Computing Machinery and Intelligence

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The Myth of Artificial Intelligence: Why Computers Can't Think the Way We Do by Erik J. Larson

AI winter, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, Alignment Problem, AlphaGo, Amazon Mechanical Turk, artificial general intelligence, autonomous vehicles, Big Tech, Black Swan, Bletchley Park, Boeing 737 MAX, business intelligence, Charles Babbage, Claude Shannon: information theory, Computing Machinery and Intelligence, conceptual framework, correlation does not imply causation, data science, deep learning, DeepMind, driverless car, Elon Musk, Ernest Rutherford, Filter Bubble, Geoffrey Hinton, Georg Cantor, Higgs boson, hive mind, ImageNet competition, information retrieval, invention of the printing press, invention of the wheel, Isaac Newton, Jaron Lanier, Jeff Hawkins, John von Neumann, Kevin Kelly, Large Hadron Collider, Law of Accelerating Returns, Lewis Mumford, Loebner Prize, machine readable, machine translation, Nate Silver, natural language processing, Nick Bostrom, Norbert Wiener, PageRank, PalmPilot, paperclip maximiser, pattern recognition, Peter Thiel, public intellectual, Ray Kurzweil, retrograde motion, self-driving car, semantic web, Silicon Valley, social intelligence, speech recognition, statistical model, Stephen Hawking, superintelligent machines, tacit knowledge, technological singularity, TED Talk, The Coming Technological Singularity, the long tail, the scientific method, The Signal and the Noise by Nate Silver, The Wisdom of Crowds, theory of mind, Turing machine, Turing test, Vernor Vinge, Watson beat the top human players on Jeopardy!, Yochai Benkler

Since we have no good scientific reason to believe the myth is true, and e­ very reason to reject it for the purpose of our own ­f uture flourishing, we need to radically rethink the discussion about AI. Par t I T H E SI M PLI F I ED WOR L D Chapter 1 • • • T H E I N T EL LIGENCE ER ROR The story of artificial intelligence starts with the ideas of someone who had im­mense ­human intelligence: the computer pioneer Alan Turing. In 1950 Turing published a provocative paper, “Computing Machinery and Intelligence,” about the possibility of intelligent machines.1 The paper was bold, coming at a time when computers ­were new and unimpressive by ­today’s standards. Slow, heavy pieces of hardware sped up scientific calculations like code breaking. A ­ fter much preparation, they could be fed physical equations and initial conditions and crank out the radius of a nuclear blast.

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By allowing for intuition as distinct from and outside of the operations of a purely formal system like a computer, Turing in effect suggested that ­there may be differences between computer programs that do math and mathematicians. It was a curious turn, therefore, that Turing made from his early work in the 1930s to the more wide-­ranging speculation about the possibility of intelligent computers in “Computing Machinery and Intelligence,” published a l­ ittle over a de­cade ­later. By 1950, discussion of intuition dis­appeared from Turing’s writings about the implications of Gödel. His interests turned, in effect, to the possibility that computers might become “intuition-­machines” themselves. In essence, he de­cided that Gödel’s result d­ idn’t apply to the question of AI: if we ­humans are highly advanced computers, Gödel’s result means only that ­there are some statements that we cannot understand or see to be true, just as with less complicated computers.

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That is what playing chess is, ­after all, and that is what breaking a code is, as well. And ­here we have it: Turing’s g­ reat genius, and his g­ reat error, was in thinking that ­human intelligence reduces to problem-­solving. ­W hether or not the ideas about intelligent machines in his 1950 “Computing Machinery and Intelligence” became explicit in the war years, it is clear that his experience at Bletchley crystallized his l­ ater view of AI, and it is clear that AI in turn followed closely and without necessary self-­analysis precisely in his path. But a closer look at the Bletchley code-­cracking success immediately reveals a dangerous simplification in the philosophical ideas about man and machine.

Turing's Vision: The Birth of Computer Science by Chris Bernhardt

Ada Lovelace, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, Andrew Wiles, Bletchley Park, British Empire, cellular automata, Charles Babbage, Claude Shannon: information theory, complexity theory, Computing Machinery and Intelligence, Conway's Game of Life, discrete time, Douglas Hofstadter, Georg Cantor, Gödel, Escher, Bach, Henri Poincaré, Internet Archive, Jacquard loom, John Conway, John von Neumann, Joseph-Marie Jacquard, Ken Thompson, Norbert Wiener, Paul Erdős, Reflections on Trusting Trust, Turing complete, Turing machine, Turing test, Von Neumann architecture

A small group started work on building the ACE, but work progressed slowly. A prototype was eventually up and running in 1950, but by this time there were other more powerful computers, and even Turing had decamped to Newman’s group at Manchester University, where he would work until his death. While at Manchester, Turing published a paper called Computing Machinery and Intelligence. The paper starts with the question “Can machines think?” Turing considers how we can tell whether a person or a machine is thinking. He proposes the Imitation Game, which has since become known as the “Turing Test.” In this game a human interrogator is in a separate room from a computer and another human.

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In this, Petzold takes Turing’s paper and adds many excellent and lengthy annotations to help the reader understand exactly what Turing is saying at each stage. Petzold also includes the history that surrounds the paper. The paper in which Turing discusses the Imitation Game (Turing Test) is Computing Machinery and Intelligence. This paper was written for a general audience and is widely available on the web. It is well worth reading. For the reader who wants to study more of Turing’s writings, Andrew Hodges maintains a website at http://www.turing.co.uk containing a wealth of information. Another online resource is the Turing Archive, maintained by Jack Copeland and Diane Proudfoot, at http://www.alanturing.net.

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The examples concerning equal numbers of 0s and 1s and balanced brackets can be tackled by pushdown automata. A question that is beyond pushdown automata is looking at strings using an alphabet of three letters and asking whether the strings have the same number of each letter. Chapter 4 1. Alan Turing. “Computing machinery and intelligence.” 2. Below is the complete computation when the Turing machine TM2 is run on the string ( ( ) ). 3. Leibniz’s notation is the standard notation for the derivative of x with respect to t. This is denoted by ẋ in Newton’s notation. 4. Introduction to Wittgenstein’s Tractatus. 5.

Humans Need Not Apply: A Guide to Wealth and Work in the Age of Artificial Intelligence by Jerry Kaplan

Affordable Care Act / Obamacare, Amazon Web Services, asset allocation, autonomous vehicles, bank run, bitcoin, Bob Noyce, Brian Krebs, business cycle, buy low sell high, Capital in the Twenty-First Century by Thomas Piketty, combinatorial explosion, computer vision, Computing Machinery and Intelligence, corporate governance, crowdsourcing, driverless car, drop ship, Easter island, en.wikipedia.org, Erik Brynjolfsson, estate planning, Fairchild Semiconductor, Flash crash, Gini coefficient, Goldman Sachs: Vampire Squid, haute couture, hiring and firing, income inequality, index card, industrial robot, information asymmetry, invention of agriculture, Jaron Lanier, Jeff Bezos, job automation, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, Kiva Systems, Larry Ellison, Loebner Prize, Mark Zuckerberg, mortgage debt, natural language processing, Nick Bostrom, Own Your Own Home, pattern recognition, Satoshi Nakamoto, school choice, Schrödinger's Cat, Second Machine Age, self-driving car, sentiment analysis, short squeeze, Silicon Valley, Silicon Valley startup, Skype, software as a service, The Chicago School, The Future of Employment, Turing test, Vitalik Buterin, Watson beat the top human players on Jeopardy!, winner-take-all economy, women in the workforce, working poor, Works Progress Administration

They could bring your coffee in the morning and have your favorite drink ready for your trip home, while you relax in one of perhaps four “captain’s chairs” in the van, complete with tray table and entertainment system, similar to a first-class airplane seat. 13. Alan Turing, “Computing Machinery and Intelligence,” Mind 59, no. 236 (1950): 433–60, http://mind.oxfordjournals.org/content/LIX/236/433. 14. http://en.wikipedia.org/wiki/Loebner_Prize#Winners, last modified December 29, 2014. 15. Turing, “Computing Machinery and Intelligence,” 442. 16. Paul Miller, “iOS 5 includes Siri ‘Intelligent Assistant’ Voice-Control, Dictation—for iPhone 4S Only,” The Verge, October 4, 2011, http://www.theverge.com/2011/10/04/ios-5-assistant-voice-control-ai-features/. 17.

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That’s why I’m supremely confident that our future is very bright—if only we can figure out how to equitably distribute the benefits. Let’s look at another example of language shifting to accommodate new technology, this one predicted by Alan Turing. In 1950 he wrote a thoughtful essay called “Computing Machinery and Intelligence” that opens with the words “I propose to consider the question, ‘Can machines think?’” He goes on to define what he calls the “imitation game,” what we now know as the Turing Test. In the Turing Test, a computer attempts to fool a human judge into thinking it is human. The judge has to pick the computer out of a lineup of human contestants.

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See also specific applications television, 41–42 thinking: machine capability for, 3, 197–99 shifted meaning of, 198 3D radar (Lidar), 141 Thurlow, Edward, 87 Ticketmaster, 73–74 Torrance, Mark, 64, 67, 70–71, 72 Tracking Angle (music magazine), 193 traffic-control systems, 45 training. See skills; vocational training transportation. See autonomous vehicles Transportation Department, 44–45 Trebek, Alex, 36 truck deliveries, 141–42 TrueCompanion, 144–45 trusts, 117, 200 Turing, Alan, 197–98, 199 “Computing Machinery and Intelligence,” 197, 198 Turing Test, 197–98 2001: A Space Odyssey (film), x Uber, 16 unemployment, 3, 12, 13, 120, 136–37, 169–74 BLS definition of, 170 cyclical, 136–37, 219n5 factors in, 142, 172–73 as personal choice, 170–71, 177, 185 public interest and, 164 rise in (1995–2012), 172 structural, 137 two categories of, 170–71 University of Michigan, 99 University of Pennsylvania, 99 USA Cycling, bailout of, 115 vaccines, 169 VCR (TV recording device), 46 videos, AI recognition of, 39 viewthrough attribution, 70 vinyl records, 193 virtual law office, 148 viruses, computer, 202–3 vocational training: employer collaboration with, 13, 14, 153–54 general education vs., 153–57 volunteer work.

The Most Human Human: What Talking With Computers Teaches Us About What It Means to Be Alive by Brian Christian

"Friedman doctrine" OR "shareholder theory", 4chan, Ada Lovelace, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Bertrand Russell: In Praise of Idleness, Blue Ocean Strategy, carbon footprint, cellular automata, Charles Babbage, Claude Shannon: information theory, cognitive dissonance, commoditize, complexity theory, Computing Machinery and Intelligence, crowdsourcing, David Heinemeier Hansson, Donald Trump, Douglas Hofstadter, George Akerlof, Gödel, Escher, Bach, high net worth, Isaac Newton, Jacques de Vaucanson, Jaron Lanier, job automation, Kaizen: continuous improvement, Ken Thompson, l'esprit de l'escalier, language acquisition, Loebner Prize, machine translation, Menlo Park, operational security, Ray Kurzweil, RFID, Richard Feynman, Ronald Reagan, SimCity, Skype, Social Responsibility of Business Is to Increase Its Profits, starchitect, statistical model, Stephen Hawking, Steve Jobs, Steven Pinker, Thales of Miletus, theory of mind, Thomas Bayes, Turing machine, Turing test, Von Neumann architecture, Watson beat the top human players on Jeopardy!, zero-sum game

If this sounds odd to us in any way, it’s worth knowing that nothing at all seemed odd about it to them. Nor to their co-workers: to their Bell Labs colleagues their romance was a perfectly normal one, typical even. Engineers and computers wooed all the time. It was Alan Turing’s 1950 paper “Computing Machinery and Intelligence” that launched the field of AI as we know it and ignited the conversation and controversy over the Turing test (or the “Imitation Game,” as Turing initially called it) that has continued to this day—but modern “computers” are nothing like the “computers” of Turing’s time. In the early twentieth century, before a “computer” was one of the digital processing devices that so proliferate in our twenty-first-century lives—in our offices, in our homes, in our cars, and, increasingly, in our pockets—it was something else: a job description.

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Notes Epigraphs 1 David Foster Wallace, in interview with David Lipsky, in Although of Course You End Up Becoming Yourself (New York: Broadway Books, 2010). 2 Richard Wilbur, “The Beautiful Changes,” The Beautiful Changes and Other Poems (New York: Reynal & Hitchcock, 1947). 3 Robert Pirsig, Zen and the Art of Motorcycle Maintenance (New York: Morrow, 1974). 4 Barack Obama, “Remarks by the President on the ‘Education to Innovate’ Campaign,” press release, The White House, Office of the Press Secretary, November 23, 2009. 0. Prologue 1 See, e.g., Neil J. A. Sloane and Aaron D. Wyner, “Biography of Claude Elwood Shannon,” in Claude Elwood Shannon: Collected Papers (New York: IEEE Press, 1993). 1. Introduction: The Most Human Human 1 Alan Turing, “Computing Machinery and Intelligence,” Mind 59, no. 236 (October 1950), pp. 433–60. 2 Turing initially introduces the Turing test by way of analogy to a game in which a judge is conversing over “teleprinter” with two humans, a man and a woman, both of whom are claiming to be the woman. Owing to some ambiguity in Turing’s phrasing, it’s not completely clear how strong of an analogy he has in mind; for example, is he suggesting that in the Turing test, a woman and a computer are both claiming specifically to be a woman?

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Norman, “Defensive Tool Use in a Coconut-Carrying Octopus,” Current Biology 19, no. 23 (December 15, 2009), pp. 1069–70. 16 Douglas R. Hofstadter, Gödel, Escher, Bach: An Eternal Golden Braid (New York: Basic Books, 1979). 17 Noam Chomsky, email correspondence (emphasis mine). 18 John Lucas, “Commentary on Turing’s ‘Computing Machinery and Intelligence,’ ” in Epstein et al., Parsing the Turing Test. 2. Authenticating 1 Alix Spiegel, “ ‘Voice Blind’ Man Befuddled by Mysterious Callers,” Morning Edition, National Public Radio, July 12, 2010. 2 David Kernell, posting (under the handle “rubico”) to the message board www.4chan.org, September 17, 2008. 3 Donald Barthelme, “Not-Knowing,” in Not-Knowing: The Essays and Interviews of Donald Barthelme, edited by Kim Herzinger (New York: Random House, 1997).

Human Compatible: Artificial Intelligence and the Problem of Control by Stuart Russell

3D printing, Ada Lovelace, AI winter, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Alfred Russel Wallace, algorithmic bias, AlphaGo, Andrew Wiles, artificial general intelligence, Asilomar, Asilomar Conference on Recombinant DNA, augmented reality, autonomous vehicles, basic income, behavioural economics, Bletchley Park, blockchain, Boston Dynamics, brain emulation, Cass Sunstein, Charles Babbage, Claude Shannon: information theory, complexity theory, computer vision, Computing Machinery and Intelligence, connected car, CRISPR, crowdsourcing, Daniel Kahneman / Amos Tversky, data science, deep learning, deepfake, DeepMind, delayed gratification, Demis Hassabis, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Ernest Rutherford, fake news, Flash crash, full employment, future of work, Garrett Hardin, Geoffrey Hinton, Gerolamo Cardano, Goodhart's law, Hans Moravec, ImageNet competition, Intergovernmental Panel on Climate Change (IPCC), Internet of things, invention of the wheel, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John Nash: game theory, John von Neumann, Kenneth Arrow, Kevin Kelly, Law of Accelerating Returns, luminiferous ether, machine readable, machine translation, Mark Zuckerberg, multi-armed bandit, Nash equilibrium, Nick Bostrom, Norbert Wiener, NP-complete, OpenAI, openstreetmap, P = NP, paperclip maximiser, Pareto efficiency, Paul Samuelson, Pierre-Simon Laplace, positional goods, probability theory / Blaise Pascal / Pierre de Fermat, profit maximization, RAND corporation, random walk, Ray Kurzweil, Recombinant DNA, recommendation engine, RFID, Richard Thaler, ride hailing / ride sharing, Robert Shiller, robotic process automation, Rodney Brooks, Second Machine Age, self-driving car, Shoshana Zuboff, Silicon Valley, smart cities, smart contracts, social intelligence, speech recognition, Stephen Hawking, Steven Pinker, superintelligent machines, surveillance capitalism, Thales of Miletus, The Future of Employment, The Theory of the Leisure Class by Thorstein Veblen, Thomas Bayes, Thorstein Veblen, Tragedy of the Commons, transport as a service, trolley problem, Turing machine, Turing test, universal basic income, uranium enrichment, vertical integration, Von Neumann architecture, Wall-E, warehouse robotics, Watson beat the top human players on Jeopardy!, web application, zero-sum game

A long time, unfortunately—the Analytical Engine was never built, and Lovelace’s ideas were largely forgotten. With Turing’s theoretical work in 1936 and the subsequent impetus of World War II, universal computing machines were finally realized in the 1940s. Thoughts about creating intelligence followed immediately. Turing’s 1950 paper, “Computing Machinery and Intelligence,”42 is the best known of many early works on the possibility of intelligent machines. Skeptics were already asserting that machines would never be able to do X, for almost any X you could think of, and Turing refuted those assertions. He also proposed an operational test for intelligence, called the imitation game, which subsequently (in simplified form) became known as the Turing test.

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It’s also cold comfort to humans who might be worried about being wiped out by machines. It’s impossible Even before the birth of AI in 1956, august intellectuals were harrumphing and saying that intelligent machines were impossible. Alan Turing devoted much of his seminal 1950 paper, “Computing Machinery and Intelligence,” to refuting these arguments. Ever since, the AI community has been fending off similar claims of impossibility from philosophers,6 mathematicians,7 and others. In the current debate over superintelligence, several philosophers have exhumed these impossibility claims to prove that humanity has nothing to fear.8,9 This comes as no surprise.

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Taylor (R. and J. E. Taylor, 1843). Menabrea’s original article, written in French and based on lectures given by Babbage in 1840, appears in Bibliothèque Universelle de Genève 82 (1842). 42. One of the seminal early papers on the possibility of artificial intelligence: Alan Turing, “Computing machinery and intelligence,” Mind 59 (1950): 433–60. 43. The Shakey project at SRI is summarized in a retrospective by one of its leaders: Nils Nilsson, “Shakey the robot,” technical note 323 (SRI International, 1984). A twenty-four-minute film, SHAKEY: Experimentation in Robot Learning and Planning, was made in 1969 and garnered national attention. 44.

The Lights in the Tunnel by Martin Ford

Alan Greenspan, Albert Einstein, Bear Stearns, Bill Joy: nanobots, Black-Scholes formula, business cycle, call centre, carbon tax, cloud computing, collateralized debt obligation, commoditize, Computing Machinery and Intelligence, creative destruction, credit crunch, double helix, en.wikipedia.org, factory automation, full employment, income inequality, index card, industrial robot, inventory management, invisible hand, Isaac Newton, job automation, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, knowledge worker, low skilled workers, mass immigration, Mitch Kapor, moral hazard, pattern recognition, prediction markets, Productivity paradox, Ray Kurzweil, Robert Solow, Search for Extraterrestrial Intelligence, Silicon Valley, Stephen Hawking, strong AI, technological singularity, the long tail, Thomas L Friedman, Turing test, Vernor Vinge, War on Poverty, warehouse automation, warehouse robotics

This irrational, but perhaps understandable, objection to the idea that machines might someday begin to think and reason was first articulated by the founder of computer science, Alan Turing (Please see the last section of this Appendix). Turing initiated the field of artificial intelligence with his 1950 paper “Computing Machinery and Intelligence.” Here’s how Turing expressed what he called the “Heads in the Sand” Objection (which, of course, he rejected): “The consequences of machines thinking would be too dreadful. Let us hope and believe that they cannot do so.” 54 Two Questions Worth Thinking About One While you might not agree that it will ever be a reality, it is easy to imagine an economy with no human workers.

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If strong AI does arrive, how will we know? That is a question that was first asked by Alan Turing nearly sixty years ago. Turing, a legendary British mathematician and code breaker during World War II, is often considered to be the founder of computer science. In 1950, Turing published a paper entitled “Computing Machinery and Intelligence,” in which he proposed a test to answer the question: “Can machines think?” Turing’s test was based on a game popular at parties at the time. In today’s terms, it amounts to a three-way instant messaging conversation. One participant is a human judge. The other participants are another person and a machine—both of whom attempt to convince the judge that they are human by conducting a normal conversation.

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Web: http://www.econ.yale.edu/smith/econ116a/keynes1.pdf p. 195 footnote, Einstein’s view on technological unemployment, see: Walter Isaacson, Einstein: His Life and Universe, New York, Simon & Schuster, 2007, p.403. Chapter 5: The Green Light 53 For more on the challenges of addressing poverty, see: William Easterly, The Elusive Quest for Growth: Economists’ Adventures and Misadventures in the Tropics, Cambridge, MA, MIT Press, 2002. Appendix / Final Thoughts 54 A.M Turing, “Computing Machinery and Intelligence”, Mind, 1950. Web: http://loebner.net/Prizef/TuringArticle.html 55 “French students shy of real world”, BBC News, March 14, 2008. Web: http://news.bbc.co.uk/2/hi/europe/7293992.stm 56 Blue Brain Project, Web: http://bluebrain.epfl.ch/ 57 Roger Penrose, The Emperor’s New Mind: Concerning Computers, Minds, and the Laws of Physics, Oxford University Press, 1989 and Shadows of the Mind: A Search for the Missing Science of Consciousness, Oxford University Press, 1994. 58 For example: John Markoff, “Scientists worry that Machines may Outsmart Man”, New York Times, July 25, 2009.

The Road to Conscious Machines by Michael Wooldridge

Ada Lovelace, AI winter, algorithmic bias, AlphaGo, Andrew Wiles, Anthropocene, artificial general intelligence, Asilomar, augmented reality, autonomous vehicles, backpropagation, basic income, Bletchley Park, Boeing 747, British Empire, call centre, Charles Babbage, combinatorial explosion, computer vision, Computing Machinery and Intelligence, DARPA: Urban Challenge, deep learning, deepfake, DeepMind, Demis Hassabis, don't be evil, Donald Trump, driverless car, Elaine Herzberg, Elon Musk, Eratosthenes, factory automation, fake news, future of work, gamification, general purpose technology, Geoffrey Hinton, gig economy, Google Glasses, intangible asset, James Watt: steam engine, job automation, John von Neumann, Loebner Prize, Minecraft, Mustafa Suleyman, Nash equilibrium, Nick Bostrom, Norbert Wiener, NP-complete, P = NP, P vs NP, paperclip maximiser, pattern recognition, Philippa Foot, RAND corporation, Ray Kurzweil, Rodney Brooks, self-driving car, Silicon Valley, Stephen Hawking, Steven Pinker, strong AI, technological singularity, telemarketer, Tesla Model S, The Coming Technological Singularity, The Future of Employment, the scientific method, theory of mind, Thomas Bayes, Thomas Kuhn: the structure of scientific revolutions, traveling salesman, trolley problem, Turing machine, Turing test, universal basic income, Von Neumann architecture, warehouse robotics

The Turing test achieves this by clearly separating the interrogators from the thing that is being interrogated: the only evidence that the interrogators have to go on are the inputs and outputs – the questions sent by the interrogator, and the responses that the interrogator later receives. The thing on the other end is a black box as far as the Turing test is concerned, in the sense that we are not allowed to examine its internal structure: all that we have are the inputs and outputs. Turing’s article ‘Computing Machinery and Intelligence’, describing his test, was published in the prestigious international journal Mind in 1950.9 Although many articles touching on AI-like ideas had been published before this, Turing approached the subject for the first time from the standpoint of the modern digital computer. As such, his article is generally recognized as the first AI publication.

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Both have moved in and out of fashion over the past 60 years, and as we will see, there has even been acrimony between the two schools. However, as AI emerged as a new scientific discipline in the 1950s, it was symbolic AI that largely held sway. PART TWO How did We Get Here? Chapter 2 The Golden Age Although Turing’s article ‘Computing Machinery and Intelligence’, which introduced the Turing test, made what we now recognize as the first substantial scientific contribution to the discipline of AI, it was a rather isolated contribution, because AI as a discipline simply did not exist at the time. It did not have a name, there was no community of researchers working on it, and the only contributions at the time were speculative conceptual ones, such as the Turing test – there were no AI systems.

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The instructions I’ve listed here are typical of a relatively low-level programming language, but still much more abstract (and much easier to understand) than a Turing machine program. 8. T. H. Cormen, C. E. Leiserson and R. L. Rivest. Introduction to Algorithms (1st edn). MIT Press and McGraw-Hill, 1990. 9. A. M. Turing. ‘Computing Machinery and Intelligence’. Mind, 49, 1950, pp. 433–60. 10. This dialogue was generated with a version of ELIZA that comes with every Apple Macintosh computer. If you have a Mac you can try it yourself. Launch the Terminal application by opening the Applications folder, then the Utilties folder within it, and double-click on the Terminal application icon.

When Things Start to Think by Neil A. Gershenfeld

3D printing, Ada Lovelace, Bretton Woods, cellular automata, Charles Babbage, Claude Shannon: information theory, Computing Machinery and Intelligence, disinformation, Dynabook, Hedy Lamarr / George Antheil, I think there is a world market for maybe five computers, information security, invention of movable type, Iridium satellite, Isaac Newton, Jacquard loom, Johannes Kepler, John von Neumann, low earth orbit, means of production, new economy, Nick Leeson, packet switching, RFID, speech recognition, Stephen Hawking, Steve Jobs, telemarketer, the medium is the message, Turing machine, Turing test, Vannevar Bush, world market for maybe five computers

By typing questions on both terminals, the challenge is to determine which is which. This is a quantitative test that can be run without having to answer deep questions about the meaning of intelligence. Armed with a test for intelligence, Turing wondered how to go about developing a machine that might display it. In his elegant essay "Computing Machinery and Intelligence," he offers a suggestion for where to start: We may hope that machines will eventually compete with men in all purely intellectual fields. But which are the best ones to start with? Even this is a difficult decision. Many people think that a very abstract activity, like the playing of chess, would be best.

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The importance of perception to cognition can be seen in the wiring of our brains. Our senses are connected by two-way channels: information goes in both directions, letting the brain fine-tune how we see and hear and touch in order to learn the most about our environment. This insight takes us back to Turing. He concludes "Computing Machinery and Intelligence" with an alternative suggestion for how to develop intelligent machines: It can also be maintained that it is best to provide the machine with the best sense organs that money can buy, and then teach it to understand and speak English. This process could follow the normal teaching of a child.

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., 51 Clausius, Rudolf, 175 clocks, 104 clothing and wearable computers, 50, 52,55-56,61,102-3,179 coffeemaker, intelligent, 201 communications: imposing on our lives, 95, 100-2 performance limit of a channel of, 176 privacy issues and, 100-1 regulation of, 99-100 see also specific forms of communication, e.g. e-mail; telephones Communications Act of 1934, 99 Communications Assistance for Law Enforcement Act (CALEA), 208 compact disc players, 4 Compumachine, 67 computer chips: entropy and, 177 future uses of, 152 lowering the cost of, 152-56 computers: affective states and, 53-54 Babbage's contribution in developing, 124-25, 132 battle of operating systems, 146 chips, see computer chips cost of, 4, 103 desktop, 5 difficulty using, 4, 7, 103 division of industry into software and hardware, 7 ease of use, 4, 7, 103 educational use of, 201 expectations from, 4 inability to anticipate your needs, 7-8 interfaces, see interfaces, computer irritation with, 199-200 laptop, see laptop computers mainframes, see mainframes minicomputers, 52, 138 Moore's law, 155-57, 163 music and, see musiC and computers parallel, 68, 157 PCs, see personal computers (PCs) peripherals, 52-53 INDEX+ pnvacy issue and, 56-57, 100-1 productivity and, 7 pyramid of information technology, 151 quantum, 157-63, 177 software, see software speed of, 7 standards, 88-90, 126 supercomputers, 151, 177, 199 unobtrusive computing, 44, 200, 211 upgrades, 98 wearable, see wearable computers "Computing Machinery and Intelligence," 128, 135 consciousness, quantum mechanics to describe human, 130-31 Constitution, U.S., 98-99 Copernicus, 113-14 copyrights, 181 Creapole, 55 credit cards: electronic commerce and, 80-81 privacy and use of, 100-1 reflective holograms on, 142 cryptography, 80-81, 156, 207-8 "curse of dimensionality," 164 Daiwa Bank, 77, 86 Darwin, Charles, 125 Data Glove, 49 "Deep Blue," 129-30 "Deep Thought," 129 Defense Advanced Research Projects Agency (DARPA), 79, 129 derivative~ 78, 85-86 Deutsch, David, 158 Deutsche Telekom, 203 developing countries, 210-11 Dickinson, Becton, 204 Difference Engine, 124-25, 132 digital evolution, 10 digital money, see smart money digital representation, effect of time and use on, 5-6 219 Digital Revolution: disturbance resulting from, 10 promise and reality of, 3, 5 disabled, wearable computers and, 58 discovery, the business of, 169-84 Disney, 203 distance learning, 19 3 distribution of wealth, 78 division of labor between people and machines, 8 DNA molecules, 157 Domus, 55 Doom (computer game), 89 Dynabook, 138 e-broidery, 55 Economist, 115 economy, electronic, 79 education: classroom, 188, 197 departmental organization of, 190-91 distance learning, 193 just-in-time, 192 local learning, 193 at Massachusetts Institute of Technology (MIT) Media Lab, 187-97 use of computers for, 201 Einstein's theory of relativity, 178 electronic books, 15-25, 38, 72 electronic commerce, 80-81, 152, 156 cryptography and, 80-81 paying-as-you-go, 82 electronic funds transfers, 80 electronic ink, 16, 17, 200 universal book and, 18-20 e-mail, 101-2, 104-6 encryption, 80-81 Engelhart, Doug, 139 English Bill of Rights, 98 entanglement, 159 entropy, 175, 176, 177, 188-90 "Entschedidungsproblem," 127 Equifax, 101 220 + Ernst, Richard R.

Smart Machines: IBM's Watson and the Era of Cognitive Computing (Columbia Business School Publishing) by John E. Kelly Iii

AI winter, book value, call centre, carbon footprint, Computing Machinery and Intelligence, crowdsourcing, demand response, discovery of DNA, disruptive innovation, Erik Brynjolfsson, Fairchild Semiconductor, future of work, Geoffrey West, Santa Fe Institute, global supply chain, Great Leap Forward, Internet of things, John von Neumann, Large Hadron Collider, Mars Rover, natural language processing, optical character recognition, pattern recognition, planetary scale, RAND corporation, RFID, Richard Feynman, smart grid, smart meter, speech recognition, TED Talk, Turing test, Von Neumann architecture, Watson beat the top human players on Jeopardy!

CODA: AN ALLIANCE OF HUMAN AND MACHINE Ever since Watson won at Jeopardy!, people have been asking the research scientists who designed the machine if they’d like to try to pass the so-called Turing test. That’s an exercise suggested by computing pioneer Alan Turing in his 1950 paper “Computing Machinery and Intelligence,” where he raised the question: “Can machines think?” He suggested that to test whether a machine can think, a human judge should have a written conversation via computer screen and keyboard with another human and a computer. If the judge couldn’t tell the human from the machine based on their responses, the machine would have passed the test.1 With this test, Turing set a standard for measuring the capabilities of machines that has not yet been met.

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Colin Harrison, IBM, “Smarter Cities—NextGen,” PowerPoint presentation, presented at the Major Cities of Europe Conference, Vienna, Austria, June 5, 2012. 9. Milind Naphade, IBM Research, interview, September 27, 2012. 10. Chandra Ravada, Iowa East Central Intergovernmental Association, interview, January 7, 2013. CODA: AN ALLIANCE OF HUMAN AND MACHINE 1. Alan Turing, “Computing Machinery and Intelligence,” Mind 59 (October 1950): 433–60; see http://www.loebner.net/Prizef/TuringArticle.html.

The Age of Spiritual Machines: When Computers Exceed Human Intelligence by Ray Kurzweil

Ada Lovelace, Alan Greenspan, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, Alvin Toffler, Any sufficiently advanced technology is indistinguishable from magic, backpropagation, Buckminster Fuller, call centre, cellular automata, Charles Babbage, classic study, combinatorial explosion, complexity theory, computer age, computer vision, Computing Machinery and Intelligence, cosmological constant, cosmological principle, Danny Hillis, double helix, Douglas Hofstadter, Everything should be made as simple as possible, financial engineering, first square of the chessboard / second half of the chessboard, flying shuttle, fudge factor, functional programming, George Gilder, Gödel, Escher, Bach, Hans Moravec, I think there is a world market for maybe five computers, information retrieval, invention of movable type, Isaac Newton, iterative process, Jacquard loom, John Gilmore, John Markoff, John von Neumann, Lao Tzu, Law of Accelerating Returns, mandelbrot fractal, Marshall McLuhan, Menlo Park, natural language processing, Norbert Wiener, optical character recognition, ought to be enough for anybody, pattern recognition, phenotype, punch-card reader, quantum entanglement, Ralph Waldo Emerson, Ray Kurzweil, Richard Feynman, Robert Metcalfe, Schrödinger's Cat, Search for Extraterrestrial Intelligence, self-driving car, Silicon Valley, social intelligence, speech recognition, Steven Pinker, Stewart Brand, stochastic process, Stuart Kauffman, technological singularity, Ted Kaczynski, telepresence, the medium is the message, The Soul of a New Machine, There's no reason for any individual to have a computer in his home - Ken Olsen, traveling salesman, Turing machine, Turing test, Whole Earth Review, world market for maybe five computers, Y2K

The Birth of Artificial Intelligence The similarity of the computational process to the human thinking process was not lost on Turing. In addition to having established much of the theoretical foundations of computation and having invented the first operational computer, he was instrumental in the early efforts to apply this new technology to the emulation of intelligence. In his classic 1950 paper, Computing Machinery and Intelligence, Turing described an agenda that would in fact occupy the next half century of advanced computer research: game playing, decision making, natural language understanding, translation, theorem proving, and, of course, encryption and the cracking of codes.6 He wrote (with his friend David Champernowne) the first chess-playing program.

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Anscombe, Wittgenstein “acknowledges” that he made “grave mistakes” in his earlier work, the Tractatus. 9 For a useful overview of Descartes’s life and work, see The Dictionary of Scientific Biography, vol. 4, pp. 55-65. Also, Jonathan Rées Descartes presents a unified view of Descartes’s philosophy and its relation to other systems of thought. 10 Quoted from Douglas R. Hofstadter, Gödel, Escher, Bach: An Eternal Golden Braid (New York: Basic Books, 1979). 11 “Computing Machinery and Intelligence,” Mind 59 (1950): 433-460, reprinted in E. Feigenbaum and J. Feldman, eds., Computers and Thought (New York: McGraw-Hill, 1963). 12 For a description of quantum mechanics, read George Johnson, “Quantum Theorists Try to Surpass Digital Computing,” New York Times, February 18, 1997.

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Zuse, “Verfahren zur Selbst Atigen Durchfurung von Rechnungen mit Hilfe von Rechenmaschinen,” German Patent Application Z23624, April 11, 1936. Translated extracts, titled “Methods for Automatic Execution of Calculations with the Aid of Computers,” appear in Brian Randell, ed., The Origins of Digital Computers, pp. 159-166. 6 “Computing Machinery and Intelligence,” Mind 59 (1950): 433-460, reprinted in E. Feigenbaum and J. Feldman, eds., Computers and Thought (New York: McGraw-Hill, 1963). 7 See A. Newell, J. C. Shaw, and H. A. Simon, “Programming the Logic Theory Machine,” Proceedings of the Western joint Computer Conference, 1957, pp. 230-240. 8 Russell and Whitehead’s Principia Mathematica (see reference at the end of this end-note), first published in 1910-1913, was a seminal work that reformulated mathematics based on Russell’s new conception of set theory.

Nine Algorithms That Changed the Future: The Ingenious Ideas That Drive Today's Computers by John MacCormick, Chris Bishop

Ada Lovelace, AltaVista, Charles Babbage, Claude Shannon: information theory, Computing Machinery and Intelligence, fault tolerance, information retrieval, Menlo Park, PageRank, pattern recognition, Richard Feynman, Silicon Valley, Simon Singh, sorting algorithm, speech recognition, Stephen Hawking, Steve Jobs, Steve Wozniak, traveling salesman, Turing machine, Turing test, Vannevar Bush

NEURAL NETWORKS The remarkable abilities of the human brain have fascinated and inspired computer scientists ever since the creation of the first digital computers. One of the earliest discussions of actually simulating a brain using a computer was by Alan Turing, a British scientist who was also a superb mathematician, engineer, and code-breaker. Turing's classic 1950paper, entitled Computing Machinery and Intelligence, is most famous for a philosophical discussion of whether a computer could masquerade as a human. The paper introduced a scientific way of evaluating the similarity between computers and humans, known these days as a “Turing test.” But in a less well-known passage of the same paper, Turing directly analyzed the possibility of modeling a human brain using a computer.

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But if its strongest version holds, then our computers aren't the only ones humbled by the limits of undecidability. The same limits would apply not only to the genius at our fingertips, but the genius behind them: our own minds. 11 Conclusion: More Genius at Your Fingertips? We can only see a short distance ahead, but we can see plenty there that needs to be done. —ALAN TURING, Computing Machinery and Intelligence, 1950 I was fortunate, in 1991, to attend a public lecture by the great theoretical physicist Stephen Hawking. During the lecture, which was boldly titled “The Future of the Universe,” Hawking confidently predicted that the universe would keep expanding for at least the next 10 billion years.

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See also hardware computer program; analyzing another program; executable; impossible; input and output; intelligent; programmers; programming; programming languages; verification; world's first programmer; yes-no computer programming. See computer program computer science; beauty in; certainty in; curriculum; founding of; in high school; introductory teaching; popularity of; predictions about; public perception of; research; in society; theory of; undecidable problems in Computing Machinery and Intelligence concurrency consciousness consistency. See also inconsistency contradiction. See proof by contradiction Cormen, Thomas cosmology Covenant Woman CPU crash; intentional Crashing Problem CrashOnSelf.exe, CRC32 credit card Crevier, Daniel Croft, Bruce cryptographic hash function cryptography; public key (see public key cryptography) cuneiform cycle Dartmouth AI conference Dasgupta, Sanjoy data center database; column; definition of; geographically replicated; of faces; relational; replicated; row; table.

The Perfect Bet: How Science and Math Are Taking the Luck Out of Gambling by Adam Kucharski

Ada Lovelace, Albert Einstein, Antoine Gombaud: Chevalier de Méré, beat the dealer, behavioural economics, Benoit Mandelbrot, Bletchley Park, butterfly effect, call centre, Chance favours the prepared mind, Claude Shannon: information theory, collateralized debt obligation, Computing Machinery and Intelligence, correlation does not imply causation, diversification, Edward Lorenz: Chaos theory, Edward Thorp, Everything should be made as simple as possible, Flash crash, Gerolamo Cardano, Henri Poincaré, Hibernia Atlantic: Project Express, if you build it, they will come, invention of the telegraph, Isaac Newton, Johannes Kepler, John Nash: game theory, John von Neumann, locking in a profit, Louis Pasteur, Nash equilibrium, Norbert Wiener, p-value, performance metric, Pierre-Simon Laplace, probability theory / Blaise Pascal / Pierre de Fermat, quantitative trading / quantitative finance, random walk, Richard Feynman, Ronald Reagan, Rubik’s Cube, statistical model, The Design of Experiments, Watson beat the top human players on Jeopardy!, zero-sum game

To train his software, Dahl set up lots of bots and got them to face off against each other in game after game. The computer programs sat through billions of hands, betting and bluffing, their artificial brains developing while they played. As the bots improved, Dahl found that they began to do some surprising things. IN HIS LANDMARK 1952 paper “Computing Machinery and Intelligence,” Turing pointed out that many people were skeptical about the possibility of artificial intelligence. One criticism, put forward by mathematician Ada Lovelace in the nineteenth century, was that machines could not create anything original. They could only do what they were told. Which meant a machine would never take us by surprise.

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The Essential Turing (Oxford: Oxford University Press, 2004). 170manuscript entitled “The Game of Poker”: The game of poker. File AMT/C/18. The Papers of Alan Mathison Turing. The UK National Archives. 170He also wondered how games: Details of the imitation game given in: Turing, A. M. “Computing Machinery and Intelligence.” Mind 59 (1950): 433–460. 171When it played chess against Garry Kasparov: Kasparov, Garry. “The Chess Master and the Computer.” New York Review of Books, February 11, 2010. http://www.nybooks.com/articles/archives/2010/feb/11/the-chess-master-and-the-computer/. 172In 2013, journalist Michael Kaplan: Details of Vegas bot given in: Kaplan, Michael.

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., 140–141, 142 clustered volatility, 162 coalitions, 181–183 code breaking, 26, 62–63, 64, 169–170 coefficient of determination, 54 coin tosses, 4, 5, 58, 65, 66, 199, 210–211 Coles, Stuart, 73–74, 75, 76–78, 82, 86, 97, 107, 218 collusion, 181, 182 competitive relationships, 129, 130–131, 136 competitiveness and memory, 161–162 complexity, 83–84, 120, 123, 128, 131, 134, 142, 154, 155, 159, 160, 161, 162, 170, 179–180, 188, 210, 211, 212 Computer Group, 81–82, 96, 97 computer programs, automated. See robots (bots) computerized prediction in blackjack, 42 in checkers, 156, 157 in horse racing, 46, 51, 57, 68 and the Monte Carlo method, 61 in roulette, 2, 13, 14, 15–20, 22 in sports, 80–82, 87, 88, 89–90, 97, 105, 217 “Computing Machinery and Intelligence” (Turing), 175 Connect Four, 158–159 control over events, 199 controlled randomness, 25–26, 28 cooperative relationships, 129, 136 copycats, 132 Coram, Marc, 63, 64 correlation and causation, issue of, 206–207 Corsi rating, 85 Cosmopolitan, Las Vegas 87 countermeasures, 21, 86, 195, 214 counting cards.

The Book of Why: The New Science of Cause and Effect by Judea Pearl, Dana Mackenzie

affirmative action, Albert Einstein, AlphaGo, Asilomar, Bayesian statistics, computer age, computer vision, Computing Machinery and Intelligence, confounding variable, correlation coefficient, correlation does not imply causation, Daniel Kahneman / Amos Tversky, data science, deep learning, DeepMind, driverless car, Edmond Halley, Elon Musk, en.wikipedia.org, experimental subject, Great Leap Forward, Gregor Mendel, Isaac Newton, iterative process, John Snow's cholera map, Loebner Prize, loose coupling, Louis Pasteur, Menlo Park, Monty Hall problem, pattern recognition, Paul Erdős, personalized medicine, Pierre-Simon Laplace, placebo effect, Plato's cave, prisoner's dilemma, probability theory / Blaise Pascal / Pierre de Fermat, randomized controlled trial, Recombinant DNA, selection bias, self-driving car, seminal paper, Silicon Valley, speech recognition, statistical model, Stephen Hawking, Steve Jobs, strong AI, The Design of Experiments, the scientific method, Thomas Bayes, Turing test

All evidence comes with a certain amount of uncertainty. Bayes’s rule tells us how to perform step (4) in the real world. FROM BAYES’S RULE TO BAYESIAN NETWORKS In the early 1980s, the field of artificial intelligence had worked itself into a cul-de-sac. Ever since Alan Turing first laid out the challenge in his 1950 paper “Computing Machinery and Intelligence,” the leading approach to AI had been so-called rule-based systems or expert systems, which organize human knowledge as a collection of specific and general facts, along with inference rules to connect them. For example: Socrates is a man (specific fact). All men are mortals (general fact).

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I am very confident, though, that researchers will discover the power of Bareinboim’s algorithms before long, and then external validity, like confounding before it, will cease to have its mystical and terrifying power. STRONG AI AND FREE WILL The ink was scarcely dry on Alan Turing’s great paper, “Computing Machinery and Intelligence,” when science fiction writers and futurologists began toying with the prospect of machines that think. Sometimes they envisioned these machines as benign or even noble figures, like the whirry, chirpy R2D2 and the oddly British android C3PO from Star Wars. Other times the machines are much more sinister, plotting the destruction of the human species, as in the Terminator movies, or enslaving humans in a virtual reality, as in The Matrix.

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Springer-Verlag, New York, NY. Spohn, W. (2012). The Laws of Belief: Ranking Theory and Its Philosophical Applications. Oxford University Press, Oxford, UK. Suppes, P. (1970). A Probabilistic Theory of Causality. North-Holland Publishing Co., Amsterdam, Netherlands. Turing, A. (1950). Computing machinery and intelligence. Mind 59: 433–460. Weisberg, D. S., and Gopnik, A. (2013). Pretense, counterfactuals, and Bayesian causal models: Why what is not real really matters. Cognitive Science 37: 1368–1381. CHAPTER 2. FROM BUCCANEERS TO GUINEA PIGS: THE GENESIS OF CAUSAL INFERENCE Annotated Bibliography Galton’s explorations of heredity and correlation are described in his books (Galton, 1869, 1883, 1889) and are also documented in Stigler (2012, 2016).

What Algorithms Want: Imagination in the Age of Computing by Ed Finn

Airbnb, Albert Einstein, algorithmic bias, algorithmic management, algorithmic trading, AlphaGo, Amazon Mechanical Turk, Amazon Web Services, bitcoin, blockchain, business logic, Charles Babbage, Chuck Templeton: OpenTable:, Claude Shannon: information theory, commoditize, Computing Machinery and Intelligence, Credit Default Swap, crowdsourcing, cryptocurrency, data science, DeepMind, disruptive innovation, Donald Knuth, Donald Shoup, Douglas Engelbart, Douglas Engelbart, Elon Musk, Evgeny Morozov, factory automation, fiat currency, Filter Bubble, Flash crash, game design, gamification, Google Glasses, Google X / Alphabet X, Hacker Conference 1984, High speed trading, hiring and firing, Ian Bogost, industrial research laboratory, invisible hand, Isaac Newton, iterative process, Jaron Lanier, Jeff Bezos, job automation, John Conway, John Markoff, Just-in-time delivery, Kickstarter, Kiva Systems, late fees, lifelogging, Loebner Prize, lolcat, Lyft, machine readable, Mother of all demos, Nate Silver, natural language processing, Neal Stephenson, Netflix Prize, new economy, Nicholas Carr, Nick Bostrom, Norbert Wiener, PageRank, peer-to-peer, Peter Thiel, power law, Ray Kurzweil, recommendation engine, Republic of Letters, ride hailing / ride sharing, Satoshi Nakamoto, self-driving car, sharing economy, Silicon Valley, Silicon Valley billionaire, Silicon Valley ideology, Silicon Valley startup, SimCity, Skinner box, Snow Crash, social graph, software studies, speech recognition, statistical model, Steve Jobs, Steven Levy, Stewart Brand, supply-chain management, tacit knowledge, TaskRabbit, technological singularity, technological solutionism, technoutopianism, the Cathedral and the Bazaar, The Coming Technological Singularity, the scientific method, The Signal and the Noise by Nate Silver, The Structural Transformation of the Public Sphere, The Wealth of Nations by Adam Smith, transaction costs, traveling salesman, Turing machine, Turing test, Uber and Lyft, Uber for X, uber lyft, urban planning, Vannevar Bush, Vernor Vinge, wage slave

Hayles, My Mother Was a Computer, 173. 47. Jonze, Her. 48. Ibid. 49. Ellwood et al., “‘Her’ Q&A.” 50. The Loebner Prize promises a solid gold medal and $100,000 “for the first computer whose responses [are] indistinguishable from a human’s.” “Home Page of the Loebner Prize.” 51. Turing, “Computing Machinery and Intelligence,” 443. 52. Adams, The Education of Henry Adams, XXV. 53. Plato, Symposium, 9:211d. 3 House of Cards: The Aesthetics of Abstraction There is no solace above or below. Only us—small, solitary, striving, battling one another. I pray to myself, for myself. Frank Underwood1 The Netflix Prize If Apple and Google want to dominate our relationships with search, access, and personal information, the movies-on-demand company Netflix wants to own the leisure time we spend on video entertainment.

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We desperately need more readers, more critics, to interpret the algorithms that now define the channels and horizons of our collective imaginations. Notes 1. Mnih et al., “Human-Level Control through Deep Reinforcement Learning.” 2. Reese, “Google DeepMind.” 3. Metz, “Google’s AI Takes Historic Match against Go Champ with Third Straight Win.” 4. Turing, “Computing Machinery and Intelligence,” 457. 5. Domingos, The Master Algorithm, 4. 6. Madrigal, “How Netflix Reverse Engineered Hollywood”; Strogatz, “The End of Insight.” 7. Lem, Solaris. 8. Ptolemy, Transcendent Man. Thanks to Corey Pressman for bringing this reference to my attention. 9. Bush, “As We May Think.” 10.

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Tech. http://www.washingtonpost.com/business/technology/faq-googles-new-privacy-policy/2012/01/24/gIQArw8GOQ_story.html. Tully, C., ed. ISPW ’88: Proceedings of the 4th International Software Process Workshop on Representing and Enacting the Software Process. New York: ACM, 1988. Turing, Alan M. “Computing Machinery and Intelligence.” Mind. New Series 59 (236) (October 1, 1950): 433–460. Turner, Fred. From Counterculture to Cyberculture: Stewart Brand, the Whole Earth Network, and the Rise of Digital Utopianism. Chicago: University of Chicago Press, 2006. “2014 Financial Tables—Investor Relations—Google,” Q1 2014. http://investor.google.com/financial/tables.html.

The Knowledge Illusion by Steven Sloman

Affordable Care Act / Obamacare, Air France Flight 447, attribution theory, bitcoin, Black Swan, Cass Sunstein, combinatorial explosion, computer age, Computing Machinery and Intelligence, CRISPR, crowdsourcing, Dmitri Mendeleev, driverless car, Dunning–Kruger effect, Elon Musk, Ethereum, Flynn Effect, Great Leap Forward, Gregor Mendel, Hernando de Soto, Higgs boson, hindsight bias, hive mind, indoor plumbing, Isaac Newton, John von Neumann, libertarian paternalism, Mahatma Gandhi, Mark Zuckerberg, meta-analysis, Nick Bostrom, obamacare, Peoples Temple, prediction markets, randomized controlled trial, Ray Kurzweil, Richard Feynman, Richard Thaler, Rodney Brooks, Rosa Parks, seminal paper, single-payer health, speech recognition, stem cell, Stephen Hawking, Steve Jobs, technological singularity, The Coming Technological Singularity, The Wisdom of Crowds, Vernor Vinge, web application, Whole Earth Review, Y Combinator

Thinking was assumed to be a kind of computer program that runs in people’s brains. One of Alan Turing’s claims to fame is that he took this idea to its logical extreme. If people work like computers, then it should be possible to program a computer to do what a human being can. Motivated by this idea, his classic paper “Computing Machinery and Intelligence” in 1950 addressed the question Can machines think? In the 1980s, Landauer decided to estimate the size of human memory on the same scale that is used to measure the size of computer memories. As we write this book, a laptop computer comes with around 250 or 500 gigabytes of memory as long-term storage.

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Cognitive Science 26(5): 521–562. Rozenblit and Keil quote: ibid., 10. what people know about bicycles: R. Lawson (2006). “The Science of Cycology: Failures to Understand How Everyday Objects Work.” Memory & Cognition 34(8), 1667–1675. Can machines think?: A. M. Turing (1950). “Computing Machinery and Intelligence.” Mind 59: 433–460. Landauer: T. K. Landauer (1986). “How Much Do People Remember? Some Estimates of the Quantity of Learned Information in Long-term Memory.” Cognitive Science 10(4): 477–493. They learned at approximately the same rate: For those familiar with information theory, the rate of acquisition Landauer estimated was roughly two bits per second.

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See also artificial intelligence (AI); thought body-brain cooperation in cognitive processing, 101–05 collective mind, 5–6 CRT (Cognitive Reflection Test), 80–84 division of cognitive labor, 14, 109–11, 120–21, 128–29 illusion of understanding, 8, 15 individual limitations, 4–5, 15 Landauer, Thomas, 24–26 the mind compared to a computer, 24–27 moving text window example, 93–95 origins of, 4 Turing, Alan, 25 collaboration, 14, 109–11, 115–18, 121–22, 149–50, 226 collective intelligence hypothesis, 209–10 combinatorial explosion, 34 “The Coming Technological Singularity” (Vinge), 132 communal learning Brown, Ann, 228–30 Fostering Communities of Learners program, 228–30 group/regroup strategy, 228–30 jigsaw method, 229–30 communication language, 113–14 non-verbal, 114–15, 117 community development of, 112–13 intelligence, 259 responsibility, 259–61 community of knowledge, 80, 200, 206–14, 221, 223–27, 241–42 compatibility of different group members’ knowledge, 126 complexity airplane example, 28 beehive example, 107–08, 113–14 car example, 28 chaos theory, 34–35 class reunion example, 31 combinatorial explosion, 34 fractals, 33–34 hairpin example, 34 of the human brain, 29–30 military strategy, 32–33 in the natural world, 29–31 of politics, 16 recognizing, 35 reducing, 250 of technology, 134–35 weather prediction, 30–31 comprehension illusion of, 217–18 inverted text example, 217 Pledge of Allegiance example, 217–18 “Purple Haze” example, 218 computer checkers example of testing intelligence of a team, 210–11 “Computing Machinery and Intelligence” (Turing), 25 consequences of tiny changes. See chaos theory consequences vs. values arguments, 182–87 contribution of individuals example of group thinking, 122 Copernicus, Nicolaus, 198–99 counterfactual thought, 64–65 Galileo’s experiments with dropping different weights, 65–66 imagining scenarios to figure out likely outcomes, 66 crowdsourcing expertise, 146–50 ox’s weight example, 148 Pallokerho-35 Finnish soccer club example, 148 prediction market, 149 user ratings, 148 crows ability to reason diagnostically, 62 CRT (Cognitive Reflection Test), 80–84 bat and ball problem, 81 lily pad problem, 81–82 machines and widgets problem, 82 crystallized intelligence, 202 cult communities, 260 cultural values and cognition, 160–63 reconciling conflicting beliefs, 161–62 “Science Mike” (Mike McHargue), 160–62 cumulative culture, 117–18 curse of knowledge, 128, 244 curving bullets example of physics, 69–70 Dalio, Ray, 253 Damasio, Antonio, 103 decentralized collaborative activity, 149–50 Bitcoin, 150 block chain technology, 150 Ethereum, 150 decision-making, 103–05, 240, 241, 248–49, 250–53 deficit model of science attitudes, 157–60 Dehghani, Morteza, 185–86 Descartes, René, 87 de Soto, Hernando, 244–45 DeVito, Danny, 45–46 Dewey, John, 216 diagnostic reasoning, 58–62 crow example, 62 lethargy example, 59–61 diSessa, Andrea, 71 disgust, feelings of, 104–05 division of cognitive labor, 14, 109–11, 120–21, 128–29 area of expertise example, 120 car analogy example, 207–08 in the field of science, 222–23 household finances, 247 wine expert example, 120 dogs Cassie example, 49–50 Pavlovian conditioning, 50–51 doorway example of optic flow, 99–100 driving ability example of ignorance, 257–58 Dunbar, Robin, 113 Dunning, David, 257–58 Dunning-Kruger effect, 258 Eastwood, Clint, 172 economics of science, 227–28 education application of classroom learning, 216–17 becoming a car mechanic example, 219–20 expressing desire to learn that which is unknown, 221 financial issues, 240–41 history of Spain example, 220 Ignorance course, 221 illusion of comprehension, 217–18 just-in-time, 251–52 learning to accept what you don’t know, 220–21 mathematical abilities of Brazilian children, 215–16 peer, 230–31 purpose of, 219–21 teaching science, 222, 225–32 Einstein, Albert, 199 embodied intelligence, 91–93 embodiment, 102 emotional responses that influence decision-making, 103–05, 240 engagement as a human concept, 117 environment, knowledge of your personal, 94–96 Ethereum, 150 expertise and crowdsourcing, 146–50 in scientific matters, 226–27 to understand community issues, 188–89 explanation foes and fiends, 237–39 advertising, 239–40, 241–42 Band-Aids example, 237–38 skin care example, 239–40 vesting service letter example, 243–44 explorers’ self-confidence, 263 eyesight.

The Seventh Sense: Power, Fortune, and Survival in the Age of Networks by Joshua Cooper Ramo

air gap, Airbnb, Alan Greenspan, Albert Einstein, algorithmic trading, barriers to entry, Berlin Wall, bitcoin, Bletchley Park, British Empire, cloud computing, Computing Machinery and Intelligence, crowdsourcing, Danny Hillis, data science, deep learning, defense in depth, Deng Xiaoping, drone strike, Edward Snowden, Fairchild Semiconductor, Fall of the Berlin Wall, financial engineering, Firefox, Google Chrome, growth hacking, Herman Kahn, income inequality, information security, Isaac Newton, Jeff Bezos, job automation, Joi Ito, Laura Poitras, machine translation, market bubble, Menlo Park, Metcalfe’s law, Mitch Kapor, Morris worm, natural language processing, Neal Stephenson, Network effects, Nick Bostrom, Norbert Wiener, Oculus Rift, off-the-grid, packet switching, paperclip maximiser, Paul Graham, power law, price stability, quantitative easing, RAND corporation, reality distortion field, Recombinant DNA, recommendation engine, Republic of Letters, Richard Feynman, road to serfdom, Robert Metcalfe, Sand Hill Road, secular stagnation, self-driving car, Silicon Valley, Skype, Snapchat, Snow Crash, social web, sovereign wealth fund, Steve Jobs, Steve Wozniak, Stewart Brand, Stuxnet, superintelligent machines, systems thinking, technological singularity, The Coming Technological Singularity, The Wealth of Nations by Adam Smith, too big to fail, Vernor Vinge, zero day

The human was still doing the thinking; the computer was simply computing. It was extremely easy to draw a line between where the biological ended and the digital commenced. This was a puzzle that had been, in a sense, anticipated at the very dawn of the digital revolution by the mathematician Alan Turing in a paper called “Computing Machinery and Intelligence,” which he published in 1950. “Can machines think?” Turing began. His idea was to test this question in the following way: Have a research subject—a secretary, a graduate student, anyone—chat with an invisible interlocutor by way of a keyboard. Then ask, What are you connected to? Another human?

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“Poetry mustn’t be taken seriously as a serious thing laying hold of truth,” Socrates warns, “but that the man who hears it must be careful, fearing for the regime in himself.” Thus: Hesiod’s magnificent Works and Days, banned. Homer, banned. There has always been about poetry this sense of the magical, this sense that it is a key to something intimately bound to the human mystery. It was no surprise to me to find, when I went back to reread Turing’s “Computing Machinery and Intelligence,” that the very first thing the great mathematician dreamed up to ask a digital brain was “Write me a sonnet.” Socrates and Plato gatekeep the poets out of their republic because they know the mad part of the soul that verse can touch. It is hard to blame them. After all, they were among the earliest Western minds to try to dispel madness and superstition and sophistry.

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The essential facilitating feature: Nathalie Mezza-Garcia, Tom Froese, and Nelson Fernández, “Reflections on the Complexity of Ancient Social Heterarchies: Toward New Models of Social Self-Organization in Pre-Hispanic Colombia,” Journal of Sociocybernetics 12 (2014): 3–17. Chapter 11. CITIZENS! “Can machines think”: A. M. Turing, “Computing Machinery and Intelligence,” Mind 59, no. 236 (October 1950): 433. The AI systems designer: Roger Grosse, “Predictive Learning vs. Representation Learning,” Building Intelligent Probabilistic Systems (blog), February 4, 2013. Wouldn’t it be nice: Andrej Karpathy, “The Unreasonable Effectiveness of Recurrent Neural Networks,” The Hacker’s Guide to Neural Networks (blog), May 21, 2015; John Supko, “How I Taught My Computer to Write Its Own Music,” Nautilus 21 (February 12, 2015); Daniel Johnson, “Composing Music with Recurrent Neural Networks,” Hexahedria (blog), August 3, 2015.

How to Create a Mind: The Secret of Human Thought Revealed by Ray Kurzweil

Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, Albert Michelson, anesthesia awareness, anthropic principle, brain emulation, cellular automata, Charles Babbage, Claude Shannon: information theory, cloud computing, computer age, Computing Machinery and Intelligence, Dean Kamen, discovery of DNA, double helix, driverless car, en.wikipedia.org, epigenetics, George Gilder, Google Earth, Hans Moravec, Isaac Newton, iterative process, Jacquard loom, Jeff Hawkins, John von Neumann, Law of Accelerating Returns, linear programming, Loebner Prize, mandelbrot fractal, Nick Bostrom, Norbert Wiener, optical character recognition, PalmPilot, pattern recognition, Peter Thiel, Ralph Waldo Emerson, random walk, Ray Kurzweil, reversible computing, selective serotonin reuptake inhibitor (SSRI), self-driving car, speech recognition, Steven Pinker, strong AI, the scientific method, theory of mind, Turing complete, Turing machine, Turing test, Wall-E, Watson beat the top human players on Jeopardy!, X Prize

That brings us to the fourth important idea, which is to go beyond Ada Byron’s conclusion that a computer could not think creatively and find the key algorithms employed by the brain and then use these to turn a computer into a brain. Alan Turing introduced this goal in his 1950 paper “Computing Machinery and Intelligence,” which includes his now-famous Turing test for ascertaining whether or not an AI has achieved a human level of intelligence. In 1956 von Neumann began preparing a series of lectures intended for the prestigious Silliman lecture series at Yale University. Due to the ravages of cancer, he never delivered these talks nor did he complete the manuscript from which they were to be given.

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It can consider more than just the highest-rated solution creature from the most recent generation(s). It can also consider a trend that goes beyond just the last two generations. 12. Dileep George, “How the Brain Might Work: A Hierarchical and Temporal Model for Learning and Recognition” (PhD dissertation, Stanford University, June 2008). 13. A. M. Turing, “Computing Machinery and Intelligence,” Mind, October 1950. 14. Hugh Loebner has a “Loebner Prize” competition that is run each year. The Loebner silver medal will go to a computer that passes Turing’s original text-only test. The gold medal will go to a computer that can pass a version of the test that includes audio and video input and output.

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., 113 busy beaver problem, 207 Butler, Samuel, 62, 199–200, 224, 248–49 Byron, Ada, Countess of Lovelace, 190, 191 California, University of, at Berkeley, 88 “CALO” project, 162 carbon atoms, information structures based on, 2 Carroll, Lewis, 109 cells, replacement of, 245, 246 cellular automata, 236–39 cerebellum, 7, 77, 103–4 uniform structure of, 103 cerebral cortex, 7–8 see also neocortex Chalmers, David, 201–2, 218, 241 “chatbots,” 161 chemistry, 37 chess, AI systems and, 6, 38–39, 165–66, 257 chimpanzees: language and, 3, 41 tool use by, 41 “Chinese room” thought experiment, 170, 274–75 Chomsky, Noam, 56, 158 Church, Alonzo, 186 Church-Turing thesis, 186 civil rights, 278 cloud computing, 116–17, 123, 246, 279–80 cochlea, 96, 97, 135, 138 cochlear implants, 243 Cockburn, David, 214 Cold Spring Harbor Laboratory, 129 Colossus, 187, 188 “common sense,” 40 communication, reliability of, 182–85, 190 communication technology, LOAR and, 253, 254 compatibilism, 234 complexity, 198, 233 of human brain, 8–9, 181, 272 modeling and, 37–38 true vs. apparent, 10–11 computation: price/performance of, 4–5, 250–51, 257, 257, 267–68, 301n–3n thinking compared with to, 26–27 universality of, 26, 181–82, 185, 188, 192, 207 Computer and the Brain, The (von Neumann), 191 computers: brain emulated by, see brain, human, computer emulation of consciousness and, 209–11, 213–15, 223 intelligent algorithms employed by, 6–7 knowledge base expanded by, 4, 246, 247 logic gates in, 185 memory in, 185, 259, 260, 268, 301n–3n, 306n–7n reliability of communication by, 182–85, 190 see also neocortex, digital “Computing Machinery and Intelligence” (Turing), 191 conditionals, 65, 69, 153, 189, 190 confabulation, 70, 217, 227, 228, 229 connectionism, 133, 191 “connectome,” 262 consciousness, 11, 199–209 cerebral hemispheres and, 226–29 computers and, 209–11, 213–15, 223, 233 Descartes on, 221–22 dualist views of, 202–3 Eastern vs.

Artificial Intelligence: A Guide for Thinking Humans by Melanie Mitchell

Ada Lovelace, AI winter, Alignment Problem, AlphaGo, Amazon Mechanical Turk, Apple's 1984 Super Bowl advert, artificial general intelligence, autonomous vehicles, backpropagation, Bernie Sanders, Big Tech, Boston Dynamics, Cambridge Analytica, Charles Babbage, Claude Shannon: information theory, cognitive dissonance, computer age, computer vision, Computing Machinery and Intelligence, dark matter, deep learning, DeepMind, Demis Hassabis, Douglas Hofstadter, driverless car, Elon Musk, en.wikipedia.org, folksonomy, Geoffrey Hinton, Gödel, Escher, Bach, I think there is a world market for maybe five computers, ImageNet competition, Jaron Lanier, job automation, John Markoff, John von Neumann, Kevin Kelly, Kickstarter, license plate recognition, machine translation, Mark Zuckerberg, natural language processing, Nick Bostrom, Norbert Wiener, ought to be enough for anybody, paperclip maximiser, pattern recognition, performance metric, RAND corporation, Ray Kurzweil, recommendation engine, ride hailing / ride sharing, Rodney Brooks, self-driving car, sentiment analysis, Silicon Valley, Singularitarianism, Skype, speech recognition, Stephen Hawking, Steve Jobs, Steve Wozniak, Steven Pinker, strong AI, superintelligent machines, tacit knowledge, tail risk, TED Talk, the long tail, theory of mind, There's no reason for any individual to have a computer in his home - Ken Olsen, trolley problem, Turing test, Vernor Vinge, Watson beat the top human players on Jeopardy!, world market for maybe five computers

For Searle, the strong AI claim would be that “the appropriately programmed digital computer does not just simulate having a mind; it literally has a mind.”13 In contrast, in Searle’s terminology, weak AI views computers as tools to simulate human intelligence and does not make any claims about them “literally” having a mind.14 We’re back to the philosophical question I was discussing with my mother: Is there a difference between “simulating a mind” and “literally having a mind”? Like my mother, Searle believes there is a fundamental difference, and he argued that strong AI is impossible even in principle.15 The Turing Test Searle’s article was spurred in part by Alan Turing’s 1950 paper, “Computing Machinery and Intelligence,” which had proposed a way to cut through the Gordian knot of “simulated” versus “actual” intelligence. Declaring that “the original question ‘Can a machine think?’ is too meaningless to deserve discussion,” Turing proposed an operational method to give it meaning. In his “imitation game,” now called the Turing test, there are two contestants: a computer and a human.

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Lorica, “What Is Artificial Intelligence?,” O’Reilly, June 20, 2016, www.oreilly.com/ideas/what-is-artificial-intelligence. 10.  S. Pinker, “Thinking Does Not Imply Subjugating,” in What to Think About Machines That Think, ed. J. Brockman (New York: Harper Perennial, 2015), 5–8. 11.  A. M. Turing, “Computing Machinery and Intelligence,” Mind 59, no. 236 (1950): 433–60. 12.  J. R. Searle, “Minds, Brains, and Programs,” Behavioral and Brain Sciences 3, no. 3 (1980): 417–24. 13.  J. R. Searle, Mind: A Brief Introduction (Oxford: Oxford University Press, 2004), 66. 14.  The terms strong AI and weak AI have also been used to mean something more like general AI and narrow AI.

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This harks back to what Alan Turing called “Lady Lovelace’s objection,” named for Lady Ada Lovelace, a British mathematician and writer who worked with Charles Babbage on developing the Analytical Engine, a nineteenth-century proposal for a (never completed) programmable computer. Turing quotes from Lady Lovelace’s writings: “The Analytical Engine has no pretensions to originate anything. It can do whatever we know how to order it to perform.” A. M. Turing, “Computing Machinery and Intelligence,” Mind 59, no. 236 (1950): 433–60.   7.  Karl Sims website, accessed Dec. 18, 2018, www.karlsims.com.   8.  D. Cope, Virtual Music: Computer Synthesis of Musical Style (Cambridge, Mass.: MIT Press, 2004).   9.  Quoted in G. Johnson, “Undiscovered Bach? No, a Computer Wrote It,” New York Times, Nov. 11, 1997. 10.  

The Price of Tomorrow: Why Deflation Is the Key to an Abundant Future by Jeff Booth

3D printing, Abraham Maslow, activist fund / activist shareholder / activist investor, additive manufacturing, AI winter, Airbnb, Albert Einstein, AlphaGo, Amazon Web Services, artificial general intelligence, augmented reality, autonomous vehicles, basic income, bitcoin, blockchain, Bretton Woods, business intelligence, butterfly effect, Charles Babbage, Claude Shannon: information theory, clean water, cloud computing, cognitive bias, collapse of Lehman Brothers, Computing Machinery and Intelligence, corporate raider, creative destruction, crony capitalism, crowdsourcing, cryptocurrency, currency manipulation / currency intervention, dark matter, deep learning, DeepMind, deliberate practice, digital twin, distributed ledger, Donald Trump, Elon Musk, fiat currency, Filter Bubble, financial engineering, full employment, future of work, game design, gamification, general purpose technology, Geoffrey Hinton, Gordon Gekko, Great Leap Forward, Hyman Minsky, hype cycle, income inequality, inflation targeting, information asymmetry, invention of movable type, Isaac Newton, Jeff Bezos, John Maynard Keynes: Economic Possibilities for our Grandchildren, John von Neumann, Joseph Schumpeter, late fees, low interest rates, Lyft, Maslow's hierarchy, Milgram experiment, Minsky moment, Modern Monetary Theory, moral hazard, Nelson Mandela, Network effects, Nick Bostrom, oil shock, OpenAI, pattern recognition, Ponzi scheme, quantitative easing, race to the bottom, ride hailing / ride sharing, self-driving car, software as a service, technoutopianism, TED Talk, the long tail, the scientific method, Thomas Bayes, Turing test, Uber and Lyft, uber lyft, universal basic income, winner-take-all economy, X Prize, zero-sum game

But he was also an early believer that the human brain was in large part a digital computing machine, and therefore that computers could be made to have intelligence—to think. In 1950, he published a paper titled “Computing Machinery and Intelligence” where he proposed a test called the imitation game, now commonly referred to as the Turing test. In the test, a human evaluator would have a conversation with two others, one being a machine and one a human, and the test would be passed when the human evaluator could not distinguish between the human and machine—in short, when humans can’t distinguish artificial from real intelligence. Around the same time that Turing was publishing “Computing Machinery and Intelligence,” another eminent thinker named Claude Shannon (1916–2001) was breaking barriers that enabled many of the advances in computers and artificial intelligence that we now take for granted.

Einstein's Fridge: How the Difference Between Hot and Cold Explains the Universe by Paul Sen

Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, anthropic principle, anti-communist, Bletchley Park, British Empire, Brownian motion, Claude Shannon: information theory, Computing Machinery and Intelligence, cosmic microwave background, cosmological constant, Ernest Rutherford, heat death of the universe, invention of radio, Isaac Newton, James Watt: steam engine, John von Neumann, Khan Academy, Kickstarter, Richard Feynman, seminal paper, Stephen Hawking, traveling salesman, Turing complete, Turing test

But Baby and its successors pioneered concepts such as random-access memory (RAM) that are essential to all modern computers. Turing played a crucial role by testing these machines’ capabilities by running ever-more-complex software on them. Inspired by this firsthand experience of the world’s first computers, in 1950 Turing wrote a now-famous paper in the philosophy journal Mind entitled “Computing Machinery and Intelligence.” In it he presented a series of arguments in favor of the idea that machines would one day be able to think as well as or even better than humans. In this paper he introduced “the imitation game,” the idea that if a computer provides answers that are indistinguishable from those that a human might provide to a given series of questions, the computer should for all intents and purposes be treated as human.

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The head of the daisy: See “The Mathematical Daisy” by Robert Dixon, New Scientist, December 17, 1981. Turing played a crucial role: See chapter 6 of Turing Guide by Copeland; chapter 9 of The Essential Turing by B. Jack Copeland; and Manchester University website http://curation.cs.manchester.ac.uk/computer50/www.computer50.org/mark1/new.baby.html. “Computing Machinery and Intelligence”: The article first appeared in Mind 59 (1950). “The Chemical Basis of Morphogenesis”: The article first appeared in Philosophical Transactions of the Royal Society of London, Series B 237 (1952–54). Turing considered it his best work: See an unpublished short story by Turing at the Turing Digital Archive, maintained by King’s College Cambridge, ref.

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See also telephone systems link between thermodynamics and, 167 Shannon’s experience with, 170, 174 SIGSALY encryption in, 173–74, 202 Turing’s experience with, 206 compression, in data networks, 182 compressors, in refrigeration, 112, 164–65 computers IBM’s changes over time to, 193 mathematical calculations using, 171 Shannon’s experience with, 171, 172 thermodynamic cost of a bit in, 194–97 transistors and heat generation by, 184–85, 193, 195 Turing’s analysis of pattern formation in morphogenesis and, 209–10, 212 Turing’s paper on intelligence and, 204–5 Turing’s Universal Machine and, 201, 204 “Computing Machinery and Intelligence” (Turing), 204–5 conduction, in heat flow, 133, 137 conservation of energy. See also first law of thermodynamics Clausius’s thought experiment using ideal engine and refrigerator and, 55–58, 253 Einstein’s E = mc2 equation on, x, 152–54 Helmholtz’s tract on Kraft and, 47–49, 51–52, 106, 154 Joule’s research and, 28, 30, 154 Noether’s theorem on, 157–59 symmetry and, 159 Thomson’s paper on, 59–60 Conservatory of Arts and Crafts, Paris, 6, 7, 8, 9 convection, in heat flow, 133, 137 coolants, in refrigeration, 111–12, 162, 163, 164, 165 Copenhagen group, 160 cosmic microwave background radiation, 158 cotton-manufacturing industry, 2, 23–24 creation of universe Boltzmann brain theory and, 130 Boltzmann’s creation moment in, 126, 127–30 random fluctuation hypothesis on, 129–30 cryptography, 169, 203 Shannon’s early experience with, 170 Turing’s reputation in, 173–74, 202–4 Dalton, John, 24 Dancer, John Benjamin, 30 dark reaction, in photosynthesis, 122–23 Darwin, Charles, 70–73, 107 age of earth and evolution by natural selection theory of, 70–71 reaction to Thomson’s objection to, 72 Thomson’s critiques of, 71–72, 73 data networks, file compression and digital redundancy in, 182 “Decrease of Entropy by Intelligent Beings, The” (Szilard), 190, 192 De l’Angleterre et des Anglais (Say), 5 Despretz, César-Mansuète, 44–45 developmental biology Turing’s contribution to, 200–201, 217 Turing’s morphogenesis paper and, 205–11, 215–16, 217 Dewar, Daniel, 84 Diesel, Rudolf, 20, 111 diffusion, in morphogenesis, 206, 209, 215 digital age processing of information in, 185 redundancy in file compression in, 182 dissipation of heat, Thompson’s paper on, 59–61 Drunkard’s Walk formula, 150 Dulong, Pierre Louis, 44–45 duty in steam engines Carnot’s theory on, 12 Newcomen engines and, 4, 10 earth age of.

Speaking Code: Coding as Aesthetic and Political Expression by Geoff Cox, Alex McLean

4chan, Amazon Mechanical Turk, augmented reality, bash_history, bitcoin, Charles Babbage, cloud computing, commons-based peer production, computer age, computer vision, Computing Machinery and Intelligence, crowdsourcing, dematerialisation, Donald Knuth, Douglas Hofstadter, en.wikipedia.org, Everything should be made as simple as possible, finite state, Free Software Foundation, Gabriella Coleman, Gödel, Escher, Bach, Hacker Conference 1984, Ian Bogost, Jacques de Vaucanson, language acquisition, Larry Wall, late capitalism, means of production, natural language processing, Neal Stephenson, new economy, Norbert Wiener, Occupy movement, packet switching, peer-to-peer, power law, Richard Stallman, Ronald Coase, Slavoj Žižek, social software, social web, software studies, speech recognition, SQL injection, stem cell, Stewart Brand, systems thinking, The Nature of the Firm, Turing machine, Turing test, Vilfredo Pareto, We are Anonymous. We are Legion, We are the 99%, WikiLeaks, Yochai Benkler

At the same Vocable Code 31 time, natural-language processing programs and other chatterbots offer good examples of the speechlike procedures mentioned thus far, as well as the apparent impossibility of duplicating actual speech. Intelligence To demonstrate believability, a machine would be required to possess some kind of intelligence that reflects the capacity for human reasoning, in parallel to turning mere voice sounds into proper speech that expresses human gentility. In a paper of 1950, “Computing Machinery and Intelligence,” Alan Turing made the claim that computers would be capable of imitating human intelligence, or more precisely the human capacity for rational thinking. He set out what become commonly known as the “Turing test” to examine whether a machine is able to respond convincingly to an input with an output similar to a human’s.48 The contemporary equivalent, CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart), turns this idea around, so that the software has to decide whether it is dealing with a human or a script.49 Perhaps it is the lack of speech that makes this software appear crude by comparison, as human intelligence continues to be associated with speech as a marker of reasoned semantic processing.

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See Wikipedia entry, available at http://en.wikipedia.org/wiki/Wolfgang_von_Kempelen% 27s_Speaking_Machine. 43. Rée, I See a Voice, 258. 44. Ong, Orality and Literacy, 86. 45. See http://www.omniglot.com/writing/korean.htm. 46. Rée, I See a Voice, 262. 47. George Bernard Shaw, Pygmalion (1916). Also see Ovid’s Metamorphoses, book X. 48. Alan Turing, “Computing Machinery and Intelligence” (1950), in Noah Wardrip-Fruin and Nick Montfort, eds., The New Media Reader (Cambridge, MA: MIT Press, 2003), 49–64. 49. See http://www.captcha.net/. 50. John R. Searle, “Minds, Brains, and Programs,” Behavioral and Brain Sciences 3 (1980): 417. 51. Ibid., 418. 52. Diane Proudfoot, “Wittgenstein’s Anticipation of the Chinese Room,” in John Preston and Mark Bishop, eds., Views into the Chinese Room: New Essays on Searle and Artificial Intelligence (Oxford: Clarendon Press, 2002), 168. 53.

The Information: A History, a Theory, a Flood by James Gleick

Ada Lovelace, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, AltaVista, bank run, bioinformatics, Bletchley Park, Brownian motion, butterfly effect, Charles Babbage, citation needed, classic study, Claude Shannon: information theory, clockwork universe, computer age, Computing Machinery and Intelligence, conceptual framework, crowdsourcing, death of newspapers, discovery of DNA, Donald Knuth, double helix, Douglas Hofstadter, en.wikipedia.org, Eratosthenes, Fellow of the Royal Society, Gregor Mendel, Gödel, Escher, Bach, Henri Poincaré, Honoré de Balzac, index card, informal economy, information retrieval, invention of the printing press, invention of writing, Isaac Newton, Jacquard loom, Jaron Lanier, jimmy wales, Johannes Kepler, John von Neumann, Joseph-Marie Jacquard, Lewis Mumford, lifelogging, Louis Daguerre, machine translation, Marshall McLuhan, Menlo Park, microbiome, Milgram experiment, Network effects, New Journalism, Norbert Wiener, Norman Macrae, On the Economy of Machinery and Manufactures, PageRank, pattern recognition, phenotype, Pierre-Simon Laplace, pre–internet, quantum cryptography, Ralph Waldo Emerson, RAND corporation, reversible computing, Richard Feynman, Rubik’s Cube, Simon Singh, Socratic dialogue, Stephen Hawking, Steven Pinker, stochastic process, talking drums, the High Line, The Wisdom of Crowds, transcontinental railway, Turing machine, Turing test, women in the workforce, yottabyte

♦ “A BRAIN CONSISTING OF RANDOMLY CONNECTED IMPRESSIONAL SYNAPSES”: Ibid., 110. ♦ “THINK OF THE BRAIN AS A TELEGRAPHIC RELAY”: “Brain and Behavior,” Comparative Psychology Monograph, Series 103 (1950), in Warren S. McCulloch, Embodiments of Mind (Cambridge, Mass.: MIT Press, 1965), 307. ♦ “I PROPOSE TO CONSIDER THE QUESTION”: Alan M. Turing, “Computing Machinery and Intelligence,” Minds and Machines 59, no. 236 (1950): 433–60. ♦ “THE PRESENT INTEREST IN ‘THINKING MACHINES’ ”: Ibid., 436. ♦ “SINCE BABBAGE’S MACHINE WAS NOT ELECTRICAL”: Ibid., 439. ♦ “IN THE CASE THAT THE FORMULA IS NEITHER PROVABLE NOR DISPROVABLE”: Alan M. Turing, “Intelligent Machinery, A Heretical Theory,” unpublished lecture, c. 1951, in Stuart M.

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Turing, “Intelligent Machinery, A Heretical Theory,” unpublished lecture, c. 1951, in Stuart M. Shieber, ed., The Turing Test: Verbal Behavior as the Hallmark of Intelligence (Cambridge, Mass.: MIT Press, 2004), 105. ♦ THE ORIGINAL QUESTION, “CAN MACHINES THINK?”: Alan M. Turing, “Computing Machinery and Intelligence,” 442. ♦ “THE IDEA OF A MACHINE THINKING”: Claude Shannon to C. Jones, 16 June 1952, Manuscript Div., Library of Congress, by permission of Mary E. Shannon. ♦ “PSYCHOLOGIE IS A DOCTRINE WHICH SEARCHES OUT”: Translated in William Harvey, Anatomical Exercises Concerning the Motion of the Heart and Blood (London, 1653), quoted in “psychology, n,” draft revision Dec. 2009, OED Online, Oxford University Press, http://dictionary.oed.com/cgi/entry/50191636

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♦ “IN TURNING OUR VIEWS”: Charles Babbage, The Ninth Bridgewater Treatise, 44. ♦ “THE ART OF PHOTOGENIC DRAWING”: Nathaniel Parker Willis, “The Pencil of Nature: A New Discovery,” The Corsair 1, no. 5 (April 1839): 72. ♦ “IN FACT, THERE IS A GREAT ALBUM OF BABEL”: Ibid., 71. ♦ “THE SYSTEM OF THE ‘UNIVERSE AS A WHOLE’ ”: Alan M. Turing, “Computing Machinery and Intelligence,” Minds and Machines 59, no. 236 (1950): 440. ♦ “SUCH A BLAZE OF KNOWLEDGE AND DISCOVERY”: H. G. Wells, A Short History of the World (San Diego: Book Tree, 2000), 97. ♦ “THE ROMANS BURNT THE BOOKS OF THE JEWS”: Isaac Disraeli, Curiosities of Literature (London: Routledge & Sons, 1893), 17

The Secret War Between Downloading and Uploading: Tales of the Computer as Culture Machine by Peter Lunenfeld

Albert Einstein, Andrew Keen, anti-globalists, Apple II, Berlin Wall, British Empire, Brownian motion, Buckminster Fuller, Burning Man, business cycle, business logic, butterfly effect, Charles Babbage, computer age, Computing Machinery and Intelligence, creative destruction, crowdsourcing, cuban missile crisis, Dissolution of the Soviet Union, don't be evil, Douglas Engelbart, Douglas Engelbart, Dynabook, East Village, Edward Lorenz: Chaos theory, Fairchild Semiconductor, Fall of the Berlin Wall, folksonomy, Francis Fukuyama: the end of history, Frank Gehry, Free Software Foundation, Grace Hopper, gravity well, Guggenheim Bilbao, Herman Kahn, Honoré de Balzac, Howard Rheingold, Ian Bogost, invention of movable type, Isaac Newton, Ivan Sutherland, Jacquard loom, Jane Jacobs, Jeff Bezos, John Markoff, John von Neumann, Jon Ronson, Kickstarter, Mark Zuckerberg, Marshall McLuhan, Mercator projection, Metcalfe’s law, Mother of all demos, mutually assured destruction, Neal Stephenson, Nelson Mandela, Network effects, new economy, Norbert Wiener, PageRank, pattern recognition, peer-to-peer, planetary scale, plutocrats, post-materialism, Potemkin village, RFID, Richard Feynman, Richard Stallman, Robert Metcalfe, Robert X Cringely, Schrödinger's Cat, Search for Extraterrestrial Intelligence, seminal paper, SETI@home, Silicon Valley, Skype, social bookmarking, social software, spaced repetition, Steve Ballmer, Steve Jobs, Steve Wozniak, technological determinism, Ted Nelson, the built environment, the Cathedral and the Bazaar, The Death and Life of Great American Cities, the medium is the message, Thomas L Friedman, Turing machine, Turing test, urban planning, urban renewal, Vannevar Bush, walkable city, Watson beat the top human players on Jeopardy!, William Shockley: the traitorous eight

This trifle, inspired at least in part by the renown of Christopher’s uncle Lytton Strachey’s 1918 portrait of a generation, Eminent Victorians, is the product of a stored program computer, and as such may well be the first aesthetic object produced by the ancestors of the culture machine. The love letter generator’s intentional blurring of the boundary between human and nonhuman is directly related to one of the foundational memes of artificial intelligence: the still-provocative Turing Test. In “Computing Machinery and Intelligence,” a seminal paper from 1950, Turing created a thought experiment. He posited a person holding a textual conversation on any topic with an unseen correspondent. If the person believes he or she is communicating with another person, but is in reality conversing with a machine, then that machine has passed the Turing Test.

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., 174 CNN, 58 Cobain, Kurt, 62 Code breaking, 17–18 Cold war, 101 Cole, Nat King, 62 Commercial culture, 4–5, 8 bespoke futures and, 98, 102, 108, 120, 132–134 culture machine and, 153–156, 167, 170, 172, 175–177 copyright and, 54, 88–95, 123, 164, 166, 173, 177 Mickey Mouse Protection Act and, 90 open source and, 36, 61, 69, 74–75, 91–92, 116, 121–126, 144, 170– 173, 177, 189n12 propaganda and, 124 scenario planning and, 111–119 stickiness and, 23, 28–31, 37 unimodernism and, 41, 69 Web n.0 and, 82–86 Commercial syndrome, 85–86 Communism, 97–98, 103 Compact discs (CDs), 2, 48, 53 Complex City (Simon), 39 “Computable Numbers, On” (Turing), 18 Computer Data Systems, 145 Computers, xi. See also specific model 200 INDEX Warriors and, 146–147 World War II and, 146 “Computing Machinery and Intelligence” (Turing), 19 Conran Shop, 46 Constructivism, 117 Consumption, 1 balance and, 13 best use and, 13–14 capitalism and, 4, 66, 75, 97–100, 104–105 commercial networks and, 4–5 cultural diabetes and, 3–5 patio potato and, 9–10, 13 personal, 35 production and, 13 Slow Food and, 5–7 supersizing and, 3–4 take-home, 3 television and, 8–9 viral distribution and, 30, 56, 169 wants vs. needs and, 4, 13, 37, 57 Continuous partial attention, 34 Conversation, 13 Copyleft, 91 Copyright bespoke futures and, 123 development of computer and, 164, 166, 173, 177 Mickey Mouse Protection Act and, 90 open source and, 36, 61, 69, 74–75, 91–92, 116, 121–126, 144, 170– 173, 177, 189n12 public domain and, 91 unimodernism and, 54 U.S.

Thinking Machines: The Inside Story of Artificial Intelligence and Our Race to Build the Future by Luke Dormehl

"World Economic Forum" Davos, Ada Lovelace, agricultural Revolution, AI winter, Albert Einstein, Alexey Pajitnov wrote Tetris, algorithmic management, algorithmic trading, AlphaGo, Amazon Mechanical Turk, Apple II, artificial general intelligence, Automated Insights, autonomous vehicles, backpropagation, Bletchley Park, book scanning, borderless world, call centre, cellular automata, Charles Babbage, Claude Shannon: information theory, cloud computing, computer vision, Computing Machinery and Intelligence, correlation does not imply causation, crowdsourcing, deep learning, DeepMind, driverless car, drone strike, Elon Musk, Flash crash, Ford Model T, friendly AI, game design, Geoffrey Hinton, global village, Google X / Alphabet X, Hans Moravec, hive mind, industrial robot, information retrieval, Internet of things, iterative process, Jaron Lanier, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Kickstarter, Kodak vs Instagram, Law of Accelerating Returns, life extension, Loebner Prize, machine translation, Marc Andreessen, Mark Zuckerberg, Menlo Park, Mustafa Suleyman, natural language processing, Nick Bostrom, Norbert Wiener, out of africa, PageRank, paperclip maximiser, pattern recognition, radical life extension, Ray Kurzweil, recommendation engine, remote working, RFID, scientific management, self-driving car, Silicon Valley, Skype, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, social intelligence, speech recognition, Stephen Hawking, Steve Jobs, Steve Wozniak, Steven Pinker, strong AI, superintelligent machines, tech billionaire, technological singularity, The Coming Technological Singularity, The Future of Employment, Tim Cook: Apple, Tony Fadell, too big to fail, traumatic brain injury, Turing machine, Turing test, Vernor Vinge, warehouse robotics, Watson beat the top human players on Jeopardy!

‘And it is highly unlikely without a yet-undiscovered novel approach to simulating an AI that any chatbot technology employed today could ever fool an experienced chatbot creator into believing they possess [artificial] general intelligence.’ Turing wasn’t particularly concerned with the metaphysical question of whether a machine can actually think. In his famous 1950 essay, ‘Computing Machinery and Intelligence’, he described it as ‘too meaningless to deserve discussion’. Instead he was interested in getting machines to perform activities that would be considered intelligent if they were carried out by a human. It is this idea that the MIT psychoanalyst and computer researcher Sherry Turkle talks about when she says that we should take computers at ‘interface value’.

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page_id=1438 17 Vincent, James, ‘Google Contact Lenses: Tech Giant Licenses Smart Contact Lens Technology to Help Diabetics and Glasses Wearers’, Independent, 15 July 2014: independent.co.uk/life-style/gadgets-and-tech/google-licenses-smart-contact-lens-technology-to-help-diabetics-and-glasses-wearers-9607368.html 18 https://www.fitbit.com/content/assets/wellness/FitbitWellness_InfoSheet.pdf 19 Olson, Parmy and Tilley, Aaron, ‘The Quantified Other: Nest and Fitbit Chase a Lucrative Side Business’, Forbes, 5 May 2014: forbes.com/sites/parmyolson/2014/04/17/the-quantified-other-nest-and-fitbit-chase-a-lucrative-side-business/#6c5408e15403 20 Dormehl, Luke, ‘This Algorithm Predicts a Neighborhood’s Crime Rate Using Google Street View’, Fast Company, 6 October 2014: fastcolabs.com/3036677/this-algorithm-knows-your-neighborhood-better-than-you-do Chapter 4: How May I Serve You? 1 Sundman, John, ‘Artificial Stupidity’, Salon, 26 February 2003: salon.com/2003/02/26/loebner_part_one/ 2 Turing, Alan, ‘Computing Machinery and Intelligence’, 1950: csee.umbc.edu/courses/471/papers/turing.pdf 3 Lee, Dave, ‘Tay: Microsoft issues apology over racist chatbot fiasco,’ BBC News, 25 March 2016: bbc.co.uk/news/technology-35902104 4 facebook.com/zuck/posts/10102577175875681 5 Isaacson, Walter, Steve Jobs (New York: Simon & Schuster, 2011). 6 Remarkably, John Sculley’s prediction for the arrival of a Siri-like AI assistant was correct right down to the month it first shipped with the iPhone 4s. 7 Keenan, Thomas, Technocreep: The Surrender of Privacy and the Capitalization of Intimacy (Vancouver: Greystone Books, 2014). 8 oddisgood.com/pages/cd-clippy.html 9 Wilcox, Joe, ‘Microsoft Tool “Clippy” Gets Pink Slip’, CNET, 2 January 2002: news.cnet.com/2100-1001-255671.html 10 Wasserman, Todd, ‘Wozniak: Siri Was Better Before Apple Bought It’, Mashable UK, 15 June 2012: mashable.com/2012/06/15/wozniak-on-siri/#W9rFoovbVaqT 11 Wortham, Jenna, ‘Will Google’s Personal Assistant Be Creepy or Cool?’

12 Bytes: How We Got Here. Where We Might Go Next by Jeanette Winterson

"Margaret Hamilton" Apollo, "World Economic Forum" Davos, 3D printing, Ada Lovelace, Airbnb, Albert Einstein, Alignment Problem, Amazon Mechanical Turk, Anthropocene, Apollo 11, Apple's 1984 Super Bowl advert, artificial general intelligence, Asilomar, augmented reality, autonomous vehicles, basic income, Big Tech, bitcoin, Bletchley Park, blockchain, Boston Dynamics, call centre, Cambridge Analytica, Capital in the Twenty-First Century by Thomas Piketty, cashless society, Charles Babbage, computer age, Computing Machinery and Intelligence, coronavirus, COVID-19, CRISPR, cryptocurrency, dark matter, Dava Sobel, David Graeber, deep learning, deskilling, digital rights, discovery of DNA, Dominic Cummings, Donald Trump, double helix, driverless car, Elon Musk, fake news, flying shuttle, friendly AI, gender pay gap, global village, Grace Hopper, Gregor Mendel, hive mind, housing crisis, Internet of things, Isaac Newton, Jacquard loom, James Hargreaves, Jeff Bezos, Johannes Kepler, John von Neumann, Joseph-Marie Jacquard, Kickstarter, Large Hadron Collider, life extension, lockdown, lone genius, Mark Zuckerberg, means of production, microdosing, more computing power than Apollo, move fast and break things, natural language processing, Nick Bostrom, Norbert Wiener, off grid, OpenAI, operation paperclip, packet switching, Peter Thiel, pink-collar, Plato's cave, public intellectual, QAnon, QWERTY keyboard, Ray Kurzweil, rewilding, ride hailing / ride sharing, Rutger Bregman, Sam Altman, self-driving car, sharing economy, Sheryl Sandberg, Shoshana Zuboff, Silicon Valley, Skype, Snapchat, SoftBank, SpaceX Starlink, speech recognition, spinning jenny, stem cell, Stephen Hawking, Steve Bannon, Steve Jobs, Steven Levy, Steven Pinker, superintelligent machines, surveillance capitalism, synthetic biology, systems thinking, tech billionaire, tech worker, TED Talk, telepresence, telepresence robot, TikTok, trade route, Turing test, universal basic income, Virgin Galactic, Watson beat the top human players on Jeopardy!, women in the workforce, Y Combinator

Turing, with his famous Turing Test, believed that a machine would, one day, prove indistinguishable from human intelligence. He believed that day would come sooner than it has done – he suggested the year 2000 – but he was sure that a machine could display human-level interpersonal skills. Minsky credited his own enthusiasm for developing an AI system that can think for itself to Turing’s 1950 paper Computing Machinery and Intelligence. Read it now, and to me the most interesting part of a fascinating paper that includes telepathy and hive-mind networking is what Turing called Lady Lovelace’s Objection – replying directly to the dead genius who 100 years earlier had concluded that Babbage’s Analytical Engine, while being theoretically able to write novels and compose music (a big insight in 1843!)

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Anyway, it’s v good.) Gnostic Know-How The Society of Mind, Marvin Minsky, 1986 2001: A Space Odyssey, Arthur C. Clarke, 1968 Probability and the Weighing of Evidence, I. J. Good, 1950 Our Final Invention: Artificial Intelligence and the End of the Human Era, James Barrat, 2013 ‘Computing Machinery and Intelligence’ (article), Alan Turing, 1950 The Gnostic Gospels, Elaine Pagels, 1979 The Nag Hammadi Scriptures, edited by Marvin W. Meyer, 2007 Mysterium Coniunctionis, Carl Jung, 1955 On the Origin of Species, Charles Darwin, 1859 The Odyssey, Homer He Ain’t Heavy, He’s My Buddha An Introduction to Cybernetics, W.

The Future of the Professions: How Technology Will Transform the Work of Human Experts by Richard Susskind, Daniel Susskind

23andMe, 3D printing, Abraham Maslow, additive manufacturing, AI winter, Albert Einstein, Amazon Mechanical Turk, Amazon Robotics, Amazon Web Services, Andrew Keen, Atul Gawande, Automated Insights, autonomous vehicles, Big bang: deregulation of the City of London, big data - Walmart - Pop Tarts, Bill Joy: nanobots, Blue Ocean Strategy, business process, business process outsourcing, Cass Sunstein, Checklist Manifesto, Clapham omnibus, Clayton Christensen, clean water, cloud computing, commoditize, computer age, Computer Numeric Control, computer vision, Computing Machinery and Intelligence, conceptual framework, corporate governance, creative destruction, crowdsourcing, Daniel Kahneman / Amos Tversky, data science, death of newspapers, disintermediation, Douglas Hofstadter, driverless car, en.wikipedia.org, Erik Brynjolfsson, Evgeny Morozov, Filter Bubble, full employment, future of work, Garrett Hardin, Google Glasses, Google X / Alphabet X, Hacker Ethic, industrial robot, informal economy, information retrieval, interchangeable parts, Internet of things, Isaac Newton, James Hargreaves, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joseph Schumpeter, Khan Academy, knowledge economy, Large Hadron Collider, lifelogging, lump of labour, machine translation, Marshall McLuhan, Metcalfe’s law, Narrative Science, natural language processing, Network effects, Nick Bostrom, optical character recognition, Paul Samuelson, personalized medicine, planned obsolescence, pre–internet, Ray Kurzweil, Richard Feynman, Second Machine Age, self-driving car, semantic web, Shoshana Zuboff, Skype, social web, speech recognition, spinning jenny, strong AI, supply-chain management, Susan Wojcicki, tacit knowledge, TED Talk, telepresence, The Future of Employment, the market place, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Tragedy of the Commons, transaction costs, Turing test, Two Sigma, warehouse robotics, Watson beat the top human players on Jeopardy!, WikiLeaks, world market for maybe five computers, Yochai Benkler, young professional

In summary, we suggest that it should indeed be feasible to make some practical expertise available on a commons basis, and this need not require the elaborate or extensive granting of exclusivity to future providers. Lurking behind this conclusion and much that we say throughout this chapter is our clear preference for what we call the ‘liberation’ of expertise. In the remainder of the book, we explain why we take this position. 1 Three influential publications are Alan Turing, ‘Computing Machinery and Intelligence’, Mind, 59: 236 (1950), 433–60; Margaret Boden, Artificial Intelligence and Natural Man (1977); and Douglas Hoftstadter and Daniel Dennett (eds.), The Mind’s I (1982). The term ‘artificial intelligence’ was coined by John McCarthy in 1955. 2 John Searle, ‘Watson Doesn’t Know It Won on “Jeopardy!”’

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Also relevant is the Human Brain Project at <https://www.humanbrainproject.eu/en_GB> (accessed 23 March 2015). 10 Quoted in Searle, Minds, Brains and Science, 30. 11 For a discussion of relevant science-fiction work, see Jon Bing, ‘The Riddle of the Robots’, Journal of International Commercial Law and Technology, 3: 3 (2008), 197–206. 12 Nick Bostrom, Superintelligence (2014). 13 See Turing, ‘Computing Machinery and Intelligence’. In 2014 it was claimed by researchers at Reading University that their computer program had passed the Turing Test by convincing judges it was a 13-year-old boy. See Izabella Kaminska, ‘More Work to Do on the Turing Test’, Financial Times, 13 June 2014 <http://www.ft.com> (accessed 23 March 2015). 14 See Richard P.

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Topol, Eric, The Patient Will See You Now (New York: Basic Books, 2015). Trefis Team, ‘eBay: The Year 2013 in Review’, 26 Dec. 2013 <http://www.forbes.com/sites/greatspeculations/2013/12/26/ebay-the-year-2013-in-review/> (accessed 24 March 2015). Tuck, Richard, Free Riding (Cambridge, Mass.: Harvard University Press, 2008). Turing, Alan, ‘Computing Machinery and Intelligence’, Mind, 59: 236 (1950), 433–60. Turkle, Sherry, Alone Together (New York: Basic Books, 2011). Tversky, Amos, and Daniel Kahneman, ‘Judgment under Uncertainty: Heuristics and Biases’, Science, 185: 4157 (1974), 1124–31. Twilley, Nicola, ‘Artificial Intelligence Goes to the Arcade’, New Yorker, 25 Feb. 2015.

Ways of Being: Beyond Human Intelligence by James Bridle

Ada Lovelace, Airbnb, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Anthropocene, Any sufficiently advanced technology is indistinguishable from magic, autonomous vehicles, behavioural economics, Benoit Mandelbrot, Berlin Wall, Big Tech, Black Lives Matter, blockchain, Californian Ideology, Cambridge Analytica, carbon tax, Charles Babbage, cloud computing, coastline paradox / Richardson effect, Computing Machinery and Intelligence, corporate personhood, COVID-19, cryptocurrency, DeepMind, Donald Trump, Douglas Hofstadter, Elon Musk, experimental subject, factory automation, fake news, friendly AI, gig economy, global pandemic, Gödel, Escher, Bach, impulse control, James Bridle, James Webb Space Telescope, John von Neumann, Kickstarter, Kim Stanley Robinson, language acquisition, life extension, mandelbrot fractal, Marshall McLuhan, microbiome, music of the spheres, negative emissions, Nick Bostrom, Norbert Wiener, paperclip maximiser, pattern recognition, peer-to-peer, planetary scale, RAND corporation, random walk, recommendation engine, self-driving car, SETI@home, shareholder value, Silicon Valley, Silicon Valley ideology, speech recognition, statistical model, surveillance capitalism, techno-determinism, technological determinism, technoutopianism, the long tail, the scientific method, The Soul of a New Machine, theory of mind, traveling salesman, trolley problem, Turing complete, Turing machine, Turing test, UNCLOS, undersea cable, urban planning, Von Neumann architecture, wikimedia commons, zero-sum game

This error infects all our reckonings with artificial intelligence. For example, despite never being used by serious AI researchers, the Turing Test remains the most widely understood way of thinking about the capabilities of AI in the public consciousness. It was proposed by Alan Turing in a 1950 paper, ‘Computing Machinery and Intelligence’. Turing thought that instead of questioning whether computers were truly intelligent, we could at least establish that they appeared intelligent. Turing called his method for doing this ‘the imitation game’: he imagined a set-up in which an interviewer interrogated two hidden interlocutors – one human, one machine – and tried to tell which was which.

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The creation of these images was supported by Nome Gallery, as part of Failing to Distinguish Between a Tractor Trailer and the Bright White Sky, an exhibition held in Berlin, April–July 2017. For more on the exhibition, visit https://nomegallery.com/exhibitions/failing-to-distinguish-between-a-tractor-trailer-and-the-bright-white-sky/. 5. A. M. Turing, ‘Computing Machinery and Intelligence’, Mind, 49 (1950), pp. 433–60. 6. H. F. Harlow, H. Uehling and A. H. Maslow, ‘Comparative Behavior of Primates. I. Delayed Reaction Tests on Primates from the Lemur to the Orang-Outan’, Journal of Comparative Psychology, 13(3) (1932), pp. 313–43. In the original study, all the apes have familiar as well as scientific names, some of dubious provenance.

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Ross 181–3, 185 aspens 77 astrobiology 87 atomic bomb 224–5 Augustin, Regynald 156 Australopithecus 88 Author of the Acacia Seeds, The 169–71 automatic machine see Turing machine Autonomous Trap 26–7, 26, 204 autonomous vehicles 23–6, 65, 275 avocados 108 Babbage, Charles 30 baboons 32, 52–55, 64, 74 bacteria 17, 87–8, 104–10, 236–7, 248, 300 badgers 291 Barabási, Albert-László 81 Barad, Karen 84–6, 130, 249 Basilicata 138, 140–43 bears 1, 89–90, 92, 266, 290–91, 293–4 beavers 256 BeeAdHoc (computer programme) 262 beech 125, 142 Beer, Stafford 184–91, 211, 214–15, 230 bees 145, 187, 258–62 Bergson, Henri 279 Berners-Lee, Tim 81 birch 60, 118, 124, 138, 279 Black Language 168 Black Lives Matter 155 Blake, William 16 Blas, Zach 208 Boeing X-37 136 Bonner, John Tyler 238–9 bonobos 37, 50, 98 Boran (people) 146 Bornmuellera tymphaea 309 Boulez, Pierre 229 Boulle, Marcellin 90 Bouvet, Joachim 234 bow-wow theory 148 Brainfuck (programming language) 161–2 Brassica juncea 310 Bruniquel cave 92 buen vivir 268 cacti 64, 235, 294 Cage, John 227–35, 241, 242, 312 Cambridge Analytica 155 cantu a tenòre 148 capuchin monkeys 163 Caputo, Francesco 143 Caputo, Matteo 143 caribou 120 Carrol, Lewis 180 Carson, Rachel 12, 15 Castro, Eduardo Viveiros de 18 caterpillars 65 Cecilia (chimpanzee) 265 cedars 138 cephalopods 47–51 CERN 81 Charlotte (gibbon) 32 Chassenée, Bartholomew 252 Chaucer, Geoffrey 152 Chernobyl 293 Chesapeake Bay Model 202, 203, 204 chestnuts 61, 118 Children of Time 49 chimpanzees 36–37, 50, 55–6, 88, 98, 145 choice machine see oracle machine Christ Stopped at Eboli 140 Christmas Island 293, 295 Chua, Leon O. 194 Chucho (bear) 266 Churchill, Winston 18 Citizens’ Assembly 243–5 Clarke, Arthur C. 158 climate change 5–6, 121–4, 242–5, 282, 301–2 climate modelling 78–9 Cloud (computing) 111–12, 158–9 Cochran, William 285, 297 cockatoos 163 Cockroach Controlled Mobile Robot see Roachbot cockroaches 212, 258 cognitive diversity 246–8 Colossus (computer) 220 ‘Computing Machinery and Intelligence’ 29 Conway’s Game of Life 161 corn 75 Corraro, Rosina 143 cougars 290 Covid-19 114 cows 140, 143, 149, 265, 302 crabs 48, 195–7, 256, 293, 293–5, 293, 307, 312 cuckoos 118 cuttlefish 47, 49 Cybernetic Factory 185, 186, 189–90 Cybernetic Serendipity 231 cybernetics 181–90, 214 Dallol see Danakil Depression Danakil Depression 86–8, 104 Daphnia 188–9, 191, 198 Darwin, Charles 12, 34–6, 72, 89, 127–30, 129, 235, 239 Darwin, Francis 127–30, 129 De Anima 122 de Martino, Ernesto 141–2 de Waal, Frans 39 Debord, Guy 24 decentralization 49, 208–10, 213, 280 DeepMind 8, 275 deer 65, 77, 258, 290–93, 298–9, 299 Delphi 174, 177 demilitarized zone (DMZ) 292 Denisova Cave 96 denisovans 96–8, 100 Denny (denisovan) 97, 100 Descartes, René 16 Descent of Man, The 36 Dimkaroski, Ljubem 90 ding-dong theory 147 Dinkinesh (Australopithecus) 88 distributed computing 209 Divje Babe 90–91, 91 DNA 95–7, 103–7 dodder vine 75 dogs 147–8, 163, 302 spinal dog 184, 212 Dolphin Embassy 165–6, 165 dolphins 37–8, 41–2, 145, 166, 170, 263, 286 Doolittle, Ford 109–10 Duchamp, Marcel 128–31, 129 ducks 256 earthquakes 302–3 Ebonics 168 EDVAC (computer) 223, 230 Eglash, Ron 156 elephants 34, 38–9, 40–44, 41, 64, 250–51, 263–5, 278, 291–2, 296, 312 Elmer (robot tortoise) 180 Elsie (robot tortoise) 180 email apnea 155 Emojicode (programming language) 161, 173 endosymbiosis 108 ENIAC (computer) 225, 230 Epirus 1–5, 308–9, 311 Epstein, Jean 138 ERNIE (computer) 220–22, 221, 222, 226, 236 Euglena 188–91 Euler, Leonhard 81 European Green Belt 292 evolution 12, 54, 67, 71, 96, 102, 146, 164, 235, 241, 247, 311 of computers 222 convergent evolution 42, 51, 231, 262 Darwin’s theories 36, 89, 128, 132, 235, 256 process 107–12 randomness 235–40 tree of evolution 47, 50–51, 96, 100 Explanation of Binary Arithmetic 234 Facebook 154, 275 ethics 277 gender categories 111–12, 208 language applications 167–9, 173 Fensom, Harry 220 finches 132, 235, 239 firs 60, 142, 279 Flowers, Tommy 220 Folding@home 209 Forte, Giovanni 143, 144 fossil fuels 3–6 Franklin, Benjamin 248 Fredkin, Edward 195 Frisch, Karl von 259 fungi 11, 17, 60–63, 78–82, 106–8, 128, 192, 290 Gagliano, Monica 71–5, 127, 303, 319 Gaia (goddess) 174, 190, 215 Gaia theory 190 Gallup, Gordon G., Jr 36, 39 Ganges River 266 gannets 132 Gates, Bill 8, 275 Gaup, Ingor Ántte Áilu 150 Gebru, Timnit 277 geese 164, 170 General Morphology of Organisms 11 ghost populations 88, 98 gibbons 32–4, 33, 38–9, 42, 52, 64, 312 goats 1, 140, 143, 148, 293, 302 Göbekli Tepe 93–4, 93 Godfrey-Smith, Peter 50 Gombe Stream National Park 55 gomphotheres 108 Goodall, Jane 55–6, 263 Google 8, 111, 154, 211, 241, 269, 275 ethics 156, 277 oil and gas applications 5–6 language applications 163, 167, 169 gorillas 44–7, 44, 98 Grant, Peter 236 Grant, Rosemary 236 graph theory 81 Great Chain of Being 123 Greece 1–5, 114, 216 Greenpeace 5 Griffith, Frederick 105 grouse 150 Grumpy (elephant) 40 Guantánamo Bay 296 Gudynas, Eduardo 268 gulls 133, 256 habeas corpus 41, 264–6, 270, 296 Hadza (people) 146 Haeckel, Ernst 11–12, 105, 239–40, 240 Hagenback, Karl 254 Half-Earth Project 305–6 Happy (elephant) 39–41, 41, 263–5, 273, 296 Haudenosaunee see Iroquois Confederacy Hawira, Turama 267 hawks 256 hawthorn 118 Heritage Foundation 277 Herodotus 3 Hertz, Garnet 212–13 Hilbert, David 178 Hiller, Lejaren 230–31, 233 Hofstadter, Douglas 262 Holmes, Rob 203 homeostat, 181–3, 182, 187, 206, 215 honey 143–6 honeyguides 143–6, 164 horizontal gene transfer 105–7 hornbeam 118 Hotbits 222 HPSCHD (composition) 230–32 Hribal, Jason 253–5 Hubble Space Telescope 135 HUGO Gene Nomenclature Committee 154 Humboldt, Alexander von 239 Huxley, Aldous 113, 208 hyenas 257 hyperaccumulators 308–10 I Ching 228–231, 228, 234, 242 IBM 4–5 ICARUS (animal tracking) 284, 300, 302–3 ICHING (computer programme) 230–31 iguanas 296 ILLIAC (computer) 230 IM see instant messaging Inky (octopus) 48 instant messaging 152–3, 172–3 Institute of Contemporary Art 231 International Meridian Conference 116 International Space Station (ISS) 284 internet 80–82 Iroquois Confederacy 248 Island (novel) 113 Israeli Defense Forces 295 jackdaws 163 jaguars 294 jaguarundi cats 294 James Webb Space Telescope 135 jellyfish 180 Jenny (orang-utan) 34–6, 35 joik 149–50, 312 Keyhole (satellite) 136 Khan-Dossos, Navine 140 khoomei 149 Kidder, Tracy 117 King, William 89 King Solomon’s Ring 163 klepsydra 216–17, 217 klerotereion 218–19, 243 Koko (gorilla) 44, 45, 47 Konstantinou, Maria 309 Kowalsczewski, Bruno 91 Kropotkin, Peter 256–7, 279 Kunstforum der Natur 239, 240 Lack, David 132–3, 285 Land Art 203 Landsat 137, 137–9, 139 lapwing 256 laurel 174 Lavarand 222 Le Guin, Ursula 13, 169–71 Leakey, Louis 56 Lederberg, Esther 105 Lederberg, Joshua 105 Legg, Shane 8, 275 lemurs 163 Leptoplax emarginata 309 Levi, Carlo 141 lichens 107, 171 Liebniz, Gottfried 234 Lindauer, Martin 259–60, 284 lions 77, 257 Lord, Rexford 285, 297 Lorenz, Konrad 163–4 Lovelace, Ada 30 Lovelock, James 190 LUCA (last universal common ancestor) 103 Lucy (Australopithecus) see Dinkinesh Lukyanov, Valdimir 199–200, 199 lynx 290 macaques 42–4, 64, 254 machine learning 30, 63 Mandelbrot, Benoit 102 mangroves 138 Mansfield, Lord (William Murray) 264 Margulis, Lyn 108, 110, 112 Marino, Lori 38 Marsham, Robert 118 Marsham record 118–21 Matera 140 Maxine (elephant) 39 Maxwell, Sarah 301 McLuhan, Marshall 18 memristors 124–5 Merleau-Ponty, Maurice 150 Metropolis, Nick 225 mice 187 Michael (gorilla) 45, 47 Microsoft 5, 8, 154 Million Random Digits with 100,000 Normal Deviates, A 226, 226 mimosa 71–4, 127–8, 192, 195, 303 Mimosa pudica see mimosa Ministry for the Future, The 282 mirror test 36–46, 181 Mississippi Basin Model 201–2, 204 Mondrian, Piet 161 MONIAC 205, 205–7 Monte Carlo 225–7, 242 Moore, Michael 135 Morgan-Mar, David 161 moths 180 mouse-eared cress see rock cress Muir, John 11 Müller, Max 146–8 Müller, Urban 161 Museum of the Ancient Agora 216–18 Musk, Elon 8, 158, 275 Mutual Aid: A Factor in Evolution 256 mycorrhiza 60–62, 77–9, 81–2, 194 mynah birds 113 NASA see National Aeronautics and Space Administration Nasser, Ramsey 160–61 National Aeronautics and Space Administration (NASA) 135, 137–9, 284, 286 National Oceanic and Atmospheric Administration (NOAA) 137–8, 286 National Reconnaissance Office (NRO) 135 neanderthals 89–92, 94–8, 100 network theory 81 neural networks 24–5, 25, 82, 166, 275, 312 NEXRAD (Next-generation radar) 133, 134 Niassa National Reserve 143 nightingales 118 nightjars 118 non-binary activism 208 computing 208–9, 213, 312 identity 112 Nonhuman Rights Project 41, 263–5, 296 nutation 128, 197 oak 118–19, 124 ocelots 294 octopuses 111, 47–51, 73, 197, 209 oil industry 4–6 oleander 174 On the Origin of Species 11, 36, 89 Ook!

Artificial Unintelligence: How Computers Misunderstand the World by Meredith Broussard

"Susan Fowler" uber, 1960s counterculture, A Declaration of the Independence of Cyberspace, Ada Lovelace, AI winter, Airbnb, algorithmic bias, AlphaGo, Amazon Web Services, autonomous vehicles, availability heuristic, barriers to entry, Bernie Sanders, Big Tech, bitcoin, Buckminster Fuller, Charles Babbage, Chris Urmson, Clayton Christensen, cloud computing, cognitive bias, complexity theory, computer vision, Computing Machinery and Intelligence, crowdsourcing, Danny Hillis, DARPA: Urban Challenge, data science, deep learning, Dennis Ritchie, digital map, disruptive innovation, Donald Trump, Douglas Engelbart, driverless car, easy for humans, difficult for computers, Electric Kool-Aid Acid Test, Elon Musk, fake news, Firefox, gamification, gig economy, global supply chain, Google Glasses, Google X / Alphabet X, Greyball, Hacker Ethic, independent contractor, Jaron Lanier, Jeff Bezos, Jeremy Corbyn, John Perry Barlow, John von Neumann, Joi Ito, Joseph-Marie Jacquard, life extension, Lyft, machine translation, Mark Zuckerberg, mass incarceration, Minecraft, minimum viable product, Mother of all demos, move fast and break things, Nate Silver, natural language processing, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, One Laptop per Child (OLPC), opioid epidemic / opioid crisis, PageRank, Paradox of Choice, payday loans, paypal mafia, performance metric, Peter Thiel, price discrimination, Ray Kurzweil, ride hailing / ride sharing, Ross Ulbricht, Saturday Night Live, school choice, self-driving car, Silicon Valley, Silicon Valley billionaire, speech recognition, statistical model, Steve Jobs, Steven Levy, Stewart Brand, TechCrunch disrupt, Tesla Model S, the High Line, The Signal and the Noise by Nate Silver, theory of mind, traumatic brain injury, Travis Kalanick, trolley problem, Turing test, Uber for X, uber lyft, Watson beat the top human players on Jeopardy!, We are as Gods, Whole Earth Catalog, women in the workforce, work culture , yottabyte

There are different ways to react to this news: you can be sad that the thing you dreamed of is not possible—or you can be excited and embrace what is possible when artificial devices (computers) work in sync with truly intelligent beings (humans). I prefer the latter approach. Notes 1. Silver et al., “Mastering the Game of Go with Deep Neural Networks and Tree Search,” 484. 2. Turing, “Computing Machinery and Intelligence.” 3. Searle, “Artificial Intelligence and the Chinese Room.” 4 Hello, Data Journalism We are at an exciting moment, when every field has taken a computational turn. We now have computational social science, computational biology, computational chemistry, or digital humanities; visual artists use languages like Processing to create multimedia art; 3-D printing allows sculptors to push further into physical possibilities with art.

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Turban, Stephen, Laura Freeman, and Ben Waber. “A Study Used Sensors to Show That Men and Women Are Treated Differently at Work.” Harvard Business Review, October 23, 2017. https://hbr.org/2017/10/a-study-used-sensors-to-show-that-men-and-women-are-treated-differently-at-work. Turing, A. M. “Computing Machinery and Intelligence.” Mind 59, no. 236 (1950): 433–460. Turner, Fred. From Counterculture to Cyberculture: Stewart Brand, the Whole Earth Network, and the Rise of Digital Utopianism. Chicago: University of Chicago Press, 2008. Tversky, Amos, and Daniel Kahneman. “Availability: A Heuristic for Judging Frequency and Probability.”

Rule of the Robots: How Artificial Intelligence Will Transform Everything by Martin Ford

AI winter, Airbnb, algorithmic bias, algorithmic trading, Alignment Problem, AlphaGo, Amazon Mechanical Turk, Amazon Web Services, artificial general intelligence, Automated Insights, autonomous vehicles, backpropagation, basic income, Big Tech, big-box store, call centre, carbon footprint, Chris Urmson, Claude Shannon: information theory, clean water, cloud computing, commoditize, computer age, computer vision, Computing Machinery and Intelligence, coronavirus, correlation does not imply causation, COVID-19, crowdsourcing, data is the new oil, data science, deep learning, deepfake, DeepMind, Demis Hassabis, deskilling, disruptive innovation, Donald Trump, Elon Musk, factory automation, fake news, fulfillment center, full employment, future of work, general purpose technology, Geoffrey Hinton, George Floyd, gig economy, Gini coefficient, global pandemic, Googley, GPT-3, high-speed rail, hype cycle, ImageNet competition, income inequality, independent contractor, industrial robot, informal economy, information retrieval, Intergovernmental Panel on Climate Change (IPCC), Internet of things, Jeff Bezos, job automation, John Markoff, Kiva Systems, knowledge worker, labor-force participation, Law of Accelerating Returns, license plate recognition, low interest rates, low-wage service sector, Lyft, machine readable, machine translation, Mark Zuckerberg, Mitch Kapor, natural language processing, Nick Bostrom, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, Ocado, OpenAI, opioid epidemic / opioid crisis, passive income, pattern recognition, Peter Thiel, Phillips curve, post scarcity, public intellectual, Ray Kurzweil, recommendation engine, remote working, RFID, ride hailing / ride sharing, Robert Gordon, Rodney Brooks, Rubik’s Cube, Sam Altman, self-driving car, Silicon Valley, Silicon Valley startup, social distancing, SoftBank, South of Market, San Francisco, special economic zone, speech recognition, stealth mode startup, Stephen Hawking, superintelligent machines, TED Talk, The Future of Employment, The Rise and Fall of American Growth, the scientific method, Turing machine, Turing test, Tyler Cowen, Tyler Cowen: Great Stagnation, Uber and Lyft, uber lyft, universal basic income, very high income, warehouse automation, warehouse robotics, Watson beat the top human players on Jeopardy!, WikiLeaks, women in the workforce, Y Combinator

Recent advances in AI have led prominent figures like Elon Musk and the late Stephen Hawking to warn of scenarios remarkably similar to what Butler worried about more than 150 years ago. Opinions differ as to exactly when artificial intelligence became a serious field of study. I would mark the origin as 1950. In that year, the brilliant mathematician Alan Turing published a scientific paper entitled “Computing Machinery and Intelligence” that asked the question “Can machines think?”2 In his paper Turing invented a test, based on a game that was popular at parties, which is still the most commonly cited method for determining if a machine can be considered to be genuinely intelligent. Turing, born in London in 1912, did groundbreaking work on the theory of computation and the nature of algorithms, and is generally regarded as the founding father of computer science.

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“CORD-19: COVID-19 Open Research Dataset,” Semantic Scholar, accessed May 6, 2020, www.semanticscholar.org/cord19. CHAPTER 4. THE QUEST TO BUILD INTELLIGENT MACHINES 1. Samuel Butler, “Darwin among the machines, a letter to the editors,” The Press, Christchurch, New Zealand, June 13, 1863. 2. Alan Turing, “Computing machinery and intelligence,” Mind, volume LIX, issue 236, pp. 433–460 (October 1950). 3. J. McCarthy, M. L. Minsky, N. Rochester and C. E. Shannon, “A proposal for the Dartmouth Summer Research Project on Artificial Intelligence,” August 31, 1955, raysolomonoff.com/dartmouth/boxa/dart564props.pdf. 4. Brad Darrach, “Meet Shaky, the first electronic person: The fascinating and fearsome reality of a machine with a mind of its own,” LIFE, November 20, 1970, p. 58D. 5.

The Simulation Hypothesis by Rizwan Virk

3D printing, Albert Einstein, AlphaGo, Apple II, artificial general intelligence, augmented reality, Benoit Mandelbrot, bioinformatics, butterfly effect, Colossal Cave Adventure, Computing Machinery and Intelligence, DeepMind, discovery of DNA, Dmitri Mendeleev, Elon Musk, en.wikipedia.org, Ernest Rutherford, game design, Google Glasses, Isaac Newton, John von Neumann, Kickstarter, mandelbrot fractal, Marc Andreessen, Minecraft, natural language processing, Nick Bostrom, OpenAI, Pierre-Simon Laplace, Plato's cave, quantum cryptography, quantum entanglement, Ralph Waldo Emerson, Ray Kurzweil, Richard Feynman, Schrödinger's Cat, Search for Extraterrestrial Intelligence, Silicon Valley, Stephen Hawking, Steve Jobs, Steve Wozniak, technological singularity, TED Talk, time dilation, Turing test, Vernor Vinge, Zeno's paradox

The History and Rise of AI The Turing Test Figure 13: A visual depiction of the Turing Test 12 The Turing Test is more of a milestone than a definition, since most AI today cannot pass this test. Alan Turing, considered by many to be the father of modern computer science, conjectured a time when a machine would exhibit intelligent behaviors. In his 1950 paper titled “Computing Machinery and Intelligence,” Turing took on the question of whether a machine could “think.” Since it was very difficult to say what “thinking” would mean, Turing devised a party game to tell if a computer was “intelligent” enough in conversation that it could fool a human. In this party game, an interrogator (in Figure 13, party C) was behind the curtain, and he was “interrogating” two parties: A and B.

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., 96 classical physics, 29, 125, 161, 166, 283–84, 288 classical vs. relativistic physics, 122–24 Cline, Ernest, 56 clock-speed and quantized time, computer simulations, 171–73 Close Encounters of the Third Kind, 232, 276 cloud of probabilities, 127 collective dream, 187–88 Colossal Cave Adventure, 27–29, 32, 34 Colossal Cave Adventure, map of, 29f computation, 18–19 computation, and other sciences, 287 computation, evidence of, 256–57, 267–68 overview, 246–47 computation in nature, evidence of, 263–66 computational irreducibility, 18, 79, 266 computer simulations clock-speed and quantized time, 171–73 . see also ancestor simulation; Great Simulation; Simulation Argument; simulation hypothesis; Simulation Point computer-generated imagery (CGI) techniques, 64–66 “Computing Machinery and Intelligence” (Turing, 1950), 85 conditional rendering, evidence of, 253–55 conflict resolution, 173 conscious players, people as, 114–15 consciousness, 148 as digital informaion, 17–18 as information and computation, 82 consciousness, defined, 115–16 consciousness, digital vs. spiritual, 116–18 consciousness and metaphysical experiments, 249–250 consciousness as information, 104–5 consciousness transference, 198–99 Constraints on the Universe as a Numerical Simulation (Beane, Davoudi and Savage), 255 Copenhagen interpretation, 131 Cosmos, 251 CPUs (central processing units), 137 . see also GPUs/CPUs Creative Labs, 62 Crichton, Michael, 71–72 Crick, Francis, 116 Crowther, Will, 27 Curry, Adam, 76 D Dalai Lama, 207 Data, Star Trek: The Next Generation, 95–96, 115 Davoudi, Zohreh, 255 deathmatch mode, 43–44 Deep Blue, 86 DeepMind, 86–88, 94, 98 déjà vu, 240–41 delayed-choice double slit experiment, 145f delayed-choice experiment, 143–46 delayed-measurement experiment, 146 DELTA t (T), 174 Department of Defense (DOD), 232 Descartes, René, 11 DeWitt, Bryce, 149 dharma, 191 Dick, Leslie “Tessa” B., 8–9 Dick, Philip K., 274, 289 and alternate realities, 8–9 computer simulations and variables, 19 and implanted memories, 77–78 life as computer-generated simulation, 78–79 Metz Sci-Fi Convention, 1977, 2 question of reality vs. fiction, 71–72 simulated worlds, 80 speculative technologies, 53 digital consciousness, 116–18 digital film resolution, 65 digital immortality, 82, 105 digital psychiatrist, 88–89, 161 directed graph, 153–55 Discrete World, 165–66 Do Androids Dream of Electric Sheep, 9 Donkey Kong, 1 Doom, 43–44, 43f, 59–60, 137–38 DOTA 2, 87, 94 dot-matrix printers (2D), 69–71 double slit experiment, 128–29, 129f downloadable consciousness, 54, 101–4, 198, 207, 281 downloadable consciousness and seventh yoga, 197–99 Dr.

Possible Minds: Twenty-Five Ways of Looking at AI by John Brockman

AI winter, airport security, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Alignment Problem, AlphaGo, artificial general intelligence, Asilomar, autonomous vehicles, basic income, Benoit Mandelbrot, Bill Joy: nanobots, Bletchley Park, Buckminster Fuller, cellular automata, Claude Shannon: information theory, Computing Machinery and Intelligence, CRISPR, Daniel Kahneman / Amos Tversky, Danny Hillis, data science, David Graeber, deep learning, DeepMind, Demis Hassabis, easy for humans, difficult for computers, Elon Musk, Eratosthenes, Ernest Rutherford, fake news, finite state, friendly AI, future of work, Geoffrey Hinton, Geoffrey West, Santa Fe Institute, gig economy, Hans Moravec, heat death of the universe, hype cycle, income inequality, industrial robot, information retrieval, invention of writing, it is difficult to get a man to understand something, when his salary depends on his not understanding it, James Watt: steam engine, Jeff Hawkins, Johannes Kepler, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Kevin Kelly, Kickstarter, Laplace demon, Large Hadron Collider, Loebner Prize, machine translation, market fundamentalism, Marshall McLuhan, Menlo Park, military-industrial complex, mirror neurons, Nick Bostrom, Norbert Wiener, OpenAI, optical character recognition, paperclip maximiser, pattern recognition, personalized medicine, Picturephone, profit maximization, profit motive, public intellectual, quantum cryptography, RAND corporation, random walk, Ray Kurzweil, Recombinant DNA, Richard Feynman, Rodney Brooks, self-driving car, sexual politics, Silicon Valley, Skype, social graph, speech recognition, statistical model, Stephen Hawking, Steven Pinker, Stewart Brand, strong AI, superintelligent machines, supervolcano, synthetic biology, systems thinking, technological determinism, technological singularity, technoutopianism, TED Talk, telemarketer, telerobotics, The future is already here, the long tail, the scientific method, theory of mind, trolley problem, Turing machine, Turing test, universal basic income, Upton Sinclair, Von Neumann architecture, Whole Earth Catalog, Y2K, you are the product, zero-sum game

Writing at a time when vacuum tubes were still the primary electronic building blocks and there were only a few actual computers in operation, Norbert Wiener imagined the future we now contend with in impressive detail and with few clear mistakes. Alan Turing’s famous 1950 article “Computing Machinery and Intelligence,” in the philosophy journal Mind, foresaw the development of AI, and so did Wiener, but Wiener saw further and deeper, recognizing that AI would not just imitate—and replace—human beings in many intelligent activities but change human beings in the process: We are but whirlpools in a river of ever-flowing water.

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., 49, 240–53 AI safety concerns, 242–43 background and overview of work of, 240–41 conventional computers versus bio-electronic hybrids, 246–48 equal rights, 248–49 ethical rules for intelligent machines, 243–44 free will of machines, and rights, 250–51 genetic red lines, 251–52 human manipulation of humans, 244–46, 252 humans versus nonhumans and hybrids, treatment of, 249–53 non-Homo intelligences, fair and safe treatment of, 247–48 rights for nonhumans and hybrids, 249–53 science versus religion, 243–44 self-consciousness of machines, and rights, 250–51 technical barriers/red lines, malleability of, 244–46 transhumans, rights of, 252–53 clinical (subjective) method of prediction, 233, 234–35 Colloquy of Mobiles (Pask), 259 Colossus: The Forbin Project (film), 242 competence of superintelligent AGI, 85 computational theory of mind, 102–3, 129–33, 222 computer learning systems Bayesian models, 226–28 cooperative inverse-reinforcement learning (CIRL), 30–31 deep learning (See deep learning) human learning, similarities to, 11 reality blueprint, need for, 16–17 statistical, model-blind mode of current, 16–17, 19 supervised learning, 148 unsupervised learning, 225 Computer Power and Human Reason (Weizenbaum), 48–49, 248 computer virus, 61 “Computing Machinery and Intelligence” (Turing), 43 conflicts among hybrid superintelligences, 174–75 controllable-agent designs, 31–32 control systems beyond human control (control problem) AI designed as tool and not as conscious agent, 46–48, 51–53 arguments against AI risk (See risk posed by AI, arguments against) Ashby’s Law and, 39, 179, 180 cognitive element in, xx–xxi Dyson on, 38–39, 40 Macy conferences, xx–xxi purpose imbued in machines and, 23–25 Ramakrishnan on, 183–86 risk of superhuman intelligence, arguments against, 25–29 Russell on templates for provably beneficial AI, 29–32 Tallinn on, 93–94 Wiener’s warning about, xviii–xix, xxvi, 4–5, 11–12, 22–23, 35, 93, 104, 172 Conway, John Horton, 263 cooperative inverse-reinforcement learning (CIRL), 30–31 coordination problem, 137, 138–41 corporate/AI scenario, in relation of machine superintelligences to hybrid superintelligences, 176 corporate superintelligences, 172–74 credit-assignment function, 196–200 AI and, 196–97 humans, applied to, 197–200 Crick, Francis, 58, 66 culture in evolution, selecting for, 198–99 curiosity, and AI risk denial, 96 Cybernetic Idea, xv cybernetics, xv–xxi, 3–7, 102–4, 153–54, 178–80, 194–95, 209–10, 256–57 “Cybernetic Sculpture” exhibition (Tsai), 258, 260–61 “Cybernetic Serendipity” exhibition (Reichardt), 258–59 Cybernetics (Wiener), xvi, xvii, 3, 5, 7, 56 “Cyborg Manifesto, A” (Haraway), 261 data gathering and exploitation, computation platforms used for, 61–63 Dawkins, Richard, 243 Declaration of Helsinki, 252 declarative design, 166–67 Deep Blue, 8, 184 Deep Dream, 211 deep learning, 184–85 bottom-up, 224–26 Pearl on lack of transparency in, and limitations of, 15–19 reinforcement learning, 128, 184–85, 225–26 unsupervised learning, 225 visualization programs, 211–13 Wiener’s foreshadowing of, 9 Deep-Mind, 184–85, 224, 225, 262–63 Deleuze, Gilles, 256 Dennett, Daniel C., xxv, 41–53, 120, 191 AI as “helpless by themselves,” 46–48 AI as tool, not colleagues, 46–48, 51–53 background and overview of work of, 41–42 dependence on new tools and loss of ability to thrive without them, 44–46 gap between today’s AI and public’s imagination of AI, 49 humanoid embellishment of AI, 49–50 intelligent tools versus artificial conscious agents, need for, 51–52 operators of AI systems, responsibilities of, 50–51 on Turing Test, 46–47 on Weizenbaum, 48–50 on Wiener, 43–45 Descartes, René, 191, 223 Desk Set (film), 270 Deutsch, David, 113–24 on AGI risks, 121–22 background and overview of work of, 113–14 creating AGIs, 122–24 developing AI with goals under unknown constraints, 119–21 innovation in prehistoric humans, lack of, 116–19 knowledge imitation of ancestral humans, understanding inherent in, 115–16 reward/punishment of AI, 120–21 Differential Analyzer, 163, 179–80 digital fabrication, 167–69 digital signal encoding, 180 dimensionality, 165–66 distributed Thompson sampling, 198 DNA molecule, 58 “Dollie Clone Series” (Hershman Leeson), 261, 262 Doubt and Certainty in Science (Young), xviii Dragan, Anca, 134–42 adding people to AI problem definition, 137–38 background and overview of work of, 134–35 coordination problem, 137, 138–41 mathematical definition of AI, 136 value-alignment problem, 137–38, 141–42 The Dreams of Reason: The Computer and the Rise of the Science of Complexity (Pagels), xxiii Drexler, Eric, 98 Dyson, Freeman, xxv, xxvi Dyson, George, xviii–xix, 33–40 analog and digital computation, distinguished, 35–37 background and overview of work of, 33–34 control, emergence of, 38–39 electronics, fundamental transitions in, 35 hybrid analog/digital systems, 37–38 on three laws of AI, 39–40 “Economic Possibilities for Our Grandchildren” (Keynes), 187 “Einstein, Gertrude Stein, Wittgenstein and Frankenstein” (Brockman), xxii emergence, 68–69 Emissaries trilogy (Cheng), 216–17 Empty Space, The (Brook), 213 environmental risk, AI risk as, 97–98 Eratosthenes, 19 Evans, Richard, 217 Ex Machina (film), 242 expert systems, 271 extreme wealth, 202–3 fabrication, 167–69 factor analysis, 225 Feigenbaum, Edward, xxiv Feynman, Richard, xxi–xxii Fifth Generation, xxiii–xxiv The Fifth Generation: Artificial Intelligence and Japan’s Computer Challenge to the World (Feigenbaum and McCorduck), xxiv Fodor, Jerry, 102 Ford Foundation, 202 Foresight and Understanding (Toulmin), 18–19 free will of machines, and rights, 250–51 Frege, Gottlob, 275–76 Galison, Peter, 231–39 background and overview of work of, 231–32 clinical versus objective method of prediction, 233–35 scientific objectivity, 235–39 Gates, Bill, 202 generative adversarial networks, 226 generative design, 166–67 Gershenfeld, Neil, 160–69 background and overview of work of, 160–61 boom-bust cycles in evolution of AI, 162–63 declarative design, 166–67 digital fabrication, 167–69 dimensionality problem, overcoming, 165–66 exponentially increasing amounts of date, processing of, 164–65 knowledge in AI systems, 164 scaling, and development of AI, 163–66 Ghahramani, Zoubin, 190 Gibson, William, 253 Go, 10, 150, 184–85 goal alignment.

I, Warbot: The Dawn of Artificially Intelligent Conflict by Kenneth Payne

Abraham Maslow, AI winter, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, AlphaGo, anti-communist, Any sufficiently advanced technology is indistinguishable from magic, artificial general intelligence, Asperger Syndrome, augmented reality, Automated Insights, autonomous vehicles, backpropagation, Black Lives Matter, Bletchley Park, Boston Dynamics, classic study, combinatorial explosion, computer age, computer vision, Computing Machinery and Intelligence, coronavirus, COVID-19, CRISPR, cuban missile crisis, data science, deep learning, deepfake, DeepMind, delayed gratification, Demis Hassabis, disinformation, driverless car, drone strike, dual-use technology, Elon Musk, functional programming, Geoffrey Hinton, Google X / Alphabet X, Internet of things, job automation, John Nash: game theory, John von Neumann, Kickstarter, language acquisition, loss aversion, machine translation, military-industrial complex, move 37, mutually assured destruction, Nash equilibrium, natural language processing, Nick Bostrom, Norbert Wiener, nuclear taboo, nuclear winter, OpenAI, paperclip maximiser, pattern recognition, RAND corporation, ransomware, risk tolerance, Ronald Reagan, self-driving car, semantic web, side project, Silicon Valley, South China Sea, speech recognition, Stanislav Petrov, stem cell, Stephen Hawking, Steve Jobs, strong AI, Stuxnet, technological determinism, TED Talk, theory of mind, TikTok, Turing machine, Turing test, uranium enrichment, urban sprawl, V2 rocket, Von Neumann architecture, Wall-E, zero-sum game

‘A cautionary tale on ambitious feats of AI: The Strategic Computing program’, War on the Rocks, 22 May 2020, https://warontherocks.com/2020/05/cautionary-tale-on-ambitious-feats-of-ai-the-strategic-computing-program/; and Roland, Alex, and Philip Shiman. Strategic Computing: DARPA and the Quest for Machine Intelligence, 1983–1993. Cambridge, Mass: MIT Press, 2002. 22. Lenat, Douglas B. ‘CYC: A large-scale investment in knowledge infrastructure’, Communications of the ACM 38, no. 11 (1995): 33–38. 23. Turing, Alan Mathison. ‘Computing machinery and intelligence’, Mind, Volume LIX, Issue 236, October 1950, pp. 433–460, https://doi.org/10.1093/mind/LIX.236.433. 24. Baard, Mark. ‘AI founder blasts modern research’, WIRED, 13 May 2003, https://www.wired.com/2003/05/ai-founder-blasts-modern-research/. 25. Nilsson, Quest for Artificial Intelligence, p. 323.

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‘Marines are building robotic war balls’, Defense One, 12 February 2015, https://www.defenseone.com/technology/2015/02/marines-are-building-robotic-war-balls/105258/. Turing, Alan Mathison. ‘On computable numbers, with an application to the Entscheidungsproblem.’ J. of Math 58, no. 345–363 (1936): 5. Turing, Alan Mathison. ‘Computing machinery and intelligence’, Mind, Volume LIX, Issue 236, October 1950, pp. 433–460, https://doi.org/10.1093/mind/LIX.236.433. Twilley, Nicola. ‘Seeing with your tongue,’ The New York Times, 8 May 2017, https://www.newyorker.com/magazine/2017/05/15/seeing-with-your-tongue. United States National Security Commission on Artificial Intelligence, ‘Draft Final Report,’ January 2021, https://www.nscai.gov/wp-content/uploads/2021/01/NSCAI-Draft-Final-Report-1.19.21.pdf.

Alone Together by Sherry Turkle

Albert Einstein, Columbine, Computing Machinery and Intelligence, fake news, Future Shock, global village, Hacker Ethic, helicopter parent, Howard Rheingold, industrial robot, information retrieval, Jacques de Vaucanson, Jaron Lanier, Joan Didion, John Markoff, Kevin Kelly, lifelogging, Loebner Prize, Marshall McLuhan, meta-analysis, mirror neurons, Nicholas Carr, Norbert Wiener, off-the-grid, Panopticon Jeremy Bentham, Paradox of Choice, Ralph Waldo Emerson, Rodney Brooks, Skype, social intelligence, stem cell, technological determinism, technoutopianism, The Great Good Place, the medium is the message, the strength of weak ties, theory of mind, Turing test, Vannevar Bush, Wall-E, warehouse robotics, women in the workforce, Year of Magical Thinking

See the Feldman Gallery’s Kelly Heaton page at www.feldmangallery.com/pages/artistsrffa/arthea01.html (accessed August 18, 2009). 9 Baird developed her thought experiment comparing how people would treat a gerbil, a Barbie, and a Furby for a presentation at the Victoria Institute, Gothenburg, Sweden, in 1999. 10 In Turing’s paper that argued the existence of intelligence if a machine could not be distinguished from a person, one scenario involved gender. In “Computing Machinery and Intelligence,” he suggested an “imitation game”: a man and then a computer pose as female, and the interrogator tries to distinguish them from a real woman. See Alan Turing, “Computing Machinery and Intelligence,” Mind 59, no. 236 (October 1950): 433-460. 11 Antonio Damasio, The Feeling of What Happens: Body and Emotion in the Making of Consciousness (New York: Harcourt, 1999). Since emotions are cognitive representations of body states, the body cannot be separated from emotional life, just as emotion cannot be separated from cognition. 12 There are online worlds and communities where people feel comfortable expressing love for Furbies and seriously mourning Tamagotchis.

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In 1950, he wrote, “It can also be maintained that it is best to provide the machine with the best sense organs that money can buy, and then teach it to understand and speak English. That process could follow the normal teaching of a child. Things would be pointed out and named, etc.” Alan Turing, “Computing Machinery and Intelligence,” Mind 59, no. 236 (October 1950): 433-460. 7 This branch of artificial intelligence (sometimes called “classical AI”) attempts to explicitly represent human knowledge in a declarative form in facts and rules. For an overview of AI and its schools that explores its relations to theories of mind, see Margaret Boden, Artificial Intelligence and Natural Man (1981; New York: Basic Books, 1990). 8 Hubert Dreyfus, “Why Computers Must Have Bodies in Order to Be Intelligent,” Review of Metaphysics 21, no. 1 (September 1967): 13-32.

Turing's Cathedral by George Dyson

1919 Motor Transport Corps convoy, Abraham Wald, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, anti-communist, Benoit Mandelbrot, Bletchley Park, British Empire, Brownian motion, cellular automata, Charles Babbage, cloud computing, computer age, Computing Machinery and Intelligence, Danny Hillis, dark matter, double helix, Dr. Strangelove, fault tolerance, Fellow of the Royal Society, finite state, Ford Model T, Georg Cantor, Henri Poincaré, Herman Kahn, housing crisis, IFF: identification friend or foe, indoor plumbing, Isaac Newton, Jacquard loom, John von Neumann, machine readable, mandelbrot fractal, Menlo Park, Murray Gell-Mann, Neal Stephenson, Norbert Wiener, Norman Macrae, packet switching, pattern recognition, Paul Erdős, Paul Samuelson, phenotype, planetary scale, RAND corporation, random walk, Richard Feynman, SETI@home, social graph, speech recognition, The Theory of the Leisure Class by Thorstein Veblen, Thorstein Veblen, Turing complete, Turing machine, Von Neumann architecture

Nigel Goldenfeld and Carl Woese, “Biology’s Next Revolution,” Nature, January 25, 2007, p. 369. 51. Nils Barricelli, in Paul S. Moorhead and Martin M. Kaplan, eds., Mathematical Challenges to the Neo-Darwinian Interpretation of Evolution: A Symposium Held at the Wistar Institute, April 25–26, 1966 (Philadelphia: Wistar Institute, 1966), p. 67; Alan Turing, “Computing Machinery and Intelligence,” Mind 59, no. 236 (October 1950): 456. 52. George Church, West Hollywood, Calif., July 26, 2009, EDGE Foundation, “A Short Course on Synthetic Genomics” (http://edge.org/​event/​master-classes/​the-edge-master-class-2008-a-short-course-on-synthetic-genomics). THIRTEEN: TURING’S CATHEDRAL 1.

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Turing, “Lecture to the London Mathematical Society on 20 February 1947,” pp. 23–24. 48. Turing, “Intelligent Machinery,” p. 2. 49. Turing, “Lecture to the London Mathematical Society on 20 February 1947,” p. 2. 50. Turing, “Intelligent Machinery,” p. 6. 51. Ibid. 52. Ibid., p. 18. 53. Turing, “Computing Machinery and Intelligence,” p. 456; Turing, “Intelligent Machinery,” p. 17. 54. I. J. Good to Sara Turing, December 9, 1956, AMT; Lyn Newman to Antoinette Esher, June 24, 1949, AMT; I. J. Good, “Ethical Machines,” prepared for the Tenth Machine Intelligence Workshop, Case Western Reserve University, April 20–25, 1981, unpublished draft, October 7, 1980, p. ix. 55.

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Alfvén, The Tale of the Big Computer, p. 125. 22. William C. Dement, “Ontogenetic Development of the Human Sleep-Dream Cycle,” Science 152, no. 3722 (April 29, 1966): 604. 23. Nathaniel Hawthorne, The House of the Seven Gables (Boston: Ticknor, Reed, and Fields, 1851), p. 283; Turing, “Computing Machinery and Intelligence,” p. 433. 24. Alfvén, The Tale of the Big Computer, p. 116. 25. Ibid., pp. 117–18. 26. Eva Wisten, personal communication, October 25, 2005, GBD. 27. Alfvén, The Tale of the Big Computer, p. 119. 28. Ibid., p. 126. EIGHTEEN: THE THIRTY-NINTH STEP 1. Klára von Neumann, The Computer. 2.

The Creativity Code: How AI Is Learning to Write, Paint and Think by Marcus Du Sautoy

3D printing, Ada Lovelace, Albert Einstein, algorithmic bias, AlphaGo, Alvin Roth, Andrew Wiles, Automated Insights, Benoit Mandelbrot, Bletchley Park, Cambridge Analytica, Charles Babbage, Claude Shannon: information theory, computer vision, Computing Machinery and Intelligence, correlation does not imply causation, crowdsourcing, data is the new oil, data science, deep learning, DeepMind, Demis Hassabis, Donald Trump, double helix, Douglas Hofstadter, driverless car, Elon Musk, Erik Brynjolfsson, Fellow of the Royal Society, Flash crash, Gödel, Escher, Bach, Henri Poincaré, Jacquard loom, John Conway, Kickstarter, Loebner Prize, machine translation, mandelbrot fractal, Minecraft, move 37, music of the spheres, Mustafa Suleyman, Narrative Science, natural language processing, Netflix Prize, PageRank, pattern recognition, Paul Erdős, Peter Thiel, random walk, Ray Kurzweil, recommendation engine, Rubik’s Cube, Second Machine Age, Silicon Valley, speech recognition, stable marriage problem, Turing test, Watson beat the top human players on Jeopardy!, wikimedia commons

Bartender gives them water because he is able to distinguish the boundary tones that dictate the grammatical function of homonyms in coda position, as well as pragmatic context. Joke posted on Twitter If you are going to be a writer it’s important that you understand language, or at least give the illusion of understanding it. So how good are machines at navigating human communication? The opening sentence of Alan Turing’s famous paper ‘Computing Machinery and Intelligence’ sets out the challenge: ‘I propose to consider the question “Can machines think?”’ This, Turing believed, was too general, so he refined his challenge: he wondered if a machine could be programmed so that if a human were to engage it in conversation, its responses would be so convincing that the human could not tell it was talking to a machine.

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Ekhad 179 Shankar, Ravi 11 Shannon, Claude 19, 203 Shapley, Lloyd 57, 58, 61 Shelley, Percy Bysshe 281 Shinshu University 236 shogi 97 Siemens 110, 111 SIGGRAPH conference (1980) 115 Sigur Rós: ‘Óveður 228–9 Silver, David 33, 38, 39, 98 Simrock, Nikolaus 194 Sky Arts 290 Slater, David 108–9 Sloane, Neil 291–2 Smith, Alvy Ray 115 Smith, Zadie 303 Société des auteurs, compositeurs et éditeurs de musique (SACEM) 229–30 Socrates 165 songwriting 213–32; AIVA and 229–30; The Continuator and 218–21; ‘Daddy’s Car’ (first pop song written by AI) 223–4; emotion and 204–6; Eno and 229; Fantom app and 226–8; Flow Machine and 221–4, 222; Hello World (AI album) 224; jazz/improvisation and 213–14, 218–24, 298, 299; Jukedeck and 225–6; Markov chain and 214–18, 216, 217; Sigur Rós: ‘Óveður and 228–9; Spotify and fake artists 224–5; why we make music 230–1 Sony 116, 124; Computer Science Laboratory, Paris 214, 224, 271 Sophocles 165 Spain football team 55 spam filters 90–1 SPEAC 198–200, 198 Spielberg, Steven 115 Spotify 135, 224–5 square root 1; of minus one 12; of 2 163, 244 Stable Marriage Problem, The 57–61, 58, 59, 60 Stanford University 48, 196, 259; Law School 109 Star Trek: The Next Generation (Cause and Effect episode) 251 Steels, Luc 271–2 Stokes, Mark 77 Stoppard, Tom 99 storytelling 275–97, 305; Android Lloyd Webber and 290; Beyond the Fence (musical) and 290–1; Botnik and 284–6; Cambridge Analytica and 296; Cybernetic Poet and 280–2; Ferranti Mark 1 and 277–8; future of AI and 305–6; mathematical tales, generating new 291–3; MduS uses AI to compose section of this book 297; NaNoGenMo (National Novel Generation Month)/AI novels 282–3; news stories, AI generated 293–6; Oulipo (Ouvroir de littérature potentielle) 278–80; plagiarism and 297; PropperWryter and 290; Scheherazade-IF and 286–8, 306; ‘The Great Automatic Grammatizator’ (Dahl) and 276–7, 297; What If Machine (Whim) and 288–91 Strachey, Christopher 278 Stravinsky, Igor 204–6 string theory 171 Stuttgart Academy of Fine Art 126 Suleyman, Mustafa 25 supervised learning 95–6, 97, 137 surprise, creativity and 4, 8, 40, 65, 66, 102–3, 148, 168, 202, 241, 248–9 symmetries 3, 4, 10, 11, 18, 100, 102, 172, 175, 177, 187, 191–2, 208, 235, 250, 292 tabula rasa learning 73, 97, 98 Taylor, Richard 123, 124, 172 Theme Park 23 Thiel, Peter 25 Thomas, Rob 227–8 Tinguely, Jean 119 Tolstoy, Leo 105, 242, 243 Touchette, Hugo 55 Trebek, Alex 262 Trinity College, Cambridge 240 Trump, Donald 54, 258 Trybulec, Andrzej 236 Turing, Alan 2, 7, 8, 24, 66, 277, 278; ‘Computing Machinery and Intelligence’ 254 Turing Test 7, 38, 71, 200–2, 220–1, 239–41, 254–7, 258, 260, 273, 281, 282, 297 University College London 25 University of Alberta 236 University of California, San Diego 117 University of Manchester 277–8 University of Oregon 123, 201 University of Texas 88 Up (film) 115 Valéry, Paul 233 value, creativity and 4, 8, 12, 16, 17, 40–1, 102–3, 167–8, 238–9, 301, 304 Van Gogh, Vincent 16, 41, 126, 128, 131, 135, 136, 137, 138 Veenendaal, Albert van 220–1 Venice Biennale (1966) 117 Vinyals, Oriol 235, 236, 238 vision, computer 43, 70–80, 75, 93–4, 137–8, 143, 145, 212 visuals, code made 110–13 Voevodsky, Vladimir 181–5 Vogelkop gardener bowerbird 108 Vol Libre (‘Free Flight’) animation 114 Walsh, Toby 292 Warhol, Andy 107 Watson 261–8 Watson, Thomas J. 262 Weierstrass, Karl 7 Weizenbaum, Joseph 255, 256 Wells, H.

The Cultural Logic of Computation by David Golumbia

Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, American ideology, Benoit Mandelbrot, Bletchley Park, borderless world, business process, cellular automata, citizen journalism, Claude Shannon: information theory, computer age, Computing Machinery and Intelligence, corporate governance, creative destruction, digital capitalism, digital divide, en.wikipedia.org, finite state, folksonomy, future of work, Google Earth, Howard Zinn, IBM and the Holocaust, iterative process, Jaron Lanier, jimmy wales, John von Neumann, Joseph Schumpeter, late capitalism, Lewis Mumford, machine readable, machine translation, means of production, natural language processing, Norbert Wiener, One Laptop per Child (OLPC), packet switching, RAND corporation, Ray Kurzweil, RFID, Richard Stallman, semantic web, Shoshana Zuboff, Slavoj Žižek, social web, stem cell, Stephen Hawking, Steve Ballmer, Stewart Brand, strong AI, supply-chain management, supply-chain management software, technological determinism, Ted Nelson, telemarketer, The Wisdom of Crowds, theory of mind, Turing machine, Turing test, Vannevar Bush, web application, Yochai Benkler

In addition, there exists (in that same abstract space) a Turing machine whose operation is directly related to that of the brain; Chomsky’s approach and language show that he had read Turing (1936, 1937, 1950), and he was no doubt influenced by Turing’s mathematical and logical work as well.2 Putnam’s “Minds and Machines” proceeds along lines inspired at least in part by Wittgenstein and by Turing. Putnam wants to show that the traditional philosophical mind/body problem is soluble, in a Wittgensteinian sense—a problem that is an artifact of our language and that philosophical analysis can clear up, in the sense of “dissolve.” Putnam seems to be endorsing Turing’s method in “Computing Machinery and Intelligence,” namely, rejecting the question “can machines think?” by replacing it with a question about the way machines and human beings each use language. Since it explicitly invokes the operations of Turing machines at length and the way in which they use language to refer to themselves as entities, it is hard not to see the article as in some sense a response to and elaboration of Turing (1950).

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New York: Regan Books. Turing, Alan. 1936. “On Computable Numbers, with an Application to the Entscheidungsproblem.” Proceedings of the London Mathematical Society, Series 2, Volume 42 (1936–37), 230–265. ———. 1937. “Computability and λ-Definability.” The Journal of Symbolic Logic 2, 153–163. ———. 1950. “Computing Machinery and Intelligence.” Mind: A Quarterly Review of Psychology and Philosophy 59, Number 236 (October), 433–460. Turkle, Sherry. 1984. The Second Self: Computers and the Human Spirit. New York: Simon & Schuster. ———. 1995. Life on the Screen: Identity in the Age of the Internet. New York: Simon & Schuster.

Augmented: Life in the Smart Lane by Brett King

23andMe, 3D printing, additive manufacturing, Affordable Care Act / Obamacare, agricultural Revolution, Airbnb, Albert Einstein, Amazon Web Services, Any sufficiently advanced technology is indistinguishable from magic, Apollo 11, Apollo Guidance Computer, Apple II, artificial general intelligence, asset allocation, augmented reality, autonomous vehicles, barriers to entry, bitcoin, Bletchley Park, blockchain, Boston Dynamics, business intelligence, business process, call centre, chief data officer, Chris Urmson, Clayton Christensen, clean water, Computing Machinery and Intelligence, congestion charging, CRISPR, crowdsourcing, cryptocurrency, data science, deep learning, DeepMind, deskilling, different worldview, disruptive innovation, distributed generation, distributed ledger, double helix, drone strike, electricity market, Elon Musk, Erik Brynjolfsson, Fellow of the Royal Society, fiat currency, financial exclusion, Flash crash, Flynn Effect, Ford Model T, future of work, gamification, Geoffrey Hinton, gig economy, gigafactory, Google Glasses, Google X / Alphabet X, Hans Lippershey, high-speed rail, Hyperloop, income inequality, industrial robot, information asymmetry, Internet of things, invention of movable type, invention of the printing press, invention of the telephone, invention of the wheel, James Dyson, Jeff Bezos, job automation, job-hopping, John Markoff, John von Neumann, Kevin Kelly, Kickstarter, Kim Stanley Robinson, Kiva Systems, Kodak vs Instagram, Leonard Kleinrock, lifelogging, low earth orbit, low skilled workers, Lyft, M-Pesa, Mark Zuckerberg, Marshall McLuhan, megacity, Metcalfe’s law, Minecraft, mobile money, money market fund, more computing power than Apollo, Neal Stephenson, Neil Armstrong, Network effects, new economy, Nick Bostrom, obamacare, Occupy movement, Oculus Rift, off grid, off-the-grid, packet switching, pattern recognition, peer-to-peer, Ray Kurzweil, retail therapy, RFID, ride hailing / ride sharing, Robert Metcalfe, Salesforce, Satoshi Nakamoto, Second Machine Age, selective serotonin reuptake inhibitor (SSRI), self-driving car, sharing economy, Shoshana Zuboff, Silicon Valley, Silicon Valley startup, Skype, smart cities, smart grid, smart transportation, Snapchat, Snow Crash, social graph, software as a service, speech recognition, statistical model, stem cell, Stephen Hawking, Steve Jobs, Steve Wozniak, strong AI, synthetic biology, systems thinking, TaskRabbit, technological singularity, TED Talk, telemarketer, telepresence, telepresence robot, Tesla Model S, The future is already here, The Future of Employment, Tim Cook: Apple, trade route, Travis Kalanick, TSMC, Turing complete, Turing test, Twitter Arab Spring, uber lyft, undersea cable, urban sprawl, V2 rocket, warehouse automation, warehouse robotics, Watson beat the top human players on Jeopardy!, white picket fence, WikiLeaks, yottabyte

These algorithms don’t learn language like a human; they identify a phrase through recognition, look it up on a database and then deliver an appropriate response. Recognising speech and being able to carry on a conversation are two very different achievements. What would it take for a computer to fool a human into thinking it was a human, too? The Turing Test or Not… In 1950, Alan Turing published a famous paper entitled “Computing Machinery and Intelligence”. In his paper, he asked not just if a computer or machine could be considered something that could “think”, but more specifically “Are there imaginable digital computers which would do well in the imitation game?”26 Turing proposed that this “test” of a machine’s intelligence—which he called the “imitation game”—be tested in a human-machine question and answer session.

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Low friction interfaces also have optimal presentation of information so that readability and usability are high. 20 Ian Parker, “The Shape of Things to Come—How an Industrial Designer became Apple’s Greatest Product,” New Yorker, 23 February 2015, http://www.newyorker.com/magazine/2015/02/23/shape-things-come. 21 Henry Blodget, “Uber CEO Reveals Mind-Boggling Statistic That Skeptics Will Hate,” Business Insider, 19 January 2015. 22 Todd Spangler, “Streaming overtakes live TV among consumer viewing preferences,” Variety, 22 April 2015, http://variety.com/2015/digital/news/streaming-overtakes-live-tv-among-consumer-viewing-preferences-study-1201477318/. 23 Tesla uses Tegra chips in its cars. 24 “Meet the Robot Telemarketer Who Denies She’s a Robot,” Time, 13 December 2013, http://newsfeed.time.com/2013/12/10/meet-the-robot-telemarketer-who-denies-shes-a-robot/. 25 Taken from Bill Gates’ speech at the Microsoft Developers Conference on 1st October 1997 26 A. M. Turing, “Computing Machinery and Intelligence,” MIND: A Quarterly Review of Psychology and Philosophy vol. LIX, no. 236. (October 1950), http://mind.oxfordjournals.org/content/LIX/236/433. 27 Test Car A and Test Car B became Ajay and Bobby, respectively. Chapter 4 The Robot Advantage Contributed by Alex Lightman Edited by Brett King “The central question of 2025 will be: What are people for in a world that does not need their labor, and where only a minority are needed to guide the ‘bot-based’ economy?”

Rage Inside the Machine: The Prejudice of Algorithms, and How to Stop the Internet Making Bigots of Us All by Robert Elliott Smith

"World Economic Forum" Davos, Ada Lovelace, adjacent possible, affirmative action, AI winter, Alfred Russel Wallace, algorithmic bias, algorithmic management, AlphaGo, Amazon Mechanical Turk, animal electricity, autonomous vehicles, behavioural economics, Black Swan, Brexit referendum, British Empire, Cambridge Analytica, cellular automata, Charles Babbage, citizen journalism, Claude Shannon: information theory, combinatorial explosion, Computing Machinery and Intelligence, corporate personhood, correlation coefficient, crowdsourcing, Daniel Kahneman / Amos Tversky, data science, deep learning, DeepMind, desegregation, discovery of DNA, disinformation, Douglas Hofstadter, Elon Musk, fake news, Fellow of the Royal Society, feminist movement, Filter Bubble, Flash crash, Geoffrey Hinton, Gerolamo Cardano, gig economy, Gödel, Escher, Bach, invention of the wheel, invisible hand, Jacquard loom, Jacques de Vaucanson, John Harrison: Longitude, John von Neumann, Kenneth Arrow, Linda problem, low skilled workers, Mark Zuckerberg, mass immigration, meta-analysis, mutually assured destruction, natural language processing, new economy, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, On the Economy of Machinery and Manufactures, p-value, pattern recognition, Paul Samuelson, performance metric, Pierre-Simon Laplace, post-truth, precariat, profit maximization, profit motive, Silicon Valley, social intelligence, statistical model, Stephen Hawking, stochastic process, Stuart Kauffman, telemarketer, The Bell Curve by Richard Herrnstein and Charles Murray, The Future of Employment, the scientific method, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, theory of mind, Thomas Bayes, Thomas Malthus, traveling salesman, Turing machine, Turing test, twin studies, Vilfredo Pareto, Von Neumann architecture, warehouse robotics, women in the workforce, Yochai Benkler

His invention of the thought-experiment computer the Turing machine literally created the field of computer science, the bedrock field for an immeasurable fraction of today’s global society. And he created another thought experiment that has forever altered the cultural zeitgeist about man and machines: the so-called Turing test. The test was first described in the 1950 paper entitled ‘Computing Machinery and Intelligence’,4 in which Turing acknowledges the difficulty of defining ‘thinking’, such that one could answer the question, ‘Do computers think?’ He posed instead the alternative question: ‘Are there imaginable digital computers which would do well in the imitation game?’ The imitation game (Turing never used his own name for the test) is a thought experiment about communication, which he saw as a way of determining progress in AI.

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Boston: Shambhala. 2Alyssa Newcomb, 2015, How Many Pages It Takes to Print the Entire Internet, ABC News, https://abcnews.go.com/Technology/pages-takes-print-entire-internet/story?id=30956365 3Drew McDermott, 1976, Artificial Intelligence Meets Natural Stupidity. SIGART Bull., 57: 4–9. http://dx.doi.org/10.1145/1045339.1045340 4A.M. Turing, 1995, Computing Machinery and Intelligence. In Edward A. Feigenbaum and Julian Feldman (eds), Computers and Thought, pp. 1–35. Cambridge, MA: MIT Press. 5James Gleick, The Information: a History, a Theory, a Flood. New York: Pantheon Books. 6‘Cybernetics’ was a precursor name for the field that came to be known as artificial intelligence soon after this conference.

Empire of the Sum: The Rise and Reign of the Pocket Calculator by Keith Houston

Ada Lovelace, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Andy Kessler, Apollo 11, Apollo 13, Apple II, Bletchley Park, Boris Johnson, Charles Babbage, classic study, clockwork universe, computer age, Computing Machinery and Intelligence, double entry bookkeeping, Edmond Halley, Fairchild Semiconductor, Fellow of the Royal Society, Grace Hopper, human-factors engineering, invention of movable type, invention of the telephone, Isaac Newton, Johann Wolfgang von Goethe, Johannes Kepler, John Markoff, John von Neumann, Jony Ive, Kickstarter, machine readable, Masayoshi Son, Menlo Park, meta-analysis, military-industrial complex, Mitch Kapor, Neil Armstrong, off-by-one error, On the Revolutions of the Heavenly Spheres, orbital mechanics / astrodynamics, pattern recognition, popular electronics, QWERTY keyboard, Ralph Waldo Emerson, Robert X Cringely, side project, Silicon Valley, skunkworks, SoftBank, Steve Jobs, Steve Wozniak, The Home Computer Revolution, the payments system, Turing machine, Turing test, V2 rocket, William Shockley: the traitorous eight, Works Progress Administration, Yom Kippur War

Turing, “On Computable Numbers, with an Application to the Entscheidungsproblem,” Proceedings of the London Mathematical Society s2-42, no. 1 (1937): 230–265, https://doi.org/10.1112/plms/s2-42.1.230; Alan M. Turing, “Computing Machinery and Intelligence,” Mind LIX, no. 236 (1950): 433–460, https://doi.org/10.1093/mind/LIX.236.433. 5 Roland Pease, “Alan Turing: Inquest’s Suicide Verdict ‘Not Supportable,’ ” BBC News, June 26, 2012, https://www.bbc.co.uk/news/science-environment-18561092; “Royal Pardon for Codebreaker Alan Turing,” BBC News, December 24, 2013, https://www.bbc.co.uk/news/technology-25495315. 6 Turing, “Computing Machinery and Intelligence,” 436–437. 7 Menninger, Number Words, 212, 306. 8 Heinrich Schreiber, Ayn New Kunstlich Buech, Welches Gar Gewiß Vnd Behend Lernet Nach Der Gemainen Regel Detre, Welschen Practic, Regeln Falsi vñ Etlichē Regeln Cosse Mancherlay Schöne Uñ Zu Wissen Notürfftig Rechnu~g Auff Kauffmanschafft . . .

The Dream Machine: J.C.R. Licklider and the Revolution That Made Computing Personal by M. Mitchell Waldrop

Ada Lovelace, air freight, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, anti-communist, Apple II, battle of ideas, Berlin Wall, Bill Atkinson, Bill Duvall, Bill Gates: Altair 8800, Bletchley Park, Boeing 747, Byte Shop, Charles Babbage, Claude Shannon: information theory, Compatible Time-Sharing System, computer age, Computing Machinery and Intelligence, conceptual framework, cuban missile crisis, Dennis Ritchie, do well by doing good, Donald Davies, double helix, Douglas Engelbart, Douglas Engelbart, Dynabook, experimental subject, Fairchild Semiconductor, fault tolerance, Frederick Winslow Taylor, friendly fire, From Mathematics to the Technologies of Life and Death, functional programming, Gary Kildall, Haight Ashbury, Howard Rheingold, information retrieval, invisible hand, Isaac Newton, Ivan Sutherland, James Watt: steam engine, Jeff Rulifson, John von Neumann, Ken Thompson, Leonard Kleinrock, machine translation, Marc Andreessen, Menlo Park, Multics, New Journalism, Norbert Wiener, packet switching, pink-collar, pneumatic tube, popular electronics, RAND corporation, RFC: Request For Comment, Robert Metcalfe, Silicon Valley, Skinner box, Steve Crocker, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, Ted Nelson, The Soul of a New Machine, Turing machine, Turing test, Vannevar Bush, Von Neumann architecture, Wiener process, zero-sum game

Turing, of course, had spent much of his time since the war trying to create his abstract machine "in the metal," first with his designs for the ACE com- puter at the National Physical Laboratory and then, starting in 1948, with his work as chief programmer for the Mark I computer project at Manchester Uni- versity. In parallel, however-and to Turing's way of thinking, far more impor- tant-he was also continuing his struggle to understand the fundamental nature of intelligence. That effort culminated in 1950 with his paper "Computing Machinery and Intelligence,"14 in which he addressed the fundamental question: Can a machine think? Instead of trying to answer that directly, however-an exercise that had al- ready generated entirely too much philosophical hot air for his taste-he parsed it into two questions that were even more elemental. First, What do we mean by a "machine"?

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Henry S. Tropp, "History of the Design of the SAGE Computer-The AN/FSQ7," Annals of the History of Computing 5 (1983): 340. 13. Norbert Wiener, Cybernetics, or Control and CommunicatiOn in the Animal and the Machine, 2d ed. (Cambridge, Mass.: MIT Press, 1961), vii. 14. Alan M. Turing, "Computing Machinery and Intelligence," Mind 59, no. 236 (1950). Repnnted In The Mind's I: Fantasies and ReflectiOns on Self & Soul, ed. Douglas R. Hofstadter and Daniel C. Den- nett (New York: BasIC Books, 1981), 53-67. 15. Ibid. 16. QIoted In Steve Heims, John von Neumann and Norbert Wiener: From Mathematics to the Technologies of Life and Death (Cambridge, Mass.: MIT Press, 1980), 276. 17.

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Forrester)." Annals of the H15tory ofComputzng 5 (1983). -. "Origin of the Term Bit." Annals of the History ofComputzng 6 (1984). Turing, Alan M. "On Computable Numbers, with an ApplIcation to the Entschldungsproblem." Pro- ceedzngs of the London Mathematical Soczety 2, no. 42 (1937). -. "Computing Machinery and Intelligence." Mind 59, no. 236 (1950). Reprinted In The Mznd's I: Fantaszes and ReflectIOns on Self & Soul, edited by Douglas R. Hofstadter and Daniel C. Dennett. New York: BasIC Books, 1981. Turkle, Sherry. The Second Self: Computers and the Human Spznt. New York: Simon & Schuster, 1984. U mpleby, Stuart A., and Eric B.

Information: A Very Short Introduction by Luciano Floridi

agricultural Revolution, Albert Einstein, bioinformatics, Bletchley Park, carbon footprint, Claude Shannon: information theory, Computing Machinery and Intelligence, conceptual framework, digital divide, disinformation, double helix, Douglas Engelbart, Douglas Engelbart, George Akerlof, Gordon Gekko, Gregor Mendel, industrial robot, information asymmetry, intangible asset, Internet of things, invention of writing, John Nash: game theory, John von Neumann, Laplace demon, machine translation, moral hazard, Nash equilibrium, Nelson Mandela, Norbert Wiener, Pareto efficiency, phenotype, Pierre-Simon Laplace, prisoner's dilemma, RAND corporation, RFID, Thomas Bayes, Turing machine, Vilfredo Pareto

Jones, Elementary Information Theory (Oxford: Clarendon Press, 1979). D. M. MacKay, Information, Mechanism and Meaning (Cambridge, MA: MIT Press, 1969). J. R. Pierce, An Introduction to Information Theory: Symbols, Signals and Noise, 2nd edn (New York: Dover Publications, 1980). A. M. Turing, `Computing Machinery and Intelligence', Minds and Machines, 1950, 59, 433-60. Chapter 3 C. Cherry, On Human Communication: A Review, a Survey, and a Criticism, 3rd edn (Cambridge, MA; London: MIT Press, 1978). A. Golan, `Information and Entropy Econometrics - Editor's View', Journal of Econometrics, 2002,107(1-2),1-15.

Darwin Among the Machines by George Dyson

Ada Lovelace, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, anti-communist, backpropagation, Bletchley Park, British Empire, carbon-based life, cellular automata, Charles Babbage, Claude Shannon: information theory, combinatorial explosion, computer age, Computing Machinery and Intelligence, Danny Hillis, Donald Davies, fault tolerance, Fellow of the Royal Society, finite state, IFF: identification friend or foe, independent contractor, invention of the telescope, invisible hand, Isaac Newton, Jacquard loom, James Watt: steam engine, John Nash: game theory, John von Neumann, launch on warning, low earth orbit, machine readable, Menlo Park, Nash equilibrium, Norbert Wiener, On the Economy of Machinery and Manufactures, packet switching, pattern recognition, phenotype, RAND corporation, Richard Feynman, spectrum auction, strong AI, synthetic biology, the scientific method, The Wealth of Nations by Adam Smith, Turing machine, Von Neumann architecture, zero-sum game

., The Leibniz–Clarke Correspondence (Manchester, England: Manchester University Press, 1956), 193. 52.Leibniz, 1714, The Monadology, in George R. Montgomery, trans., Basic Writings: Discourse on Metaphysics; Correspondence with Arnauld; Monadology (La Salle, Ill.: Open Court, 1902), 254. 53.Leibniz to Caroline, Princess of Wales, ca. 1716, in Alexander, Correspondence, 191. CHAPTER 4 1.Alan Turing, “Computing Machinery and Intelligence,” Mind 59 (October 1950): 443. 2.A. K. Dewdney, The Turing Omnibus (Rockville, Md.: Computer Science Press, 1989), 389. 3.Robin Gandy, “The Confluence of Ideas in 1936,” in Rolf Herken, ed., The Universal Turing Machine: A Half-century Survey (Oxford: Oxford University Press, 1988), 85. 4.Alan Turing, “On Computable Numbers, with an Application to the Entscheidungsproblem,” Proceedings of the London Mathematical Society, 2d ser. 42 (1936–1937); reprinted, with corrections, in Martin Davis, ed., The Undecidable (Hewlett, N.Y.: Raven Press, 1965), 117. 5.Ibid., 136. 6.Kurt Gödel, 1946, “Remarks Before the Princeton Bicentennial Conference on Problems in Mathematics,” reprinted in Davis, The Undecidable, 84. 7.W.

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Origin of the Genetic Code as a Primordial Collector Language; The Pairing-Release Hypothesis,” BioSystems 11 (1979): 19, 21. 54.Martin Davis, “Influences of Mathematical Logic on Computer Science,” in Rolf Herken, ed., The Universal Turing Machine: A Half-century Survey (Oxford: Oxford University Press, 1988), 315. 55.Alan Turing, “Computing Machinery and Intelligence,” Mind 59 (October 1950): 456. CHAPTER 8 1.W. Daniel Hillis, “New Computer Architectures and Their Relationship to Physics, or Why Computer Science Is No Good,” International Journal of Theoretical Physics 21, nos. 3–4 (April 1982): 257. 2.Aeschylus, Agamemnon, lines 280–316, trans, and ed.

Tools for Thought: The History and Future of Mind-Expanding Technology by Howard Rheingold

Ada Lovelace, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Bletchley Park, card file, cellular automata, Charles Babbage, Claude Shannon: information theory, combinatorial explosion, Compatible Time-Sharing System, computer age, Computer Lib, Computing Machinery and Intelligence, conceptual framework, Conway's Game of Life, Douglas Engelbart, Dynabook, experimental subject, Hacker Ethic, heat death of the universe, Howard Rheingold, human-factors engineering, interchangeable parts, invention of movable type, invention of the printing press, Ivan Sutherland, Jacquard loom, John von Neumann, knowledge worker, machine readable, Marshall McLuhan, Menlo Park, Neil Armstrong, Norbert Wiener, packet switching, pattern recognition, popular electronics, post-industrial society, Project Xanadu, RAND corporation, Robert Metcalfe, Silicon Valley, speech recognition, Steve Jobs, Steve Wozniak, Stewart Brand, Ted Nelson, telemarketer, The Home Computer Revolution, Turing machine, Turing test, Vannevar Bush, Von Neumann architecture

His 1936 paper was published in a mathematical journal, but it eventually created the foundation of a whole new field of investigation beyond the horizons of mathematics -- computer science. In 1950, Turing published another article that was to have profound impact; the piece, more simply titled "Computing Machinery and Intelligence," was published in the philosophical journal Mind. In relatively few words, using tools no more esoteric than common sense, and absolutely no mathematical formulas, Turing provided the boldest subspecialty of computer science -- the field of artificial intelligence. Despite the simplicity of Turing's hypothetical machine, the formal description in the mathematics journal makes very heavy reading.

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[2] An amusing example of an easily constructed Turing machine, using pebbles and toilet paper, is given in the third chapter of Joseph Weizenbaum, Computer Power and Human Reason (San Francisco: W. H. Freeman, 1976). [3] Turing, "Computable Numbers." [4] Andrew Hodges, Alan Turing: The Enigma (New York: Simon and Schuster, 1983), 396. [5]Ibid., 326. [6] Alan M. Turing, "Computing Machinery and intelligence," Mind, vol. 59, no. 236 (1950). [7] Ibid. [8] Hodges, Turing, 488. Chapter Four: Johnny Builds Bombs and Johnny Builds Brains [1] Steve J. Heims, John von Neumann and Norbert Wiener (Cambridge, Mass.: MIT Press, 1980), 371. [2] C. Blair, "Passing of a great Mind," Life,, February 25, 1957, 96

The Innovators: How a Group of Inventors, Hackers, Geniuses and Geeks Created the Digital Revolution by Walter Isaacson

1960s counterculture, Ada Lovelace, AI winter, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, AltaVista, Alvin Toffler, Apollo Guidance Computer, Apple II, augmented reality, back-to-the-land, beat the dealer, Bill Atkinson, Bill Gates: Altair 8800, bitcoin, Bletchley Park, Bob Noyce, Buckminster Fuller, Byte Shop, c2.com, call centre, Charles Babbage, citizen journalism, Claude Shannon: information theory, Clayton Christensen, commoditize, commons-based peer production, computer age, Computing Machinery and Intelligence, content marketing, crowdsourcing, cryptocurrency, Debian, desegregation, Donald Davies, Douglas Engelbart, Douglas Engelbart, Douglas Hofstadter, driverless car, Dynabook, El Camino Real, Electric Kool-Aid Acid Test, en.wikipedia.org, eternal september, Evgeny Morozov, Fairchild Semiconductor, financial engineering, Firefox, Free Software Foundation, Gary Kildall, Google Glasses, Grace Hopper, Gödel, Escher, Bach, Hacker Ethic, Haight Ashbury, Hans Moravec, Howard Rheingold, Hush-A-Phone, HyperCard, hypertext link, index card, Internet Archive, Ivan Sutherland, Jacquard loom, Jaron Lanier, Jeff Bezos, jimmy wales, John Markoff, John von Neumann, Joseph-Marie Jacquard, Leonard Kleinrock, Lewis Mumford, linear model of innovation, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, Menlo Park, Mitch Kapor, Mother of all demos, Neil Armstrong, new economy, New Journalism, Norbert Wiener, Norman Macrae, packet switching, PageRank, Paul Terrell, pirate software, popular electronics, pre–internet, Project Xanadu, punch-card reader, RAND corporation, Ray Kurzweil, reality distortion field, RFC: Request For Comment, Richard Feynman, Richard Stallman, Robert Metcalfe, Rubik’s Cube, Sand Hill Road, Saturday Night Live, self-driving car, Silicon Valley, Silicon Valley startup, Skype, slashdot, speech recognition, Steve Ballmer, Steve Crocker, Steve Jobs, Steve Wozniak, Steven Levy, Steven Pinker, Stewart Brand, Susan Wojcicki, technological singularity, technoutopianism, Ted Nelson, Teledyne, the Cathedral and the Bazaar, The Coming Technological Singularity, The Nature of the Firm, The Wisdom of Crowds, Turing complete, Turing machine, Turing test, value engineering, Vannevar Bush, Vernor Vinge, Von Neumann architecture, Watson beat the top human players on Jeopardy!, Whole Earth Catalog, Whole Earth Review, wikimedia commons, William Shockley: the traitorous eight, Yochai Benkler

“Not until a machine can write a sonnet or compose a concerto because of thoughts and emotions felt, and not by the chance fall of symbols, could we agree that machine equals brain,” declared a famous brain surgeon, Sir Geoffrey Jefferson, in the prestigious Lister Oration in 1949.92 Turing’s response to a reporter from the London Times seemed somewhat flippant, but also subtle: “The comparison is perhaps a little bit unfair because a sonnet written by a machine will be better appreciated by another machine.”93 The ground was thus laid for Turing’s second seminal work, “Computing Machinery and Intelligence,” published in the journal Mind in October 1950.94 In it he devised what became known as the Turing Test. He began with a clear declaration: “I propose to consider the question, ‘Can machines think?’ ” With a schoolboy’s sense of fun, he then invented a game—one that is still being played and debated—to give empirical meaning to that question.

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It makes no more sense to say that the machine “thinks” than it does to say that the fellow following the massive instruction manual understands Chinese.95 One response to the Searle objection is to argue that, even if the man does not really understand Chinese, the entire system incorporated in the room—the man (processing unit), instruction manual (program), and files full of Chinese characters (the data)—as a whole might indeed understand Chinese. There’s no conclusive answer. Indeed, the Turing Test and the objections to it remain to this day the most debated topic in cognitive science. For a few years after he wrote “Computing Machinery and Intelligence,” Turing seemed to enjoy engaging in the fray that he provoked. With wry humor, he poked at the pretensions of those who prattled on about sonnets and exalted consciousness. “One day ladies will take their computers for walks in the park and tell each other ‘My little computer said such a funny thing this morning!’

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., ref1, ref2 Centralab, ref1 central processing unit, ref1 Cerf, Sigrid, ref1 Cerf, Vint, ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8 background of, ref1 internet created by, ref1 nuclear attack simulated by, ref1 CERN, ref1, ref2 Cézanne, Paul, ref1 Cheatham, Thomas, ref1 Cheriton, David, ref1 Chicago Area Computer Hobbyists’ Exchange, ref1 Childe Harold’s Pilgrimage (Byron), ref1, ref2 Chinese Room, ref1, ref2 Christensen, Clay, ref1 Christensen, Ward, ref1 Church, Alonzo, ref1, ref2 circuit switching, ref1 Cisco, ref1 Clark, Dave, ref1 Clark, Jim, ref1 Clark, Wes, ref1, ref2, ref3 Clinton, Bill, ref1n Clippinger, Richard, ref1 COBOL, ref1, ref2n, ref3, ref4, ref5, ref6 Cold War, ref1 Collingwood, Charles, ref1 Colossus, ref1, ref2, ref3, ref4, ref5 as special-purpose machine, ref1 Command and Control Research, ref1 Commodore, ref1 Community Memory, ref1, ref2, ref3 Complex Number Calculator, ref1, ref2, ref3 Compton, Karl, ref1 CompuServe, ref1, ref2, ref3, ref4, ref5 computer, ref1, ref2 debate over, ref1, ref2, ref3 “Computer as a Communication Device, The” (Licklider and Taylor), ref1 Computer Center Corporation (C-Cubed), ref1 Computer Quiz, ref1 Computer Science and Artificial Intelligence Laboratory, ref1 computers (female calculators), ref1, ref2 Computer Space, ref1, ref2, ref3 “Computing Machinery and Intelligence” (Turing), ref1 Conant, James Bryant, ref1, ref2 condensers, ref1, ref2 conditional branching, ref1 Congregationalist, ref1 Congress, U.S., ref1 Congress of Italian Scientists, ref1 Constitution, U.S., ref1n content sharing, ref1 Control Video Corporation (CVC), ref1, ref2 copper, ref1 Coupling, J.

Elon Musk by Walter Isaacson

4chan, activist fund / activist shareholder / activist investor, Airbnb, Albert Einstein, AltaVista, Apollo 11, Apple II, Apple's 1984 Super Bowl advert, artificial general intelligence, autism spectrum disorder, autonomous vehicles, basic income, Big Tech, blockchain, Boston Dynamics, Burning Man, carbon footprint, ChatGPT, Chuck Templeton: OpenTable:, Clayton Christensen, clean tech, Colonization of Mars, computer vision, Computing Machinery and Intelligence, coronavirus, COVID-19, crowdsourcing, cryptocurrency, deep learning, DeepMind, Demis Hassabis, disinformation, Dogecoin, Donald Trump, Douglas Engelbart, drone strike, effective altruism, Elon Musk, estate planning, fail fast, fake news, game design, gigafactory, GPT-4, high-speed rail, hiring and firing, hive mind, Hyperloop, impulse control, industrial robot, information security, Jeff Bezos, Jeffrey Epstein, John Markoff, John von Neumann, Jony Ive, Kwajalein Atoll, lab leak, large language model, Larry Ellison, lockdown, low earth orbit, Marc Andreessen, Marc Benioff, Mars Society, Max Levchin, Michael Shellenberger, multiplanetary species, Neil Armstrong, Network effects, OpenAI, packet switching, Parler "social media", paypal mafia, peer-to-peer, Peter Thiel, QAnon, Ray Kurzweil, reality distortion field, remote working, rent control, risk tolerance, Rubik’s Cube, Salesforce, Sam Altman, Sam Bankman-Fried, San Francisco homelessness, Sand Hill Road, Saturday Night Live, self-driving car, seminal paper, short selling, Silicon Valley, Skype, SpaceX Starlink, Stephen Hawking, Steve Jobs, Steve Jurvetson, Steve Wozniak, Steven Levy, Streisand effect, supply-chain management, tech bro, TED Talk, Tesla Model S, the payments system, Tim Cook: Apple, universal basic income, Vernor Vinge, vertical integration, Virgin Galactic, wikimedia commons, William MacAskill, work culture , Y Combinator

At the 2012 gathering, Musk met Demis Hassabis, a neuroscientist, video-game designer, and artificial intelligence researcher with a courteous manner that conceals a competitive mind. A chess prodigy at age four, he became the five-time champion of an international Mind Sports Olympiad that includes competition in chess, poker, Mastermind, and backgammon. In his modern London office is an original edition of Alan Turing’s seminal 1950 paper, “Computing Machinery and Intelligence,” which proposed an “imitation game” that would pit a human against a ChatGPT–like machine. If the responses of the two were indistinguishable, he wrote, then it would be reasonable to say that machines could “think.” Influenced by Turing’s argument, Hassabis cofounded a company called DeepMind that sought to design computer-based neural networks that could achieve artificial general intelligence.

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It’s like the way humans learn to speak and drive and play chess and eat spaghetti and do almost everything else; we might be given a set of rules to follow, but mainly we pick up the skills by observing how other people do them. It was the approach to machine learning envisioned by Alan Turing in his 1950 paper, “Computing Machinery and Intelligence.” Tesla had one of the world’s largest supercomputers to train neural networks. It was powered by graphics processing units (GPUs) made by the chipmaker Nvidia. Musk’s goal for 2023 was to transition to using Dojo, the supercomputer that Tesla was building from the ground up, to use video data to train the AI system.

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., 101 Butterfield, Elissa, 258, 321, 329 Buzza, Tim Falcon 1 launch attempts and, 151, 184, 185, 186 Falcon 9 liftoff and, 210 on improvisation, 116–17 launch location and, 145 NASA contract and, 205 on production algorithm, 113 testing and, 115, 116 Calacanis, Jason, 523, 529, 530, 531, 576 Cameron, James, 92 Cantrell, Jim, 95–96, 98, 99–100, 101 CAPTCHA technology, 83 Challenger mission, 119, 385 Chanos, Jim, 278 Chappelle, Dave, 580 ChatGPT, 243, 593, 600–601, 606 Chinnery, Anne, 149 Christensen, Clayton, 84 Christian symbolism, 71 CitySearch, 65 Civilization, 46, 51, 425 Claassen, Kate, 511 Cleese, John, 498 Clinton, Hillary, 261, 424, 525 Clooney, George, 143 Cobra Kai, 346 Cocconi, Alan, 126 Coffin, Gage, 273 comics, 27 communications satellites. See Starlink Compaq Computer, 66 computer programming EM’s childhood interest in, 29, 33–34 EM’s college years and, 50 EM’s Silicon Valley internship and, 55–56 See also Zip2 “Computing Machinery and Intelligence” (Turing), 595 Confinity, 76 Cook, Tim, 261, 559 Corcoran, Kyle, Twitter acquisition and, 511 COVID-19 pandemic conspiracy theories and, 578–80 EM’s reconciliation with Kimbal and, 346 EM’s resistance to authority and, 379, 417–18 Tesla and, 408, 417–18, 441 Twitter content moderation and, 572–73 Cramer, Jim, 293 Crawford, Esther, 509, 540 Crider, Johnna, 290 Culture, The novels (Banks), 400 Cyberpunk video games, 310, 318, 485 Daimler, 193 Davenport, Christian, 357 David, Larry, 491 Davis, Steve The Boring Company and, 257, 258 EM’s management of Twitter and, 547, 583 flamethrowing and, 299, 496 Model 3 production surge and, 271 Twitter server move and, 584, 585 DeepMind, 240–41, 600, 601, 605 Deese, Brian, 421 Demolition Man, 591 Denholm, Robyn, 580 Depp, Johnny, 263 Dharamsi, Tejas, 514 DiCaprio, Leonardo, 381 Diez, Shana, 478, 608 Diplomacy, 46 Diversity Myth: Multiculturalism and Political Intolerance on Campus, The (Thiel and Musk), 424 Dojo, 244, 394, 397, 487, 596 Dontchev, Kiko, 347, 349–51, 362, 385 Doohan, James, 176 Dorsey, Jack, 440, 444, 461, 510, 567 Dow, Brian, 271, 369, 370–71, 372, 373–74 Downey, Robert, Jr., 142 Drexler, Mickey, 143 Dreyer, Lauren, 428–29 Drori, Ze’ev, 167 Duan, Phil, 499 Dungeons & Dragons, 32–33, 50, 309 Durban, Egon, 492 Dyer, Deborah Anne (Skin), 344 eBay PayPal and, 85, 86–87 X.com and, 76, 77, 78–79 Eberhard, Martin, 124, 162 component outsourcing and, 132–33, 156 departure of, 163–64 development mule and, 133 electric car ideas, 127–28, 129, 130 EM’s attacks on, 164–65 EM’s design input and, 136–37 EM’s enmity and, 164, 192 EM’s sensitivity about credit and, 139, 141–42 legal settlement with EM, 164 Roadster launch and, 140–41, 143 Roadster production costs and, 160 Tesla financial issues and, 161, 163 Tesla founding and, 130, 133, 139, 164 Tesla leadership conflicts and, 134, 137, 139–40 economic crisis (2007–2008), 179–81, 193 Edgett, Sean, 513 effective altruism movement, 460 Ehrenpreis, Ira, 167 Einhorn, David, 278 Ekenstam, Felix, 425 Elden Ring, 7, 455, 588 electric cars AC Propulsion and, 126–27, 129 auto industry abandonment of, 193 Biden and, 420–21 Eberhard and, 127–28, 129, 130 EM’s college interest in, 51, 55, 57–58 Rosen meeting and, 125–26 Tesla Motors and, 127–28, 129–30 tzero prototype, 126–27, 128 See also Tesla Ellison, Larry, 7, 218, 451, 459–60, 461, 558–59, 590–91 Elluswamy, Ashok, 596–97, 598 Emanuel, Ari, 488, 491, 494, 497, 554 EM’s management of Twitter advertiser boycotts and, 537–38 advertisers and, 533–35, 537–38, 547, 559–60, 580 Apple and, 559–60 content moderation and, 524–31, 537, 554, 566, 567, 572–73, 574–77 desk-siding, 552 EM’s demon mode and, 537–39 EM’s management style and, 367 EM’s personality and, 534 EM’s stress and, 544–45, 547–48 engineering integration and, 79, 494, 557 financial issues and, 541 firings and, 509, 510, 521–22, 540, 547–50, 555–57 government agencies and, 568, 572 hardcore culture and, 220, 349, 508, 522, 547, 550–51 hardcore opt-in, 550–51, 556 impulsive tweets and, 533, 534, 577–78 in-person vs. remote work, 519, 541–42 journalist suspensions, 575–77 layoff reviews, 515, 516–19, 536, 548–49 product changes, 514 product review, 508–9 risk and, 522, 555 Roth departure, 542–44 server move, 581, 582–86, 588–90, 598 survival, 558 top management question, 520–21 troll/bot campaign and, 530–31 Twitter Blue, 539–40, 542–43, 547, 613 Twitter Files, 529, 566–68, 569–73, 575, 576, 579 visibility filtering, 529, 571, 572–73, 575 X.com and, 87, 507, 509, 560 Yaccarino as CEO, 613 Endeavor, 491 Engelbart, Doug, 399 Epstein, Jeffrey, 296 Fabricant, James, 173, 174 Falcon 1 launch attempts EM’s stress and, 5, 173, 179 first attempt (Mar. 2006), 150–52 second attempt (Mar. 2007), 153–54 third attempt (Aug. 2008), 175, 176–77, 197–98 fourth attempt (Sept. 2008), 184–88, 206 Kimbal’s support and, 150, 151, 186–87, 300 Obama administration and, 206 Farooq, Navaid, 44, 235 EM’s friendship with, 45 on EM’s grief, 103–4 EM’s marriage to Justine and, 71–72 EM’s marriage to Talulah and, 215 strategy games and, 46, 47, 51 Twitter and, 455–56 Zip2 and, 62 Farooq, Nyame, 61 Fath, Joe, 291, 334 Fauci, Anthony, 577–78, 587 Favreau, Jon, 142 Federal Aviation Administration (FAA), 351–52, 360, 362 Federal Communications Commission (FCC), 355–56 Fedorov, Mykhailo, 428, 431, 433, 434 Felsenthal, Ed, 416 Ferguson, Niall, 430 Fermi, Enrico, 93 Fermi’s Paradox, 93 Fibonacci Sequence, 37 Field, Doug, 301 Fisker, Henrik, 196, 197 Flesh without Blood, 306 Fletcher, Winnifred.

The One Device: The Secret History of the iPhone by Brian Merchant

Airbnb, animal electricity, Apollo Guidance Computer, Apple II, Apple's 1984 Super Bowl advert, Black Lives Matter, Charles Babbage, citizen journalism, Citizen Lab, Claude Shannon: information theory, computer vision, Computing Machinery and Intelligence, conceptual framework, cotton gin, deep learning, DeepMind, Douglas Engelbart, Dynabook, Edward Snowden, Elon Musk, Ford paid five dollars a day, Frank Gehry, gigafactory, global supply chain, Google Earth, Google Hangouts, Higgs boson, Huaqiangbei: the electronics market of Shenzhen, China, information security, Internet of things, Jacquard loom, John Gruber, John Markoff, Jony Ive, Large Hadron Collider, Lyft, M-Pesa, MITM: man-in-the-middle, more computing power than Apollo, Mother of all demos, natural language processing, new economy, New Journalism, Norbert Wiener, offshore financial centre, oil shock, pattern recognition, peak oil, pirate software, profit motive, QWERTY keyboard, reality distortion field, ride hailing / ride sharing, rolodex, Shenzhen special economic zone , Silicon Valley, Silicon Valley startup, skeuomorphism, skunkworks, Skype, Snapchat, special economic zone, speech recognition, stealth mode startup, Stephen Hawking, Steve Ballmer, Steve Jobs, Steve Wozniak, Steven Levy, TED Talk, Tim Cook: Apple, Tony Fadell, TSMC, Turing test, uber lyft, Upton Sinclair, Vannevar Bush, zero day

Primed by hundreds of years of fantasy and possibility, around the mid-twentieth century, once sufficient computing power was available, the scientific work investigating actual artificial intelligence began. With the resonant opening line “I propose to consider the question, ‘Can machines think?’” in his 1950 paper “Computing Machinery and Intelligence,” Alan Turing framed much of the debate to come. That work discusses his famous Imitation Game, now colloquially known as the Turing Test, which describes criteria for judging whether a machine may be considered sufficiently “intelligent.” Claude Shannon, the communication theorist, published his seminal work on information theory, introducing the concept of the bit as well as a language through which humans might speak to computers.

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Hey, Siri The backbone of the Siri chapter is a lengthy interview conducted with Tom Gruber, Apple’s head of advanced development for Siri. Artificial intelligence is obviously a loaded topic—I attempted to approach it through the lens of what Siri actually does, or tries to do. The first stop on any AI reading list is Alan Turing’s classic “Computing Machinery and Intelligence.” Additional research concerned the Hearsay II papers. The Oral History Collection at the Charles Babbage Institute is a great resource, and the interview conducted with Raj Reddy is no different; it provides a fascinating look at the life of one of the first AI pioneers. I also drew from published talks Reddy has given.

Advances in Artificial General Intelligence: Concepts, Architectures and Algorithms: Proceedings of the Agi Workshop 2006 by Ben Goertzel, Pei Wang

AI winter, artificial general intelligence, backpropagation, bioinformatics, brain emulation, classic study, combinatorial explosion, complexity theory, computer vision, Computing Machinery and Intelligence, conceptual framework, correlation coefficient, epigenetics, friendly AI, functional programming, G4S, higher-order functions, information retrieval, Isaac Newton, Jeff Hawkins, John Conway, Loebner Prize, Menlo Park, natural language processing, Nick Bostrom, Occam's razor, p-value, pattern recognition, performance metric, precautionary principle, Ray Kurzweil, Rodney Brooks, semantic web, statistical model, strong AI, theory of mind, traveling salesman, Turing machine, Turing test, Von Neumann architecture, Y2K

McCarthy, The Future of AI — A Manifesto, AI Magazine, 26(2005), Winter, 39 [9] R. Brachman, Getting Back to “The Very Idea”, AI Magazine, 26(2005), Winter, 48–50 [10] P. Langley, Cognitive Architectures and General Intelligent Systems, AI Magazine 27(2006), Summer, 33-44. [11] A. M. Turing, Computing machinery and intelligence, Mind LIX (1950), 433-460. [12] A. Newell and H. A. Simon, GPS, a program that simulates human thought, E. A. Feigenbaum and J. Feldman (editors), Computers and Thought, 279-293, McGraw-Hill, 1963. [13] A. Newell, Unified Theories of Cognition, Harvard University Press, 1990. [14] D.

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Wang, On the Working Definition of Intelligence, Technical Report No. 94, Center for Research on Concepts and Cognition, Indiana University, 1994. [3] L. Barsalou, Perceptual symbol systems, Behavioral and Brain Sciences 22 (1999), 577-609. [4] R. Brooks, Intelligence without representation, Artificial Intelligence 47 (1991), 139-159. [5] A. M. Turing, Computing machinery and intelligence, Mind LIX (1950), 433-460. [6] D. Lenat and E. Feigenbaum, On the thresholds of knowledge, Artificial Intelligence 47 (1991), 185-250. [7] J. Holland, Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence, MIT Press, 1992. [8] A.

Overcomplicated: Technology at the Limits of Comprehension by Samuel Arbesman

algorithmic trading, Anthropocene, Anton Chekhov, Apple II, Benoit Mandelbrot, Boeing 747, Chekhov's gun, citation needed, combinatorial explosion, Computing Machinery and Intelligence, Danny Hillis, data science, David Brooks, digital map, discovery of the americas, driverless car, en.wikipedia.org, Erik Brynjolfsson, Flash crash, friendly AI, game design, Google X / Alphabet X, Googley, Hans Moravec, HyperCard, Ian Bogost, Inbox Zero, Isaac Newton, iterative process, Kevin Kelly, machine translation, Machine translation of "The spirit is willing, but the flesh is weak." to Russian and back, mandelbrot fractal, Minecraft, Neal Stephenson, Netflix Prize, Nicholas Carr, Nick Bostrom, Parkinson's law, power law, Ray Kurzweil, recommendation engine, Richard Feynman, Richard Feynman: Challenger O-ring, Second Machine Age, self-driving car, SimCity, software studies, statistical model, Steve Jobs, Steve Wozniak, Steven Pinker, Stewart Brand, superintelligent machines, synthetic biology, systems thinking, the long tail, Therac-25, Tyler Cowen, Tyler Cowen: Great Stagnation, urban planning, Watson beat the top human players on Jeopardy!, Whole Earth Catalog, Y2K

how we realize that we are in the Entanglement: Distinguished Google Fellow Urs Hölzle: “Complexity is evil in the grand scheme of things because it makes it possible for these bugs to lurk that you see only once every two or three years, but when you see them it’s a big story because it had a large, cascading effect.” Jack Clark, “Google: ‘At Scale, Everything Breaks,’” ZDNet, June 22, 2011, http://www.zdnet.com/article/google-at-scale-everything-breaks/2/. In 1950, Alan Turing noted: A. M. Turing, “Computing Machinery and Intelligence,” Mind 59 (1950): 433–60. Widely available online, e.g., http://cogprints.org/499/1/turing.html. a widely used simulator of gravitation: There are about 10,000 mixed-precision instances (the specific type of error) across about 1,000 lines out of approximately 30,000 lines of code.

Team Human by Douglas Rushkoff

1960s counterculture, Abraham Maslow, Adam Curtis, autonomous vehicles, basic income, Berlin Wall, big-box store, bitcoin, blockchain, Burning Man, carbon footprint, circular economy, clean water, clockwork universe, cloud computing, collective bargaining, Computing Machinery and Intelligence, corporate personhood, digital capitalism, disintermediation, Donald Trump, drone strike, European colonialism, fake news, Filter Bubble, full employment, future of work, game design, gamification, gig economy, Google bus, Gödel, Escher, Bach, hockey-stick growth, Internet of things, invention of the printing press, invention of writing, invisible hand, iterative process, John Perry Barlow, Kevin Kelly, Kevin Roose, knowledge economy, Larry Ellison, Lewis Mumford, life extension, lifelogging, Mark Zuckerberg, Marshall McLuhan, means of production, mirror neurons, multilevel marketing, new economy, patient HM, pattern recognition, peer-to-peer, Peter Thiel, planned obsolescence, power law, prosperity theology / prosperity gospel / gospel of success, Ray Kurzweil, recommendation engine, ride hailing / ride sharing, Ronald Reagan, Ronald Reagan: Tear down this wall, shareholder value, sharing economy, Silicon Valley, Silicon Valley billionaire, social intelligence, sovereign wealth fund, Steve Jobs, Steven Pinker, Stewart Brand, tech billionaire, technoutopianism, TED Talk, theory of mind, trade route, Travis Kalanick, Turing test, universal basic income, Vannevar Bush, We are as Gods, winner-take-all economy, zero-sum game

Either we enhance ourselves with chips, nanotechnology, or genetic engineering Future of Life Institute, “Beneficial AI 2017,” https://futureoflife.org/bai-2017/. to presume that our reality is itself a computer simulation Clara Moskowitz, “Are We Living in a Computer Simulation?” Scientific American, April 7, 2016. The famous “Turing test” for computer consciousness Alan Turing, “Computing Machinery and Intelligence,” Mind 59, no. 236 (October 1950). 58. The human mind is not computational Andrew Smart, Beyond Zero and One: Machines, Psychedelics and Consciousness (New York: OR Books, 2009). consciousness is based on totally noncomputable quantum states in the tiniest structures of the brain Roger Penrose and Stuart Hameroff, “Consciousness in the universe: A review of the ‘Orch OR’ theory,” Physics of Life Review 11, no. 1 (March 2014).

Demystifying Smart Cities by Anders Lisdorf

3D printing, artificial general intelligence, autonomous vehicles, backpropagation, behavioural economics, Big Tech, bike sharing, bitcoin, business intelligence, business logic, business process, chief data officer, circular economy, clean tech, clean water, cloud computing, computer vision, Computing Machinery and Intelligence, congestion pricing, continuous integration, crowdsourcing, data is the new oil, data science, deep learning, digital rights, digital twin, distributed ledger, don't be evil, Elon Musk, en.wikipedia.org, facts on the ground, Google Glasses, hydroponic farming, income inequality, information security, Infrastructure as a Service, Internet of things, Large Hadron Collider, Masdar, microservices, Minecraft, OSI model, platform as a service, pneumatic tube, ransomware, RFID, ride hailing / ride sharing, risk tolerance, Salesforce, self-driving car, smart cities, smart meter, software as a service, speech recognition, Stephen Hawking, Steve Jobs, Steve Wozniak, Stuxnet, Thomas Bayes, Turing test, urban sprawl, zero-sum game

ID=3137815&GUID=437A6A6D-62E1-47E2-9C42-461253F9C6D0 (October 2, 2019) the official publication of Local Law 49 of 2018 in New York City that requires a task force to provide recommendations about automated decision systems https://alvelor.com/ (October 2, 2019) the official site of the open source traffic camera computer vision project Alvelor Computing Machinery and Intelligence , Alan M. Turing, Mind 49, 433–460, 1950 The Hundred-Page Machine Learning Book , Andriy Burkov, 2019 Chapter 6 Diffusion of Innovations (5th edition) , Rogers, Everett M., Free Press, 2003 https://commons.wikimedia.org/wiki/File:Diffusion_of_ideas.svg (September 25, 2019) the source of Figure 6-1 Chapter 7 Yes is More: An Archicomic on Architectural Evolution , Bjarke Ingels, Taschen 2009 www.youtube.com/watch?

The Beginning of Infinity: Explanations That Transform the World by David Deutsch

agricultural Revolution, Albert Michelson, anthropic principle, Apollo 13, artificial general intelligence, Bonfire of the Vanities, Charles Babbage, Computing Machinery and Intelligence, conceptual framework, cosmological principle, dark matter, David Attenborough, discovery of DNA, Douglas Hofstadter, Easter island, Eratosthenes, Ernest Rutherford, first-past-the-post, Georg Cantor, global pandemic, Gödel, Escher, Bach, illegal immigration, invention of movable type, Isaac Newton, Islamic Golden Age, Jacquard loom, Johannes Kepler, John Conway, John von Neumann, Joseph-Marie Jacquard, Kenneth Arrow, Loebner Prize, Louis Pasteur, mirror neurons, Nick Bostrom, pattern recognition, Pierre-Simon Laplace, precautionary principle, Richard Feynman, Search for Extraterrestrial Intelligence, seminal paper, Stephen Hawking, supervolcano, technological singularity, Thales of Miletus, The Coming Technological Singularity, the scientific method, Thomas Malthus, Thorstein Veblen, Turing test, Vernor Vinge, Whole Earth Review, William of Occam, zero-sum game

He is rightly known as the father of modern computing. Babbage deserves to be called its grandfather, but, unlike Babbage and Lovelace, Turing did understand that artificial intelligence (AI) must in principle be possible because a universal computer is a universal simulator. In 1950, in a paper entitled ‘Computing Machinery and Intelligence’, he famously addressed the question: can a machine think? Not only did he defend the proposition that it can, on the grounds of universality, he also proposed a test for whether a program had achieved it. Now known as the Turing test, it is simply that a suitable (human) judge be unable to tell whether the program is human or not.

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., Science and Ultimate Reality (Cambridge University Press, 2003) David Deutsch, ‘Quantum Theory of Probability and Decisions’, Proceedings of the Royal Society A455 (1999) David Deutsch, ‘The Structure of the Multiverse’, Proceedings of the Royal Society A458 (2002) Richard Feynman, The Character of Physical Law (BBC Publications, 1965) Richard Feynman, The Meaning of It All (Allen Lane, 1998) Ernest Gellner, Words and Things (Routledge & Kegan Paul, 1979) William Godwin, Enquiry Concerning Political Justice (1793) Douglas Hofstadter, Gödel, Escher, Bach: An Eternal Golden Braid (Basic Books, 1979) Douglas Hofstadter, I am a Strange Loop (Basic Books, 2007) Bryan Magee, Popper (Fontana, 1973) Pericles, ‘Funeral Oration’ Plato, Euthyphro Karl Popper, In Search of a Better World (Routledge, 1995) Karl Popper, The World of Parmenides (Routledge, 1998) Roy Porter, Enlightenment: Britain and the Creation of the Modern World (Allen Lane, 2000) Martin Rees, Just Six Numbers (Basic Books, 2001) Alan Turing, ‘Computing Machinery and Intelligence’, Mind, 59, 236 (October 1950) Jenny Uglow, The Lunar Men (Faber, 2002) Vernor Vinge, ‘The Coming Technological Singularity’, Whole Earth Review, winter 1993 *The term was coined by the philosopher Norwood Russell Hanson. *This terminology differs slightly from that of Dawkins.

The Alignment Problem: Machine Learning and Human Values by Brian Christian

Albert Einstein, algorithmic bias, Alignment Problem, AlphaGo, Amazon Mechanical Turk, artificial general intelligence, augmented reality, autonomous vehicles, backpropagation, butterfly effect, Cambridge Analytica, Cass Sunstein, Claude Shannon: information theory, computer vision, Computing Machinery and Intelligence, data science, deep learning, DeepMind, Donald Knuth, Douglas Hofstadter, effective altruism, Elaine Herzberg, Elon Musk, Frances Oldham Kelsey, game design, gamification, Geoffrey Hinton, Goodhart's law, Google Chrome, Google Glasses, Google X / Alphabet X, Gödel, Escher, Bach, Hans Moravec, hedonic treadmill, ImageNet competition, industrial robot, Internet Archive, John von Neumann, Joi Ito, Kenneth Arrow, language acquisition, longitudinal study, machine translation, mandatory minimum, mass incarceration, multi-armed bandit, natural language processing, Nick Bostrom, Norbert Wiener, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, OpenAI, Panopticon Jeremy Bentham, pattern recognition, Peter Singer: altruism, Peter Thiel, precautionary principle, premature optimization, RAND corporation, recommendation engine, Richard Feynman, Rodney Brooks, Saturday Night Live, selection bias, self-driving car, seminal paper, side project, Silicon Valley, Skinner box, sparse data, speech recognition, Stanislav Petrov, statistical model, Steve Jobs, strong AI, the map is not the territory, theory of mind, Tim Cook: Apple, W. E. B. Du Bois, Wayback Machine, zero-sum game

The answer which seems to me to fit all or nearly all the facts is . . . the force and mechanism of reinforcement, applied to a connection. —EDWARD THORNDIKE12 If the animal researchers following Thorndike were, like he was, ultimately interested in the psychology of the human child, they were not alone; computer scientists—the very first ones—were too. Alan Turing’s most famous paper, “Computing Machinery and Intelligence,” in 1950, explicitly framed the project of artificial intelligence in these terms. “Instead of trying to produce a programme to simulate the adult mind,” he wrote, “why not rather try to produce one which simulates the child’s? If this were then subjected to an appropriate course of education one would obtain the adult brain.”

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“Reliance on Head Versus Eyes in the Gaze Following of Great Apes and Human Infants: The Cooperative Eye Hypothesis.” Journal of Human Evolution 52, no. 3 (2007): 314–20. Tomasik, Brian. “Do Artificial Reinforcement-Learning Agents Matter Morally?” arXiv Preprint arXiv:1410.8233, 2014. Turing, A. M. “Computing Machinery and Intelligence.” Mind 59, no. 236 (1950): 433–60. ———. “Intelligent Machinery.” In The Essential Turing, edited by B. Jack Copeland, 410–32. 1948. Reprint, Oxford University Press, 2004. Turing, Alan. “Can Digital Computers Think?” BBC Third Programme, May 15, 1951. Turing, Alan, Richard Braithwaite, Geoffrey Jefferson, and Max Newman.

The Logician and the Engineer: How George Boole and Claude Shannon Created the Information Age by Paul J. Nahin

air gap, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, Any sufficiently advanced technology is indistinguishable from magic, Charles Babbage, Claude Shannon: information theory, Computing Machinery and Intelligence, conceptual framework, Edward Thorp, Fellow of the Royal Society, finite state, four colour theorem, Georg Cantor, Grace Hopper, Isaac Newton, John von Neumann, knapsack problem, New Journalism, Pierre-Simon Laplace, reversible computing, Richard Feynman, Schrödinger's Cat, Steve Jobs, Steve Wozniak, thinkpad, Thomas Bayes, Turing machine, Turing test, V2 rocket

For example, what do you get if you multiply all the rational fractions by all the rational fractions? Why, nothing more or less than just all the rational fractions back again!6 NOTES AND REFERENCES 1. The reference to Turing is almost certainly due to Shannon having read Turing’s famous paper “Computing Machinery and Intelligence,” Mind, October 1950, pp. 433–460. It was in this paper that Turing put forth what was to become famous in computer science as the Turing test, an experimental procedure to unemotionally decide if a machine possessed artificial intelligence. For Turing’s comparison of ideas to neutrons, see in particular, p. 454. 2.

Work in the Future The Automation Revolution-Palgrave MacMillan (2019) by Robert Skidelsky Nan Craig

3D printing, Airbnb, algorithmic trading, AlphaGo, Alvin Toffler, Amazon Web Services, anti-work, antiwork, artificial general intelligence, asset light, autonomous vehicles, basic income, behavioural economics, business cycle, cloud computing, collective bargaining, Computing Machinery and Intelligence, correlation does not imply causation, creative destruction, data is the new oil, data science, David Graeber, David Ricardo: comparative advantage, deep learning, DeepMind, deindustrialization, Demis Hassabis, deskilling, disintermediation, do what you love, Donald Trump, driverless car, Erik Brynjolfsson, fake news, feminist movement, Ford Model T, Frederick Winslow Taylor, future of work, Future Shock, general purpose technology, gig economy, global supply chain, income inequality, independent contractor, informal economy, Internet of things, Jarndyce and Jarndyce, Jarndyce and Jarndyce, job automation, job polarisation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Joseph Schumpeter, knowledge economy, Loebner Prize, low skilled workers, Lyft, Mark Zuckerberg, means of production, moral panic, Network effects, new economy, Nick Bostrom, off grid, pattern recognition, post-work, Ronald Coase, scientific management, Second Machine Age, self-driving car, sharing economy, SoftBank, Steve Jobs, strong AI, tacit knowledge, technological determinism, technoutopianism, TED Talk, The Chicago School, The Future of Employment, the market place, The Nature of the Firm, The Wealth of Nations by Adam Smith, Thorstein Veblen, Turing test, Uber for X, uber lyft, universal basic income, wealth creators, working poor

Philosophy in a New Century: Selected Essays. Cambridge: Cambridge University Press. Turello, D. (2015). Brain, Mind, and Consciousness: A Conversation with Philosopher John Searle. Library of Congress, March 3. Retrieved from https:// blogs.loc.gov/kluge/2015/03/conversation-with-john-searle/ Turing, A. M. (1950). Computing Machinery and Intelligence. Mind, New Series, 59(236), 433–460. 12 Possibilities and Limitations for AI: What Can’t Machines Do? Simon Colton I will talk here about limitations and possibilities for Artificial Intelligence (AI) in the future of work. I will put forward my opinion that we can and should take a practical rather than philosophical view of what intelligent algorithms are already doing in work environments, and plan for solid and sensible, rather than sensational, mid-term progress that will bring benefits to workforces, but only if advanced AI systems are properly handled by business leaders and politicians, amongst others.

Leadership by Algorithm: Who Leads and Who Follows in the AI Era? by David de Cremer

"Friedman doctrine" OR "shareholder theory", algorithmic bias, algorithmic management, AlphaGo, bitcoin, blockchain, business climate, business process, Computing Machinery and Intelligence, corporate governance, data is not the new oil, data science, deep learning, DeepMind, Donald Trump, Elon Musk, fake news, future of work, job automation, Kevin Kelly, Mark Zuckerberg, meta-analysis, Norbert Wiener, pattern recognition, Peter Thiel, race to the bottom, robotic process automation, Salesforce, scientific management, shareholder value, Silicon Valley, Social Responsibility of Business Is to Increase Its Profits, Stephen Hawking, The Future of Employment, Turing test, work culture , workplace surveillance , zero-sum game

Depicted by actor Benedict Cumberbatch in the movie The Imitation Game, Alan Turing is best known for his accomplishment of deciphering the Enigma code used by the Germans during the second world war. To achieve this, he developed an electro-mechanical computer, which was called the Bombe. The fact that the Bombe achieved something that no human was capable of led Turing to think about the intelligence of the machine. This led to his 1950 article, ‘Computing Machinery and Intelligence,’ in which he introduced the now-famous Alan Turing test, which is today still considered the crucial test to determine whether a machine is truly intelligent. In the test, a human interacts with another human and a machine. The participant cannot see the other human or the machine and can only use information on how the other unseen party behaves.

Power and Progress: Our Thousand-Year Struggle Over Technology and Prosperity by Daron Acemoglu, Simon Johnson

"Friedman doctrine" OR "shareholder theory", "World Economic Forum" Davos, 4chan, agricultural Revolution, AI winter, Airbnb, airline deregulation, algorithmic bias, algorithmic management, Alignment Problem, AlphaGo, An Inconvenient Truth, artificial general intelligence, augmented reality, basic income, Bellingcat, Bernie Sanders, Big Tech, Bletchley Park, blue-collar work, British Empire, carbon footprint, carbon tax, carried interest, centre right, Charles Babbage, ChatGPT, Clayton Christensen, clean water, cloud computing, collapse of Lehman Brothers, collective bargaining, computer age, Computer Lib, Computing Machinery and Intelligence, conceptual framework, contact tracing, Corn Laws, Cornelius Vanderbilt, coronavirus, corporate social responsibility, correlation does not imply causation, cotton gin, COVID-19, creative destruction, declining real wages, deep learning, DeepMind, deindustrialization, Demis Hassabis, Deng Xiaoping, deskilling, discovery of the americas, disinformation, Donald Trump, Douglas Engelbart, Douglas Engelbart, Edward Snowden, Elon Musk, en.wikipedia.org, energy transition, Erik Brynjolfsson, European colonialism, everywhere but in the productivity statistics, factory automation, facts on the ground, fake news, Filter Bubble, financial innovation, Ford Model T, Ford paid five dollars a day, fulfillment center, full employment, future of work, gender pay gap, general purpose technology, Geoffrey Hinton, global supply chain, Gordon Gekko, GPT-3, Grace Hopper, Hacker Ethic, Ida Tarbell, illegal immigration, income inequality, indoor plumbing, industrial robot, interchangeable parts, invisible hand, Isaac Newton, Jacques de Vaucanson, James Watt: steam engine, Jaron Lanier, Jeff Bezos, job automation, Johannes Kepler, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joseph-Marie Jacquard, Kenneth Arrow, Kevin Roose, Kickstarter, knowledge economy, labor-force participation, land reform, land tenure, Les Trente Glorieuses, low skilled workers, low-wage service sector, M-Pesa, manufacturing employment, Marc Andreessen, Mark Zuckerberg, megacity, mobile money, Mother of all demos, move fast and break things, natural language processing, Neolithic agricultural revolution, Norbert Wiener, NSO Group, offshore financial centre, OpenAI, PageRank, Panopticon Jeremy Bentham, paperclip maximiser, pattern recognition, Paul Graham, Peter Thiel, Productivity paradox, profit maximization, profit motive, QAnon, Ralph Nader, Ray Kurzweil, recommendation engine, ride hailing / ride sharing, Robert Bork, Robert Gordon, Robert Solow, robotic process automation, Ronald Reagan, scientific management, Second Machine Age, self-driving car, seminal paper, shareholder value, Sheryl Sandberg, Shoshana Zuboff, Silicon Valley, social intelligence, Social Responsibility of Business Is to Increase Its Profits, social web, South Sea Bubble, speech recognition, spice trade, statistical model, stem cell, Steve Jobs, Steve Wozniak, strikebreaker, subscription business, Suez canal 1869, Suez crisis 1956, supply-chain management, surveillance capitalism, tacit knowledge, tech billionaire, technoutopianism, Ted Nelson, TED Talk, The Future of Employment, The Rise and Fall of American Growth, The Structural Transformation of the Public Sphere, The Wealth of Nations by Adam Smith, theory of mind, Thomas Malthus, too big to fail, total factor productivity, trade route, transatlantic slave trade, trickle-down economics, Turing machine, Turing test, Twitter Arab Spring, Two Sigma, Tyler Cowen, Tyler Cowen: Great Stagnation, union organizing, universal basic income, Unsafe at Any Speed, Upton Sinclair, upwardly mobile, W. E. B. Du Bois, War on Poverty, WikiLeaks, wikimedia commons, working poor, working-age population

Undeterred by the hostile reactions of participants, Turing continued to work on the problem. In 1951 he wrote: “‘You cannot make a machine think for you.’ This is a commonplace that is usually accepted without question. It will be the purpose of this paper to question it.” His seminal 1950 paper, “Computing Machinery and Intelligence,” defines one notion of what it means for a machine to be intelligent. Turing imagined an “imitation game” (now called a Turing test) in which an evaluator engages in a conversation with two entities, one human and one machine. By asking a series of questions communicated via a computer keyboard and screen, the evaluator attempts to tell which one is which.

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Forbes, December 2. www.forbes.com/sites/cognitiveworld/2018/12/02/the-big-rpa-bubble/?sh=9972fe68d950. Tugwell, Rexford G. 1933. “Design for Government.” Political Science Quarterly 48, no. 3 (September): 331‒332. Tunzelmann, G. N. von. 1978. Steam Power and British Industrialization to 1860. Oxford: Clarendon. Turing, Alan. 1950. “Computing Machinery and Intelligence.” Mind 59, no. 236: 433–460. Turing, Alan. 1951 [2004]. “Intelligent Machinery, a Heretical Theory.” In The Turing Test: Verbal Behavior as the Hallmark of Intelligence, edited by Stuart M. Shieber, 105–110. Cambridge, MA: MIT Press. Turner, John. 1991. Social Influence. New York: Thomson Brooks/Cole.

Life at the Speed of Light: From the Double Helix to the Dawn of Digital Life by J. Craig Venter

Albert Einstein, Alfred Russel Wallace, Apollo 11, Asilomar, Barry Marshall: ulcers, bioinformatics, borderless world, Brownian motion, clean water, Computing Machinery and Intelligence, discovery of DNA, double helix, dual-use technology, epigenetics, experimental subject, global pandemic, Gregor Mendel, Helicobacter pylori, Isaac Newton, Islamic Golden Age, John von Neumann, Louis Pasteur, Mars Rover, Mikhail Gorbachev, phenotype, precautionary principle, Recombinant DNA, Richard Feynman, stem cell, Stuart Kauffman, synthetic biology, the scientific method, Thomas Kuhn: the structure of scientific revolutions, Turing machine

Turing’s Cathedral: The Origins of the Digital Universe (London: Allen Lane, 2012), p. 284. 23. Schrödinger, What Is Life?, pp. 20–21. 24. Brenner, “Life’s code script.” 25. J. D. Watson and F. H. Crick. “Molecular structure of nucleic acids: A structure for deoxyribose nucleic acid.” Nature 171, no. 4356 (April 25, 1953): pp. 737–38. 26. A. M. Turing. “Computing machinery and intelligence.” Mind 59, no. 236 (October 1950): pp. 433–60. Accessible online at www.loebner.net/Prizef/TuringArticle.html. 27. Ibid. 28. Mark A. Bedau. “Artificial life: Organization, adaptation and complexity from the bottom up.” Trends in Cognitive Sciences 7, no. 11 (November 2003): pp. 505–512.

Web Scraping With Python: Collecting Data From the Modern Web by Ryan Mitchell

AltaVista, Amazon Web Services, Apollo 13, cloud computing, Computing Machinery and Intelligence, data science, en.wikipedia.org, Firefox, Guido van Rossum, information security, machine readable, meta-analysis, natural language processing, optical character recognition, random walk, self-driving car, Turing test, web application

Reading CAPTCHAs and Training Tesseract Although the word “CAPTCHA” is familiar to most, far fewer people know what it stands for: Computer Automated Public Turing test to tell Computers and Humans Apart. Its unwieldy acronym hints at its rather unwieldy role in obstructing otherwise perfectly usable web interfaces, as both humans and nonhuman robots often struggle to solve CAPTCHA tests. The Turing test was first described by Alan Turing in his 1950 paper, “Computing Machinery and Intelligence.” In the paper, he described a setup in which a human being could communicate with both humans and artificial intelligence programs through a computer terminal. If the human was unable to distinguish the humans from the AI programs during a casual conversation, the AI programs would be con‐ sidered to have passed the Turing test, and the artificial intelligence, Turing reasoned, would be genuinely “thinking” for all intents and purposes.

Total Recall: How the E-Memory Revolution Will Change Everything by Gordon Bell, Jim Gemmell

airport security, Albert Einstein, book scanning, cloud computing, Computing Machinery and Intelligence, conceptual framework, Douglas Engelbart, full text search, information retrieval, invention of writing, inventory management, Isaac Newton, Ivan Sutherland, John Markoff, language acquisition, lifelogging, Menlo Park, optical character recognition, pattern recognition, performance metric, RAND corporation, RFID, semantic web, Silicon Valley, Skype, social web, statistical model, Stephen Hawking, Steve Ballmer, Steve Bannon, Ted Nelson, telepresence, Turing test, Vannevar Bush, web application

Pondering digital immortality with Jim Gray back in 2001: Bell, G., and J. N. Gray. 2001. “Digital Immortality.” Communications of the ACM 44, no. 3 (March): 28-30. MyCyberTwin: MyCyberTwin Web site. www.mycybertwin.com Roush, Wade. 2007. Your Virtual Clone. Technology Review (April 20). The Turing test: Turing, A. 1950. “Computing Machinery and Intelligence.” Mind 59, no. 236: 433-60. Creating biographical and family histories: LifeBio: www.lifebio.com, formed in 2000, has a process, tools, and software to enable a person, family, or groups to create stories and documents that can be printed or displayed on the Web. 8. REVOLUTION Dear Appy: Bell, Gordon. 2000.

The Man Who Invented the Computer by Jane Smiley

1919 Motor Transport Corps convoy, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, anti-communist, Arthur Eddington, Bletchley Park, British Empire, c2.com, Charles Babbage, computer age, Computing Machinery and Intelligence, Fellow of the Royal Society, Ford Model T, Henri Poincaré, IBM and the Holocaust, Isaac Newton, John von Neumann, Karl Jansky, machine translation, Norbert Wiener, Norman Macrae, Pierre-Simon Laplace, punch-card reader, RAND corporation, Turing machine, Vannevar Bush, Von Neumann architecture

For the next year, he discussed and pondered the question of thinking—how, indeed, could a machine be said to be “thinking”? How could a human interacting with a machine without knowing it detect whether he was interacting with a machine or with another human? The result was a paper, published in October 1950, entitled “Computing Machinery and Intelligence.” Turing proposed a thought experiment, a situation in which an investigator would question a man (A) and a woman (B) in order to determine which was the man and which was the woman. The man would be told to obstruct the investigator, and the woman would be instructed to help the investigator.

On Intelligence by Jeff Hawkins, Sandra Blakeslee

airport security, Albert Einstein, backpropagation, computer age, Computing Machinery and Intelligence, conceptual framework, Jeff Hawkins, Johannes Kepler, Necker cube, PalmPilot, pattern recognition, Paul Erdős, Ray Kurzweil, Silicon Valley, Silicon Valley startup, speech recognition, superintelligent machines, the scientific method, Thomas Bayes, Turing machine, Turing test

"Minds, Brains, and Programs," The Behavioral and Brain Sciences, vol. 3 (1980): pp. 417–24. Presents the famous "Chinese Room" argument against computation as a model for the mind. You can find many descriptions and discussions of Searle's thought experiment on the World Wide Web. Turing, A. M. "Computing Machinery and Intelligence," Mind, vol. 59 (1950): pp. 433–60. Presents the famous "Turing Test" for detecting the presence of intelligence. Again, many references and discussions on the Turing Test can be found on the World Wide Web. Palm, Günther. Neural Assemblies: An Alternative Approach to Artificial Intelligence (New York: Springer Verlag, 1982).

Outnumbered: From Facebook and Google to Fake News and Filter-Bubbles – the Algorithms That Control Our Lives by David Sumpter

affirmative action, algorithmic bias, AlphaGo, Bernie Sanders, Brexit referendum, Cambridge Analytica, classic study, cognitive load, Computing Machinery and Intelligence, correlation does not imply causation, crowdsourcing, data science, DeepMind, Demis Hassabis, disinformation, don't be evil, Donald Trump, Elon Musk, fake news, Filter Bubble, Geoffrey Hinton, Google Glasses, illegal immigration, James Webb Space Telescope, Jeff Bezos, job automation, Kenneth Arrow, Loebner Prize, Mark Zuckerberg, meta-analysis, Minecraft, Nate Silver, natural language processing, Nelson Mandela, Nick Bostrom, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, p-value, post-truth, power law, prediction markets, random walk, Ray Kurzweil, Robert Mercer, selection bias, self-driving car, Silicon Valley, Skype, Snapchat, social contagion, speech recognition, statistical model, Stephen Hawking, Steve Bannon, Steven Pinker, TED Talk, The Signal and the Noise by Nate Silver, traveling salesman, Turing test

‘Current-reinforced random walks for constructing transport networks.’ Journal of the Royal Society Interface 10, no. 80: 20120864. 14 Baker, M. D. and Stock, J. B. 2007. ‘Signal transduction: networks and integrated circuits in bacterial cognition.’ Current Biology 17, no. 23: R1021–4. 15 Turing, A. M. 1950. ‘Computing machinery and intelligence.’ Mind 59, no. 236: 433–60. 16 I looked at one such example in the following article: Herbert-Read, J. E., Romenskyy, M. and Sumpter, D. J. T. 2015. ‘A Turing test for collective motion.’ Biology letters 11, no. 12: 20150674. 17 www.facebook.com/zuck/posts/10154361492931634 Chapter 18 : Back to Reality 1 Although you can find this on Reddit, of course: www.reddit.com/r/TheSilphRoad/comments/6ryd6e/cumulative_probability_legendary_raid_boss_catch Acknowledgements Thank you to all the people who I interviewed or answered my questions over email for this book.

Social Life of Information by John Seely Brown, Paul Duguid

Alvin Toffler, business process, Charles Babbage, Claude Shannon: information theory, computer age, Computing Machinery and Intelligence, cross-subsidies, disintermediation, double entry bookkeeping, Frank Gehry, frictionless, frictionless market, future of work, George Gilder, George Santayana, global village, Goodhart's law, Howard Rheingold, informal economy, information retrieval, invisible hand, Isaac Newton, John Markoff, John Perry Barlow, junk bonds, Just-in-time delivery, Kenneth Arrow, Kevin Kelly, knowledge economy, knowledge worker, lateral thinking, loose coupling, Marshall McLuhan, medical malpractice, Michael Milken, moral hazard, Network effects, new economy, Productivity paradox, Robert Metcalfe, rolodex, Ronald Coase, scientific management, shareholder value, Shoshana Zuboff, Silicon Valley, Steve Jobs, Superbowl ad, tacit knowledge, Ted Nelson, telepresence, the medium is the message, The Nature of the Firm, the strength of weak ties, The Wealth of Nations by Adam Smith, Thomas Malthus, transaction costs, Turing test, Vannevar Bush, Y2K

Princeton, NJ: Princeton University Press. Trollope, Frances. 1984. Domestic Manners of the Americans. Oxford: Oxford University Press, 1984. Trow, Martin. 1996. "Trust, Markets, and Accountability in Higher Education: A Comparative Perspective." Higher Education Policy 9 (4): 309 324. Turing, Alan. 1963. "Computing Machinery and Intelligence." In Computers and Thought, edited by Edward A. Feigenbaum and Julian Feldman, 11 35. New York: McGraw-Hill. Van Maanen, John, and Stephen R. Barley. 1984. "Occupational Communities: Culture and Control in Organizations." In vol. 6 of Research in Organizational Behavior, edited by Barry M.

Our Final Invention: Artificial Intelligence and the End of the Human Era by James Barrat

AI winter, air gap, AltaVista, Amazon Web Services, artificial general intelligence, Asilomar, Automated Insights, Bayesian statistics, Bernie Madoff, Bill Joy: nanobots, Bletchley Park, brain emulation, California energy crisis, cellular automata, Chuck Templeton: OpenTable:, cloud computing, cognitive bias, commoditize, computer vision, Computing Machinery and Intelligence, cuban missile crisis, Daniel Kahneman / Amos Tversky, Danny Hillis, data acquisition, don't be evil, drone strike, dual-use technology, Extropian, finite state, Flash crash, friendly AI, friendly fire, Google Glasses, Google X / Alphabet X, Hacker News, Hans Moravec, Isaac Newton, Jaron Lanier, Jeff Hawkins, John Markoff, John von Neumann, Kevin Kelly, Law of Accelerating Returns, life extension, Loebner Prize, lone genius, machine translation, mutually assured destruction, natural language processing, Neil Armstrong, Nicholas Carr, Nick Bostrom, optical character recognition, PageRank, PalmPilot, paperclip maximiser, pattern recognition, Peter Thiel, precautionary principle, prisoner's dilemma, Ray Kurzweil, Recombinant DNA, Rodney Brooks, rolling blackouts, Search for Extraterrestrial Intelligence, self-driving car, semantic web, Silicon Valley, Singularitarianism, Skype, smart grid, speech recognition, statistical model, stealth mode startup, stem cell, Stephen Hawking, Steve Jobs, Steve Jurvetson, Steve Wozniak, strong AI, Stuxnet, subprime mortgage crisis, superintelligent machines, technological singularity, The Coming Technological Singularity, Thomas Bayes, traveling salesman, Turing machine, Turing test, Vernor Vinge, Watson beat the top human players on Jeopardy!, zero day

Between 2002 and 2005: Yudkowsky, Eliezer, “Shut Up and Do the Impossible,” Less Wrong (blog), October 8, 2008, http://lesswrong.com/lw/up/shut_up_and_do_the_impossible/ (accessed May 18, 2010). From this starting point you can start a search on the AI-Box Experiment, and learn almost everything about it I did. May not machines carry out: Turing, A. M., “Computing Machinery and Intelligence,” Mind, 49 (1950):433–460. Marvin Minsky, one of the founders: Newsgroups, “comp.ai,comp.ai.philosophy.” Last modified March 30, 1995, http://loebner.net/Prizef/minsky.txt (accessed July 18, 2011). 5: PROGRAMS THAT WRITE PROGRAMS … we are beginning to depend: Hillis, Danny, “The Big Picture,” WIRED, June 1, 1998.

Wonderland: How Play Made the Modern World by Steven Johnson

"hyperreality Baudrillard"~20 OR "Baudrillard hyperreality", Ada Lovelace, adjacent possible, Alfred Russel Wallace, Antoine Gombaud: Chevalier de Méré, Berlin Wall, bitcoin, Book of Ingenious Devices, Buckminster Fuller, Charles Babbage, Claude Shannon: information theory, Clayton Christensen, colonial exploitation, computer age, Computing Machinery and Intelligence, conceptual framework, cotton gin, crowdsourcing, cuban missile crisis, Drosophila, Edward Thorp, Fellow of the Royal Society, flying shuttle, game design, global village, Great Leap Forward, Hedy Lamarr / George Antheil, HyperCard, invention of air conditioning, invention of the printing press, invention of the telegraph, Islamic Golden Age, Jacquard loom, Jacques de Vaucanson, James Watt: steam engine, Jane Jacobs, John von Neumann, joint-stock company, Joseph-Marie Jacquard, land value tax, Landlord’s Game, Lewis Mumford, lone genius, mass immigration, megacity, Minecraft, moral panic, Murano, Venice glass, music of the spheres, Necker cube, New Urbanism, Oculus Rift, On the Economy of Machinery and Manufactures, pattern recognition, peer-to-peer, pets.com, placebo effect, pneumatic tube, probability theory / Blaise Pascal / Pierre de Fermat, profit motive, QWERTY keyboard, Ray Oldenburg, SimCity, spice trade, spinning jenny, statistical model, Steve Jobs, Steven Pinker, Stewart Brand, supply-chain management, talking drums, the built environment, The Great Good Place, the scientific method, The Structural Transformation of the Public Sphere, trade route, Turing machine, Turing test, Upton Sinclair, urban planning, vertical integration, Victor Gruen, Watson beat the top human players on Jeopardy!, white flight, white picket fence, Whole Earth Catalog, working poor, Wunderkammern

Deep Blue, the computer that ultimately defeated Gary Kasparov at chess, had been a Grand Challenge a decade before, exceeding Alan Turing’s hunch that chess-playing computers could be made to play a tolerable game. Horn was interested in Turing’s more celebrated challenge: the Turing Test, which he first formulated in a 1950 essay on “Computing Machinery and Intelligence.” In Turing’s words, “A computer would deserve to be called intelligent if it could deceive a human into believing that it was human.” The deception of the Turing Test had nothing to do with physical appearances; the classic Turing Test scenario involves a human sitting at a keyboard, engaged in a text-based conversation with an unknown entity who may or may not be a machine.

Richard Dawkins: How a Scientist Changed the Way We Think by Alan Grafen; Mark Ridley

Alfred Russel Wallace, Arthur Eddington, bioinformatics, Charles Babbage, cognitive bias, computer age, Computing Machinery and Intelligence, conceptual framework, Dava Sobel, double helix, Douglas Hofstadter, Easter island, epigenetics, Fellow of the Royal Society, Haight Ashbury, interchangeable parts, Isaac Newton, Johann Wolfgang von Goethe, John von Neumann, loose coupling, Murray Gell-Mann, Necker cube, phenotype, profit maximization, public intellectual, Ronald Reagan, Stephen Hawking, Steven Pinker, the scientific method, theory of mind, Thomas Kuhn: the structure of scientific revolutions, Yogi Berra, zero-sum game

Dennett, ‘The New Replicators’, in Mark Page (ed.), The Encyclopedia of Evolution (Oxford: Oxford University Press, 2002), vol. 1, E83-E92. 36 J. M. Balkin, Cultural Software: A Theory of Ideology (New Haven: Yale University Press, 1998). 37 Daniel C. Dennett, Breaking the Spell (London: Penguin, 2006). 38 A. Turing, ‘Computing Machinery and Intelligence’, Mind, 59 (1950): 433-46°. 39 Thomas Kuhn, The Structure of Scientific Revolutions (Chicago: University of Chicago Press, 1962). The invention of an algorithmic biology Seth Bullock BIOLOGY and computing might not seem the most comfortable of bedfellows. It is easy to imagine nature and technology clashing as the green-welly brigade rub up awkwardly against the back-room boffins.

Heart of the Machine: Our Future in a World of Artificial Emotional Intelligence by Richard Yonck

3D printing, AI winter, AlphaGo, Apollo 11, artificial general intelligence, Asperger Syndrome, augmented reality, autism spectrum disorder, backpropagation, Berlin Wall, Bletchley Park, brain emulation, Buckminster Fuller, call centre, cognitive bias, cognitive dissonance, computer age, computer vision, Computing Machinery and Intelligence, crowdsourcing, deep learning, DeepMind, Dunning–Kruger effect, Elon Musk, en.wikipedia.org, epigenetics, Fairchild Semiconductor, friendly AI, Geoffrey Hinton, ghettoisation, industrial robot, Internet of things, invention of writing, Jacques de Vaucanson, job automation, John von Neumann, Kevin Kelly, Law of Accelerating Returns, Loebner Prize, Menlo Park, meta-analysis, Metcalfe’s law, mirror neurons, Neil Armstrong, neurotypical, Nick Bostrom, Oculus Rift, old age dependency ratio, pattern recognition, planned obsolescence, pneumatic tube, RAND corporation, Ray Kurzweil, Rodney Brooks, self-driving car, Skype, social intelligence, SoftBank, software as a service, SQL injection, Stephen Hawking, Steven Pinker, superintelligent machines, technological singularity, TED Talk, telepresence, telepresence robot, The future is already here, The Future of Employment, the scientific method, theory of mind, Turing test, twin studies, Two Sigma, undersea cable, Vernor Vinge, Watson beat the top human players on Jeopardy!, Whole Earth Review, working-age population, zero day

Without even more sophisticated technology (augmented by human intelligence, a crucial ingredient), the Allies couldn’t have cracked what was the cutting-edge and nearly unbreakable encryption of its day. Following the war, Turing, still sworn to silence under the Britain’s Official Secrets Acts, published his famous 1950 paper, “Computing Machinery and Intelligence,” which opens with the words “I propose to consider the question, ‘Can machines think?’”7 Combine this with other insights, such as the formalized logic of mid-nineteenth-century mathematician and logician George Boole, author of The Laws of Thought, and it’s even easier to see how computer scientists were blind to the difficulties they faced.

The Big Nine: How the Tech Titans and Their Thinking Machines Could Warp Humanity by Amy Webb

"Friedman doctrine" OR "shareholder theory", Ada Lovelace, AI winter, air gap, Airbnb, airport security, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, algorithmic bias, AlphaGo, Andy Rubin, artificial general intelligence, Asilomar, autonomous vehicles, backpropagation, Bayesian statistics, behavioural economics, Bernie Sanders, Big Tech, bioinformatics, Black Lives Matter, blockchain, Bretton Woods, business intelligence, Cambridge Analytica, Cass Sunstein, Charles Babbage, Claude Shannon: information theory, cloud computing, cognitive bias, complexity theory, computer vision, Computing Machinery and Intelligence, CRISPR, cross-border payments, crowdsourcing, cryptocurrency, Daniel Kahneman / Amos Tversky, data science, deep learning, DeepMind, Demis Hassabis, Deng Xiaoping, disinformation, distributed ledger, don't be evil, Donald Trump, Elon Musk, fail fast, fake news, Filter Bubble, Flynn Effect, Geoffrey Hinton, gig economy, Google Glasses, Grace Hopper, Gödel, Escher, Bach, Herman Kahn, high-speed rail, Inbox Zero, Internet of things, Jacques de Vaucanson, Jeff Bezos, Joan Didion, job automation, John von Neumann, knowledge worker, Lyft, machine translation, Mark Zuckerberg, Menlo Park, move fast and break things, Mustafa Suleyman, natural language processing, New Urbanism, Nick Bostrom, one-China policy, optical character recognition, packet switching, paperclip maximiser, pattern recognition, personalized medicine, RAND corporation, Ray Kurzweil, Recombinant DNA, ride hailing / ride sharing, Rodney Brooks, Rubik’s Cube, Salesforce, Sand Hill Road, Second Machine Age, self-driving car, seminal paper, SETI@home, side project, Silicon Valley, Silicon Valley startup, skunkworks, Skype, smart cities, South China Sea, sovereign wealth fund, speech recognition, Stephen Hawking, strong AI, superintelligent machines, surveillance capitalism, technological singularity, The Coming Technological Singularity, the long tail, theory of mind, Tim Cook: Apple, trade route, Turing machine, Turing test, uber lyft, Von Neumann architecture, Watson beat the top human players on Jeopardy!, zero day

He was able to show that such a person could be limited to a few extremely simple basic actions without changing the final outcome of the computation. Then, by proving that no machine performing only those basic actions could determine whether or not a given proposed conclusion follows from given premises… he was able to conclude that no algorithm for the Entscheidungsproblem exists.” 16. Alan Turing, “Computing Machinery and Intelligence,” Mind 59, no. 236 (1950): 433–60. 17. “A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence,” Stanford Computer Science Department’s Formal Reasoning Group, John McCarthy’s home page, links to articles of historical interest, last modified April 3, 1996, http://www-formal.stanford.edu/jmc/history/dartmouth/dartmouth.html. 18.

Messy: The Power of Disorder to Transform Our Lives by Tim Harford

affirmative action, Air France Flight 447, Airbnb, airport security, Albert Einstein, Amazon Mechanical Turk, Amazon Web Services, assortative mating, Atul Gawande, autonomous vehicles, banking crisis, Barry Marshall: ulcers, Basel III, Berlin Wall, Bletchley Park, British Empire, Broken windows theory, call centre, Cass Sunstein, Chris Urmson, cloud computing, collateralized debt obligation, Computing Machinery and Intelligence, crowdsourcing, deindustrialization, Donald Trump, Erdős number, experimental subject, Ferguson, Missouri, Filter Bubble, financial engineering, Frank Gehry, game design, global supply chain, Googley, Guggenheim Bilbao, Helicobacter pylori, high net worth, Inbox Zero, income inequality, industrial cluster, Internet of things, Jane Jacobs, Jeff Bezos, Loebner Prize, Louis Pasteur, machine readable, Marc Andreessen, Mark Zuckerberg, Menlo Park, Merlin Mann, microbiome, out of africa, Paul Erdős, Richard Thaler, Rosa Parks, self-driving car, side project, Silicon Valley, Silicon Valley startup, Skype, Steve Jobs, Steven Levy, Stewart Brand, Susan Wojcicki, tacit knowledge, TED Talk, telemarketer, the built environment, The Death and Life of Great American Cities, the strength of weak ties, Turing test, Tyler Cowen, urban decay, warehouse robotics, William Langewiesche

Gill Plimmer, “How to Cheat a Psychometric Test,” Financial Times, April 3, 2014, http://www.ft.com/cms/s/2/eeda84e4-b4f6-11e3-9166-00144feabdc0.html#axzz3pxipi4Dk. 27. Matt Novak, “Mechanical Matchmaking: The Science of Love in the 1920s,” Smithsonian, May 23, 2013, http://www.smithsonianmag.com/history/mechanical-matchmaking-the-science-of-love-in-the-1920s-103877403/#Dl8eC83OzkKhyp75.99. 28. A. M. Turing, “Computing Machinery and Intelligence,” Mind, 59 (1950), pp. 433–460. 29. Brian Christian, The Most Human Human (London: Viking, 2011). 30. “This Really Happened, No Joke (I Got Caught Using Jealous Girlfriend Opener),” The Attraction Forums, http://www.theattractionforums.com/general-discussion/46830-really-happened-no-joke-i-got-caught-using-jealous-girlfriend-opener.html. 31.

Being You: A New Science of Consciousness by Anil Seth

AlphaGo, artificial general intelligence, augmented reality, backpropagation, carbon-based life, Claude Shannon: information theory, computer age, computer vision, Computing Machinery and Intelligence, coronavirus, correlation does not imply causation, CRISPR, cryptocurrency, deep learning, deepfake, DeepMind, Drosophila, en.wikipedia.org, Filter Bubble, GPT-3, GPT-4, John Markoff, longitudinal study, Louis Pasteur, mirror neurons, Neil Armstrong, Nick Bostrom, Norbert Wiener, OpenAI, paperclip maximiser, pattern recognition, Paul Graham, Pierre-Simon Laplace, planetary scale, Plato's cave, precautionary principle, Ray Kurzweil, self-driving car, speech recognition, stem cell, systems thinking, technological singularity, TED Talk, telepresence, the scientific method, theory of mind, Thomas Bayes, TikTok, Turing test

PLoS Computational Biology, 16(4), e1007805. Tsuchiya, N., Wilke, M., Frässle, S., et al. (2015). ‘No-report paradigms: extracting the true neural correlates of consciousness’. Trends in Cognitive Sciences, 19(12), 757–70. Tulving, E. (1985). ‘Memory and consciousness’. Canadian Psychology, 26, 1–12. Turing, A. M. (1950). ‘Computing machinery and intelligence’. Mind, 59, 433–60. Uexküll, J. v. (1957). ‘A stroll through the worlds of animals and men: a picture book of invisible worlds’. In C. Schiller (ed.), Instinctive Behavior: The Development of a Modern Concept, New York: International Universities Press, 5. van Giesen, L., Kilian, P.

MegaThreats: Ten Dangerous Trends That Imperil Our Future, and How to Survive Them by Nouriel Roubini

"World Economic Forum" Davos, 2021 United States Capitol attack, 3D printing, 9 dash line, AI winter, AlphaGo, artificial general intelligence, asset allocation, assortative mating, autonomous vehicles, bank run, banking crisis, basic income, Bear Stearns, Big Tech, bitcoin, Bletchley Park, blockchain, Boston Dynamics, Bretton Woods, British Empire, business cycle, business process, call centre, carbon tax, Carmen Reinhart, cashless society, central bank independence, collateralized debt obligation, Computing Machinery and Intelligence, coronavirus, COVID-19, creative destruction, credit crunch, crony capitalism, cryptocurrency, currency manipulation / currency intervention, currency peg, data is the new oil, David Ricardo: comparative advantage, debt deflation, decarbonisation, deep learning, DeepMind, deglobalization, Demis Hassabis, democratizing finance, Deng Xiaoping, disintermediation, Dogecoin, Donald Trump, Elon Musk, en.wikipedia.org, energy security, energy transition, Erik Brynjolfsson, Ethereum, ethereum blockchain, eurozone crisis, failed state, fake news, family office, fiat currency, financial deregulation, financial innovation, financial repression, fixed income, floating exchange rates, forward guidance, Fractional reserve banking, Francis Fukuyama: the end of history, full employment, future of work, game design, geopolitical risk, George Santayana, Gini coefficient, global pandemic, global reserve currency, global supply chain, GPS: selective availability, green transition, Greensill Capital, Greenspan put, Herbert Marcuse, high-speed rail, Hyman Minsky, income inequality, inflation targeting, initial coin offering, Intergovernmental Panel on Climate Change (IPCC), Internet of things, invention of movable type, Isaac Newton, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, junk bonds, Kenneth Rogoff, knowledge worker, Long Term Capital Management, low interest rates, low skilled workers, low-wage service sector, M-Pesa, margin call, market bubble, Martin Wolf, mass immigration, means of production, meme stock, Michael Milken, middle-income trap, Mikhail Gorbachev, Minsky moment, Modern Monetary Theory, money market fund, money: store of value / unit of account / medium of exchange, moral hazard, mortgage debt, Mustafa Suleyman, Nash equilibrium, natural language processing, negative equity, Nick Bostrom, non-fungible token, non-tariff barriers, ocean acidification, oil shale / tar sands, oil shock, paradox of thrift, pets.com, Phillips curve, planetary scale, Ponzi scheme, precariat, price mechanism, price stability, public intellectual, purchasing power parity, quantitative easing, race to the bottom, Ralph Waldo Emerson, ransomware, Ray Kurzweil, regulatory arbitrage, reserve currency, reshoring, Robert Shiller, Ronald Reagan, Salesforce, Satoshi Nakamoto, Savings and loan crisis, Second Machine Age, short selling, Silicon Valley, smart contracts, South China Sea, sovereign wealth fund, Stephen Hawking, TED Talk, The Great Moderation, the payments system, Thomas L Friedman, TikTok, too big to fail, Turing test, universal basic income, War on Poverty, warehouse robotics, Washington Consensus, Watson beat the top human players on Jeopardy!, working-age population, Yogi Berra, Yom Kippur War, zero-sum game, zoonotic diseases

Assembly lines built war materiel, newfangled radar tracked aircraft, and researchers at Bletchley Park, England, used advanced mathematics to break secret German naval codes that revealed the whereabouts of deadly submarines. The brilliant and tragic Alan Turing led the code-breaking initiative. His Enigma machine shortened the war and saved countless lives. After the war, Turing wrote a paper entitled “Computing Machinery and Intelligence.” Instead of asking whether machines can think, he wondered whether computer responses might seem human by replicating the external manifestations of human thought processes. “This is the premise of Turing’s ‘imitation game,’ where a computer attempts to convince a human interrogator that it is, in fact, human rather than machine,” according to Matthew Scherer in the Spring 2016 Harvard Journal of Law and Technology.29 Turing imagined a place for artificial intelligence two decades before the term was coined.

New Horizons in the Study of Language and Mind by Noam Chomsky

Computing Machinery and Intelligence, dark matter, Isaac Newton, Jacques de Vaucanson, language acquisition, Sapir-Whorf hypothesis, tacit knowledge, theory of mind, Turing test

London, Methuen. Stryker, Michael (1994) “Precise development from imprecise rules.” Science 263: 1244–5. Thackray, Arnold (1970) Atoms and Powers. Cambridge, MA, Harvard University Press. Tremblay, Mireille (1991) “Possession and Datives.” PhD dissertation, McGill University. Turing, Alan (1950) “Computing Machinery and Intelligence.” Mind 49: 433– 60. Uebel, Thomas, with comments by Christopher Hookway (1995) The Vienna Circle Revisited. Centre for the Philosophy of the Natural and Social Sciences, London. DP 6/95. Ullman, Shimon (1979) The Interpretation of Visual Motion. Cambridge, MA, MIT Press. Waldrop, M.

Superminds: The Surprising Power of People and Computers Thinking Together by Thomas W. Malone

Abraham Maslow, agricultural Revolution, Airbnb, Albert Einstein, Alvin Toffler, Amazon Mechanical Turk, Apple's 1984 Super Bowl advert, Asperger Syndrome, Baxter: Rethink Robotics, bitcoin, blockchain, Boeing 747, business process, call centre, carbon tax, clean water, Computing Machinery and Intelligence, creative destruction, crowdsourcing, data science, deep learning, Donald Trump, Douglas Engelbart, Douglas Engelbart, driverless car, drone strike, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, experimental economics, Exxon Valdez, Ford Model T, future of work, Future Shock, Galaxy Zoo, Garrett Hardin, gig economy, happiness index / gross national happiness, independent contractor, industrial robot, Internet of things, invention of the telegraph, inventory management, invisible hand, Jeff Rulifson, jimmy wales, job automation, John Markoff, Joi Ito, Joseph Schumpeter, Kenneth Arrow, knowledge worker, longitudinal study, Lyft, machine translation, Marshall McLuhan, Nick Bostrom, Occupy movement, Pareto efficiency, pattern recognition, prediction markets, price mechanism, radical decentralization, Ray Kurzweil, Rodney Brooks, Ronald Coase, search costs, Second Machine Age, self-driving car, Silicon Valley, slashdot, social intelligence, Stephen Hawking, Steve Jobs, Steven Pinker, Stewart Brand, technological singularity, The Nature of the Firm, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, theory of mind, Tim Cook: Apple, Tragedy of the Commons, transaction costs, Travis Kalanick, Uber for X, uber lyft, Vernor Vinge, Vilfredo Pareto, Watson beat the top human players on Jeopardy!

., “Decoding Motor Imagery from the Posterior Parietal Cortex of a Tetraplegic Human,” Science 348, no. 6,237 (May 22, 2015): 906–910, http://science.sciencemag.org/content/348/6237/906.full, doi:10.1126/science.aaa5417. CHAPTER 4 1. Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach (New York: Prentice Hall, 1995). 2. Alan Turing, “Computing Machinery and Intelligence,” Mind 59 (1950): 433–60. 3. Wikipedia, s.v. “artificial intelligence,” accessed August 8, 2016, https://en.wikipedia.org/wiki/Artificial_intelligence. 4. Rodney Brooks, “Artificial Intelligence Is a Tool, Not a Threat,” Rethink Robotics, November 10, 2014, http://www.rethinkrobotics.com/blog/artificial-intelligence-tool-threat. 5.

The AI Economy: Work, Wealth and Welfare in the Robot Age by Roger Bootle

"World Economic Forum" Davos, 3D printing, agricultural Revolution, AI winter, Albert Einstein, AlphaGo, Alvin Toffler, anti-work, antiwork, autonomous vehicles, basic income, Ben Bernanke: helicopter money, Bernie Sanders, Bletchley Park, blockchain, call centre, Cambridge Analytica, Capital in the Twenty-First Century by Thomas Piketty, Carl Icahn, Chris Urmson, computer age, Computing Machinery and Intelligence, conceptual framework, corporate governance, correlation does not imply causation, creative destruction, David Ricardo: comparative advantage, deep learning, DeepMind, deindustrialization, Demis Hassabis, deskilling, Dr. Strangelove, driverless car, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, everywhere but in the productivity statistics, facts on the ground, fake news, financial intermediation, full employment, future of work, Future Shock, general purpose technology, Great Leap Forward, Hans Moravec, income inequality, income per capita, industrial robot, Internet of things, invention of the wheel, Isaac Newton, James Watt: steam engine, Jeff Bezos, Jeremy Corbyn, job automation, job satisfaction, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Joseph Schumpeter, Kevin Kelly, license plate recognition, low interest rates, machine translation, Marc Andreessen, Mark Zuckerberg, market bubble, mega-rich, natural language processing, Network effects, new economy, Nicholas Carr, Ocado, Paul Samuelson, Peter Thiel, Phillips curve, positional goods, quantitative easing, RAND corporation, Ray Kurzweil, Richard Florida, ride hailing / ride sharing, rising living standards, road to serfdom, Robert Gordon, Robert Shiller, Robert Solow, Rutger Bregman, Second Machine Age, secular stagnation, self-driving car, seminal paper, Silicon Valley, Silicon Valley billionaire, Simon Kuznets, Skype, social intelligence, spinning jenny, Stanislav Petrov, Stephen Hawking, Steven Pinker, synthetic biology, technological singularity, The Future of Employment, The Wealth of Nations by Adam Smith, Thomas Malthus, trade route, universal basic income, US Airways Flight 1549, Vernor Vinge, warehouse automation, warehouse robotics, Watson beat the top human players on Jeopardy!, We wanted flying cars, instead we got 140 characters, wealth creators, winner-take-all economy, world market for maybe five computers, Y2K, Yogi Berra

It grew out of digital computing, which was explored and developed at Bletchley Park in England during the Second World War, famously enabling the Nazis’ Enigma code to be broken. That feat is closely associated with the name of Alan Turing. Turing was also responsible for AI’s early conceptual framework, publishing in 1950 the seminal paper “Computing Machinery and Intelligence.” The subject was subsequently developed mainly in the USA and the UK. But it waxed and waned in both esteem and achievement. Over the last decade, however, a number of key developments have come together to power AI forward: • Enormous growth in computer processing power. • Rapid growth in available data

The Smart Wife: Why Siri, Alexa, and Other Smart Home Devices Need a Feminist Reboot by Yolande Strengers, Jenny Kennedy

active measures, Amazon Robotics, Anthropocene, autonomous vehicles, Big Tech, Boston Dynamics, cloud computing, cognitive load, computer vision, Computing Machinery and Intelligence, crowdsourcing, cyber-physical system, data science, deepfake, Donald Trump, emotional labour, en.wikipedia.org, Evgeny Morozov, fake news, feminist movement, game design, gender pay gap, Grace Hopper, hive mind, Ian Bogost, Intergovernmental Panel on Climate Change (IPCC), Internet of things, Jeff Bezos, John Markoff, Kitchen Debate, knowledge economy, Masayoshi Son, Milgram experiment, Minecraft, natural language processing, Network effects, new economy, pattern recognition, planned obsolescence, precautionary principle, robot derives from the Czech word robota Czech, meaning slave, self-driving car, Shoshana Zuboff, side hustle, side project, Silicon Valley, smart grid, smart meter, social intelligence, SoftBank, Steve Jobs, surveillance capitalism, systems thinking, technological solutionism, technoutopianism, TED Talk, Turing test, Wall-E, Wayback Machine, women in the workforce

Rob Waugh, “Webcam Site Uses VR Helmets to Turn Sex Robots into Real, Living People,” Metro, January 24, 2018, https://metro.co.uk/2018/01/24/webcam-site-uses-vr-helmets-to-turn-sex-robots-into-real-living-people-7257248/. 43. Peter Rubin, Future Presence: How Virtual Reality Is Changing Human Connection, Intimacy, and the Limits of Ordinary Life (New York: HarperCollins, 2018). 44. Sharkey et al., Our Sexual Future with Robots. 45. Engadget, “Interview with Realdoll Founder”; A. M. Turing, “Computing Machinery and Intelligence,” Mind 59, no. 236 (October 1950): 433–460. 46. “Info/Help,” Lumidolls, accessed December 3, 2019, https://lumidolls.com/en/content/info-help. 47. Davis, “Are We Ready for Robot Sex?” 48. RealdollX (website). 49. Laurie Mintz, Becoming Cliterate: Why Orgasm Equality Matters—and How to Get It (New York: HarperOne, 2017). 50.

In Our Own Image: Savior or Destroyer? The History and Future of Artificial Intelligence by George Zarkadakis

3D printing, Ada Lovelace, agricultural Revolution, Airbnb, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, animal electricity, anthropic principle, Asperger Syndrome, autonomous vehicles, barriers to entry, battle of ideas, Berlin Wall, bioinformatics, Bletchley Park, British Empire, business process, carbon-based life, cellular automata, Charles Babbage, Claude Shannon: information theory, combinatorial explosion, complexity theory, Computing Machinery and Intelligence, continuous integration, Conway's Game of Life, cosmological principle, dark matter, data science, deep learning, DeepMind, dematerialisation, double helix, Douglas Hofstadter, driverless car, Edward Snowden, epigenetics, Flash crash, Google Glasses, Gödel, Escher, Bach, Hans Moravec, income inequality, index card, industrial robot, intentional community, Internet of things, invention of agriculture, invention of the steam engine, invisible hand, Isaac Newton, Jacquard loom, Jacques de Vaucanson, James Watt: steam engine, job automation, John von Neumann, Joseph-Marie Jacquard, Kickstarter, liberal capitalism, lifelogging, machine translation, millennium bug, mirror neurons, Moravec's paradox, natural language processing, Nick Bostrom, Norbert Wiener, off grid, On the Economy of Machinery and Manufactures, packet switching, pattern recognition, Paul Erdős, Plato's cave, post-industrial society, power law, precautionary principle, prediction markets, Ray Kurzweil, Recombinant DNA, Rodney Brooks, Second Machine Age, self-driving car, seminal paper, Silicon Valley, social intelligence, speech recognition, stem cell, Stephen Hawking, Steven Pinker, Strategic Defense Initiative, strong AI, Stuart Kauffman, synthetic biology, systems thinking, technological singularity, The Coming Technological Singularity, The Future of Employment, the scientific method, theory of mind, Turing complete, Turing machine, Turing test, Tyler Cowen, Tyler Cowen: Great Stagnation, Vernor Vinge, Von Neumann architecture, Watson beat the top human players on Jeopardy!, Y2K

Peters. 20‘You shall not make for yourself an idol’ under the Philonic division used by Hellenistic Jews, Greek Orthodox and Protestants except Lutherans. 21Around the seventh century BC. 22My discussion on the polar narratives about Artificial Intelligence focuses on Western civilisation; in Japan, for example, attitudes towards robots are not so polarised. Japanese society is more open to robots than Europeans and Americans. 4 Loving the alien 1Turing, A. (1950), ‘Computing Machinery and Intelligence’, in: Mind LIX (236), pp. 433–466, ISSN 0026-4423. 2‘Gynaecoids’ is a more appropriate term, from the Greek gynē: woman (while ‘android’ comes from the Greek andro: man). Some-times the shortened term ‘gynoid’ is used, or ‘fembot’ (female robot). 3Isaac Asimov introduced his ‘three laws of robotics’ in his 1942 short story ‘Runaround’.

Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again by Eric Topol

"World Economic Forum" Davos, 23andMe, Affordable Care Act / Obamacare, AI winter, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, algorithmic bias, AlphaGo, Apollo 11, artificial general intelligence, augmented reality, autism spectrum disorder, autonomous vehicles, backpropagation, Big Tech, bioinformatics, blockchain, Cambridge Analytica, cloud computing, cognitive bias, Colonization of Mars, computer age, computer vision, Computing Machinery and Intelligence, conceptual framework, creative destruction, CRISPR, crowdsourcing, Daniel Kahneman / Amos Tversky, dark matter, data science, David Brooks, deep learning, DeepMind, Demis Hassabis, digital twin, driverless car, Elon Musk, en.wikipedia.org, epigenetics, Erik Brynjolfsson, fake news, fault tolerance, gamification, general purpose technology, Geoffrey Hinton, George Santayana, Google Glasses, ImageNet competition, Jeff Bezos, job automation, job satisfaction, Joi Ito, machine translation, Mark Zuckerberg, medical residency, meta-analysis, microbiome, move 37, natural language processing, new economy, Nicholas Carr, Nick Bostrom, nudge unit, OpenAI, opioid epidemic / opioid crisis, pattern recognition, performance metric, personalized medicine, phenotype, placebo effect, post-truth, randomized controlled trial, recommendation engine, Rubik’s Cube, Sam Altman, self-driving car, Silicon Valley, Skinner box, speech recognition, Stephen Hawking, techlash, TED Talk, text mining, the scientific method, Tim Cook: Apple, traumatic brain injury, trolley problem, War on Poverty, Watson beat the top human players on Jeopardy!, working-age population

Kohane, “Big Data and Machine Learning in Health Care.” JAMA, 2018. 319(13): pp. 1317–1318. 13. Turing, A. M., “On Computable Numbers with an Application to the Entscheidungsproblem.” Proceedings of the London Mathematical Society, 1936. 42(1): pp. 230–265. doi: 10.1112/plms/s2-42.1.230. 14. Turing, A. M., “Computing Machinery and Intelligence.” Mind, 1950. 49: pp. 433–460. https://www.csee.umbc.edu/courses/471/papers/turing.pdf. 15. Rumelhart, D. E., G. Hinton, and R. J. Williams, “Learning Representations by Back-Propagating Errors.” Nature, 1986. 323: pp. 533–536. 16. Parloff, R., “Why Deep Learning Is Suddenly Changing Your Life,” in Fortune. 2016. 17.

Visual Thinking: The Hidden Gifts of People Who Think in Pictures, Patterns, and Abstractions by Temple Grandin, Ph.D.

2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 3D printing, a long time ago in a galaxy far, far away, air gap, Albert Einstein, American Society of Civil Engineers: Report Card, Apollo 11, Apple II, ASML, Asperger Syndrome, autism spectrum disorder, autonomous vehicles, Black Lives Matter, Boeing 737 MAX, Captain Sullenberger Hudson, clean water, cloud computing, computer vision, Computing Machinery and Intelligence, coronavirus, cotton gin, COVID-19, defense in depth, Drosophila, Elon Musk, en.wikipedia.org, GPT-3, Gregor Mendel, Greta Thunberg, hallucination problem, helicopter parent, income inequality, industrial robot, invention of movable type, Isaac Newton, James Webb Space Telescope, John Nash: game theory, John von Neumann, Jony Ive, language acquisition, longitudinal study, Mark Zuckerberg, Mars Rover, meta-analysis, Neil Armstrong, neurotypical, pattern recognition, Peter Thiel, phenotype, ransomware, replication crisis, Report Card for America’s Infrastructure, Robert X Cringely, Saturday Night Live, self-driving car, seminal paper, Silicon Valley, Skinner box, space junk, stem cell, Stephen Hawking, Steve Jobs, Steve Wozniak, Tacoma Narrows Bridge, TaskRabbit, theory of mind, TikTok, twin studies, unpaid internship, upwardly mobile, US Airways Flight 1549, warehouse automation, warehouse robotics, web application, William Langewiesche, Y Combinator

Agnesian Health Care, April 25, 2017. Treffert, D. A. Islands of Genius. London: Jessica Kingsley, 2010. Turing, A. M. “The Chemical Basis of Morphogenesis.” Philosophical Transactions of the Royal Society of London, Series B, Biological Sciences 237, no. 641 (August 14, 1952): 37–72. Turing, A. M. “Computing Machinery and Intelligence.” Mind 59, no. 236 (October 1950): 433–60. Van Noorden, R. “Interdisciplinary by the Numbers.” Nature 525, no. 7569 (2015): 305–7. Vance, A. Elon Musk: How the Billionaire CEO of SpaceX and Tesla Is Shaping Our Future. New York: Virgin Books, 2015. Vietnam Veterans Memorial Fund.

The Equality Machine: Harnessing Digital Technology for a Brighter, More Inclusive Future by Orly Lobel

2021 United States Capitol attack, 23andMe, Ada Lovelace, affirmative action, Airbnb, airport security, Albert Einstein, algorithmic bias, Amazon Mechanical Turk, augmented reality, barriers to entry, basic income, Big Tech, bioinformatics, Black Lives Matter, Boston Dynamics, Charles Babbage, choice architecture, computer vision, Computing Machinery and Intelligence, contact tracing, coronavirus, corporate social responsibility, correlation does not imply causation, COVID-19, crowdsourcing, data science, David Attenborough, David Heinemeier Hansson, deep learning, deepfake, digital divide, digital map, Elon Musk, emotional labour, equal pay for equal work, feminist movement, Filter Bubble, game design, gender pay gap, George Floyd, gig economy, glass ceiling, global pandemic, Google Chrome, Grace Hopper, income inequality, index fund, information asymmetry, Internet of things, invisible hand, it's over 9,000, iterative process, job automation, Lao Tzu, large language model, lockdown, machine readable, machine translation, Mark Zuckerberg, market bubble, microaggression, Moneyball by Michael Lewis explains big data, natural language processing, Netflix Prize, Network effects, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, occupational segregation, old-boy network, OpenAI, openstreetmap, paperclip maximiser, pattern recognition, performance metric, personalized medicine, price discrimination, publish or perish, QR code, randomized controlled trial, remote working, risk tolerance, robot derives from the Czech word robota Czech, meaning slave, Ronald Coase, Salesforce, self-driving car, sharing economy, Sheryl Sandberg, Silicon Valley, social distancing, social intelligence, speech recognition, statistical model, stem cell, Stephen Hawking, Steve Jobs, Steve Wozniak, surveillance capitalism, tech worker, TechCrunch disrupt, The Future of Employment, TikTok, Turing test, universal basic income, Wall-E, warehouse automation, women in the workforce, work culture , you are the product

Loomis, 881 N.W. 2d 749, 766 (Wis. 2016), cert. denied, 137 S. Ct. 2290 (2017). 16. Artificial Intelligence: With Great Power Comes Great Responsibility: Hearing Before the H. Subcomm. on Rsch. & Tech. and H. Subcomm. on Energy, H. Comm. on Sci., Space & Tech., 115th Cong. 50 (2018). 17. A. M. Turing, “Computing Machinery and Intelligence,” Mind 59, no. 236 (October 1950): 433, https://doi.org/10.1093/mind/LIX.236.433. 18. David Z. Morris, “Elon Musk Says Artificial Intelligence Is the ‘Greatest Risk We Face as a Civilization,” Fortune, July 15, 2017, https://fortune.com/2017/07/15/elon-musk-artificial-intelligence-2/. 19.

When Computers Can Think: The Artificial Intelligence Singularity by Anthony Berglas, William Black, Samantha Thalind, Max Scratchmann, Michelle Estes

3D printing, Abraham Maslow, AI winter, air gap, anthropic principle, artificial general intelligence, Asilomar, augmented reality, Automated Insights, autonomous vehicles, availability heuristic, backpropagation, blue-collar work, Boston Dynamics, brain emulation, call centre, cognitive bias, combinatorial explosion, computer vision, Computing Machinery and Intelligence, create, read, update, delete, cuban missile crisis, David Attenborough, DeepMind, disinformation, driverless car, Elon Musk, en.wikipedia.org, epigenetics, Ernest Rutherford, factory automation, feminist movement, finite state, Flynn Effect, friendly AI, general-purpose programming language, Google Glasses, Google X / Alphabet X, Gödel, Escher, Bach, Hans Moravec, industrial robot, Isaac Newton, job automation, John von Neumann, Law of Accelerating Returns, license plate recognition, Mahatma Gandhi, mandelbrot fractal, natural language processing, Nick Bostrom, Parkinson's law, patent troll, patient HM, pattern recognition, phenotype, ransomware, Ray Kurzweil, Recombinant DNA, self-driving car, semantic web, Silicon Valley, Singularitarianism, Skype, sorting algorithm, speech recognition, statistical model, stem cell, Stephen Hawking, Stuxnet, superintelligent machines, technological singularity, Thomas Malthus, Turing machine, Turing test, uranium enrichment, Von Neumann architecture, Watson beat the top human players on Jeopardy!, wikimedia commons, zero day

So while these results are landmarks in the progress of theoretical mathematical logic, they have almost no relevance to the question of whether it is possible to build a practical artificial intelligence. Alan Turing himself did not consider these issues to be relevant. Indeed, in 1950 Turing wrote a landmark paper “Computing machinery and intelligence”in which he discussed the proposition that computers will be able to really think. In the paper he addressed nine objections to the proposition, and specifically addressed the irrelevance of the halting problem and the incompleteness theorem to this question. Combinatorial explosion Many problems in artificial intelligence involve searching for a solution out of a large number of possibilities.

Bootstrapping: Douglas Engelbart, Coevolution, and the Origins of Personal Computing (Writing Science) by Thierry Bardini

Apple II, augmented reality, Bill Duvall, Charles Babbage, classic study, Compatible Time-Sharing System, Computing Machinery and Intelligence, conceptual framework, Donald Davies, Douglas Engelbart, Douglas Engelbart, Dynabook, experimental subject, Grace Hopper, hiring and firing, hypertext link, index card, information retrieval, invention of hypertext, Ivan Sutherland, Jaron Lanier, Jeff Rulifson, John von Neumann, knowledge worker, Leonard Kleinrock, Menlo Park, military-industrial complex, Mother of all demos, Multics, new economy, Norbert Wiener, Norman Mailer, packet switching, Project Xanadu, QWERTY keyboard, Ralph Waldo Emerson, RAND corporation, RFC: Request For Comment, Sapir-Whorf hypothesis, Silicon Valley, Steve Crocker, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, stochastic process, Ted Nelson, the medium is the message, theory of mind, Turing test, unbiased observer, Vannevar Bush, Whole Earth Catalog, work culture

"From TrailblazIng to Guided Tours: The Legacy of Vannevar Bush's VisIon of Hypertext Use." In From Memex to Hypertext: Vannevar 274 Works C,ted Bush and the Mind's MachIne, edited by J. M. Nyce and P. Kahn, pp. 353- 67. San Diego, Calif.: Academic Press. Turing, A. M. 1950. "Computing Machinery and Intelligence." MInd 59: 433-60. Turkle, S. 1984. The Second Self: Computers and the Human SpIrit. New York: Simon and Schuster. Uttal, B. 1983. "The Lab that Ran Away from Xerox." Fortune (September 5), 97- 102. Vallee, J. 19 82 . The Network Revolution: ConfessIons of a Computer SCIentIst. Berkeley, Calif.: And/Or Press. van Dam, A. 1997.

The Music of the Primes by Marcus Du Sautoy

Ada Lovelace, Andrew Wiles, Arthur Eddington, Augustin-Louis Cauchy, Bletchley Park, Charles Babbage, computer age, Computing Machinery and Intelligence, Dava Sobel, Dmitri Mendeleev, Eddington experiment, Eratosthenes, Erdős number, Georg Cantor, German hyperinflation, global village, Henri Poincaré, Isaac Newton, Jacquard loom, lateral thinking, Leo Hollis, music of the spheres, Neal Stephenson, New Journalism, P = NP, Paul Erdős, Richard Feynman, Rubik’s Cube, Search for Extraterrestrial Intelligence, seminal paper, Simon Singh, Stephen Hawking, Turing machine, William of Occam, Wolfskehl Prize, Y2K

But it was the war, and in particular the code-breakers at Bletchley Park, that were responsible for the development of the machine that would generate this new evidence: the computer. CHAPTER EIGHT Machines of the Mind I propose to consider the question, ‘Can machines think?’ Alan Turing, Computing Machinery and Intelligence Alan Turing’s name will always be associated with the cracking of Germany’s wartime code, Enigma. From the comfort of the country house of Bletchley Park, halfway between Oxford and Cambridge, Churchill’s code-breakers created a machine which could decode the messages sent each day by German intelligence.

The Science of Language by Noam Chomsky

Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Alfred Russel Wallace, backpropagation, British Empire, Brownian motion, Computing Machinery and Intelligence, dark matter, Drosophila, epigenetics, finite state, Great Leap Forward, Howard Zinn, language acquisition, phenotype, public intellectual, statistical model, stem cell, Steven Pinker, Stuart Kauffman, theory of mind, trolley problem

Cambridge University Press. Tomalin, Marcus (2007) “Reconsidering Recursion in Linguistic Theory.” Lingua 117: 1784–1800. Turing, Alan (1937) “On Computable Numbers, with an Application to the Entscheidungsproblem.” London Mathematical Society, Series 2 42: 230–265. Turing, Alan (1950) “Computing Machinery and Intelligence.” Mind 59: 433–460. Turing, Alan (1992) Collected Works of Alan Turing: Morphogenesis. Ed. P. T. Saunders. Amsterdam: North Holland. Tversky, Amos and Daniel Kahneman (1974) “Judgment under Uncertainty.” Science, New Series 185 (4157): 1124–1131. Waddington, Conrad H. (1940) Organisers and Genes.

The Fabric of Reality by David Deutsch

Any sufficiently advanced technology is indistinguishable from magic, Arthur Eddington, Boeing 747, butterfly effect, coherent worldview, complexity theory, Computing Machinery and Intelligence, conceptual framework, cosmological principle, different worldview, Donald Knuth, Douglas Hofstadter, Eddington experiment, Georg Cantor, Gödel, Escher, Bach, Johannes Kepler, Occam's razor, phenotype, quantum cryptography, Richard Feynman, scientific worldview, Stephen Hawking, the scientific method, Thomas Kuhn: the structure of scientific revolutions, time dilation, Turing machine

Dennis Sciama, The Unity of the Universe, Faber &c Faber, 1967. Ian Stewart, Does God Play Dice? The Mathematics of Chaos, Basil Blackwell, 1989; Penguin Books, 1990. L. J. Stockmeyer and A. K. Chandra, 'Intrinsically Difficult Problems', Scientific American, May 1979. Frank Tipler, The Physics of Immortality, Doubleday, 1995. Alan Turing, 'Computing Machinery and Intelligence', Mind, October 1950. [Reprinted in The Mind's I, edited by Douglas Hofstadter and Daniel C. Dennett, Harvester, 1981.] Steven Weinberg, Gravitation and Cosmology, John Wiley, 1972. Steven Weinberg, The First Three Minutes, Basic Books, 1977. Steven Weinberg, Dreams of a Final Theory, Vintage, 1993, Random, 1994.

The Extended Phenotype: The Long Reach of the Gene by Richard Dawkins

Alfred Russel Wallace, assortative mating, Computing Machinery and Intelligence, Douglas Hofstadter, Drosophila, epigenetics, Gödel, Escher, Bach, impulse control, Menlo Park, Necker cube, p-value, Peter Pan Syndrome, phenotype, quantitative trading / quantitative finance, Recombinant DNA, selection bias, stem cell, Tragedy of the Commons

In Sexual Selection and the Descent of Man (ed. B. Campbell), pp. 136–179. Chicago: Aldine. Trivers, R. L. (1974). Parent-offspring conflict. American Zoologist 14, 249–264. Trivers, R. L. & Hare, H. (1976). Haplodiploidy and the evolution of the social insects. Science 191, 249–263. Turing, A. (1950). Computing machinery and intelligence. Mind 59, 433–460. Turnbull, C. (1961). The Forest People. London: Cape. Turner, J. R. G. (1977). Butterfly mimicry: the genetical evolution of an adaptation. In Evolutionary Biology, Vol. 10 (eds M. K. Hecht et al.), pp. 163–206. New York: Plenum Press. Vermeij, G. J. (1973). Adaptation, versatility and evolution.

From Bacteria to Bach and Back: The Evolution of Minds by Daniel C. Dennett

Ada Lovelace, adjacent possible, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, AlphaGo, Andrew Wiles, Bayesian statistics, bioinformatics, bitcoin, Bletchley Park, Build a better mousetrap, Claude Shannon: information theory, computer age, computer vision, Computing Machinery and Intelligence, CRISPR, deep learning, disinformation, double entry bookkeeping, double helix, Douglas Hofstadter, Elon Musk, epigenetics, experimental subject, Fermat's Last Theorem, Gödel, Escher, Bach, Higgs boson, information asymmetry, information retrieval, invention of writing, Isaac Newton, iterative process, John von Neumann, language acquisition, megaproject, Menlo Park, Murray Gell-Mann, Necker cube, Norbert Wiener, pattern recognition, phenotype, Richard Feynman, Rodney Brooks, self-driving car, social intelligence, sorting algorithm, speech recognition, Stephen Hawking, Steven Pinker, strong AI, Stuart Kauffman, TED Talk, The Wealth of Nations by Adam Smith, theory of mind, Thomas Bayes, trickle-down economics, Turing machine, Turing test, Watson beat the top human players on Jeopardy!, Y2K

“Consciousness as Integrated Information: A Provisional Manifesto.” Biological Bulletin 215 (3): 216–42. Trivers, Robert. 1985. Social Evolution. Menlo Park, Calif.: Benjamin/Cummings. Turing, Alan M. 1936. “On Computable Numbers, with an Application to the Entscheidungs Problem.” Journal of Math 58 (345–363): 5. —. 1960. “Computing Machinery and Intelligence.” Mind: 59: 433–460. von Neumann, John, and Oskar Morgenstern. 1953 (©1944). Theory of Games and Economic Behavior. Princeton, N.J.: Princeton University Press. von Uexküll, Jakob. 1934. “A Stroll through the Worlds of Animals and Men: A Picture Book of Invisible Worlds.” In Instinctive Behavior: The Development of a Modern Concept, translated and edited by Claire H.

Robot Rules: Regulating Artificial Intelligence by Jacob Turner

"World Economic Forum" Davos, Ada Lovelace, Affordable Care Act / Obamacare, AI winter, algorithmic bias, algorithmic trading, AlphaGo, artificial general intelligence, Asilomar, Asilomar Conference on Recombinant DNA, autonomous vehicles, backpropagation, Basel III, bitcoin, Black Monday: stock market crash in 1987, blockchain, brain emulation, Brexit referendum, Cambridge Analytica, Charles Babbage, Clapham omnibus, cognitive dissonance, Computing Machinery and Intelligence, corporate governance, corporate social responsibility, correlation does not imply causation, crowdsourcing, data science, deep learning, DeepMind, Demis Hassabis, distributed ledger, don't be evil, Donald Trump, driverless car, easy for humans, difficult for computers, effective altruism, Elon Musk, financial exclusion, financial innovation, friendly fire, future of work, hallucination problem, hive mind, Internet of things, iterative process, job automation, John Markoff, John von Neumann, Loebner Prize, machine readable, machine translation, medical malpractice, Nate Silver, natural language processing, Nick Bostrom, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, nudge unit, obamacare, off grid, OpenAI, paperclip maximiser, pattern recognition, Peace of Westphalia, Philippa Foot, race to the bottom, Ray Kurzweil, Recombinant DNA, Rodney Brooks, self-driving car, Silicon Valley, Stanislav Petrov, Stephen Hawking, Steve Wozniak, strong AI, technological singularity, Tesla Model S, The Coming Technological Singularity, The Future of Employment, The Signal and the Noise by Nate Silver, trolley problem, Turing test, Vernor Vinge

Searle’s experiment has been met with various numbers of replies and criticisms, which are set out in the entry on The Chinese Room Argument, Stanford Encyclopedia of Philosophy, First published 19 March 2004; substantive revision 9 April 2014, https://​plato.​stanford.​edu/​entries/​chinese-room/​, accessed 1 June 2018. 33Alan M. Turing, “Computing Machinery and Intelligence”, Mind: A Quarterly Review of Psychology and Philosophy, Vol. 59, No. 236 (October 1950), 433–460, 460. 34Yuval Harari has offered the interesting explanation that the form of Turing’s Imitation Game resulted in part from Turing’s own need to suppress his homosexuality, to fool society and the authorities into thinking he was something that he was not.

Fancy Bear Goes Phishing: The Dark History of the Information Age, in Five Extraordinary Hacks by Scott J. Shapiro

3D printing, 4chan, active measures, address space layout randomization, air gap, Airbnb, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, availability heuristic, Bernie Sanders, bitcoin, blockchain, borderless world, Brian Krebs, business logic, call centre, carbon tax, Cass Sunstein, cellular automata, cloud computing, cognitive dissonance, commoditize, Compatible Time-Sharing System, Computing Machinery and Intelligence, coronavirus, COVID-19, CRISPR, cryptocurrency, cyber-physical system, Daniel Kahneman / Amos Tversky, Debian, Dennis Ritchie, disinformation, Donald Trump, double helix, Dr. Strangelove, dumpster diving, Edward Snowden, en.wikipedia.org, Evgeny Morozov, evil maid attack, facts on the ground, false flag, feminist movement, Gabriella Coleman, gig economy, Hacker News, independent contractor, information security, Internet Archive, Internet of things, invisible hand, John Markoff, John von Neumann, Julian Assange, Ken Thompson, Larry Ellison, Laura Poitras, Linda problem, loss aversion, macro virus, Marc Andreessen, Mark Zuckerberg, Menlo Park, meta-analysis, Minecraft, Morris worm, Multics, PalmPilot, Paul Graham, pirate software, pre–internet, QWERTY keyboard, Ralph Nader, RAND corporation, ransomware, Reflections on Trusting Trust, Richard Stallman, Richard Thaler, Ronald Reagan, Satoshi Nakamoto, security theater, Shoshana Zuboff, side hustle, Silicon Valley, Skype, SoftBank, SQL injection, Steve Ballmer, Steve Jobs, Steven Levy, Stuxnet, supply-chain attack, surveillance capitalism, systems thinking, TaskRabbit, tech billionaire, tech worker, technological solutionism, the Cathedral and the Bazaar, the new new thing, the payments system, Turing machine, Turing test, Unsafe at Any Speed, vertical integration, Von Neumann architecture, Wargames Reagan, WarGames: Global Thermonuclear War, Wayback Machine, web application, WikiLeaks, winner-take-all economy, young professional, zero day, éminence grise

Hacking is less about breaking encryption than breaking something around the encryption in order to sidestep it. 50 million lines of code: “Windows 10 Lines of Code,” Microsoft, 2020, https://answers.microsoft.com/en-us/windows/forum/all/windows-10-lines-of-code/a8f77f5c-0661–4895–9c77–2efd42429409. Turing Test: Turing set out his test for intelligence in Alan Turing, “Computing Machinery and Intelligence,” Mind 59, no. 236 (October 1950): 433–60. A Turing Test has a human judge and a computer subject attempting to appear human. A “reverse” Turing Test has a computer judge and a human subject trying to appear human. CAPTCHA—the irritating image-recognition challenge that websites use for detecting bots—stands for “Completely Automated Public Turing test to tell Computers and Humans Apart.”

Natural language processing with Python by Steven Bird, Ewan Klein, Edward Loper

bioinformatics, business intelligence, business logic, Computing Machinery and Intelligence, conceptual framework, Donald Knuth, duck typing, elephant in my pajamas, en.wikipedia.org, finite state, Firefox, functional programming, Guido van Rossum, higher-order functions, information retrieval, language acquisition, lolcat, machine translation, Menlo Park, natural language processing, P = NP, search inside the book, sparse data, speech recognition, statistical model, text mining, Turing test, W. E. B. Du Bois

Boston, Allyn and Bacon, 1999. [Thompson and McKelvie, 1997] Henry S. Thompson and David McKelvie. Hyperlink semantics for standoff markup of read-only documents. In SGML Europe ’97, 1997. http://www.ltg.ed.ac.uk/~ht/sgmleu97.html. [TLG, 1999] TLG. Thesaurus Linguae Graecae, 1999. [Turing, 1950] Alan M. Turing. Computing machinery and intelligence. Mind, 59(236): 433–460, 1950. [van Benthem and ter Meulen, 1997] Johan van Benthem and Alice ter Meulen, editors. Handbook of Logic and Language. MIT Press, Cambridge, MA, 1997. [van Rossum and Drake, 2006a] Guido van Rossum and Fred L. Drake. An Introduction to Python—The Python Tutorial.

Superintelligence: Paths, Dangers, Strategies by Nick Bostrom

agricultural Revolution, AI winter, Albert Einstein, algorithmic trading, anthropic principle, Anthropocene, anti-communist, artificial general intelligence, autism spectrum disorder, autonomous vehicles, backpropagation, barriers to entry, Bayesian statistics, bioinformatics, brain emulation, cloud computing, combinatorial explosion, computer vision, Computing Machinery and Intelligence, cosmological constant, dark matter, DARPA: Urban Challenge, data acquisition, delayed gratification, Demis Hassabis, demographic transition, different worldview, Donald Knuth, Douglas Hofstadter, driverless car, Drosophila, Elon Musk, en.wikipedia.org, endogenous growth, epigenetics, fear of failure, Flash crash, Flynn Effect, friendly AI, general purpose technology, Geoffrey Hinton, Gödel, Escher, Bach, hallucination problem, Hans Moravec, income inequality, industrial robot, informal economy, information retrieval, interchangeable parts, iterative process, job automation, John Markoff, John von Neumann, knowledge worker, Large Hadron Collider, longitudinal study, machine translation, megaproject, Menlo Park, meta-analysis, mutually assured destruction, Nash equilibrium, Netflix Prize, new economy, Nick Bostrom, Norbert Wiener, NP-complete, nuclear winter, operational security, optical character recognition, paperclip maximiser, pattern recognition, performance metric, phenotype, prediction markets, price stability, principal–agent problem, race to the bottom, random walk, Ray Kurzweil, recommendation engine, reversible computing, search costs, social graph, speech recognition, Stanislav Petrov, statistical model, stem cell, Stephen Hawking, Strategic Defense Initiative, strong AI, superintelligent machines, supervolcano, synthetic biology, technological singularity, technoutopianism, The Coming Technological Singularity, The Nature of the Firm, Thomas Kuhn: the structure of scientific revolutions, time dilation, Tragedy of the Commons, transaction costs, trolley problem, Turing machine, Vernor Vinge, WarGames: Global Thermonuclear War, Watson beat the top human players on Jeopardy!, World Values Survey, zero-sum game

“Formation of the Adult Nervous System.” In The Development of Drosophila Melanogaster, edited by Michael Bate and Alfonso Martinez Arias. Plainview, NY: Cold Spring Harbor Laboratory. Tuomi, Ilkka. 2002. “The Lives and the Death of Moore’s Law.” First Monday 7 (11). Turing, A. M. 1950. “Computing Machinery and Intelligence.” Mind 59 (236): 433–60. Turkheimer, Eric, Haley, Andreana, Waldron, Mary, D’Onofrio, Brian, and Gottesman, Irving I. 2003. “Socioeconomic Status Modifies Heritability of IQ in Young Children.” Psychological Science 14 (6): 623–8. Uauy, Ricardo, and Dangour, Alan D. 2006. “Nutrition in Brain Development and Aging: Role of Essential Fatty Acids.”

The Founders: The Story of Paypal and the Entrepreneurs Who Shaped Silicon Valley by Jimmy Soni

activist fund / activist shareholder / activist investor, Ada Lovelace, AltaVista, Apple Newton, barriers to entry, Big Tech, bitcoin, Blitzscaling, book value, business logic, butterfly effect, call centre, Carl Icahn, Claude Shannon: information theory, cloud computing, Colonization of Mars, Computing Machinery and Intelligence, corporate governance, COVID-19, crack epidemic, cryptocurrency, currency manipulation / currency intervention, digital map, disinformation, disintermediation, drop ship, dumpster diving, Elon Musk, Fairchild Semiconductor, fear of failure, fixed income, General Magic , general-purpose programming language, Glass-Steagall Act, global macro, global pandemic, income inequality, index card, index fund, information security, intangible asset, Internet Archive, iterative process, Jeff Bezos, Jeff Hawkins, John Markoff, Kwajalein Atoll, Lyft, Marc Andreessen, Mark Zuckerberg, Mary Meeker, Max Levchin, Menlo Park, Metcalfe’s law, mobile money, money market fund, multilevel marketing, mutually assured destruction, natural language processing, Network effects, off-the-grid, optical character recognition, PalmPilot, pattern recognition, paypal mafia, Peter Thiel, pets.com, Potemkin village, public intellectual, publish or perish, Richard Feynman, road to serfdom, Robert Metcalfe, Robert X Cringely, rolodex, Sand Hill Road, Satoshi Nakamoto, seigniorage, shareholder value, side hustle, Silicon Valley, Silicon Valley startup, slashdot, SoftBank, software as a service, Startup school, Steve Ballmer, Steve Jobs, Steve Jurvetson, Steve Wozniak, technoutopianism, the payments system, transaction costs, Turing test, uber lyft, Vanguard fund, winner-take-all economy, Y Combinator, Y2K

“go to the north”… “lose the war”: Akira Kurosawa, Seven Samurai [Shichinin no samurai]. Directed by Akira Kurosawa, Toho Company, 1954. “[Fraud] saved us”: Author interview with Luke Nosek, May 31, 2018. “You would marvel”: Author interview with Todd Pearson, October 8, 2018. “I propose to consider”: TURING, A. M. “I.—COMPUTING MACHINERY AND INTELLIGENCE,” Mind (vol. LIX, no. 236), October 1, 1950, 433–60, https://doi.org/10.1093/mind/LIX.236.433. “What is something”: Author interview with David Gausebeck, January 31, 2019. “The world is run”: John Mulaney, “Robots,” segment of Kid Gorgeous Netflix special featuring John Mulaney, https://www.facebook.com/watch/?

Architects of Intelligence by Martin Ford

3D printing, agricultural Revolution, AI winter, algorithmic bias, Alignment Problem, AlphaGo, Apple II, artificial general intelligence, Asilomar, augmented reality, autonomous vehicles, backpropagation, barriers to entry, basic income, Baxter: Rethink Robotics, Bayesian statistics, Big Tech, bitcoin, Boeing 747, Boston Dynamics, business intelligence, business process, call centre, Cambridge Analytica, cloud computing, cognitive bias, Colonization of Mars, computer vision, Computing Machinery and Intelligence, correlation does not imply causation, CRISPR, crowdsourcing, DARPA: Urban Challenge, data science, deep learning, DeepMind, Demis Hassabis, deskilling, disruptive innovation, Donald Trump, Douglas Hofstadter, driverless car, Elon Musk, Erik Brynjolfsson, Ernest Rutherford, fake news, Fellow of the Royal Society, Flash crash, future of work, general purpose technology, Geoffrey Hinton, gig economy, Google X / Alphabet X, Gödel, Escher, Bach, Hans Moravec, Hans Rosling, hype cycle, ImageNet competition, income inequality, industrial research laboratory, industrial robot, information retrieval, job automation, John von Neumann, Large Hadron Collider, Law of Accelerating Returns, life extension, Loebner Prize, machine translation, Mark Zuckerberg, Mars Rover, means of production, Mitch Kapor, Mustafa Suleyman, natural language processing, new economy, Nick Bostrom, OpenAI, opioid epidemic / opioid crisis, optical character recognition, paperclip maximiser, pattern recognition, phenotype, Productivity paradox, radical life extension, Ray Kurzweil, recommendation engine, Robert Gordon, Rodney Brooks, Sam Altman, self-driving car, seminal paper, sensor fusion, sentiment analysis, Silicon Valley, smart cities, social intelligence, sparse data, speech recognition, statistical model, stealth mode startup, stem cell, Stephen Hawking, Steve Jobs, Steve Wozniak, Steven Pinker, strong AI, superintelligent machines, synthetic biology, systems thinking, Ted Kaczynski, TED Talk, The Rise and Fall of American Growth, theory of mind, Thomas Bayes, Travis Kalanick, Turing test, universal basic income, Wall-E, Watson beat the top human players on Jeopardy!, women in the workforce, working-age population, workplace surveillance , zero-sum game, Zipcar