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Only Humans Need Apply: Winners and Losers in the Age of Smart Machines by Thomas H. Davenport, Julia Kirby
AI winter, Andy Kessler, artificial general intelligence, asset allocation, Automated Insights, autonomous vehicles, basic income, Baxter: Rethink Robotics, business intelligence, business process, call centre, carbon-based life, Clayton Christensen, clockwork universe, commoditize, conceptual framework, dark matter, David Brooks, deliberate practice, deskilling, digital map, disruptive innovation, Douglas Engelbart, Edward Lloyd's coffeehouse, Elon Musk, Erik Brynjolfsson, estate planning, fixed income, follow your passion, Frank Levy and Richard Murnane: The New Division of Labor, Freestyle chess, game design, general-purpose programming language, global pandemic, Google Glasses, Hans Lippershey, haute cuisine, income inequality, index fund, industrial robot, information retrieval, intermodal, Internet of things, inventory management, Isaac Newton, job automation, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joi Ito, Khan Academy, knowledge worker, labor-force participation, lifelogging, longitudinal study, loss aversion, Mark Zuckerberg, Narrative Science, natural language processing, Norbert Wiener, nuclear winter, pattern recognition, performance metric, Peter Thiel, precariat, quantitative trading / quantitative ﬁnance, Ray Kurzweil, Richard Feynman, risk tolerance, Robert Shiller, Robert Shiller, Rodney Brooks, Second Machine Age, self-driving car, Silicon Valley, six sigma, Skype, social intelligence, speech recognition, spinning jenny, statistical model, Stephen Hawking, Steve Jobs, Steve Wozniak, strong AI, superintelligent machines, supply-chain management, transaction costs, Tyler Cowen: Great Stagnation, Watson beat the top human players on Jeopardy!, Works Progress Administration, Zipcar
AP’s customers may be constrained for newsprint space, but there are few if any constraints on online content volume. As Robbie Allen, the CEO of the automation software vendor Automated Insights, put it, “The sign of a true innovator is someone that can look into the future and map a course from how to get from here to there. Lou understands the pressure on the publishing industry. . . . While the publishing industry isn’t known for being the most forward-looking from a technology perspective, Lou has been a shining example of how to use new technologies to help the Associated Press adapt and gain new ground in the digital world.” The testimony from Allen suggests another hallmark of step-up types: They build an ecosystem of partners that collectively makes progress, and profits from it. In fact, AP invested in Automated Insights and gained a substantial return on its investment when the vendor was acquired in 2015.
In insurance claims, for example, “auto-adjudication” can automatically evaluate and approve up to 75 percent of claims. Human claims adjusters are left to approve only the most challenging ones. 9. It involves the creation of data-based narratives. Jobs involving the narrative description of data and analysis were once the province of humans, but automated systems are already beginning to take them over. In journalism, companies like Automated Insights and Narrative Science are already creating data-intensive content. Sports and financial reporting are already at some risk, although the automation of these domains is on the margins thus far—high school and fantasy sports, and earnings reports for small companies. Other companies, like AnalytixInsight, create investment analysis narratives on more than 40,000 public companies with its CapitalCube service.
But he first introduced automation into content production in 2014 and 2015, when he was a vice president and managing editor for Entertainment, Sports, and Business News at the Associated Press (AP), which provides news content to broadcasters, newspapers, and websites around the world. Ferrara also oversaw the newsroom’s delivery of “digital products.” He led the development of several technology-based innovation projects (including user-generated content, advertising tweets, and social media), but we’ll focus here on his leadership of the automation of business and sports news for AP. AP is now using an automated story-writing tool called Wordsmith, from Automated Insights. The tool generates prose accounts of corporate earnings and sports events. The project started in 2014 and has been expanded since then; when we checked in 2015 the system was cranking out 3,000 earnings reports per quarter (versus 300 per quarter by human journalists in the recent past), with plans to get to 4,700 per quarter by the end of the year. In sports, the plan is for the system to begin generating stories soon about Division I college baseball, and Division 2 and 3 basketball and football, which will add thousands of stories a year for fans of those teams.
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!
The Washington Post, which is now owned by Jeff Bezos, uses in-house software called Heliograf that takes pure data—local election results or high school football box scores—and transforms the information into short articles that sound human written. The Associated Press uses a company called Automated Insights to automatically produce thousands of financial stories. The potential for AI journalism was entertainingly demonstrated on an episode of NPR’s Planet Money podcast that pitted Automated Insights against veteran reporter Scott Horsley. Both were given a quarterly earnings report from Denny’s and tasked with quickly generating a short article. One of their stories opened this way: “Denny’s Corporation on Monday reported first-quarter profit of 8.5 million dollars. The Spartanburg, South Carolina–based company said it had profit of 10 cents per share.”
The other article began like this: “Denny’s Corporation notched a grand slam of its own in the first quarter, earning a better-than-expected 10 cents a share as restaurant sales jumped by more than 7 percent.” The latter lede, which clearly had more panache, was crafted by Horsley. But the other opener was perfectly serviceable. If it hadn’t been presented side by side with Horsley’s work, it wouldn’t stand out as robotically generated. Even style can be digitally dialed up. Witness the millions of articles that Automated Insights produces for fantasy-sports players, transforming the statistics from their teams’ matchups into lively reports. The computer-generated articles are written with a light, sassy tone and have headlines such as “You snooze, you lose.” The faux media coverage helps fantasy-sports participants to imagine that they are presiding over actual players and teams. It’s journalism as George Plimpton and other legendary sports scribes could never have imagined it: AIs writing articles about games that took place on silicon chips instead of grassy fields.
Neil Patel, undated, https://goo.gl/jrsaqT. 212 “urinates all over Google’s model”: Dan Kaplan, “Eric Schmidt Is Right: Google’s Glory Days Are Numbered,” TechCrunch, November 6, 2011, https://goo.gl/zwKf3G. 212 “A million blue links from Google”: Rip Empson, “Gary Morgenthaler Explains Exactly How Siri Will Eat Google’s Lunch,” TechCrunch, November 9, 2011, https://goo.gl/H3W9S1. 213 In a test by the market research firm Loup Ventures: Gene Munster and Will Thompson, “Annual Digital Assistant IQ Test—Siri, Google Assistant, Alexa, Cortana,” Loup Ventures blog post, July 25, 2018, https://is.gd/VanF69. 214 A survey by the Reuters Institute: Newman, “Digital News Report: Journalism, Media, and Technology Trends and Predictions 2018.” 214 The potential for AI journalism: Stacey Vanek Smith, “An NPR Reporter Raced A Machine To Write A News Story. Who Won?” NPR’s Planet Money, May 20, 2015, https://goo.gl/ErTLYF. 215 “You snooze, you lose”: Automated Insights, undated, https://goo.gl/B9gHHj. 215 “This is about using technology to free journalists to do more”: Paul Colford, “A leap forward in quarterly earnings stories,” Associated Press, June 30, 2014, https://goo.gl/zgBn6o. 216 Two researchers at the University of Southern California: Alessandro Bessi and Emilio Ferrara, “Social bots distort the 2016 U.S. presidential election online discussion,” First Monday 21, no. 11 (November 2016), https://goo.gl/DMmnTw. 216 “Over time the hashtag moves out of the bot network”: Erin Griffith, “Pro-gun Russian Bots Flood Twitter after Parkland Shooting,” Wired, February 15, 2018, https://goo.gl/TZt854. 217 To illustrate the threat: Yuanshun Yao et al., “Automated Crowdturfing Attacks and Defenses in Online Review Systems,” Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security (September 8, 2017), 1143–58, https://goo.gl/5GrCJm. 218 “How did the Romans tell time at night?”
Squeezed: Why Our Families Can't Afford America by Alissa Quart
Affordable Care Act / Obamacare, Airbnb, Automated Insights, autonomous vehicles, barriers to entry, basic income, Bernie Sanders, business intelligence, Donald Trump, Downton Abbey, East Village, Elon Musk, full employment, future of work, gig economy, glass ceiling, haute couture, income inequality, Jaron Lanier, job automation, late capitalism, Lyft, minimum wage unemployment, moral panic, new economy, nuclear winter, obamacare, Ponzi scheme, post-work, precariat, price mechanism, rent control, ride hailing / ride sharing, school choice, sharing economy, Silicon Valley, Skype, Snapchat, surplus humans, TaskRabbit, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, union organizing, universal basic income, upwardly mobile, wages for housework, women in the workforce, working poor
Will software be able to stand up to him or any other bullying financier, especially one who denies facts? Meanwhile, sites like Automated Insights, whose very name is an oxymoron, use algorithms to generate stories in publications such as Forbes, generating one story every thirty seconds in this fashion. This process may replace writers like me who freelance for publications like Forbes. The Associated Press regularly publishes stories of companies’ quarterly earnings—“Apple Tops Street 1Q Forecasts”—without a byline, because they are written by a computerized system that has memorized the AP Stylebook rather than by a fleshand-blood reporter. (Every quarter, the AP publishes three thousand “robot”-written stories with Automated Insights, which has the unsubtle and frightening acronym AI.) The incentive for the AP is not only to save on labor costs but also to write up business news before anyone else can—literally, before a human being could—and with no misspellings.
It can’t analyze and isn’t even as good as the worst j-school students at getting a decent quote from a source (even, one would imagine, if the sources were other robots). The writing lacks specifics and the level of precision that even a mediocre reporter would be able to muster. A robot can’t spot telling details about people or events, nor can it organize information in a compelling fashion. Automated Insights reads to me like the worst reporting from any journalism school. As a student at journalism school and also at times as a professor, I feared having to use or teach the pyramid structure: the newspaper article outline for creating news stories—to which traditional newsrooms slavishly adhere—like a player piano “creates” music. Yet the software has embraced such rote and dead-eyed aspects of my profession.
Above the Law, 106 Academic tenure, 41, 59 Activism, 116, 183, 231 Adjunct Action, 58 Adjunct faculty author’s story, 48–49 Brianne Bolin’s story, 33–37, 40–46, 57, 61–62 Carla Bellamy’s story, 50–53 downward mobility of, 36–38, 41–42, 41–43, 49–50 “fair labor seal,” 54–55 pay, 34, 36–37, 41, 54 PrecariCorps, 56–58 remedies, 53–60 Advertisers, and TV, 217 Aethon, 227, 229, 238 Affordable housing, 52–53, 156–57, 200–201 Ageism, 99–100, 169, 182 Airline pilots, breastfeeding case of, 19–20 Alaska, basic income support, 242 Algorithmic journalism, 235–36 Alumni donors, and adjunct faculty pay, 55 Amazon, 197, 290n American Civil Liberties Union, 19–20 American Dream, 115, 121, 123, 150, 172 American Psychological Association (APA), 185 American Time Use Survey (ATUS), 129 American Trucking Associations, 227 Amodeo, Michael, 155, 156, 161 Andersonville, Chicago, 45 Ansanelli, Sean, 158 Antidepressants, 45 Antiheroes, 207–8, 217–21 Anti-immigration, 120, 123–24 Anxiety, 5, 45, 62 Apprentice, The (TV show), 210–11 ApprenticeshipUSA, 290n “Arc TV,” 217 Arinwine, Anthony, 152–53, 160 “Aspirational” television. See One percent TV Atlantic (magazine), 82–83, 95, 105 Augie March (Bellow), 180 Austen, Jane, 52 “Automata, The” (Hoffmann), 248 Automated Insights, 235–36 Automation, 225–48, 252 of care work, 243–47 critics of, 229–37 enthusiasts of, 229–30, 237–39 fourth camp and UBI, 240–45 in hospitals, 225–27, 229, 238–39 of journalism, 235–36 of legal profession, 106, 232–33 of nursing, 227, 228, 229, 233–35 third framework on, 239–40 of trucking, 227, 230–32 Bakersfield Californian, 197–98 Ball State University, 228 Baltimore Sinai Hospital, 239 Baraitser, Lisa, 260–61 Barbarella (film), 252 Barenberg, Mark, 182–83 “Barrel children,” 119–20 Barry, Matt, 59–160, 162–63 Barry, Nicole, 147–48, 163 Barter trade, 201–2 Baruch College, 50, 52 Baum, Devorah, 279n Beck, Richard, 75 Bellamy, Carla, 50–53 Bellow, Saul, 180 Belmont, Eamon, 1–2 Belmont, Michelle, 1–2, 36, 100, 184–86 Benns, Roderick, 256 Berdahl, Jennifer, 16 Berlant, Lauren, 39, 60 Berman, Casey, 109 Betters, Lauren, 30 Beyond Care Childcare Cooperative, 158–59 Bilingual education, 132–33 Billions (TV show), 210, 219–20, 221 Biological age, 27 Birkman Method, 179 Birth control, 27 Bischoff, Dianne, 181 Black Indian Inn, 195 Blame.
New Dark Age: Technology and the End of the Future by James Bridle
AI winter, Airbnb, Alfred Russel Wallace, Automated Insights, autonomous vehicles, back-to-the-land, Benoit Mandelbrot, Bernie Sanders, bitcoin, British Empire, Brownian motion, Buckminster Fuller, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, cognitive bias, cognitive dissonance, combinatorial explosion, computer vision, congestion charging, cryptocurrency, data is the new oil, Donald Trump, Douglas Engelbart, Douglas Engelbart, Douglas Hofstadter, drone strike, Edward Snowden, fear of failure, Flash crash, Google Earth, Haber-Bosch Process, hive mind, income inequality, informal economy, Internet of things, Isaac Newton, John von Neumann, Julian Assange, Kickstarter, late capitalism, lone genius, mandelbrot fractal, meta analysis, meta-analysis, Minecraft, mutually assured destruction, natural language processing, Network effects, oil shock, p-value, pattern recognition, peak oil, recommendation engine, road to serfdom, Robert Mercer, Ronald Reagan, self-driving car, Silicon Valley, Silicon Valley ideology, Skype, social graph, sorting algorithm, South China Sea, speech recognition, Spread Networks laid a new fibre optics cable between New York and Chicago, stem cell, Stuxnet, technoutopianism, the built environment, the scientific method, Uber for X, undersea cable, University of East Anglia, uranium enrichment, Vannevar Bush, WikiLeaks
When one haywire algorithm started placing and cancelling orders that ate up 4 per cent of all traffic in US stocks in October 2012, one commentator was moved to comment wryly that ‘the motive of the algorithm is still unclear’.30 Since 2014, writers tasked with turning out short news items for the Associated Press have had help from a new kind of journalist: an entirely automated one. AP is one of the many clients of a company called Automated Insights, whose software is capable of scanning news stories and press releases, as well as live stock tickers and price reports, in order to create human-readable summaries in AP’s house style. AP uses the service to write tens of thousands of quarterly company reports every year, a lucrative but laborious process; Yahoo, another client, generates match reports for its fantasy football service. In turn, AP started carrying more sports reports, all generated from the raw data about each game. All the stories, in place of a journalist’s byline, carry the credit: ‘This story was generated by Automated Insights.’ Each story, assembled from pieces of data, becomes another piece of data, a revenue stream, and another potential source for further stories, data, and streams.
Index Locators in bold italic represent images/pictures A AAIB (Air Accidents Investigations Branch), 188–9 ABC Trial, 189 Aberdeen Proving Ground, 28–9 acceleration, 132 AdSense, 218 Advanced Chess, 159–60 Aeroflot, 65 Aero Lease UK, 190–1 AI (artificial intelligence), 139 Air Accidents Investigations Branch (AAIB), 188–9 Airbnb, 127 Air France, 71 air loom, 208, 209, 209 al-Assad, Bashar, 55, 124 Aldrich, Richard, 189–90 algorithms about, 108, 126 reaction speed of, 123 YouTube, 217–8, 229, 232 AlphaGo software, 149, 156–8 Al-Qaeda, 212 Alterman, Boris, 158, 159 ‘Alterman Wall,’ 158 Amash-Conyers Amendment, 178 Amazon, 39, 113–8, 115, 125–7 American Coalition for Clean Coal Electricity, 64 American Meteorological Society, 26 ‘A National Infrastructure for the 21st century’ report, 59 Anderson, Chris ‘End of Theory,’ 83–4, 146 anthropocene, 203 antiquisation programme, 234 approximation, conflating with simulation, 34–5 Arimaa, 158–9 Arkin, Alan, 188 ‘the ark,’ 52–3 Army Balloon Factory, 188–9 artificial intelligence (AI), 139 AshleyMadison.com (website), 237–8 Asimov, Isaac Three Laws of Robotics, 157 Assange, Julian ‘Conspiracy as Governance,’ 183 Assistant software, 152 Associated Press, 124 ‘As We May Think’ (Bush), 23–4 Aubrey, Crispin, 189 Aurora (Robinson), 128 AutoAwesome software, 152 Automated Insights, 123–4 automated journalism, 123–4 automated trading programs, 124 automation bias, 40, 42–3, 95 aviation, 35–6 B BABYFUN TV, 225 Ballistic Research Laboratory, 28–9 Bank of England, 123 Banks, Iain M., 149–50 Barclays, 109 basic research/brute force bias, 95 Bel Geddes, Norman, 30–1 Bell, Alexander Graham, 19–20 Benjamin, Walter, 144, 156 The Task of the Translator, 147, 155–6 Berners-Lee, Conway, 78 Berners-Lee, Tim, 78–9, 81 Berry, John, 189 ‘better than the Beatles’ problem, 94 Bevan Aneurin, 111 In Place of Fear, 110 big bang, 106 big data, 84 Bilderberg Group, 241 Binney, William, 176, 180, 181 Birther movement, 206 Bitcoin, 63 ‘Black Chamber,’ 249 blast furnace, 77–8 BND, 174 Borges, Jorge Luis, 79–80 Bounce Patrol, 223 branded content, 220 Brin, Sergey, 139 Broomberg, Adam, 143 Bush, George W., 176 Bush, Vannevar ‘As We May Think,’ 23–4 Bush Differential Analyser, 27 on hypertext, 79 Bush Differential Analyser, 27 Byron “Darkness,” 201–2 C Cadwalladr, Carole, 236 calculating machines, 27 calculation p-hacking, 89–91 raw computing, 82–3 replicability, 88–9 translation algorithms, 84 Cambridge Analytica, 236 Campbell, Duncan, 189 ‘Can We Survive Technology?’
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
Sample B was written by an automated publishing platform created by Robbie Allen of Automated Insights. In one year his Durham, N.C.–based company has generated 100,000 automatically written sports articles and posted them on hundreds of Web sites devoted to specific teams (look for the trade name Statsheet). Why does the world need robot sportswriters? Allen told me that many teams were not covered by any journalists, leaving a vacuum for fans. And, AI’s completed articles could be sent to team Web sites and picked up by other sites just minutes after the game bell. Humans can’t work that fast. Allen, a former Cisco Systems Distinguished Engineer, wouldn’t tell me the “secret sauce” of his dazzling architecture. But soon, he said, Automated Insights will supply content for finance, weather, real estate, and local news.
Aboujaoude, Elias accidents AI and, see risks of artificial intelligence nuclear power plant Adaptive AI affinity analysis agent-based financial modeling “Age of Robots, The” (Moravec) Age of Spiritual Machines, The: When Computers Exceed Human Intelligence (Kurzweil) AGI, see artificial general intelligence AI, see artificial intelligence AI-Box Experiment airplane disasters Alexander, Hugh Alexander, Keith Allen, Paul Allen, Robbie Allen, Woody AM (Automatic Mathematician) Amazon Anissimov, Michael anthropomorphism apoptotic systems Apple iPad iPhone Siri Arecibo message Aristotle artificial general intelligence (AGI; human-level AI): body needed for definition of emerging from financial markets first-mover advantage in jump to ASI from; see also intelligence explosion by mind-uploading by reverse engineering human brain time and funds required to develop Turing test for artificial intelligence (AI): black box tools in definition of drives in, see drives as dual use technology emotional qualities in as entertainment examples of explosive, see intelligence explosion friendly, see Friendly AI funding for jump to AGI from Joy on risks of, see risks of artificial intelligence Singularity and, see Singularity tight coupling in utility function of virtual environments for artificial neural networks (ANNs) artificial superintelligence (ASI) anthropomorphizing gradualist view of dealing with jump from AGI to; see also intelligence explosion morality of nanotechnology and runaway Artilect War, The (de Garis) ASI, see artificial superintelligence Asilomar Guidelines ASIMO Asimov, Isaac: Three Laws of Robotics of Zeroth Law of Association for the Advancement of Artificial Intelligence (AAAI) asteroids Atkins, Brian and Sabine Automated Insights availability bias Banks, David L. Bayes, Thomas Bayesian statistics Biden, Joe biotechnology black box systems Blue Brain project Bok globules Borg, Scott Bostrom, Nick botnets Bowden, B. V. brain augmentation of, see intelligence augmentation basal ganglia in cerebral cortex in neurons in reverse engineering of synapses in uploading into computer Brautigan, Richard Brazil Brooks, Rodney Busy Child scenario Butler, Samuel CALO (Cognitive Assistant that Learns and Organizes) Carr, Nicholas cave diving Center for Applied Rationality (CFAR) Chandrashekar, Ashok chatbots chess-playing computers Deep Blue China Chinese Room Argument Cho, Seung-Hui Church, Alonso Churchill, Winston Church-Turing hypothesis Clarke, Arthur C.
Digital Disconnect: How Capitalism Is Turning the Internet Against Democracy by Robert W. McChesney
2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, access to a mobile phone, Albert Einstein, American Legislative Exchange Council, American Society of Civil Engineers: Report Card, Automated Insights, barriers to entry, Berlin Wall, business cycle, Cass Sunstein, citizen journalism, cloud computing, collaborative consumption, collective bargaining, creative destruction, crony capitalism, David Brooks, death of newspapers, declining real wages, Double Irish / Dutch Sandwich, Erik Brynjolfsson, failed state, Filter Bubble, full employment, future of journalism, George Gilder, Gini coefficient, Google Earth, income inequality, informal economy, intangible asset, invention of agriculture, invisible hand, Jaron Lanier, Jeff Bezos, jimmy wales, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, Joseph Schumpeter, Julian Assange, Kickstarter, Mark Zuckerberg, Marshall McLuhan, means of production, Metcalfe’s law, mutually assured destruction, national security letter, Nelson Mandela, Network effects, new economy, New Journalism, Nicholas Carr, Occupy movement, offshore financial centre, patent troll, Peter Thiel, plutocrats, Plutocrats, post scarcity, price mechanism, profit maximization, profit motive, QWERTY keyboard, Ralph Nader, Richard Stallman, road to serfdom, Robert Metcalfe, Saturday Night Live, sentiment analysis, Silicon Valley, single-payer health, Skype, spectrum auction, Steve Jobs, Steve Wozniak, Steven Levy, Steven Pinker, Stewart Brand, Telecommunications Act of 1996, the medium is the message, The Spirit Level, The Structural Transformation of the Public Sphere, The Wealth of Nations by Adam Smith, Thorstein Veblen, too big to fail, transfer pricing, Upton Sinclair, WikiLeaks, winner-take-all economy, yellow journalism
But the economics are such that Macpherson argues outsourcing is inevitable: “The real lesson of Journatic is that outsourcing is not going to go away.”103 As journalism becomes increasingly rote, the logical question becomes who needs human labor at all? StatSheet, a subsidiary of Automated Insights, uses algorithms to turn numerical data into narrative articles for its 418 sports websites. Automated Insights now also computer-generates ten thousand to twenty thousand articles per week for a real estate website, and the emerging computer-generated content industry is convinced that algorithms will become a key part of writing news stories in the near future. “I am sure a journalist could do a better job writing an article than a machine,” says a real estate agency CEO who contracted with Automated Insights, “but what I’m looking for is quantity at a certain quality.”104 Who knows—maybe we will someday look back at Journatic as a golden age of journalism.
See mobile apps Arab Spring, 2011, 8, 174, 234n36 Ariely, Dan, 35–36 Aristotle: Politics, 53–54 Armstrong, Tim, 189, 191 ARPAnet, 99, 103 arrest of journalists, 209 artificial scarcity, 114–15, 124, 127, 132, 187, 219, 223 artists, 10, 74 Artzt, Edwin, 146–47 Assange, Julian, 195 Associated Content, 188 AT&T, 93, 94–95, 103, 110, 112–13, 115, 119, 122, 131 cooperates with government wiretapping, 163 declines offer to control ARPAnet, 99–100 gets “the bill they wrote,” 253n60 law enforcement relations, 165 Athens (ancient Greece), 71 Automated Insights, 193 “Baby Bells,” 106, 110, 111 Bagdikian, Ben, 84, 93, 179 Baker, Dean, 211, 213, 214 Baker, Randy, 211 Baltimore, 179, 182 Baltimore Sun, 179, 274n52 Bamford, James, 161 Banks, Russell: Lost Memory of Skin, 11 banks and banking, 38–39, 41, 131, 164, 283n30 Baran, Paul, 99 Baran, Paul A., 42, 224, 227, 228 Barlow, John Perry, 81, 105 Barnes, Peter, 115 Barton, David Watts, 191 Battelle, John, 135 Bauerlein, Mark, 9 Beck, Glenn, 94 Becker, Gary S., 44 beer, marketing of, 43 Benkler, Yochai, 15, 108, 126, 173, 231 The Penguin and the Leviathan, 6–7 Berners-Lee, Tim, 103, 133–34, 134–35 Bezos, Jeff, 138 billionaires, 27–29, 30 Bliven, Bruce, 158 blogs, 196 Boeing, 163 Bogusky, Alex, 77 book publishing, 78–79, 120, 121, 122, 127–28, 138 bookselling, 131, 138 Botsman, Rachel, 15 bourgeois.
Big Data at Work: Dispelling the Myths, Uncovering the Opportunities by Thomas H. Davenport
Automated Insights, autonomous vehicles, bioinformatics, business intelligence, business process, call centre, chief data officer, cloud computing, commoditize, data acquisition, disruptive innovation, Edward Snowden, Erik Brynjolfsson, intermodal, Internet of things, Jeff Bezos, knowledge worker, lifelogging, Mark Zuckerberg, move fast and break things, move fast and break things, Narrative Science, natural language processing, Netflix Prize, New Journalism, recommendation engine, RFID, self-driving car, sentiment analysis, Silicon Valley, smart grid, smart meter, social graph, sorting algorithm, statistical model, Tesla Model S, text mining, Thomas Davenport
Of course, if the primary output of a big data analysis is an automated decision, there is no need for visualization. Computers would prefer to get their inputs in numbers, not pictures! Another possibility for the applications layer is to create an automated narrative in textual format. Users of big data often talk about “telling a story with data,” but they don’t often enough employ narrative (rather than graphic images) to do so. This approach, used by such companies as Narrative Sciences and Automated Insights, creates a story from raw data. Automated narrative was initially used by these companies to write journalistic accounts of sporting contests, but it is also being used for financial data, marketing data, and many other types. Its proponents don’t argue that it will win the Nobel Prize in Literature, but they do think such tools are quite good at telling stories built around data—in some cases, better than humans.
See also Storm Apache YARN, 171 Apple Computer, 12 application code, in big data stack, 119t, 122–123 applications, in big data stack, 119t, 124–126 Applied Predictive Technologies, 165 architecture big data orientation in, 4, 18, 20, 114, 116, 134, 163, 175, 192, 199, 200, 203, 204 data management and, 137, 185 data scientists and, 88, 185 IT functions and, 73, 76, 77f, 134 Argyros, Tasso, 140 assessment of readiness for big data, 205–209 Aster Data, 140 @WalMartLabs, 22 auto-analytics, 12 Automated Insights, 126 automated decision making, 108–109, 124 automated modeling, 118, 124 automated narratives, 125–126 automated testing, 96, 160, 164, 165 automation of existing processes in large companies, 190–193 factories with, 52 military applications using, 19 automobile industry big data applications in, 46, 56, 83 self-driving cars and, 35, 41, 42, 65, 83, 148 banking industry, 8, 9, 42t, 44, 49, 55, 61–62, 67–68, 71, 77, 95f, 108–109, 131–133, 138, 142, 143, 153, 164, 177, 179, 180, 182, 186–188, 191, 197 Bank of America, 67, 143, 185, 186–187 Bell Labs, 71, 86–87 Index.indd 218 benchmarking, 69 Bezos, Jeff, 141 Bhasin, Aditya, 187 BI Delivery and Governance, 138 big data analytics differentiated from, 3, 4t assessment of readiness for, 205–209 attributes of big data organizational culture, 147–149 awareness of term, 6 customer relationships and, 26–27 data disadvantaged organizations and, 42t, 43 definition of, 1 earlier terms for, 10, 10t embedding, 149–151 enterprise focus for, 138–139 external focus of company with, 21–22 future scenarios on transformational impact of, 31–41 historical industry use of, 42–43, 42t importance of, 2, 3–4, 30 industrial applications of, 25–26, 47 industries well suited to, 42–50 industry categories transformed by, 32 key business functions and, 50–56 lack of structure of, 1, 2, 3, 4t, 7, 8t management changes with usage of, 27–28 management perspective on, 15–18 massive amount and volume of data in, 1–2, 11 new management orientation needed toward, 18–22 new opportunities from, 22–26 organizational structure and, 26 popularity of the term, 3 problematic aspects of the term, 6–9 staying power of, 9–15 strategy for, 59–84 succeeding with, 135–152 targets for, 144–145 training programs for, 14, 104, 112, 184, 209 underachievers in, 42t, 43–44 use of term, 9 variations of choices in, 8–9, 8t vendors’ use of term, 7–8 Big Data in Big Companies (Davenport and Dyché), 113 03/12/13 2:04 PM Index 219 big data strategy, 59–84 action plan for manager in, 84 big data areas to address in, 77–79 big data initiative portfolio in, 73–76 big data objective and, 60 cost reduction in, 60–63 discovery versus production in, 70–73 internal business decision support and, 67–70 new product development and, 65–66 objectives and stages in, 75f, 76–77, 77f percentage of organizations with, 6 responsibility locus in, 76–77, 77f right speed of big data adoption in, 80 time frame for moving on, 79–84 time reduction in, 63–65 variations of choices in, 8–9, 8t big data technology.
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
You could probably cover about 1000 companies during a year, but that meant so many other companies that people might be interested in were not reported on. Journalists in the office dreaded being chosen to write these stories. They were the bane of any reporter’s existence. So there are few journalists crying over Associated Press’s decision to enlist machines to help tell these stories. Algorithms like Wordsmith, created by Automated Insights, or Narrative Science’s Quill are now helping to churn out data-driven stories that match the dry efficiency of many of the articles that humans used to have to produce for the Associated Press. Most times you will know only when you come to the bottom of the article that a machine wrote the piece. The algorithms are freeing the journalists to write about the bigger picture. Data-mining algorithms are also increasingly useful to businesses producing the numbers reported on at Associated Press.
AARON 117–18, 119, 121, 122 Adams, Douglas: The Hitchhiker’s Guide to the Galaxy 66–7, 268 adversarial algorithms 132–42, 298, 300 AIVA 229–30; Genesis 230 Alberti bass pattern 197, 197 algebra 44, 47, 65, 158–60, 158, 171, 182, 237 Algorithmic Justice League 94 algorithms 2, 5, 11, 13, 17, 21, 24; adversarial 132–42, 298, 300; art and see art; biases and blind spots 91–5; characteristics, key 46; computer vision and see computer vision; consciousness and see consciousness; dating/matching and 57–61, 58, 59, 60; first 44–7, 45, 158–9; free will and 112–13, 300, 301; games and see individual game name; Google search 47–56, 50, 51, 52, 57; language and see language; Lovelace Test and 7–8, 102–3, 219–20; mathematics and see mathematics; music and see musical composition; neural networks and see neural networks; Nobel Prize and 57; recommender 79–80, 81–91, 85, 86; reinforcement learning and 27, 96–7; spam filters and 90–1; sports and 55–6; supervised learning and 95–6, 97, 137; tabula rasa learning and 97, 98; term 46; training 89–91; unexpected consequences of 62–5 see also individual algorithm name Al-Khwarizmi, Muhammad 46, 47, 159 AlphaGo 22, 29–43, 95–6, 97–8, 131, 145, 168, 209, 219–20, 233 AlphaZero 97–8 Al Qadiri, Fatima 224 Altamira, Cave of, Spain 104, 105 Amazon (online retailer) 62, 67, 286 Amiga Power 23 Analytical Engine 1–2, 44 Android Lloyd Webber 290 Annals of Mathematics 152, 170–1, 177, 243 Appel, Kenneth 170, 174 Apple 117 Archer, Jodie 283 Argand, Jean-Robert 237 Aristophanes 165 Aristotle: The Art of Rhetoric 166 Arnold, Malcolm 231 art: AARON and 117–18, 119, 121, 122; adversarial networks and generating new 132–42, 135, 136, 137, 140; animals and 107–9; BOB (artificial life form) and 146–8; bone carvings, ancient 104–5; cave art, ancient 103–4, 156; coding the visual world 110–12; commercial considerations and 131–2; copyright ownership and 108–9; creativity and see creativity; definition of 103–7; emotional response, AI and 106–7; fractals and 113–16, 124–5; future of AI 148–9; identifying artists and waves of creativity with AI 134–9, 135, 136; mathematics and 99–103, 106, 146, 155; origins of human 103; ‘The Painting Fool’ 119–22, 200, 291; Pollock, attempts to fake a 123–6; Rembrandt, recreating 127–32; rules and 1; sale of computer generated work, first 141; visual recognition algorithms, understanding 142–5; Wundt Curve and 139–40, 140 Art Basel 141, 142, 143, 145, 151 artificial intelligence (AI): algorithms and see algorithms; art and see art; birth of 1–2, 67; computer vision and see computer vision; consciousness and see consciousness; creativity and see creativity; data, importance of 67–8; games and see individual game name; language and see language; Lovelace Test and 7–8, 102–3, 219–20; mathematics and see mathematics; music and see musical composition; neural networks and see neural networks; systems see individual system name; term 24; transformational impact of 66–7 Ascent of Man, The (TV series) 104 Ashwood, Mary 48 Associated Press 293, 294 Atari 25–8, 92, 97, 115–16, 132 Atiyah, Michael 179, 248–9 Augustus, Ron 127 Automated Insights 293 Babbage, Charles 1, 7, 65 Babylonians, Ancient 157–60, 161, 165 Bach, Carl Philipp Emanuel 189–90, 193–4; ‘Inventions by Which Six Measures of Double Counterpoint Can be Written without Knowledge of the Rules’ 193–4 Bach, Johann Sebastian 10, 185, 186–7, 189–93, 204, 205, 207, 230, 231, 299; AIVA and 230; algorithms and method of composing music 189–94, 191; The Art of Fugue 186, 198; DeepBach and 207–12, 232; Emmy and 195–6, 197, 198, 200, 201; The Musical Offering 189–94; ‘Ricercar’ 192; St John Passion 207–8 Baroque 10, 13, 138 Barreau, Pierre 230 Barreau, Vincent 230 Barry, Robert 106 Barthes, Roland 251–2 Bartók, Béla 186–7, 197, 205 Batten, Dan 234 Beatles, the 224; ‘Yesterday’ 223 Beckett, Samuel 17 Beethoven, Ludwig van 10, 41, 127, 200, 230, 244 Belamy, Edmond 141 BellKor’s Pragmatic Chaos 87–8 Berlyne, D.
When Computers Can Think: The Artificial Intelligence Singularity by Anthony Berglas, William Black, Samantha Thalind, Max Scratchmann, Michelle Estes
3D printing, AI winter, anthropic principle, artificial general intelligence, Asilomar, augmented reality, Automated Insights, autonomous vehicles, availability heuristic, blue-collar work, brain emulation, call centre, cognitive bias, combinatorial explosion, computer vision, create, read, update, delete, cuban missile crisis, David Attenborough, Elon Musk, en.wikipedia.org, epigenetics, Ernest Rutherford, factory automation, feminist movement, finite state, Flynn Effect, friendly AI, general-purpose programming language, Google Glasses, Google X / Alphabet X, Gödel, Escher, Bach, industrial robot, Isaac Newton, job automation, John von Neumann, Law of Accelerating Returns, license plate recognition, Mahatma Gandhi, mandelbrot fractal, natural language processing, Parkinson's law, patent troll, patient HM, pattern recognition, phenotype, ransomware, Ray Kurzweil, self-driving car, semantic web, Silicon Valley, Singularitarianism, Skype, sorting algorithm, speech recognition, statistical model, stem cell, Stephen Hawking, Stuxnet, superintelligent machines, technological singularity, Thomas Malthus, Turing machine, Turing test, uranium enrichment, Von Neumann architecture, Watson beat the top human players on Jeopardy!, wikimedia commons, zero day
I blork your dork. is likely to produce Why are you concerned about my dork? Or, more cleverly if dork and blork are not in its dictionary Please stop talking nonsense. Journalistic generation One commentator thought that a recent program called Automated Insights demonstrated a new level of artificial intelligence research because it could generate exciting commentary on sporting events that is indistinguishable from that written by professional journalists. Further, it can do this almost instantly, and can be used for lesser matches that would not otherwise justify the attention of a journalist. This is the type of dialog that can be generated (not actually from Automated Insights):The Reds put on a magnificent show and slaughtered the Blues 27 points to 7. This promoted the Reds to a well earned third place in the league. It will be interesting to see whether they can maintain this momentum in their upcoming match against the Greens.
Always Day One: How the Tech Titans Plan to Stay on Top Forever by Alex Kantrowitz
accounting loophole / creative accounting, Albert Einstein, AltaVista, Amazon Web Services, augmented reality, Automated Insights, autonomous vehicles, Bernie Sanders, Clayton Christensen, cloud computing, collective bargaining, computer vision, Donald Trump, drone strike, Elon Musk, Firefox, Google Chrome, hive mind, income inequality, Infrastructure as a Service, inventory management, iterative process, Jeff Bezos, job automation, Jony Ive, knowledge economy, Lyft, Mark Zuckerberg, Menlo Park, new economy, Peter Thiel, QR code, ride hailing / ride sharing, self-driving car, Silicon Valley, Skype, Snapchat, Steve Ballmer, Steve Jobs, Steve Wozniak, Tim Cook: Apple, uber lyft, wealth creators, zero-sum game
“Mark Zuckerberg Has Baby and Says He Will Give Away 99% of His Facebook Shares.” BuzzFeed News. BuzzFeed News, December 1, 2015. https://www.buzzfeednews.com/article/mathonan/mark-zuckerberg-has-baby-and-says-he-will-give-away-99-of-hi. Amazon AI tool gone bad: Dastin, Jeffrey. “Amazon Scraps Secret AI Recruiting Tool That Showed Bias Against Women.” Reuters. Thomson Reuters, October 9, 2018. https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G. J. Robert Oppenheimer: Ratcliffe, Susan. Oxford Essential Quotations. Oxford, UK: Oxford University Press, 2016. Twenty-five US federal agencies: “NITAAC Solutions Showcase: Technatomy and UI Path.” YouTube, March 29, 2019. https://youtu.be/IakpZK9q6ys. ABCDEFGHIJKLMNOPQRSTUVWXYZ INDEX The page numbers in this index refer to the printed version of this book.
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!
He was the last of the organisers of the original Dartmouth AI conference to do so, with John McCarthy having died in 2011, and both Nathaniel Rochester and Claude Shannon a decade earlier in 2001. Newspapers immediately rushed to print tributes to Minsky’s work, noting that he had ‘laid the foundation for the field of Artificial Intelligence by demonstrating the possibilities of imparting common-sense reasoning to computers’. Wired magazine, taking a different tack, decided to print an obituary to Minsky written by a news-writing AI built by the AI startup Automated Insights. It was more than serviceable. Minsky’s symbolically loaded death closed the door on the first generation of researchers who readily identified themselves as working in Artificial Intelligence. But, as the news spread through blogs and tech forums, he was considered far from a dusty relic of a bygone age. The year 2016 marks the sixtieth since Minsky and a select few other ambitious young computer scientists gathered on a New England university campus with the goal of solving machine intelligence over the course of a single summer.
The Autonomous Revolution: Reclaiming the Future We’ve Sold to Machines by William Davidow, Michael Malone
2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, agricultural Revolution, Airbnb, American Society of Civil Engineers: Report Card, Automated Insights, autonomous vehicles, basic income, bitcoin, blockchain, blue-collar work, Bob Noyce, business process, call centre, cashless society, citizen journalism, Clayton Christensen, collaborative consumption, collaborative economy, collective bargaining, creative destruction, crowdsourcing, cryptocurrency, disintermediation, disruptive innovation, distributed ledger, en.wikipedia.org, Erik Brynjolfsson, Filter Bubble, Francis Fukuyama: the end of history, Geoffrey West, Santa Fe Institute, gig economy, Gini coefficient, Hyperloop, income inequality, industrial robot, Internet of things, invention of agriculture, invention of movable type, invention of the printing press, invisible hand, Jane Jacobs, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joseph Schumpeter, license plate recognition, Lyft, Mark Zuckerberg, mass immigration, Network effects, new economy, peer-to-peer lending, QWERTY keyboard, ransomware, Richard Florida, Robert Gordon, Ronald Reagan, Second Machine Age, self-driving car, sharing economy, Shoshana Zuboff, Silicon Valley, Simon Kuznets, Snapchat, speech recognition, Stuxnet, TaskRabbit, The Death and Life of Great American Cities, The Rise and Fall of American Growth, the scientific method, trade route, Turing test, Uber and Lyft, uber lyft, universal basic income, uranium enrichment, urban planning, zero day, zero-sum game, Zipcar
“No one I know has a job anymore,” Tina Brown, the former editor of The New Yorker and The Daily Beast, observed. “They’ve got gigs” and are living “on what’s left of their 401(K)s.”26 In most cases, displaced reporters earn far less than they did when they had full-time jobs. Some reporters now find themselves in direct competition with intelligent machines that are capable of writing simple stories about sporting events and financial news. Yahoo and the Associated Press use WordSmith, produced by Automated Insights, to get the news out fast.27 The value of the work those reporters did is being set by the cost of the writing done by intelligent machines. Even though newspapers have a fraction of their former readership, everyone still gets the news. Many get it for free over the Internet (much of it, ironically, from those same dying newspapers), and it is more timely, often uses multimedia, is continuously updated, and offers links to endless quantities of supporting information for those who want to dive deeper.
The Future of the Professions: How Technology Will Transform the Work of Human Experts by Richard Susskind, Daniel Susskind
23andMe, 3D printing, additive manufacturing, AI winter, Albert Einstein, Amazon Mechanical Turk, Amazon Web Services, Andrew Keen, Atul Gawande, Automated Insights, autonomous vehicles, Big bang: deregulation of the City of London, big data - Walmart - Pop Tarts, Bill Joy: nanobots, business process, business process outsourcing, Cass Sunstein, Checklist Manifesto, Clapham omnibus, Clayton Christensen, clean water, cloud computing, commoditize, computer age, Computer Numeric Control, computer vision, conceptual framework, corporate governance, creative destruction, crowdsourcing, Daniel Kahneman / Amos Tversky, death of newspapers, disintermediation, Douglas Hofstadter, en.wikipedia.org, Erik Brynjolfsson, Filter Bubble, full employment, future of work, Google Glasses, Google X / Alphabet X, Hacker Ethic, industrial robot, informal economy, information retrieval, interchangeable parts, Internet of things, Isaac Newton, James Hargreaves, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joseph Schumpeter, Khan Academy, knowledge economy, lifelogging, lump of labour, Marshall McLuhan, Metcalfe’s law, Narrative Science, natural language processing, Network effects, optical character recognition, Paul Samuelson, personalized medicine, pre–internet, Ray Kurzweil, Richard Feynman, Second Machine Age, self-driving car, semantic web, Shoshana Zuboff, Skype, social web, speech recognition, spinning jenny, strong AI, supply-chain management, telepresence, The Future of Employment, the market place, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, transaction costs, Turing test, Watson beat the top human players on Jeopardy!, WikiLeaks, young professional
The algorithm that determines what news appears on users’ Facebook newsfeeds, for example, is in effect a computerized editor—and its editorial stance is unclear.215 As a result of these changes, some of the tasks that fall to traditional journalists, and the way they undertake those tasks, are very different. Journalists can manually sift through social media looking for breaking news or popular stories, or use computerized systems like Storyful.216 They can secure help with their copy-editing from apps like Grammarly, and with note-taking from Evernote.217 And, as noted, some tasks are no longer undertaken by people at all. In 2014 Associated Press started to use algorithms developed by Automated Insights to computerize the production of several hundred formerly handcrafted earnings reports, producing fifteen times as many as before.218 Forbes now provides similarly for earnings reports and sport, using algorithms developed by Narrative Science.219 The Los Angeles Times uses an algorithm called ‘Quakebot’ (which is currently followed by 95,600 people on Twitter) to monitor the US Geological Survey for earthquake alerts, and automatically to compose articles if an event takes place.220 Users can struggle to tell the difference.221 2.6.
To Save Everything, Click Here: The Folly of Technological Solutionism by Evgeny Morozov
3D printing, algorithmic trading, Amazon Mechanical Turk, Andrew Keen, augmented reality, Automated Insights, Berlin Wall, big data - Walmart - Pop Tarts, Buckminster Fuller, call centre, carbon footprint, Cass Sunstein, choice architecture, citizen journalism, cloud computing, cognitive bias, creative destruction, crowdsourcing, data acquisition, Dava Sobel, disintermediation, East Village, en.wikipedia.org, Fall of the Berlin Wall, Filter Bubble, Firefox, Francis Fukuyama: the end of history, frictionless, future of journalism, game design, Gary Taubes, Google Glasses, illegal immigration, income inequality, invention of the printing press, Jane Jacobs, Jean Tirole, Jeff Bezos, jimmy wales, Julian Assange, Kevin Kelly, Kickstarter, license plate recognition, lifelogging, lone genius, Louis Pasteur, Mark Zuckerberg, market fundamentalism, Marshall McLuhan, moral panic, Narrative Science, Nelson Mandela, Nicholas Carr, packet switching, PageRank, Parag Khanna, Paul Graham, peer-to-peer, Peter Singer: altruism, Peter Thiel, pets.com, placebo effect, pre–internet, Ray Kurzweil, recommendation engine, Richard Thaler, Ronald Coase, Rosa Parks, self-driving car, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, Skype, Slavoj Žižek, smart meter, social graph, social web, stakhanovite, Steve Jobs, Steven Levy, Stuxnet, technoutopianism, the built environment, The Chicago School, The Death and Life of Great American Cities, the medium is the message, The Nature of the Firm, the scientific method, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, Thomas L Friedman, transaction costs, urban decay, urban planning, urban sprawl, Vannevar Bush, WikiLeaks
Thus, the language, for example, might reflect what the site can guess about the education level of the reader (Economist-like vocabulary for the educated few; New York Post–like vocabulary for the uneducated masses). Or perhaps a story about Angelina Jolie might end with a reference to her film about Bosnia (if you are into international news) or some gossipy tidbit about her life with Brad Pitt (if you are into Hollywood affairs). Many firms—with names like Automated Insights and Narrative Science—already employ algorithms to produce stories automatically. The next logical step—and probably a very lucrative one—will be to target such stories to individual readers, giving us, essentially, a new generation of content farms that can produce stories on demand tailored for particular users. The implications of such shifts for our public life are profound: the kind of personalization described above might destroy the opportunities for solidarity and informed debate that occur when the entire polis has access to the same stories.