Quotations

AI is not the science of building artificial people. It’s not the science of understanding human intelligence. It’s not even the science of trying to build artifacts that can imitate human behavior well enough to fool someone that the machine is human, as proposed in the famous Turing test…AI is the science of making machines do tasks that humans can do or try to do…you could argue…that much of computer science and engineering is included in this definition…that’s probably right…(but) the field (of AI) focuses on the more complex things that people do.

James F. Allen, Professor of Computer Science, University of Rochester,
from “AI Growing Up,” AI Magazine, Winter 1998

AI is about making machines more fathomable and more under the control of human beings, not less. Conventional technology has indeed been making our environment more complex and more incomprehensible, and if it continues as it is doing now the only conceivable outcome is disaster.

Donald Michie, leading British AI researcher quoted by Daniel Crevier
“The Tumultuous History of the Search for Artificial Intelligence,” 1993.

Advances in the cognitive sciences and AI almost always directly precede advances in business intelligence technology—data mining, query methods, and so on. Barry Grushkin.

Intelligent Enterprise magazine, May 15, 2000

Today’s AI is about new ways of connecting people to computers, people to knowledge, people to the physical world,  and people to people.

Patrick Winston, MIT AI Lab, 1997
www.ai.mit.edu/director/briefing.html

Artificial intelligence is used to solve complex problems that are:

• Usually resolved by an expert

• Not amenable to straight forward solution by numerical computation; or, if they might theoretically be solved numerically, the computations would take an impractically long time and/or use too much computational resources

• Usually solved by people using rules of thumb (heuristics), that work most of the time but with no guarantees

• Ill-defined

• Related to situations that constantly change over time (i.e., are dynamic), so that a better solution is likely to be made by someone (or some software) that can take the changes into account as they happen, rather than set up rules for decision making in advance by trying to anticipate what changes may happen

• Not readily solvable by breaking the problem into interacting sub-problems

• Highly dependent on the context within which the problem occurs in terms of determining an adequate solution

Derek Partridge (1998)

AI and Software Engineering It may well be that the way to build an intelligence is just to get your hands on dirty engineering problems. We don’t have a theory of automobiles. We have good cars, but there are no fundamental equations of automotive science. Hans Moravec

quoted by Daniel Crevier
“The Tumultuous History of the Search for Artificial Intelligence,” 1993

There is a popular cliche…which says that you cannot get out of computers any more than you have put in…, that computers can only do exactly what you tell them to, and that therefore computers are never creative. This cliché is true only in a crashingly trivial sense, the same sense in which Shakespeare never wrote anything except what his first schoolteacher taught him to write—words.

Richard Dawkins, “The Blind Watchmaker”  quoted by Stan Franklin
“Artificial Minds,” 1997

I think it is getting increasingly difficult to draw a circle around it (artificial intelligence). Like everybody else, I have started a company and as I go out into the real world, the scales fall from my eyes. One of these scales has been the belief that AI could be sold to anybody by itself. It really must be blended with other more standard technology to be useful. The new enterprise of AI is to combine with people to produce something that neither can produce alone. It means your programs don’t even have to be really smart. If all you do is save a $200 million blunder once in a while by asking somebody to look at something, that’s good enough to be very important. I think we are going to enter into a new era with respect to applications of AI that’s quite different from the 1980s. This was the age where expert systems were replacing people, whereas the 1990s will be the age of what we could call “raisin bread systems” for making people smarter. AI is now embedded in systems like raisins in raisin bread. It doesn’t have to occupy much volume and may carry a lot of the nutrition. You can’t have the raisin bread without the raisins, and there can be different kinds of raisins. That’s the way I think the 1990s will benefit from AI: raisin bread systems for making people smarter.

Patrick Winston, director of MIT’s AI Laboratory, 1991 quoted by Daniel Crevier,
“The Tumultuous History of the Search for Artificial Intelligence,” 1993

…the deep paradox uncovered by AI research: the only way to deal efficiently with very complex problems is to move away from pure logic…Most of the time, reaching the right decision requires little reasoning …Expert systems are, thus, not about reasoning: they are about knowing  … Reasoning takes time, so we try to do it as seldom as possible. Instead we store the results of our reasoning for later reference…

Daniel Crevier
“The Tumultuous History of the Search for Artificial Intelligence,” 1993.

We tend not even to use the term AI. The tendency now is for AI companies to embed expert systems into conventional products to build up a functional unit. They strive at becoming known as successful solution providers, rather than AI technology enterprises. A typical example of this covert approach is a sales support program for a retail company that takes orders by telephone.  In its standard form, the program would simply check the presence of a requested item in inventory, record the sale, prepare the invoice, and advise shipping to act on it. The new-wave AI touch consists in “embedding” an expert system into this program. To the sales clerk it looks exactly the same, but for one exception: for sold-out items, suggestions for alternative choices pop on screen.

Harry Reinstein, president of Aion Corp., ~1988 quoted by Daniel Crevier
“The Tumultuous History of the Search for Artificial Intelligence,” 1993

The insight at the root of artificial intelligence was that these “bits” (manipulated by computers) could just as well stand as symbols for concepts that the machine would combine by the strict rules of logic or the looser associations of psychology.

Daniel Crevier
“The Tumultuous History of the Search for Artificial Intelligence,” 1993

Emergent behavior is that which cannot be predicted through analysis at any level simpler than that of the system as a whole…Emergent behavior, by definition, is what’s left after everything else has been explained.

George B. Dyson
“Darwin Among the Machines: The Evolution of Global Intelligence,”  p9, 1997

Minds choose what to do next.

Stan Franklin, “Artificial Minds,” 1997

Artificial intelligence is no match for natural stupidity.

Anonymous from a list of sayings on the Internet

We should, by the way, be prepared for some radical, and perhaps surprising, transformations of the disciplinary structure of science (technology included) as information processing pervades it. In particular, as we become more aware of the detailed information processes that go on in doing science, the sciences will find themselves increasingly taking a metaposition, in which doing science (observing, experimenting, theorizing, testing, archiving, …) will involve understanding these information processes, and building systems that do the object-level science. Then the boundaries between the enterprise of science as a whole (the acquisition and organization of knowledge of the world) and AI (the understanding of how knowledge is acquired and organized) will become increasingly fuzzy.

Allen Newell in D.G. Bobrow and P.J. Hayes
“Artificial Intelligence – Where Are We?” Artif. Intell. 25 (1985) 3.

The ability to learn faster than your competitors may be the only sustainable competitive advantage.

Arie P. De Geus, former coordinator, group planning, Royal Dutch/Shell quoted by Peter M. Senge
“The Fifth Discipline”

Artificial intelligence is that field of computer usage which attempts to construct computational mechanisms for activities that are considered to require intelligence when performed by humans.

Derek Partridge (1998) – Artificial Intelligence and Software Engineering: Understanding the Promise of the Future; Chicago: Glenlake Publishing Company.

—there is no demand for the art and artifice of AI in most numerical computation.

Derek Partridge (1998) – Artificial Intelligence and Software Engineering: Understanding the Promise of the Future; Chicago: Glenlake Publishing Company.

Artificial intelligence is the study of how to make real computers act like the ones in the movies.

Anonymous quoted by the Port 2000 Newsletter,
The Information Technology Newsletter for Port Washington Educators, Dec. 96

The essential division in the (computer) industry between hardware and software represents the organization of computing from the system designer’s viewpoint, not the user’s. In successful mature technologies it’s not possible to isolate the form and function. The logical design and the mechanical design of a pen or a piano bind their mechanism with their user interface so closely that it’s possible to use them without thinking of them as technology, or even thinking of them at all. Invisibility is the missing goal in computing.

Neil Gershenfeld, “When Things Start to Think.”

Yet excesses of optimism seem to occur with particular frequency in AI.

Daniel Crevier,
“The Tumultuous History of the Search for Artificial Intelligence,” p4, 1993.

Machines will be capable, within twenty years, of doing any work that a man can do.

Herbert Simon, 1965. Quoted by Daniel Crevier
“The Tumultuous History of the Search for Artificial Intelligence,” 1993.

…in activities other than purely logical thought, our minds function much faster than any computer yet devised.

Daniel Crevier
“The Tumultuous History of the Search for Artificial Intelligence,” p5, 1993.

The human brain has about 100 billion neurons. With an estimated average of one thousand connections between each neuron and its neighbors, we have about 100 trillion connections, each capable of a simultaneous calculation… (but) only 200 calculations per second… With 100 trillion connections, each computing at 200 calculations per second, we get 20 million billion calculations per second. This is a conservatively high estimate… by the year 2020, (a massively parallel neural net computer) will have doubled about 23 times (from 1997’s $2,000 modestly parallel computer that could perform around 2 billion connection calculations per second) … resulting in a speed of about 20 million billion neural connection calculations per second, which is equal to the human brain.

Ray Kurzweil, “The Age of Spiritual Machines”, 1999

Pattern recognition and association make up the core of our thought. These activities involve millions of operations carried out in parallel, outside the field of our consciousness. If AI appeared to hit a brick wall after a few quick victories, it did so owing to its inability to emulate these processes.

Daniel Crevier
“The Tumultuous History of the Search for Artificial Intelligence,” p5, 1993.

If you feel you have a knowledge management issue, you have an AI issue.

Richard Stottler, May 99

Artificial intelligence is the mimicking of human thought and cognitive processes to solve complex problems.

Richard Stottler, May 1999

Our ultimate objective is to make programs that learn from their experience as effectively as humans do. We shall…say that a program has common sense if it automatically deduces for itself a sufficient wide class of immediate consequences of anything it is told and what it already knows.

John McCarthy, from his paper, “Programs with Common Sense,” 1958.
Quoted by Daniel Crevier, “The Tumultuous History of the Search for Artificial Intelligence,” 1993

Artificial intelligence has done well in tightly constrained domains—Winograd, for example, astonished everyone with the expertise of his blocks-world natural language. Extending this kind of ability to larger worlds has not proved straightforward, however…The time has come to treat the problems involved as central issues.

Patrick H. Winston and staff of the MIT AI Laboratory,  AI Memo no. 366, May 1976, p22.
Quoted by Daniel Crevier, “The Tumultuous History of the Search for Artificial Intelligence,” 1993.

We achieve more than we know. We know more than we understand. We understand more than we can explain.

Claude Bernard, 19th C French scientific philosopher.  Quoted by Daniel Crevier
“The Tumultuous History of the Search for Artificial Intelligence,” 1993.

AI has never been a monolithic science; by the mid-1970s, the diverging interests of its pioneers were giving birth to recognizable specialties.

Daniel Crevier
“The Tumultuous History of the Search for Artificial Intelligence,” 1993.

Worthless.

Reply by the British Astronomer Royal, Sir George Biddell Airy, September 15, 1842,  responding to a query from the Chancellor of the Exchequer, who was considering funding of construction of Charles Babbage’s analytical engine, a mechanical calculator, a predecessor to the digital computer

Artificial intelligence is not a term generally used at IBM.

Kathleen Keeshen, IBM spokesperson, 1982, quoted by Daniel Crevier,
“The Tumultuous History of the Search for Artificial Intelligence,” 1993.

The part of intuition that involves pattern making and recognition of familiar and typical cases can be trained. If you want people to size up situations quickly and accurately, you need to expand their experience base. One way is to arrange for a person to receive more difficult cases.

Gary Klein, “Sources of Power: How People Make Decisions.”

The growing emphasis on high-technology production means greater demands on the competence of each individual employee. And so the element of comprehensive, life long learning for all members of the enterprise will probably turn out to be the most characteristic feature of work in the 21st century.

Robert B. McKersie and Richard E. Walton,
“Organizational Change, in The Corporation of the 1990s, Oxford University Press, 1991.

Intelligence is the art of good guesswork.

H.B. Barlow
The Oxford Companion to the Mind

Intelligence is what you use when you don’t know what to do.

Jean Piaget

Artificial intelligence is what you use when you want to intelligently automate a complex task.

Rick Row, 1999

A skill learned also needs to be a skill practiced continuously.

Elliott Masie, 1999

It is (the ability of humans to think and reason in imprecise, non quantitative terms) that makes it possible for humans to decipher sloppy hand-writing, understand distorted speech, and focus on that information that is relevant to a decision. It is the lack of this ability that makes even the most sophisticated computer incapable of communicating with humans in natural—rather than artificially constructed—languages.

Lotfi Zadeh, inventor of fuzzy sets

If we desire to form individuals capable of inventive thought and of helping the society of tomorrow to achieve progress, then it is clear that an education which is an active discovery of reality is superior to one that consists merely in providing the young with ready-made wills to will with and ready-made truths to know with…

Jean Piaget,
The Science of Education and the Psychology of the Child, The Viking Press, 1971

Our everyday reasoning is not precise, but it is nevertheless efficient. Nature, itself, from galaxies to genes, is approximate and inexact. Philosophical concepts are among the least precise. Terms such as ‘mind,’ ‘perception,’ ‘memory,’ and ‘knowledge’ do not have either a fixed nor a clear meaning but they make sense just the same.

Gian-Carlo Rota, mathematician quoted by Arturo Sangalli
“The Importance of Being Fuzzy and Other Insights from the Border between Math and Computers”

The deadly paradox of the information society is this: The more others know about us, the better they can serve us and deliver the services we require. But the more they know, the more likely are the misuses and the selling of private data, threatening privacy.

Donald A. Norman, informationweek.com, Jan. 3, 2000

I’m not a fan of technology. I’m a fan of pedagogy, of understanding how people learn and the most effective learning methods. But technology enables some exciting changes.

Don Norman, president, UNext Learning Systems
quoted in Inside Technology Training, Jan, 2000

An individual understands a concept, skill, theory, or domain of knowledge to the extent that he or she can apply it appropriately in a new situation.

Howard Gardner,
The Disciplined Mind: What All Students Should Understand, Simon & Schuster, 1999.

Learning is any change in a system that produces a more or less permanent change in its capacity for adapting to its environment.

Herbert A. Simon
The Sciences of the Artificial, The MIT Press, 1996.