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Historical and contemporary papers on the philosophical issues raised by the Turing Test as a criterion for intelligence.The Turing Test is part of the vocabulary of popular culture-it has appeared in works ranging from the Broadway play "Breaking the Code" to the comic strip "Robotman." The writings collected by Stuart Shieber for this book examine the profound philosophical issues surrounding the Turing Test as a criterion for intelligence. Alan Turing's idea, originally expressed in a 1950 paper titled "Computing Machinery and Intelligence" and published in the journal Mind, proposed an "indistinguishability test" that compared artifact and person. Following Descartes's dictum that it is the ability to speak that distinguishes human from beast, Turing proposed to test whether machine and person were indistinguishable in regard to verbal ability. He was not, as is often assumed, answering the question "Can machines think?" but proposing a more concrete way to ask it. Turing's proposed thought experiment encapsulates the issues that the writings in The Turing Test define and discuss. The first section of the book contains writings by philosophical precursors, including Descartes, who first proposed the idea of indistinguishablity tests. The second section contains all of Turing's writings on the Turing Test, including not only the Mind paper but also less familiar ephemeral material. The final section opens with responses to Turing's paper published in Mind soon after it first appeared. The bulk of this section, however, consists of papers from a broad spectrum of scholars in the field that directly address the issue of the Turing Test as a test for intelligence.ContributorsJohn R. Searle, Ned Block, Daniel C. Dennett, and Noam Chomsky (in a previously unpublished paper). Each chapter is introduced by background material that can also be read as a self-contained essay on the Turing Test

In 1950 Alan Turing (1912-1954) published his famous article, "Computing Machinery and Intelligence" in the journal Mind. This article is arguably the most influential and widely read article in the philosophy of artificial intelligence. Indeed, most of the debate in the philosophy of artificial intelligence over the last fifty years concerns issues that were raised and discussed by Turing. Turing's genius was not only in developing the theory of computability but also in understanding the impact, both practical and philosophical, that computing machinery would have. Turing believed that computers, if properly designed and educated, could exhibit intelligent behavior, even behavior that would be indistinguishable from human intelligent behavior. His vision of the possibility of machine intelligence has been highly inspiring and extremely controversial. In this classic article Turing presented his well known imitation game and predicted that about the year 2000 "an average interrogator will not have more than 70 per cent chance of making the right identification after five minutes of questioning" in the imitation game. Based on the results of the Loebner 2000 contest and the accomplishments in the field of AI, as impressive as they are, Turing's prediction remains unfulfilled.

In 1950 Alan Turing (1912-1954) published his famous article, "Computing Machinery and Intelligence" in the journal Mind. This article is arguably the most influential and widely read article in the philosophy of artificial intelligence. Indeed, most of the debate in the philosophy of artificial intelligence over the last fifty years concerns issues that were raised and discussed by Turing. Turing's genius was not only in developing the theory of computability but also in understanding the impact, both practical and philosophical, that computing machinery would have. Turing believed that computers, if properly designed and educated, could exhibit intelligent behavior, even behavior that would be indistinguishable from human intelligent behavior. His vision of the possibility of machine intelligence has been highly inspiring and extremely controversial. In this classic article Turing presented his well known imitation game and predicted that about the year 2000 "an average interrogator will not have more than 70 per cent chance of making the right identification after five minutes of questioning" in the imitation game. Based on the results of the Loebner 2000 contest and the accomplishments in the field of AI, as impressive as they are, Turing's prediction remains unfulfilled.

Riga is sixteen, bored, angry, frustrated, unpredictable and way out of control. An ordinary teenager, in other words, but one who's desperately trying to make sense of an extraordinary world. Turns out that climate science ended up getting rid of the climate altogether, and the survivors live in artificial domes from which their only escape are the virtual worlds of the Second Skin. Unless you're a Mariner like Colt Covance, violinist, martial arts expert and genius in Artificial Intelligence, and your job is to help salvage what's left of civilisation after the Flood. It's the world post 2012, it's The Hunger Games without the rules, it's Twilight without the vampires, Donnie Darko without the rabbit, Avatar without the Smurfs, Xbox with electrifying extras, as Riga and Colt pursue the separate searches that will lead them to the edge of the horrifying mystery only the Turing Test can solve. Because there's only one way to tell if he's human...

Set in 2105, The Turing Test is a sci-fi thriller that blends sharp, sarcastic dialogue with a compelling espionage narrative. Motorcycles fly here, corporations battle hackers, bots are everywhere, and people can communicate without speaking.A global tech corporation faces a series of crises that could lead to its rapid downfall. CEO Rick Archee no longer trusts his bots or his people. He arranges a secret meeting aboard his private plane, where he plans to test his board of directors. But things go wrong-at 40,000 feet, a hacked pilot bot can be a serious problem. Unfortunately, this is only one of the challenges, and it's far from the main one... Outside the cabin, things spiral from bad to worse.Overnight, Rick goes from a powerful executive to a fugitive, pursued by mysterious assailants. With no one left to trust, he must seek help from his former enemies-the anarchic hackers of the futures movement. Meanwhile, a mysterious virus, based on quantum entanglement, silently infiltrates systems and takes control of devices, bots, and computers. A massive data leak threatens to unravel everything Rick has built. Drawn into a web of betrayal and espionage, he faces relentless pressure from fellow executive Ava Canberry, who is advancing her own agenda."Bots, you'll never go beyond the program," says a character in the book.Really? Think again... humans.The events of this science fiction series take readers to New York, California, Central Asia, India, and Australia.Get more at: www.2105change.com

This book departs from existing accounts of Alan Turing's imitation game and test by placing Turing's proposal in its historical, social, and cultural context.It reconstructs a controversy in England, 1946–1952, over the intellectual capabilities of digital computers, which led Turing to propose his test. It argues that the Turing test is best understood not as a practical experiment, but as a thought experiment in the modern scientific tradition of Galileo Galilei. The logic of the Turing test argument is reconstructed from the rhetoric of Turing’s irony and wit. Turing believed that learning machines should be understood as a new kind of species, and their thinking as different from human thinking and yet capable of imitating it. He thought that the possibilities of the machines he envisioned were not utopian dreams. And yet he hoped that they would rival and surpass chauvinists and intellectuals who sacrifice independent thinking to maintain their power. These would be transformed into ordinary people, as work once considered 'intellectual' would be transformed into non-intellectual, 'mechanical' work.The Turing Test Argument will appeal to scholars and students in the sciences and humanities and all those interested in Turing's vision of the future of intelligent machines in society and nature.

This book departs from existing accounts of Alan Turing's imitation game and test by placing Turing's proposal in its historical, social, and cultural context.It reconstructs a controversy in England, 1946–1952, over the intellectual capabilities of digital computers, which led Turing to propose his test. It argues that the Turing test is best understood not as a practical experiment, but as a thought experiment in the modern scientific tradition of Galileo Galilei. The logic of the Turing test argument is reconstructed from the rhetoric of Turing’s irony and wit. Turing believed that learning machines should be understood as a new kind of species, and their thinking as different from human thinking and yet capable of imitating it. He thought that the possibilities of the machines he envisioned were not utopian dreams. And yet he hoped that they would rival and surpass chauvinists and intellectuals who sacrifice independent thinking to maintain their power. These would be transformed into ordinary people, as work once considered 'intellectual' would be transformed into non-intellectual, 'mechanical' work.The Turing Test Argument will appeal to scholars and students in the sciences and humanities and all those interested in Turing's vision of the future of intelligent machines in society and nature.

Parsing the Turing Test is a landmark exploration of both the philosophical and methodological issues surrounding the search for true artificial intelligence. Will computers and robots ever think and communicate the way humans do? When a computer crosses the threshold into self-consciousness, will it immediately jump into the Internet and create a World Mind? Will intelligent computers someday recognize the rather doubtful intelligence of human beings? Distinguished psychologists, computer scientists, philosophers, and programmers from around the world debate these weighty issues – and, in effect, the future of the human race – in this important volume.

Parsing the Turing Test is a landmark exploration of both the philosophical and methodological issues surrounding the search for true artificial intelligence. Will computers and robots ever think and communicate the way humans do? When a computer crosses the threshold into self-consciousness, will it immediately jump into the Internet and create a World Mind? Will intelligent computers someday recognize the rather doubtful intelligence of human beings? Distinguished psychologists, computer scientists, philosophers, and programmers from around the world debate these weighty issues – and, in effect, the future of the human race – in this important volume.

What artificial intelligence can tell us about the mind and intelligent behavior.What can artificial intelligence teach us about the mind? If AI's underlying concept is that thinking is a computational process, then how can computation illuminate thinking? It's a timely question. AI is all the rage, and the buzziest AI buzz surrounds adaptive machine learning: computer systems that learn intelligent behavior from massive amounts of data. This is what powers a driverless car, for example. In this book, Hector Levesque shifts the conversation to "good old fashioned artificial intelligence," which is based not on heaps of data but on understanding commonsense intelligence. This kind of artificial intelligence is equipped to handle situations that depart from previous patterns-as we do in real life, when, for example, we encounter a washed-out bridge or when the barista informs us there's no more soy milk. Levesque considers the role of language in learning. He argues that a computer program that passes the famous Turing Test could be a mindless zombie, and he proposes another way to test for intelligence-the Winograd Schema Test, developed by Levesque and his colleagues. "If our goal is to understand intelligent behavior, we had better understand the difference between making it and faking it," he observes. He identifies a possible mechanism behind common sense and the capacity to call on background knowledge: the ability to represent objects of thought symbolically. As AI migrates more and more into everyday life, we should worry if systems without common sense are making decisions where common sense is needed.