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John McCarthy

John McCarthy at a summit in 2006
Born September 4, 1927 (1927-09-04) (age 82)
Boston, Massachusetts, USA
Residence USA
Nationality American
Fields Computer Technology
Institutions Massachusetts Institute of Technology; Stanford University; Dartmouth College; Princeton University
Alma mater Princeton University; California Institute of Technology
Doctoral advisor Solomon Lefschetz
Doctoral students Ruzena Rajcsy
Randall Davis
Claude Green
Barbara Liskov
Robert Moore
Francis Morris
Raj Reddy
Known for Artificial Intelligence; Circumscription; Situation calculus; LISP
Notable awards Turing Award, 1971; Benjamin Franklin Medal in Computer and Cognitive Science, 2003

John McCarthy (born September 4, 1927, in Boston, Massachusetts), is an American computer scientist and cognitive scientist who received the Turing Award in 1971 for his major contributions to the field of Artificial Intelligence (AI). He was responsible for the coining of the term "Artificial Intelligence" in his 1955 proposal for the 1956 Dartmouth Conference and is the inventor of the Lisp programming language.

Contents

Early life and education

John McCarthy was born in Boston on September 4, 1927 to two Irish immigrants, John Patrick and Ida Glatt McCarthy. The family was forced to move frequently during the Depression, until McCarthy's father found work as an organizer for the Amalgamated Clothing Workers in Los Angeles, California.

McCarthy showed an early aptitude for mathematics; in his teens he taught himself mathematics by studying the textbooks used at the nearby California Institute of Technology (Caltech). As a result, when he was accepted into Caltech the following year, he was able to skip the first two years of mathematics.[1]

Receiving a B.S. in Mathematics in 1948, McCarthy initially continued his studies at Caltech. He received a Ph.D. in Mathematics from Princeton University in 1951 under Solomon Lefschetz.

Career in computer science

After short-term appointments at Princeton, Stanford University, Dartmouth, and MIT, he became a full professor at Stanford in 1962, where he remained until his retirement at the end of 2000. He is now a professor emeritus.

McCarthy championed mathematical logic for Artificial Intelligence. In 1958, he proposed the advice taker, which inspired later work on question-answering and logic programming. Based on the Lambda Calculus, Lisp rapidly became the programming language of choice for AI applications after its publication in 1960.[2] He helped to motivate the creation of Project MAC at MIT, but left MIT for Stanford University in 1962, where he helped set up the Stanford AI Laboratory, for many years a friendly rival to Project MAC.

In 1961, he was the first to publicly suggest (in a speech given to celebrate MIT's centennial) that computer time-sharing technology might lead to a future in which computing power and even specific applications could be sold through the utility business model (like water or electricity). This idea of a computer or information utility was very popular in the late 1960s, but faded by the mid-1970s as it became clear that the hardware, software and telecommunications technologies of the time were simply not ready. However, since 2000, the idea has resurfaced in new forms (see application service provider and cloud computing.)

From 1978 to 1986, McCarthy developed the circumscription method of nonmonotonic reasoning.

In 1982 he appears to have originated the idea of the space fountain which was further examined by Roderick Hyde.[3]

McCarthy often comments on world affairs on the Usenet forums. Some of his ideas can be found in his sustainability web page, which is "aimed at showing that human material progress is desirable and sustainable".

Major publications

  • McCarthy, J. 1959. Programs with common sense. In Proceedings of the Teedington Conference on the Mechanization of Thought Processes, 756-91. London: Her Majesty's Stationery Office.
  • McCarthy, J. 1960. Recursive functions of symbolic expressions and their computation by machine. Communications of the ACM 3(4):184-195.
  • McCarthy, J. 1963a A basis for a mathematical theory of computation. In Computer Programming and formal systems. North-Holland.
  • McCarthy, J. 1963b. Situations, actions, and causal laws. Technical report, Stanford University.
  • McCarthy, J., and Hayes, P. J. 1969. Some philosophical problems from the standpoint of artificial intelligence. In Meltzer, B., and Michie, D., eds., Machine Intelligence 4. Edinburgh: Edinburgh University Press. 463-502.
  • McCarthy, J. 1977. Epistemological problems of artificial intelligence. In IJCAI, 1038-1044.
  • McCarthy, J. 1980. Circumscription: A form of non-monotonic reasoning. Artificial Intelligence 13(1-2):23-79.
  • McCarthy, J. 1986. Applications of circumscription to common sense reasoning. Artificial Intelligence 28(1):89-116.
  • McCarthy, J. 1990. Generality in artificial intelligence. In Lifschitz, V., ed., Formalizing Common Sense. Ablex. 226-236.
  • McCarthy, J. 1993. Notes on formalizing context. In IJCAI, 555-562.
  • McCarthy, J., and Buvac, S. 1997. Formalizing context: Expanded notes. In Aliseda, A.; van Glabbeek, R.; and Westerstahl, D., eds., Computing Natural Language. Stanford University. Also available as Stanford Technical Note STAN-CS-TN-94-13.
  • McCarthy, J. 1998. Elaboration tolerance. In Working Papers of the Fourth International Symposium on Logical formalizations of Commonsense Reasoning, Commonsense-1998.
  • Costello, T., and McCarthy, J. 1999. Useful counterfactuals. Electronic Transactions on Artificial Intelligence 3(A):51-76
  • McCarthy, J. 2002. Actions and other events in situation calculus. In Fensel, D.; Giunchiglia, F.; McGuinness, D.; and Williams, M., eds., Proceedings of KR-2002, 615-628.

See also

References

  1. ^ Hayes, Patrick J.; Leora Morgenstern (2007). "On John McCarthy's 80th Birthday, in Honor of his Contributions". AI Magazine 28 (4).  
  2. ^ McCarthy, John. "Recursive Functions of Symbolic Expressions and Their Computation by Machine". CACM 3 (4): 184–195. http://portal.acm.org/citation.cfm?id=367199.  
  3. ^ Usenet posting in sci.space.tech on 1 Aug 1994

Further reading

  • Scientific Temperaments: Three Lives in Contemporary Science by Philip J. Hilts, Simon and Schuster, 1982. Lengthy profiles of John McCarthy, physicist Robert R. Wilson and geneticist Mark Ptashne.
  • Machines Who Think: a personal inquiry into the history and prospects of artificial intelligence by Pamela McCorduck, 1979, second edition 2004.
  • The Omni Interviews edited by Pamela Weintraub, New York: Ticknor and Fields, 1984. Collected interviews originally published in Omni magazine; contains an interview with McCarthy.

External links

Set of interviews
Preceded by
Lucy Suchman
Benjamin Franklin Medal in Computer and Cognitive Science
2003
Succeeded by
Richard M. Karp
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Quotes

Up to date as of January 14, 2010

From Wikiquote

It's difficult to be rigorous about whether a machine really 'knows', 'thinks', etc., because we're hard put to define these things. We understand human mental processes only slightly better than a fish understands swimming.

John McCarthy (born September 4, 1927, in Boston, Massachusetts) is an American computer scientist and cognitive scientist who received the Turing Award in 1971 for his major contributions to the field of Artificial Intelligence (AI). He was responsible for the coining of the term "Artificial Intelligence" in his 1955 proposal for the 1956 Dartmouth Conference and is the inventor of the Lisp programming language.

Sourced

  • In 1936 the notion of a computable function was clarified by Turing, and he showed the existence of universal computers that, with an appropriate program, could compute anything computed by any other computer. [...] In some subconscious sense even the sales departments of computer manufacturers are aware of this, and they do not advertise magic instructions that cannot be simulated on competitors machines, but only that their machines are faster, cheaper, have more memory, or are easier to program.
  • Intelligence has two parts, which we shall call the epistemological and the heuristic. The epistemological part is the representation of the world in such a form that the solution of problems follows from the facts expressed in the representation. The heuristic part is the mechanism that on the basis of the information solves the problem and decides what to do.
    [...]
    The right way to think about the general problems of metaphysics and epistemology is not to attempt to clear one's own mind of all knowledge and start with 'Cogito ergo sum' and build up from there. Instead, we propose to use all of our knowledge to construct a computer program that knows. The correctness of our philosophical system will be tested by numerous comparisons between the beliefs of the program and our own observations and knowledge.
  • Machines as simple as thermostats can be said to have beliefs, and having beliefs seems to be a characteristic of most machines capable of problem solving performance. However, the machines mankind has so far found it useful to construct rarely have beliefs about beliefs, although such beliefs will be needed by computer programs that reason about what knowledge they lack and where to get it. Mental qualities peculiar to human-like motivational structures , such as love and hate, will not be required for intelligent behavior, but we could probably program computers to exhibit them if we wanted to, because our common sense notions about them translate readily into certain program and data structures. Still other mental qualities, e.g. humor and appreciation of beauty, seem much harder to model.
  • When we program a computer to make choices intelligently after determining its options, examining their consequences, and deciding which is most favorable or most moral or whatever, we must program it to take an attitude towards its freedom of choice essentially isomorphic to that which a human must take to his own.
  • It's difficult to be rigorous about whether a machine really 'knows', 'thinks', etc., because we're hard put to define these things. We understand human mental processes only slightly better than a fish understands swimming.
  • Program designers have a tendency to think of the users as idiots who need to be controlled. They should rather think of their program as a servant, whose master, the user, should be able to control it. If designers and programmers think about the apparent mental qualities that their programs will have, they'll create programs that are easier and pleasanter — more humane — to deal with.
  • Whenever we write an axiom, a critic can say that the axiom is true only in a certain context. With a little ingenuity the critic can usually devise a more general context in which the precise form of the axiom doesn't hold. [...] There simply isn't a most general context.

External links


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