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The Most Human Human: What Talking With Computers Teaches Us About What It Means to Be Alive by Brian Christian
4chan, Ada Lovelace, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Bertrand Russell: In Praise of Idleness, carbon footprint, cellular automata, Claude Shannon: information theory, cognitive dissonance, commoditize, complexity theory, 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, l'esprit de l'escalier, Loebner Prize, Menlo Park, Ray Kurzweil, RFID, Richard Feynman, Ronald Reagan, 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
Or: all of a sudden I have to be me, to act like myself instead of describing myself. Form and Content in the Turing Test The first Loebner Prize competition was held on November 8, 1991, at the Boston Computer Museum. In its first few years, the Loebner Prize gave each program and human confederate a “topic” as a means of limiting the conversation. In some ways, that first contest was a battle between style and content. One of the confederates was Shakespeare expert Cynthia Clay, who was, famously, deemed a computer by three different judges. The consensus seemed to be “No one knows that much about Shakespeare.” (For this reason, Clay took her misclassifications as a compliment.) The program behind the topic of “whimsical conversation”—PC Therapist III by Joseph Weintraub—won the Loebner Prize that year, earning the very first Most Human Computer award. As the program practiced it, “whimsical conversation” was not a topic at all, but a manner—a crucial distinction.
Griping about the weather with the barista, instead of simply stating your order and waiting patiently, reinforces the fact that he or she is not simply a flesh-and-blood extension of the espresso machine, but in fact a whole person, with moods and attitudes and opinions about most everything under the sun, and a life outside of work. Domain General One of the leading academics interested in the Turing test (and, as it turns out, an outspoken critic of the Loebner Prize) is Harvard’s Stuart Shieber, who actually served in the very first Loebner Prize contest as one of the “referees.” It’s a role that didn’t exist as I prepared for the 2009 test: the referees were there to keep the conversations “in bounds”—but what did that mean, exactly? The organizers and referees at the first Loebner Prize competition held an emergency meeting the night before the competition9 to address it. I called Shieber. “The night before the first competition there was a meeting with the referees,” he says. “How are we going to make sure that the confederates stay on topic and the judges don’t ask things outside of the—They’re not supposed to ask anything tricky—And what is a trick question?
Different written media, for instance, leverage their unique characteristics with time to produce different brands of intimacy, different communicative possibilities—the quick-moving text message saying one was just now being thought of and producing the empathic delight of a moment shared across space between two minds; the slow-moving postal letter or handmade gift saying that one was being thought of at length without knowing it, imbuing future days with the sheen of possibility. In some sense the story of instant messaging—the medium of the Turing test—is the story of the telegram, accelerated to the breaking point. I discover, though, that the protocol the Loebner Prize was using in 2009 was unlike emails, text messages, and standard instant-messaging systems in a very crucial way. The Loebner Prize chat protocols transmitted typing keystroke by keystroke. You’re watching each other type, typos and backspacing and all. Part of what I needed to figure out was how exactly to use the Loebner Prize competition’s unusual “live typing” medium. What did this enable and disable, compared to the standard walkie-talkie, telegram-like, turn-taking style? To make typing visible also, then, makes typing’s “negative space” visible: hesitation.
Talk to Me: How Voice Computing Will Transform the Way We Live, Work, and Think by James Vlahos
Albert Einstein, AltaVista, Amazon Mechanical Turk, Amazon Web Services, augmented reality, Automated Insights, autonomous vehicles, Chuck Templeton: OpenTable:, cloud computing, computer age, Donald Trump, Elon Musk, information retrieval, Internet of things, Jacques de Vaucanson, Jeff Bezos, lateral thinking, Loebner Prize, Machine translation of "The spirit is willing, but the flesh is weak." to Russian and back, Mark Zuckerberg, Menlo Park, natural language processing, PageRank, pattern recognition, Ponzi scheme, randomized controlled trial, Ray Kurzweil, Ronald Reagan, Rubik’s Cube, self-driving car, sentiment analysis, Silicon Valley, Skype, Snapchat, speech recognition, statistical model, Steve Jobs, Steve Wozniak, Steven Levy, Turing test, Watson beat the top human players on Jeopardy!
In 1991 Mauldin liberated Julia from the labyrinths of TinyMUD and entered her into the first-ever edition of a chatbot competition called the Loebner Prize, which has continued annually to this day. Unlike the experiment within Mauldin’s game, the Loebner Prize, which took place in England, was overtly framed as a Turing test. The setup was that the contest’s handful of judges were instructed to exchange messages over a computer with someone who might either be a chatbot or a real person. But the actual identity was kept secret. So the chatbot makers were hoping to fool the judges with their creations while the judges were charged with trying to guess what or whom they were talking to. Out of the six bots entered in the contest, Julia finished a respectable third. Mauldin thought he could do better, so for the 1992 Loebner Prize, he entered a beefed-up version of Julia. The previous edition had treated conversation as a series of unrelated exchanges—user statement leading to bot response, then back to square one as if nothing had happened.
And he needed to then map out all of the possible directions the conversation could go next. The permutations for all of the above were nearly infinite; predicting all but the most obvious was impossible. As Mauldin dryly explained in a postmortem paper about the contest, “Very few of the conversations follow the expected lines of questioning.” The Loebner Prize organizers seemed sympathetic to Mauldin’s plight and that of the other contestants. So they decided that the 1993 version of the Loebner Prize would be a restricted Turing test in which the chatbots were allowed to focus on a single topic of their choosing. Mauldin chose one for Julia that he thought everyone would enjoy: pets. Mauldin knew from his experience the year before that it wouldn’t work to force people down branching preordained conversational paths.
(Consider that alums of the DARPA Grand Challenges, an early set of autonomous-vehicle competitions, went on to run the self-driving-car divisions of Google, Ford, Uber, and General Motors.) The victors would also walk away with the Alexa Prize itself—a $1 million purse. The Alexa Prize is not the only contest that tries to squeeze more humanlike rapport out of the world’s chatbots; recall the Loebner Prize, the one that Mauldin entered, from chapter 4. The Loebner Prize, however, has inspired its share of controversy over the years. Critics believe that the deception at the heart of the contest—contestants trying to trick judges into believing that a chatbot is human—encourages gimmickry. For instance, one prize-winning bot presented itself as an insolent teenager to mask its conversational deficits. In the Alexa Prize contest, by contrast, the machines don’t try to pass as human.
Thinking Machines: The Inside Story of Artificial Intelligence and Our Race to Build the Future by Luke Dormehl
Ada Lovelace, agricultural Revolution, AI winter, Albert Einstein, Alexey Pajitnov wrote Tetris, algorithmic trading, Amazon Mechanical Turk, Apple II, artificial general intelligence, Automated Insights, autonomous vehicles, book scanning, borderless world, call centre, cellular automata, Claude Shannon: information theory, cloud computing, computer vision, correlation does not imply causation, crowdsourcing, drone strike, Elon Musk, Flash crash, friendly AI, game design, global village, Google X / Alphabet X, 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, Marc Andreessen, Mark Zuckerberg, Menlo Park, natural language processing, Norbert Wiener, out of africa, PageRank, pattern recognition, Ray Kurzweil, recommendation engine, remote working, RFID, 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, technological singularity, The Coming Technological Singularity, The Future of Employment, Tim Cook: Apple, too big to fail, Turing machine, Turing test, Vernor Vinge, Watson beat the top human players on Jeopardy!
Mitsuku had no good answer.fn1 Not everyone is enamoured with the Loebner Prize. Marvin Minsky called the competition ‘obnoxious and stupid’. Part of this is down to Hugh Loebner himself, who seems to have an ingrained desire to upset the AI old guard wherever possible. Years ago, he provoked Minsky so much that Minsky finally snapped and said he would put up $100 to whoever could stop Loebner from staging his infernal contest. Loebner argued that since the only way the contest could be stopped was for someone to win its $100,000 grand prize, Minsky was essentially co-sponsoring the Loebner Prize. He wasted no time issuing a press release to say exactly that. Minsky spent years fuming about it. But the other reason some (although not all) serious AI experts dismiss the Loebner Prize is that it is, essentially, a trick of the light.
No one alive today has done more to promote the idea of the Turing Test than Hugh Loebner, a colourful, self-proclaimed egotist with dyed black hair, who started out his career selling folding disco dance floors. Now in his seventies, the decision to stage what is now one of the world’s best-known AI competitions only occurred to Loebner when he was well into middle age. The success of what he named the Loebner Prize is all the more surprising given that he has no qualifications whatsoever in computer science. ‘In years to come, there may be richer prizes, and more prestigious contests, but gads, this will always be the oldest,’ Loebner has said, with typical chutzpah. Loebner started the annual Loebner Prize in 1990. Each year it draws ‘chatterbot’ – or ‘chatbot’ – creators from all over the world, as their conversational AIs compete in text-based conversations designed to fool human judges. The best-performing chatterbot receives $4,000, which is paid out by Loebner himself.
But the other reason some (although not all) serious AI experts dismiss the Loebner Prize is that it is, essentially, a trick of the light. It is reminiscent of a magician who is praised not for his ability to perform genuine magic, but rather for his use of sleight-of-hand and misdirection to create an impressive illusion. ‘Unfortunately, the chatbots of today can only resort to trickery to hopefully fool a human into thinking they are sentient,’ one recent entrant in the Loebner Prize told me. ‘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’.
What Algorithms Want: Imagination in the Age of Computing by Ed Finn
Airbnb, Albert Einstein, algorithmic trading, Amazon Mechanical Turk, Amazon Web Services, bitcoin, blockchain, Chuck Templeton: OpenTable:, Claude Shannon: information theory, commoditize, Credit Default Swap, crowdsourcing, cryptocurrency, disruptive innovation, Donald Knuth, Douglas Engelbart, Douglas Engelbart, Elon Musk, factory automation, fiat currency, Filter Bubble, Flash crash, game design, Google Glasses, Google X / Alphabet X, High speed trading, hiring and firing, invisible hand, Isaac Newton, iterative process, Jaron Lanier, Jeff Bezos, job automation, John Conway, John Markoff, Just-in-time delivery, Kickstarter, late fees, lifelogging, Loebner Prize, Lyft, Mother of all demos, Nate Silver, natural language processing, Netflix Prize, new economy, Nicholas Carr, Norbert Wiener, PageRank, peer-to-peer, Peter Thiel, Ray Kurzweil, recommendation engine, Republic of Letters, ride hailing / ride sharing, Satoshi Nakamoto, self-driving car, sharing economy, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, social graph, software studies, speech recognition, statistical model, Steve Jobs, Steven Levy, Stewart Brand, supply-chain management, TaskRabbit, technological singularity, technoutopianism, 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
Discourse on the Method, Part V, quoted in Oppy and Dowe, “The Turing Test.” 43. Hafner, “Researchers Yearn to Use AOL Logs, but They Hesitate”; “AOL User 927 Illuminated.” 44. Anderson, “U Are What U Seek”; Engelberts and Plug, I Love Alaska. 45. Parisian Love. 46. 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.
Hill, Kashmir. “How Google Can ‘Forget’ People without the Rest of Us Forgetting It Happened.” Forbes, May 15, 2014. http://www.forbes.com/sites/kashmirhill/2014/05/15/how-google-can-rebelliously-comply-with-europes-right-to-be-forgotten-ruling. Hillis, Ken. Online a Lot of the Time: Ritual, Fetish, Sign. Durham, N.C.: Duke University Press, 2009. “Home Page of the Loebner Prize.” Accessed May 28, 2014. http://www.loebner.net/Prizef/loebner-prize.html. Honan, Mat. “Siri Is Apple’s Broken Promise.” Gizmodo. Accessed May 28, 2014. http://gizmodo.com/5864293/siri-is-apples-broken-promise. “Internet Used by 3.2 Billion People in 2015.” BBC News, May 26, 2015. http://www.bbc.com/news/technology-32884867. “Introducing Netflix Social.” Netflix Media Center. Accessed February 6, 2016. https://media.netflix.com/en/company-blog/introducing-netflix-social.
While less omnipresent than Google, the company’s influence on digital culture is still striking: on any given day in 2014, roughly a third of all Internet data downloaded during peak periods consisted of streaming files from Netflix.2 By the end of 2013, the company’s 40 million subscribers watched a billion hours of content each month.3 In 2006, Netflix announced a mathematical competition with a million dollar prize: improve the company’s recommendation algorithm by at least 10 percent. Modeled on other contests like DARPA grand challenges and the Loebner Prize (the annual Turing Test competition), the Netflix Prize invited outside researchers to teach them new algorithmic tricks that could improve the efficiency with which they recommended movies to their customers. It was an approach entirely in keeping with the company’s reputation as an early darling of the disruptors: a Silicon Valley firm that was successfully upending a staid economic model.
Average Is Over: Powering America Beyond the Age of the Great Stagnation by Tyler Cowen
Amazon Mechanical Turk, Black Swan, brain emulation, Brownian motion, business cycle, Cass Sunstein, choice architecture, complexity theory, computer age, computer vision, computerized trading, cosmological constant, crowdsourcing, dark matter, David Brooks, David Ricardo: comparative advantage, deliberate practice, Drosophila, en.wikipedia.org, endowment effect, epigenetics, Erik Brynjolfsson, eurozone crisis, experimental economics, Flynn Effect, Freestyle chess, full employment, future of work, game design, income inequality, industrial robot, informal economy, Isaac Newton, Johannes Kepler, John Markoff, Khan Academy, labor-force participation, Loebner Prize, low skilled workers, manufacturing employment, Mark Zuckerberg, meta analysis, meta-analysis, microcredit, Myron Scholes, Narrative Science, Netflix Prize, Nicholas Carr, P = NP, pattern recognition, Peter Thiel, randomized controlled trial, Ray Kurzweil, reshoring, Richard Florida, Richard Thaler, Ronald Reagan, Silicon Valley, Skype, statistical model, stem cell, Steve Jobs, Turing test, Tyler Cowen: Great Stagnation, upwardly mobile, Yogi Berra
So far the machines have had only mixed results at passing the Turing test. Getting human conversation “right” is a complex, multidimensional problem, highly sensitive to context and background understanding, and so it isn’t easy for a computer program. Here is a dialogue that Teppo Felin, a sociology blogger, had with Rosette, the program that won the 2011 Loebner Prize, which is dedicated to the Turing task: ROSETTE: Hello, again. Did you have a good day? TEPPO: congrats on winning the Loebner prize! ROSETTE: Why are you so excited about this? I think shopping summons up the ancient hunter-gatherer in me. I like having a mission to find something I need or want. Sometimes I’ll research online, to find a great deal, but I like rummaging through Jeremy’s up the road, if I want an outfit for a special occasion, or just for fun.
On the difficulties of building full AI without accompanying bodies, see Virginia Hughes, “Body Conscious: When It Comes to Artificial Intelligence, the Brain Isn’t Everything,” New Scientist, August 20, 2011. See also David J. Linden, “The Singularity Is Far: A Neuroscientist’s View,” BoingBoing, July 14, 2011, http://boingboing.net /2011/07/14/far.html. Another useful essay is David Robson, “Your Clever Body: Thinking from Head to Toe,” New Scientist, October 15, 2011. For the dialogue with Rosette, see http://orgtheory.wordpress.com/2011/10/22/2011 -loebner-prize-artificial-intelligence-still-has-a-long-way-to-go/. For a Tyler Cowen and Michelle Dawson paper on Turing, see “What Does the Turing Test Really Mean? And How Many Human Beings (Including Turing) Could Pass?”, June 3, 2009, http://www.gmu.edu/centers/publicchoice/faculty%20pages /Tyler/turingfinal.pdf. The characterization of Turing in particular, and his views in his famous essay, is taken from the article, although Dawson is not liable for any mistakes or shortcomings in this particular use of the material.
, 7, 12, 157 Jobs, Steve, 25 Jones, Benjamin, 216 Journal of the American Statistical Association, 10 journalism, 9 Junior (chess program), 68, 72, 78 Jurafsky, Dan, 12–13 K-12 education, 4, 168, 181–82 Kabbalah, 153 Kahneman, Daniel, 105, 227 Kaiser Family Foundation, 60 Karlan, Dean, 223 Kasparov, Garry, 7, 69, 77, 80–81, 110, 124, 157 Kaufman, Larry, 203 Kempelen, Wolfgang von, 149 Kepler, Johannes, 153 Keynesian economics, 53–54, 56, 226 Khan Academy, 180, 184–85 KIPP schools, 199 Knoxville, Tennessee, 244 Komodo (chess program), 68, 203 Kraai, Jesse, 188 Kramnik, Vladimir, 103, 109, 149–50 Kronrod, Alexander, 68 Krueger, Alan, 59 Krugman, Paul, 180–81, 227 Kurzweil, Ray, 6, 137–38 labor market and age of workers, 41–42, 51–52, 62–63 and benefit costs, 36, 59, 113 careers in the changing market, 41–44 changing worker profiles, 29–40 and computer skills, 21, 33 and conscientiousness of workers, 201–2 and factor price equalization, 163 and global trends, 3–4 and healthcare reform, 238 and hiring costs, 36, 59, 60 important worker characteristics, 32 and income trends, 39 labor economics, 226 and layoffs, 54–55, 57–58, 61 and management, 27–29 and man-machine collaboration, 93 and marketing, 22–27 and outsourcing, 163–71 participation rates, 45, 46, 51 polarization in, 37, 55, 231 and “reshoring” trend, 177 and residential segregation, 247–48 and retraining, 202 and the social contract, 229 laboratory science, 100 land prices, 236, 247 language recognition, 119, 139–41 Latin America, 167–68, 170–71, 242 law and legal issues and the changing labor market, 41 costs of employing labor, 36, 59 lawsuits, 36, 59, 60 lawyer ratings, 121 malpractice suits, 128 and medical diagnosis, 128–29 and reliance on computer systems, 128–31 See also regulatory issues layoffs, 54–55, 57–58, 61 Levitt, Steven, 226–27 liberalism, 252, 253–54 libertarianism, 256–57 lie detection, 12–13, 16 The Lights in the Tunnel (Ford), 6 liquidity crunch, 54, 55 Liu, Runjuan, 164 Loebner Prize, 139–40 logistic function, 203 long-term unemployment, 58 machine intelligence. See artificial intelligence (AI) machine science, 217–20 machine simulations, 200 macroeconomics, 9, 166, 211–12, 226 Makel, Matthew C., 188 malapropisms, 140–41 malpractice suits, 128 Malthusian wages, 136 management, 25, 27–29, 33 mandates, 237–38 Mandel, Michael, 165–66 manual labor, 56 manufacturing sector, 177 marginal costs, 182 marginal tax rates, 234 MarginalRevolution (blog), 90 Maria Theresa of Austria, 148 marketing, 11–12, 22–27, 34, 146 Marzolo, Cyril, 147 Massachusetts Institute of Technology (MIT), 37, 193, 222 master’s degrees, 37 Match Teacher Residency program, 200 Match.com, 9, 96, 98 matchmaking.
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, British Empire, Broken windows theory, call centre, Cass Sunstein, Chris Urmson, cloud computing, collateralized debt obligation, crowdsourcing, deindustrialization, Donald Trump, Erdős number, experimental subject, Ferguson, Missouri, Filter Bubble, Frank Gehry, game design, global supply chain, Googley, Guggenheim Bilbao, high net worth, Inbox Zero, income inequality, industrial cluster, Internet of things, Jane Jacobs, Jeff Bezos, Loebner Prize, Louis Pasteur, 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, telemarketer, the built environment, The Death and Life of Great American Cities, Turing test, urban decay, William Langewiesche
In Turing’s “imitation game,” a judge would communicate through a teleprompter with a human and a computer. The human’s job was to prove that she was, indeed, human. The computer’s job was to imitate human conversation convincingly enough to confuse the judge.28 Turing optimistically predicted that by the year 2000, computers would be able to fool 30 percent of human judges after five minutes of conversation. He was almost right: in 2008, at an annual Turing test tournament called the Loebner Prize, the best computer came within a single vote of Turing’s benchmark. How? The science writer Brian Christian had an answer: computers are able to imitate humans not because the computers are such accomplished conversationalists, but because we humans are so robotic.29 An extreme example is the “pickup artist” subculture, devoted to seducing women through prescripted interactions. On Internet forums, these men will swap ideas for “openers”—the Jealous Girlfriend opener, the My Little Pony opener, the You Guys Can Settle a Debate opener—which men can use to approach “sets,” or what you and I might call “groups of women talking to one another.”
And it isn’t just high school seniors who like to fool themselves about that. From Marco “Rubot” Rubio’s strange repetitive glitch, to the schwerfällig British generals outmaneuvered by Erwin Rommel, to the managers who try to tie performance down to a reductive target, we are always reaching for tidy answers, only to find that they’re of little use when the questions get messy. Each year that the computers fail to pass the Turing test, the Loebner Prize judges award a consolation prize for the best effort: it is the prize for the Most Human Computer. But there is also a prize for the human confederates who participate in the contest: the Most Human Human. Brian Christian entered the 2009 Loebner contest with the aim of winning that honor. He understood that it was not enough simply to chat away as humans often do, because too much human chat is itself formulaic and robotic.
We don’t have to be a genius like Keith Jarrett or Martin Luther King to make a risk pay off. Second, he stepped away from the generic, always looking for the details of the world around him. Chatbots, automated phone menus, and pickup artists flourish in a sterile bubble, devoid of context and history. Human conversation works best when it is rooted in the subtleties of a particular moment. At one point in the 2009 Loebner Prize competition, two participants realized that they were both from Toronto and started geeking out about ice hockey. It was instantly clear that neither of them was a computer. When a Zappos customer service rep realizes that the customer is physically just down the street in Las Vegas, she proves she isn’t a computer, either. Third, Brian Christian disrupted the conversation, because that is what real humans do.
The Creativity Code: How AI Is Learning to Write, Paint and Think by Marcus Du Sautoy
3D printing, Ada Lovelace, Albert Einstein, Alvin Roth, Andrew Wiles, Automated Insights, Benoit Mandelbrot, Claude Shannon: information theory, computer vision, correlation does not imply causation, crowdsourcing, data is the new oil, Donald Trump, double helix, Douglas Hofstadter, Elon Musk, Erik Brynjolfsson, Fellow of the Royal Society, Flash crash, Gödel, Escher, Bach, Henri Poincaré, Jacquard loom, John Conway, Kickstarter, Loebner Prize, mandelbrot fractal, Minecraft, music of the spheres, 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, Turing test, Watson beat the top human players on Jeopardy!, wikimedia commons
Great resource for AlphaGo including all the games with Lee Sedol: https://deepmind.com/research/alphago/. To read The Seeker by thricedotted, see the following link at github, the hosting service for computer code: https://github.com/thricedotted/theseeker. Other novels created as part of NaNoGenMo can be found at: https://nanogenmo.github.io/. Loebner prize transcripts can be found at: https://www.aisb.org.uk/events/loebner-prize. To view works by and articles about AARON: http://aaronshome.com/. To view works by and articles about ‘The Painting Fool’: http://www.thepaintingfool.com/. To see the paintings generated by the Elgammal’s Creative Adversarial Network: https://sites.google.com/site/digihumanlab/home. To see how good algorithms are at recognising an image: https://cloud.google.com/vision/.
An algorithmic doctor is expected to have the answers, so ELIZA wouldn’t be much good at diagnosing your illness, but there are algorithms evolving that might be better than your GP at figuring out what’s wrong with you. If you are tempted, you can give ELIZA a spin with the many online versions that still exist on the internet. The challenge of creating a program that could be more flexible and persuasive in its responses was spiced up in the early 1990s by the creation of the Loebner Prize. Underwritten by Hugh Loebner, an inventor and something of an outsider to the mainstream research on AI, the prize invited a panel of judges to interact with a human and a computer for a set period of time and decide which was the AI. If a system could fool half the judges, its creator would receive a silver medal and $25,000. In the event that this did not happen in any given year, prizes were to be awarded to the creators of the AI system that convinced most judges it was human.
(game show) 260–7, 273 Jie Shan 56 Jockers, Matthew 283 Jones, Jonathan 129–30, 148 Joyce, James 11 Jukedeck 225–6 Jung, Carl 81, 100 kabbalah 207–8 Kafka, Franz 274, 289, 290 Kahana, Eran 109 Kant, Immanuel 4, 105 Kapoor, Anish 118 Kasparov, Garry 29, 260–1 Kazemi, Darius 282 Keats, John 281 Ke Jie 42–3 Kepler’s Conjecture 170 Kerner, Winifred 201 K-456 (robot) 119 Kinect 72–6, 79, 81–2 Klee, Paul 18, 123, 134; Pedagogical Sketchbook 134 Knipe, Adolphe 276–7 Kolof, Lorenz Mizler von 185, 193, 208 Korsten, Bas 129 Kurzweil, Ray 280–1 LabSix 77–8 Laird, Benjamin 281–2 Lampard, Frank 55 language 254–75; Chinese Room experiment and 273–5; ELIZA and 255–7, 259; encryption, algorithms create language to aide 272–3; Jeopardy! and 260–3; Loebner Prize and 257–9; robots and 271–2; translator algorithms 268–71; Turing Test and 254–7, 258, 260, 273; Watson and 261–8, 273; Winograd challenges and 259–60 see also storytelling large numbers, law of 215 Larson, Steve 201 Lascaux cave, France 156 Lawrence, Peter: The Making of a Fly 62–4 Le Corbusier 112 Le Cri de Paris 139 legal system 25, 94–5, 109, 165–6 Legg, Shane 25 Leibniz, Gottfried Wilhelm 186 Les Publications mathématiques de l’IHES 177, 243 Lescure, Jean 278, 279, 282 Levine, Mark: The Jazz Theory Book 214 literature, algorithmic generated 276–97 Littlewood, J.
The Language Instinct: How the Mind Creates Language by Steven Pinker
Albert Einstein, cloud computing, David Attenborough, double helix, Drosophila, elephant in my pajamas, finite state, illegal immigration, Joan Didion, Loebner Prize, mass immigration, Maui Hawaii, meta analysis, meta-analysis, MITM: man-in-the-middle, natural language processing, out of africa, phenotype, rolodex, Ronald Reagan, Sapir-Whorf hypothesis, Saturday Night Live, speech recognition, Steven Pinker, theory of mind, transatlantic slave trade, Turing machine, Turing test, twin studies, Yogi Berra
Understanding a sentence is one of these hard easy problems. To interact with computers we still have to learn their languages; they are not smart enough to learn ours. In fact, it is all too easy to give computers more credit at understanding than they deserve. Recently an annual competition was set up for the computer program that can best fool users into thinking that they are conversing with another human. The competition for the Loebner Prize was intended to implement a suggestion made by Alan Turing in a famous 1950 paper. He suggested that the philosophical question “Can machines think?” could best be answered in an imitation game, where a judge converses with a person over one terminal and with a computer programmed to imitate a person on another. If the judge cannot guess which is which, Turing suggested, there is no basis for denying that the computer can think.
Computer: Are you depressed often? User: Yes, almost all the time. Computer: Why do you say yes almost all the time? User: Right now I feel like I could cry. Computer: Is it because right now you feel like you could cry that you came to me? To Weizenbaum’s horror, one day he found his secretary transfixed at the terminal, pouring her heart out to the program. Most computer scientists are annoyed by the Loebner Prize competition. They consider it a pointless publicity stunt, because it is an exercise in how to fool an amateur, not how to get computers to use language. (Artificial intelligence researchers and other professionals who are knowledgeable about language were not allowed to act as judges, and none bothered to compete; the submissions were from hobbyists.) It is about as productive as promoting biology by offering a prize to the designer of the most convincing silk flower, or running a space program by simulating a moon landing on a Hollywood back lot.
Signs were not coordinated into the well-defined motion contours of ASL and were not inflected for aspect, agreement, and so on—a striking omission, since inflection is the primary means in ASL of conveying who did what to whom and many other kinds of information. The trainers frequently claim that the chimps have syntax, because pairs of signs are sometimes placed in one order more often than chance would predict, and because the brighter chimps can act out sequences like Would you please carry the cooler to Penny. But remember from the Loebner Prize competition (for the most convincing computer simulation of a conversational partner) how easy it is to fool people into thinking that their interlocutors have humanlike talents. To understand the request, the chimp could ignore the symbols would, you, please, carry, the, and to; all the chimp had to notice was the order of the two nouns (and in most of the tests, not even that, because it is more natural to carry a cooler to a person than a person to a cooler).
I Think You'll Find It's a Bit More Complicated Than That by Ben Goldacre
call centre, conceptual framework, correlation does not imply causation, crowdsourcing, death of newspapers, Desert Island Discs, en.wikipedia.org, experimental subject, Firefox, Flynn Effect, jimmy wales, John Snow's cholera map, Loebner Prize, meta analysis, meta-analysis, moral panic, placebo effect, publication bias, selection bias, selective serotonin reuptake inhibitor (SSRI), Simon Singh, statistical model, stem cell, the scientific method, Turing test, WikiLeaks
Reading New Scientist’s chat with Nanniebot, the excellent www.ntk.net/ (Private Eye for geeks) points out that Nanniebot ‘seems to be able to make logical deductions, parse colloquial English, correctly choose the correct moment to scan a database of UK national holidays, comment on the relative qualities of the Robocop series, and divine the nature of pancakes and pancake day’. Jabberwock, the winner of last year’s Loebner Prize for the Turing test, is rubbish in comparison (you can talk to it online and see for yourself). But Jim Wightman, the Nanniebot inventor – whose site claims they’ve passed the Turing test – isn’t entering the Loebner Prize this year. Maybe next year … it’s too buggy. But it’s live on the internet already? Can I test it? Sure. But I want to see with my own eyes that there’s not a real human being somewhere tapping out the answers, I explain. Jim offers network-monitoring software on my computer, to prove it’s connected to the one server.
263 heart attack 8, 9, 79, 119–20, 134–6, 172, 173, 174–6, 209–10, 265 Hegarty LLP 256 Helicobacter pylori 9 hepatitis B 233, 356 hepatitis C 225, 233 heroin, xx, 221–4, 225–44 hierarchies of evidence 359 highly active antiretroviral therapy (HAART) 140 Hinkley Point 95–6 HIV 182–7, 225, 233–4, 244, 254, 281–3, 284, 285, 286 see also Aids Hodgkinson, Neville 283 Holfordwatch 252 Holt, Peter 19 Home Office xix, 157, 158, 159, 163, 193, 230, 232 home taping 159–62 homeopathy xvii, 20–1, 124, 137, 194, 262, 264, 304, 321–4, 389 Homeopathy News 389 homosexuality: age and 92–4; mental illness and 312–13 hormone-replacement therapy (HRT) 8–9 Hospital Episodes Statistics 18 Houben, Rom 324–6 House of Numbers (film) 281–3, 284 How to be Beautiful (Murray) 387 HPV 334 Huff, Darrell: How to Lie with Statistics 89–91 Hussein, Saddam 316–17 Hutton, John 221, 224 hypoactive sexual desire disorder (HSDD) 38 IARC (International Agency for Research on Cancer) 116 ICM 96 ignoring results from people you don’t trust 20–2 Imperial College 285 inclusion body myositis (IBM) 26, 27 Independent External Review for Department of Education on improving use if evidence and data in schools 202n Independent 29, 61, 197, 345, 390 Insight Cube™ 154 Institute of Child Health 120 intelligent design 13 International Journal of Evidence-Based Healthcare: ‘Deconstructing the Evidence-Based Discourse in Health Sciences: Truth, Power and Fascism’ (International Journal of Evidence-Based Healthcare) 297 International Journal of Obesity 338 International Journal of Psychology 15–16 internet use, autism and 3 The Internet’s Own Boy (documentary) 34 Interphone 118 Ioannidis, Professor John 9–10, 132, 133 Ion-Conditioning Hairdryer 388 IQ scores, gradual improvement in 188 Iraq, detecting bombs in 273–5; weapons of mass destruction (WMD) in 316–17 irrationality, science of xxi, 301–26; cigarette packaging 318–21; crime, outrage is lower when a criminal has more victims xxi, 306–9; evidence-based smear campaigns 316–18; facilitated communication in coma patients 324–6; female musicians’ clothing and performance 309–11; illusions of control 305–6; nocebo effect 321–4; pre-existing view, scientific evidence that challenges a 311–13; superstition and improved performance 313–15; visualisation and fruit intake 303–4 IVF 107, 180, 181 Jack of Kent (blogger) 252 Jammeh, Yahya 182 JCVI (Joint Committee on Vaccination and Immunisation) 353 Jill Dando Institute 163 Johnson, Alan 22, 24 Johnston, Lucy 333 Jordan, David Starr: Higher Foolishness 262 Journal of Aids 139 Journal of Applied Social Psychology 312 Journal of Public Health Nutrition 337 Journal of the American Chemical Society (JACS) 135 Journal of the American Medical Association (JAMA) 11, 12 Journal of Trionic Physics 388 Journal of Wine Research 125 journalism, bad xxi–xxii, 327–67; academic PR, dodgy 358–60; breast cancer and diet 338–40; caveats, hidden 338–40; cervical cancer jab, dangers of 331–4; exercise, weight gain and 335–8; fish oil and concentration 343–7; journalists linking to primary sources 340–2; MMR and 347–58; rape, women’s clothing, alcohol and 329–31; Roger Coghill and ‘the Aids test’ 363–7; suicide and phone masts 363–5; suicide, press coverage of details of 361–3 JSTOR 32–4 Kelsey, Tim 80, 81 Kelvedon Hatch secret nuclear bunker 94 Kemshall, Professor Hazel 158 Kenyon, Paul 289–90 King’s College London: Mobile Phones Research Unit 125 King’s Fund 19, 176 Kirlian photography 387 Krügel, Danie 275–7 Labour Party 59, 150, 155–6, 176, 177 Ladies Home Journal 44 Lancet 118, 121, 140, 145 Lansley, Andrew 171–4 Laureys, Professor Steven 326 Lawrence, Nikki 267 LayScience 252 libel xvii, xx, 245–58; BCA sue Simon Singh 250–4; breast enhancement cream 254–7; Dr Gillian McKeith calls Bad Science ‘lies’ 257–8; NMT sue Dr Peter Wilmshurst 247–50 libido problems, brain and 37–9 ‘Lindsay Syndrome’ 305–6 lipid-lowering drugs 119–20 local council overspending xix, 152–4 ‘locked-in syndrome’ 324, 325 Loebner Prize 392 London Raindance Film Festival 284 LSD 230 lucky ball xxi, 314 lung cancer 22, 107–9, 319 Lysenko, Trofim 262–3 McDonnell, Mary 307 McKee, Martin 175–6 McKeith, Gillian xvii, xx, 257–8 McTimoney Chiropractic Association (MCA) 253, 254 Maggiore, Christine 283, 285, 286 Maggiore, Eliza Jane 283, 286 magic boxes xxi, 271–8; ADE 651 273–5; bioresonance 277–8; Krügel missing people locator 275–7 magnetic wine 122–6 Manchester Evening News 155 Manning, Julia 180 Marcus, Adam 134 Marketing Innovations Inc. 21 Martin, Simon 278 masturbation, nasal congestion and 139, 143–6 maths, decline in quality of UK 194–6 MBA California Facial Mask 309 Mbeki, Thabo 185, 285 ‘Measuring the Mathematics Problem’ report, Engineering Council 190 Medical Hypotheses 139–46; AIDS denialism 138–41; ‘Down Subjects and Oriental Population Share Several Specific Attitudes and Characteristics’ article 139, 141–3; masturbation as a treatment for nasal congestion, articles discussing benefits and side effects of 139, 143–6 Medical Research Council 252 Medicines and Healthcare Regulatory Authority, The 321–2 Medline 125, 141 Melville, Caspar 281, 283 Merck 333 meta-analysis 235, 304, 359, 401 methadone 227–9, 231, 234–43 Metro 37–8, 66–7 MI5 52 microfinance 204–5 miniature steam railways xxii, 379–81 Ministry of Defence (MoD) 221–3 MinistryofTruth 252 ‘Miracle Mineral Solution’ 12 MIT 32–3 MMR jab 85, 304; Bad Science column manifesto and 399; Lancet 1998 paper on MMR, autism and bowel problems 145, Lucy Johnston stories on 333; return of scare stories about 347–58 mobile phones: cancer and 116–18, 290; council spending and 153, 154; electrosensitivity and 292; stalking your girlfriend using xxii, 382–3; suicides and phone masts 363–7 Mobile Phones Research Unit, King’s College London 125 Monbiot, George 32 Morgan, Rhys 12 Mozambique 183–4 MRI machines 37–9 MRSA 124 Mullen, Dr Michael 249 Mulrow, Celia 6 multiple sclerosis 356 Munro, Professor Geoffrey 312 Muntoni, Francesco 121 Murray, Dale 274 music piracy xix, 159–62 ‘Nanniebots’, search for paedophiles and 391–5 nasal congestion, masturbation and 139, 143–6 Nash, Barbara 268–9 National Autistic Society 325 National Centre for the Replacement, Refinement and Reduction of Animals in Research, The 137 National Down Syndrome Cytogenetic Register 62, 63 National Explosive Engineering Sciences Security Center, Sandia Labs 274 National Institute for Health Research (NIHR) 216 Nature Neuroscience 129, 131 Nature Reviews Neuroscience 38 Nazis 22, 23, 262, 300 Nelson, Fraser 284, 285, 286 Nerdydaytrips.com 381 network theory 26–8 neuroscience xix, 37–9, 129, 130–1, 138 Neverland Systems 393 Nevirapine 186 New England Journal of Medicine 9 New Humanist 281 New Scientist xxii, 391, 393, 394, 395 New York Herald Tribune 261 New York Times 39, 273, 274–5 New York University 297 Newsnight 197 NHS xix; abortion and 90–1; Cancer Plan 170; care.data and 78–86; coalition government reforms xix, 73, 169–77; constitution 180; GP Consortiums 171–4, 175, 176; NHS Choices website 18, 63; NHS Information Centre (NHSIC) 84, 85, 170; ‘NHS Operating Framework’ 172; pornography for sperm donors xix, 179–82; price-based competition in 172–3, 174–5; Primary Care Research Network 216; Primary Care Trusts 171–2; waiting times 73–5; ‘Working Together For A Stronger NHS’ government leaflet 169 Nield, Dr Dalia 255–6 Nieuwenhuis, Sander 129, 130–1 Nigeria: polio vaccine scare in 273, 356–7 9/11 13 ‘95 per cent confidence intervals’ 59–61 NMT 247–50 nocebo effect 321–4 Nolte, Ellen 175–6 Nordgren, Loran 307 NSA (National Security Agency), US 79–80 NSPCC 394 ntk.net 391 nuclear power xvi, xxii, 85, 94, 95–7, 379, 381 O’Connor, Cardinal Cormac Murphy 183 Observer: Denis Campbell MMR stories 347–55; Denis Campbell ‘fish oil helps schoolchildren to concentrate’ story 343–7; ‘Forensic DNA Tests “Reveal Traces of Madeleine’s Body on Resort Beach”’ story 276 OECD 175 Office of Fair Trading 265 Office of National Statistics (ONS): ‘Annual Survey of Hours and Earnings’ 150–2; births per year statistics 49–50; exam results and 189; ‘Labour Market’ figures 59; Statistical Bulletin 49–50 Olympics: 1992 156; 2012 xix, 155–7 Omand, Sir David 51–3 omega-3 fatty acids 343–6 The One Show 12 open data 20, 80, 85 Open Data (government initiative) 85 Opera Solutions 153–4 Oransky, Ivan 134 organic food xix, 191–4 Overfield, Dr Derek 57 Oxford University 3, 4, 5, 138, 194 Oxygizer 390–1 paedophiles, ‘Nanniebots’ and 391–5 Page, Dawn 268, 269–70 Pain 322 Pakistan 231, 232, 357 Panorama: wi-fi link to radiation story xxi, 289–91, 293 Parker, Matt 68, 69 Parliament 76, 84, 85, 196–7, 200–1, 322 Parry, Vivienne 353 peer review xvii, 4–5, 29, 139–41, 145; alternatives to 139–41, 145–6; dodgy peer reviewers delaying publication of findings they don’t like 10; GP fundholding and 176–7; journals deliberately not peer reviewed 145–6; post-publication xvi, 4–5; problematic nature of 138–41; putting a finding in a press release but not into the paper as a subversion of 66; refusal to submit ideas to 3–5 Pell, Cardinal George 183 Perfect Sommelier 123, 124 Perry, Simon 252–3, 266 pesticides, food and 191–4 Pfizer Trovan drug trial 357 Phelan, Jo: ‘Genetic Bases of Mental Illness – a Cure for Stigma?’
The End of Absence: Reclaiming What We've Lost in a World of Constant Connection by Michael Harris
4chan, Albert Einstein, AltaVista, Andrew Keen, augmented reality, Burning Man, Carrington event, cognitive dissonance, crowdsourcing, dematerialisation, en.wikipedia.org, Filter Bubble, Firefox, Google Glasses, informal economy, information retrieval, invention of movable type, invention of the printing press, invisible hand, James Watt: steam engine, Jaron Lanier, jimmy wales, Kevin Kelly, lifelogging, Loebner Prize, low earth orbit, Marshall McLuhan, McMansion, moral panic, Nicholas Carr, pattern recognition, pre–internet, Republic of Letters, Silicon Valley, Skype, Snapchat, social web, Steve Jobs, the medium is the message, The Wisdom of Crowds, Turing test
He declared, “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!’” Turing proposed that a machine could be called “intelligent” if people exchanging text messages with that machine could not tell whether they were communicating with a human. (There are a few people I know who would fail such a test, but that is another matter.) This challenge—which came to be called “the Turing test”—lives on in an annual competition for the Loebner Prize, a coveted solid-gold medal (plus $100,000 cash) for any computer whose conversation is so fluid, so believable, that it becomes indistinguishable from a human correspondent.7 At the Loebner competition (founded in 1990 by New York philanthropist Hugh Loebner), a panel of judges sits before computer screens and engages in brief, typed conversations with humans and computers—but they aren’t told which is which.
., III, 84–85 “He Poos Clouds” (Pallett), 164 History of Reading, A (Manguel), 16, 117, 159 Hollinghurst, Alan, 115 Holmes, Sherlock, 147–48 House at Pooh Corner, The (Milne), 93 Hugo, Victor, 20–21 “Idea of North, The” (Gould), 200–201 In Defense of Elitism (Henry), 84–85 Information, The (Gleick), 137 information retrieval, 141–42 Innis, Harold, 202 In Search of Lost Time (Proust), 160 Instagram, 19, 104, 149 Internet, 19, 20, 21, 23, 26–27, 55, 69, 125, 126, 129, 141, 143, 145, 146, 187, 199, 205 brain and, 37–38, 40, 142, 185 going without, 185, 186, 189–97, 200, 208–9 remembering life before, 7–8, 15–16, 21–22, 48, 55, 203 Internship, The, 89 iPad, 21, 31 children and, 26–27, 45 iPhone, see phones iPotty, 26 iTunes, 89 Jobs, Steve, 134 Jones, Patrick, 152n Justification of Johann Gutenberg, The (Morrison), 12 Kaiser Foundation, 27, 28n Kandel, Eric, 154 Kaufman, Charlie, 155 Keen, Andrew, 88 Kelly, Kevin, 43 Kierkegaard, Søren, 49 Kinsey, Alfred, 173 knowledge, 11–12, 75, 80, 82, 83, 86, 92, 94, 98, 141, 145–46 Google Books and, 102–3 Wikipedia and, 63, 78 Koller, Daphne, 95 Kranzberg, Melvin, 7 Kundera, Milan, 184 Lanier, Jaron, 85, 106–7, 189 latent Dirichlet allocation (LDA), 64–65 Leonardo da Vinci, 56 Lewis, R. W. B., 117 LinkedIn, 175 literacy, 13 Loebner, Hugh, 60 Loebner Prize, 60 Long Now Foundation, 204 “Look at ME,” 69 love, 176, 177 Luddites, 18, 207–8, 209 Luther, Martin, 12, 20 “Machine Stops, The” (Forster), 106–7, 109 Maeterlinck, Maurice, 5 magazines, 26–28, 45–46, 102 Malaysia, 1–2, 19 Man, John, 12n, 103 Manguel, Alberto, 16–17, 117, 117n, 159 Manhunt, 165 maps, 35, 98 Marx, Groucho, 17 Marx, Karl, 12n massive open online courses (MOOCs), 95–98 Matrix, The, 44–45 McGraw, Phil, 63 McLuhan, Marshall, 14, 34–35, 99, 179, 194, 201, 205 memes, 41–43 technology-based, 42–44 memorization, 145, 151–52, 156–59 memory, 32–33, 35, 40, 137–63 of absence, 202–3 brain and, 139, 140, 142, 146, 151–53, 155, 158 computer, 148, 149, 151, 152, 154–56 fear-based, 155–56 Google and, 143–47 group (transactive), 142–43 method of loci and, 146–47, 148 Molaison and, 138 off-loaded, 140–43, 145, 151, 155 of pre-Internet life, 7–8, 15–16, 21–22, 48, 55, 203 reconsolidation and, 154, 155 search engines and, 142–43, 146 Timehop and, 148–51, 160 memory palace, 146–47 Mesopotamia, 81 Microsoft, 64n Bing, 62 Windows, 43 Miller, Geoffrey, 105 Milne, A.
Race Against the Machine: How the Digital Revolution Is Accelerating Innovation, Driving Productivity, and Irreversibly Transforming Employment and the Economy by Erik Brynjolfsson
"Robert Solow", Amazon Mechanical Turk, Any sufficiently advanced technology is indistinguishable from magic, autonomous vehicles, business cycle, business process, call centre, combinatorial explosion, corporate governance, creative destruction, crowdsourcing, David Ricardo: comparative advantage, easy for humans, difficult for computers, Erik Brynjolfsson, factory automation, first square of the chessboard, first square of the chessboard / second half of the chessboard, Frank Levy and Richard Murnane: The New Division of Labor, hiring and firing, income inequality, intangible asset, job automation, John Markoff, John Maynard Keynes: technological unemployment, Joseph Schumpeter, Khan Academy, Kickstarter, knowledge worker, Loebner Prize, low skilled workers, minimum wage unemployment, patent troll, pattern recognition, Paul Samuelson, Ray Kurzweil, rising living standards, Robert Gordon, self-driving car, shareholder value, Skype, too big to fail, Turing test, Tyler Cowen: Great Stagnation, Watson beat the top human players on Jeopardy!, wealth creators, winner-take-all economy, zero-sum game
The mathematician and computer science pioneer Alan Turing considered the question of whether machines could think “too meaningless to deserve discussion,” but in 1950 he proposed a test to determine how humanlike a machine could become. The “Turing test” involves a test group of people having online chats with two entities, a human and a computer. If the members of the test group can’t in general tell which entity is the machine, then the machine passes the test. Turing himself predicted that by 2000 computers would be indistinguishable from people 70% of the time in his test. However, at the Loebner Prize, an annual Turing test competition held since 1990, the $25,000 prize for a chat program that can persuade half the judges of its humanity has yet to be awarded. Whatever else computers may be at present, they are not yet convincingly human. But as the examples in this chapter make clear, computers are now demonstrating skills and abilities that used to belong exclusively to human workers. This trend will only accelerate as we move deeper into the second half of the chessboard.
Outnumbered: From Facebook and Google to Fake News and Filter-Bubbles – the Algorithms That Control Our Lives by David Sumpter
affirmative action, Bernie Sanders, correlation does not imply causation, crowdsourcing, don't be evil, Donald Trump, Elon Musk, Filter Bubble, Google Glasses, illegal immigration, Jeff Bezos, job automation, Kenneth Arrow, Loebner Prize, Mark Zuckerberg, meta analysis, meta-analysis, Minecraft, Nate Silver, natural language processing, Nelson Mandela, p-value, prediction markets, random walk, Ray Kurzweil, Robert Mercer, selection bias, self-driving car, Silicon Valley, Skype, Snapchat, speech recognition, statistical model, Stephen Hawking, Steven Pinker, The Signal and the Noise by Nate Silver, traveling salesman, Turing test
Our automated author demonstrates that a set of logic gates, adjusted slightly to incorporate randomness, can capture some elements of the basic process of creating language. My ‘cat and dog’ algorithm is constrained by grammar, alternating patterns of verbs and nouns as well as stylistic requirements – an insistence that it is cats and dogs that fight each other. It is also creative in its random choice of verbs. Logical rules and random creativity are central components of the chatbot, Mitsuku, which won the Loebner Prize in both 2016 and 2017 for being the most human-like bot. She takes in the sentence generated by the person she is talking to, uses grammatical rules of the English language to pick out nouns and verbs and then generates replies. Her replies include a degree of randomness. When I asked Mitsuku if she always answers the same way to every question, she told me: ‘Not always; my botmaster has programmed me with more than 8MB of replies.’
But she was inconsistent on a number of points, claiming to work both as a lawyer and a doctor, depending on how the question was posed. Even after a joint, most students still know what course they are on. Oriol and Quoc paid Mechanical Turk workers to compare Julia with a top-down bot, called Cleverbot, to see which approach gave the best answers. Julia scored a narrow victory over Cleverbot. But from what I have read, I’m not sure she would beat Mitsuku. It would be fascinating to see them in a talk-off at the Loebner Prize competition. Let’s get back to reality here. What exactly is Julia? Mitsuku was limited by the time that Steve Worswick could realistically invest answering every possible question someone might pose to his bot. What are Julia’s limits? If we fed her a few hundred million more movie scenes, would she become even more realistic? I discussed these issues with Tomas Mikolov, an authority on computerised language processing.
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, Claude Shannon: information theory, cloud computing, computer age, Dean Kamen, discovery of DNA, double helix, en.wikipedia.org, epigenetics, George Gilder, Google Earth, Isaac Newton, iterative process, Jacquard loom, John von Neumann, Law of Accelerating Returns, linear programming, Loebner Prize, mandelbrot fractal, Norbert Wiener, optical character recognition, 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
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. In my view, the inclusion of audio and video does not actually make the test more challenging. 15. “Cognitive Assistant That Learns and Organizes,” Artificial Intelligence Center, SRI International, http://www.ai.sri.com/project/CALO. 16.
(TV show), 6–7, 108, 157–58, 160, 165, 166, 167, 168, 169, 172, 178, 232–33, 270 Joyce, James, 55 Kasparov, Garry, 39, 166 K Computer, 196 knowledge bases: AI systems and, 4, 6–7, 170–71, 246, 247 of digital neocortex, 177 exponential growth of, 3 as inherently hierarchical, 220 language and, 3 professional, 39–40 as recursively linked ideas, 3 Kodandaramaiah, Suhasa, 126 Koene, Randal, 89 Koltsov, Nikolai, 16 Kotler, Steven, 278 KurzweilAI.net, 161 Kurzweil Applied Intelligence, 144 Kurzweil Computer Products, 122 Kurzweil Voice, 160 lamina 1 neurons, 97 language: chimpanzees and, 3, 41 and growth of knowledge base, 3 hierarchical nature of, 56, 159, 162, 163 as metaphor, 115 as translation of thinking, 56, 68 language software, 51, 72–73, 92, 115–16, 122–23, 144–45, 145, 156, 157–72, 174, 270 expert managers in, 166–67 hand-coded rules in, 164–65, 166, 168 HHMMs in, 167–68 hierarchical systems in, 162–65 Larson, Gary, 277 “Last Voyage of the Ghost, The” (García Márquez), 3–4 lateral geniculate nucleus, 95, 100 law of accelerating returns (LOAR), 4, 6, 7, 41, 123 as applied to human brain, 261–63, 263, 264, 265 biomedicine and, 251, 252, 253 communication technology and, 253, 254 computation capacity and, 281, 316n–19n information technology and, 4, 249–57, 252, 257, 258, 259, 260, 261, 261 objections to, 266–82 predictions based on, 256–57, 257, 258, 259, 260, 261 and unlikelihood of other intelligent species, 5 “Law of Accelerating Returns, The” (Kurzweil), 267 laws of thermodynamics, 37, 267 learning, 61–65, 122, 155, 273–74 conditionals in, 65 and difficulty of grasping more than one conceptual level at a time, 65 in digital neocortex, 127–28, 175–76 environment and, 119 Hebbian, 80 hierarchical, 164, 195, 197 in neural nets, 132–33 neurological basis of, 79–80 pattern recognition as basic unit of, 80–81 of patterns, 63–64, 90 recognition as simultaneous with, 63 simultaneous processing in, 63, 146 legal systems, consciousness as basis of, 212–13 Leibniz, Gottfried Wilhelm, 34, 223 Lenat, Douglas, 162 Leviathan (Hobbes), 278 Lewis, Al, 93 Libet, Benjamin, 229–30, 231, 234 light, speed of, 281 Einstein’s thought experiments on, 18–23 linear programming, 64 LISP (LISt Processor), 153–55, 163 pattern recognition modules compared with, 154, 155 Lloyd, Seth, 316n, 317n Loebner, Hugh, 298n Loebner Prize, 298n logic, 38–39 logical positivism, 220 logic gates, 185 Lois, George, 113 love, 117–20 biochemical changes associated with, 118–19 evolutionary goals and, 119 pattern recognition modules and, 119–20 “Love Is the Drug,” 118 Lovelace, Ada Byron, Countess of, 190, 191 lucid dreaming, 72, 287n–88n Lyell, Charles, 14–15, 114, 177 McCarthy, John, 153 McClelland, Shearwood, 225 McGinn, Colin, 200 magnetic data storage, growth in, 261, 301n–3n magnetoencephalography, 129 Manchester Small-Scale Experimental Machine, 189 Mandelbrot set, 10–11, 10 Marconi, Guglielmo, 253 Mark 1 Perceptron, 131–32, 134, 135, 189 Markov, Andrei Andreyevich, 143 Markram, Henry, 80–82, 124–27, 129 mass equivalent, of energy, 22–23 Mathematica, 171 “Mathematical Theory of Communication, A” (Shannon), 184 Mauchly, John, 189 Maudsley, Henry, 224 Maxwell, James Clerk, 20 Maxwell, Robert, 225 Mead, Carver, 194–95 medial geniculate nucleus, 97, 100 medicine, AI and, 6–7, 39, 108, 156, 160–61, 168 memes: consciousness as, 211, 235 free will as, 235 memory, in computers, 185, 259, 260, 268, 301n–3n, 306n–7n memory, memories, human: abstract concepts in, 58–59 capacity of, 192–93 computers as extensions of, 169 consciousness vs., 28–29, 206–7, 217 dimming of, 29, 59 hippocampus and, 101–2 as ordered sequences of patterns, 27–29, 54 redundancy of, 59 unexpected recall of, 31–32, 54, 68–69 working, 101 Menabrea, Luigi, 190 metacognition, 200, 201 metaphors, 14–15, 113–17, 176–77 Michelson, Albert, 18, 19, 36, 114 Michelson-Morley experiment, 19, 36, 114 microtubules, 206, 207, 208, 274 Miescher, Friedrich, 16 mind, 11 pattern recognition theory of (PRTM), 5–6, 8, 11, 34–74, 79, 80, 86, 92, 111, 172, 217 thought experiments on, 199–247 mind-body problem, 221 Minsky, Marvin, 62, 133–35, 134, 199, 228 MIT Artificial Intelligence Laboratory, 134 MIT Picower Institute for Learning and Memory, 101 MobilEye, 159 modeling, complexity and, 37–38 Modha, Dharmendra, 128, 195, 271–72 momentum, 20–21 conservation of, 21–22 Money, John William, 118, 119 montane vole, 119 mood, regulation of, 106 Moore, Gordon, 251 Moore’s law, 251, 255, 268 moral intelligence, 201 moral systems, consciousness as basis of, 212–13 Moravec, Hans, 196 Morley, Edward, 18, 19, 36, 114 Moskovitz, Dustin, 156 motor cortex, 36, 99 motor nerves, 99 Mountcastle, Vernon, 36, 37, 94 Mozart, Leopold, 111 Mozart, Wolfgang Amadeus, 111, 112 MRI (magnetic resonance imaging), 129 spatial resolution of, 262–65, 263, 309n MT (V5) visual cortex region, 83, 95 Muckli, Lars, 225 music, as universal to human culture, 62 mutations, simulated, 148 names, recalling, 32 National Institutes of Health, 129 natural selection, 76 geologic process as metaphor for, 14–15, 114, 177 see also evolution Nature, 94 nematode nervous system, simulation of, 124 neocortex, 3, 7, 77, 78 AI reverse-engineering of, see neocortex, digital bidirectional flow of information in, 85–86, 91 evolution of, 35–36 expansion of, through AI, 172, 266–72, 276 expansion of, through collaboration, 116 hierarchical order of, 41–53 learning process of, see learning linear organization of, 250 as metaphor machine, 113 neural leakage in, 150–51 old brain as modulated by, 93–94, 105, 108 one-dimensional representations of multidimensional data in, 53, 66, 91, 141–42 pattern recognition in, see pattern recognition pattern recognizers in, see pattern recognition modules plasticity of, see brain plasticity prediction by, 50–51, 52, 58, 60, 66–67, 250 PRTM as basic algorithm of, 6 pruning of unused connections in, 83, 90, 143, 174 redundancy in, 9, 224 regular grid structure of, 82–83, 84, 85, 129, 262 sensory input in, 58, 60 simultaneous processing of information in, 193 specific types of patterns associated with regions of, 86–87, 89–90, 91, 111, 152 structural simplicity of, 11 structural uniformity of, 36–37 structure of, 35–37, 38, 75–92 as survival mechanism, 79, 250 thalamus as gateway to, 100–101 total capacity of, 40, 280 total number of neurons in, 230 unconscious activity in, 228, 231, 233 unified model of, 24, 34–74 as unique to mammalian brain, 93, 286n universal processing algorithm of, 86, 88, 90–91, 152, 272 see also cerebral cortex neocortex, digital, 6–8, 41, 116–17, 121–78, 195 benefits of, 123–24, 247 bidirectional flow of information in, 173 as capable of being copied, 247 critical thinking module for, 176, 197 as extension of human brain, 172, 276 HHMMs in, 174–75 hierarchical structure of, 173 knowledge bases of, 177 learning in, 127–28, 175–76 metaphor search module in, 176–77 moral education of, 177–78 pattern redundancy in, 175 simultaneous searching in, 177 structure of, 172–78 virtual neural connections in, 173–74 neocortical columns, 36–37, 38, 90, 124–25 nervous systems, 2 neural circuits, unreliability of, 185 neural implants, 243, 245 neural nets, 131–35, 144, 155 algorithm for, 291n–97n feedforward, 134, 135 learning in, 132–33 neural processing: digital emulation of, 195–97 massive parallelism of, 192, 193, 195 speed of, 192, 195 neuromorphic chips, 194–95, 196 neuromuscular junction, 99 neurons, 2, 36, 38, 43, 80, 172 neurotransmitters, 105–7 new brain, see neocortex Newell, Allen, 181 New Kind of Science, A (Wolfram), 236, 239 Newton, Isaac, 94 Nietzsche, Friedrich, 117 nonbiological systems, as capable of being copied, 247 nondestructive imaging techniques, 127, 129, 264, 312n–13n nonmammals, reasoning by, 286n noradrenaline, 107 norepinephrine, 118 Notes from Underground (Dostoevsky), 199 Nuance Speech Technologies, 6–7, 108, 122, 152, 161, 162, 168 nucleus accumbens, 77, 105 Numenta, 156 NuPIC, 156 obsessive-compulsive disorder, 118 occipital lobe, 36 old brain, 63, 71, 90, 93–108 neocortex as modulator of, 93–94, 105, 108 sensory pathway in, 94–98 olfactory system, 100 Oluseun, Oluseyi, 204 OmniPage, 122 One Hundred Years of Solitude (García Márquez), 283n–85n On Intelligence (Hawkins and Blakeslee), 73, 156 On the Origin of Species (Darwin), 15–16 optical character recognition (OCR), 122 optic nerve, 95, 100 channels of, 94–95, 96 organisms, simulated, evolution of, 147–53 overfitting problem, 150 oxytocin, 119 pancreas, 37 panprotopsychism, 203, 213 Papert, Seymour, 134–35, 134 parameters, in pattern recognition: “God,” 147 importance, 42, 48–49, 60, 66, 67 size, 42, 49–50, 60, 61, 66, 67, 73–74, 91–92, 173 size variability, 42, 49–50, 67, 73–74, 91–92 Parker, Sean, 156 Parkinson’s disease, 243, 245 particle physics, see quantum mechanics Pascal, Blaise, 117 patch-clamp robotics, 125–26, 126 pattern recognition, 195 of abstract concepts, 58–59 as based on experience, 50, 90, 273–74 as basic unit of learning, 80–81 bidirectional flow of information in, 52, 58, 68 distortions and, 30 eye movement and, 73 as hierarchical, 33, 90, 138, 142 of images, 48 invariance and, see invariance, in pattern recognition learning as simultaneous with, 63 list combining in, 60–61 in neocortex, see pattern recognition modules redundancy in, 39–40, 57, 60, 64, 185 pattern recognition modules, 35–41, 42, 90, 198 autoassociation in, 60–61 axons of, 42, 43, 66, 67, 113, 173 bidirectional flow of information to and from thalamus, 100–101 dendrites of, 42, 43, 66, 67 digital, 172–73, 175, 195 expectation (excitatory) signals in, 42, 52, 54, 60, 67, 73, 85, 91, 100, 112, 173, 175, 196–97 genetically determined structure of, 80 “God parameter” in, 147 importance parameters in, 42, 48–49, 60, 66, 67 inhibitory signals in, 42, 52–53, 67, 85, 91, 100, 173 input in, 41–42, 42, 53–59 love and, 119–20 neural connections between, 90 as neuronal assemblies, 80–81 one-dimensional representation of multidimensional data in, 53, 66, 91, 141–42 prediction by, 50–51, 52, 58, 60, 66–67 redundancy of, 42, 43, 48, 91 sequential processing of information by, 266 simultaneous firings of, 57–58, 57, 146 size parameters in, 42, 49–50, 60, 61, 66, 67, 73–74, 91–92, 173 size variability parameters in, 42, 67, 73–74, 91–92, 173 of sounds, 48 thresholds of, 48, 52–53, 60, 66, 67, 111–12, 173 total number of, 38, 40, 41, 113, 123, 280 universal algorithm of, 111, 275 pattern recognition theory of mind (PRTM), 5–6, 8, 11, 34–74, 79, 80, 86, 92, 111, 172, 217 patterns: hierarchical ordering of, 41–53 higher-level patterns attached to, 43, 45, 66, 67 input in, 41, 42, 44, 66, 67 learning of, 63–64, 90 name of, 42–43 output of, 42, 44, 66, 67 redundancy and, 64 specific areas of neocortex associated with, 86–87, 89–90, 91, 111, 152 storing of, 64–65 structure of, 41–53 Patterns, Inc., 156 Pavlov, Ivan Petrovich, 216 Penrose, Roger, 207–8, 274 perceptions, as influenced by expectations and interpretations, 31 perceptrons, 131–35 Perceptrons (Minsky and Papert), 134–35, 134 phenylethylamine, 118 Philosophical Investigations (Wittgenstein), 221 phonemes, 61, 135, 137, 146, 152 photons, 20–21 physics, 37 computational capacity and, 281, 316n–19n laws of, 37, 267 standard model of, 2 see also quantum mechanics Pinker, Steven, 76–77, 278 pituitary gland, 77 Plato, 212, 221, 231 pleasure, in old and new brains, 104–8 Poggio, Tomaso, 85, 159 posterior ventromedial nucleus (VMpo), 99–100, 99 prairie vole, 119 predictable outcomes, determined outcomes vs., 26, 239 President’s Council of Advisors on Science and Technology, 269 price/performance, of computation, 4–5, 250–51, 257, 257, 267–68, 301n–3n Principia Mathematica (Russell and Whitehead), 181 probability fields, 218–19, 235–36 professional knowledge, 39–40 proteins, reverse-engineering of, 4–5 qualia, 203–5, 210, 211 quality of life, perception of, 277–78 quantum computing, 207–9, 274 quantum mechanics, 218–19 observation in, 218–19, 235–36 randomness vs. determinism in, 236 Quinlan, Karen Ann, 101 Ramachandran, Vilayanur Subramanian “Rama,” 230 random access memory: growth in, 259, 260, 301n–3n, 306n–7n three-dimensional, 268 randomness, determinism and, 236 rationalization, see confabulation reality, hierarchical nature of, 4, 56, 90, 94, 172 recursion, 3, 7–8, 56, 65, 91, 153, 156, 177, 188 “Red” (Oluseum), 204 redundancy, 9, 39–40, 64, 184, 185, 197, 224 in genome, 271, 314n, 315n of memories, 59 of pattern recognition modules, 42, 43, 48, 91 thinking and, 57 religious ecstacy, 118 “Report to the President and Congress, Designing a Digital Future” (President’s Council of Advisors on Science and Technology), 269 retina, 95 reverse-engineering: of biological systems, 4–5 of human brain, see brain, human, computer emulation of; neocortex, digital Rosenblatt, Frank, 131, 133, 134, 135, 191 Roska, Boton, 94 Rothblatt, Martine, 278 routine tasks, as series of hierarchical steps, 32–33 Rowling, J.
Heart of the Machine: Our Future in a World of Artificial Emotional Intelligence by Richard Yonck
3D printing, AI winter, artificial general intelligence, Asperger Syndrome, augmented reality, Berlin Wall, brain emulation, Buckminster Fuller, call centre, cognitive bias, cognitive dissonance, computer age, computer vision, crowdsourcing, Elon Musk, en.wikipedia.org, epigenetics, friendly AI, 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, meta-analysis, Metcalfe’s law, neurotypical, Oculus Rift, old age dependency ratio, pattern recognition, RAND corporation, Ray Kurzweil, Rodney Brooks, self-driving car, Skype, social intelligence, software as a service, Stephen Hawking, Steven Pinker, superintelligent machines, technological singularity, telepresence, telepresence robot, The Future of Employment, the scientific method, theory of mind, Turing test, twin studies, undersea cable, Vernor Vinge, Watson beat the top human players on Jeopardy!, Whole Earth Review, working-age population, zero day
Now, it would be easy to excuse Robert’s gullibility—after all, anyone can fall prey to emotions, wishful thinking, loneliness, hormones, etc. Except that Robert was Dr. Robert Epstein, the former editor-in-chief of Psychology Today magazine, who has written numerous books on relationships and love and is one of the leading experts on human-machine interactions—more specifically, chatbots. In fact, in the 1990s, Epstein directed the Loebner Prize Competition in Artificial Intelligence, a contest in which judges attempt to distinguish conversations with computer programs from those with real people. To top it all off, Robert admits to having been tricked again by another chatbot not long after the first incident. In this case, he didn’t even make the discovery himself but was contacted by the chatbot’s programmer in the UK. The programmer wrote to say he knew who Robert was and that he needed to inform him that all this time he’d been communicating with a software program.
See implantable medical devices (IMDs) Immersive Labs, 144 impersonators, 141 implantable medical devices (IMDs), 167 implantable neuro-stimulation systems, 125–126 IMRSV, 72, 74–75 Indiegogo, 86 inferior frontal gyrus (IFG), 16, 23 information gathering and law enforcement, 142–143 Institute of Electrical and Electronics Engineers (IEEE), 45–46, 58 Intel, 217 intelligence development of, 257–259 and EQ, 202, 252, 257 ranges of, 255–257 intelligence explosion, 208, 241, 261–264 intercranial electroencephalography, 213 interface, 27–28 International Committee for Robot Arms Control (ICRAC), 130–131 International Joint Conference on Artificial Intelligence, 132 internet dating and chatbots, 140–141 Internet of Things, 137–138, 223 Introspective-consciousness, 243, 245, 250–251, 270 invasive brain-computer interface (BCI), 126 IRC, 210 iRobot, 200 iSET, 60 Ishiguro, Hiroshi, 100–101 J James, William, 17–18 James-Lange theory, 17–18, 214 ’Jaynes, Julian, 250, 257 Jennings, Ken, 233 Jentsch, Ernst, 96 Jeopardy, 197, 233 Jibo, 86 Johnson, Brian David, 168 Junko Chihira, 87 K Kairos, 144 Kappas, Arvid, 19 Kasparov, Gary, 232–233 Kelly, Kevin, 23, 267, 271–272 Kenyanthropus platyops, 10, 12–13 Kernal, 205 Kidd, Cory, 85–86 Kiiroo, 188 Kismet, 85 Knewton, 117–118 Kryder’s law, 40, 147 Kubrick, Stanley, 232 Kurzweil, Ray, 39, 41, 110, 174–175, 261–264 L LaBrie, Erika, 187 Lange, Carl, 17–18 Lars and the Real Girl (Oliver/Gillespie), 193 last common ancestor (LCA), 14 Laurel, Brenda, 27 law enforcement and information gathering, 142–143 Law of Accelerating Returns, 41, 261–264 Lawrence Livermore National Lab, the University of California at San Francisco, 125–126 The Laws of Thought (Boole), 37 Leading Futurists, 173–174 Leakey, Louis, 12 Leakey, Mary, 12 learning and AI teacher assistants, 120–121 autistic children and affective computing, 108–114 and CERTS, 114–115 Knewton and adaptive learning technology, 117–118 and robot tutors, 115–117 LeDoux, Joseph, 247 Leibniz, Gottfried Wilhelm, 36 Leonardo, 85 Levanon, Yoram, 72, 265 Levy, David, 185 “Liar!” (Asimov), 231 lie detection, 143–144 Lie to Me, 55 LIGO’s direct detection of gravitational waves, 272 limbic system, 19, 45, 205 Linden Labs, 189 LISP (1958), 37 Loebner Prize Competition in Artificial Intelligence, 141 Logic Theorist (1956), 37 loneliness scale, UCLA, 153–154 long-term potentiation (LTP), 126 Lorenz, Konrad, 187 Love and Sex with Robots (Levy), 185 Luddism, 266 M MacDorman, Karl, 97, 99 machine consciousness, 193, 270. See also consciousness and AI machine logic, 36 Machine Perception Laboratory, 114–115 “The Machine Stops” (Forster), 229 Madame Tussauds Wax Museum, 100 magnetoencephalography (MEG), 126–127 Mahaffie, John, 173–174 Mahoor, Mohammad, 113 The Man Who Tasted Shapes (Cytowick, Richard), 45 Manber, Udi, 39 Mandy, digital assistant, 3–4, 74, 161–162 Manhattan Project, 272 marketing and affective computing, 138–139 Mars Needs Moms (Breathed/Wells), 95–96 massive open online courses (MOOCs), 120–121 Matrix scenario, 262–263 The Media Equation (Nass and Reeves), 28, 50–51 Media Lab, MIT, 42, 52–53, 56–57, 61 Medtronic, 125–126 Mehrabian, Albert, 25–26 memory and emotion, 21 memory formation, 110, 115, 145 Metcalfe’s law, 40, 147 METI.
Robot Rules: Regulating Artificial Intelligence by Jacob Turner
Ada Lovelace, Affordable Care Act / Obamacare, AI winter, algorithmic trading, artificial general intelligence, Asilomar, Asilomar Conference on Recombinant DNA, autonomous vehicles, Basel III, bitcoin, blockchain, brain emulation, Clapham omnibus, cognitive dissonance, corporate governance, corporate social responsibility, correlation does not imply causation, crowdsourcing, distributed ledger, don't be evil, Donald Trump, easy for humans, difficult for computers, effective altruism, Elon Musk, financial exclusion, financial innovation, friendly fire, future of work, hive mind, Internet of things, iterative process, job automation, John Markoff, John von Neumann, Loebner Prize, medical malpractice, Nate Silver, natural language processing, nudge unit, obamacare, off grid, pattern recognition, Peace of Westphalia, race to the bottom, Ray Kurzweil, 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, Turing test, Vernor Vinge
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. The focus on gender and subterfuge in the first iteration of the test is, perhaps, not accidental. Yuval Harari, Homo Deus (London: Harvill Secker, 2016), 120. 35See, for example, the website of The Loebner Prize in Artificial Intelligence, http://www.loebner.net/Prizef/loebner-prize.html, accessed 1 June 2018. 36José Hernández-Orallo, “Beyond the Turing Test”, Journal of Logic, Language and Information, Vol. 9, No. 4 (2000), 447–466. 37“Turing Test Transcripts Reveal How Chatbot ‘Eugene’ Duped the Judges”, Coventry University, 30 June 2015, http://www.coventry.ac.uk/primary-news/turing-test-transcripts-reveal-how-chatbot-eugene-duped-the-judges/, accessed 1 June 2018. 38Various competitions are now held around the world in an attempt to find a ‘chatbot’, as conversational programs are known, which is able to pass the Imitation Game.
Army of None: Autonomous Weapons and the Future of War by Paul Scharre
active measures, Air France Flight 447, algorithmic trading, artificial general intelligence, augmented reality, automated trading system, autonomous vehicles, basic income, brain emulation, Brian Krebs, cognitive bias, computer vision, cuban missile crisis, dark matter, DARPA: Urban Challenge, DevOps, drone strike, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, facts on the ground, fault tolerance, Flash crash, Freestyle chess, friendly fire, IFF: identification friend or foe, ImageNet competition, Internet of things, Johann Wolfgang von Goethe, John Markoff, Kevin Kelly, Loebner Prize, loose coupling, Mark Zuckerberg, moral hazard, mutually assured destruction, Nate Silver, pattern recognition, Rodney Brooks, Rubik’s Cube, self-driving car, sensor fusion, South China Sea, speech recognition, Stanislav Petrov, Stephen Hawking, Steve Ballmer, Steve Wozniak, Stuxnet, superintelligent machines, Tesla Model S, The Signal and the Noise by Nate Silver, theory of mind, Turing test, universal basic income, Valery Gerasimov, Wall-E, William Langewiesche, Y2K, zero day
., Ludwig Blau, Joseph Jacobs, Judah David Eisenstein, “Golem,” JewishEncylclopedia.com, http://www.jewishencyclopedia.com/articles/6777-golem#1137. 235 “the dream of AI”: Micah Clark, interview, May 4, 2016. 235 “building human-like persons”: Ibid. 236 “Why would we expect a silica-based intelligence”: Ibid. 236 Turing test: The Loebner Prize runs the Turing test every year. While no computer has passed the test by fooling all of the judges, some programs have fooled at least one judge in the past. Tracy Staedter, “Chat-Bot Fools Judges Into Thinking It’s Human,” Seeker, June 9, 2014, https://www.seeker.com/chat-bot-fools-judges-into-thinking-its-human-1768649439.html. Every year the Loebner Prize awards a prize to the “most human” AI. You can chat with the 2016 winner, “Rose,” here: http://ec2-54-215-197-164.us-west-1.compute.amazonaws.com/speech.php. 236 AI virtual assistant called “Amy”: “Amy the Virtual Assistant Is So Human-Like, People Keep Asking It Out on Dates,” accessed June 15, 2017, https://mic.com/articles/139512/xai-amy-virtual-assistant-is-so-human-like-people-keep-asking-it-out-on-dates. 236 “If we presume an intelligent alien life”: Micah Clark, interview, May 4, 2016. 237 “any level of intelligence could in principle”: Nick Bostrom, “The Superintelligent Will: Motivation and Instrumental Rationality in Advanced Artificial Agents,” http://www.nickbostrom.com/superintelligentwill.pdf. 237 “The AI does not hate you”: Eliezer S.
Alone Together by Sherry Turkle
Albert Einstein, Columbine, 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, meta-analysis, Nicholas Carr, Norbert Wiener, Panopticon Jeremy Bentham, Ralph Waldo Emerson, Rodney Brooks, Skype, social intelligence, stem cell, technoutopianism, The Great Good Place, the medium is the message, theory of mind, Turing test, Vannevar Bush, Wall-E, women in the workforce, Year of Magical Thinking
They had overreached in their predictions for their young science. It would be another decade before Levy was bested in chess by a computer program, Deep Thought, an early version of the program that beat Gary Kasparov, the reigning chess champion in the 1990s.3 These days, Levy is the chief executive officer at a company that develops “smart” toys for children. In 2009, Levy and his team won—and this for the second time—the prestigious Loebner Prize, widely regarded as the world championship for conversational software. In this contest, Levy’s “chat bot” program was best at convincing people that they were talking to another person and not to a machine. Always impressed with Levy’s inventiveness, I found myself underwhelmed by the message of this latest book, Love and Sex with Robots.4 No tongue-in-cheek science fiction fantasy, it was reviewed without irony in the New York Times by a reporter who had just spent two weeks at the Massachusetts Institute of Technology (MIT) and wrote glowingly about its robotics culture as creating “new forms of life.”5 Love and Sex is earnest in its predictions about where people and robots will find themselves by mid-century: “Love with robots will be as normal as love with other humans, while the number of sexual acts and lovemaking positions commonly practiced between humans will be extended, as robots will teach more than is in all of the world’s published sex manuals combined.” 6 Levy argues that robots will teach us to be better friends and lovers because we will be able to practice on them.
Fox, and J. Binney, “Virtual Experiences, Physical Behaviors: The Effect of Presence on Imitation of an Eating Avatar,” PRESENCE: Teleoperators and Virtual Environments 18, no. 4: 294-303, and J. A. Fox and J. N. Bailenson, “Virtual Self-modeling: The Effects of Vicarious Reinforcement and Identification on Exercise Behaviors,” Media Psychology 12 (2009): 1-25. 7 Turkle, Life on the Screen. 8 The Loebner Prize Competition also awards a prize to the person who is most obviously a person, the person who is least confused with an artificial intelligence. See Charles Platt, “What’s It Mean to Be Human, Anyway?” Wired, May 1995, www.wired.com/wired/archive/3.04/turing_pr.html (accessed May 31, 2010). 9 Mihaly Csíkszentmihalyi, Beyond Boredom and Anxiety (San Francisco: Jossey-Bass, 2000 [1st ed. 1975]), and Natasha Schüll, Addiction by Design: Machine Gambling in Las Vegas (Princeton, NJ: Princeton University Press, forthcoming). 10 Mihaly Csíkszentmihalyi, Flow: The Psychology of Optimal Experience (New York: Harper & and Row, 1990). 11 With too much volume, of course, e-mail becomes too stressful to be relaxing.
Robots Will Steal Your Job, But That's OK: How to Survive the Economic Collapse and Be Happy by Pistono, Federico
3D printing, Albert Einstein, autonomous vehicles, bioinformatics, Buckminster Fuller, cloud computing, computer vision, correlation does not imply causation, en.wikipedia.org, epigenetics, Erik Brynjolfsson, Firefox, future of work, George Santayana, global village, Google Chrome, happiness index / gross national happiness, hedonic treadmill, illegal immigration, income inequality, information retrieval, Internet of things, invention of the printing press, jimmy wales, job automation, John Markoff, Kevin Kelly, Khan Academy, Kickstarter, knowledge worker, labor-force participation, Lao Tzu, Law of Accelerating Returns, life extension, Loebner Prize, longitudinal study, means of production, Narrative Science, natural language processing, new economy, Occupy movement, patent troll, pattern recognition, peak oil, post scarcity, QR code, race to the bottom, Ray Kurzweil, recommendation engine, RFID, Rodney Brooks, selection bias, self-driving car, slashdot, smart cities, software as a service, software is eating the world, speech recognition, Steven Pinker, strong AI, technological singularity, Turing test, Vernor Vinge, women in the workforce
At the time the plan of IBM was to rely on the computational superiority of their machine using brute force,80 crunching billions of combinations; against the intuition, memory recall and pattern recognition of the Russian chess grandmaster. Nobody believed it represented an act of intelligence of any sort, since it worked in a very mechanistic way. Boy, we have gone so far since then. The classical “Turing test approach” has been largely abandoned as a realistic research goal, and is now just an intellectual curiosity (the annual Loebner prize for realistic chattiest81), but helped spawn the two dominant themes of modern cognition and artificial intelligence: calculating probabilities and producing complex behaviour from the interaction of many small, simple processes. As of today (2012), we believe these represent more closely what the human brain does, and they have been used in a variety of real-world applications: Google’s autonomous cars, search results, recommendation systems, automated language translation, personal assistants, cybernetic computational search engines, and IBM’s newest super brain Watson.
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, corporate governance, crowdsourcing, en.wikipedia.org, Erik Brynjolfsson, estate planning, 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, Loebner Prize, Mark Zuckerberg, mortgage debt, natural language processing, Own Your Own Home, pattern recognition, Satoshi Nakamoto, school choice, Schrödinger's Cat, Second Machine Age, self-driving car, sentiment analysis, Silicon Valley, Silicon Valley startup, Skype, software as a service, The Chicago School, The Future of Employment, Turing test, 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. Loren Schweninger, Black Property Owners in the South, 1790–1915 (Champaign: University of Illinois Press, 1997), 65–66. 18.
Work in the Future The Automation Revolution-Palgrave MacMillan (2019) by Robert Skidelsky Nan Craig
3D printing, Airbnb, algorithmic trading, Amazon Web Services, anti-work, artificial general intelligence, autonomous vehicles, basic income, business cycle, cloud computing, collective bargaining, correlation does not imply causation, creative destruction, data is the new oil, David Graeber, David Ricardo: comparative advantage, deindustrialization, deskilling, disintermediation, Donald Trump, Erik Brynjolfsson, feminist movement, Frederick Winslow Taylor, future of work, gig economy, global supply chain, income inequality, informal economy, Internet of things, Jarndyce and Jarndyce, Jarndyce and Jarndyce, job automation, 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, off grid, pattern recognition, post-work, Ronald Coase, Second Machine Age, self-driving car, sharing economy, Steve Jobs, strong AI, technoutopianism, 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
So back in 2013, together with a group of researchers at our engineering sciences department in Oxford, Michael Osborne and I set out to determine the potential scope of automation in the age of machine learn- 10 Attitudes to Technology: Part 2 91 ing.1 Because the recent inroads of automation are many, we began by asking the question: in which domains do automation technologies still perform poorly despite recent advances in machine learning? Broadly speaking, we found that humans still hold the competitive advantage in three broad domains: creativity, complex social interactions, and the perception and manipulation of irregular objects. To take one example, the state-of-the-art of technology in reproducing human social interactions is best described by the Loebner Prize—a Turing test competition—where chatbots try to convince human judges that they are actually chatting with a person. Some pundits have argued that there was a breakthrough in 2014, when one chatbot actually managed to convince 30 percent of judges of it being a human. But it did so by pretending to be a 13-year-old boy speaking English as his second language. And if you think about the variety of much more complex in-person interactions many of us do in our daily jobs, like trying to persuade people, assisting and taking care of customers, managing teams, and so on, algorithms are nowhere near being capable of replacing us in those tasks.
Our Final Invention: Artificial Intelligence and the End of the Human Era by James Barrat
AI winter, AltaVista, Amazon Web Services, artificial general intelligence, Asilomar, Automated Insights, Bayesian statistics, Bernie Madoff, Bill Joy: nanobots, brain emulation, cellular automata, Chuck Templeton: OpenTable:, cloud computing, cognitive bias, commoditize, computer vision, cuban missile crisis, Daniel Kahneman / Amos Tversky, Danny Hillis, data acquisition, don't be evil, drone strike, Extropian, finite state, Flash crash, friendly AI, friendly fire, Google Glasses, Google X / Alphabet X, Isaac Newton, Jaron Lanier, John Markoff, John von Neumann, Kevin Kelly, Law of Accelerating Returns, life extension, Loebner Prize, lone genius, mutually assured destruction, natural language processing, Nicholas Carr, optical character recognition, PageRank, pattern recognition, Peter Thiel, prisoner's dilemma, Ray Kurzweil, Rodney Brooks, 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 Wozniak, strong AI, Stuxnet, 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
Once that starts, our input may be irrelevant. Second, if the AI’s cognitive architecture is derived from human brains, or from a human brain upload, it may not be as alien as purely new AI. But, there’s a vigorous debate among computer scientists whether that connection to mankind will solve problems or create them. No computer has yet passed the Turing test, though each year the controversial Loebner Prize, sponsored by philanthropist Hugh Loebner, is offered to the maker of one that does. But while the $100,000 grand prize goes unclaimed, an annual contest awards $7,000 to the creator of the “most humanlike computer.” For the last few years they’ve been chatbots—robots created to simulate conversation, with little success. Marvin Minsky, one of the founders of the field of artificial intelligence, has offered $100 to anyone who can talk Loebner into revoking his prize.
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, artificial general intelligence, Asilomar, autonomous vehicles, basic income, Benoit Mandelbrot, Bill Joy: nanobots, Buckminster Fuller, cellular automata, Claude Shannon: information theory, Daniel Kahneman / Amos Tversky, Danny Hillis, David Graeber, easy for humans, difficult for computers, Elon Musk, Eratosthenes, Ernest Rutherford, finite state, friendly AI, future of work, Geoffrey West, Santa Fe Institute, gig economy, income inequality, industrial robot, information retrieval, invention of writing, James Watt: steam engine, Johannes Kepler, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Kevin Kelly, Kickstarter, Laplace demon, Loebner Prize, market fundamentalism, Marshall McLuhan, Menlo Park, Norbert Wiener, optical character recognition, pattern recognition, personalized medicine, Picturephone, profit maximization, profit motive, RAND corporation, random walk, Ray Kurzweil, 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, technological singularity, technoutopianism, telemarketer, telerobotics, the scientific method, theory of mind, Turing machine, Turing test, universal basic income, Upton Sinclair, Von Neumann architecture, Whole Earth Catalog, Y2K, zero-sum game
Weizenbaum’s ELIZA was the pioneer example of such superficial illusion making, and it was his dismay at the ease with which his laughably simple and shallow program could persuade people they were having a serious heart-to-heart conversation that first sent him on his mission. He was right to be worried. If there is one thing we have learned from the restricted Turing Test competitions for the Loebner Prize, it is that even very intelligent people who aren’t tuned in to the possibilities and shortcuts of computer programming are readily taken in by simple tricks. The attitudes of people in AI toward these methods of dissembling at the “user interface” have ranged from contempt to celebration, with a general appreciation that the tricks are not deep but can be potent. One shift in attitude that would be very welcome is a candid acknowledgment that humanoid embellishments are false advertising—something to condemn, not applaud.
The Singularity Is Near: When Humans Transcend Biology by Ray Kurzweil
additive manufacturing, AI winter, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, anthropic principle, Any sufficiently advanced technology is indistinguishable from magic, artificial general intelligence, Asilomar, augmented reality, autonomous vehicles, Benoit Mandelbrot, Bill Joy: nanobots, bioinformatics, brain emulation, Brewster Kahle, Brownian motion, business cycle, business intelligence, c2.com, call centre, carbon-based life, cellular automata, Claude Shannon: information theory, complexity theory, conceptual framework, Conway's Game of Life, coronavirus, cosmological constant, cosmological principle, cuban missile crisis, data acquisition, Dava Sobel, David Brooks, Dean Kamen, disintermediation, double helix, Douglas Hofstadter, en.wikipedia.org, epigenetics, factory automation, friendly AI, George Gilder, Gödel, Escher, Bach, informal economy, information retrieval, invention of the telephone, invention of the telescope, invention of writing, iterative process, Jaron Lanier, Jeff Bezos, job automation, job satisfaction, John von Neumann, Kevin Kelly, Law of Accelerating Returns, life extension, lifelogging, linked data, Loebner Prize, Louis Pasteur, mandelbrot fractal, Marshall McLuhan, Mikhail Gorbachev, Mitch Kapor, mouse model, Murray Gell-Mann, mutually assured destruction, natural language processing, Network effects, new economy, Norbert Wiener, oil shale / tar sands, optical character recognition, pattern recognition, phenotype, premature optimization, randomized controlled trial, Ray Kurzweil, remote working, reversible computing, Richard Feynman, Robert Metcalfe, Rodney Brooks, scientific worldview, Search for Extraterrestrial Intelligence, selection bias, semantic web, Silicon Valley, Singularitarianism, speech recognition, statistical model, stem cell, Stephen Hawking, Stewart Brand, strong AI, superintelligent machines, technological singularity, Ted Kaczynski, telepresence, The Coming Technological Singularity, Thomas Bayes, transaction costs, Turing machine, Turing test, Vernor Vinge, Y2K, Yogi Berra
The Turing test is important not so much for its practical significance but rather because it will demarcate a crucial threshold. As I have pointed out, there is no simple means to pass a Turing test, other than to convincingly emulate the flexibility, subtlety, and suppleness of human intelligence. Having captured that capability in our technology, it will then be subject to engineering's ability to concentrate, focus, and amplify it. Variations of the Turing test have been proposed. The annual Loebner Prize contest awards a bronze prize to the chatterbot (conversational bot) best able to convince human judges that it's human.217 The criteria for winning the silver prize is based on Turing's original test, and it obviously has yet to be awarded. The gold prize is based on visual and auditory communication. In other words, the AI must have a convincing face and voice, as transmitted over a terminal, and thus it must appear to the human judge as if he or she is interacting with a real person over a videophone.
Marvin Minsky, The Society of Mind (New York: Simon & Schuster, 1988). 214. Hans Moravec, "When Will Computer Hardware Match the Human Brain?" Journal of Evolution and Technology 1 (1998). 215. Ray Kurzweil, The Age of Spiritual Machines (New York: Viking, 1999), p. 156. 216. See chapter 2, notes 22 and 23, on the International Technology Roadmap for Semiconductors. 217. "The First Turing Test," http://www.loebner.net/Prizef/loebner-prize.html. 218. Douglas R. Hofstadter, "A Coffeehouse Conversation on the Turing Test," May 1981, included in Ray Kurzweil, The Age of Intelligent Machines (Cambridge, Mass.: MIT Press, 1990), pp. 80–102, http://www.KurzweilAI.net/meme/frame.html?main=/articles/art0318.html. 219. Ray Kurzweil, "Why I Think I Will Win," and Mitch Kapor, "Why I Think I Will Win," rules: http://www.KurzweilAI.net/meme/frame.html?
The Human Age: The World Shaped by Us by Diane Ackerman
23andMe, 3D printing, additive manufacturing, airport security, Albert Einstein, augmented reality, back-to-the-land, carbon footprint, clean water, dark matter, dematerialisation, double helix, Drosophila, epigenetics, Google Earth, Google Glasses, haute cuisine, Internet of things, Loebner Prize, Louis Pasteur, Masdar, mass immigration, megacity, microbiome, nuclear winter, personalized medicine, phenotype, Ray Kurzweil, refrigerator car, Search for Extraterrestrial Intelligence, SETI@home, skunkworks, Skype, stem cell, Stewart Brand, the High Line, theory of mind, urban planning, urban renewal, Whole Earth Catalog
v=6FFd6VWIPrE. 199Some days it feels like we’re drowning in a twittering bog of information: The Twitter haiku site is but one example. The “twaikus” appear too fast to contemplate, which rather defeats the original purpose of haikus. But at 140 characters they’re a great way to let off steam, and they’re immensely popular. When Robots Weep, Who Will Comfort Them? 214“when, by the glimmer of the half-extinguished light”: Mary Shelley, Frankenstein, chapter 5. 230On September 14, 2013, the annual Loebner Prize for robots that can pass for human went to a chatbot named Mitsuku. However, it ultimately gave itself away in December with this exchange. Q: “Why am I tired after a long sleep?” A: “The reason is due to my mental model of you as a client.” 231“Can we live inside a house”: Technological inventions, such as refrigerators and refrigerated train cars, made frozen food possible, including nutritious out-of-season foods, such as frozen fruits and vegetables.
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, bioinformatics, brain emulation, combinatorial explosion, complexity theory, computer vision, conceptual framework, correlation coefficient, epigenetics, friendly AI, G4S, information retrieval, Isaac Newton, John Conway, Loebner Prize, Menlo Park, natural language processing, Occam's razor, p-value, pattern recognition, performance metric, Ray Kurzweil, Rodney Brooks, semantic web, statistical model, strong AI, theory of mind, traveling salesman, Turing machine, Turing test, Von Neumann architecture, Y2K
When we do read journals, we very rarely see the case that someone frames a hypothesis and a null hypothesis and has a statistical test to distinguish between them. We don’t have repeatable experiments because no one in the field can repeat the experiments of anyone else in the field really. We don’t have post docs, we don’t have degree programs, we don’t have a curriculum, we don’t even have an AI prize, that’s the equivalent of the Nobel prize or something. [Ben Goertzel]: There’s the Loebner prize. [Phil Goetz]: But nobody’s won it. Do we even really have a community in the way that many others sciences do? So I guess I would like to pose the question to whoever among you would choose to answer it: Have we reached the status of being a science and if not, what can we do to be more scientific? [Steve Grand]: We’ve never really been a science. AI has always been an engineering discipline.
The Book of Why: The New Science of Cause and Effect by Judea Pearl, Dana Mackenzie
affirmative action, Albert Einstein, Asilomar, Bayesian statistics, computer age, computer vision, correlation coefficient, correlation does not imply causation, Daniel Kahneman / Amos Tversky, Edmond Halley, Elon Musk, en.wikipedia.org, experimental subject, Isaac Newton, iterative process, John Snow's cholera map, Loebner Prize, loose coupling, Louis Pasteur, Menlo Park, pattern recognition, Paul Erdős, personalized medicine, Pierre-Simon Laplace, placebo effect, prisoner's dilemma, probability theory / Blaise Pascal / Pierre de Fermat, randomized controlled trial, selection bias, self-driving car, Silicon Valley, speech recognition, statistical model, Stephen Hawking, Steve Jobs, strong AI, The Design of Experiments, the scientific method, Thomas Bayes, Turing test
Turing was very confident that this was within the realm of feasibility. “I believe that in about fifty years’ time it will be possible to program computers,” he wrote, “to make them play the imitation game so well that an average interrogator will not have more than a 70 percent chance of making the right identification after five minutes of questioning.” Turing’s prediction was slightly off. Every year the Loebner Prize competition identifies the most humanlike “chatbot” in the world, with a gold medal and $100,000 offered to any program that succeeds in fooling all four judges into thinking it is human. As of 2015, in twenty-five years of competition, not a single program has fooled all the judges or even half of them. Turing didn’t just suggest the “imitation game”; he also proposed a strategy to pass it.
The Beginning of Infinity: Explanations That Transform the World by David Deutsch
agricultural Revolution, Albert Michelson, anthropic principle, artificial general intelligence, Bonfire of the Vanities, conceptual framework, cosmological principle, dark matter, David Attenborough, discovery of DNA, Douglas Hofstadter, 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, pattern recognition, Pierre-Simon Laplace, Richard Feynman, Search for Extraterrestrial Intelligence, 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
A related difficulty is that the human participant in the test might intentionally imitate a chatbot – as in the Hofstadter hoax – and so spoil the test, which is based on comparing the two. Should the rules nevertheless allow the human to do this, in order to mitigate the previous problem? Unfortunately, such subtleties are not relevant at the current state of the art. This is well illustrated by the following excerpts from the conversation with which the program Elbot won the (lesser) Loebner prize in 2008: JUDGE: do you understand the point of a turing test? ELBOT: There are some people who would not pass the Turing test themselves. Why must they inflict it on computers? JUDGE: I spose it is a little harsh ELBOT: If we robots ever had marriages they would be eternal: ‘Till rust do us part’. In that passage, Elbot’s first utterance is not a reply to the question but presumably a stock response triggered by the keywords ‘Turing test’.
The Technology Trap: Capital, Labor, and Power in the Age of Automation by Carl Benedikt Frey
"Robert Solow", 3D printing, autonomous vehicles, basic income, Bernie Sanders, Branko Milanovic, British Empire, business cycle, business process, call centre, Capital in the Twenty-First Century by Thomas Piketty, Clayton Christensen, collective bargaining, computer age, computer vision, Corn Laws, creative destruction, David Graeber, David Ricardo: comparative advantage, deindustrialization, demographic transition, desegregation, deskilling, Donald Trump, easy for humans, difficult for computers, Edward Glaeser, Elon Musk, Erik Brynjolfsson, everywhere but in the productivity statistics, factory automation, falling living standards, first square of the chessboard / second half of the chessboard, Ford paid five dollars a day, Frank Levy and Richard Murnane: The New Division of Labor, full employment, future of work, game design, Gini coefficient, Hyperloop, income inequality, income per capita, industrial cluster, industrial robot, intangible asset, interchangeable parts, Internet of things, invention of agriculture, invention of movable type, invention of the steam engine, invention of the wheel, Isaac Newton, James Hargreaves, James Watt: steam engine, job automation, job satisfaction, job-hopping, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joseph Schumpeter, Kickstarter, knowledge economy, knowledge worker, labor-force participation, labour mobility, Loebner Prize, low skilled workers, Malcom McLean invented shipping containers, manufacturing employment, mass immigration, means of production, Menlo Park, minimum wage unemployment, natural language processing, new economy, New Urbanism, Norbert Wiener, oil shock, On the Economy of Machinery and Manufactures, Pareto efficiency, pattern recognition, pink-collar, Productivity paradox, profit maximization, Renaissance Technologies, rent-seeking, rising living standards, Robert Gordon, robot derives from the Czech word robota Czech, meaning slave, Second Machine Age, secular stagnation, self-driving car, Silicon Valley, Simon Kuznets, social intelligence, speech recognition, spinning jenny, Stephen Hawking, The Future of Employment, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, Thomas Malthus, total factor productivity, trade route, Triangle Shirtwaist Factory, Turing test, union organizing, universal basic income, washing machines reduced drudgery, wealth creators, women in the workforce, working poor, zero-sum game
Because its potential applications are so vast, Michael and I began by looking at tasks that computers still perform poorly and where technological leaps have been limited in recent years. For a glimpse of the state of the art in machine social intelligence, for example, consider the Turing test, which captures the ability of an AI algorithm to communicate in a way that is indistinguishable from an actual human. The Loebner Prize is an annual Turing test competition that awards prizes to chat bots that are considered to be the most humanlike. These competitions are straightforward. A human judge holds computer-based textual interactions with both an algorithm and a human at the same time. Based on these conversations, the judge must then try to distinguish between the two. In a paper written in 2013, Michael and I noted: “Sophisticated algorithms have so far failed to convince judges about their human resemblance.”49 Yet a year later the computer program Eugene Goostman managed to convince 33 percent of the judges that it was a person.
Architects of Intelligence by Martin Ford
3D printing, agricultural Revolution, AI winter, Apple II, artificial general intelligence, Asilomar, augmented reality, autonomous vehicles, barriers to entry, basic income, Baxter: Rethink Robotics, Bayesian statistics, bitcoin, business intelligence, business process, call centre, cloud computing, cognitive bias, Colonization of Mars, computer vision, correlation does not imply causation, crowdsourcing, DARPA: Urban Challenge, deskilling, disruptive innovation, Donald Trump, Douglas Hofstadter, Elon Musk, Erik Brynjolfsson, Ernest Rutherford, Fellow of the Royal Society, Flash crash, future of work, gig economy, Google X / Alphabet X, Gödel, Escher, Bach, Hans Rosling, ImageNet competition, income inequality, industrial robot, information retrieval, job automation, John von Neumann, Law of Accelerating Returns, life extension, Loebner Prize, Mark Zuckerberg, Mars Rover, means of production, Mitch Kapor, natural language processing, new economy, optical character recognition, pattern recognition, phenotype, Productivity paradox, Ray Kurzweil, recommendation engine, Robert Gordon, Rodney Brooks, Sam Altman, self-driving car, sensor fusion, sentiment analysis, Silicon Valley, smart cities, social intelligence, speech recognition, statistical model, stealth mode startup, stem cell, Stephen Hawking, Steve Jobs, Steve Wozniak, Steven Pinker, strong AI, superintelligent machines, Ted Kaczynski, 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, zero-sum game, Zipcar
By the way, the test that I proposed is not time-limited; in fact, it is actually supposed to be extended in time. Turing’s test was also not supposed to have a time limit, but that characteristic has been frequently forgotten, in particular in various recent AI competitions. MARTIN FORD: That seems silly. People aren’t intelligent for only half an hour. It has to be for an indefinite time period to demonstrate true intelligence. I think there’s something called the Loebner Prize where Turing tests are run under certain limited conditions each year. BARBARA GROSZ: Right, and it proves what you say. It also makes clear what we learned very early on in the natural-language processing arena, which is that if you have only a fixed task with a fixed set of issues (and in this case, a fixed amount of time), then cheap hacks will always win over real intelligent processing, because you’ll just design your AI system to the test!