CHAPTER SEVEN: DOES ARTIFICIAL INTELLIGENCE EXIST?
SUMMER 1956
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“Thinking Machines!” “Cybernetics!” “Automata Theory!” “Computer Information Processing!” These words flew around the staid conference room, slung between accomplished aca-demics from prestigious universities and representatives from corporate research laboratories adjourned at Dartmouth College in New Hampshire. John McCarthy, a math professor at Dartmouth, who organized the meeting, first flung out the term “artificial intelligence.” McCarthy’s proposal for what he thought would be a summer project is a striking document that helps us understand the historical roots of what has become the wide field of “artificial intelligence.” The proposal was sent to fifty potential attendees, all involved in some way in the burgeoning field of computers. The goals are clearly stated by McCarthy:
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McCarthy was nothing if not ambitious. Nearly seven decades later, the now-established field of artificial intelligence has not achieved what he thought could be done in a summer. The field still struggles to describe both human and machine intelligence, and how to simulate exceptional human cognitive abilities such as language, problem solving, reasoning, ethics, and empathy.
Artificial intelligence (AI) seeks to simulate higher func-tions of the human brain. However, the extent and depth of AI programming ballooned far beyond McCarthy’s original conception. Projects like AlphaZero and AlphaGo, launched in Google’s DeepMind laboratory during the 2010s, yielded programs that can beat world champions at complex games like chess and Go. These projects, accomplished in just a few years each, exemplify the frantic competition and enormous expenditures put into use cases of AI: Google spent at least $35 million on one forty- day experiment in this time period, according to the Wikipedia page for AlphaGo. And these are just one-off use cases. Today, there is no area that hasn’t been invaded by AI—it is a revolution within a revolution. Corporate, social media, and academic empires are built on this technology. AI is an academic discipline of its own, an integral part of most businesses and the driving force behind all our digital devices. With the recent development of cryptocurrencies, even our money is generated by and distributed via algorithms.
Although artificial intelligence has become the commonly accepted moniker for myriad computer programs and functionalities, the definition of artificial intelligence remains hotly debated. I offer arguments why I view the term “artificial intelligence” as an oxymoron.
​We propose that a 2 month, 10 man [sic] study of artificial intelligence be carried out during the summer of 1956 at Dartmouth College in Hanover, New Hampshire. 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. An attempt will be made to find how to make machines use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves. We think that a significant advance can be made in one or more of these problems if a carefully selected group of
scientists work on it together for a summer.