The history of artificial intelligence (AI) began in antiquity, with myths, stories and rumors of artificial beings endowed with intelligence or consciousness by master craftsmen; as Pamela McCorduck writes, AI began with "an ancient wish to forge the gods." The seeds of modern AI were planted by classical philosophers who attempted to describe the process of human thinking as the mechanical manipulation of symbols. This work culminated in the invention of the programmable digital computer in the 1940s, a machine based on the abstract essence of mathematical reasoning. This device and the ideas behind it inspired a handful of scientists to begin seriously discussing the possibility of building an electronic brain. The Turing test was proposed by British mathematician Alan Turing in his 1950 paper Computing Machinery and Intelligence, which opens with the words: "I propose to consider the question, 'Can machines think?'" The term'Artificial Intelligence' was created at a conference held at Dartmouth College in 1956. Allen Newell, J. C. Shaw, and Herbert A. Simon pioneered the newly created artificial intelligence field with the Logic Theory Machine (1956), and the General Problem Solver in 1957. In 1958, John McCarthy and Marvin Minsky started the MIT Artificial Intelligence lab with 50,000. John McCarthy also created LISP in the summer of 1958, a programming language still important in artificial intelligence research. In 1973, in response to the criticism of James Lighthill and ongoing pressure from congress, the U.S. and British Governments stopped funding undirected research into artificial intelligence. Seven years later, a visionary initiative by the Japanese Government inspired governments and industry to provide AI with billions of dollars, but by the late 80s the investors became disillusioned and withdrew funding again. McCorduck (2004) writes "artificial intelligence in one form or another is an idea that has pervaded Western intellectual history, a dream in urgent need of being realized," expressed in humanity's myths, legends, stories, speculation and clockwork automatons. Mechanical men and artificial beings appear in Greek myths, such as the golden robots of Hephaestus and Pygmalion's Galatea. In the Middle Ages, there were rumors of secret mystical or alchemical means of placing mind into matter, such as J?bir ibn Hayy?n's Takwin, Paracelsus' homunculus and Rabbi Judah Loew's Golem. By the 19th century, ideas about artificial men and thinking machines were developed in fiction, as in Mary Shelley's Frankenstein or Karel?apek's
Every day brings considerable AI news, from breakthrough capabilities to dire warnings. A quick read of recent headlines shows both: an AI system that claims to predict dengue fever outbreaks up to three months in advance, and an opinion piece from Henry Kissinger that AI will end the Age of Enlightenment. Then there's the father of AI who doesn't believe there's anything to worry about. Meanwhile, Robert Downey, Jr. is in the midst of developing an eight-part documentary series about AI to air on Netflix. AI is more than just "hot," it's everywhere.
Here are the slides from my York Festival of Ideas keynote yesterday, which introduced the festival focus day Artificial Intelligence: Promises and Perils. I start the keynote with Alan Turing's famous question: Can a Machine Think? and explain that thinking is not just the conscious reflection of Rodin's Thinker but also the largely unconscious thinking required to make a pot of tea. I note that at the dawn of AI 60 years ago we believed the former kind of thinking would be really difficult to emulate artificially and the latter easy. In fact it has turned out to be the other way round: we've had computers that can expertly play chess for 20 years, but we can't yet build a robot that could go into your kitchen and make you a cup of tea. In slides 5 and 6 I suggest that we all assume a cat is smarter than a crocodile, which is smarter than a cockroach, on a linear scale of intelligence from not very intelligent to human intelligence.
The vast increase in speed, memory capacity, and communications ability allows today's computers to do things that were unthinkable when I started programming six decades ago. Then, computers were primarily used for numerical calculations; today, they process text, images, and sound recordings. Then, it was an accomplishment to write a program that played chess badly but correctly. Today's computers have the power to compete with the best human players. The incredible capacity of today's computing systems allows some purveyors to describe them as having "artificial intelligence" (AI). They claim that AI is used in washing machines, the "personal assistants" in our mobile devices, self-driving cars, and the giant computers that beat human champions at complex games. Remarkably, those who use the term "artificial intelligence" have not defined that term. I first heard the term more than 50 years ago and have yet to hear a scientific definition. Even now, some AI experts say that defining AI is a difficult (and important) question--one that they are working on. "Artificial intelligence" remains a buzzword, a word that many think they understand but nobody can define. Application of AI methods can lead to devices and systems that are untrustworthy and sometimes dangerous.
Ethics and safety research in artificial intelligence is increasingly framed in terms of "alignment" with human values and interests. I argue that Turing's call for "fair play for machines" is an early and often overlooked contribution to the alignment literature. Turing's appeal to fair play suggests a need to correct human behavior to accommodate our machines, a surprising inversion of how value alignment is treated today. Reflections on "fair play" motivate a novel interpretation of Turing's notorious "imitation game" as a condition not of intelligence but instead of value alignment: a machine demonstrates a minimal degree of alignment (with the norms of conversation, for instance) when it can go undetected when interrogated by a human. I carefully distinguish this interpretation from the Moral Turing Test, which is not motivated by a principle of fair play, but instead depends on imitation of human moral behavior. Finally, I consider how the framework of fair play can be used to situate the debate over robot rights within the alignment literature. I argue that extending rights to service robots operating in public spaces is "fair" in precisely the sense that it encourages an alignment of interests between humans and machines.