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.

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

The main lesson of thirty-five years of AI research is that the hard problems are easy and the easy problems are hard. The mental abilities of a four-year-old that we take for granted – recognizing a face, lifting a pencil, walking across a room, answering a question – in fact solve some of the hardest engineering problems ever conceived.... As the new generation of intelligent devices appears, it will be the stock analysts and petrochemical engineers and parole board members who are in danger of being replaced by machines. The gardeners, receptionists, and cooks are secure in their jobs for decades to come.

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.

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.

Intelligence is the art of good guesswork.

Instead of trying to produce a programme to simulate the adult mind, why not rather try to produce one which simulates the child's? If this were then subjected to an appropriate course of education one would obtain the adult brain.

An important concept both in Artificial Life and in Artificial Intelligence is that of a genetic algorithm (GA). GAs employ methods analogous to the processes of natural evolution in order to produce successive generations of software entities that are increasingly fit for their intended purpose.

If Artificial Intelligence really has little to do with computer technology and much more to do with abstract principles of mental organization, then the distinctions among AI, psychology, and even philosophy of mind seem to melt away. One can study those basic principles using tools and techniques from computer science, or with the methods of experimental psychology, or in traditional philosophical terms--but it's the same subject in each case. Thus a grand interdisciplinary marriage seems imminent; indeed, a number of enthusiasts have already taken the vows. For their new "unified" field, they have coined the name cognitive science. If you believe the advertisements, Artificial Intelligence and psychology, as well as parts of philosophy, linguistics, and anthropology, are now just "subspecialties" within one coherent study of cognition, intelligence, and mind--that is, of symbol manipulation.

What is most important about artificial intelligence as an area of specialization ... would be its ultimate objective of replicating semiotic systems. Indeed, while artificial intelligence can achieve at least some of its goals by building systems that simulate--and improve upon--the mental abilities that are deployed by human beings, it cannot secure its most treasured goals short of replication, if such a conception is correct. It therefore appears to be an ultimate irony that the ideal limit and final aim of artificial intelligence could turn out to be the development of systems capable of making mistakes.

The popular definition of artificial intelligence research means designing computers that think as people do, and who needs that? There is no commercial reason to duplicate human thought because there is no market for electronic people, although it might be nice if everyone could have a maid and butler. There are plenty of organic people, and computer vendors can't compete with the modern low-cost technology used in making people.

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.

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

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

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.... In 1997, $2,000 of neural computer chips using only modest parallel processing could perform around 2 billion calculations per second.... This capacity will double every twelve months. Thus by the year 2020, it will have doubled about twenty-three times, resulting in a speed of about 20 million billion neural connection calculations per second, which is equal to the human brain.

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.

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.

With the increasingly important role of intelligent machines in all phases of our lives--military, medical, economic and financial, political--it is odd to keep reading articles with titles such as Whatever Happened to Artificial Intelligence? This is a phenomenon that Turing had predicted: that machine intelligence would become so pervasive, so comfortable, and so well integrated into our information-based economy that people would fail even to notice it.

Artificial intelligence is no match for natural stupidity.

The key issue as to whether or not a non-biological entity deserves rights really comes down to whether or not it's conscious.... Does it have feelings?