The Emotion Machine

using different descriptions of the same pictures. Thus, because it has multiple “ways to look at things,” the program usually finds a way to find a good solution. The program performed on this kind of test as well as a typical fifteen-year old. To be sure, it could work only this kind of problem, and had no way to learn from experience, but still, knowing ways to use analogies is a vital part of how people think.

Of course, whenever we need to make a choice, the differences that will concern us most will depend on what we now want to achieve. If Carol wants merely to build an arch, then all of these forms may seem adequate—but if she plans to build more on its top, then the one on the right will seem less suitable.

Although these particular “geometric analogy” problems are not so common in everyday life, Evan’s program shows the value of being able to change and adapt its descriptions until it finds a way to describe different things so that they seem more similar. This is an important step toward the ability to use knowledge about one kind of thing to understand some other different kind of thing—so finding new ways to look at things this must be among our most important commonsense processes.

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§6-7. Knowledge needs Multiple Representations

What distinguishes people from animals? Perhaps our largest distinction is that none of the others can ask such a question! We’re unique in being able to treat our own ideas as though they were things. In other words, we ‘conceptualize.’

However, to think about ideas or things, we need representations of them in our minds. Everyone who has written a program knows that you can’t get a computer to do what you want by simply ‘pouring knowledge in.’ You must represent each process or fact in the form of some sort of structure. For knowledge is not composed of ‘things’ that each can exist apart from the rest—no more than a word can have a meaning without being part of some larger-scale language; fragments of knowledge can only make sense when they have appropriate kinds of interconnections. It does not much matter how these are embodied; you can make the same computer with wires and switches, or even with pulleys, blocks, and strings; all that matters is how each part changes its state in response to what some other parts do. And the same kinds of relationships can also be represented in terms of parts that have no behavior at all—such as arrangements of symbols in diagrams, or the sentences of written texts—so long as there is some way these to affect how some other systems will behave.

So when programmers set out to develop a program, they usually start by selecting a way to represent the knowledge their program will need. But each representation works well only in certain realms, and none works well in every domain. Yet we frequently hear discussions like this about what is the best way to represent knowledge:

Mathematician: It is always best to express things with Logic.

Connectionist: No, Logic is far too inflexible to represent commonsense knowledge. Instead, you ought to use Neural Networks.

Linguist: No, because Neural Nets are even more rigid. They represent things in numerical ways that are hard to convert to useful abstractions. Instead, why not simply use everyday language—with its unrivaled expressiveness.

Conceptualist: No, language is much too ambiguous. You should use Semantic Networks instead—where ideas get connected by definite concepts!

Statistician: Those linkages are too definite, and don’t express the uncertainties we face, so you need to use probabilities.

Mathematician: All such informal schemes are so unconstrained that they can be self- contradictory. Only Logic can ensure us against those circular inconsistencies.”

This shows that it makes no sense to seek a single best way to represent knowledge—because each particular form of expression also brings its own particular limitations. For example, logic-based systems are very precise, but they make it hard to do reasoning with analogies. Similarly, statistical systems are useful for making predictions, but do not serve well to represent the reasons why those predictions are sometimes correct. It was recognized even in ancient times that we must represent things in multiple ways:

Aristotle: “Thus the essence of a house is assigned in such a formula as ‘a shelter against destruction by wind, rain, and heat’; the physicist would describe it as ‘stones, bricks, and timbers’; but there is a third possible description which would say that it was that form in that material with that purpose or end. Which, then, among these is entitled to be regarded as the genuine physicist? The one who confines himself to the material, or the one who restricts himself to the formulable essence alone? Is it not rather the one who combines both in a single formula?”[129]

However, sometimes there are advantages to not combining those ways to describe things.

Richard Feynman: “...psychologically we must keep all the theories in our heads, and every theoretical physicist who is any good knows six or seven different theoretical representations for exactly the same physics. He knows that they are all equivalent, and that nobody is ever going to be able to decide which one is right at that level, but he keeps them in his head, hoping that they will give him different ideas for guessing.”[130]

Much of our human resourcefulness comes from being able to choose among diverse ways to represent the same situation. This has value because each such point of view may provide a way to get around some deficiencies of the other ones. However, to exploit this fact, one needs to develop good ways to decide when to use each kind of representation; we’ll come back to this in §10-X. {Causal Diversity.} Of course, to change representations efficiently, one must also be able to quickly switch without losing the work that’s already been done—and that is why this chapter emphasized the iuse of panalogies to link analogous aspects of multiple ways to represent and to think about things.

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QUESTIONS

Part VII. Thinking

“I am aware of a constant play of furtherances and hindrances in my thinking, of checks and releases, tendencies which run with desire, and tendencies which run the other way … welcoming or opposing, appropriating or disowning, striving with or against, saying yes or no.”

—William James, [Principles of Psychology]

Which characteristics help us to surpass all the rest of our animal relatives? Surely our most outstanding