Why, then, do certain kinds of jokes, particularly those about forbidden sexual subjects, seem to remain persistently funny to so many people? Why do those censors remain unchanged for so long? Here we can reuse our explanation of the prolonged persistence of attachment, infatuation, sexuality, and mourning-grief; because these areas relate to self-ideals, their memories, once formed, are slow to change.  In fact, we could argue that they literally are retarded children — that is, they are among the frozen remnants of our earlier selves.
Why do angry people act as though some measure of aggression must be spent and, when no proper object lies in reach, strike out and damage harmless things? It almost seems as though our feelings can accumulate like fluids bottled up inside. In earlier times, some scientists identified these quantities with substances like bile and blood. No one believes those theories now — yet still we often speak of having mental energy and momentum or of succumbing to depletion or inertia. Do mental quantities really exist within the mind? If so, how are they made and stored, brought forth and then spent? And what are their relations to the quantities and magnitudes we read about in technical books? The answer is that words like energy and force are not used with much precision in everyday psychology. They still have the connotations that they carried several centuries ago, when they referred to commonsense ideas about vitality. Then, energy referred to vigor of action and expression, and force referred to the binding strength of a commitment or to the fighting strength of an army.
Modern scientists use a concept of energy that, though narrower and more precise, not only explains more perfectly why engines stop when they run out of fuel, but also applies to our bodies as well: each of the cells of which we're made, including those inside the brain, requires some chemical energy in the form of food and oxygen. Accordingly, the body as a whole can do only a limited amount of physical work before it needs another meal. Now many people naively assume that our higher-level mental processes have similar requirements and that they need some second form of fuel — a mythical form of mental energy — to keep from becoming bored or mentally exhausted. And yet that simply isn't true! If each of Builder's agents has physical energy enough to do its work, then Builder — as an agency — needs nothing more to do its work. Builder, after all, is but a name for a certain assembly of agents. It can't require anything its separate agents do not need.
Machines and brains require ordinary energy to do their jobs — and need no other, mental forms of energy. Causality is quite enough to keep them working toward their goals.
But if our higher-level processes require no extra quantities like fuels or energies, what makes it seem to us as though they do? Why do so many people talk about their levels of mental or emotional energy ? Why do tedious and boring occupations make us feel run down ? We all experience so many such phenomena that we cannot help thinking our minds depend on many kinds of mental quantities — yet scientists apparently have shown that no such quantities exist. How can we explain this? It is not enough to say, simply, that these phenomena are illusions; we must understand why the illusions appear and, if possible, determine what functions they serve. The next few sections show how various illusions of mental force and energy evolve as convenient ways for mental agencies to regulate their transactions, much as many human communities have discovered how to use money.
How can a hurt be canceled by a kiss? How can an insult add to injury? Why do we so often speak as though our wishes and desires were like forces, which increase one another's effects when they're aligned but cancel out when they're opposed? I'll argue that this is because, at every moment of our lives, we're forced to choose between alternatives we can't compare. Suppose, for example, that you must choose between two homes: one of them offers a mountain view; the other is closer to where you work. It really is a strange idea that two such unrelated things as nearness to work and beautiful scenery could be compared at all. But a person could instead assess that pleasant, restful view as worth a certain amount of travel time. Instead of comparing the items themselves, you could simply compare how much time they seem to be worth.
We turn to using quantities when we can't compare the qualities of things.
This way, for better or for worse, we often assign some magnitude or price to each alternative. That tactic helps to simplify our lives so much that virtually every social community works out its own communal measure-schemes — let's call them currencies — that let its people work and trade in harmony, even though each individual has somewhat different personal goals. The establishment of a currency can foster both competition and cooperation by providing us with peaceful ways to divide and apportion the things we have to share.
But who can set prices on things like time or measure the values of comfort and love? What makes our mental marketplaces work so well when emotional states seem so hard to compare? One reason is that no matter how different those mental conditions seem, they must all compete for certain limited resources — such as space, time, and energy — and these, to a rather large extent, are virtually interchangeable. For example, you'd end up with essentially the same result whether you measure things in terms of food or time — because it takes time to find food, and each amount of food helps you survive for some amount of time. Thus the value we place on each commodity constrains, to some extent, the values we'll assign to many other kinds of goods. Because there are so many such constraints, once a community sets up a currency, that currency takes on a life of its own, and soon we start to treat our wealth as though it were a genuine commodity, a real substance that we can use, save, lend, or waste.
In a similar way, a group of agencies inside the brain could exploit some amount to keep account of their transactions with one another. Indeed agencies need such techniques even more than people do, because they are less able to appreciate each other's concerns. But if agents had to pay their way, what might they use for currency? One family of agents might evolve ways to exploit their common access to some chemical that is available in limited quantities; another family of agents might contrive to use a quantity that doesn't actually exist at all, but whose amount is simply computed. I suspect that what we call the pleasure of success may be, in effect, the currency of some such scheme. To the extent that success is interchangeable with time or food or energy, it's useful to treat pleasure as equivalent to wealth.
We've scarcely mentioned at all inside this book the kinds of quantities that could be measured — though surely brain cells use them all the time. For example, it seems quite likely that many of our agents employ quantitative schemes for summarizing evidence or establishing the strengths of connections. But I have said little about such matters because I suspect that such matters play diminished roles, the more we move toward higher-level operations of the mind. This is because whenever we're forced to compare magnitudes, we have to pay a heavy price: it tends to terminate what we call thinking.
Whenever we turn to measurements, we forfeit some uses of intellect. Currencies and magnitudes help us make comparisons only by concealing the differences among what they purport to represent.
By their nature, quantitative descriptions are so one-dimensional and featureless that they cannot help but conceal the structures that give rise to them. This is inescapable, since any act that makes two different things comparable must do it by deflecting our attention from their differences. Numbers themselves are the greatest masters of disguise because they perfectly conceal all traces of their origins. Add five and eight to make thirteen, and tell that answer to a friend: thirteen will be all your friend can know, since no amount of ingenious thought can ever show that it came from adding five and eight! It's much the same inside the head: quantitative judgments help us make decisions only by keeping us from thinking too much about the actual evidence.
No matter that such judgments have faults; you often have no choice but to choose. This happens when you can't stay where you are and must turn either right or left. Somewhere in some agencies, alternatives must be compared — and sometimes one can find no way except by using currencies. Then, various agents in your brain may turn to whatever quantities — chemical, electrical, or whatever — that happen to be available. Any substance or quantity whose availability is limited can be made to serve as a currency. But when we make our theories about how such systems work, we simply must remember not to make the easy mistake of confusing those quantities with their adopted functions and thus, for example, believing that certain drugs are inherently stimulating or depressing, or that certain foodstuffs are inherently more natural, or more healthy. Most of the properties of a currency are not inherent — but merely conventional.
In any case, we should never assume that the quality or character of a thought process depends directly on the nature of the circumstances that evoke it. There is no quality of sweetness inherent in sugar itself, which is a mere chemical. Its quality of sweetness is, in effect, a currency involved with certain agencies that are connected to sensors that detect the presence of sugar. Those agencies evolved that way because whenever we have hunger goals, it pays to recognize the taste of sugar as a sign of success — simply because sugar itself supplies energy, is easy to detect, and usually indicates the presence of other edible sources of nutrition. Similarly, inside our brains, many agencies have come to influence one another by controlling the amounts of various chemicals in much the way that many kinds of human transactions have come to use substances like candy, coins, or bags of salt — or banknotes backed by promises.
It seems completely natural to us that we should feel pain when we're injured or hunger when we're deprived of food. Such feelings seem to us to be inherent in those predicaments. Then why doesn't a car feel pain when its tire is punctured or feel hungry when its fuel runs low? The answer is that pain and hunger are not inherent in being injured or starved: such feelings must be engineered. These physical circumstances do not directly produce the states of mind they arouse; on the contrary, this depends upon intricate networks of agencies and nerve-bundles that took millions of years to evolve. We have no conscious sense of that machinery. When your skin is touched, it seems as though it were your skin that feels — and not your brain — because you're unaware of everything that happens in between.
In order for hunger to keep us fed, it must engage some agency that gives priority to food-acquiring goals. But unless such signals came before our fuel reserves were entirely gone, they'd arrive too late to have any use. This is why feeling hungry or tired is not the same as being genuinely starved or exhausted. To serve as useful warning signs, feelings like pain and hunger must be engineered not simply to indicate dangerous conditions, but to anticipate them and warn us before too much damage is done.
But what about the feelings of depression and discouragement we get when stuck at boring jobs or with problems we cannot solve? Such feelings resemble those that accompany physical fatigue, but they do not signify genuine depletions because they often easily respond to changes of context, interest, and schedule. Nevertheless, the similarity would be no accident, for probably those feelings arise because our higher-level brain centers have evolved connections that exploit our ancient fuel-exhaustion warning systems. After all, the unproductive use of time is virtually equivalent to wasting hard- earned energy!
Now what about those incidents in which some person seems to go beyond what we supposed were the normal bounds of endurance, strength, or tolerance of pain? We like to believe this demonstrates that the force of will can overrule the physical laws that govern the world. But a person's ability to persist in circumstances we hadn't thought were tolerable need not indicate anything supernatural. Since our feelings of pain, depression, exhaustion, and discouragement are themselves mere products of our minds' activities — and ones that are engineered to warn us before we reach our ultimate limits — we need no extraordinary power of mind over matter to overcome them. It is merely a matter of finding ways to rearrange our priorities.
In any case, what hurts — and even what is felt at all — may, in the end, be more dependent upon culture than biology. Ask anyone who runs a marathon, or ask your favorite Amazon.
We spend our lives in several realms. The first is the ordinary physical world of objects that exist in space and time. Objects obey simple laws. When any object moves or changes, we can usually account for it in terms of other objects pushing it, or else of gravity or wind. We also live in a social realm of persons, families, and companies; those entities appear to be ruled by quite different kinds of causes and laws. Whenever a person moves or changes, we look for signs of intentions, ambitions, infatuations, promises, threats, and the like — none of which could affect a brick. We also live in a psychological realm — inhabited by entities we call by names like meanings, ideas, and memories. These, too, appear to obey different rules.
The causes in the physical realm seem terribly different from those that work in the social and psychological realms — so different that they seem to belong to different worlds In some respects our bodies act exactly like ordinary objects: they have shapes we can see and touch, and they have locations that change when we're dropped or pushed. Yet in other ways, our bodies act quite differently from other things, and this appears to be because of minds. But what on earth are minds? For ages people have wondered about the relationship between the mind and body; some philosophers became so desperate as to suggest that only the mental world is real and the real world is merely an illusion. (That idea just makes the problem worse, because it can't even explain why there seems to be a physical world.) Most thinkers have ended up with images that portray two different kinds of worlds, one of matter and one of mind, somehow connected by mysterious threads of spiritual causality, somewhat like the films and tendrils formed when sticky stuff is pulled apart. Certain modern physicists have even speculated that these connections are somehow involved with the uncertainty principle in physics, perhaps because that problem also confounds their usual conceptions of causality. I see no merit in such ideas because as far as I'm concerned, the so-called problem of body and mind does not hold any mystery:
Minds are simply what brains do.
Whenever we speak about a mind, we're speaking of the processes that carry our brains from state to state. And this is what makes minds appear to us so separate from their physical embodiments: it is because concerns about minds are really concerns with relationships between states — and this has virtually nothing to do with the natures of the states themselves. This is why we can understand how a society of agents like Builder will work without knowing the physical constitution of its agents: what happens depends only on how each agent changes its state in response to its previous state and those of the other agents that connect to it. Other than that, it does not matter in the least what are the individual agents' colors, sizes, shapes, or any other properties that we could sense. So naturally minds seem detached from physical existence. It doesn't matter what agents are; it only matters what they do — and what they are connected to.
Why does a mind seem so unlike any other kind of thing? First, as we just said, minds aren't things — at least they share none of the usual properties of things, like colors, sizes, shapes, or weights. Minds lie beyond the reach of the senses of sound, touch, sight, smell, and taste. Yet though minds aren't things at all, they certainly have vital links to the things we call brains. What is the nature of those bonds? Are minds peculiar entities, possessed alone by brains like ours? Or could those qualities of minds be shared, to various degrees, by everything? Now, when we said, Minds are simply what brains do, that should have made us ask as well, Does every other kind of process also have a corresponding kind of mind? This could lead to an argument. One side might insist that this is merely a matter of degree, because people have well-developed minds while bricks or stones have almost none. Another side might try to draw a sharper boundary, arguing that only people can have minds — and, maybe, certain animals. Which side is right? This isn't a matter of wrong or right, since the issue is not about a fact, but only about when it's wise to use a certain word. Those who wish to reserve the label mind for only certain processes are obliged to specify which processes deserve that name. Those who claim that every kind of process has a corresponding type of mind are obliged to classify all minds and processes. The trouble with this is that we don't yet have adequate ways to classify processes.
Why are processes so hard to classify? In earlier times, we could usually judge machines and processes by how they transformed raw materials into finished products. But it makes no sense to speak of brains as though they manufacture thoughts the way factories make cars. The difference is that brains use processes that change themselves — and this means we cannot separate such processes from the products they produce. In particular, brains make memories, which change the ways we'll subsequently think. The principal activities of brains are making changes in themselves. Because the whole idea of self-modifying processes is new to our experience, we cannot yet trust our commonsense judgments about such matters.
As for brain science, no one ever before tried to study machines with billions of working parts. That would be difficult enough, even if we knew exactly how every part worked, and our present-day technology does not yet allow us to study the brain cells of higher animals while they're actually working and learning. This is partly because those cells are extremely small and sensitive to injury, and partly because they are so crowded together that we have not yet been able to map out their interconnections.
These problems will all be solved once we have better instruments and better theories. In the meantime, the hardest problems we have to face do not come from philosophical questions about whether brains are machines or not. There is not the slightest reason to doubt that brains are anything other than machines with enormous numbers of parts that work in perfect accord with physical laws. As far as anyone can tell, our minds are merely complex processes. The serious problems come from our having had so little experience with machines of such complexity that we are not yet prepared to think effectively about them.
Suppose I had once borrowed your boat and, secretly, replaced each board with a similar but different one. Then, later, when I brought it back, did I return your boat to you? What kind of question is that? It's really not about boats at all, but about what people mean by same. For same is never absolute but always a matter of degree. If I had merely changed one plank, we'd all agree that it's still your boat — but after all its parts are changed, we're not so sure of its identity. In any case, we do not doubt that the second boat will behave in much the same way — to the extent that all those substituted boards are suitably equivalent.
What has this to do with brains?  If we put it in the same environment, this new machine would reproduce the same processes as those within your brain. Would that new machine be the same as you? Again, the real question is not what we mean by you, but what we mean by same. There isn't any reason to doubt that the substitute machine would think and feel the same kinds of thoughts and feelings that you do — since it embodies all the same processes and memories. Indeed, it would surely be disposed to declare, with all your own intensity, that it is you. Would that machine be right or wrong? As far as I can see, this, too, is merely a matter of words. A mind is a way in which each state gives rise to the state that follows it. If that new machine had a suitable body and were placed in a similar environment, its sequence of thoughts would be essentially the same as yours — since its mental states would be equivalent to yours.
Modifying or replacing the physical parts of a brain will not affect the mind it embodies, unless this alters the successions of states in that brain.
You might object to this idea about duplicating minds on the grounds that it would never be practical to duplicate enough details. You could argue the same about that borrowed boat: no matter how carefully a carpenter were to copy every board, there would always remain some differences. This plank would be a little too stiff, that one would be a little too weak, and no two of them would bend in exactly the same way. The copied boat would never be precisely the same — even though you might need a microscope to see the differences. For similar reasons, it would be impractical to duplicate, with absolute fidelity, all the interactions in a brain. For example, our brain cells are all immersed in a liquid that conducts electricity, which means that every cell has at least a small effect on every other cell. If we tried to imitate your brain with a network of computer chips, many of those tiny interactions would be left out.
Can you then boast that your duplicated brain-machine would not have the same mind as yours because its computer chips don't work exactly like the brain cells they purport to replace? No; you'd get more than you bargained for if you argued that the new machine was not the same as you, merely because of microscopic differences. Consider that as you age, you're never the same as a moment ago. If such small differences matter that much, this would prove that you yourself are not the same as you.
Consider the popular idea that a person is capable of two kinds of thinking at once — a right brain kind and a left brain kind — as though there were two different individuals inside each human brain. This raises some odd questions, since there are many other ways to draw imaginary boundaries through brains.
If you agree that each person has both a left-brain mind and right-brain mind, then you must also agree that each person also has a front-brain mind and a back-brain mind! Can a single large mind contain so many smaller ones, with overlapping boundaries? It makes sense to think of part of a structure as being a thing in its own right only when the relationships among parts of that structure have some significant type of coherency. Before you'd say that a certain arbitrary section of brain contains a mind, you'd want to have some evidence that what happens inside that boundary is something you would consider to be a mind.
The less another entity resembles you, the less it means for you to say that it, like you, must have a mind. Do our very smallest agencies have minds? No, because it would make no more sense to say this than to say that two trees form a forest or that two bricks form a wall. But there are indeed some agencies inside our brains that do have humanlike abilities to solve, by themselves, some types of problems that we regard as hard. For example, your agencies for locomotion, vision, and language may contain within their boundaries some processes that are quite as intricate as those you use for your own conscious thought. Possibly, some of those processes are actually more conscious than you are yourself, in the sense that they maintain and use even more complete records of their own internal activities. Yet what happens in those agencies is so sealed off that you have no direct experience of how you distinguish a cat from a dog, retrace your last few steps, or listen and talk without knowing how you do it.
All this suggests that it can make sense to think there exists, inside your brain, a society of different minds. Like members of a family, the different minds can work together to help each other, each still having its own mental experiences that the others never know about. Several such agencies could have many agents in common, yet still have no more sense of each other's interior activities than do people whose apartments share opposite sides of the same walls. Like tenants in a rooming house, the processes that share your brain need not share one another's mental lives.
If each of us contains several such mini-minds, could any special exercise help put them all in closer touch ? Certainly there are ways to become selectively aware of processes that are usually not conscious at all. But becoming aware of everything that happens in brains would leave no room for thought. And the reports of those who claim to have developed such skills seem singularly uninformative. If anything, they demonstrate that it's even harder than we think to penetrate those unresisting barriers.
Our view of the body and the mind as separate entities is only one example of our many ways to view the world as divided into different realms. Imagine that a committee were commissioned to write down everything about the universe in a perfectly organized book.
Why do the gaps between the lines seem smaller than those that separate the pages? It is because we better understand what happens in between. We understand how walls relate to bricks because they represent closely related levels of organization. Similarly, we understand the relation between houses and walls. But it would be hard to cross the gap between houses and bricks without having enough intermediate concepts such as that of a wall. It simply isn't practical to think of the place where someone lives as a network of relationships among a million boards and bricks.
It's much the same in other realms; we need to be able to describe things at many levels of detail. We all belong to families or companies, and sometimes we can think of each group as nothing but a network of agreements and relationships. But when we need a larger view, as when thinking about the politics of an entire country, we cannot think effectively without regarding entire families or companies as though they were single objects in a different realm. The same applies to how we think about our minds. Even if you knew all the details of each little agent in your brain, your higher-level processes would still need coarser summaries.
Why is it easier to understand how walls relate to bricks, or families to individuals, than to understand how thoughts relate to things? It's not because there's any single mystery. It is because the level gap between walls and bricks is really much smaller than that between minds and brain cells. Suppose we actually had that wonderful encyclopedia of all possible knowledge, arranged according to the nearness of topics. There we'd find the essays on walls quite close to those about bricks. But the sections that cover the nature of thoughts would lie volumes away from the ones on the nature of things.
To see that we can think in several mental realms at once, consider the role of the word give in this simple sentence:
Mary gives Jack the kite.
We can see at least three distinct meanings here. First, we could represent the idea of the kite's motion through physical space by using a Trans-frame whose Trajectory begins at Mary's hand and ends at Jack's.
But quite beyond that realm of space, we also find a different significance in what Mary did — in another realm that we'll call
estates. This involves a different sense of give, in which the object need not actually move at all! Instead, what happens is the transfer of its ownership.
Each of us has an estate — the collection of possessions we control. And this realm of estate is more important than it might seem, because it lies between the realms of objects and ideas. In order to carry out our plans, it is not enough only to know what things or ideas are required and how to adapt them to our purposes. We must also be able to take possession of those objects or ideas, either by right or by might.
Possession plays essential roles in all our plans, because we can't use any materials, tools, or ideas until we gain control of them.
We can also interpret Mary's act within a social realm, in which we understand that giving gifts involves yet other kinds of relationships. No sooner do you hear of Mary's gift than certain parts of your mind become concerned with why she was so generous and how this involved her affections and obligations.
How can so many different thoughts proceed at the same time, without interfering with one another? I suspect that it is for the same reason that we have no trouble imagining an apple as both round and red at the same time: in that case, the processes for color and shape use agents that do not compete. Similarly, the different processes involved with ideas like give may operate in agencies so different that they rarely need to compete for the same resources.
What enables us to comprehend Mary gives Jack the kite in so many ways at once? Different meanings don't conflict when they apply to separate realms — but that can't be quite what's happening here, since the physical, social, and mental realms are closely linked in many ways. So now I'll argue just the opposite, that these meanings are so similar they don't conflict! Here is my hypothesis about what holds together all these aspects of our thoughts:
Many of our higher level conceptual-frames are really parallel arrays of analogous frames, each active in a different realm.
Consider all the different roles played by the Actor pronome of our sentence. In the physical realm, the Origin of give is Mary's hand. In the possessional realm of give and take, that Origin is in Mary's estate — since Mary can only give Jack what she owns. Similarly, in the physical realm, it is the kite itself that moves from Mary's hand to Jack's; however, in the realm of estates, the kite's ownership is what changes hands.
This suggests that certain pronomes can operate in several different realms at once. Let's call them paranomes to emphasize their parallel activities. When the language-agency activates some polynemes and paranomes, these agents run crosswise through the agencies of various realms to arouse several processes and frames at the same time; these correspond to different interpretations, in different realms, of the same phrase or sentence. Then, because each major agency contains its own memory-control system, the agencies within each realm can simultaneously apply their own methods for dealing with the corresponding aspect of the common topic of concern. In this way, a single language-phrase can at the same time evoke different processes involved with social dispositions, spatial images, poetical fancies, musical themes, mathematical structures — or any other assortment of types of thought that don't interfere too much with one another.
This is not to say that all these different modes of thought will proceed independently of one another. Whenever any process gains momentary control over a paranome, many other processes can be affected. For example, one agency's memory-control process might thus cause the agencies in several other realms simultaneously to blink on and off their Origin and Destination paranomes. This would force the agencies active in each of those realms to focus upon whichever types of differences they then discern; then, in between such episodes, each agency can apply its own way of thinking to the corresponding topic, difference, or relationship. By using these cross-connecting polynemes and paranomes, the activity in each realm can proceed sometimes independently, yet at other times influence and be affected by what happens in the other realms.
We often describe the things we like as elevated, lofty, or heavenly. Why do we see such things in terms of altitude in space? We often speak of time itself in spatial terms, as though the future were ahead of us while the past remains behind. We think of problems as obstacles to go around and turn to using diagrams to represent things that don't have shapes at all. What enables us to turn so many skills to so many other purposes? These tendencies reflect the systematic cross-realm correspondences embodied in our families of polynemes and paranomes.
At each instant, several realms may be engaged in active processing. Each has separate processes but must compete for control of the ascending nemes that lead into the language- agency. Which polyneme will play the role of Origin in the next sentence-frame? Will it be Mary's physical arm or hand, or Mary's social role as party guest? It sometimes seems
as though the language-agency can focus on only one realm at a time.
This could be one reason why language scientists find it hard to classify the roles words play in sentence-frames. No sooner does a language-agency assign some polynemes and isonomes to a phrase than various mind divisions proceed to alter how they're used inside each different realm. Every shift of control from one realm to another affects which particular nemes will be next to influence the language-agency. This causes moment-to-moment changes in the apparent meaning of a phrase.
At one moment, control over language may reside in the realm of thought that is working most successfully; at the next moment, it may be the one experiencing the most difficulty. Each shift in attention affects how the various expressions will be interpreted, and this in turn can affect which realm will next take center stage.
For example, the sentence Mary gives Jack the kite might start by arousing a listener's concern with Mary's social role as party guest. That would cause the pronomes of a social-frame to represent Mary's obligation to bring a present. But then the listener's possession realm might become concerned with Mary's ownership of that gift or with how she got control of it. This shift from social to possessional concern could then affect the processing of future sentences. For example, it will influence whether a phrase like Jack's kite is interpreted to refer to the kite that Jack happens to be holding or to a different kite that Jack happens to own.
Every mental realm accumulates its own abilities but also discovers, from time to time, how to exploit the skills of other realms. Thus the mind as a whole can learn to exploit the frames developed in the realm of space both for representing events in time and for thinking about social relationships. Perhaps our chaining skills are the best example of this; no matter which realm or realms they originate in, we eventually learn to apply them to any collection of entities, events, or ideas (in any realm whatever) that we can arrange into sequences. Then chains assume their myriad forms, such as spatial order, psychological causality, or social dominance.
What makes our minds form many separate mental realms, instead of attempting, as scientists do, to see all aspects of the world in a unified way? Because, at least in everyday life, the latter simply isn't practical. Consider how different the rules are within the physical and social realms. If you want your furniture inside a different room, you normally would push it there. But when you want to move your party guests, it would be rude to push them there. Contrast the principles of physics and geometry with those we use in the social realm. In the physical realm, the rules seem very orderly:
-- A stationary object stays where it is unless another object pushes it. --- A moving object continues in its course until some external force makes it stop. ----All unsupported objects start to fall.
-----No two things can occupy the same location. -----Etc.
These principles seem clear to us — but infants cannot appreciate them until they've built up ways to represent ingredients like thing, shape, place, move, and near. It takes each child many years to develop these abilities.
Our comprehensions of social acts are based on different principles. When an ordinary object moves around, we usually see an obvious cause; most likely, another object pushed it. But when we see a person move, we rarely see the cause at all — because it's buried in a brain. In predicting how a person will react to an expression or gesture, we have little use for physical properties like color, shape, or place. Instead, we employ almost entirely different conceptions. To guess the outcome of a social interaction, we have to be able to represent each person's mental state — and to do that, we must develop concepts about traits, dispositions, motives, and plans. The concepts that serve so well for physical objects are of little help within the social realm — and vice versa.
When normal children start to talk, among the early aspects of their speech are words that distinguish animate things. Frequently, a child will use a single expression for all kinds of animals, and for everything else that can move by itself — for example, an automobile. According to our view of things, this surely is no accident.
To adults, the laws that govern the physical world seem simpler and more orderly than those that apply to human events. Does this mean that for infants, too, it should be easier first to master the physical world and later to proceed toward social and psychological understanding? No. Paradoxically, the social realm is initially the easier! Imagine that an infant wants a certain toy and that there's a sympathetic person near. The easiest thing is to make a request — that is, a gesture, smile, or cry — and this will probably achieve the goal. It would be far more difficult for the infant to coordinate all the complicated machinery for planning and executing the trajectory for propelling the object from where it is to where the infant wishes it to be. From the point of view of a physically helpless infant, the social realm is by far the simpler one.
Isn't it curious that infants find social goals easier to accomplish than physical goals, while adults find the social goals more difficult? One way to explain this is to say that the presence of helpful people simplifies the infant's social world — since because of them, simpler actions solve harder problems. Another explanation might be that the infant's social world is just as complicated as that of the adult, except the presence of helpful people makes the infant's mind more powerful — by making the agencies inside those other people's brains available for exploitation by the agencies in the infant's brain. Both explanations are the same, except for drawing different boundaries.
How do children start on the path toward distinguishing between psychological and physical relationships? In the appendix I'll suggest that our infant brains are genetically equipped with machinery for making it easy to learn social signals. But what if that machinery should somehow fail, so that by chance — or by neglect or accident — the realm-divisions never form? Then all those different kinds of thoughts would fuse together into one — and the child would face the impossible task of formulating principles that work in all domains. A child that tried to see the world without dividing it into realms would find no simple rules at all that work across so large a range.
This is why each child must learn different rules for the physical and psychological realms. But this means that the child must face not merely two formidable problems, but three. In addition to developing two different sets of concepts, the child must also develop agencies to manage those concepts by keeping them apart in different agencies, as we saw when we talked about Papert's principle.
This could explain some aspects of the disorders of the children psychiatrists call autistic. These unhappy individuals do not establish effective communication with other people, although they may acquire some competence at dealing with physical things. No one knows the causes of those disorders. Some might begin when certain mental realms do not develop normally. Other kinds of problems could emerge after those divisions form, if their separateness were compromised by some too intense attempt to unify them. To be sure, that is what scientists do, but unlike those whom we regard as mentally ill, scientists also manage to maintain their ordinary views. Once a child is deprived of the normal ways to divide those realms — no matter what the cause of this — that hapless mind is doomed to fail.
We always try to use old memories to recollect how we solved problems in the past. But nothing's ever twice the same, so recollections rarely match. Then we must force our memories to fit — so we can see those different things as similar. To do this, we can either modify a memory or change how we represent the present scene. For example, suppose you need a hammer but can only find a stone. One way to turn that stone to your purposes would be to make it fit your memory of a hammer's appearance — for example, by making your description of the stone include an imaginary boundary that divides it into two parts, to serve as handle and as head. Another way would be to make your hammer frame accept the entire stone as a hammer without a handle. Either scheme will make the memory match the description, but both will lead to conflicts in other agencies.
How hard it will be to make such a match depends both on which agents are now active in your mind and on the levels of their priorities — in short, upon the context already established. It will be easy for you to see two things as similar when you only need to change relatively weak attachments at the conceptual fringes of familiar things. But frequently the ease of comprehension will also depend upon how readily you can switch from one mental realm to another.
Consider what must happen in our minds when poets speak about their loves in romantic, floral terms. We all have learned a certain common way to represent a woman's beauty in terms of flowers that are prone, alas, to fade. For centuries this formula has been established in our language and literature; however, at first it must have seemed bizarre. We cannot possibly match our descriptions of women and flowers if we insist on interpreting such phrases and poems literally — that is to say, illiterately — entirely within the physical realm of the appearance, composition, and behavior of a typical flower.
To be sure, the colors, symmetries, and smells of flowers can certainly arouse the sorts of states we associate with things we've come to see as beautiful. But the more essential trick is in knowing how to turn entirely away from the physical realm and dwell instead upon the images and fantasies that flowers evoke in other spheres — such as the sense of a thing so sweet and innocent, so helpless and delicate, that it invites affection, nurture, and protection. Features like these must be made to fit the listener's private love ideal — only then can the metaphor match.
This, Herrick's bitter verse defeats. By holding us so tightly to the usual frames for human shapes, he steers us into fantasies of vegetables with hands and feet.
Listen closely to anything anyone says, and soon you'll hear analogies. We speak of time in terms of space, as like a fluid that's running out; we talk of our friends in physical terms, as in Mary and John are very close. All of our language is riddled and stitched with curious ways of portraying things as though they belonged to alien realms.
We sometimes call these metaphors, our ways to transport thoughts between the various mental realms. Some metaphors seem utterly pedestrian, as when we speak of taking steps to cause or prevent some happening. Other metaphors seem more miraculous, when unexpected images lead to astonishing insights — as when a scientist solves a problem by conceiving of a fluid as made of tubes or of a wave as an array of overlapping, expanding spheres. When such conceptions play important roles in our most productive forms of thought, we find it natural to ask, What is a metaphor? But we rarely notice how frequently we use the same techniques in ordinary thought.
What, then, is a metaphor? It might be easy to agree on functional definitions like A metaphor is that which allows us to replace one kind of thought with another. But when we ask for a structural definition of metaphor, we find no unity, only an endless variety of processes and strategies. Some are simple, as when we make an analogy by stripping away so many details that two different objects seem the same. But other forms of metaphor are as complex as can be. In the end there is little to gain by cloaking them all under the same name metaphor, because there isn't any boundary between metaphorical thought and ordinary thought. No two things or mental states ever are identical, so every psychological process must employ one means or another to induce the illusion of sameness. Every thought is to some degree a metaphor.
Once scientists like Volta and Ampere discovered how to represent electricity in terms of the pressures and flows of fluids, they could transport much of what they already knew about fluids to the domain of electricity. Good metaphors are useful because they transport uniframes, intact, from one world into another. Such cross-realm correspondences can enable us to transport entire families of problems into other realms, in which we can apply to them some already well-developed skills. However, such correspondences are hard to find since most reformulations merely transform the uniframes of one realm into disorderly accumulations in the other realm.
From where do we obtain our most productive, systematic, cross- realm correspondences? Some must be virtually born into our brains through the wiring of our paranomes; other metaphors we discover by ourselves as individuals; but most of them are learned from other members of our cultural communities. Finally, from time to time, someone discovers a new reformulation that is both so fruitful and so easy to explain that it becomes part of the general culture. Naturally, we'd like to know how the greatest metaphorical discoveries were made. But because this is buried in the past, the best and rarest of those events may never be explained at all. Our greatest ideas, like our evolutionary genes, need form only once, by accident, and then can spread from brain to brain.
What does knowing really mean? Suppose Mary (or some other creature or machine) can answer certain questions about the world — without the need to do any actual experiments. Then we'd agree that Mary knows those things about the world. But what would it mean, to you or to me, to hear Jack say that Mary knows geometry ? For all we know, Mary might believe that circles are squares and it happens that Jack agrees! Jack's statement tells us more about Jack than about Mary.
When Jack says, Mary knows geometry, this indicates to us that Jack would probably be satisfied by Mary's answers to the questions about geometry that he would be disposed to ask.
The meaning of Mary knows geometry depends on who is saying it. After all, no one knows everything about geometry; that statement would not mean the same to us as to a mathematician, whose concepts of geometry are different from those of ordinary persons. In the same way, the meanings of many other terms depend upon the speaker's role. Even an apparently unambiguous statement like This is a painting of a horse shares this character: you can be sure of little more than that it displays a representation that in someone's view resembles a horse in some respects.
Then why, when we talk about knowledge, don't we have to say who all those speakers and observers are? Because we make assumptions by default. When a stranger says that Mary knows geometry, we simply assume that the speaker would expect any typical person who knows Mary to agree that she knows geometry. Assumptions like that allow us to communicate; unless there is some reason to think otherwise, we assume that all the things involved are typical. It does not bother us that a professional mathematician might not agree that Mary knows geometry — because a mathematician doesn't fit our stereotype of a typical person.
You might maintain that none of this applies to you, since you know what you know about geometry. But there's still an observer on the scene, only now it is hiding inside your mind — namely, the portion of you that claims you know geometry. But the part of you that makes this claim has little in common with the other parts that actually do geometry for you; those agencies are probably incapable of speech and probably devoid of thoughts about your knowledge and beliefs.
Naturally, we'd all prefer to think of knowledge as more positive and less provisional or relative. But little good has ever come from trying to link what we believe to our ideals about absolute truths. We always yearn for certainty, but the only thing beyond dispute is that there's always room for doubt. And doubt is not an enemy that sets constraints on what we know; the real danger to mental growth is perfect faith, doubt's antidote.
We often speak as though we classify our thoughts into different types called facts, opinions, and beliefs.
How do these statements differ from one another? Some philosophers have argued that knowing must mean true and justified belief. However, no one has ever found a test to prove what's justified or true. For example, we all know that the sun rises in the morning. Once, long ago, some people thought this was due to godlike agents in the sky, and that the sun's trajectory was where Apollo steered his chariot. Today our scientists tell us that the sun doesn't really rise at all, because sunrise is simply what we each experience when the planet Earth's rotation moves us into the sun's unchanging light. This means we all know something that isn't true.
To comprehend what knowing is, we have to guard ourselves against that single-agent fallacy of thinking that the I in I believe is actually a single, stable thing. The truth is that a person's mind holds different views in different realms. Thus, one part of an astronomer's mind can apply the common view of sunrise to down-to-earth affairs, regarding the sun as like a lamp that wakes us up and lights our way. But at the same time, that same astronomer can apply the modern physical view to technical problems in astronomy. We each use many different views, and which we choose to use depends, from one moment to the next, upon the changing balance of power among our agencies.
Then if what we believe is so conditional, what makes us feel that our beliefs are much more definite than that? It is because whenever we commit ourselves to speak or act, we thereby have to force ourselves into clear-cut, action-oriented states of mind in which most of our questions are suppressed. As far as everyday life is concerned, decisiveness is indispensable; otherwise we'd have to act so cautiously that nothing would get done. And here lies much of what we express with words like guess, believe, and know. In the course of making practical decisions (and thereby turning off most agencies), we use such words to summarize our various varieties of certainty.
The notion that only certain of a person's beliefs are genuine plays vital roles in all our moral and legal schemes. Whenever we censure or applaud what other people do, we're taught to be more concerned with what those other people genuinely expected or intended to happen than with what actually happened. This doctrine underlies how we distinguish thoughtlessness and forgetfulness from lies, deceit, and treachery. I do not mean that such distinctions are not important, only that they do not justify the simplistic assumption that, among all the mind's activities, certain special kinds of thoughts are essentially more genuine than others. All such distinctions seem less absolute when every deeper probe into beliefs reveals more ambiguities.
Does a book know what is written inside it? Clearly, no. Does a book contain knowledge? Clearly, yes. But how could anything contain knowledge, yet not know it? We've seen how saying that a person or machine possesses knowledge amounts to saying that some observer could employ that person or machine to answer certain kinds of questions. Here is another view of what it means to know.
Jack knows about A means that there is a model M of A inside Jack's head.
But what does it mean to say that one thing is a model of another and how could one have a model in one's head? Again, we have to specify some standard or authority. Let's make Jack be the judge of that:
Jack considers M to be a good model of A to the extent that he finds M useful for answering questions about A.
For example, suppose that A is a real automobile, and M is the kind of object we call a toy or model car. Then Jack will be able to use M to answer certain questions about A. However, we would think it strange to say that M is Jack's knowledge about A — because we reserve the word knowledge for something inside a head, and Jack can't keep a toy inside his head. But we never said that a model must be an ordinary physical object. Our definition allows a model to be anything that helps a person answer questions. Accordingly, a person could possess a mental model, too — in the form of some machinery or subsociety of agents inside the brain. This provides us with a simple explanation of what we mean by knowledge: Jack's knowledge about A is simply whichever mental models, processes, or agencies Jack's other agencies can use to answer questions about A. Thus, a person's mental model of a car need not itself resemble an actual car in any obvious way. It need not itself be heavy, fast, or consume gasoline to be able to answer questions about a car like How heavy is it? or How fast can it go?
Our mental models also work in social realms to answer questions like Who owns that car? or Who permitted you to park it there? However, to understand questions like these, we have to ask what people mean by who — and the answer is that we make mental models of people, too. In order for Mary to know about Jack's dispositions, motives, and possessions, Mary has to build inside her head some structure to help answer those kinds of questions — and that structure will constitute her mental model of Jack. Just think of all the different things our person-models do for us! If Mary knows Jack well enough, she'll be able to reply not only to physical questions like How tall is Jack? but also to social inquiries such as Does he like me? and even to psychological queries like What are Jack's ideals? Quite possibly, Mary's model of Jack will be able to produce more accurate answers to such questions than Jack himself could produce. People's mental models of their friends are often better, in certain respects, than their mental models of themselves.
We all make models of ourselves and use them to predict which sorts of things we'll later be disposed to do. Naturally, our models of ourselves will often provide us with wrong answers because they are not faultless ways to see ourselves, but merely self-made answering machines.
Now let's look at Mary's model of the world. (By world I mean the universe, not just the planet Earth.) This is simply all the structures in Mary's head that Mary's agencies can use to answer questions about things in the world.
But what if we were to ask Mary a question not about any particular object, but one like What sort of thing is the world itself? That would put Mary in a curious predicament. She cannot answer this by using her world model, because each part of that model is designed only to answer questions about particular things. The trouble is that the world itself is not a particular thing inside the world.
One way to deal with this (and a method that, surely, many children use) is adding to the model of the world an additional object — that represents the world itself. Then, since any object must have properties, the child might then assign to this the features, say, of an extremely large ball. Naturally this will lead to trouble should that child persist in asking ordinary questions about this extraordinary object — such as What keeps the universe in place? or What's outside the universe? — for these then lead to strange and inconsistent images. Eventually we learn some ways to deal with this — for example, by learning which questions to suppress. But as in the case of a perfect point, we may always feel uncomfortable with the thought of a thing that is unimaginably large in size, but has no shape at all.
When you get right down to it, you can never really describe any worldly thing, either — that is, in any absolute sense. Whatever you purport to say about a thing, you're only expressing your own beliefs. Yet even that gloomy thought suggests an insight. Even if our models of the world cannot yield good answers about the world as a whole, and even though their other answers are frequently wrong, they can tell us something about ourselves. We can regard what we learn about our models of the world as constituting our models of our models of the world.
Now let's ask Mary to describe herself — to tell us everything she can about her shape and weight and size and strength, her dispositions and her traits, her accomplishments and ambitions, wishes, fears, possessions, and so on. What might be the general character of what we'd hear? At first it would be hard to assemble any coherent sense of all those details. But gradually we'd notice that various groups of items were closely related, while others were rarely mentioned in connection with one another. Little by little, we would discern structure and organization in what Mary had said, and finally we'd start to see the outlines of at least two different mental realms.
Now, what would happen if we asked Mary to speak not about specific things, but about the general subject of What kind of entity am I? Since she has no direct way to examine her entire self, she can only summarize what she can discover about her mental model of herself. In doing so, she'll probably find that almost everything she knows appears to lie in two domains, with relatively little in between. This means that Mary's model of her model of herself will have an overall dumbbell shape, one side of which represents her physical self, the other side of which represents her psychological self.
Do people go on to make models of their models of their models of themselves? If we kept on doing things like that, we'd get trapped in an infinite regress. What saves us is that we get confused and lose track of the distinctions between each model and the next — just as our language-agencies lose track when they hear about the rat that the cat that the dog worried killed. The same thing must happen whenever we ask ourselves questions like Did John know that I knew that he knew that I knew that he knew that? And the same thing happens whenever we try to probe into our own motivations by continually repeating, What was my motive for wanting that?
Eventually, we simply stop and say, Because I simply wanted to. The same when we find things hard to decide: we can simply say, I just decide, and this can help us interrupt what otherwise might be an endless chain of reasoning.
We each believe that we possess an Ego, Self, or Final Center of Control, from which we choose what we shall do at every fork in the road of time. To be sure, we sometimes have the sense of being dragged along despite ourselves, by internal processes which, though they come from within our minds, nevertheless seem to work against our wishes. But on the whole we still feel that we can choose what we shall do. Whence comes this sense of being in control? According to the modern scientific view, there is simply no room at all for freedom of the human will. Everything that happens in our universe is either completely determined by what's already happened in the past or else depends, in part, on random chance. Everything, including that which happens in our brains, depends on these and only on these:
A set of fixed, deterministic laws. A purely random set of accidents.
There is no room on either side for any third alternative. Whatever actions we may choose, they cannot make the slightest change in what might otherwise have been — because those rigid, natural laws already caused the states of mind that caused us to decide that way. And if that choice was in part made by chance — it still leaves nothing for us to decide.
Every action we perform stems from a host of processes inside our minds. We sometimes understand a few of them, but most lie far beyond our ken. But none of us enjoys the thought that what we do depends on processes we do not know; we prefer to attribute our choices to volition, will, or self-control. We like to give names to what we do not know, and instead of wondering how we work, we simply talk of being free. Perhaps it would be more honest to say, My decision was determined by internal forces I do not understand. But no one likes to feel controlled by something else.
Why don't we like to feel compelled? Because we're largely made of systems designed to learn to achieve their goals. But in order to achieve any long-range goals, effective difference-engines must also learn to resist whatever other processes attempt to make them change those goals. In childhood, everyone learns to recognize, dislike, and resist various forms of aggression and compulsion. Naturally we're horrified to hear about agents that hide in our minds and influence what we decide.
In any case, both alternatives are unacceptable to self-respecting minds. No one wants to submit to laws that come to us like the whims of tyrants who are too remote for any possible appeal. And it's equally tormenting to feel that we're a toy to mindless chance, caprice, or probability — for though these leave our fate unfixed, we'd still not play the slightest part in choosing what shall come to be. So, though it's futile to resist, we continue to regard both Cause and Chance as intrusions on our freedom of choice. There remains only one thing to do: we add another region to our model of our mind. We imagine a third alternative, one easier to tolerate; we imagine a thing called freedom of will, which lies beyond both kinds of constraint.
To save our belief in the freedom of will from the fateful grasps of Cause and Chance, people simply postulate an empty, third alternative. We imagine that somewhere in each person's mind, there lies a Spirit, Will, or Soul, so well concealed that it can elude the reach of any law — or lawless accident.
I've drawn the box for Will so small because we're always taking things out of it — and scarcely ever putting things in! This is because whenever we find some scrap of order in the world, we have to attribute it to Cause — and whenever things seem to obey no laws at all, we attribute that to Chance. This means that the dominion controlled by Will can only hold what, up to now, we don't yet understand. In ancient times, that realm was huge, when every planet had its god, and every storm or animal did manifest some spirit's wish. But now for many centuries, we've had to watch that empire shrink.
Does this mean that we must embrace the modern scientific view and put aside the ancient myth of voluntary choice? No. We can't do that: too much of what we think and do revolves around those old beliefs. Consider how our social lives depend upon the notion of responsibility and how little that idea would mean without our belief that personal actions are voluntary. Without that belief, no praise or shame could accrue to actions that were caused by Cause, nor could we assign any credit or blame to deeds that came about by Chance. What could we make our children learn if neither they nor we perceived some fault or virtue anywhere? We also use the idea of freedom of will to justify our judgments about good and evil. A person can entertain a selfish impulse, yet turn it aside because it seems wrong, and that must happen when some self-ideal has intervened to overrule another goal. We can feel virtuous when we think that we ourselves have chosen to resist an evil temptation. But if we suspected that such choices were not made freely, but by the interference of some hidden agency, we might very well resent that interference. Then we might become impelled to try to wreck the precious value-schemes that underlie our personalities or become depressed about the futility of a predestination tempered only by uncertainty. Such thoughts must be suppressed.
No matter that the physical world provides no room for freedom of will: that concept is essential to our models of the mental realm. Too much of our psychology is based on it for us to ever give it up. We're virtually forced to maintain that belief, even though we know it's false — except, of course, when we're inspired to find the flaws in all our beliefs, whatever may be the consequence to cheerfulness and mental peace.
How could anything as complex as a human mind work so well for so many years? We all appreciate those splendid feats of writing plays and symphonies. But we rarely recognize how wonderful it is that a person can traverse an entire lifetime without making a single really serious mistake — like putting a fork in one's eye or using a window instead of a door. How do we do such amazing feats as to imagine things we've never seen before, to overcome obstacles, to repair things that are broken, to speak to one another, to have new ideas? What magical trick makes us intelligent? The trick is that there is no trick. The power of intelligence stems from our vast diversity, not from any single, perfect principle. Our species has evolved many effective although imperfect methods, and each of us individually develops more on our own. Eventually, very few of our actions and decisions come to depend on any single mechanism. Instead, they emerge from conflicts and negotiations among societies of processes that constantly challenge one another. In this book we've seen many such dimensions of diversity:
The accumulation of myriad subagents. We learn many different ways to achieve each kind of goal. The many realms of ordinary thought. When one viewpoint fails to solve a problem, we can adopt other perspectives. The endowment of several instinctive protominds. We embody different kinds of organizations for achieving many kinds of goals. The hierarchies of administration grown in accord with Papert's principle. When simple methods fail, we can build new levels of organization. The evolutionary vestiges of animals that still remain inside our brains. We use machinery evolved from fish, amphibia, reptiles, and earlier mammals. The sequence of stages of the growing child's personality. We accumulate different personalities that we can apply to
different situations. The complex, ever-growing heritage of language and culture. We can use methods and ideas developed by millions of our ancestors. The subordination of thought processes to censors and suppressors. We do not need perfect methods, since we can remember how imperfect methods fail.
Each of these dimensions gives you toughness and versatility. They offer alternative ways to proceed when any system fails. If part of your society of mind proposes to do what other parts find unacceptable, your agencies can usually find another way. Sometimes you merely need to turn to another branch of the same accumulation. When that fails, you can ascend to a higher level and engage a larger change in strategy. Then, even if an entire agency should fail, your brain retains earlier versions of it. This means that every facet of your personality may have the option to regress to an earlier stage, which already has proved itself competent to deal with the usual problems of life. Finally, when even that won't work, you can usually switch to an entirely different family of agencies. Whenever anything goes wrong, there are always other realms of thought.
Sometimes we ask why people are so similar. At other times, we wonder why they differ so much from one to the next. Often we try to classify our differences into those with which we're born and those we later learn — and then we find ourselves arguing about which virtues are inherited, and which we acquire from experience. Most arguments about nature vs. nurture are based on two mistakes. One is to talk about intelligence as though a person's quality of mind were like a quantity one could pour into a cup. The other mistake is to assume that there is a clear distinction between what we learn and how we learn — as though experience had no effect on how we learn.
Chance plays a major role in human differences, because each of us starts out by drawing lots from among our parents' genes. A gene is a unit of heredity — a specific chemical whose structure affects some aspects of the construction of the body and the brain. We inherit each of our genes from one parent or the other, more or less by chance, so as to receive about half of each parent's genes. Within the population as a whole, each particular kind of gene has variants that work in somewhat different ways, and there are so many possible combinations of these alternative genes that every child is born unique — except in the case of identical twins, who carry identical copies of genes. One thing that makes people both so different and so similar is this: we are similar because those alternative genes are usually quite similar — and we are different because those genes are not identical.
Every cell of the body contains identical copies of all of that person's genes. But not all genes are active at the same time — and this is why the cells in our different organs do different things. When a particular gene is turned on inside a cell, that cell manufactures copies of a particular chemical (called a protein), whose structure is determined by the structure of that gene. Proteins are used in many ways. Some of them are assembled into permanent structures, some are involved in manufacturing other chemicals, and certain proteins move around in the cell, to serve as messages that alter other processes.
Every cell has windows in its walls and special genes that control which chemicals can enter or leave through those windows. Then, certain of those chemicals can act as messages that change the states of specific genes in other cells. Thus groups of cells can also be societies. The effects of most of those messages between cells are temporary and reversible, but some of them can permanently change the character of other cells by altering the types of messages they can transmit and receive. In effect, this converts them into other types of cells. When new types of cells are produced this way, certain of them remain in place, but other types proceed to move and reproduce — to form new layers, strands, or clumps. Inside the brain, certain types of cells emit specific chemicals that drift out like scents; this causes certain other types of mobile cells that are sensitive to those particular chemicals to sniff out those scents and track them back to their sources — leaving tubelike trails behind. These traces of the travels of those migratory cells then form the nerve-bundles that interconnect various pairs of far-apart brain-agencies. With all this activity, the embryonic brain resembles a complex animal ecology — which even includes predators programmed to find and kill the many cells that happen to reach wrong destinations.
All human brains are similar in size and shape but differ in many smaller respects because of different alternative genes. Why does the human population support so many variant genes? One reason is that genes are sometimes altered by accidents. When this happens to a gene that lies within a reproductive cell — that is, inside an ovum or a sperm — the change will be inherited. We call this a mutation. Most often, a mutant gene will simply fail to manufacture some vital chemical, and this will so badly impair the offspring that natural selection will quickly remove the mutated gene from the population. But occasionally a mutant gene will endow those offspring with some substantial advantage. Then natural selection will spread copies of that gene so widely among the population that its predecessor gene becomes extinct. Finally, a variant gene may provide an advantage only in certain circumstances; this type of mutation may spread only to a certain proportion of the population, and both the new and the old variants will continue to coexist indefinitely. The richness of this reservoir of alternative genes can determine how quickly a population adapts to changes in ecological conditions — and thus determines whether the entire species can escape extinction over longer periods of time.
Now let's return to what genes do. Not all genes turn on at once; some start early and some start late. In general, the sooner a gene starts working, the greater its effect on what comes afterward. Accordingly, it is the early-starting genes that most affect the basic, large-scale architecture of our bodies and our brains. A mutation in an early-working gene is likely to cause such a drastic alteration of an animal's basic architecture that the embryo will not survive to be born, grow up, and reproduce successfully. Accordingly, most mutations of early-working genes are swiftly weeded out of the population by natural selection. Mutations in later-starting genes tend to cause less drastic differences, hence are not so swiftly weeded out and can accumulate in the population — for example, as variations in the genes that affect the sizes of connections between various brain-agencies. Every different combination of such variant genes produces a person with a somewhat different brain.
The early-starting genes thus frame the large-scale outlines of the brain — and their uniformity explains why people are so similar on the broadest scale. These must be the genes responsible for what we call human nature — that is, the predispositions every normal person shares. Generally, the uniformity of early-starting genes is what makes all the members of each animal species seem so similar; indeed, it is partly why the earth is populated with distinct, recognizable species like lions, turtles, and people, rather than with an indistinct continuum of all conceivable animals. No human mother ever bears a cat, since that would require too many different early-starting genes.
All normal children come to recognize the same sorts of physical objects. Is that because the concept of an object is innate in the human mind? Each of us becomes attached to certain other individuals. Does this mean that the concept of person, and the notion of love, are part of our inheritance? Every human child forms realms of thought that represent the physical, possessional, and psychological. But how could genes build concepts into minds when genes themselves are merely linked-together chemicals?
The problem is that thoughts proceed on levels so far removed from those of chemicals. This makes it hard for genes, which are merely chemicals, to represent such things as objects, persons, or ideas — at least in anything like the way that strings of words express our thoughts. Then how do genes encode ideas? The answer lies in the concept of predestined learning discussed in section 11.7. Although groups of genes cannot directly encode specific ideas, they can determine the architecture of agencies that are destined to learn particular kinds of processes. To illustrate this principle, we'll outline the architecture of an agency destined to learn to recognize a human individual.
When we first introduced the concept of a recognizer, we suggested a simple way to represent a physical object in terms of properties like color, texture, size, and shape — by combining evidence from several agencies, each containing sensors especially designed to react to certain particular properties. Now we'll take another step, by dividing each of those agencies into two sections that are similar in architecture, and which both receive sensory inputs from the eyes, ears, skin, and nose. The first system is destined, as before, to learn to represent physical objects in terms of simple properties. However, because the second system's inputs come from different types of agents, it is destined to learn to represent social objects — that is, people.
Our second social object agency takes all of its inputs from sensors that detect stimuli which usually signify the presence of a person — namely, human odors, voices, and faces. Because of this — and even though the genes that assemble this system know nothing of people — this system has no alternative but to learn to represent relations among the features of human individuals. Accordingly, this agency is destined to learn to recognize people!
The large-scale outline of this agency poses no engineering mystery — but we have to ask how genes could produce the sensory detectors that the system needs to do its job. There is ample evidence that the recognition of both voices and faces does indeed take place in special sections of the brain — since certain injuries of the brain leave their victims unable to distinguish voice sounds yet still able to recognize many other kinds of sounds, while other brain injuries destroy the ability to recognize faces but leave other visual functions intact. No one yet knows just how these recognition-systems work, but let's consider each in turn.
ODOR RECOGNITION: It is easy to build recognizers for particular odors because an odor is merely the presence of a certain combination of chemicals in the air, and a specific gene can make a cell sensitive to a particular chemical. So, to build agents for recognizing the odors of particular objects or people requires little more than connecting a variety of evidence-weighing
agents to a variety of specific chemical detectors. VOICE RECOGNITION: To distinguish the sounds of a human voice requires more machinery because vocal expressions are complicated sequences of events. Machines have been built that can make such distinctions. FACE RECOGNITION: No one has yet been able to build vision machines that approach our human ability to distinguish faces from other objects — or even to distinguish dogs from cats. This remains a problem for research.
In their first few days, human infants learn to distinguish people by their odors; then, over the next few weeks, they learn to recognize individuals by sound of voice; only after several months do they start to reliably distinguish the sights of faces. Most likely we learn to make each of these distinctions by several different methods, and it is probably no accident that these abilities develop in a sequence that corresponds to their increasing complexity.
To recognize a voice or face seems hard enough; how does a child learn to recognize another person's mental state — of being angry or affectionate, for example. One way is by distinguishing trajectories. Just as we learn to interpret certain types of changes as representing the motions of objects in the physical realm, we learn to classify other types of changes as signifying mental events; these are what we call gestures and expressions. For example, to identify a certain sound to be a particular language-word, some agencies inside your brain must recognize that a certain sequence of phonetic features has occurred. At the same time, other agencies interpret sequences of vocal sounds as having significance in other realms. In particular, certain types of vocal sounds are recognized as signifying specific emotional qualities. For example, people almost universally agree on which expressions seem most angry or imperative. In general, abruptly changing sounds evoke alarm — perhaps by inducing the sort of narrowing of interest that comes with pain; in any case, sudden changes in volume and pitch demand that we attend to them. In contrast, we react to gentle sounds in ways that people label positive, as with affection, love, or reverence; the smoother time-trajectories do somehow serve to calm us down, thus frequently inducing us to set aside our other interests. It's quite the same for sight and touch; hostile persons tend to jab and shout, while friendly people speak and wave with gestures and trajectories that we perceive as signifying gentleness and tenderness. Indeed, as shown in Manfred Clynes's book, Sentics, Doubleday, New York, 1978, people show similar emotional responses to certain types of time-trajectories regardless of the sensory domain. We consistently identify certain sudden, jerky types of action patterns as indicating anger — regardless of whether these are presented as visual motions, as envelopes of voice sounds, or as pushing, shoving tactile stimuli. In the same way, we consistently identify certain other, smoother action patterns to indicate affection. Clynes concludes that at least half a dozen distinct types of trajectories are universally associated with particular emotional states. What sort of brain-machinery could cause us to react in such similar ways to such different kinds of stimuli? I propose a three-part hypothesis. First, each of our sensory-agencies is equipped with special agents that detect certain types of time-trajectories. Second, the outputs of all the agents that detect similar trajectory types in different agencies are connected, through special connection bundles, to converge upon agents in some central gesture-recognizing agency. Finally, genetically established nerve-bundles run from each gesture-recognizing agent to a particular infantile proto-specialist of the sort described in section 16. 3.
According to this hypothesis, each sensory-agency contains agents that are specialized to react to various types of temporal trajectories. For example, one kind might react only to stimuli that increase slowly and then decrease quickly; another kind might react only to signals that increase quickly and decay slowly. Inside the brain, although the agencies for hearing, sight, and touch lie far apart, the signals from agents that detect similar trajectories converge on a common agency composed of evidence-weighing agents.
Notice that the architecture of this system is so similar to that of our person-recognizing agency that the two systems could form parallel layers; however, the destiny of each central trajectory-type agent is to learn to recognize, not a particular person, but a particular type of gesture or expression. For example, one such agent might learn to react in similar ways to a snarl, grimace, or shaken fist — and thus become an anger-recognizing agent whose function is abstract in the sense of being detached from any particular class of sensations.
To be sure, recognizing anger is not the same as comprehending or sympathizing with anger — nor does merely learning to make such a recognition, by itself, teach us to identify an anger-type trajectory of another person with our own personal experience of being angry. But if our genes equip us with connections from particular central trajectory-type agents to specific proto-specialist agencies, then each particular trajectory-type recognition would tend to activate a specific kind of emotional reaction.
Some of these connections could endow us with certain empathies — for example, to feel elated upon recognizing another person's joyous gestures. Other connections could make us become defensive at signs of aggression — or even aggressive at signs of weakness and withdrawal. There are innumerable examples, in animal behavior, of particular types of gestures evoking instinctive types of reactions, as when a sudden motion toward a bird provokes a fear-reaction flight. Surely our human genes provide us with a great deal of instinctive wiring. However, far more than any other kind of animal, we also have machinery that can bridge new agencies across the older ones, so that we can learn to bury ancient instincts under modern social disciplines.
We've seen how a gene-built agency could predispose us to use trajectory types to represent emotional and other sorts of states of mind. Once this is done, higher-level agencies could use the signals from trajectory-type agents to learn to recognize and represent more complex successions of mental states. In time, those representations could be assembled into models we could use for predicting and controlling our own mental processes. This illustrates how architectures framed by genes could serve our minds as stepping- stones toward learning how to think about ourselves.
As soon as you enter a certain room, you may experience the feeling that you can directly sense its history. Many people attribute such perceptions to imaginary influences with names like intuitions, spirits, atmospheres, and vibrations. Yet very likely all such perceptions come from inside the mind of those observers, as various mental agencies accomplish clever syntheses from clues derived from features and trajectories. In my view, believing in vibrations and ghosts diminishes our capabilities for mental growth by diverting attention from the mind and attributing those abilities to imaginary entities outside ourselves.
What possible sort of brain-machine could support a billion-agent society of mind? The human brain contains so many agencies and connections that it resembles a great nation of cities and towns, linked by vast networks of roads and highways. We are born with brain centers that are specialized for every sense and muscle group: for moving every eye and limb; for distinguishing the sounds of words, the features of faces, and all sorts of touches, tastes and smells. We're born with protospecialists involved with hunger, laughter, fear and anger, sleep, and sexual activity — and surely many other functions no one has discovered yet — each based upon a somewhat different architecture and mode of operation. Thousands of different genes must be involved in laying out these agencies and the nerve-bundles between them — and those brain-growth genes must generate at least three kinds of processes. Those genetic systems first must form the clumps and layers of brain cells that eventually become groups of agents; they must dictate the inner workings of those agencies; and, finally, they must determine the sizes and destinations of the nerve-bundles that interconnect those agencies — in order to constrain who talks to whom within each mind-society.
Now every population will include some variants among the genes that shape those highways in the brain, and this must influence their bearers' potential styles of thought. A person born with unusually sparse connections between the agencies for sight and speech might develop powerful machinery in both those realms but find it hard to make direct connections between them. On the surface, that might seem to constitute a disability. However, it might also lead to an advantage — if it served to force one's higher-level agencies to seek out indirect connections that lead to more articulate ways to represent reality. Similarly, one might suppose there would be advantages in having an uncommonly large capacity for short-term memory. Yet for all we know, our evolution has disfavored that because it tends to lead to less effective use of hard-learned long-term memories. Other differences in how we think could stem from variations in connection paths. An individual whose K-lines had more branches than usual might become inclined to assemble larger-than-usual accumulations in cases where a person whose memory-agents had fewer branches might be more disposed toward building uniframes. But the same genetic disposition can lead to different styles of thought: one person who is genetically disposed toward making uniframes might succumb to the chronic use of superficial stereotypes, while another person similarly endowed might compensate by building more deeply layered agencies that lead to more profound ideas. Although each particular variation will dispose each individual toward certain traits of personality, the final effect of any gene depends upon how it interacts with the structures built by other genes — and upon countless other accidents. This makes it almost meaningless to ask which particular genes lead to good forms of thought. It is better to think of a developing brain as a forest within which many different creatures grow, in conflict and in harmony.
Let's return to the architecture of machines that could hold societies of mind. How complicated this must be depends in part upon how many agents must be active at each moment. We can clarify the problem by considering two extremes. If only a few agents need to work at any time, then even an ordinary, serial, one-step-at-a-time computer could support billions of such agents — because each agent could be represented by a separate computer program. Then the computer itself could be quite simple, provided it has access to enough memory to hold all those little programs. On the other hand, no such arrangement would suffice to simulate societies of mind in which each of billions of agents constantly interact with all the others, all at once, because that would need more wires than any animal could carry in its head. I suspect that the human brain works somewhere in between; we do indeed have billions of nerve cells working at the same time, but relatively few of them have any need to communicate with more than a small proportion of the rest; this is simply because most agents are too specialized to deal with many types of messages. Accordingly, we'll propose an architecture that lies between those serial and parallel extremes — namely, a compromise in which a typical agent has comparatively few direct connections to other agents but can still influence a great many other agents through several indirect steps. For example, we can imagine a society in which each of a billion agents is connected to thirty other agents, selected at random. Then most pairs of agents should be able to communicate through merely half a dozen intermediates! This is because a typical agent can reach thirty others in one step, a thousand others in two steps, and a million others in only four steps. Thus a typical agent could reach any of the other billion agents in only six or seven steps!
However, randomly selected connections would not be very useful, because very few randomly selected pairs of agents would have any messages that might be useful to one another. When we actually examine the human brain, we find that connections between cells are not made either uniformly or randomly. Instead, within any typical small region, we see a great many direct connections between nearby cells but only a relatively small number of bundles of connections to other regions of cells that lie farther away. Here is an idealized representation of this arrangement:
An embryonic brain might assemble such a structure by repeating a sequence of cell divisions and migrations perhaps half a dozen times. If only that were done, the resulting structure would be uselessly repetitive. However, in a real brain's growth, this underlying building plan is modified at every step by many other processes, and this produces many agencies that are similar in general form but different in specific details. Some of these gene-controlled interventions modify the properties of specific layers and clumps of cells, and this determines the internal workings of particular agencies. Other interventions affect the sizes and destinations of the nerve-bundles that interconnect particular pairs of agencies. Such highway-routing processes could be used, for example, to lead the nerves that emerge from the trajectory-type sensors in different agencies to the same central destination. This would be quite easy to arrange because the trajectory agents of similar types would tend to have similar genetic origins — and that would predispose them to be able to smell the same varieties of embryonic message chemicals and thus grow toward the same destination.
The same genetic argument can be applied to other aspects of a child's development — for example, to why all children seem to grow such similar Societies-of-More. When we discussed Jean Piaget's experiments, we left it as a mystery how children form the agencies called History and Appearance. What leads all those different minds to similar conceptions of comparisons? In section 10.7 we hinted that this might happen because similar agents like Tall and Thin originate in related sections of the brain. Consider that despite the fact that we do not know the brain-machinery for agents like Tall and Thin, we can be virtually sure that they are similar internally, because they both respond to the same sorts of spatial differences. Therefore, they almost surely have a common evolutionary origin and are constructed by the same or similar genes. Consequently, the embryonic brain cells that form these agents will tend to have similar senses of smell and are therefore likely to send out nerves that converge upon the same (or similar) agencies. From this point of view, the formation of a Spatial agency on which such properties converge need not be an unlikely chance event, but could be virtually predestined by inheritance.
Papert's principle requires many agencies to grow by inserting new layers of agents into older, already working systems. But this poses a problem because, once brain cells reach maturity, they no longer have much mobility. Consequently, adding new layers to old agencies must involve using brain cells in other locations. As far as we know, the only way this could be done is by using connections already available in the neighborhood of the original agency. Here's one way embryonic cells could provide frameworks for future multilayered mind-societies:
Any agency that is potentially capable of expanding to assimilate a lifetime of experience would need more space than any clump or layer of cells could provide in any compact neighborhood. This must be why the cerebral cortex — the newest and largest portion of the brain — evolved its convoluted form.
If the connections in the cortex of the brain develop this way, through sequences of cell migrations, it could provide each local neighborhood with potential access to several other areas, through fanlike bundles and arrays of nerves. I have the impression the human cortex becomes thus folded upon itself perhaps five or six times, so that agents in each neighborhood have potential access to several other levels of convolution. This makes it possible for a typical agent to become connected to millions of other agents through only a few indirect connections. Presumably, only a small minority of cells ever actually acquire many such connections for their own exclusive use; however, such an arrangement makes any particular group of cells potentially capable of acquiring more significance — for example, by gaining control of a substantial bundle of connections that comes to represent some useful microneme. In its evolutionary course of making available so many potential connections, the human brain has actually gone so far that the major portion of its substance is no longer in its agencies but constitutes the enormous bundles of nerve fibers that potentially connect those agencies. The brain of Homo sapiens is mainly composed of cabling.
Many people seem to think that living things are born endowed with built-in instincts to survive. And certainly all animals do many things to stay alive. They build defenses against threats; they reproduce at any cost; they shy away from extremes of cold or heat, and from unfamiliarity. Now it usually is sensible, when one sees similarities, to seek some common cause for them. But I'll argue that it's usually wrong to seek a common force. There are many different reasons why animals do many things that help keep them alive — and, as we'll see, there is even a reason why there are so many different reasons. But to attribute this to any single, central force or to some basic, underlying survival instinct is as foolish as believing in special powers that attract corpses to cemeteries or broken cars to scrapyards.
No animal requires any central reason to survive, nor does the process of evolution itself require any reason to produce all those survival aids. On the contrary, evolution's versatility stems from its very lack of any fixed direction or constraint that might restrict its possibilities.
To understand why animals survive, one must see evolution as a sieve — that only passes through its mesh those animals who leave more offspring than the rest.
 But hindsight makes us tend to count only the survivors we see, while overlooking all the misfits that have disappeared; it is the same mistake that one might make from looking only at the sky — to then conclude that all the animals were birds. The animals we see today are precisely those whose ancestors accumulated a great many survival aids — and that is why so much of their behavior seems directed toward promoting their welfare — if only in the surroundings in which their ancestors evolved. It is an illusion that all those accumulated mechanisms have anything in common; actually, that seeming uniformity has no coherence of its own: it is nothing but the shadow of that evolutionary sieve. The myth of an underlying survival instinct explains nothing that cannot better be explained without it, and blinds us to the fact that each of those survival aids may exploit an entirely different mechanism.
I certainly don't mean to deny that people learn to love life and to fear death. But this is no simple matter of obeying some elemental instinct. It involves the development over many years of elaborate societies of concepts. Nor do I mean to say that people are born without any instincts at all and must learn everything from experience. On the contrary, we start with many built-in fragments of machinery, and these predestine us to learn to shy away from diverse forms of pain, discomfort, insecurity, and other forms of bodily and mental harm. But compared to those instinctive fears, the state of nonexistence we call death is a far more strange and difficult idea, of which no infant can conceive.
Could animals have evolved as they did, if nature had no sense of goal? A century ago, the world of biologists split in two on one side stood the evolutionists, who held that animals evolve through nothing more than accidents of chance. Their antagonists were called the teleologists ; they disbelieved that such excellent animals could evolve without any purposeful guidance. The evolutionists turned out to be right, for now we can watch small animals and plants evolve before our very eyes and, at a correspondingly slower pace, see similar developments in creatures that have longer lives. In fact, we can actually observe how random accidents to genes lead to the selective survival of particular individuals in various environments — without the faintest reason to suspect that any goals must be involved. So why do so many people feel that evolution must have purposes? I suspect that this belief is based on combining a sound insight about problem solving with an unsound image of how evolution works. For example, common sense tells us that a person might never hit upon a design for a flying machine entirely by trial and error, without having any goals or purposes. This leads one to suppose that nature, too, must be subject to that same constraint. The error comes from thinking of nature as being concerned with such problems as finding a way to make animals fly.
The trouble is that this confuses uses with purposes. For example, suppose one asked how birds evolved, while thoughtlessly assuming that feathers and wings evolved exclusively for use in flight. One would be confronted with a formidable problem, since any organ as complex as a wing would require too many different genes to ever appear by random chance.
So long as one's mind is fixed on flight, one might feel that the only solution is to find some flight advantage in each and every earlier stage that merely produced a protofeather or protowing too small and weak for actual flight. This is why so many antievolutionists demand that evolutionary advocates must fill in every imagined gap along a direct path toward a specified goal. However, once we abandon that fixed idea, it is easier to see how various intermediate developments could have provided those animals with advantages quite unrelated to flying. For example, the early ancestors of birds could have accumulated genes to manufacture various sorts of feathered appendages that helped to wrap those protobirds in body cloaks that kept them warm. This sort of fortuitous preparation unrelated to any goal of flight would have made it much more likely that other accidents, perhaps millions of years later, might have brought a few such elements together to lend some genuine aerial advantage to an animal already prone to making leaps.
Incidentally, I do not mean to say that evolutionary processes must by their nature be devoid of purposes. We can actually conceive of how machinery could exist inside an animal, to purposefully direct some aspects of its evolution in much the way a farmer can promote the evolution of chickens that bear more meat or sheep that grow more wool. Indeed, the reproductive machinery inside our cells has already evolved so as to produce variations that are more likely to be useful than would otherwise occur by purely random chance; this idea is explained in a brilliant essay by Douglas Lenat, entitled The role of Heuristics in learning by Discovery, in Machine Learning: An Artificial Intelligence Approach, edited by R. Z. Michalski, J. J. Carbonell, and T. M. Mitchell; Tioga Publishing Co., Palo Alto, Calif., 1983. It is even conceivable that our genetic systems might even contain some forms of difference-engine-like machinery that, over very long periods of time, generate variations in a somewhat purposeful manner. To be sure, this is mere speculation, since no such system has yet been discovered.
In any case, one aftermath of the controversy with teleologists was that many scientists in other realms became so afraid of making similar mistakes that the very concept of purpose became taboo throughout science. Even today, most scientists regard it as an abomination to use anthropomorphic or intentional language in connection with anything but persons or higher animals. This burdened the science of psychology with a double-barreled handicap. On one side, it made psychologists regard many of their most important problems as outside the scope of scientific explanation. On the other side, it deprived them of many useful technical ideas — because such concept-words as want, expect, and recognize are among the most effective ever found for describing what happens in human minds. It was not until the cybernetic revolution of the 1940s that scientists finally realized there is nothing inherently unscientific about the concept of goal itself and that attributing goals to evolution was bad not because it was impossible, but simply because it was wrong. Human minds do indeed use goal-machinery, and there is nothing wrong with recognizing this and bringing technical theories about intentions and goals into psychology.
The hardest thing to understand is why we can understand anything at all. —Albert Einstein
What hope is there for any human mind to understand a human brain? No one could ever memorize the whole of all its small details. Our only hope is in formulating their principles. It wouldn't be much use, in any case, to know how each separate part works and how it interacts with the rest — because that simply isn't practical. Even if you knew all those details, if someone asked you to describe — in general terms — how brains work and how they change, you would have no way to reply.
We usually like to think in positive terms about how various parts of systems interact. But to do that, we must first have good ideas about which aspects of a system do not interact — since otherwise there would be too many possibilities to consider. In other words, we have to understand insulations before we can comprehend interactions. To put this in a stronger form: No complicated society would actually work if it really depended on interactions among most of its parts. This is because any such system would be disabled by virtually any distortion, injury, or environmental fluctuation. Nor could any such society evolve in the first place.
The science of biology was itself shaped by the discovery of insulations. Plants and animals were scarcely understood at all until it was found that they were made of separate cells. Then little more was learned so long as scientists thought of cells as bags of fluid within which countless chemicals could freely interact. Today we know that cells are more like factories, containing systems that are kept apart by sturdy walls, with doors that open only to those substances that bear the proper keys. Furthermore, even within these compartments, most pairs of chemicals cannot interact except by permission of particular genes. Without those insulations, so many chemicals would interact that all our cells would die.
For the purposes of this book, I have emphasized highly insulated systems — that is, mechanisms in which different functions are embodied in different agents. However, it is important to put this in perspective. For example, in chapter 19, we drew a sharp distinction between memorizers and recognizers; this made it easy to explain those ideas. However, in section 20.9 we mentioned very briefly the idea of a distributed memory, in which both those functions are combined in the same network of agents. Now I do not want the reader to take the brevity of that discussion to suggest the subject is not important. On the contrary, I suspect that most of the human brain is actually composed of distributed learning-systems and that it is extremely important for us to understand how they can work. It is possible to combine even more functions; for example, John Hopfield has demonstrated a single distributed network that not only combines memory and recognition, but also correctly yields an entire memory from any subpart of sufficient size — in other words, an agency that closes the ring, much as described in section 19.10. See Hopfield's article in the Proceedings of the National Academy of Science, 79, p. 2554, 1982, or the book Parallel Distributed Processing by D. E. Rumelhart and J. L. McLelland, M.I.T. Press, 1986.
The advantages of distributed systems are not alternatives to the advantages of insulated systems; the two are complementary. To say that the brain may be composed of distributed systems is not the same as saying that it is a distributed system — that is, a single network in which all functions are uniformly distributed. I do not believe any brain of that sort could work, because the interactions would be uncontrollable. To be sure, we have to explain how different ideas can become connected to one another — but we must also explain what keeps our separate memories intact. For example, we have praised the power of metaphors that allow us to combine ideas from different realms — but all that power would be lost if all our metaphors got mixed! Similarly, the architecture of a mind-society must encourage the formation and maintenance of distinct levels of management by preventing the formation of connections between agencies whose messages have no mutual significance. Some theorists have assumed that distributed systems are inherently both robust and versatile, but actually those attributes are likely to conflict. Systems with too many interactions of different types will tend to be fragile, while systems with too many interactions of similar types will be too redundant to adapt to novel situations and requirements. Finally, distributed systems tend to lack explicit, articulated representations, and this makes it difficult for any such agency to discover how any other such agency works. Thus, if distributed memory-systems are widely used within our brains, as I suspect they are, that could be yet another reason for the shallowness of human consciousness.
What are the origins of human thought? Today, we're almost sure that our closest living relatives branched out according to the diagram below. It shows that none of the species that still exist are directly descended from any of the others, but that they all share common ancestors, now long extinct.
How different are we human beings from all the other animals? We recognize how similar those various brains and bodies are. But in view of our exceptional abilities to speak and think, we certainly seem to be unique. Could chimpanzees or gorillas ever learn to speak the way we do? Experience has shown that these wonderful animals can indeed learn to make connections among hundreds of different words and ideas, enabling them to produce speechlike strings of symbol- signs for expressing Trans-actions such as Put the candy into the box. However, the same experiments appear to show that these animals find it much more difficult to construct language-strings in which the terminals of certain frames are filled with other filled-in frames. In other words, no one has succeeded in teaching these animals to use expressions that involve interruption clauses, such as Put the candy that is in the pail into the box. To be sure, our inability to teach such things does not prove that these animals are inherently incapable of them. Still, no one can doubt that we have capabilities our ancestors did not possess. What sorts of brain developments could have given rise to our new and mighty forms of thought? Here are some possible candidates:
The capacity to attach new K-lines to old ones enabled us to build hierarchical memory-trees. The availability of more versatile temporary memories enabled us to pursue subgoals and to tolerate more complicated kinds of interruptions. The evolution of paranomes — that is, of isonomes that bridge across multiple realms — enabled us to examine the same problem from several viewpoints.
The emergence of additional layers of agents allowed each child to grow through more stages of development.
None of those advances by itself would seem to pose any special evolutionary difficulty. But what could have caused so many changes to have appeared so rapidly? Our ancestors diverged from their relatives, the gorillas and the chimpanzees, only a few million years ago, and our human brains have grown substantially in only the last few hundred thousand years. Little is known of what happened in that interval because we have found very few fossil remains of our ancestors. (This could be partly because their population was never very large but could also be because they had become too smart to permit themselves to be fossilized.) The evolutionary interval was so brief that most of our genes and brain structures remain nearly the same as those of the chimpanzees. Was it merely an increase in the brain's size and capacity that produced our new abilities? Consider that, by itself, an increase in the size of the brain might only cause the disadvantage of mental confusion and the inconvenience of a heavier head. However, if we first evolved significant advances in the ability to manage our memories, we could then take advantage of more memory. Similarly, inserting new layers of agents into old agencies might only lead to bad results — unless this were preceded by mechanisms for using such layers as middle- level managers without disrupting older functions. In other words, our evolution must have worked the other way: first came enhancements in abilities that made it feasible for us to manage larger agencies. Then, once we had the capability for using more machinery, natural selection could favor those who grew more massive brains.
Never speak more clearly than you think. —Jeremy Bernstein
This book assumes that any brain, machine, or other thing that has a mind must be composed of smaller things that cannot think at all. The structure of the book itself reflects this view: each page explores a theory or idea that exploits what other pages do. Some readers might prefer a more usual form of story plot. I tried to do that several times, but it never seemed to work; each way I tried to line things up left too many thoughts that would not fit. A mind is too complex to fit the mold of narratives that start out here and end up there; a human intellect depends upon the connections in a tangled web — which simply wouldn't work at all if it were neatly straightened out.
Many psychologists dream of describing minds so economically that psychology would become as simple and precise as physics. But one must not confuse reality with dreams. It was not the ambitions of the physicists that made it possible to describe so much of the world in terms of so few and simple principles; that was because of the nature of our universe. But the operations of our minds do not depend on similarly few and simple laws, because our brains have accumulated many different mechanisms over aeons of evolution. This means that psychology can never be as simple as physics, and any simple theory of mind would be bound to miss most of the big picture. The science of psychology will be handicapped until we develop an overview with room for a great many smaller theories.
To assemble the overview suggested in this book, I had to make literally hundreds of assumptions. Some scientists might object to this on the ground that successful sciences like physics and chemistry have found it more productive to develop theories that make the fewest assumptions, eliminating everything that does not seem absolutely essential. But until we have a more coherent framework for psychology, it will remain too early for the task of weeding out unproved hypotheses or for trying to show that one theory is better than another — since none of our present-day theories seem likely to survive very long in any case. Before we can have an image of the forest of psychology, we'll have to imagine more of its trees and restrain ourselves from simplifying them to death. Instead, we have to make ourselves complicated enough to deal with what is actually there.
It is scarcely a century since people started to think effectively about the natures of the brainmachines that manufacture thoughts. Before that, those who tried to speculate about this were handicapped on one side by their failure to do experiments, particularly with young children, and on the other side by their lack of concepts for describing complicated machinery. Now, for the first time, mankind has accumulated enough conceptual tools to begin comprehending machines with thousands of parts. However, we are only beginning to deal with machines that have millions of parts and we have barely started to acquire the concepts that we'll need to understand the billion-part machines that constitute our brains. New kinds of problems always arise when one encounters systems built on larger, less familiar scales.
Since most of the statements in this book are speculations, it would have been too tedious to mention this on every page. Instead, I did the opposite — by taking out all words like possibly and deleting every reference to scientific evidence. Accordingly, this book should be read less as a text of scientific scholarship and more as an adventure story for the imagination. Each idea should be seen not as a firm hypothesis about the mind, but as another implement to keep inside one's toolbox for making theories of the mind. Indeed, there is a sense in which that can be the only realistic way to think about psychology — since every particular person's mind develops as a huge machine that grows in a somewhat different way. Are minds machines? Of that, I've raised no doubt at all but have only asked, what kind of machines? And though most people still consider it degrading to be regarded as machines, I hope this book will make them entertain, instead, the thought of how wonderful it is to be machines with such marvelous powers.
Scientists like to credit those who first discovered each idea. But the central concept of this book, that the mind is a society of many smaller mechanisms, involved so many years of work to bring it to its present form that I can mention only a few of the people who had the most influence on it. In this research I shared the greatest privilege a human mind can have: to work on new ideas together with the foremost intellects of one's time. As a student at Harvard, I immersed myself in mathematics and psychology and attached myself to two great young scientists, the mathematician Andrew Gleason and the psychologist George A. Miller. This was the era of the scientific movement that was later called cybernetics, and I was especially entranced with the works of Nicholas Rashevsky and of Warren McCulloch, who were making the first theories of how assemblies of simple cell-machines could do such things as recognize objects and remember what they'd seen. By the time I started graduate school in mathematics at Princeton in 1950, I had a clear enough idea about how to make a multi-agent learning machine. George Miller obtained funds for building it; this was the Snarc machine of chapter 7. Constructed with the help of a fellow student, Dean Edmonds, it managed to learn in certain ways, but its limitations convinced me that a more versatile thinking machine would have to exploit many other principles.
My teachers in the golden age of mathematics at Princeton were not particularly interested in psychology, but the ways of thought are more important than the subject matter, and I learned new mental strategies from Albert Tucker, Ralph Fox, Solomon Lefshetz, John Tukey, Salomon Bochner, and John von Neumann. I learned even more from my own generation of students at Princeton: particularly from John Nash, Lloyd Shapley, Martin Shubik, and John McCarthy. In 1954 I returned to Harvard as a Junior Fellow of the Harvard Society of Fellows, with no obligation but to pursue whatever goal seemed most important. There seemed no way to get around the apparent limitations of low-level, distributed-connection learning machines, so I turned toward a new theory being pioneered by Ray Solomonoff, about generalizing from experience. I attached myself to Warren McCulloch and Oliver Selfridge, with whom I worked most closely of all until becoming a professor of mathematics at MIT. It was from them that I derived my image of how to make a laboratory work.
In 1959, John McCarthy came to MIT from Dartmouth, and we started the MIT Artificial Intelligence Project. We agreed that the most critical problem was of how minds do common-sense reasoning. McCarthy was more concerned with establishing logical and mathematical foundations for reasoning, while I was more involved with theories of how we actually reason using pattern recognition and analogy. This combination of theoretical and practical research attracted students of great ability, and our laboratory had an atmosphere that combined mathematical power with engineering adventure; this led not only to new theories of computation, but also to developing some of the very first automatic robots. In 1963, McCarthy left to start a new AI laboratory at Stanford, and now there were three principal centers of research in Artificial Intelligence, including the one that Allen Newell and Herbert Simon had started earlier at Carnegie-Mellon University. A fourth center soon emerged at Stanford Research Laboratory, and we all worked closely together.
The money to support the people and equipment for this work came mainly from an office of the Advanced Research Projects Agency concerned with information processing technology. This office was directed, in effect, by the scientists themselves, initially by Dr. J.C.R.
Licklider, who had been my teacher and friend when I was a student at Harvard. Licklider had already organized a research center at the Bolt, Beranek, and Newman company in Cambridge, Massachusetts, and McCarthy and I and several of our students had worked closely with that group for several years. Later, when Licklider returned to become a professor at MIT, the Information Processing Technology Office was taken over successively by Lawrence G. Roberts and Ivan Sutherland (who had been students of ours at MIT) and then by Robert Taylor and Robert Kahn — all of whom made important intellectual contributions. The actual details of all these research contracts were managed in the Office of Naval Research by Marvin Denicoff, whose vision of the future had a substantial influence on the entire field. My own research was supported by the ONR over an even longer period, since it had previously financed my graduate studies in topology at Princeton, and, subsequently, Denicoff's successor, Alan Meyrowitz, supported my research during the completion of this book.
Jerome Wiesner and Philip Morse of MIT obtained the resources for our first laboratory. Our development at MIT was encouraged by William Ted Martin, Norman Levinson, Witold Hurewicz, Norbert Weiner, Claude Shannon, Peter Elias, and Robert Fano. I was given the privilege of sharing with Shannon the endowed chair of Donner Professor of Science at MIT and enjoyed the support of many other people and organizations over the years: John Williams, Paul Armer, and Merril Flood enabled me to work with Newell, Shaw, and Simon at the Rand Corporation; Oliver Selfridge and Gerald Dinneen encouraged research at MIT's Lincoln Laboratory; Michel Gouilloud supported my work from the Schlumberger Corporation; Edward David provided support from Exxon; and Alan Kay supported many of our students with funding from (successively) the Xerox, Atari, and Apple corporations. For several years, the Thinking Machines Corporation has supported both this research and the development of a new type of computer called the Connection Machine — designed by my student Danny Hillis for embodying societies of mind.
Most of all, I want to acknowledge the contributions to this book of Seymour Papert, who came to MIT in 1963 after five years of studying child development with Jean Piaget in Geneva. Papert and I worked so well together that for a decade we supervised the laboratory jointly, each able at any time to leave the other to decide what should be done. Together we evolved new mathematical techniques, designed laboratory experiments, built computer hardware and software, and supervised the same students. Such a partnership could not have worked so well had we not both developed in similar intellectual directions before we met; we were both involved with the same areas of mathematics, with similar concerns about machinery, and with similar attitudes about psychology. One of our projects was to build a machine that could see well enough to use mechanical hands for solving real-world problems; this was the origin of Builder and the insights that emerged from it. In trying to make that robot see, we found that no single method ever worked well by itself. For example, the robot could rarely discern an object's shape by using vision alone; it also had to exploit other types of knowledge about which kinds of objects were likely to be seen. This experience impressed on us the idea that only a society of different kinds of processes could possibly suffice. Papert and I worked together not only on robotic machines, but in many other areas; for example, we spent several years developing a new mathematical theory for the then mysterious Perceptron type of learning machine. In the middle 1970s Papert and I tried together to write a book about societies of mind but abandoned the attempt when it became clear that the ideas were not mature enough. The results of that collaboration shaped many earlier sections of this book.
Eventually Papert and I both turned away from large-scale scientific enterprises toward somewhat different individual goals, and we imposed the directorship of our laboratory upon one of our most original and productive students, Patrick Winston — who first worked out the idea of making uniframes. Papert went on to develop a host of new theories about mental development and education; these led to the computer language LOGO and to many other concepts that started to enter the mainstream of educational thought over the next decade. I focused my concern on searching for better theories about the little world of how a child might learn to build with blocks. The parts of the puzzle that form this book began to fit together in my mind in the mid-1970s, around the concept of frame-array, and this eventually led to the theories about communication-lines, K-lines, and level-bands, and then, during the book's final stages, to the ideas about pronomes, polynemes, and cross-realm correspondences.
As for the manuscript itself, Bradley Marx read through every draft, comparing each version with earlier ones, helping to maintain clarity, stylistic coherency, and especially protecting good ideas from destructive revisionary impulses. This was hard because the early manuscript was more than twice its present length. Robin Lakoff suggested neutering the English; this seemed at first impossible but soon became quite natural. Theodore Sturgeon reviewed an early draft; I wish he had lived to see it now. Kenneth Haase, Betty Dexter, and Tom Beckman made innumerable suggestions and corrections. Successive drafts were reviewed by Danny Hillis, Steve Bagley, Marvin Denicoff, Charlotte Minsky, Michel Gouilloud, Justin Lieber, Philip Agre, David Wallace, Ben Kuipers, Peter de Jong, and Sona Vogel. Richard Feynman contributed a variety of insights about memory and parallel processing. David Yarmush helped to organize the book into sections, to smooth out the transitions, and to establish the gradient wherein the words begin with commonsense meanings and gradually become more technical. Bob Whittinghill made many suggestions about language as well as about psychology. Douglas Hofstadter evaluated the entire theory, forcing me to make several substantial changes. Michael Crichton made many technical suggestions and helped me to refine the early chapters.