Computing Methodologies -- Artificial Intelligence.

It seems to me that the ingredients of most theories both in Artificial Intelligence and in Psychology have been on the whole too minute, local, and unstructured to account–either practically or phenomenologically–for the effectiveness of common-sense thought. The "chunks" of reasoning, language, memory, and "perception" ought to be larger and more structured; their factual and procedural contents must be more intimately connected in order to explain the apparent power and speed of mental activities.

Received by the IRE, October 24, 1960. The author's work summarized here—which was done at the MIT Lincoln Laboratory, a center for research operated by MIT at Lexington, Mass., with the joint Support of the U. S. Army, Navy, and Air Force under Air Force Contract AF 19-5200; and at the Res. Lab. of Electronics, MIT, Cambridge, Mass., which is supported in part by the U. S. Army Signal Corps, the Air Force Office of Scientific Research, and the ONR—is based (...) on earlier work done by the author as a Junior Fellow of the Society of Fellows, Harvard University. (shrink)

A leading contributor to artificial intelligence offers insight into the numerous ways in which the mind works to demonstrate how emotions and feelings are just ...

You don a comfortable jacket lined with sensors and muscle-like motors. Each motion of your arm, hand, and fingers is reproduced at another place by mobile, mechanical hands. Light, dexterous, and strong, these hands have their own sensors through which you see and feel what is happening. Using this instrument, you can "work" in another room, in another city, in another country, or on another planet. Your remote presence possesses the strength of a giant or the delicacy of a surgeon. (...) Heat or pain is translated into informative but tolerable sensation. Your dangerous job becomes safe and pleasant. (shrink)

Most theories of memory suggest that when we learn or memorize something, some drepresentation of that something is constructed, stored and later retrieved. This raises questions like:How is information represented?How is it stored?How is it retrieved?Then, how is it used?This paper tries to deal with all these at once. When you get an idea and want to “remember” it, you create a “K‐line” for it. When later activated, the K‐line induces a partial mental state resembling the one that created it. (...) A “partial mental state” is a subset of those mental agencies operating at one moment. This view leads to many ideas about the development, structure and physiology of memory, and about how to implement framelike representations in a distributed processor. (shrink)

This chapter attempts to explain why people become confused by questions about the relation between mental and physical events. When a question leads to confused, inconsistent answers, this may be because the question is ultimately meaningless or at least unanswerable, but it may also be because an adequate answer requires a powerful analytical apparatus. It is the author's view that many important questions about the relation between mind and brain are of that second kind, and that some of the necessary (...) technical and conceptual tools are becoming available as a result of work on the problems of making computer programs behave intelligently. We shall suggest a theory to explain why introspection does not give clear answers to these questions. Technical solutions to the questions will not be attempted, but there is probably some value in finding at least a clear explanation of why we are confused. (shrink)

Everyone wants wisdom and wealth. Nevertheless, our health often gives out before we achieve them. To lengthen our lives, and improve our minds, in the future we will need to change our our bodies and brains. To that end, we first must consider how normal Darwinian evolution brought us to where we are. Then we must imagine ways in which future replacements for worn body parts might solve most problems of failing health. We must then invent strategies to augment our (...) brains and gain greater wisdom. Eventually we will entirely replace our brains -- using nanotechnology. Once delivered from the limitations of biology, we will be able to decide the length of our lives--with the option of immortality-- and choose among other, unimagined capabilities as well. (shrink)

This is a revised version of AI Memo No. 616, MIT Artificial Intelligence Laboratory. An earlier published version appeared in Music, Mind, and Brain: The Neuropsychology of Music (Manfred Clynes, ed.) Plenum, New York, 1981 Why Do We Like Music? Why do we like music? Our culture immerses us in it for hours each day, and everyone knows how it touches our emotions, but few think of how music touches other kinds of thought. It is astonishing how little curiosity we (...) have about so pervasive an "environmental" influence. What might we discover if we were to study musical thinking? (shrink)

An excessive preoccupation with formalism is impeding the development of computer science. Form- content confusion is discussed relative to three areas: theory of computation, programming languages, and education.

We tend to think of knowledge in positive terms -- and of experts as people who know what to do. But a 'negative' way to seem competent is, simply, never to make mistakes. How much of what we learn to do -- and learn to think -- is of this other variety? It is hard to tell, experimentally, because knowledge about what not to do never appears in behavior. And it is also difficult to assess, psychologically, because many of the (...) judgments that we traditionally regard as positive -- such as beauty, humor, pleasure, and decisiveness -- may actually reflect the workings of unconscious double negatives. (shrink)

I hope this book will be useful to everyone who seeks ideas about how human minds work, or wants suggestions about better ways to think, or who aims toward building smarter machines. It should be useful to readers who want to learn about the field of Artificial Intelligence. It should also be of interest to psychologists, neurologists, computer scientists, and philosophers because it develops many new ideas about the subjects those specialists struggle with.

People often complain that AI is not developing as well as expected. They say, "Progress was quick in the early years of AI, but now it is not growing so fast." I find this funny, because people have been saying the same thing as long as I can remember. In fact we are still rapidly developing new useful systems for recognizing patterns and for supervising processes. Furthermore, modern hardware is so fast and reliable that we can employ almost any programs (...) we can create. Good new systems appear every year, for different "expert" applications. (shrink)

Some computer programs are expert at some games. Other programs can recognize some words. Yet other programs are highly competent at solving certain technical problems. However, each of those programs is specialized, and no existing program today shows the common sense or resourcefulness of a typical two-year-old child—and certainly, no program can yet understand a typical sentence from a child’s first-grade storybook. Nor can any program today can look around a room and then identify the things that meet its eyes.

Most people think computers will never be able to think. That is, really think. Not now or ever. To be sure, most people also agree that computers can do many things that a person would have to be thinking to do. Then how could a machine seem to think but not actually think? Well, setting aside the question of what thinking actually is, I think that most of us would answer that by saying that in these cases, what the computer (...) is doing is merely a superficial imitation of human intelligence. It has been designed to obey certain simple commands, and then it has been provided with programs composed of those commands. Because of this, the computer has to obey those commands, but without any idea of what's happening. (shrink)

I usually shock people by telling them about all sorts of possible wonders of the future, but it is probably impossible to shock an Extropian. If I am talking to a general audience I usually explain to them that if it weren't for their bad habits and superstitions they could live forever.

In this issue, we carry an article which we invited Prof. Marvin Minsky to write about his invention of the confocal scanning microscope. This is not a question of recognizing priority for a scientific insight or discovery. It is much more a question of raising the problem of how it can be possible that such an immensely important idea can go unrecognized for such a very long period. It may possibly be the case that after more research we (...) find that yet another person discovered the same idea. That does not matter. The fact is that Minsky invented such a microscope identical with the concept later developed extensively by Egger and Davidovits at Yale and by Shepherd and Wilson in Oxford and Brakenhoff and colleagues in Amsterdam etc. The circumstances are also remarkable in that Minsky only published his invention as a patent. Yet he not only built a microscope and made it work and it was the kind of prototype of which we would be proud but he showed it to a number of people who went away impressed but nevertheless failed to adopt the concept. (shrink)

People often complain that AI is not developing as well as expected. They say, "Progress was quick in the early years of AI, but now it is not growing so fast." I find this funny, because people have been saying the same thing as long as I can remember. In fact we are still rapidly developing new useful systems for recognizing patterns and for supervising processes. Furthermore, modern hardware is so fast and reliable that we can employ almost any programs (...) we can create. Good new systems appear every year, for different "expert" applications. (shrink)

Two interstellar aliens have come to assess the life-forms of Earth. The human life-forms will be entitled to rights--if the aliens can conclude that they think. Most such decisions are easy to make-- -- but this case is unusual.

tion of Ordinary DIfferential Equations Routine) solves first order, first degree ordinary differential equations at the level of a good college sophomore and at an average of about five seconds per problem attempted. The differences in philosophy and operation between SAINT and SIN are described, and suggestions for extending the work presented are made.

§3-1. Being in Pain................................................................................................ .............................................. 1 §3-2. Why does Persistent Pain lead to Suffering?.......................................................................................... .... 2 §3-3. The Machinery of Suffering........................................................................................... ............................ 4..

“Great pain urges all animals, and has urged them during endless generations, to make the most violent and diversified efforts to escape from the cause of suffering. Even when a limb or other separate part of the body is hurt, we often see a tendency to shake it, as if to shake off the cause, though this may obviously be impossible.” —Charles Darwin[1].

Engineering and scientific education conditions us to expect everything, including intelligence, to have a simple, compact explanation. Accordingly, when people new to AI ask "What's AI all about," they seem to expect an answer that defines AI in terms of a few basic mathematical laws.

When first we meet those aliens in outer space, will we and they be able to converse? I'll try to show that, yes, we will–provided they are motivated to cooperate–because we'll both think similar ways. My arguments for this are very weak but let's pretend, for brevity, that things are clearer than they are. I'll propose two reasons why aliens will think like us, in spite of different origins. All problem-solvers, intelligent or not, are subject to the same ultimate constraints–limitations (...) on space, time, and materials. In order for animals to evolve powerful ways to deal with such constraints, they must have ways to represent the situations they face, and they must have processes for manipulating those representations. (shrink)

Adults worry a lot these days. Especially, they worry about how to make other people learn more about computers. They want to make us all "computer-literate." Literacy means both reading and writing, but most books and courses about computers only tell you about writing programs. Worse, they only tell about commands and instructions and programming-language grammar rules. They hardly ever give examples. But real languages are more than words and grammar rules. There's also literature -- what people use the language (...) for. No one ever learns a language from being told its grammar rules. We always start with stories about things that interest us. This book tells some good stories -- in LOGO. (shrink)

This is the first of several memos about how OLPC could initiate useful projects that then could grow without our further support—if adopted by groups in our Diaspora.

Freud's theory of jokes explains how they overcome the mental "censors" that make it hard for us to think "forbidden" thoughts. But his theory did not work so well for humorous nonsense as for other comical subjects. In this essay I argue that the different forms of humor can be seen as much more similar, once we recognize the importance of knowledge about knowledge and, particularly, aspects of thinking concerned with recognizing and suppressing bugs -- ineffective or destructive thought processes. (...) When seen in this light, much humor that at first seems pointless, or mysterious, becomes more understandable. (shrink)

Then, how do we manage to cope with things we don't understand? And, how do we ever understand anything in the first place? Almost always, I think, by using analogies––by pretending that each alien thing we see resembles something we already know. Whenever an object's internal workings are too strange, complicated, or unknown to deal with directly, we try to extract what parts of its behavior seem familiar––and then represent them by familiar symbols––that is, be the names of things we (...) already know which we think behave in similar ways. That way, we make each novelty at least appear to be like something we already know from our own pasts. It is a great idea, that use of symbols. It lets our minds transform the strange into the commonplace. It is the same with names. (shrink)

This chapter contains sections titled: Cultural Predators The Prize is a Clear Conscience Souvenir Parts, Remembered Wholes Snapshots from the Other Side Still Lives Memories as Reanimation Notes.