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AI marks the beginning of the Age of Thinking Machines


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.

What is artificial intelligence? (Or, can machines think?)


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.

Value Alignment, Fair Play, and the Rights of Service Robots Artificial Intelligence

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.

Is It Enough to Get the Behaviour Right?

AAAI Conferences

This paper deals with the relationship between intelligent behaviour, on the   one hand, and the mental qualities needed to produce it, on the other.  We   consider two well-known opposing positions on this issue: one due to Alan   Turing and one due to John Searle (via the Chinese Room).  In particular, we   argue against Searle, showing that his answer to the so-called System Reply   does not work.  The argument takes a novel form:   we shift the debate to a different and more plausible room where the   required conversational behaviour is much easier to characterize and to   analyze.  Despite being much simpler than the Chinese Room, we show that    the  behaviour there is still complex enough that it cannot be produced without   appropriate mental qualities.

A Brief History of Artificial Intelligence


Inspite of all the current hype, AI is not a new field of study, but it has its ground in the fifties. If we exclude the pure philosophical reasoning path that goes from the Ancient Greek to Hobbes, Leibniz, and Pascal, AI as we know it has been officially started in 1956 at Dartmouth College, where the most eminent experts gathered to brainstorm on intelligence simulation. This happened only a few years after Asimov set his own three laws of robotics, but more relevantly after the famous paper published by Turing (1950), where he proposes for the first time the idea of a thinking machine and the more popular Turing test to assess whether such machine shows, in fact, any intelligence. As soon as the research group at Dartmouth publicly released the contents and ideas arisen from that summer meeting, a flow of government funding was reserved for the study of creating a nonbiological intelligence. Atthat time, AI seemed to be easily reachable, but it turned out that was not the case.