Automated Insights

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pages: 347 words: 97,721

Only Humans Need Apply: Winners and Losers in the Age of Smart Machines by Thomas H. Davenport, Julia Kirby

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AI winter, Andy Kessler, artificial general intelligence, asset allocation, Automated Insights, autonomous vehicles, Baxter: Rethink Robotics, business intelligence, business process, call centre, carbon-based life, Clayton Christensen, clockwork universe, conceptual framework, dark matter, David Brooks, deliberate practice, deskilling, Edward Lloyd's coffeehouse, Elon Musk, Erik Brynjolfsson, estate planning, follow your passion, Frank Levy and Richard Murnane: The New Division of Labor, Freestyle chess, game design, general-purpose programming language, 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 Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Khan Academy, knowledge worker, labor-force participation, 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, Richard Feynman, risk tolerance, Robert Shiller, Robert Shiller, Rodney Brooks, Second Machine Age, self-driving car, Silicon Valley, six sigma, Skype, 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

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.

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.

When he looked at AP’s situation, he saw several factors that suggested the potential for automation, including scarce resources, pressure on margins, and a need despite these limitations for more content. 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.”


pages: 294 words: 81,292

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

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3D printing, AI winter, Amazon Web Services, artificial general intelligence, Automated Insights, Bernie Madoff, Bill Joy: nanobots, brain emulation, cellular automata, cloud computing, cognitive bias, computer vision, cuban missile crisis, Daniel Kahneman / Amos Tversky, Danny Hillis, data acquisition, don't be evil, Extropian, finite state, Flash crash, friendly AI, friendly fire, Google Glasses, Google X / Alphabet X, Isaac Newton, Jaron Lanier, 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, traveling salesman, Turing machine, Turing test, Vernor Vinge, Watson beat the top human players on Jeopardy!, zero day

John’s shot up eight spots to number fifteen after wins against then fifteenth-ranked Villanova, 81–68 and DePaul, 76–51. Have you made your guess? Neither is any Red Smith, but just one is human. That’s the author of sample A, which appeared on an ESPN Web site. 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. All his hungry servers require is semistructured data. * * * Once you’ve started examining computational neuroscience’s results, it’s hard (at least for me) to imagine significant progress being made with AGI architectures that rely solely on cognitive science.

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.

Big Data at Work: Dispelling the Myths, Uncovering the Opportunities by Thomas H. Davenport

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Automated Insights, autonomous vehicles, bioinformatics, business intelligence, business process, call centre, chief data officer, cloud computing, data acquisition, Edward Snowden, Erik Brynjolfsson, intermodal, Internet of things, Jeff Bezos, knowledge worker, Mark Zuckerberg, 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

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.


pages: 606 words: 157,120

To Save Everything, Click Here: The Folly of Technological Solutionism by Evgeny Morozov

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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, 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, lone genius, Louis Pasteur, Mark Zuckerberg, market fundamentalism, Marshall McLuhan, Narrative Science, Nicholas Carr, packet switching, PageRank, Paul Graham, 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.


pages: 742 words: 137,937

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

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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, computer age, computer vision, conceptual framework, corporate governance, crowdsourcing, Daniel Kahneman / Amos Tversky, death of newspapers, disintermediation, Douglas Hofstadter, en.wikipedia.org, Erik Brynjolfsson, Filter Bubble, Frank Levy and Richard Murnane: The New Division of Labor, 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, lump of labour, Marshall McLuhan, Narrative Science, natural language processing, Network effects, optical character recognition, personalized medicine, pre–internet, Ray Kurzweil, Richard Feynman, Richard Feynman, Second Machine Age, self-driving car, semantic web, Skype, social web, speech recognition, spinning jenny, strong AI, supply-chain management, telepresence, 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!, young professional

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.