more assertive, more leaderly), though the evidence is cloudy because they are more serious, which makes them seem more introverted. Read more at location 9430
Sulloway analyzed biographical data from 3,894 scientists who had voiced opinions on radical scientific revolutions (such as the Copernican revolution and Darwinism), 893 members of the French National Convention during the Terror of 1793–1794, more than seven hundred protagonists in the Protestant Reformation, and the leaders of sixty-two American reform movements such as the abolition of slavery. In each of these shake-ups, later-borns were more likely to support the revolution, first-borns were more likely to be reactionary. The effects are not by-products of family size, family attitudes, social class, or other confounding factors. When evolutionary theory was first proposed and still incendiary, later-borns were ten times as likely to support it as first-borns. Other alleged causes of radicalism, such as nationality and social class, have only minor effects. Read more at location 9436
**** The discovery that children brought up in the same family are no more similar than they would be if they had been brought up on different planets shows how poorly we understand the development of personality. All we know is that cherished ideas about the influence of parents are wrong. The most promising hypotheses, I suspect, will come from recognizing that childhood is a jungle and that the first problem children face in life is how to hold their own among siblings and peers. Read more at location 9448
MEN AND WOMEN
Even the happiest couples can fight like cats and dogs, and today fifty percent of marriages in the United States end in divorce. George Bernard Shaw wrote, “When we want to read of the deeds that are done for love, whither do we turn? To the murder column.” Conflict between men and women, sometimes deadly, is universal, and it suggests that sex is not a bonding force in human affairs but a divisive one. Once again, that banality must be stated because the conventional wisdom denies it. One of the utopian ideals of the 1960s, reiterated ever since by sex gurus like Dr. Ruth, is the intensely erotic, mutually enjoyable, guilt-free, emotionally open, lifelong monogamous pair-bond. The alternative from the counterculture was the intensely erotic, mutually enjoyable, guilt-free, emotionally open, round-robin orgy. Both were attributed to our hominid ancestors, to earlier stages of civilization, or to primitive tribes still out there somewhere. Both are as mythical as the Garden of Eden. The battle between the sexes is not just a skirmish in the war between unrelated individuals but is fought in a different theater, for reasons first explained by Donald Symons. “With respect to human sexuality,” he wrote, “there is a female human nature and a male human nature, and these natures are extraordinarily different. . . . Men and women differ in their sexual natures because throughout the immensely long hunting and gathering phase of human evolutionary history the sexual desires and dispositions that were adaptive for either sex were for the other tickets to reproductive oblivion.” Read more at location 9563
An evolutionary arms race goes on between hosts and pathogens, though a better analogy might be an escalating contest between lockpickers and locksmiths. Germs are small, and they evolve diabolical tricks for infiltrating and hijacking the machinery of the cells, for skimming off its raw materials, and for passing themselves off as the body’s own tissues to escape the surveillance of the immune system. Read more at location 9592
Now, if an organism is asexual, once the pathogens crack the safe of its body they also have cracked the safes of its children and siblings. Sexual reproduction is a way of changing the locks once a generation. By swapping half the genes out for a different half, an organism gives its offspring a head start in the race against the local germs. Its molecular locks have a different combination of pins, so the germs have to start evolving new keys from scratch. Read more at location 9598
In each pair of parents, one “agrees” to unilateral disarmament. It contributes a cell that provides no metabolic machinery, just naked DNA for the new nucleus. The species reproduces by fusing a big cell that contains a half-set of genes plus all the necessary machinery with a small cell that contains a half-set of genes and nothing else. The big cell is called an egg and the small cell is called a sperm. Read more at location 9609
A few animals, hermaphrodites, put both kinds of organs in every individual, but most specialize further and divide up into two kinds, each allocating all their reproductive tissue to one kind of organ or the other. They are called males and females. Trivers has worked out how all the prominent differences between males and females stem from the difference in the minimum size of their investment in offspring. Read more at location 9618
The investment can be energy, nutrients, time, or risk. The female, by definition, begins with a bigger investment—the larger sex cell—and in most species commits herself to even more. The male contributes a puny package of genes and usually leaves it at that. Read more at location 9622
The greater-investing sex chooses, the lesser-investing sex competes. Relative investment, then, is the cause of sex differences. Everything else—testosterone, estrogen, penises, vaginas, Y chromosomes, X chromosomes—is secondary. Males compete and females choose only because the slightly bigger investment in an egg that defines being female tends to get multiplied by the rest of the animal’s reproductive habits. In a few species, the whole animal reverses the initial difference in investment between egg and sperm, and in those cases females should compete and males should choose. Sure enough, these exceptions prove the rule. In some fishes, the male broods the young in a pouch. In some birds, the male sits on the egg and feeds the young. In those species, the females are aggressive and try to court the males, who select partners carefully. In a typical mammal, though, the female does almost all the investing. Mammals have opted for a body plan in which the female carries the fetus inside her, nourishes it with her blood, and nurses and protects it after it is born until the offspring has grown big enough to fend for itself. The male contributes a few seconds of copulation and a sperm cell weighing one ten-trillionth of a gram. Not surprisingly, male mammals compete for opportunities to have sex with female mammals. Read more at location 9636
We are mammals, so a woman’s minimum parental investment is much larger than a man’s. She contributes nine months of pregnancy and (in a natural environment) two to four years of nursing. He contributes a few minutes of sex and a teaspoon of semen. Men are about 1.15 times as large as women, which tells us that they have competed in our evolutionary history, with some men mating with several women and some men mating with none. Unlike gibbons, who are isolated, monogamous, and relatively sexless, and gorillas, who are clustered, harem-forming, and relatively sexless, we are gregarious, with men and women living together in large groups and constantly facing opportunities to couple. Men have smaller testicles for their body size than chimpanzees but bigger ones than gorillas and gibbons, suggesting that ancestral women were not wantonly promiscuous but were not always monogamous either. Children are born helpless and remain dependent on adults for a large chunk of the human lifespan, presumably because knowledge and skills are so important to the human way of life. So children need parental investment, and men, because they get meat from hunting and other resources, have something to invest. Men far exceed the minimum investment that their anatomy would let them get away with: they feed, protect, and teach their children. Read more at location 9705
Until recently, men hunted and women gathered. Women were married soon after puberty. There was no contraception, no institutionalized adoption by nonrelatives, and no artificial insemination. Sex meant reproduction and vice versa. There was no food from domesticated plants or animals, so there was no baby formula; all children were breast-fed. There was also no paid day care, and no househusbands; babies and toddlers hung around with their mothers and other women. These conditions persisted through ninety-nine percent of our evolutionary history and have shaped our sexuality. Our sexual thoughts and feelings are adapted to a world in which sex led to babies, whether or not we want to make babies now. And they are adapted to a world in which children were a mother’s problem more than a father’s. Read more at location 9718
Many male mammals are indefatigable when a new willing female is available after each copulation. They cannot be fooled by the experimenter cloaking a previous partner or masking her scent. This shows, incidentally, that male sexual desire is not exactly “undiscriminating.” Males may not care what kind of female they mate with, but they are hypersensitive to which female they mate with. It is another example of the logical distinction between individuals and categories that I argued was so important when criticizing associationism Read more at location 9765
The desire for sexual variety is an unusual adaptation, for it is insatiable. Most commodities of fitness show diminishing returns or an optimal level. People do not seek mass quantities of air, food, and water, and they want to be not too hot and not too cold but just right. But the more women a man has sex with, the more offspring he leaves; too much is never enough. That gives men a limitless appetite for casual sex partners (and perhaps for the commodities that in ancestral environments would have led to multiple partners, such as power and wealth). Read more at location 9805
Symons notes that homosexual relations offer a clear window on the desires of each sex. Every heterosexual relationship is a compromise between the wants of a man and the wants of a woman, so differences between the sexes tend to be minimized. But homosexuals do not have to compromise, and their sex lives showcase human sexuality in purer form (at least insofar as the rest of their sexual brains are not patterned like those of the opposite sex). In a study of homosexuals in San Francisco before the AIDS epidemic, twenty-eight percent of gay men reported having had more than a thousand sex partners, and seventy-five percent reported having had more than a hundred. No gay woman reported a thousand partners, and only two percent reported as many as a hundred. Other desires of gay men, like pornography, prostitutes, and attractive young partners, also mirror or exaggerate the desires of heterosexual men. (Incidentally, the fact that men’s sexual wants are the same whether they are directed at women or directed at other men refutes the theory that they are instruments for oppressing women.) It’s not that gay men are oversexed; they are simply men whose male desires bounce off other male desires rather than off female desires. Symons writes, “I am suggesting that heterosexual men would be as likely as homosexual men to have sex most often with strangers, to participate in anonymous orgies in public baths, and to stop off in public restrooms for five minutes of fellatio on the way home from work if women were interested in these activities. But women are not interested.” Among heterosexuals, if men want variety more than women do, Econ 101 tells us what should follow. Copulation should be conceived of as a female service, a favor that women can bestow on or withhold from men. Scores of metaphors treat sex with a woman as a precious commodity, whether they take the woman’s perspective (saving yourself, giving it away, feeling used) or the man’s (getting any, sexual favors, getting lucky). And sexual transactions often obey market principles, as cynics of all persuasions have long recognized. The feminist theorist Andrea Dworkin has written, “A man wants what a woman has—sex. He can steal it (rape), persuade her to give it away (seduction), rent it (prostitution), lease it over the long term (marriage in the United States) or own it outright (marriage in most societies).” In all societies, it is mostly or entirely the men who woo, proposition, seduce, use love magic, give gifts in trade for sex, pay bride-prices (rather than collect dowries), hire prostitutes, and rape. Read more at location 9813
HUSBANDS AND WIVES
In foraging societies wealth cannot accumulate, but a few fierce men, skilled leaders, and good hunters may have two to ten wives. With the invention of agriculture and massive inequality, polygyny can reach ridiculous proportions. Laura Betzig has documented that in civilization after civilization, despotic men have implemented the ultimate male fantasy: a harem of hundreds of nubile women, closely guarded (often by eunuchs) so no other man can touch them. Similar arrangements have popped up in India, China, the Islamic world, sub-Saharan Africa, and the Americas. King Solomon had a thousand concubines. Roman emperors called them slaves, and medieval European kings called them serving maids. Polyandry, by comparison, is vanishingly rare. Men occasionally share a wife in environments so harsh that a man cannot survive without a woman, but the arrangement collapses when conditions improve. Read more at location 9874
The most florid polygynists are always despots, men who could kill without fear of retribution. (According to the Guinness Book of World Records, the man with the most recorded children in history—888—was an emperor of Morocco with the evocative name Moulay Ismail The Bloodthirsty.) The hyperpolygynist not only must fend off the hundreds of men he has deprived of wives, but must oppress his harem. Marriages always have at least a bit of reciprocity, and in most polygynous societies a man may forgo additional wives because of their emotional and financial demands. A despot can keep them imprisoned and terrified. But oddly enough, in a freer society polygyny is not necessarily bad for women. On financial and ultimately on evolutionary grounds, a woman may prefer to share a wealthy husband than to have the undivided attention of a pauper, and may even prefer it on emotional grounds. Laura Betzig summed up the reason: Would you rather be the third wife of John F. Kennedy or the first wife of Bozo the Clown? Co-wives often get along, sharing expertise and child-care duties, though jealousies among the subfamilies often erupt, much as in stepfamilies but with more factions and adult players. If marriage were genuinely a free market, then in a polygamous society men’s greater demand for a limited supply of partners and their inflexible sexual jealousy would give the advantage to women. Read more at location 9887
Legal monogamy historically has been an agreement between more and less powerful men, not between men and women. Its aim is not so much to exploit the customers in the romance industry (women) as to minimize the costs of competition among the producers (men). Under polygyny, men vie for extraordinary Darwinian stakes—many wives versus none—and the competition is literally cutthroat. Many homicides and most tribal wars are directly or indirectly about competition for women. Read more at location 9912
when women go through with an affair, they generally pick men of higher status than their husbands; the qualities that lead to status are almost certainly heritable (though a taste for prestigious lovers may also help with the first motive, extracting resources). Liaisons with superior men also may allow a woman to test her ability to trade up in the marriage market, either as a prelude to doing so or to improve her bargaining position within the marriage. Symons’ summary of the sex difference in adultery is that a woman has an affair because she feels that the man is in some way superior or complementary to her husband, and a man has an affair because the woman is not his wife. Do men require anything in a casual sex partner other than two X chromosomes? Sometimes it would appear that the answer is no. Read more at location 9945
Since a woman can bear and nurse one child every few years, and her childbearing years are finite, the younger the bride, the bigger the future family. That is true even though the youngest brides, teenagers, are somewhat less fertile than women in their early twenties. Ironically for the men-are-slime theory, an eye for nubile women may have evolved in the service of marriage and fatherhood, not one-night stands. Among chimpanzees, where a father’s role ends with copulation, some of the wrinkled and saggy females are the sexiest. Read more at location 9973
Buss designed a questionnaire asking about the importance of eighteen qualities of a mate and gave it to ten thousand people in thirty-seven countries on six continents and five islands—monogamous and polygynous, traditional and liberal, communist and capitalist. Men and women everywhere place the highest value of all on intelligence and on kindness and understanding. But in every country men and women differ on the other qualities. Women value earning capacity more than men do; the size of the difference varies from a third more to one and a half times more, but it’s always there. In virtually every country, women place a greater value than men on status, ambition, and industriousness. And in most, they value dependability and stability more than men do. In every country, men place a higher value on youth and on looks than women do. On average, men want a bride 2.66 years younger; women want a groom 3.42 years older. The results have been replicated many times. People’s actions tell the same story. According to the contents of personal advertisements, Men Seeking Women seek youth and looks, Women Seeking Men seek financial security, height, and sincerity. Read more at location 9978
In our society, the best predictor of a man’s wealth is his wife’s looks, and the best predictor of a woman’s looks is her husband’s wealth. Read more at location 9992
Symmetry, an absence of deformities, cleanliness, unblemished skin, clear eyes, and intact teeth are attractive in all cultures. Orthodontists have found that a good-looking face has teeth and jaws in the optimal alignment for chewing. Luxuriant hair is always pleasing, possibly because it shows not only current health but a record of health in the years before. Malnutrition and disease weaken the hair as it grows from the scalp, leaving a fragile spot in the shaft. Long hair implies a long history of good health. Read more at location 10023
The psychologist Devendra Singh has shown photographs and computer-generated pictures of female bodies of different sizes and shapes to hundreds of people of various ages, sexes, and cultures. Everyone finds a ratio of .70 or lower the most attractive. The ratio captures the old idea of the hourglass figure, the wasp waist, and the 36–24–36 ideal measurements. Singh also measured the ratio in Playboy centerfolds and winners of beauty contests over seven decades. Their weight has gone down, but their waist-to-hip ratio has stayed the same. Even most of the Upper Paleolithic Venus figurines, carved tens of thousands of years ago, have the right proportions. Read more at location 10058
Singh found that very fat women and very thin women are judged less attractive (and in fact they are less fertile), but there is a range of weights considered attractive, and shape (waist-to-hip ratio) is more important than size. The hoopla about thinness applies more to women who pose for other women than to women who pose for men. Twiggy and Kate Moss are fashion models, not pinups; Marilyn Monroe and Jayne Mansfield were pinups, not fashion models. Weight is a factor mostly in the competition among women for status in an age in which wealthy women are more likely to be slender than poor ones, a reversal of the usual relation. Read more at location 10075
Both sexes can feel intense jealousy at the thought of a dallying mate, but their emotions are different in two ways. Women’s jealousy appears to be under the control of more sophisticated software, and they can appraise their circumstances and determine whether the man’s behavior poses a threat to their ultimate interests. Men’s jealousy is cruder and more easily triggered. (Once triggered, though, women’s jealousy appears to be as intensely felt as men’s.) In most societies, some women readily share a husband, but in no society do men readily share a wife. A woman having sex with another man is always a threat to the man’s genetic interests, because it might fool him into working for a competitor’s genes, but a man having sex with another woman is not necessarily a threat to the woman’s genetic interests, because his illegitimate child is another woman’s problem. It is only a threat if the man diverts investment from her and her children to the other woman and her children, either temporarily or, in the case of desertion, permanently. So men and women should be jealous of different things. Read more at location 10110
Buss then pasted electrodes on people and asked them to imagine the two kinds of treachery. The men sweated, frowned, and palpitated more from images of sexual betrayal; the women sweated, frowned, and palpitated more from images of emotional betrayal. Read more at location 10127
What evolutionary psychology challenges is not the goals of feminism, but parts of the modern orthodoxy about the mind that have been taken up by the intellectual establishment of feminism. One idea is that people are designed to carry out the interests of their class and sex, rather than to act out of their own beliefs and desires. A second is that the minds of children are formed by their parents, and the minds of adults are formed by language and by media images. A third is the romantic doctrine that our natural inclinations are good and that ignoble motives come from society. The unstated premise that nature is nice lies behind many of the objections to the Darwinian theory of human sexuality. Read more at location 10198
RIVALS
The biologists John Maynard Smith and Geoffrey Parker came up with a better explanation by modeling how the different aggressive strategies that animals might adopt would stack up against each other and against themselves. Fighting every contest to the bitter end is a poor strategy for an animal, because chances are its adversary has evolved to do the same thing. A fight is costly to the loser, because it will be injured or dead and hence worse off than if it had relinquished the prize from the start. It also can be costly to the victor because he may sustain injuries in the course of victory. Read more at location 10239
Many group-living primates settle into two dominance hierarchies, one for each sex. The females compete for food; the males compete for females. Dominant males mate more often, both because they can shove other males out of the way and because the females prefer to mate with them, if for no other reason than that a high-ranking sex partner will tend to sire high-ranking sons, who will give the female more grandchildren than low-ranking sons. Humans don’t have rigid pecking orders, but in all societies people recognize a kind of dominance hierarchy, particularly among men. High-ranking men are deferred to, have a greater voice in group decisions, usually have a greater share of the group’s resources, and always have more wives, more lovers, and more affairs with other men’s wives. Men strive for rank, and achieve it in some ways that are familiar from zoology books and other ways that are uniquely human. Better fighters have higher rank, and men who look like better fighters have higher rank. Sheer height is surprisingly potent in a species that calls itself the rational animal. The word for “leader” in most foraging societies is “big man,” and in fact the leaders usually are big men. Read more at location 10255
Why don’t we see periodontists or college professors dueling over a parking space? First, they live in a world in which the state has a monopoly on the legitimate use of violence. In places beyond the reach of the state, like urban underworlds or rural frontiers, or in times when the state did not exist, like the foraging bands in which we evolved, a credible threat of violence is one’s only protection. Second, the assets of periodontists and professors, such as houses and bank accounts, are hard to steal. “Cultures of honor” spring up when a rapid response to a threat is essential because one’s wealth can be carried away by others. Read more at location 10297
**** Maleness is by far the biggest risk factor for violence. Daly and Wilson report thirty-five samples of homicide statistics from fourteen countries, including foraging and preliterate societies and thirteenth-century England. In all of them, men kill men massively more often than women kill women—on average, twenty-six times more often. Read more at location 10304
Status is the public knowledge that you possess assets that would allow you to help others if you wished to. The assets may include beauty, irreplaceable talent or expertise, the ear and trust of powerful people, and especially wealth. Status-worthy assets tend to be fungible. Wealth can bring connections and vice versa. Beauty can be parlayed into wealth (through gifts or marriage), can attract the attention of important people, or can draw more suitors than the beautiful one can handle. Asset-holders, then, are not just seen as holders of their assets. They exude an aura or charisma that makes people want to be in their graces. Read more at location 10330
The logic is: You can’t see all my wealth and earning power (my bank account, my lands, all my allies and flunkeys), but you can see my gold bathroom fixtures. No one could afford them without wealth to spare, therefore you know I am wealthy. Conspicuous consumption is counterintuitive because squandering wealth can only reduce it, bringing the squanderer down to the level of his or her rivals. But it works when other people’s esteem is useful enough to pay for and when not all the wealth or earning power is sacrificed. Read more at location 10361
Conspicuous consumption works when only the richest can afford luxuries. When the class structure loosens, or sumptuous goods (or good imitations) become widely available, the upper middle class can emulate the upper class, the middle class can emulate the upper middle class, and so on down the ladder. The upper class cannot very well stand by as they begin to resemble the hoi polloi; they must adopt a new look. But then the look is emulated once again by the upper middle class and begins to trickle down again, prompting the upper class to leap to yet a different look, and so on. The result is fashion. Read more at location 10371
FRIENDS AND ACQUAINTANCES
people are good at detecting cheaters and are fitted with moralistic emotions that prompt them to punish the cheaters and reward the cooperators. Does that mean that tit-for-tat underlies the widespread cooperation we find in the human species? It certainly underlies much of the cooperation we find in our society. Read more at location 10435
One of the fondest beliefs of many intellectuals is that there are cultures out there where everyone shares freely. Marx and Engels thought that preliterate peoples represented a first stage in the evolution of civilization called primitive communism, whose maxim was “From each according to his abilities, to each according to his needs.” Indeed, people in foraging societies do share food and risk. But in many of them, people interact mainly with their kin, so in the biologist’s sense they are sharing with extensions of themselves. Many cultures also have an ideal of sharing, but that means little. Of course I will proclaim how great it is for you to share; the question is, will I share when my turn comes? Foraging peoples, to be sure, really do share with nonrelatives, but not out of indiscriminate largesse or a commitment to socialist principles. The data from anthropology show that the sharing is driven by cost-benefit analyses and a careful mental ledger for reciprocation. People share when it would be suicidal not to. In general, species are driven to share when the variance of success in gathering food is high. Read more at location 10445
The theory has been confirmed in nonhuman species, such as vampire bats, and it has also been confirmed in humans in two elegant studies that control for differences among cultures by contrasting the forms of sharing within a culture. The Ache of Paraguay hunt game and gather plant foods. Hunting is largely a matter of luck: on any given day an Ache hunter has a forty percent chance of coming home empty-handed. Gathering is largely a matter of effort: the longer you work, the more you bring home, and an empty-handed gatherer is probably lazy rather than unlucky. As predicted, the Ache share plant foods only within the nuclear family but share meat throughout the band. Read more at location 10458
When it comes to friendship, reciprocal altruism does not ring true. It would be in questionable taste for a dinner guest to pull out his wallet and offer to pay the hosts for his dinner. Inviting the hosts back the very next night would not be much better. Tit-for-tat does not cement a friendship; it strains it. Read more at location 10490
The couples who keep close track of what each has done for the other are the couples who are the least happy. Companionate love, the emotion behind close friendship and the enduring bond of marriage (the love that is neither romantic nor sexual), has a psychology of its own. Friends or spouses feel as if they are in each other’s debt, but the debts are not measured and the obligation to repay is not onerous but deeply satisfying. People feel a spontaneous pleasure in helping a friend or a spouse, without anticipating repayment or regretting the favor if repayment never comes. Read more at location 10493
The quest for status is in part a motive for making oneself irreplaceable. Another is to associate with people who benefit from the things that benefit you. Merely by going about your life and pursuing your own interests, you can advance someone else’s interests as a side effect. Marriage is the clearest example: the husband and wife share an interest in their children’s welfare. Read more at location 10517
Once you have made yourself valuable to someone, the person becomes valuable to you. You value him or her because if you were ever in trouble, they would have a stake—albeit a selfish stake—in getting you out. But now that you value the person, they should value you even more. Not only are you valuable because of your talents or habits, but you are valuable because of your stake in rescuing him or her from hard times. The more you value the person, the more the person values you, and so on. This runaway process is what we call friendship. Read more at location 10528
ALLIES AND ENEMIES
War is not universal, but people in all cultures feel that they are members of a group (a band, tribe, clan, or nation) and feel animosity toward other groups. And warfare itself is a major fact of life for foraging tribes. Many intellectuals believe that primitive warfare is rare, mild, and ritualized, or at least was so until the noble savages were contaminated by contact with Westerners. But this is romantic nonsense. War has always been hell. Read more at location 10546
Why would anyone be so stupid as to start a war? Tribal people can fight over anything of value, and the causes of tribal wars are as difficult to disentangle as the causes of World War I. But one motive that is surprising to Westerners appears over and over. In foraging societies, men go to war to get or keep women—not necessarily as a conscious goal of the warriors (though often it is exactly that), but as the ultimate payoff that allowed a willingness to fight to evolve. Access to women is the limiting factor on males’ reproductive success. Having two wives can double a man’s children, having three wives can triple it, and so on. For a man who is not at death’s door, no other resource has as much impact on evolutionary fitness. The most common spoils of tribal warfare are women. Read more at location 10557
The feminist writer Susan Brownmiller has documented that rape was systematically practiced by the English in the Scottish Highlands, the Germans invading Belgium in World War I and eastern Europe in World War II, the Japanese in China, the Pakistanis in Bangladesh, the Cossacks during the pogroms, the Turks persecuting the Armenians, the Ku Klux Klan in the American South, and, to a lesser extent, Russian soldiers marching toward Berlin and American soldiers in Vietnam. Recently the Serbs in Bosnia and the Hutus in Rwanda have added themselves to this list. Prostitution, which in wartime is often hard to distinguish from rape, is a ubiquitous perquisite of soldiers. Leaders may sometimes use rape as a terror tactic to attain other ends, as Henry V obviously did, but the tactic is effective precisely because the soldiers are so eager to implement it, as Henry took pains to remind the Frenchmen. In fact it often backfires by giving the defenders an incalculable incentive to fight on, and probably for that reason, more than out of compassion for enemy women, modern armies have outlawed rape. Even when rape is not a prominent part of our warfare, we invest our war leaders with enormous prestige, just as the Yanomamö do, and by now you know the effects of prestige on a man’s sexual attractiveness and, until recently, his reproductive success. Read more at location 10611
The theory also explains why in modern warfare most people are unwilling to send women into combat and feel morally outraged when women are casualties, even though no ethical argument makes a woman’s life more precious than a man’s. It is hard to shake the intuition that war is a game that benefits men (which was true for most of our evolutionary history), so they should bear the risks. The theory also predicts that men should be willing to fight collectively only if they are confident of victory and none of them knows in advance who will be injured or killed. If defeat is likely, it’s pointless to fight on. And if you bear more than your share of the risk—say, if your platoonmates are exposing you to danger by looking out for their own hides—it’s also pointless to fight on. These two principles shape the psychology of war. Read more at location 10662
Here is another peculiarity of the logic and psychology of war. A man should agree to stay in a coalition for as long as he does not know that he is about to die. He may know the odds, but he cannot know whether the spinner of death is slowing down at him. But at some point he may see it coming. He may glimpse an archer who has him in his sights, or detect an impending ambush, or notice that he has been sent on a suicide mission. At that point everything changes, and the only rational move is to desert. Read more at location 10683
HUMANITY
history has seen terrible blights disappear permanently, sometimes only after years of bloodshed, sometimes as if in a puff of smoke. Slavery, harem-holding despots, colonial conquest, blood feuds, women as property, institutionalized racism and anti-Semitism, child labor, apartheid, fascism, Stalinism, Leninism, and war have vanished from expanses of the world that had suffered them for decades, centuries, or millennia. The homicide rates in the most vicious American urban jungles are twenty times lower than in many foraging societies. Modern Britons are twenty times less likely to be murdered than their medieval ancestors. If the brain has not changed over the centuries, how can the human condition have improved? Part of the answer, I think, is that literacy, knowledge, and the exchange of ideas have undermined some kinds of exploitation. It’s not that people have a well of goodness that moral exhortations can tap. It’s that information can be framed in a way that makes exploiters look like hypocrites or fools. One of our baser instincts—claiming authority on a pretext of beneficence and competence—can be cunningly turned on the others. When everyone sees graphic representations of suffering, it is no longer possible to claim that no harm is being done. Read more at location 10717
though conflict is a human universal, so are efforts to reduce it. The human mind occasionally catches a glimmering of the brute economic fact that often adversaries can both come out ahead by dividing up the surplus created by their laying down their arms. Read more at location 10732
8 THE MEANING OF LIFE
Man does not live by bread alone, nor by know-how, safety, children, or sex. People everywhere spend as much time as they can afford on activities that, in the struggle to survive and reproduce, seem pointless. In all cultures, people tell stories and recite poetry. They joke, laugh, and tease. They sing and dance. They decorate surfaces. They perform rituals. They wonder about the causes of fortune and misfortune, and hold beliefs about the supernatural that contradict everything else they know about the world. They concoct theories of the universe and their place within it. As if that weren’t enough of a puzzle, the more biologically frivolous and vain the activity, the more people exalt it. Art, literature, music, wit, religion, and philosophy are thought to be not just pleasurable but noble. They are the mind’s best work, what makes life worth living. Why do we pursue the trivial and futile and experience them as sublime? Read more at location 10756
The function of the arts is almost defiantly obscure, and I think there are several reasons why. One is that the arts engage not only the psychology of aesthetics but the psychology of status. The very uselessness of art that makes it so incomprehensible to evolutionary biology makes it all too comprehensible to economics and social psychology. Read more at location 10770
What is it about the mind that lets people take pleasure in shapes and colors and sounds and jokes and stories and myths? Read more at location 10802
**** Another reason the psychology of the arts is obscure is that they are not adaptive in the biologist’s sense of the word. This book has been about the adaptive design of the major components of the mind, but that does not mean that I believe that everything the mind does is biologically adaptive. The mind is a neural computer, fitted by natural selection with combinatorial algorithms for causal and probabilistic reasoning about plants, animals, objects, and people. It is driven by goal states that served biological fitness in ancestral environments, such as food, sex, safety, parenthood, friendship, status, and knowledge. That toolbox, however, can be used to assemble Sunday afternoon projects of dubious adaptive value. Some parts of the mind register the attainment of increments of fitness by giving us a sensation of pleasure. Other parts use a knowledge of cause and effect to bring about goals. Put them together and you get a mind that rises to a biologically pointless challenge: figuring out how to get at the pleasure circuits of the brain and deliver little jolts of enjoyment without the inconvenience of wringing bona fide fitness increments from the harsh world. Read more at location 10813
There are problems in the universe other than those: where the universe came from, how physical flesh can give rise to sentient minds, why bad things happen to good people, what happens to our thoughts and feelings when we die. The mind can pose such questions but may not be equipped to answer them, even if the questions have answers. Read more at location 10837
Some readers may be surprised to learn that after seven chapters of reverse-engineering the major parts of the mind, I will conclude by arguing that some of the activities we consider most profound are nonadaptive by-products. But both kinds of argument come from a single standard, the criteria for biological adaptation. For the same reason that it is wrong to write off language, stereo vision, and the emotions as evolutionary accidents—namely, their universal, complex, reliably developing, well-engineered, reproduction-promoting design—it is wrong to invent functions for activities that lack that design merely because we want to ennoble them with the imprimatur of biological adaptiveness. Read more at location 10844
ARTS AND ENTERTAINMENT
The thought experiment shows that drabness comes from an environment with nothing to offer, and its opposite, visual pizzazz, comes from an environment that contains objects worth paying attention to. Thus we are designed to be dissatisfied by bleak, featureless scenes and attracted to colorful, patterned ones. We push that pleasure button with vivid artificial colors and patterns. Read more at location 10893
Compared with language, vision, social reasoning, and physical know-how, music could vanish from our species and the rest of our lifestyle would be virtually unchanged. Music appears to be a pure pleasure technology, a cocktail of recreational drugs that we ingest through the ear to stimulate a mass of pleasure circuits at once. “Music is the universal language,” says the cliché, Read more at location 10903
Musical idioms vary greatly in complexity across time, cultures, and subcultures. And music communicates nothing but formless emotion. Even a plot as simple as “Boy meets girl, boy loses girl” cannot be narrated by a sequence of tones in any musical idiom. All this suggests that music is quite different from language and that it is a technology, not an adaptation. But there are some parallels. As we shall see, music may borrow some of the mental software for language. And just as the world’s languages conform to an abstract Universal Grammar, the world’s musical idioms conform to an abstract Universal Musical Grammar. That idea was first broached by the composer and conductor Leonard Bernstein in The Unanswered Question, Read more at location 10912
The building blocks of a musical idiom are its inventory of notes— roughly, the different sounds that a musical instrument is designed to emit. The notes are played and heard as discrete events with beginnings and ends and a target pitch or coloring. That sets music apart from most other streams of sound, which slide continuously up or down, such as a howling wind, an engine roar, or the intonation of speech. The notes differ in how stable they feel to a listener. Some give a feeling of finality or settledness, and are suitable endings of a composition. Others feel unstable, and when they are played the listener feels a tension that is resolved when the piece returns to a more stable note. In some musical idioms, the notes are drumbeats with different timbres (coloring or quality). In others, the notes are pitches that are arrayed from high to low but not placed at precise intervals. Read more at location 10923
The human sense of pitch is determined by the frequency of vibration of the sound. In most forms of tonal music, the notes in the inventory are related to the frequencies of vibration in a straightforward way. When an object is set into a sustained vibration (a string is plucked, a hollow object is struck, a column of air reverberates), the object vibrates at several frequencies at once. The lowest and often loudest frequency—the fundamental—generally determines the pitch we hear, but the object also vibrates at twice the fundamental frequency (but typically not as intensely), at three times the frequency (even less intensely), at four times (less intensely still), and so on. These vibrations are called harmonics or overtones. They are not perceived as pitches distinct from the fundamental, but when they are all heard together they give a note its richness or timbre. Read more at location 10932
The musicologist Deryck Cooke worked out a theory of the emotional semantics of the prolongation reduction. He showed how music conveys tension and resolution by transitions across unstable and stable intervals, and conveys joy and sorrow by transitions across major and minor intervals. Read more at location 11007
So that is the basic design of music. But if music confers no survival advantage, where does it come from and why does it work? I suspect that music is auditory cheesecake, an exquisite confection crafted to tickle the sensitive spots of at least six of our mental faculties. Read more at location 11018
1. Language. We can put words to music, and we wince when a lazy lyricist aligns an accented syllable with an unaccented note or vice versa. That suggests that music borrows some of its mental machinery from language—in particular, from prosody, the contours of sound that span many syllables. Read more at location 11022
2. Auditory scene analysis. Just as the eye receives a jumbled mosaic of patches and must segregate surfaces from their backdrops, the ear receives a jumbled cacophony of frequencies and must segregate the streams of sound that come from different sources—the Read more at location 11030
3. Emotional calls. Darwin noticed that the calls of many birds and primates are composed of discrete notes in harmonic relations. He speculated that they evolved because they were easy to reproduce time after time. Read more at location 11060
4. Habitat selection. We pay attention to features of the visual world that signal safe, unsafe, or changing habitats, such as distant views, greenery, gathering clouds, and sunsets (see Chapter 6). Perhaps we also pay attention to features of the auditory world that signal safe, unsafe, or changing habitats. Read more at location 11069
5. Motor control. Rhythm is the universal component of music, and in many idioms it is the primary or only component. Read more at location 11082
6. Something else. Something that explains how the whole is more than the sum of the parts. Read more at location 11091
When the illusions work, there is no mystery to the question “Why do people enjoy fiction?” It is identical to the question “Why do people enjoy life?” When we are absorbed in a book or a movie, we get to see breathtaking landscapes, hobnob with important people, fall in love with ravishing men and women, protect loved ones, attain impossible goals, and defeat wicked enemies. Not a bad deal for seven dollars and fifty cents! Read more at location 11117
Literature, though, not only delights but instructs. The computer scientist Jerry Hobbs has tried to reverse-engineer the fictional narrative in an essay he was tempted to call “Will Robots Ever Have Literature?” Novels, he concluded, work like experiments. The author places a fictitious character in a hypothetical situation in an otherwise real world where ordinary facts and laws hold, and allows the reader to explore the consequences. Read more at location 11146
**** Characters in a fictitious world do exactly what our intelligence allows us to do in the real world. We watch what happens to them and mentally take notes on the outcomes of the strategies and tactics they use in pursuing their goals. What are those goals? A Darwinian would say that ultimately organisms have only two: to survive and to reproduce. And those are precisely the goals that drive the human organisms in fiction. Most of the thirty-six plots in Georges Polti’s catalogue are defined by love or sex or a threat to the safety of the protagonist or his kin Read more at location 11159
The intrigues of people in conflict can multiply out in so many ways that no one could possibly play out the consequences of all courses of action in the mind’s eye. Fictional narratives supply us with a mental catalogue of the fatal conundrums we might face someday and the outcomes of strategies we could deploy in them. Read more at location 11199
none of the features may be ignored or casually altered; any might have been deliberately crafted by the artist. Goodman calls this property of art “repleteness.” A good artist takes advantage of repleteness and puts every aspect of the medium to good use. She might as well do so. She already has the eye and ear of the audience, and the work, having no practical function, does not have to meet any demanding mechanical specifications; every part is up for grabs. Read more at location 11212
A skillful use of repleteness impresses us not only by evoking a pleasurable feeling through several channels at once. Some of the parts are anomalous at first, and in resolving the anomaly we discover for ourselves the clever ways in which the artist shaped the different parts of the medium to do the same thing at the same time. Read more at location 11226
WHAT’S SO FUNNY?
Laughter, Koestler noted, is involuntary noisemaking. As any schoolteacher knows, it diverts attention from a speaker and makes it difficult to continue. And laughter is contagious. The psychologist Robert Provine, who has documented the ethology of laughter in humans, found that people laugh thirty times more often when they are with other people than when they are alone. Read more at location 11247
First, laughter is noisy not because it releases pent-up psychic energy but so that others may hear it; it is a form of communication. Second, laughter is involuntary for the same reason that other emotional displays are involuntary Read more at location 11254
we have two candidates for precursors to laughter: a signal of collective aggression and a signal of mock aggression. They are not mutually exclusive, and both may shed light on humor in humans. Humor is often a kind of aggression. Being laughed at is aversive and feels like an attack. Comedy often runs on slapstick and insult, and in less refined settings, including the foraging societies in which we evolved, humor can be overtly sadistic. Read more at location 11267
Koestler’s three ingredients of humor—incongruity, resolution, and indignity—have been verified in many experiments of what makes a joke funny. Slapstick humor runs off the clash between a psychological frame, in which a person is a locus of beliefs and desires, and a physical frame, in which a person is a hunk of matter obeying the laws of physics. Scatological humor runs off the clash between the psychological frame and a physiological frame, in which a person is a manufacturer of disgusting substances. Sexual humor also runs off a clash between the psychological frame and a biological one; this time the person is a mammal with all the instincts and organs necessary for internal fertilization. Verbal humor hinges on a clash between two meanings of one word, the second one unexpected, sensible, and insulting. Read more at location 11347
**** (Note: contextual, recursive nature of language) the mind reflexively interprets other people’s words and gestures by doing whatever it takes to make them sensible and true. If the words are sketchy or incongruous, the mind charitably fills in missing premises or shifts to a new frame of reference in which they make sense. Without this “principle of relevance,” language itself would be impossible. The thoughts behind even the simplest sentence are so labyrinthine that if we ever expressed them in full our speech would sound like the convoluted verbiage of a legal document. Read more at location 11374
The logic of friendship is based on a commitment to mutual unmeasured aid, come what may. People want status and dominance, but they also want friends, because status and dominance can fade but a friend will be there through thick and thin. The two are incompatible, and that raises a signaling problem. Given any two people, one will always be stronger, smarter, wealthier, better-looking, or better connected than the other. The triggers of a dominant-submissive or celebrity-fan relationship are always there, but neither party may want the relationship to go in that direction. By deprecating the qualities that you could have lorded over a friend or that a friend could have lorded over you, you are conveying that the basis of the relationship, as far as you are concerned, is not status or dominance. All the better if the signal is involuntary and hence hard to fake. Read more at location 11410
THE INQUISITIVE IN PURSUIT OF THE INCONCEIVABLE
What is religion? Like the psychology of the arts, the psychology of religion has been muddied by scholars’ attempts to exalt it while understanding it. Religion cannot be equated with our higher, spiritual, humane, ethical yearnings (though it sometimes overlaps with them). Read more at location 11435
Religion is not a single topic. What we call religion in the modern West is an alternative culture of laws and customs that survived alongside those of the nation-state because of accidents of European history. Religions, like other cultures, have produced great art, philosophy, and law, but their customs, like those of other cultures, often serve the interests of the people who promulgate them. Read more at location 11442
Let’s focus on the truly distinctive part of the psychology of religion. The anthropologist Ruth Benedict first pointed out the common thread of religious practice in all cultures: religion is a technique for success. Ambrose Bierce defined to pray as “to ask that the laws of the universe be annulled on behalf of a single petitioner confessedly unworthy.” People everywhere beseech gods and spirits for recovery from illness, for success in love or on the battlefield, and for good weather. Religion is a desperate measure that people resort to when the stakes are high and they have exhausted the usual techniques for the causation of success—medicines, strategies, courtship, and, in the case of the weather, nothing. Read more at location 11453
Believers also avoid working out the strange logical consequences of these piecemeal revisions of ordinary things. They don’t pause to wonder why a God who knows our intentions has to listen to our prayers, or how a God can both see into the future and care about how we choose to act. Compared to the mind-bending ideas of modern science, religious beliefs are notable for their lack of imagination (God is a jealous man; heaven and hell are places; souls are people who have sprouted wings). That is because religious concepts are human concepts with a few emendations that make them wondrous and a longer list of standard traits that make them sensible to our ordinary ways of knowing. Read more at location 11474
And beliefs about a world of spirits do not come from nowhere. They are hypotheses intended to explain certain data that stymie our everyday theories. Edward Tylor, an early anthropologist, noted that animistic beliefs are grounded in universal experiences. Read more at location 11487
Some problems continue to baffle the modern mind. As the philosopher Colin McGinn put it in his summary of them, “The head spins in theoretical disarray; no explanatory model suggests itself; bizarre ontologies loom. There is a feeling of intense confusion, but no clear idea about where the confusion lies.” Read more at location 11495
Another imponderable is the self. What or where is the unified center of sentience that comes into and goes out of existence, that changes over time but remains the same entity, and that has a supreme moral worth? Why should the “I” of 1996 reap the rewards and suffer the punishments earned by the “I” of 1976? Say I let someone scan a blueprint of my brain into a computer, destroy my body, and reconstitute me in every detail, memories and all. Would I have taken a nap, or committed suicide? If two I’s were reconstituted, would I have double the pleasure? How many selves are in the skull of a split-brain patient? What about in the partly fused brains of a pair of Siamese twins? When does a zygote acquire a self? Read more at location 11503
Free will is another enigma (see Chapter 1). How can my actions be a choice for which I am responsible if they are completely caused by my genes, my upbringing, and my brain state? Some events are determined, some are random; how can a choice be neither? Read more at location 11509
A fourth puzzle is meaning. When I talk about planets, I can refer to all planets in the universe, past, present, and future. But how could I, right now, here in my house, be standing in some relationship to a planet that will be created in a distant galaxy in five million years? Read more at location 11516
Knowledge is just as perplexing. How could I have arrived at the certainty that the square of the hypotenuse is equal to the sum of the squares of the other two sides, everywhere and for all eternity, here in the comfort of my armchair with not a triangle or tape measure in sight? How do I know that I’m not a brain in a vat, or dreaming, or living a hallucination programmed by an evil neurologist, or that the universe was not created five minutes ago complete with fossils, memories, and historical records? If every emerald I have seen so far is green, why should I conclude “all emeralds are green” rather than “all emeralds are grue,” where grue means “either observed before the year 2020 and green, or not so observed and blue”? All the emeralds I have seen are green, but then all the emeralds I’ve seen are grue. The two conclusions are equally warranted, but one predicts that the first emerald I see in 2020 will be the color of grass and the other predicts that it will be the color of the sky. Read more at location 11520
final conundrum is morality. If I secretly hatchet the unhappy, despised pawnbroker, where is the evil nature of that act registered? What does it mean to say that I “shouldn’t” do it? How did ought emerge from a universe of particles and planets, genes and bodies? If the aim of ethics is to maximize happiness, should we indulge a sicko who gets more pleasure from killing than his victims do from living? Read more at location 11527
Philosophical problems have a feeling of the divine, and the favorite solution in most times and places is mysticism and religion. Consciousness is a divine spark in each of us. The self is the soul, an immaterial ghost that floats above physical events. Souls just exist, or they were created by God. God granted each soul a moral worth and the power of choice. He has stipulated what is good, and inscribes every soul’s good and evil acts in the book of life and rewards or punishes it after it leaves the body. Knowledge is granted by God to the prophet or the seer, or guaranteed to all of us by God’s honesty and omniscience. Read more at location 11535
The problem with the religious solution was stated by Mencken when he wrote, “Theology is the effort to explain the unknowable in terms of the not worth knowing.” For anyone with a persistent intellectual curiosity, religious explanations are not worth knowing because they pile equally baffling enigmas on top of the original ones. Read more at location 11544
Modern philosophers have tried three other solutions. One is to say that the mysterious entities are an irreducible part of the universe and to leave it at that. The universe, we would conclude, contains space, time, gravity, electromagnetism, nuclear forces, matter, energy, and consciousness (or will, or selves, or ethics, or meaning, or all of them). The answer to our curiosity about why the universe has consciousness is, “Get over it, it just does.” We feel cheated because no insight has been offered, and because we know that the details of consciousness, will, and knowledge are minutely related to the physiology of the brain. The irreducibility theory leaves that a coincidence. A second approach is to deny that there is a problem. We have been misled by fuzzy thinking or by beguiling but empty idioms of language, such as the pronoun I. Statements about consciousness, will, self, and ethics cannot be verified by mathematical proof or empirical test, so they are meaningless. But this answer leaves us incredulous, not enlightened. As Descartes observed, our own consciousness is the most indubitable thing there is. It is a datum to be explained; it cannot be defined out of existence by regulations about what we are allowed to call meaningful (to say nothing of ethical statements, such as that slavery and the Holocaust were wrong). A third approach is to domesticate the problem by collapsing it with one we can solve. Consciousness is activity in layer 4 of the cortex, or the contents of short-term memory. Free will is in the anterior cingulate sulcus or the executive subroutine. Morality is kin selection and reciprocal altruism. Each suggestion of this kind, to the extent that it is correct, does solve one problem, but it just as surely leaves unsolved the main problem. How does activity in layer 4 of the cortex cause my private, pungent, tangy sensation of redness? I can imagine a creature whose layer 4 is active but who does not have the sensation of red or the sensation of anything; no law of biology rules the creature out. No account of the causal effects of the cingulate sulcus can explain how human choices are not caused at all, hence something we can be held responsible for. Theories of the evolution of the moral sense can explain why we condemn evil acts against ourselves and our kith and kin, but cannot explain the conviction, as unshakable as our grasp of geometry, that some acts are inherently wrong even if their net effects are neutral or beneficial to our overall well-being. Read more at location 11550
**** Maybe philosophical problems are hard not because they are divine or irreducible or meaningless or workaday science, but because the mind of Homo sapiens lacks the cognitive equipment to solve them. We are organisms, not angels, and our minds are organs, not pipelines to the truth. Our minds evolved by natural selection to solve problems that were life-and-death matters to our ancestors, not to commune with correctness or to answer any question we are capable of asking. Read more at location 11570
**** It is easy to draw extravagant and unwarranted conclusions from the suggestion that our minds lack the equipment to solve the major problems of philosophy. It does not say that there is some paradox of self-reference or infinite regress in a mind’s trying to understand itself. Psychologists and neuroscientists don’t study their own minds; they study someone else’s. Nor does it imply some principled limitation on the possibility of knowledge by any knower, like the Uncertainty Principle or Gödel’s theorem. It is an observation about one organ of one species, equivalent to observing that cats are color-blind or that monkeys cannot learn long division. It does not justify religious or mystical beliefs but explains why they are futile. Philosophers would not be out of a job, because they clarify these problems, chip off chunks that can be solved, and solve them or hand them over to science to solve. The hypothesis does not imply that we have sighted the end of science or bumped into a barrier on how much we can ever learn about how the mind works. The computational aspect of consciousness (what information is available to which processes), the neurological aspect (what in the brain correlates with consciousness), and the evolutionary aspect (when and why did the neurocomputational aspects emerge) are perfectly tractable, and I see no reason that we should not have decades of progress and eventually a complete understanding—even if we never solve residual brain-teasers like whether your red is the same as my red or what it is like to be a bat. Read more at location 11595
Is cognitive closure a pessimistic conclusion? Not at all! I find it exhilarating, a sign of great progress in our understanding of the mind. And it is my last opportunity to pursue the goal of this book: to get you to step outside your own mind for a moment and see your thoughts and feelings as magnificent contrivances of the natural world rather than as the only way that things could be. First, if the mind is a system of organs designed by natural selection, why should we ever have expected it to comprehend all mysteries, to grasp all truths? Read more at location 11611
**** But there is something peculiarly holistic and everywhere-at-once and nowhere-at-all and all-at-the-same-time about the problems of philosophy. Sentience is not a combination of brain events or computational states: how a red-sensitive neuron gives rise to the subjective feel of redness is not a whit less mysterious than how the whole brain gives rise to the entire stream of consciousness. The “I” is not a combination of body parts or brain states or bits of information, but a unity of selfness over time, a single locus that is nowhere in particular. Free will is not a causal chain of events and states, by definition. Although the combinatorial aspect of meaning has been worked out (how words or ideas combine into the meanings of sentences or propositions), the core of meaning— the simple act of referring to something—remains a puzzle, because it stands strangely apart from any causal connection between the thing referred to and the person referring. Knowledge, too, throws up the paradox that knowers are acquainted with things that have never impinged upon them. Our thoroughgoing perplexity about the enigmas of consciousness, self, will, and knowledge may come from a mismatch between the very nature of these problems and the computational apparatus that natural selection has fitted us with. If these conjectures are correct, our psyche would present us with the ultimate tease. The most undeniable thing there is, our own awareness, would be forever beyond our conceptual grasp. But if our minds are part of nature, that is to be expected, even welcomed. The natural world evokes our awe by the specialized designs of its creatures and their parts. We don’t poke fun at the eagle for its clumsiness on the ground or fret that the eye is not very good at hearing, because we know that a design can excel at one challenge only by compromising at others. Our bafflement at the mysteries of the ages may have been the price we paid for a combinatorial mind that opened up a world of words and sentences, of theories and equations, of poems and melodies, of jokes and stories, the very things that make a mind worth having. Read more at location 11631