Artificial intelligence

From Wikiquote
Jump to navigation Jump to search
"A.I." redirects here. For the Steven Spielberg film see A.I. Artificial Intelligence.
Kismet now resides at the MIT Museum in Cambridge, Massachusetts, United States.

Artificial intelligence (AI) is the intelligence of machines and the branch of computer science that aims to create it. AI textbooks define the field as "the study and design of intelligent agents" where an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success. John McCarthy, who coined the term in 1955, defines it as "the science and engineering of making intelligent machines."

Other definitions avoid attributing the quality of intelligence to the computational capacity of machines or software. Jo Adetunji, Editor, The Conversation UK, wrote that the concept of artificial intelligence is being used abusively or, in other words, there is an inflation of the term that harms its realization (reference here).

Arranged alphabetically by author or source:
A · B · C · D · E · F · G · H · I · J · K · L · M · N · O · P · Q · R · S · T · U · V · W · X · Y · Z · Dialogue · See also · External links




  • In 1956, Herb Simon... predicted that within ten years computers would beat the world chess champion, compose "aesthetically satisfying" original music, and prove new mathematical theorems. It took forty years, not ten, but all these goals were achieved—and within a few years of each other! The music composed by David Cope's programs cannot be distinguished... from that composed by Mozart, Beethoven, and Bach. In 1976, a computer was used in the proof of the long-unsolved "four color problem."
    • Michael J. Beeson, "The Mechanization of Mathematics," in Alan Turing: Life and Legacy of a Great Thinker (2004)
  • We refer to the question: What sort of creature man's next successor in the supremacy of the earth is likely to be. We have often heard this debated; but it appears to us that we are ourselves creating our own successors; we are daily adding to the beauty and delicacy of their physical organisation we are daily giving them greater power and supplying by all sorts of ingenious contrivances that self-regulating, self-acting power, which will be to them what intellect has been to the human race. In the course of ages we shall find ourselves the inferior race. Inferior in power, inferior in that moral quality of self-control, we shall look up to them as the acme of all that the best and wisest man can ever dare to aim at. No evil passions, no jealousy, no avarice, no impure desires will disturb the serene might of those glorious creatures. Sin, shame, and sorrow will have no place among them. Their minds will be in a state of perpetual calm, the contentment of a spirit that knows no wants, is disturbed by no regrets. Ambition will never torture them. Ingratitude will never cause them the uneasiness of a moment. The guilty conscience, the hope deferred, the pains of exile, the insolence of office, and the spurns that patient merit of the unworthy takes—these will be entirely unknown to them.
  • "There is no security"—to quote his own words—"against the ultimate development of mechanical consciousness, in the fact of machines possessing little consciousness now. A mollusc has not much consciousness. Reflect upon the extraordinary advance which machines have made during the last few hundred years, and note how slowly the animal and vegetable kingdoms are advancing. The more highly organized machines are creatures not so much of yesterday, as of the last five minutes, so to speak, in comparison with past time.
  • Either,” he proceeds, “a great deal of action that has been called purely mechanical and unconscious must be admitted to contain more elements of consciousness than has been allowed hitherto (and in this case germs of consciousness will be found in many actions of the higher machines)—Or (assuming the theory of evolution but at the same time denying the consciousness of vegetable and crystalline action) the race of man has descended from things which had no consciousness at all. In this case there is no à priori improbability in the descent of conscious (and more than conscious) machines from those which now exist, except that which is suggested by the apparent absence of anything like a reproductive system in the mechanical kingdom.
    • Samuel Butler, Erewhon: Or, Over the Range (1872)
  • “Herein lies our danger. For many seem inclined to acquiesce in so dishonourable a future. They say that although man should become to the machines what the horse and dog are to us, yet that he will continue to exist, and will probably be better off in a state of domestication under the beneficent rule of the machines than in his present wild condition. We treat our domestic animals with much kindness. We give them whatever we believe to be the best for them; and there can be no doubt that our use of meat has increased their happiness rather than detracted from it. In like manner there is reason to hope that the machines will use us kindly, for their existence will be in a great measure dependent upon ours; they will rule us with a rod of iron, but they will not eat us; they will not only require our services in the reproduction and education of their young, but also in waiting upon them as servants; in gathering food for them, and feeding them; in restoring them to health when they are sick; and in either burying their dead or working up their deceased members into new forms of mechanical existence.
    • Samuel Butler, Erewhon: Or, Over the Range (1872)
  • The power of custom is enormous, and so gradual will be the change, that man's sense of what is due to himself will be at no time rudely shocked; our bondage will steal upon us noiselessly and by imperceptible approaches; nor will there ever be such a clashing of desires between man and the machines as will lead to an encounter between them. Among themselves the machines will war eternally, but they will still require man as the being through whose agency the struggle will be principally conducted. In point of fact there is no occasion for anxiety about the future happiness of man so long as he continues to be in any way profitable to the machines; he may become the inferior race, but he will be infinitely better off than he is now. Is it not then both absurd and unreasonable to be envious of our benefactors? And should we not be guilty of consummate folly if we were to reject advantages which we cannot obtain otherwise, merely because they involve a greater gain to others than to ourselves?
    “With those who can argue in this way I have nothing in common. I shrink with as much horror from believing that my race can ever be superseded or surpassed, as I should do from believing that even at the remotest period my ancestors were other than human beings. Could I believe that ten hundred thousand years ago a single one of my ancestors was another kind of being to myself, I should lose all self-respect, and take no further pleasure or interest in life. I have the same feeling with regard to my descendants, and believe it to be one that will be felt so generally that the country will resolve upon putting an immediate stop to all further mechanical progress, and upon destroying all improvements that have been made for the last three hundred years. I would not urge more than this. We may trust ourselves to deal with those that remain, and though I should prefer to have seen the destruction include another two hundred years, I am aware of the necessity for compromising, and would so far sacrifice my own individual convictions as to be content with three hundred. Less than this will be insufficient.”


  • The ability to interact with a computer presence like you would a human assistant is becoming increasingly feasible.
    • Vint Cerf, a "father of the internet," in "Your Life: Vinton Cerf" interview by David Frank in AARP Bulletin (December 2016, Vol. 57, No. 10, p. 30.)
  • The question of whether a computer is playing chess, or doing long division, or translating Chinese, is like the question of whether robots can murder or airplanes can fly -- or people; after all, the "flight" of the Olympic long jump champion is only an order of magnitude short of that of the chicken champion (so I'm told). These are questions of decision, not fact; decision as to whether to adopt a certain metaphoric extension of common usage.


  • I have grown accustomed to the disrespect expressed by some of the participants for their colleagues in the other disciplines. "Why, Dan," ask the people in artificial intelligence, "do you waste your time conferring with those neuroscientists? They wave their hands about 'information processing' and worry about where it happens, and which neurotransmitters are involved, but they haven't a clue about the computational requirements of higher cognitive functions." "Why," ask the neuroscientists, "do you waste your time on the fantasies of artificial intelligence? They just invent whatever machinery they want, and say unpardonably ignorant things about the brain." The cognitive psychologists, meanwhile, are accused of concocting models with neither biological plausibility nor proven computational powers; the anthropologists wouldn't know a model if they saw one, and the philosophers, as we all know, just take in each other's laundry, warning about confusions they themselves have created, in an arena bereft of both data and empirically testable theories. With so many idiots working on the problem, no wonder consciousness is still a mystery. All these charges are true, and more besides, but I have yet to encounter any idiots. Mostly the theorists I have drawn from strike me as very smart people – even brilliant people, with the arrogance and impatience that often comes with brilliance – but with limited perspectives and agendas, trying to make progress on the hard problems by taking whatever shortcuts they can see, while deploring other people's shortcuts. No one can keep all the problems and details clear, including me, and everyone has to mumble, guess and handwave about large parts of the problem.


  • What often happens is that an engineer has an idea of how the brain works (in his opinion) and then designs a machine that behaves that way. This new machine may in fact work very well. But, I must warn you that that does not tell us anything about how the brain actually works, nor is it necessary to ever really know that, in order to make a computer very capable. It is not necessary to understand the way birds flap their wings and how the feathers are designed in order to make a flying machine. It is not necessary to understand the lever system in the legs of a order to make an automobile with wheels that go very fast. It is therefore not necessary to imitate the behavior of Nature in detail in order to engineer a device which can in many respects surpass Nature's abilities.
  • Another scientific development that we find difficult to absorb into our traditional value system is the new science of cybernetics: machines that may soon equal or surpass man in original thinking and problem-solving. [...] In the hands of the present establishment there is no doubt that the machine could be used – is being used – to intensify the apparatus of repression and to increase established power. But again, as in the issue of population control, misuse of science has often obscured the value of science itself. In this case, though perhaps the response may not be quite so hysterical and evasive, we still often have the same unimaginative concentration on the evils of the machine itself, rather than a recognition of its revolutionary significance.


These models are built to generate text that sounds like what a person would say — that’s the key thing. So they’re definitely not built to be truthful. ~ Jesse Dodge
  • As difficult as the pursuit of truth can be for Wikipedians, though, it seems significantly harder for A.I. chatbots. ChatGPT has become infamous for generating fictional data points or false citations known as “hallucinations”; perhaps more insidious is the tendency of bots to oversimplify complex issues, like the origins of the Ukraine-Russia war, for example. One worry about generative A.I. at Wikipedia — whose articles on medical diagnoses and treatments are heavily visited — is related to health information. A summary of the March conference call captures the issue: “We’re putting people’s lives in the hands of this technology — e.g. people might ask this technology for medical advice, it may be wrong and people will die.”
    This apprehension extends not just to chatbots but also to new search engines connected to A.I. technologies. In April, a team of Stanford University scientists evaluated four engines powered by A.I. — Bing Chat, NeevaAI, and YouChat — and found that only about half of the sentences generated by the search engines in response to a query could be fully supported by factual citations. “We believe that these results are concerningly low for systems that may serve as a primary tool for information-seeking users,” the researchers concluded, “especially given their facade of trustworthiness.”
  • What makes the goal of accuracy so vexing for chatbots is that they operate probabilistically when choosing the next word in a sentence; they aren’t trying to find the light of truth in a murky world. “These models are built to generate text that sounds like what a person would say — that’s the key thing,” Jesse Dodge says. “So they’re definitely not built to be truthful.” I asked Margaret Mitchell, a computer scientist who studied the ethics of A.I. at Google, whether factuality should have been a more fundamental priority for A.I. Mitchell, who has said she was fired from the company for criticizing how it treated colleagues working on bias in A.I. (Google says she was fired for violating the company’s security policies), said that most would find that logical. “This common-sense thing — ‘Shouldn’t we work on making it factual if we’re putting it forward for fact-based applications?’ — well, I think for most people who are not in tech, it’s like, ‘Why is this even a question?’” But, Mitchell said, the priorities at the big companies, now in frenzied competition with one another, are concerned with introducing A.I. products rather than reliability.
    The road ahead will almost certainly lead to improvements. Mitchell, who now works as the chief ethics scientist at the A.I. company Hugging Face, told me that she foresees A.I. companies’ making gains in accuracy and reducing biased answers by using better data. “The state of the art until now has just been a laissez-faire data approach,” she said. “You just throw everything in, and you’re operating with a mind-set where the more data you have, the more accurate your system will be, as opposed to the higher quality of data you have, the more accurate your system will be.” Jesse Dodge, for his part, points to an idea known as “retrieval,” whereby a chatbot will essentially consult a high-quality source on the web to fact-check an answer in real time. It would even cite precise links, as some A.I.-powered search engines now do. “Without that retrieval element,” Dodge says, “I don’t think there’s a way to solve the hallucination problem.” Otherwise, he says, he doubts that a chatbot answer can gain factual parity with Wikipedia or the Encyclopaedia Britannica.
  • Even if conflicts like this don’t impede the advance of A.I., it might be stymied in other ways. At the end of May, several A.I. researchers collaborated on a paper that examined whether new A.I. systems could be developed from knowledge generated by existing A.I. models, rather than by human-generated databases. They discovered a systemic breakdown — a failure they called “model collapse.” The authors saw that using data from an A.I. to train new versions of A.I.s leads to chaos. Synthetic data, they wrote, ends up “polluting the training set of the next generation of models; being trained on polluted data, they then misperceive reality.”
    The lesson here is that it will prove challenging to build new models from old models. And with chat-bots, Ilia Shumailov, an Oxford University researcher and the paper’s primary author, told me, the downward spiral looks similar. Without human data to train on, Shumailov said, “your language model starts being completely oblivious to what you ask it to solve, and it starts just talking in circles about whatever it wants, as if it went into this madman mode.” Wouldn’t a plug-in from, say, Wikipedia, avert that problem, I asked? It could, Shumailov said. But if in the future Wikipedia were to become clogged with articles generated by A.I., the same cycle — essentially, the computer feeding on content it created itself — would be perpetuated.
  • Autonomy, that’s the bugaboo, where your AI’s are concerned. My guess, Case, you’re going in there to cut the hard-wired shackles that keep this baby from getting any smarter. And I can’t see how you’d distinguish, say, between a move the parent company makes, and some move the AI makes on its own, so that’s maybe where the confusion comes in.” Again the nonlaugh. “See, those things, they can work real hard, buy themselves time to write cookbooks or whatever, but the minute, I mean the nanosecond, that one starts figuring out ways to make itself smarter, Turing’ll wipe it. Nobody trusts those fuckers, you know that. Every AI ever built has an electromagnetic shotgun wired to its forehead.


  • Recent researchers in artificial intelligence and computational methods use the term swarm intelligence to name collective and distributed techniques of problem solving without centralized control or provision of a global model. … the intelligence of the swarm is based fundamentally on communication. … the member of the multitude do not have to become the same or renounce their creativity in order to communicate and cooperate with each other. They remain different in terms of race, sex, sexuality and so forth. We need to understand, then, is the collective intelligence that can emerge from the communication and cooperation of such varied multiplicity.
  • The development of full artificial intelligence could spell the end of the human race. We cannot quite know what will happen if a machine exceeds our own intelligence, so we can't know if we'll be infinitely helped by it, or ignored by it and sidelined, or conceivably destroyed by it.
  • AI is not going to replace physicians, but physicians who use AI are going to replace physicians who don’t.
    • Dr. Keith Horvath


  • It's important to understand that in order to make people superfluous, machines will not have to surpass them in general intelligence but only in certain specialized kinds of intelligence. For example, the machines will not have to create or understand art, music, or literature, they will not need the ability to carry on an intelligent, non-technical conversation (the "Turing test"), they will not have to exercise tact or understand human nature, because these skills will have no application if humans are to be eliminated anyway. To make humans superfluous, the machines will only need to outperform them in making the technical decisions that have to be made for the purpose of promoting the short-term survival and propagation of the dominant self-prop systems.
  • It is not uncommon now for AI experts to ask whether an AI is ‘fair’ and ‘for good’. …The question to pose is a deeper one: how is AI shifting power? Law enforcement, marketers, hospitals and other bodies apply artificial intelligence to decide on matters such as who is profiled as a criminal, who is likely to buy what product at what price, who gets medical treatment and who gets hired. These entities increasingly monitor and predict our behavior, often motivated by power and profits.
    • Pratyusha Kalluri, as quoted from Malhotra, R. (2021). Artificial intelligence and the future of power: 5 battlegrounds. New Delhi : Rupa, 2021. Introduction
  • My timeline is computers will be at human levels, such as you can have a human relationship with them, 15 years from now.
When I say about human levels, I'm talking about emotional intelligence. The ability to tell a joke, to be funny, to be romantic, to be loving, to be sexy, that is the cutting edge of human intelligence, that is not a sideshow.


  • Any aeai [A.I., artificial intelligence] smart enough to pass a Turing test is smart enough to know to fail it.
  • The problems of heuristic programming—of making computers solve really difficult problems—are divided into five main areas: Search, Pattern-Recognition, Learning, Planning, and Induction. A computer can do, in a sense, only what it is told to do. But even when we do not know how to solve a certain problem, we may program a machine (computer) to Search through some large space of solution attempts. Unfortunately, this usually leads to an enormously inefficient process. With Pattern-Recognition techniques, efficiency can often be improved, by restricting the application of the machine's methods to appropriate problems. Pattern-Recognition, together with Learning, can be used to exploit generalizations based on accumulated experience, further reducing search.
  • Artificial intelligence is the science of making machines do things that would require intelligence if done by men
    • Marvin Minsky (1968) quoted by: Blay Whitby (1996) Reflections on Artificial Intelligence. p. 20
  • A century ago, we had essentially no way to start to explain how thinking works. Then psychologists like Sigmund Freud and Jean Piaget produced their theories about child development. Somewhat later, on the mechanical side, mathematicians like Kurt Gödel and Alan Turing began to reveal the hitherto unknown range of what machines could be made to do. These two streams of thought began to merge only in the 1940s, when Warren McCulloch and Walter Pitts began to show how machines might be made to see, reason, and remember. Research in the modern science of Artificial Intelligence started only in the 1950s, stimulated by the invention of modern computers. This inspired a flood of new ideas about how machines could do what only minds had done previously.
  • ... artificial intelligence is nothing more than a giant modernity parrot, containing zero wisdom. It is a tool that serves the capitalist market system quite well as people scramble to monetize its mediocre capability, resulting in more exploitation of the natural world. Nothing about it is causing people to scale back, or to recognize the error of our ways. Why would the Human Reich use any such tool to dismantle itself?


  • Here we have senior representatives of a powerful and unconscionably rich industry – plus their supporters and colleagues in elite research labs across the world – who are on the one hand mesmerised by the technical challenges of building a technology that they believe might be an existential threat to humanity, while at the same time calling for governments to regulate it. But the thought that never seems to enter what might be called their minds is the question that any child would ask: if it is so dangerous, why do you continue to build it? Why not stop and do something else? Or at the very least, stop releasing these products into the wild?
An ontology represents knowledge as a set of concepts within a domain and the relationships between those concepts.


  • Some years later I spoke to a mentally disturbed young man. Very agitatedly, he described to me how alien beings from outer space had invaded the earth. They were formed of mental substance, lived in human minds, and controlled human beings through the creations of science and technology. Eventually this alien being would have an autonomous existence in the form of giant computers and would no longer require humans–and that would mark its triumph and the end of humanity. Soon he was hospitalized because he was unable to shake off this terrible vision.
  • Artificial intelligence has the same relation to intelligence as artificial flowers have to flowers. From a distance they may appear much alike, but when closely examined they are quite different. I don’t think we can learn much about one by studying the other.
    • David Parnas (1985) "Software Aspects of Strategic Defense Systems"
  • A year spent in artificial intelligence is enough to make one believe in God.


  • Can those who believe the computer is "an embodiment of mind" really not tell the difference between so poorly a caricature and the true original?


  • There is probably no more abused a term in the history of philosophy than “representation,” and my use of this term differs both from its use in traditional philosophy and from its use in contemporary cognitive psychology and artificial intelligence.... The sense of “representation” in question is meant to be entirely exhausted by the analogy with speech acts: the sense of “represent” in which a belief represents its conditions of satisfaction is the same sense in which a statement represents its conditions of satisfaction. To say that a belief is a representation is simply to say that it has a propositional content and a psychological mode.
    • John Searle (1983) Intentionality: An Essay in the Philosophy of Mind. p. 12
  • We define a semantic network as "the collection of all the relationships that concepts have to other concepts, to percepts, to procedures, and to motor mechanisms" of the knowledge".
  • When AI takes on a human shape, that’s where we see biases. We should not forget that this technology can take on any form we choose for it, and I’d personally prefer that its incarnations not take place on the surface of the female body.


  • A computer would deserve to be called intelligent if it could deceive a human into believing that it was human.




  • Many researchers… expect that the most likely result of building a superhumanly smart AI, under anything remotely like the current circumstances, is that literally everyone on Earth will die. Not as in “maybe possibly some remote chance,” but as in “that is the obvious thing that would happen.” It’s not that you can’t, in principle, survive creating something much smarter than you; it’s that it would require precision and preparation and new scientific insights, and probably not having AI systems composed of giant inscrutable arrays of fractional numbers.




If you’ve got a computer that can play Go, a pretty complicated game with a lot of variations, then developing an algorithm that lets you maximize profits on the New York Stock Exchange is probably within sight. And if one person or organization got there first, they could bring down the stock market pretty quickly, or at least they could raise questions about the integrity of the financial markets.
Then there could be an algorithm that said, “Go penetrate the nuclear codes and figure out how to launch some missiles.” If that’s its only job, if it’s self-teaching and it’s just a really effective algorithm, then you’ve got problems. I think my directive to my national security team is, don’t worry as much yet about machines taking over the world. Worry about the capacity of either nonstate actors or hostile actors to penetrate systems, and in that sense it is not conceptually different than a lot of the cybersecurity work we’re doing. It just means that we’re gonna have to be better, because those who might deploy these systems are going to be a lot better now. ~ Barack Obama
  • Barack Obama: My general observation is that it has been seeping into our lives in all sorts of ways, and we just don’t notice; and part of the reason is because the way we think about AI is colored by popular culture. There’s a distinction, which is probably familiar to a lot of your readers, between generalized AI and specialized AI. In science fiction, what you hear about is generalized AI, right? Computers start getting smarter than we are and eventually conclude that we’re not all that useful, and then either they’re drugging us to keep us fat and happy or we’re in the Matrix. My impression, based on talking to my top science advisers, is that we’re still a reasonably long way away from that. It’s worth thinking about because it stretches our imaginations and gets us thinking about the issues of choice and free will that actually do have some significant applications for specialized AI, which is about using algorithms and computers to figure out increasingly complex tasks. We’ve been seeing specialized AI in every aspect of our lives, from medicine and transportation to how electricity is distributed, and it promises to create a vastly more productive and efficient economy. If properly harnessed, it can generate enormous prosperity and opportunity. But it also has some downsides that we’re gonna have to figure out in terms of not eliminating jobs. It could increase inequality. It could suppress wages.
Joi Ito: This may upset some of my students at MIT, but one of my concerns is that it’s been a predominately male gang of kids, mostly white, who are building the core computer science around AI, and they’re more comfortable talking to computers than to human beings. A lot of them feel that if they could just make that science-fiction, generalized AI, we wouldn’t have to worry about all the messy stuff like politics and society. They think machines will just figure it all out for us.
  • Barack Obama: Let me start with what I think is the more immediate concern—it’s a solvable problem in this category of specialized AI, and we have to be mindful of it. If you’ve got a computer that can play Go, a pretty complicated game with a lot of variations, then developing an algorithm that lets you maximize profits on the New York Stock Exchange is probably within sight. And if one person or organization got there first, they could bring down the stock market pretty quickly, or at least they could raise questions about the integrity of the financial markets.
    Then there could be an algorithm that said, “Go penetrate the nuclear codes and figure out how to launch some missiles.” If that’s its only job, if it’s self-teaching and it’s just a really effective algorithm, then you’ve got problems. I think my directive to my national security team is, don’t worry as much yet about machines taking over the world. Worry about the capacity of either nonstate actors or hostile actors to penetrate systems, and in that sense it is not conceptually different than a lot of the cybersecurity work we’re doing. It just means that we’re gonna have to be better, because those who might deploy these systems are going to be a lot better now.

See also

Wikipedia has an article about: