By Rodney Brooks (MIT),
THE EARLY DAYS
It is generally agreed that John McCarthy coined the phrase “artificial intelligence” in the written proposal2 for a 1956 Dartmouth workshop, dated August 31st, 1955. It is authored by, in listed order, John McCarthy of Dartmouth, Marvin Minsky of Harvard, Nathaniel Rochester of IBM and Claude Shannon of Bell Laboratories. Later all but Rochester would serve on the faculty at MIT, although by early in the sixties McCarthy had left to join Stanford University. The nineteen page proposal has a title page and an introductory six pages (1 through 5a), followed by individually authored sections on proposed research by the four authors. It is presumed that McCarthy wrote those first six pages which include a budget to be provided by the Rockefeller Foundation to cover 10 researchers.
The title page says A PROPOSAL FOR THE DARTMOUTH SUMMER RESEARCH PROJECT ON ARTIFICIAL INTELLIGENCE. The first paragraph includes a sentence referencing “intelligence”:
The study is to proceed on the basis of the conjecture that every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it.
And then the first sentence of the second paragraph starts out:
The following are some aspects of the artificial intelligence problem:
That’s it! No description of what human intelligence is, no argument about whether or not machines can do it (i.e., “do intelligence”), and no fanfare on the introduction of the term “artificial intelligence” (all lower case).
In the linked file above there are an additional four pages dated March 6th, 1956, by Allen Newell and Herb Simon, at that time at the RAND Corporation and Carnegie Institute of Technology respectively (later both were giants at Carnegie Mellon University), on their proposed research contribution. They say that they are engaged in a series of forays into the area of complex information processing, and that a “large part of this activity comes under the heading of artificial intelligence”. It seems that the phrase “artificial intelligence” was easily and quickly adopted without any formal definition of what it might be.
In McCarthy’s introduction, and in the outlines of what the six named participants intend to research there is no lack of ambition.
The speeds and memory capacities of present computers may be insufficient to simulate many of the higher functions of the human brain, but the major obstacle is not lack of machine capacity, but our inability to write programs taking full advantage of what we have.
Some of the AI topics that McCarthy outlines in the introduction are how to get a computer to use human language, how to arrange “neuron nets” (they had been invented in 1943–a little while before today’s technology elite first heard about them and started getting over-excited) so that they can form concepts, how a machine can improve itself (i.e., learn or evolve), how machines could form abstractions from using its sensors to observe the world, and how to make computers think creatively. These topics are expanded upon in the individual work proposals by Shannon, Minsky, Rochester, and McCarthy. The addendum from Newell and Simon adds to the mix getting machines to play chess (including through learning), and prove mathematical theorems, along with developing theories on how machines might learn, and how they might solve problems similar to problems that humans can solve.
No lack of ambition! And recall that at this time there were only a handful of digital computers in the world, and none of them had more than at most a few tens of kilobytes of memory for running programs and data, and only punched cards or paper tape for long term storage.
McCarthy was certainly not the first person to talk about machines and “intelligence”, and in fact Alan Turing had written and published about it before this, but without the moniker of “artificial intelligence”. His best known foray is Computing Machinery and Intelligence3 which was published in October 1950. This is the paper where he introduces the “Imitation Game”, which has come to be called the “Turing Test”, where a person is to decide whether the entity they are conversing with via a 1950 version of instant messaging is a person or a computer. Turing estimates that in the year 2000 a computer with 128MB of memory (he states it as binary digits) will have a 70% chance of fooling a person.
Although the title of the paper has the word “Intelligence” in it, there is only one place where that word is used in the body of the paper (whereas “machine” appears at least 207 times), and that is to refer to the intelligence of a human who is trying to build a machine that can imitate an adult human. His aim however is clear. He believes that it will be possible to make a machine that can think as well as a human, and by the year 2000. He even estimates how many programmers will be needed (sixty is his answer, working for fifty years, so only 3,000 programmer years–a tiny number by the standards of many software systems today).
In a slightly earlier 1948 paper titled Intelligent Machinery but not published4 until 1970, long after his death, Turing outlined the nature of “discrete controlling machines”, what we would today call “computers”, as he had essentially invented digital computers in a paper he had written in 1937. He then turns to making a a machine that fully imitates a person, even as he reasons, the brain part might be too big to be contained within the locomoting sensing part of the machine, and instead must operate it remotely. He points out that the sensors and motor systems of the day might not be up to it, so concludes that to begin with the parts of intelligence that may be best to investigate are games and cryptography, and to a less extent translation of languages and mathematics.
Again, no lack of ambition, but a bowing to the technological realities of the day.
When AI got started the clear inspiration was human level performance and human level intelligence. I think that goal has been what attracted most researchers into the field for the first sixty years. The fact that we do not have anything close to succeeding at those aspirations says not that researchers have not worked hard or have not been brilliant. It says that it is a very hard goal.
I wrote a (long) paper Intelligence without Reason5 about the pre-history and early days of Artificial Intelligence in 1991, twenty seven years ago, and thirty five years into the endeavor. My current blog posts are trying to fill in details and to provide an update for a new generation to understand just what a long term project this is. To many it all seems so shiny and exciting and new. Of those, it is exciting only.