Artificial Intelligence - What Is The Dartmouth AI Conference?

  

The Dartmouth Conference on Artificial Intelligence, officially known as the "Dartmouth Summer Research Project on Artificial Intelligence," was held in 1956 and is frequently referred to as the AI Constitution.

• The multidisciplinary conference, held on the Dartmouth College campus in Hanover, New Hampshire, brought together specialists in cybernetics, automata and information theory, operations research, and game theory.

• Claude Shannon (the "father of information theory"), Marvin Minsky, John McCarthy, Herbert Simon, Allen Newell ("founding fathers of artificial intelligence"), and Nathaniel Rochester (architect of IBM's first commercial scientific mainframe computer) were among the more than twenty attendees.

• Participants came from the MIT Lincoln Laboratory, Bell Laboratories, and the RAND Systems Research Laboratory.

The Rockefeller Foundation provided a substantial portion of the funding for the Dartmouth Conference.

The Dartmouth Conference, which lasted around two months, was envisaged by the organizers as a method to make quick progress on computer models of human cognition.

• "Every facet of learning or any other trait of intelligence may in theory be so clearly characterized that a computer can be constructed to replicate it," organizers said as a starting point for their deliberations (McCarthy 1955, 2).

• In his Rockefeller Foundation proposal a year before to the summer meeting, mathematician and principal organizer John McCarthy created the phrase "artificial intelligence." McCarthy subsequently said that the new name was intended to establish a barrier between his study and the discipline of cybernetics.

• He was a driving force behind the development of symbol processing techniques to artificial intelligence, which were at the time in the minority.

• In the 1950s, analog cybernetic techniques and neural networks were the most common brain modeling methodologies.

Issues Covered At The Conference.

The Dartmouth Conference included a broad variety of issues, from complexity theory and neuron nets to creative thinking and unpredictability.

• The conference is notable for being the site of the first public demonstration of Newell, Simon, and Clifford Shaw's Logic Theorist, a program that could independently verify theorems stated in Bertrand Russell and Alfred North Whitehead's Principia Mathematica.

• The only program at the conference that tried to imitate the logical features of human intellect was Logic Theorist.

• Attendees predicted that by 1970, digital computers would have become chess grandmasters, discovered new and important mathematical theorems, produced passable language translations and understood spoken language, and composed classical music.

• Because the Rockefeller Foundation never received a formal report on the conference, the majority of information on the events comes from memories, handwritten notes, and a few papers authored by participants and published elsewhere.

Mechanization of Thought Processes

Following the Dartmouth Conference, the British National Physical Laboratory (NPL) hosted an international conference on "Mechanization of Thought Processes" in 1958.

• Several Dartmouth Conference attendees, including Minsky and McCarthy, spoke at the NPL conference.

• Minsky mentioned the Dartmouth Conference's relevance in the creation of his heuristic software for solving plane geometry issues and the switch from analog feedback, neural networks, and brain modeling to symbolic AI techniques at the NPL conference.

• Neural networks did not resurface as a research topic until the mid-1980s.

Dartmouth Summer Research Project 

The Dartmouth Summer Research Project on Artificial Intelligence was a watershed moment in the development of AI. 

The Dartmouth Summer Research Project on Artificial Intelligence, which began in 1956, brought together a small group of scientists to kick off this area of study. 

To mark the occasion, more than 100 researchers and academics gathered at Dartmouth for AI@50, a conference that celebrated the past, appraised current achievements, and helped seed ideas for future artificial intelligence research. 

John McCarthy, then a mathematics professor at the College, convened the first gathering. 

The meeting would "continue on the basis of the premise that any facet of learning or any other attribute of intelligence may in theory be so clearly characterized that a computer can be constructed to replicate it," according to his plan. 

The director of AI@50, Professor of Philosophy James Moor, explains that the researchers who came to Hanover 50 years ago were thinking about methods to make robots more aware and sought to set out a framework to better comprehend human intelligence.

Context Of The Dartmouth AI Conference:

Cybernetics, automata theory, and sophisticated information processing were all terms used in the early 50s to describe the science of "thinking machines." 

The wide range of names reflects the wide range of intellectual approaches. 

In, John McCarthy, a Dartmouth College Assistant Professor of Mathematics, wanted to form a group to clarify and develop ideas regarding thinking machines. 

• For the new field, he chose the moniker 'Artificial Intelligence.' He picked the term mainly to escape a concentration on limited automata theory and cybernetics, which was largely focused on analog feedback, as well as the possibility of having to accept or dispute with the aggressive Norbert Wiener as guru. 

• McCarthy addressed the Rockefeller Foundation in early to seek money for a summer seminar at Dartmouth that would attract roughly 150 people. 

• In June, he and Claude Shannon, then at Bell Labs, met with Robert Morison, Director of Biological and Medical Research, to explore the concept and potential financing, but Morison was skeptical if money would be made available for such a bold initiative. 

McCarthy, Marvin Minsky, Nathaniel Rochester, and Claude Shannon officially proposed the proposal in September. The term "artificial intelligence" was coined as a result of this suggestion. 

According to the proposal, 

• We suggest that during the summer of at Dartmouth College in Hanover, New Hampshire, a -month, -man artificial intelligence research be conducted. 

• The research will be based on the hypothesis that any part of learning, or any other characteristic of intelligence, can be characterized exactly enough for a computer to imitate it. 

• It will be attempted to figure out how to get robots to speak, develop abstractions and ideas, solve issues that are now reserved for people, and improve themselves. 

• We believe that if a properly chosen group of scientists worked on one or more of these topics together for a summer, considerable progress might be accomplished. 

• Computers, natural language processing, neural networks, theory of computing, abstraction, and creativity are all discussed further in the proposal (these areas within the field of artificial intelligence are considered still relevant to the work of the field). 

He remarked, "We'll focus on the difficulty of figuring out how to program a calculator to construct notions and generalizations. 

Of course, this is subject to change once the group meets." Ray Solomonoff, Oliver Selfridge, Trenchard More, Arthur Samuel, Herbert A. Simon, and Allen Newell were among the participants at the meeting, according to Stottler Henke Associates. 

The real participants arrived at various times, most of which were for far shorter periods of time. 

• Rochester was replaced for three weeks by Trenchard More, and MacKay and Holland were unable to attend—but the project was prepared to commence. 

• Around June of that year, the first participants (perhaps simply Ray Solomonoff, maybe with Tom Etter) came to Dartmouth College in Hanover, New Hampshire, to join John McCarthy, who had already set up residence there. 

• Ray and Marvin remained at the Professors' apartments, while the most of the guests stayed at the Hanover Inn.

List Of Dartmouth AI Conference Attendees:

1. Ray Solomonoff
2. Marvin Minsky
3. John McCarthy
4. Claude Shannon
5. Trenchard More
6. Nat Rochester
7. Oliver Selfridge
8. Julian Bigelow
9. W. Ross Ashby
10. W.S. McCulloch
11. Abraham Robinson
12. Tom Etter
13. John Nash
14. David Sayre
15. Arthur Samuel
16. Kenneth R. Shoulders
17. Shoulders' friend
18. Alex Bernstein
19. Herbert Simon
20. Allen Newell

~ Jai Krishna Ponnappan

You may also want to read more about Artificial Intelligence here.

See also: 

Cybernetics and AI; Macy Conferences; McCarthy, John; Minsky, Marvin; Newell, Allen; Simon, Herbert A.

References & Further Reading:

Crevier, Daniel. 1993. AI: The Tumultuous History of the Search for Artificial Intelligence. New York: Basic Books.

Gardner, Howard. 1985. The Mind’s New Science: A History of the Cognitive Revolution. New York: Basic Books.

Kline, Ronald. 2011. “Cybernetics, Automata Studies, and the Dartmouth Conference on Artificial Intelligence.” IEEE Annals of the History of Computing 33, no. 4 (April): 5–16.

McCarthy, John. 1955. “A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence.” Rockefeller Foundation application, unpublished.

Moor, James. 2006. “The Dartmouth College Artificial Intelligence Conference: The Next Fifty Years.” AI Magazine 27, no. 4 (Winter): 87–91.

Solomonoff, R.J.The Time Scale of Artificial Intelligence; Reflections on Social Effects, Human Systems Management, Vol 5 1985, Pp 149-153

Moor, J., The Dartmouth College Artificial Intelligence Conference: The Next Fifty years, AI Magazine, Vol 27, No., 4, Pp. 87-9, 2006

ump up to:

Kline, Ronald R., Cybernetics, Automata Studies and the Dartmouth Conference on Artificial Intelligence, IEEE Annals of the History of Computing, October–December, 2011, IEEE Computer Society

McCorduck, P., Machines Who Think, A.K. Peters, Ltd, Second Edition, 2004

Nilsson, N., The Quest for Artificial Intelligence, Cambridge University Press, 2010

Kline, Ronald R., Cybernetics, Automata Studies and the Dartmouth Conference on Artificial Intelligence, IEEE Annals of the History of Computing, October–December, 2011, IEEE Computer Society, (citing letters, from Rockefeller Foundation Archives, Dartmouth file6, 17, 1955 etc.

McCarthy, J., Minsky, M., Rochester, N., Shannon, C.E., A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence., http://raysolomonoff.com/dartmouth/boxa/dart564props.pdf August, 1955

McCarthy, John; Minsky, Marvin; Rochester, Nathan; Shannon, Claude (1955), A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence, archived from the original on 2007-08-26, retrieved 2006-04-09 retrieved 10:47 (UTC), 9th of April 2006

 Stottler-Henke retrieved 18:19 (UTC), 27th of July 2006

"Artificial Intelligence: Past, Present, and Future (Vox of Dartmouth)".

"The Dartmouth Artificial Intelligence Conference: The Next Fifty Years".

Nilsson, N., The Quest for Artificial Intelligence, Cambridge University Press, 2010, P. 53

Solomonoff, R.J., dart56ray622716talk710.pdf, 1956 URL:{http://raysolomonoff.com/dartmouth/boxbdart/dart56ray622716talk710.pdf

Papers at http://raysolomonoff.com/dartmouth/boxbdart/boxbdart.html

McCarthy, J., List, Sept., 1956; List among Solomonoff papers to be posted on website solomonof.com
http://raysolomonoff.com/dartmouth/boxbdart/dart56ray812825who.pdf 1956

Nilsson, N., The Quest for Artificial Intelligence, Cambridge University Press, 2010,
personal communication

More, Trenchard, 1956, http://raysolomonoff.com/dartmouth/boxa/dart56more5th6thweeks.pdf

McCorduck, P., Machines Who Think, A.K. Peters, Ltd, Second Edition, 2004.

"Dartmouth AI Archives"

Artificial Intelligence - Who Was John McCarthy?

 

John McCarthy  (1927–2011) was an American computer scientist and mathematician who was best known for helping to develop the subject of artificial intelligence in the late 1950s and pushing the use of formal logic in AI research.

McCarthy was a creative thinker who earned multiple accolades for his contributions to programming languages and operating systems research.

Throughout McCarthy's life, however, artificial intelligence and "formalizing common sense" remained his primary research interest (McCarthy 1990).

As a graduate student, McCarthy first met the concepts that would lead him to AI at the Hixon conference on "Cerebral Mechanisms in Behavior" in 1948.

The symposium was place at the California Institute of Technology, where McCarthy had just finished his undergraduate studies and was now enrolled in a graduate mathematics program.

In the United States, machine intelligence had become a subject of substantial academic interest under the wide term of cybernetics by 1948, and many renowned cyberneticists, notably Princeton mathematician John von Neumann, were in attendance at the symposium.

McCarthy moved to Princeton's mathematics department a year later, when he discussed some early ideas inspired by the symposium with von Neumann.

McCarthy never published the work, despite von Neumann's urging, since he believed cybernetics could not solve his problems concerning human knowing.

McCarthy finished a PhD on partial differential equations at Princeton.

He stayed at Princeton as an instructor after graduating in 1951, and in the summer of 1952, he had the chance to work at Bell Labs with cyberneticist and inventor of information theory Claude Shannon, whom he persuaded to collaborate on an edited collection of writings on machine intelligence.

Automata Studies received contributions from a variety of fields, ranging from pure mathematics to neuroscience.

McCarthy, on the other hand, felt that the published studies did not devote enough attention to the important subject of how to develop intelligent machines.

McCarthy joined the mathematics department at Stanford in 1953, but was fired two years later, maybe because he spent too much time thinking about intelligent computers and not enough time working on his mathematical studies, he speculated.

In 1955, he accepted a position at Dartmouth, just as IBM was preparing to establish the New England Computation Center at MIT.

The New England Computation Center gave Dartmouth access to an IBM computer that was installed at MIT and made accessible to a group of New England colleges.

McCarthy met IBM researcher Nathaniel Rochester via the IBM initiative, and he recruited McCarthy to IBM in the summer of 1955 to work with his research group.

McCarthy persuaded Rochester of the need for more research on machine intelligence, and he submitted a proposal to the Rockefeller Foundation for a "Summer Research Project on Artificial Intelligence" with Rochester, Shannon, and Marvin Minsky, a graduate student at Princeton, which included the first known use of the phrase "artificial intelligence." Despite the fact that the Dartmouth Project is usually regarded as a watershed moment in the development of AI, the conference did not go as McCarthy had envisioned.

The Rockefeller Foundation supported the proposal at half the proposed budget since it was for such an unique field of research with a relatively young professor as author, and because Shannon's reputation carried substantial weight with the Foundation.

Furthermore, since the event took place over many weeks in the summer of 1955, only a handful of the guests were able to attend the whole period.

As a consequence, the Dartmouth conference was a fluid affair with an ever-changing and unpredictably diverse guest list.

Despite its chaotic implementation, the meeting was crucial in establishing AI as a distinct area of research.

McCarthy won a Sloan grant to spend a year at MIT, closer to IBM's New England Computation Center, while still at Dartmouth in 1957.

McCarthy was given a post in the Electrical Engineering department at MIT in 1958, which he accepted.

Later, he was joined by Minsky, who worked in the mathematics department.

McCarthy and Minsky suggested the construction of an official AI laboratory to Jerome Wiesner, head of MIT's Research Laboratory of Electronics, in 1958.

McCarthy and Minsky agreed on the condition that Wiesner let six freshly accepted graduate students into the laboratory, and the "artificial intelligence project" started teaching its first generation of students.

McCarthy released his first article on artificial intelligence in the same year.

In his book "Programs with Common Sense," he described a computer system he named the Advice Taker that would be capable of accepting and understanding instructions in ordinary natural language from nonexpert users.

McCarthy would later define Advice Taker as the start of a study program aimed at "formalizing common sense." McCarthy felt that everyday common sense notions, such as comprehending that if you don't know a phone number, you'll need to look it up before calling, might be written as mathematical equations and fed into a computer, enabling the machine to come to the same conclusions as humans.

Such formalization of common knowledge, McCarthy felt, was the key to artificial intelligence.

McCarthy's presentation, which was presented at the United Kingdom's National Physical Laboratory's "Symposium on Mechansation of Thought Processes," helped establish the symbolic program of AI research.

McCarthy's research was focused on AI by the late 1950s, although he was also involved in a range of other computing-related topics.

In 1957, he was assigned to a group of the Association for Computing Machinery charged with developing the ALGOL programming language, which would go on to become the de facto language for academic research for the next several decades.

He created the LISP programming language for AI research in 1958, and its successors are widely used in business and academia today.

McCarthy contributed to computer operating system research via the construction of time sharing systems, in addition to his work on programming languages.

Early computers were large and costly, and they could only be operated by one person at a time.

McCarthy identified the necessity for several users throughout a major institution, such as a university or hospital, to be able to use the organization's computer systems concurrently via computer terminals in their offices from his first interaction with computers in 1955 at IBM.

McCarthy pushed for study on similar systems at MIT, serving on a university committee that looked into the issue and ultimately assisting in the development of MIT's Compatible Time-Sharing System (CTSS).

Although McCarthy left MIT before the CTSS work was completed, his advocacy with J.C.R.

Licklider, future office head at the Advanced Research Projects Agency, the predecessor to DARPA, while a consultant at Bolt Beranek and Newman in Cambridge, was instrumental in helping MIT secure significant federal support for computing research.

McCarthy was recruited to join what would become the second department of computer science in the United States, after Purdue's, by Stanford Professor George Forsythe in 1962.

McCarthy insisted on going only as a full professor, which he believed would be too much for Forsythe to handle as a young researcher.

Forsythe was able to persuade Stanford to grant McCarthy a full chair, and he moved to Stanford in 1965 to establish the Stanford AI laboratory.

Until his retirement in 2000, McCarthy oversaw research at Stanford on AI topics such as robotics, expert systems, and chess.

McCarthy was up in a family where both parents were ardent members of the Communist Party, and he had a lifetime interest in Russian events.

He maintained numerous professional relationships with Soviet cybernetics and AI experts, traveling and lecturing there in the mid-1960s, and even arranged a chess match between a Stanford chess computer and a Russian equivalent in 1965, which the Russian program won.

He developed many foundational concepts in symbolic AI theory while at Stanford, such as circumscription, which expresses the idea that a computer must be allowed to make reasonable assumptions about problems presented to it; otherwise, even simple scenarios would have to be specified in such exacting logical detail that the task would be all but impossible.

McCarthy's accomplishments have been acknowledged with various prizes, including the 1971 Turing Award, the 1988 Kyoto Prize, admission into the National Academy of Sciences in 1989, the 1990 Presidential Medal of Science, and the 2003 Benjamin Franklin Medal.

McCarthy was a brilliant thinker who continuously imagined new technologies, such as a space elevator for economically transporting stuff into orbit and a system of carts strung from wires to better urban transportation.

In a 2008 interview, McCarthy was asked what he felt the most significant topics in computing now were, and he answered without hesitation, "Formalizing common sense," the same endeavor that had inspired him from the start.

~ Jai Krishna Ponnappan

Find Jai on Twitter | LinkedIn | Instagram

You may also want to read more about Artificial Intelligence here.

See also: 

Cybernetics and AI; Expert Systems; Symbolic Logic.

References & Further Reading:

Hayes, Patrick J., and Leora Morgenstern. 2007. “On John McCarthy’s 80th Birthday, in Honor of His Contributions.” AI Magazine 28, no. 4 (Winter): 93–102.

McCarthy, John. 1990. Formalizing Common Sense: Papers, edited by Vladimir Lifschitz. Norwood, NJ: Albex.

Morgenstern, Leora, and Sheila A. McIlraith. 2011. “John McCarthy’s Legacy.” Artificial Intelligence 175, no. 1 (January): 1–24.

Nilsson, Nils J. 2012. “John McCarthy: A Biographical Memoir.” Biographical Memoirs of the National Academy of Sciences. http://www.nasonline.org/publications/biographical-memoirs/memoir-pdfs/mccarthy-john.pdf.

Artificial Intelligence - What Were The Macy Conferences?

 

The Macy Conferences on Cybernetics, which ran from 1946 to 1960, aimed to provide the framework for developing multidisciplinary disciplines such as cybernetics, cognitive psychology, artificial life, and artificial intelligence.

Famous twentieth-century scholars, academics, and researchers took part in the Macy Conferences' freewheeling debates, including psychiatrist W.

Ross Ashby, anthropologist Gregory Bateson, ecologist G. Evelyn Hutchinson, psychologist Kurt Lewin, philosopher Donald Marquis, neurophysiologist Warren McCulloch, cultural anthropologist Margaret Mead, economist Oskar Morgenstern, statistician Leonard Savage, physicist Heinz von Foerster McCulloch, a neurophysiologist at the Massachusetts Institute of Technology's Research Laboratory for Electronics, and von Foerster, a professor of signal engineering at the University of Illinois at Urbana-Champaign and coeditor with Mead of the published Macy Conference proceedings, were the two main organizers of the conferences.

All meetings were sponsored by the Josiah Macy Jr. Foundation, a nonprofit organization.

The conferences were started by Macy administrators Frank Fremont-Smith and Lawrence K. Frank, who believed that they would spark multidisciplinary discussion.

The disciplinary isolation of medical research was a major worry for Fremont-Smith and Frank.

A Macy-sponsored symposium on Cerebral Inhibitions in 1942 preceded the Macy meetings, during which Harvard physiology professor Arturo Rosenblueth presented the first public discussion on cybernetics, titled "Behavior, Purpose, and Teleology." The 10 conferences conducted between 1946 and 1953 focused on biological and social systems' circular causation and feedback processes.

Between 1954 and 1960, five transdisciplinary Group Processes Conferences were held as a result of these sessions.

To foster direct conversation amongst participants, conference organizers avoided formal papers in favor of informal presentations.

The significance of control, communication, and feedback systems in the human nervous system was stressed in the early Macy Conferences.

The contrasts between analog and digital processing, switching circuit design and Boolean logic, game theory, servomechanisms, and communication theory were among the other subjects explored.

These concerns belong under the umbrella of "first-order cybernetics." Several biological issues were also discussed during the conferences, including adrenal cortex function, consciousness, aging, metabolism, nerve impulses, and homeostasis.

The sessions acted as a forum for discussing long-standing issues in what would eventually be referred to as artificial intelligence.

(At Dartmouth College in 1955, mathematician John McCarthy invented the phrase "artificial intelligence.") Gregory Bateson, for example, gave a lecture at the inaugural Macy Conference that differentiated between "learning" and "learning to learn" based on his anthropological research and encouraged listeners to consider how a computer might execute either job.

Attendees in the eighth conference discussed decision theory research, which was led by Leonard Savage.

Ross Ashby suggested the notion of chess-playing automatons at the ninth conference.

The usefulness of automated computers as logic models for human cognition was discussed more than any other issue during the Macy Conferences.

In 1964, the Macy Conferences gave rise to the American Society for Cybernetics, a professional organization.

The Macy Conferences' early arguments on feedback methods were applied to topics as varied as artillery control, project management, and marital therapy.

~ Jai Krishna Ponnappan

Find Jai on Twitter | LinkedIn | Instagram

You may also want to read more about Artificial Intelligence here.

See also: 

Cybernetics and AI; Dartmouth AI Conference.

References & Further Reading:

Dupuy, Jean-Pierre. 2000. The Mechanization of the Mind: On the Origins of Cognitive Science. Princeton, NJ: Princeton University Press.

Hayles, N. Katherine. 1999. How We Became Posthuman: Virtual Bodies in Cybernetics, Literature, and Informatics. Chicago: University of Chicago Press.

Heims, Steve J. 1988. “Optimism and Faith in Mechanism among Social Scientists at the Macy Conferences on Cybernetics, 1946–1953.” AI & Society 2: 69–78.

Heims, Steve J. 1991. The Cybernetics Group. Cambridge, MA: MIT Press.

Pias, Claus, ed. 2016. The Macy Conferences, 1946–1953: The Complete Transactions. Zürich, Switzerland: Diaphanes.

AI - Symbol Manipulation.

 

The broad information-processing skills of a digital stored program computer are referred to as symbol manipulation.

From the 1960s through the 1980s, seeing the computer as fundamentally a symbol manipulator became the norm, leading to the scientific study of symbolic artificial intelligence, now known as Good Old-Fashioned AI (GOFAI).

In the 1960s, the emergence of stored-program computers sparked a renewed interest in a computer's programming flexibility.

Symbol manipulation became a comprehensive theory of intelligent behavior as well as a research guideline for AI.

The Logic Theorist, created by Herbert Simon, Allen Newell, and Cliff Shaw in 1956, was one of the first computer programs to mimic intelligent symbol manipulation.

The Logic Theorist was able to prove theorems from Bertrand Russell's Principia Mathematica (1910–1913) and Alfred North Whitehead's Principia Mathematica (1910–1913).

It was presented at Dartmouth's Artificial Intelligence Summer Research Project in 1956. (the Dartmouth Conference).

John McCarthy, a Dartmouth mathematics professor who invented the phrase "artificial intelligence," convened this symposium.

The Dartmouth Conference might be dubbed the genesis of AI since it was there that the Logic Theorist first appeared, and many of the participants went on to become pioneering AI researchers.

The features of symbol manipulation, as a generic process that underpins all types of intelligent problem-solving behavior, were thoroughly explicated and provided a foundation for most of the early work in AI only in the early 1960s, when Simon and Newell had built their General Problem Solver (GPS).

In 1961, Simon and Newell took their knowledge of AI and their work on GPS to a wider audience.

"A computer is not a number-manipulating device; it is a symbol-manipulating device," they wrote in Science, "and the symbols it manipulates may represent numbers, letters, phrases, or even nonnumerical, nonverbal patterns" (Newell and Simon 1961, 2012).

Reading "symbols or patterns presented by appropriate input devices, storing symbols in memory, copying symbols from one memory location to another, erasing symbols, comparing symbols for identity, detecting specific differences between their patterns, and behaving in a manner conditional on the results of its processes," Simon and Newell continued (Newell and Simon 1961, 2012).

The growth of symbol manipulation in the 1960s was also influenced by breakthroughs in cognitive psychology and symbolic logic prior to WWII.

Starting in the 1930s, experimental psychologists like Edwin Boring at Harvard University began to advance their profession away from philosophical and behavioralist methods.

Boring challenged his colleagues to break the mind open and create testable explanations for diverse cognitive mental operations (an approach that was adopted by Kenneth Colby in his work on PARRY in the 1960s).

Simon and Newell also emphasized their debt to pre-World War II developments in formal logic and abstract mathematics in their historical addendum to Human Problem Solving—not because all thought is logical or follows the rules of deductive logic, but because formal logic treated symbols as tangible objects.

"The formalization of logic proved that symbols can be copied, compared, rearranged, and concatenated with just as much definiteness of procedure as [wooden] boards can be sawed, planed, measured, and glued [in a carpenter shop]," Simon and Newell noted (Newell and Simon 1973, 877).

~ Jai Krishna Ponnappan

Find Jai on Twitter | LinkedIn | Instagram

You may also want to read more about Artificial Intelligence here.

See also: 

Expert Systems; Newell, Allen; PARRY; Simon, Herbert A.

References & Further Reading:

Boring, Edwin G. 1946. “Mind and Mechanism.” American Journal of Psychology 59, no. 2 (April): 173–92.

Feigenbaum, Edward A., and Julian Feldman. 1963. Computers and Thought. New York: McGraw-Hill.

McCorduck, Pamela. 1979. Machines Who Think: A Personal Inquiry into the History and Prospects of Artificial Intelligence. San Francisco: W. H. Freeman and Company

Newell, Allen, and Herbert A. Simon. 1961. “Computer Simulation of Human Thinking.” Science 134, no. 3495 (December 22): 2011–17.

Newell, Allen, and Herbert A. Simon. 1972. Human Problem Solving. Englewood Cliffs, NJ: Prentice Hall.

Schank, Roger, and Kenneth Colby, eds. 1973. Computer Models of Thought and Language. San Francisco: W. H. Freeman and Company.

Artificial Intelligence - History And Timeline

 

1942

The Three Laws of Robotics by science fiction author Isaac Asimov occur in the short tale "Runaround."

1943

Emil Post, a mathematician, talks about "production systems," a notion he adopted for the 1957 General Problem Solver.

1943

"A Logical Calculus of the Ideas of Immanent in Nervous Activity," a study by Warren McCulloch and Walter Pitts on a computational theory of neural networks, is published.

1944

The Teleological Society was founded by John von Neumann, Norbert Wiener, Warren McCulloch, Walter Pitts, and Howard Aiken to explore, among other things, nervous system communication and control.

1945

In his book How to Solve It, George Polya emphasizes the importance of heuristic thinking in issue solving.

1946

In New York City, the first of eleven Macy Conferences on Cybernetics gets underway. "Feedback Mechanisms and Circular Causal Systems in Biological and Social Systems" is the focus of the inaugural conference.

1948

Norbert Wiener, a mathematician, publishes Cybernetics, or Control and Communication in the Animal and the Machine.

1949

In his book The Organization of Behavior, psychologist Donald Hebb provides a theory for brain adaptation in human education: "neurons that fire together connect together."

1949

Edmund Berkeley's book Giant Brains, or Machines That Think, is published.

1950

Alan Turing's "Computing Machinery and Intelligence" describes the Turing Test, which attributes intelligence to any computer capable of demonstrating intelligent behavior comparable to that of a person.

1950

Claude Shannon releases "Programming a Computer for Playing Chess," a groundbreaking technical study that shares search methods and strategies.

1951

Marvin Minsky, a math student, and Dean Edmonds, a physics student, create an electronic rat that can learn to navigate a labyrinth using Hebbian theory.

1951

John von Neumann, a mathematician, releases "General and Logical Theory of Automata," which reduces the human brain and central nervous system to a computer.

1951

For the University of Manchester's Ferranti Mark 1 computer, Christopher Strachey produces a checkers software and Dietrich Prinz creates a chess routine.

1952

Cyberneticist W. Edwards wrote Design for a Brain: The Origin of Adaptive Behavior, a book on the logical underpinnings of human brain function. Ross Ashby is a British actor.

1952

At Cornell University Medical College, physiologist James Hardy and physician Martin Lipkin begin developing a McBee punched card system for mechanical diagnosis of patients.

1954

Science-Fiction Thinking Machines: Robots, Androids, Computers, edited by Groff Conklin, is a theme-based anthology.

1954

The Georgetown-IBM project exemplifies the power of text machine translation.

1955

Under the direction of economist Herbert Simon and graduate student Allen Newell, artificial intelligence research began at Carnegie Tech (now Carnegie Mellon University).

1955

For Scientific American, mathematician John Kemeny wrote "Man as a Machine."

1955

In a Rockefeller Foundation proposal for a Dartmouth University meeting, mathematician John McCarthy coined the phrase "artificial intelligence."

1956

Allen Newell, Herbert Simon, and Cliff Shaw created Logic Theorist, an artificial intelligence computer software for proving theorems in Alfred North Whitehead and Bertrand Russell's Principia Mathematica.

1956

The "Constitutional Convention of AI," a Dartmouth Summer Research Project, brings together specialists in cybernetics, automata, information theory, operations research, and game theory.

1956

On television, electrical engineer Arthur Samuel shows off his checkers-playing AI software.

1957

Allen Newell and Herbert Simon created the General Problem Solver AI software.

1957

The Rockefeller Medical Electronics Center shows how an RCA Bizmac computer application might help doctors distinguish between blood disorders.

1958

The Computer and the Brain, an unfinished work by John von Neumann, is published.

1958

At the "Mechanisation of Thought Processes" symposium at the UK's Teddington National Physical Laboratory, Firmin Nash delivers the Group Symbol Associator its first public demonstration.

1958

For linear data categorization, Frank Rosenblatt develops the single layer perceptron, which includes a neural network and supervised learning algorithm.

1958

The high-level programming language LISP is specified by John McCarthy of the Massachusetts Institute of Technology (MIT) for AI research.

1959

"The Reasoning Foundations of Medical Diagnosis," written by physicist Robert Ledley and radiologist Lee Lusted, presents Bayesian inference and symbolic logic to medical difficulties.

1959

At MIT, John McCarthy and Marvin Minsky create the Artificial Intelligence Laboratory.

1960

James L. Adams, an engineering student, built the Stanford Cart, a remote control vehicle with a television camera.

1962

In his short novel "Without a Thought," science fiction and fantasy author Fred Saberhagen develops sentient killing robots known as Berserkers.

1963

John McCarthy developed the Stanford Artificial Intelligence Laboratory (SAIL).

1963

Under Project MAC, the Advanced Research Experiments Agency of the United States Department of Defense began financing artificial intelligence projects at MIT.

1964

Joseph Weizenbaum of MIT created ELIZA, the first software allowing natural language conversation with a computer (a "chatbot").

1965

I am a statistician from the United Kingdom. J. Good's "Speculations Concerning the First Ultraintelligent Machine," which predicts an impending intelligence explosion, is published.

1965

Hubert L. Dreyfus and Stuart E. Dreyfus, philosophers and mathematicians, publish "Alchemy and AI," a study critical of artificial intelligence.

1965

Joshua Lederberg and Edward Feigenbaum founded the Stanford Heuristic Programming Project, which aims to model scientific reasoning and create expert systems.

1965

Donald Michie is the head of Edinburgh University's Department of Machine Intelligence and Perception.

1965

Georg Nees organizes the first generative art exhibition, Computer Graphic, in Stuttgart, West Germany.

1965

With the expert system DENDRAL, computer scientist Edward Feigenbaum starts a ten-year endeavor to automate the chemical analysis of organic molecules.

1966

The Automatic Language Processing Advisory Committee (ALPAC) issues a cautious assessment on machine translation's present status.

1967

On a DEC PDP-6 at MIT, Richard Greenblatt finishes work on Mac Hack, a computer that plays competitive tournament chess.

1967

Waseda University's Ichiro Kato begins work on the WABOT project, which culminates in the unveiling of a full-scale humanoid intelligent robot five years later.

1968

Stanley Kubrick's adaptation of Arthur C. Clarke's science fiction novel 2001: A Space Odyssey, about the artificially intelligent computer HAL 9000, is one of the most influential and highly praised films of all time.

1968

At MIT, Terry Winograd starts work on SHRDLU, a natural language understanding program.

1969

Washington, DC hosts the First International Joint Conference on Artificial Intelligence (IJCAI).

1972

Artist Harold Cohen develops AARON, an artificial intelligence computer that generates paintings.

1972

Ken Colby describes his efforts using the software program PARRY to simulate paranoia.

1972

In What Computers Can't Do, Hubert Dreyfus offers his criticism of artificial intelligence's intellectual basis.

1972

Ted Shortliffe, a doctorate student at Stanford University, has started work on the MYCIN expert system, which is aimed to identify bacterial illnesses and provide treatment alternatives.

1972

The UK Science Research Council releases the Lighthill Report on Artificial Intelligence, which highlights AI technological shortcomings and the challenges of combinatorial explosion.

1972

The Assault on Privacy: Computers, Data Banks, and Dossiers, by Arthur Miller, is an early study on the societal implications of computers.

1972

INTERNIST-I, an internal medicine expert system, is being developed by University of Pittsburgh physician Jack Myers, medical student Randolph Miller, and computer scientist Harry Pople.

1974

Paul Werbos, a social scientist, has completed his dissertation on a backpropagation algorithm that is currently extensively used in artificial neural network training for supervised learning applications.

1974

The memo discusses the notion of a frame, a "remembered framework" that fits reality by "changing detail as appropriate." Marvin Minsky distributes MIT AI Lab document 306 on "A Framework for Representing Knowledge."

1975

The phrase "genetic algorithm" is used by John Holland to explain evolutionary strategies in natural and artificial systems.

1976

In Computer Power and Human Reason, computer scientist Joseph Weizenbaum expresses his mixed feelings on artificial intelligence research.

1978

At Rutgers University, EXPERT, a generic knowledge representation technique for constructing expert systems, becomes live.

1978

Joshua Lederberg, Douglas Brutlag, Edward Feigenbaum, and Bruce Buchanan started the MOLGEN project at Stanford to solve DNA structures generated from segmentation data in molecular genetics research.

1979

Raj Reddy, a computer scientist at Carnegie Mellon University, founded the Robotics Institute.

1979

While working with a robot, the first human is slain.

1979

Hans Moravec rebuilds and equips the Stanford Cart with a stereoscopic vision system after it has evolved into an autonomous rover over almost two decades.

1980

The American Association of Artificial Intelligence (AAAI) holds its first national conference at Stanford University.

1980

In his Chinese Room argument, philosopher John Searle claims that a computer's modeling of action does not establish comprehension, intentionality, or awareness.

1982

Release of Blade Runner, a science fiction picture based on Philip K. Dick's tale Do Androids Dream of Electric Sheep? (1968).

1982

The associative brain network, initially developed by William Little in 1974, is popularized by physicist John Hopfield.

1984

In Fortune Magazine, Tom Alexander writes "Why Computers Can't Outthink the Experts."

1984

At the Microelectronics and Computer Consortium (MCC) in Austin, TX, computer scientist Doug Lenat launches the Cyc project, which aims to create a vast commonsense knowledge base and artificial intelligence architecture.

1984

Orion Pictures releases the first Terminator picture, which features robotic assassins from the future and an AI known as Skynet.

1986

Honda establishes a research facility to build humanoid robots that can cohabit and interact with humans.

1986

Rodney Brooks, an MIT roboticist, describes the subsumption architecture for behavior-based robots.

1986

The Society of Mind is published by Marvin Minsky, who depicts the brain as a collection of collaborating agents.

1989

The MIT Artificial Intelligence Lab's Rodney Brooks and Anita Flynn publish "Fast, Cheap, and Out of Control: A Robot Invasion of the Solar System," a paper discussing the possibility of sending small robots on interplanetary exploration missions.

1993

The Cog interactive robot project is launched at MIT by Rodney Brooks, Lynn Andrea Stein, Cynthia Breazeal, and others.

1995

The phrase "generative music" was used by musician Brian Eno to describe systems that create ever-changing music by modifying parameters over time.

1995

The MQ-1 Predator unmanned aerial aircraft from General Atomics has entered US military and reconnaissance duty.

1997

Under normal tournament settings, IBM's Deep Blue supercomputer overcomes reigning chess champion Garry Kasparov.

1997

In Nagoya, Japan, the inaugural RoboCup, an international tournament featuring over forty teams of robot soccer players, takes place.

1997

NaturallySpeaking is Dragon Systems' first commercial voice recognition software product.

1999

Sony introduces AIBO, a robotic dog, to the general public.

2000

The Advanced Step in Innovative Mobility humanoid robot, ASIMO, is unveiled by Honda.

2001

At Super Bowl XXXV, Visage Corporation unveils the FaceFINDER automatic face-recognition technology.

2002

The Roomba autonomous household vacuum cleaner is released by the iRobot Corporation, which was created by Rodney Brooks, Colin Angle, and Helen Greiner.

2004

In the Mojave Desert near Primm, NV, DARPA hosts its inaugural autonomous vehicle Grand Challenge, but none of the cars complete the 150-mile route.

2005

Under the direction of neurologist Henry Markram, the Swiss Blue Brain Project is formed to imitate the human brain.

2006

Netflix is awarding a $1 million prize to the first programming team to create the greatest recommender system based on prior user ratings.

2007

DARPA has announced the commencement of the Urban Challenge, an autonomous car competition that will test merging, passing, parking, and navigating traffic and junctions.

2009

Under the leadership of Sebastian Thrun, Google launches its self-driving car project (now known as Waymo) in the San Francisco Bay Area.

2009

Fei-Fei Li of Stanford University describes her work on ImageNet, a library of millions of hand-annotated photographs used to teach AIs to recognize the presence or absence of items visually.

2010

Human manipulation of automated trading algorithms causes a "flash collapse" in the US stock market.

2011

Demis Hassabis, Shane Legg, and Mustafa Suleyman developed DeepMind in the United Kingdom to educate AIs how to play and succeed at classic video games.

2011

Watson, IBM's natural language computer system, has beaten Jeopardy! Ken Jennings and Brad Rutter are the champions.

2011

The iPhone 4S comes with Apple's mobile suggestion assistant Siri.

2011

Andrew Ng, a computer scientist, and Google colleagues Jeff Dean and Greg Corrado have launched an informal Google Brain deep learning research cooperation.

2013

The European Union's Human Brain Project aims to better understand how the human brain functions and to duplicate its computing capabilities.

2013

Stop Killer Robots is a campaign launched by Human Rights Watch.

2013

Spike Jonze's science fiction drama Her has been released. A guy and his AI mobile suggestion assistant Samantha fall in love in the film.

2014

Ian Goodfellow and colleagues at the University of Montreal create Generative Adversarial Networks (GANs) for use in deep neural networks, which are beneficial in making realistic fake human photos.

2014

Eugene Goostman, a chatbot that plays a thirteen-year-old kid, is said to have passed a Turing-like test.

2014

According to physicist Stephen Hawking, the development of AI might lead to humanity's extinction.

2015

DeepFace is a deep learning face recognition system that Facebook has released on its social media platform.

2016

In a five-game battle, DeepMind's AlphaGo software beats Lee Sedol, a 9th dan Go player.

2016

Tay, a Microsoft AI chatbot, has been put on Twitter, where users may teach it to send abusive and inappropriate posts.

2017

The Asilomar Meeting on Beneficial AI is hosted by the Future of Life Institute.

2017

Anthony Levandowski, an AI self-driving start-up engineer, formed the Way of the Future church with the goal of creating a superintelligent robot god.

2018

Google has announced Duplex, an AI program that uses natural language to schedule appointments over the phone.

2018

The General Data Protection Regulation (GDPR) and "Ethics Guidelines for Trustworthy AI" are published by the European Union.

2019

A lung cancer screening AI developed by Google AI and Northwestern Medicine in Chicago, IL, surpasses specialized radiologists.

2019

Elon Musk cofounded OpenAI, which generates realistic tales and journalism via artificial intelligence text generation. Because of its ability to spread false news, it was previously judged "too risky" to utilize.

2020

TensorFlow Quantum, an open-source framework for quantum machine learning, was announced by Google AI in conjunction with the University of Waterloo, the "moonshot faculty" X, and Volkswagen.

~ Jai Krishna Ponnappan

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