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The “Critic-Selector” Model of Mind

In the rest of this book we will frequently switch between these two different views of the mind—because each one gives better answers to different kinds of questions about ourselves. Model Six makes better distinctions between various levels of mental behaviors, whereas the Critic-Selector view suggests better ideas about how to deal with difficult problems. Chapter §7 will combine both views, because we frequently use different Selectors and Critics at each of those various cognitive levels.

However, no matter how such a system is built, it will never seem very resourceful until it knows a great deal about the world it is in. In particular, it must be able to foresee some of the outcomes of possible actions, and it won’t be able to do this unless until it possesses the right kinds of knowledge. For human beings, that’s what we mean by “commonsense” knowledge and reasoning. And although, in everyday that phrase means, ‘the things that most people find obvious,’ the following chapter will demonstrate that this subject is surprisingly complex.

Part VI. Common sense

“The way to make money is to buy stock at a low price, then when the price goes up, sell it. If the price doesn’t go up, don’t buy it.”

—Will Rogers.

Soon after the first computers appeared, their actions became the subjects of jokes. The tiniest errors in programming them could wipe out their clients’ bank accounts, credit them with outlandish amounts, or trap the computers in circular loops that kept repeating the same mistakes. This maddening lack of common sense led most observers to suspect that machines could never have genuine minds.

Today many programs do outstanding jobs more efficiently and reliably. Some of them can beat people at chess. Others can diagnose heart attacks. Yet others can recognize pictures of faces, assemble cars in factories, or even pilot planes or ships. But no machine yet can read a book, clean a house, or baby-sit.

Then why cannot our computers yet do so many things that people can do? Do they need more memory, speed, or complexity? Do they use the wrong kinds of instruction-sets? Do their limitations come from the fact that they only use zeros and ones? Or do machines lack some magical attribute that only a human brain can possess? This chapter will try to show, instead, that we don’t need to look for excuses like these, because most deficiencies of today’s machines stem from the limited ways we’ve been programming them.

One of these limitations is that we usually give a present-day program only the knowledge we think it will need to solve each particular problem. In contrast, every normal child learns millions of fragments of knowledge and skills that people regard as ‘obvious.’ For example, if you heard that someone tied a package with ‘string’ you might connect that word with ideas like these:

You can use a string to pull, but not push.

But you cannot push a thing with a string.

Loose strings tend to get tangled up.

Fill your package before you tie it up.

A string will break when pulled too tight.

The first parts of this chapter will discuss the need for very large bodies of commonsense knowledge, as well as the kinds of skills we need for retrieving and applying such knowledge.

The middle parts of this chapter explore another cause for the weakness of present-day programs: they specify what the computer should do—without telling it which goals to achieve, or the intentions of those who programmed it. This means that they have no ways to reflect on whether those goals were achieved at all—or, if they were, at what cost and how well. Furthermore, those computers will still lack resourcefulness, even with access to great stores of knowledge because few fragments of knowledge are of use by themselves, unless they are also connected to reasons or goals for using them.

If you break something, you should replace it. (Because its owner wants it intact.)

People usually go indoors when it rains. (Because they do not like to get wet.)

It is hard to stay awake when you’re bored. (Why would one want to stay awake?)

People don’t like to be interrupted. (Because they want you to hear what they say.)

It is hard to hear in a noisy place. (You might want to hear what others say.)

No one else can tell what you’re thinking. (Why might you value that privacy?)

Another deficiency is that a typical program will simply give up when it lacks some knowledge it needs—whereas a person can find other ways to proceed. So the final parts of this chapter discuss some of the tactics that people can use when we don’t already know just what to do— for example, by making useful analogies.

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§6-1. What do we mean by Common Sense?

“Common sense is the collection of prejudices acquired by age eighteen.”

—Albert Einstein

Instead of blaming machines for their deficiencies, we should try to endow them with more of the knowledge that most people have. This should include not only what we call “commonsense knowledge”—the kinds of facts and theories that most of us know— but also the commonsense kinds of reasoning skills that we accumulate for applying that knowledge.

Student: Can you more precisely define what you mean by ‘commonsense knowledge’?

We each use terms like ‘common sense’ for the things that we expect other people to know and regard as obvious. So it has different meanings for each of us.

Sociologist: What people regard as obvious depends on their communities. Each person lives in several of these—such as family, neighborhood, language, clan, nation, religion, school, and profession—and each of these ‘clubs’ shares different collections of knowledge, beliefs and ways to think.

Child Psychologist: Still, even if you know only a child’s age, you can say much about what that child is likely to know. Researchers like Jean Piaget have studied children all over the world and found that their minds grow in similar ways.

Citizen: We sometimes say people lack ‘common sense’ when they do things that seem foolish to us—not because they are lacking in knowledge, but that they’re not using it properly.

We are constantly learning, not only new facts, but also new kinds of ways to think. We learn some from our private experience, some from the teaching of parents and friends, and some from other people we meet. All this makes it hard to distinguish between what each person happens to know and what others regard as obvious. So, what each person knows (and their ways to apply it) may differ so much that we can’t always predict how others will think.