Nate Silver

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Deep Work: Rules for Focused Success in a Distracted World by Cal Newport

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8-hour work day, Albert Einstein, barriers to entry, business climate, Cal Newport, Capital in the Twenty-First Century by Thomas Piketty, Clayton Christensen, David Brooks, David Heinemeier Hansson, deliberate practice, Donald Knuth, Donald Trump, Downton Abbey, en.wikipedia.org, Erik Brynjolfsson, experimental subject, follow your passion, Frank Gehry, informal economy, information retrieval, Internet Archive, Jaron Lanier, knowledge worker, Mark Zuckerberg, Marshall McLuhan, Merlin Mann, Nate Silver, new economy, Nicholas Carr, popular electronics, remote working, Richard Feynman, Richard Feynman, Ruby on Rails, Silicon Valley, Silicon Valley startup, Snapchat, statistical model, the medium is the message, Watson beat the top human players on Jeopardy!, web application, winner-take-all economy, zero-sum game

Chapter 1 Information about Nate Silver’s election traffic on the New York Times website: Tracy, Marc. “Nate Silver Is a One-Man Traffic Machine for the Times.” New Republic, November 6, 2012. http://www.newrepublic.com/article/109714/nate-silvers-fivethirtyeight-blog-drawing-massive-traffic-new-york-times. Information about Nate Silver’s ESPN/ABC News deal: Allen, Mike. “How ESPN and ABC Landed Nate Silver.” Politico, July 22, 2013. http://www.politico.com/blogs/media/2013/07/how-espn-and-abc-landed-nate-silver-168888.html. Examples of concerns regarding Silver’s methodology: Davis, Sean M. “Is Nate Silver’s Value at Risk?” Daily Caller, November 1, 2012. http://dailycaller.com/2012/11/01/is-nate-silvers-value-at-risk/. Marcus, Gary, and Ernest Davis. “What Nate Silver Gets Wrong.” The New Yorker, January 25, 2013. http://www.newyorker.com/online/blogs/books/2013/01/what-nate-silver-gets-wrong.html.

The American Economic Review 71.5 (December 1981): 845–858. “Hearing a succession of mediocre singers does not add up to a single outstanding performance”: Ibid., 846. The Instagram example and its significance for labor disparities were first brought to my attention by the writing/speaking of Jaron Lanier. How to Become a Winner in the New Economy Details on Nate Silver’s tools: • Hickey, Walter. “How to Become Nate Silver in 9 Simple Steps.” Business Insider, November 14, 2012. http://www.businessinsider.com/how-nate-silver-and-fivethityeight-works-2012-11. • Silver, Nate. “IAmA Blogger for FiveThirtyEight at The New York Times. Ask Me Anything.” Reddit. http://www.reddit.com/r/IAmA/comments/166yeo/iama_blogger_for_fivethirtyeight_at_the_new_york. • “Why Use Stata.” www.stata.com/why-use-stata/. The SQL example I gave was from postgreSQL, an open source database system popular in both industry and (especially) academia.

The High-Skilled Workers Brynjolfsson and McAfee call the group personified by Nate Silver the “high-skilled” workers. Advances such as robotics and voice recognition are automating many low-skilled positions, but as these economists emphasize, “other technologies like data visualization, analytics, high speed communications, and rapid prototyping have augmented the contributions of more abstract and data-driven reasoning, increasing the values of these jobs.” In other words, those with the oracular ability to work with and tease valuable results out of increasingly complex machines will thrive. Tyler Cowen summarizes this reality more bluntly: “The key question will be: are you good at working with intelligent machines or not?” Nate Silver, of course, with his comfort in feeding data into large databases, then siphoning it out into his mysterious Monte Carlo simulations, is the epitome of the high-skilled worker.


pages: 829 words: 186,976

The Signal and the Noise: Why So Many Predictions Fail-But Some Don't by Nate Silver

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airport security, availability heuristic, Bayesian statistics, Benoit Mandelbrot, Berlin Wall, Bernie Madoff, big-box store, Black Swan, Broken windows theory, Carmen Reinhart, Claude Shannon: information theory, Climategate, Climatic Research Unit, cognitive dissonance, collapse of Lehman Brothers, collateralized debt obligation, complexity theory, computer age, correlation does not imply causation, Credit Default Swap, credit default swaps / collateralized debt obligations, cuban missile crisis, Daniel Kahneman / Amos Tversky, diversification, Donald Trump, Edmond Halley, Edward Lorenz: Chaos theory, en.wikipedia.org, equity premium, Eugene Fama: efficient market hypothesis, everywhere but in the productivity statistics, fear of failure, Fellow of the Royal Society, Freestyle chess, fudge factor, George Akerlof, haute cuisine, Henri Poincaré, high batting average, housing crisis, income per capita, index fund, Intergovernmental Panel on Climate Change (IPCC), Internet Archive, invention of the printing press, invisible hand, Isaac Newton, James Watt: steam engine, John Nash: game theory, John von Neumann, Kenneth Rogoff, knowledge economy, locking in a profit, Loma Prieta earthquake, market bubble, Mikhail Gorbachev, Moneyball by Michael Lewis explains big data, Monroe Doctrine, mortgage debt, Nate Silver, negative equity, new economy, Norbert Wiener, PageRank, pattern recognition, pets.com, Pierre-Simon Laplace, prediction markets, Productivity paradox, random walk, Richard Thaler, Robert Shiller, Robert Shiller, Rodney Brooks, Ronald Reagan, Saturday Night Live, savings glut, security theater, short selling, Skype, statistical model, Steven Pinker, The Great Moderation, The Market for Lemons, the scientific method, The Signal and the Noise by Nate Silver, The Wisdom of Crowds, Thomas Bayes, Thomas Kuhn: the structure of scientific revolutions, too big to fail, transaction costs, transfer pricing, University of East Anglia, Watson beat the top human players on Jeopardy!, wikimedia commons

“Election Results: House Big Board,” New York Times, November 2, 2010. http://elections.nytimes.com/2010/results/house/big-board. 26. Nate Silver, “A Warning on the Accuracy of Primary Polls,” FiveThirtyEight, New York Times, March 1, 2012. http://fivethirtyeight.blogs.nytimes.com/2012/03/01/a-warning-on-the-accuracy-of-primary-polls/. 27. Nate Silver, “Bill Buckner Strikes Again,” FiveThirtyEight, New York Times; September 29, 2011. http://fivethirtyeight.blogs.nytimes.com/2011/09/29/bill-buckner-strikes-again/. 28. Otherwise, you should have assigned the congressman a 100 percent chance of victory instead. 29. Matthew Dickinson, “Nate Silver Is Not a Political Scientist,” in Presidential Power: A Nonpartisan Analysis of Presidential Power, Blogs Dot Middlebury, November 1, 2010. http://blogs.middlebury.edu/presidentialpower/2010/11/01/nate-silver-is-not-a-political-scientist/. 30.

Alan Schwarz, “The Great Debate,” Baseball America, January. 7, 2005. http://www.baseballamerica.com/today/features/050107debate.html. 20. Per interview with Billy Beane. 21. Nate Silver, “What Tim Geithner Can Learn from Baseball,” Esquire, March 11, 2009. http://www.esquire.com/features/data/mlb-player-salaries-0409. 22. As a result of my original agreement in 2003 and a subsequent agreement in 2009, Baseball Prospectus now fully owns and operates PECOTA. Beginning with the 2010 season, the PECOTA forecasts reflect certain changes, improvements, and departures from my original methodology. The methods I describe herein apply to the 2003–2009 version of PECOTA specifically. 23. Nate Silver, “PECOTA Takes on the Field,” Baseball Prospectus, January 16, 2004. http://www.baseballprospectus.com/article.php?articleid=2515. 24. Nate Silver, “Lies, Damned Lies: Projection Reflection,” Baseball Prospectus, October 11, 2006. http://www.baseballprospectus.com/article.php?

Stephen’s Green, Dublin 2, Ireland (a division of Penguin Books Ltd) • Penguin Books Australia Ltd, 250 Camberwell Road, Camberwell, Victoria 3124, Australia (a division of Pearson Australia Group Pty Ltd) • Penguin Books India Pvt Ltd, 11 Community Centre, Panchsheel Park, New Delhi – 110 017, India • Penguin Group (NZ), 67 Apollo Drive, Rosedale, Auckland 0632, New Zealand (a division of Pearson New Zealand Ltd) • Penguin Books (South Africa) (Pty) Ltd, 24 Sturdee Avenue, Rosebank, Johannesburg 2196, South Africa Penguin Books Ltd, Registered Offices: 80 Strand, London WC2R 0RL, England First published in 2012 by The Penguin Press, a member of Penguin Group (USA) Inc. Copyright © Nate Silver, 2012 All rights reserved Illustration credits Figure 4-2: Courtesy of Dr. Tim Parker, University of Oxford Figure 7-1: From “1918 Influenza: The Mother of All Pandemics” by Jeffery Taubenberger and David Morens, Emerging Infectious Disease Journal, vol. 12, no. 1, January 2006, Centers for Disease Control and Prevention Figures 9-2, 9-3A, 9-3C, 9-4, 9-5, 9-6 and 9-7: By Cburnett, Wikimedia Commons Figure 12-2: Courtesy of Dr. J. Scott Armstrong, The Wharton School, University of Pennsylvania LIBRARY OF CONGRESS CATALOGING IN PUBLICATION DATA Silver, Nate. The signal and the noise : why most predictions fail but some don’t / Nate Silver. p. cm. Includes bibliographical references and index.


pages: 337 words: 86,320

Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are by Seth Stephens-Davidowitz

affirmative action, AltaVista, Amazon Mechanical Turk, Asian financial crisis, Bernie Sanders, big data - Walmart - Pop Tarts, Cass Sunstein, computer vision, correlation does not imply causation, crowdsourcing, Daniel Kahneman / Amos Tversky, desegregation, Donald Trump, Edward Glaeser, Filter Bubble, game design, happiness index / gross national happiness, income inequality, Jeff Bezos, John Snow's cholera map, Mark Zuckerberg, Nate Silver, peer-to-peer lending, Peter Thiel, price discrimination, quantitative hedge fund, Ronald Reagan, Rosa Parks, sentiment analysis, Silicon Valley, statistical model, Steve Jobs, Steven Levy, Steven Pinker, TaskRabbit, The Signal and the Noise by Nate Silver, working poor

Our research suggests that a person is significantly more likely to put the candidate they support first in a search that includes both candidates’ names. In the previous three elections, the candidate who appeared first in more searches received the most votes. More interesting, the order the candidates were searched was predictive of which way a particular state would go. The order in which candidates are searched also seems to contain information that the polls can miss. In the 2012 election between Obama and Republican Mitt Romney, Nate Silver, the virtuoso statistician and journalist, accurately predicted the result in all fifty states. However, we found that in states that listed Romney before Obama in searches most frequently, Romney actually did better than Silver had predicted. In states that most frequently listed Obama before Romney, Obama did better than Silver had predicted. This indicator could contain information that polls miss because voters are either lying to themselves or uncomfortable revealing their true preferences to pollsters.

Eight years later, they elected as president Donald J. Trump, a man who retweeted a false claim that black people are responsible for the majority of murders of white Americans, defended his supporters for roughing up a Black Lives Matters protester at one of his rallies, and hesitated in repudiating support from a former leader of the Ku Klux Klan. The same hidden racism that hurt Barack Obama helped Donald Trump. Early in the primaries, Nate Silver famously claimed that there was virtually no chance that Trump would win. As the primaries progressed and it became increasingly clear that Trump had widespread support, Silver decided to look at the data to see if he could understand what was going on. How could Trump possibly be doing so well? Silver noticed that the areas where Trump performed best made for an odd map. Trump performed well in parts of the Northeast and industrial Midwest, as well as the South.

It explains, as discussed earlier, why Obama’s vote totals in 2008 and 2012 were depressed in many regions. It also correlates with the black-white wage gap, as a team of economists recently reported. The areas that I had found make the most racist searches, in other words, underpay black people. And then there is the phenomenon of Donald Trump’s candidacy. As noted in the introduction, when Nate Silver, the polling guru, looked for the geographic variable that correlated most strongly with support in the 2016 Republican primary for Trump, he found it in the map of racism I had developed. That variable was searches for “nigger(s).” Scholars have recently put together a state-by-state measure of implicit prejudice against black people, which has enabled me to compare the effects of explicit racism, as measured by Google searches, and implicit bias.


pages: 317 words: 100,414

Superforecasting: The Art and Science of Prediction by Philip Tetlock, Dan Gardner

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Affordable Care Act / Obamacare, Any sufficiently advanced technology is indistinguishable from magic, availability heuristic, Black Swan, butterfly effect, cloud computing, cuban missile crisis, Daniel Kahneman / Amos Tversky, desegregation, drone strike, Edward Lorenz: Chaos theory, forward guidance, Freestyle chess, fundamental attribution error, germ theory of disease, hindsight bias, index fund, Jane Jacobs, Jeff Bezos, Kenneth Arrow, Mikhail Gorbachev, Mohammed Bouazizi, Nash equilibrium, Nate Silver, obamacare, pattern recognition, performance metric, Pierre-Simon Laplace, place-making, placebo effect, prediction markets, quantitative easing, random walk, randomized controlled trial, Richard Feynman, Richard Feynman, Richard Thaler, Robert Shiller, Robert Shiller, Ronald Reagan, Saturday Night Live, Silicon Valley, Skype, statistical model, stem cell, Steve Ballmer, Steve Jobs, Steven Pinker, the scientific method, The Signal and the Noise by Nate Silver, The Wisdom of Crowds, Thomas Bayes, Watson beat the top human players on Jeopardy!

They have no idea how good their forecasts are in the short, medium, or long term—and no idea how good their forecasts could become. At best, they have vague hunches. That’s because the forecast-measure-revise procedure operates only within the rarefied confines of high-tech forecasting, such as the work of macroeconomists at central banks or marketing and financial professionals in big companies or opinion poll analysts like Nate Silver.7 More often forecasts are made and then … nothing. Accuracy is seldom determined after the fact and is almost never done with sufficient regularity and rigor that conclusions can be drawn. The reason? Mostly it’s a demand-side problem: The consumers of forecasting—governments, business, and the public—don’t demand evidence of accuracy. So there is no measurement. Which means no revision. And without revision, there can be no improvement.

Consider the weather in Phoenix, Arizona. Each June, it gets very hot and sunny. A forecaster who followed a mindless rule like, “always assign 100% to hot and sunny” could get a Brier score close to 0, leaving 0.2 in the dust. Here, the right test of skill would be whether a forecaster can do better than mindlessly predicting no change. This is an underappreciated point. For example, after the 2012 presidential election, Nate Silver, Princeton’s Sam Wang, and other poll aggregators were hailed for correctly predicting all fifty state outcomes, but almost no one noted that a crude, across-the-board prediction of “no change”—if a state went Democratic or Republican in 2008, it will do the same in 2012—would have scored forty-eight out of fifty, which suggests that the many excited exclamations of “He called all fifty states!”

Aggregating the judgments of people who know a little is better, and if there are enough of them, it can produce impressive results, but aggregating the judgments of an equal number of people who know lots about lots of different things is most effective because the collective pool of information becomes much bigger. Aggregations of aggregations can also yield impressive results. A well-conducted opinion survey aggregates a lot of information about voter intentions, but combining surveys—a “poll of polls”—turns many information pools into one big pool. That’s the core of what Nate Silver, Sam Wang, and other statisticians did in the presidential election of 2012. And a poll of polls can be further aggregated with other data sources. PollyVote is a project of an academic consortium that forecasts presidential elections by aggregating diverse sources, including election polls, the judgments of a panel of political experts, and quantitative models developed by political scientists.


pages: 502 words: 107,657

Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die by Eric Siegel

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Albert Einstein, algorithmic trading, Amazon Mechanical Turk, Apple's 1984 Super Bowl advert, backtesting, Black Swan, book scanning, bounce rate, business intelligence, business process, call centre, commoditize, computer age, conceptual framework, correlation does not imply causation, crowdsourcing, dark matter, data is the new oil, en.wikipedia.org, Erik Brynjolfsson, Everything should be made as simple as possible, experimental subject, Google Glasses, happiness index / gross national happiness, job satisfaction, Johann Wolfgang von Goethe, lifelogging, Machine translation of "The spirit is willing, but the flesh is weak." to Russian and back, mass immigration, Moneyball by Michael Lewis explains big data, Nate Silver, natural language processing, Netflix Prize, Network effects, Norbert Wiener, personalized medicine, placebo effect, prediction markets, Ray Kurzweil, recommendation engine, risk-adjusted returns, Ronald Coase, Search for Extraterrestrial Intelligence, self-driving car, sentiment analysis, software as a service, speech recognition, statistical model, Steven Levy, text mining, the scientific method, The Signal and the Noise by Nate Silver, The Wisdom of Crowds, Thomas Bayes, Turing test, Watson beat the top human players on Jeopardy!, X Prize, Yogi Berra, zero-sum game

Michael Scherer, “Inside the Secret World of the Data Crunchers Who Helped Obama Win.” TIME Magazine, November 07, 2012. http://swampland.time.com/2012/11/07/inside-the-secret-world-of-quants-and-data-crunchers-who-helped-obama-win/. Colbert Nation, www.colbertnation.com. Stephen Colbert interviews Nate Silver, New York Times blogger about his book, The Signal and the Noise: Why So Many Predictions Fail—but Some Don’t. http://www.colbertnation.com/the-colbert-report-videos/420765/november-05-2012/nate-silver. Peggy Noonan, “They’ve Lost That Lovin’ Feeling.” Wall Street Journal, July 30, 2011. http://online.wsj.com/article/SB10001424053111904800304576474620336602248.html. Jack Gillum, “Mitt Romney Uses Secretive Data Mining To Identify Wealthy Donors.” Huffington Post, August 24, 2012. www.huffingtonpost.com/2012/08/24/mitt-romney-data-mining_n_1827318.html.

The bad news is that it’s actually more than half; the good news is that PA can learn to do better. A Faulty Oracle Everyone Loves The first step toward predicting the future is admitting you can’t. —Stephen Dubner, Freakonomics Radio, March 30, 2011 The “prediction paradox”: The more humility we have about our ability to make predictions, the more successful we can be in planning for the future. —Nate Silver, The Signal and the Noise: Why So Many Predictions Fail—but Some Don’t Half of what we will teach you in medical school will, by the time you are done practicing, be proved wrong. —Dr. Mehmet Oz Your resident “oracle,” PA, tells you which customers are most likely to respond. It earmarks a quarter of the entire list and says, “These folks are three times more likely to respond than average!”

However, they kept at it, squeezing every drop of potential out of their brainshare and data, right up until the final weeks before the big match. Confidence without Overconfidence Both experts and laypeople mistake more confident predictions for more accurate ones. But overconfidence is often the reason for failure. If our appreciation of uncertainty improves, our predictions can get better too. —Nate Silver, The Signal and the Noise: Why So Many Predictions Fail—but Some Don’t The trouble with the world is that the stupid are cocksure and the intelligent are full of doubt. —Bertrand Russell You got to know when to hold ‘em, know when to fold ‘em. —Don Schlitz, “The Gambler” (sung by Kenny Rogers) Jeopardy! wasn’t built for players with no self-doubt. —Chris Jones, Esquire Magazine Besides answering questions, there’s a second skill each Jeopardy!


pages: 75 words: 22,220

Occupy by Noam Chomsky

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corporate governance, corporate personhood, deindustrialization, Howard Zinn, income inequality, invisible hand, Martin Wolf, Nate Silver, Occupy movement, Plutonomy: Buying Luxury, Explaining Global Imbalances, precariat, Ralph Nader, Ronald Reagan, too big to fail, union organizing

—Greg Ruggiero April 27, 2012 * Rich Morin, “Rising Share of Americans See Conflict Between Rich and Poor,” Pew Research Center, January 11, 2012. † OccupyArrests.com posts a running total of how many Occupy protesters have been arrested since September 17, 2011, and when and where in the United States the arrests took place. ‡ Nate Silver, “Why Obama Will Embrace the 99 Percent,” New York Times, published online February 15, 2012. http://www.nytimes.com/2012/02/19/magazine/nate-silver-obama-reelection-chances.html?hp § Dan Barry, “In Fuel Oil Country, Cold That Cuts to the Heart,” New York Times, February 3, 2012. ¶ Charles M. Blow, “Romney, the Rich and the Rest,” New York Times, February 3, 2012, citing Richard Kogan and Paul N. Van de Water, “Romney Budget Proposals Would Require Massive Cuts in Medicare, Medicaid, and Other Nondefense Spending,” Center on Budget and Policy Priorities, revised February 16, 2012. ** Allison Kilkenny, “Report: 26 Arrested at Occupy Foreclosure Auction Blockade January 27, 2012, In These Times. †† Bailey McCann, “Cities, states pass resolutions against corporate personhood,” January 4, 2012, CivSource. http://civsourceonline.com/2012/01/04/cities-states-pass-resolutions-against-corporate-personhood/ ‡‡ Emily Ramshaw and Jay Root, “A New Rick Perry Shows Up to GOP Debate,” The Texas Tribune, October 18, 2011.


pages: 296 words: 82,501

Stuffocation by James Wallman

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3D printing, Airbnb, back-to-the-land, Berlin Wall, big-box store, Black Swan, BRICs, carbon footprint, Cass Sunstein, clean water, collaborative consumption, commoditize, creative destruction, crowdsourcing, David Brooks, Fall of the Berlin Wall, happiness index / gross national happiness, high net worth, income inequality, Intergovernmental Panel on Climate Change (IPCC), James Hargreaves, Joseph Schumpeter, Kitchen Debate, Martin Wolf, mass immigration, McMansion, means of production, Nate Silver, Occupy movement, Paul Samuelson, post-industrial society, Post-materialism, post-materialism, Richard Florida, Richard Thaler, sharing economy, Silicon Valley, Simon Kuznets, Skype, spinning jenny, The Signal and the Noise by Nate Silver, Thorstein Veblen, Tyler Cowen: Great Stagnation, World Values Survey, Zipcar

Using the Past to Tell the Future I am indebted to three sources for this section: Peter N Stearns, “Why Study History?”, American Historical Association, 1998; Nate Silver, The Signal and the Noise (New York: Allen Lane, 2012); and Rob Hyndman, “Why are some things easier to forecast than others?”, 18 September 2012, on his blog, Hyndsight (www.robjhyndman.com/hyndsight). “In the 1970s, the high temperature forecasts were wrong, on average, by about six degrees. Today they are only wrong by half that amount, three degrees. When hurricane forecasters predicted where a hurricane would hit land in the 1980s they were usually out by 350 miles. Today, their predictions are only wrong by 100 miles.” If you’re not ready – yet – to take on all of Nate Silver’s The Signal and the Noise, read Nate Silver, “The Weatherman Is Not a Moron”, New York Times, 7 September 2012. The Farm Where the Corn Did Not Grow Tall For Everett Rogers’s version of his life, read Everett M Rogers, The Fourteenth Paw (Singapore: Asian Media Information and Communication Centre, 2008).


pages: 296 words: 78,112

Devil's Bargain: Steve Bannon, Donald Trump, and the Storming of the Presidency by Joshua Green

4chan, Affordable Care Act / Obamacare, Ayatollah Khomeini, Bernie Sanders, business climate, centre right, collateralized debt obligation, conceptual framework, corporate raider, crony capitalism, currency manipulation / currency intervention, Donald Trump, Fractional reserve banking, Goldman Sachs: Vampire Squid, Gordon Gekko, guest worker program, illegal immigration, immigration reform, liberation theology, low skilled workers, Nate Silver, nuclear winter, obamacare, Peace of Westphalia, Peter Thiel, quantitative hedge fund, Renaissance Technologies, Ronald Reagan, Silicon Valley, speech recognition, urban planning

“We’re gonna go buck wild”: Joshua Green, “Trump to Intensify Attacks on Clinton over Husband’s Accusers,” Bloomberg.com, October 12, 2016, www.bloomberg.com/politics/articles/2016-10-12/trump-takes-a-back-to-the-future-focus-on-bill-clinton-s-women. “Is the Presidential Race Tightening?”: Nate Silver, “Election Update: Is the Presidential Race Tightening?,” FiveThirtyEight, New York Times, October 26, 2016, fivethirtyeight.com/features/election-update-is-the-presidential-race-tightening/. “Yes, Donald Trump Has a Path to Victory”: Nate Silver, “Election Update: Yes, Donald Trump Has a Path to Victory,” FiveThirtyEight, New York Times, November 1, 2016, fivethirtyeight.com/features/election-update-yes-donald-trump-has-a-path-to-victory/. Chapter Eleven: “The FBI Has Learned of the Existence . . .” “We’re already seeing the effects”: “Hillary Clinton Speaks to Estimated Crowd of 10,000+,” AZCentral.com, November 2, 2016, www.azcentral.com/story/news/politics/elections/2016/11/02/hillary-clinton-arizona-asu-presidential-campaign-rally/93143352/, “Arizona ain’t an indulgence”: Brian Fallon, Twitter post, October 29, 2016, 9:41 a.m., twitter.com/brianefallon/status/792043601463283713.

Whether it was a result of Trump’s apocalyptic turn, disgust at the Clintons, or simply accuser fatigue—it was likely a combination of all three—the pattern of slippage in the wake of negative news was less pronounced in Trump’s internal surveys in mid-October. Overall, he still trailed. But the data were noisy. In some states (Indiana, New Hampshire, Arizona) his support eroded, but in others (Florida, Ohio, Michigan) it actually improved. When Trump held his own at the third and final debate on October 19, the numbers inched up further. The movement was clear enough that Nate Silver and other statistical mavens began to take note of it. “Is the Presidential Race Tightening?” he asked in the title of an October 26 article. Citing Trump’s rising favorability numbers among Republicans and red-state trend lines, he cautiously concluded that probably it was. By November 1, he had no doubt. “Yes, Donald Trump Has a Path to Victory” read the headline for his column that day, in which he noted that Clinton’s lead in national polls had shrunk from seven points in mid-October down to three or four points.


pages: 265 words: 74,941

The Great Reset: How the Post-Crash Economy Will Change the Way We Live and Work by Richard Florida

banking crisis, big-box store, blue-collar work, car-free, carbon footprint, collapse of Lehman Brothers, congestion charging, creative destruction, deskilling, edge city, Edward Glaeser, falling living standards, financial innovation, Ford paid five dollars a day, high net worth, Home mortgage interest deduction, housing crisis, if you build it, they will come, income inequality, indoor plumbing, interchangeable parts, invention of the telephone, Jane Jacobs, Joseph Schumpeter, knowledge economy, labour mobility, low skilled workers, manufacturing employment, McMansion, Menlo Park, Nate Silver, New Economic Geography, new economy, New Urbanism, oil shock, Own Your Own Home, pattern recognition, peak oil, Ponzi scheme, post-industrial society, postindustrial economy, reserve currency, Richard Florida, Robert Shiller, Robert Shiller, secular stagnation, Silicon Valley, Silicon Valley startup, sovereign wealth fund, the built environment, The Wealth of Nations by Adam Smith, Thomas L Friedman, total factor productivity, urban decay, urban planning, urban renewal, white flight, young professional, Zipcar

Christopher Leinberger, “Car Free in America/Bottom Line: It’s Cheaper,” New York Times, online symposium, May 12, 2009, retrieved from http://roomfordebate.blogs.nytimes.com/2009/05/12/carless-in-america/?hp 14. Yuri Kageyama, “Car-Free: In Japan, That’s How a Generation Rolls,” Associated Press, January 6, 2009. 15. Rich Morin and Paul Taylor, “Luxury or Necessity? The Public Makes a U-Turn,” Pew Research Center, April 23, 2009, retrieved from http://pewsocialtrends.org/pubs/733/luxury-necessity-recession-era-reevaluations. 16. Nate Silver, “The End of Car Culture,” Esquire, May 6, 2009, retrieved from www.esquire.com/features/data/nate-silver-car-culture-stats-0609. 17. Martin Zimmerman, “Rebel without a Car?” Los Angeles Times, October 8, 2009, retrieved from http://latimesblogs.latimes.com/uptospeed/2009/10/james-dean-.html. 18. Micheline Maynard, “Is Happiness Still That New Car Smell?” 19. Felix Salmon, “Chart of the Day: Necessity,” Reuters (blog), April 28, 2009. 20. John Seabrook, Nobrow: The Culture of Marketing, the Marketing of Culture (New York: Vintage, 2001). 21.

The highest-ranked necessity was a car: 88 percent of people surveyed named it as a necessity.15 That may seem like a lot, but in a society where there are two cars or more for every family and where suburban life literally requires a car to accomplish life’s most basic tasks, 12 percent of people believing that it’s no longer a necessity seems like a substantial number. The statistics guru Nate Silver, writing in Esquire, says there is hard evidence that America’s once-great car culture has peaked. Silver performed a statistical analysis to show how much Americans drive based on gas prices and unemployment. He then graphed the results from 1980 to 2009. “Americans should have driven slightly more in January 2009 than they had a year earlier,” he found, pointing to sharply lower gas prices as the overriding factor.


pages: 396 words: 117,149

The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World by Pedro Domingos

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3D printing, Albert Einstein, Amazon Mechanical Turk, Arthur Eddington, basic income, Bayesian statistics, Benoit Mandelbrot, bioinformatics, Black Swan, Brownian motion, cellular automata, Claude Shannon: information theory, combinatorial explosion, computer vision, constrained optimization, correlation does not imply causation, creative destruction, crowdsourcing, Danny Hillis, data is the new oil, double helix, Douglas Hofstadter, Erik Brynjolfsson, experimental subject, Filter Bubble, future of work, global village, Google Glasses, Gödel, Escher, Bach, information retrieval, job automation, John Markoff, John Snow's cholera map, John von Neumann, Joseph Schumpeter, Kevin Kelly, lone genius, mandelbrot fractal, Mark Zuckerberg, Moneyball by Michael Lewis explains big data, Narrative Science, Nate Silver, natural language processing, Netflix Prize, Network effects, NP-complete, off grid, P = NP, PageRank, pattern recognition, phenotype, planetary scale, pre–internet, random walk, Ray Kurzweil, recommendation engine, Richard Feynman, Richard Feynman, Second Machine Age, self-driving car, Silicon Valley, speech recognition, statistical model, Stephen Hawking, Steven Levy, Steven Pinker, superintelligent machines, the scientific method, The Signal and the Noise by Nate Silver, theory of mind, Thomas Bayes, transaction costs, Turing machine, Turing test, Vernor Vinge, Watson beat the top human players on Jeopardy!, white flight, zero-sum game

In politics, as in business and war, there is nothing worse than seeing your opponent make moves that you don’t understand and don’t know what to do about until it’s too late. That’s what happened to the Romney campaign. They could see the other side buying ads in particular cable stations in particular towns but couldn’t tell why; their crystal ball was too fuzzy. In the end, Obama won every battleground state save North Carolina and by larger margins than even the most accurate pollsters had predicted. The most accurate pollsters, in turn, were the ones (like Nate Silver) who used the most sophisticated prediction techniques; they were less accurate than the Obama campaign because they had fewer resources. But they were a lot more accurate than the traditional pundits, whose predictions were based on their expertise. You might think the 2012 election was a fluke: most elections are not close enough for machine learning to be the deciding factor. But machine learning will cause more elections to be close in the future.

Either way, to obtain a learner’s prediction for a given training example, we must first apply it to the original training set excluding that example and use the resulting classifier—otherwise the committee risks being dominated by learners that overfit, since they can predict the correct class just by remembering it. The Netflix Prize winner used metalearning to combine hundreds of different learners. Watson uses it to choose its final answer from the available candidates. Nate Silver combines polls in a similar way to predict election results. This type of metalearning is called stacking and is the brainchild of David Wolpert, whom we met in Chapter 3 as the author of the “no free lunch” theorem. An even simpler metalearner is bagging, invented by the statistician Leo Breiman. Bagging generates random variations of the training set by resampling, applies the same learner to each one, and combines the results by voting.

“Machine learning in drug discovery and development,”* by Niki Wale (Drug Development Research, 2001), gives an overview of just that. Adam, the robot scientist, is described in “The automation of science,” by Ross King et al. (Science, 2009). Sasha Issenberg’s The Victory Lab (Broadway Books, 2012) dissects the use of data analysis in politics. “How President Obama’s campaign used big data to rally individual votes,” by the same author (MIT Technology Review, 2013), tells the story of its greatest success to date. Nate Silver’s The Signal and the Noise (Penguin Press, 2012) has a chapter on his poll aggregation method. Robot warfare is the theme of P. W. Singer’s Wired for War (Penguin, 2009). Cyber War, by Richard Clarke and Robert Knake (Ecco, 2012), sounds the alarm on cyberwar. My work on combining machine learning with game theory to defeat adversaries, which started as a class project, is described in “Adversarial classification,”* by Nilesh Dalvi et al.


pages: 230 words: 61,702

The Internet of Us: Knowing More and Understanding Less in the Age of Big Data by Michael P. Lynch

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Affordable Care Act / Obamacare, Amazon Mechanical Turk, big data - Walmart - Pop Tarts, bitcoin, Cass Sunstein, Claude Shannon: information theory, crowdsourcing, Edward Snowden, Firefox, Google Glasses, hive mind, income inequality, Internet of things, John von Neumann, meta analysis, meta-analysis, Nate Silver, new economy, patient HM, prediction markets, RFID, sharing economy, Steve Jobs, Steven Levy, the scientific method, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, WikiLeaks

Arguably the insiders’ information was better, and their take on it more legally sophisticated, than that of the larger crowd. In this sort of case, the larger crowd is not the one you want to listen to. One might think the same goes for predicting something like the success of medical surgery. Unless the crowd has the same information and training as the relevant experts, it is not clear that they have wisdom to impart. As Leonhardt’s colleague Nate Silver noted during the final run-up to the 2012 election, such markets may contain more or less sophisticated participants, and the more sophisticated the average participant, the more other sophisticated participants tend to trust it. Moreover, when a given market is highly cited in the press, “that opens up the possibility that someone could place a wager on [a candidate] in order to influence the news media’s perceptions about which candidate has the momentum.”10 If so, the market may not be reflecting or mapping voter opinion but helping to determine it.

After all, the interviewer example presumes that the tacit commitment in question is itself a product of the individuals’ beliefs. If so, then perhaps the best we can say is that what we can loosely call the group’s implicit commitment “supervenes” or is a product of the individuals’ commitments. 8. Surowiecki, The Wisdom of Crowds, xii. 9. David Leonhardt, “When the Crowd Isn’t Wise,” New York Times, July 7, 2012. 10. Nate Silver, “The Virtues and Vices of Election Prediction Markets,” New York Times, October 24, 2012. 11. I was helped to see these points in discussions with Sandy Goldberg and Nate Sheff. The example in the text is similar to that in Goldberg, “The Division of Epistemic Labor,” 117. 12. Weinberger, Too Big to Know, 21. 13. Descartes, Meditations, 103. 14. Weinberger, Too Big to Know, 23. 15. Sosa, Reflective Knowledge, chs. 7 and 8.. 16.


pages: 304 words: 82,395

Big Data: A Revolution That Will Transform How We Live, Work, and Think by Viktor Mayer-Schonberger, Kenneth Cukier

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23andMe, Affordable Care Act / Obamacare, airport security, AltaVista, barriers to entry, Berlin Wall, big data - Walmart - Pop Tarts, Black Swan, book scanning, business intelligence, business process, call centre, cloud computing, computer age, correlation does not imply causation, dark matter, double entry bookkeeping, Eratosthenes, Erik Brynjolfsson, game design, IBM and the Holocaust, index card, informal economy, intangible asset, Internet of things, invention of the printing press, Jeff Bezos, lifelogging, Louis Pasteur, Mark Zuckerberg, Menlo Park, Moneyball by Michael Lewis explains big data, Nate Silver, natural language processing, Netflix Prize, Network effects, obamacare, optical character recognition, PageRank, performance metric, Peter Thiel, Post-materialism, post-materialism, random walk, recommendation engine, self-driving car, sentiment analysis, Silicon Valley, Silicon Valley startup, smart grid, smart meter, social graph, speech recognition, Steve Jobs, Steven Levy, the scientific method, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, Turing test, Watson beat the top human players on Jeopardy!

Its accuracy depends on ensuring randomness when collecting the sample data, but achieving such randomness is tricky. Systematic biases in the way the data is collected can lead to the extrapolated results being very wrong. There are echoes of such problems in election polling using landline phones. The sample is biased against people who only use cell-phones (who are younger and more liberal), as the statistician Nate Silver has pointed out. This has resulted in incorrect election predictions. In the 2008 presidential election between Barack Obama and John McCain, the major polling organizations of Gallup, Pew, and ABC/Washington Post found differences of between one and three percentage points when they polled with and without adjusting for cellphone users—a hefty margin considering the tightness of the race. Most troublingly, random sampling doesn’t scale easily to include subcategories, as breaking the results down into smaller and smaller subgroups increases the possibility of erroneous predictions.

Neyman’s famous paper is Jerzy Neyman, “On the Two Different Aspects of the Representative Method: The Method of Stratified Sampling and the Method of Purposive Selection,” Journal of the Royal Statistical Society 97, no. 4 (1934), pp. 558–625. A sample of 1,100 observations is sufficient—Earl Babbie, Practice of Social Research (12th ed. 2010), pp. 204–207. [>] The cellphone effect—“Estimating the Cellphone Effect,” September 20, 2008 (http://www.fivethirtyeight.com/2008/09/estimating-cellphone-effect-22-points.html); for more on polling biases and other statistical insights see Nate Silver, The Signal and the Noise: Why So Many Predictions Fail—But Some Don’t (Penguin, 2012). [>] Steve Jobs’s gene sequencing—Walter Isaacson, Steve Jobs (Simon and Schuster, 2011), pp. 550–551. [>] Google Flu Trends predicting to city level—Dugas et al., “Google Flu Trends.” Etzioni on temporal data—Interview by Cukier, October 2011. [>] John Kunze quotation—Jonathan Rosenthal, “Special Report: International Banking,” The Economist, May 19, 2012, pp. 7–8.


pages: 293 words: 81,183

Doing Good Better: How Effective Altruism Can Help You Make a Difference by William MacAskill

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barriers to entry, basic income, Black Swan, Branko Milanovic, Cal Newport, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, clean water, corporate social responsibility, correlation does not imply causation, Daniel Kahneman / Amos Tversky, David Brooks, effective altruism, en.wikipedia.org, end world poverty, experimental subject, follow your passion, food miles, immigration reform, income inequality, index fund, Intergovernmental Panel on Climate Change (IPCC), Isaac Newton, job automation, job satisfaction, labour mobility, Lean Startup, M-Pesa, mass immigration, meta analysis, meta-analysis, microcredit, Nate Silver, Peter Singer: altruism, purchasing power parity, quantitative trading / quantitative finance, randomized controlled trial, self-driving car, Skype, Stanislav Petrov, Steve Jobs, Steve Wozniak, Steven Pinker, The Future of Employment, The Wealth of Nations by Adam Smith, universal basic income, women in the workforce

Just about anything you do with your time would be more productive. Given the concept of expected value, however, Levitt’s reasoning is too quick. We can’t just say that the chance of affecting the outcome by voting is so small as to be negligible. We need to work out how large the benefit would be if we did indeed affect the outcome. Luckily, some statisticians have done the hard work for us, including political pundit extraordinaire Nate Silver, who correctly predicted the winner of the 2012 election in all fifty states and the District of Columbia. Along with Columbia University professor of statistics Andrew Gelman and Berkeley professor of law Aaron Edlin, Silver calculated the odds of an individual vote swaying the outcome of the 2008 presidential election and found that, on average, a voter had approximately a one-in-sixty-million chance of affecting the outcome—small odds to be sure.

Hsee, and Ned Welch, “Risk as Feelings,” Psychological Bulletin 127, no. 2 (March 2001), 267–86. “Nobody in their right mind”: “Your FREAK-quently asked questions, answered,” Freakonomics (blog), January 20, 2011, http://freakonomics.com/2011/01/20/freakonomics-radio-your-freak-quently-asked-questions-answered/. the odds of an individual vote swaying the outcome of the 2008 presidential election: Andrew Gelman, Nate Silver, and Aaron Edlin, “What Is the Probability Your Vote Will Make a Difference?” Economic Inquiry 50, no. 2 (April 2012), 321–6. The authors reached this estimate by using election forecasts to calculate the probability that (1) a given state is necessary for an electoral college to win, and that (2) the election for that state is exactly tied—the two quantities that jointly determine whether a single vote is decisive in a US presidential election.


pages: 327 words: 88,121

The Vanishing Neighbor: The Transformation of American Community by Marc J. Dunkelman

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Affordable Care Act / Obamacare, Albert Einstein, assortative mating, Berlin Wall, big-box store, blue-collar work, Bretton Woods, Broken windows theory, call centre, clean water, cuban missile crisis, dark matter, David Brooks, delayed gratification, double helix, Downton Abbey, Edward Glaeser, Fall of the Berlin Wall, Filter Bubble, Francis Fukuyama: the end of history, George Santayana, Gini coefficient, glass ceiling, global supply chain, global village, helicopter parent, if you build it, they will come, impulse control, income inequality, invention of movable type, Jane Jacobs, John Markoff, Khyber Pass, Louis Pasteur, Marshall McLuhan, Martin Wolf, McMansion, Nate Silver, Nicholas Carr, obamacare, Occupy movement, Peter Thiel, post-industrial society, Richard Florida, rolodex, Saturday Night Live, Silicon Valley, Skype, Steve Jobs, telemarketer, The Chicago School, The Death and Life of Great American Cities, the medium is the message, Thomas L Friedman, Tyler Cowen: Great Stagnation, urban decay, urban planning, Walter Mischel, War on Poverty, women in the workforce, World Values Survey, zero-sum game

Viewed at the time as an intellectual successor to Riesman’s wide-ranging interest in broad social relations, Bowling Alone managed nevertheless to be a sterling example of the more contemporary academic sensibility. Moreover, all sorts of interesting conclusions have been gleaned since researchers began to apply data-centered tools to softer disciplines. Just a few years ago, for example, Freakonomics applied the tools of statistics to realms traditionally held outside the main of economic studies—and to great effect.14 More recently, new, sophisticated models and data sets have propelled authors like Nate Silver to international fame, predicting both sporting outcomes and, famously, the outcome of the 2012 presidential election.15 But that new emphasis has orphaned some of the questions earlier generations asked. There are, after all, aspects of our lives that elude rigorous data analysis. There’s no way to measure numerically how Americans balance the divergent impulses toward inner-directedness and other-directedness, or whether they’re more or less driven to conform to the expectations of each varied social environment.

Dan Clawson (Amherst: University of Massachusetts Press, 1998), 19–27. 9Riesman, 1961 introduction to The Lonely Crowd, xlii. 10Riesman, The Lonely Crowd, 24–25. 11Charles McGrath, “Big Thinkster,” New York Times Magazine, December 29, 2002. 12“Interview with Malcolm Gladwell,” Charlie Rose, December 3, 2013. 13McGrath, “Big Thinkster.” 14Steven D. Levitt and Stephen J. Dubner, Freakonomics: A Rogue Economist Explores the Hidden Side of Everything (New York: William Morrow, 2005). 15Chris Cillizza, “Best year in Washington: Nate Silver,” Washington Post, December 28, 2012. 16http://espn.go.com/nba/salaries/_/year/2011. 17Walter Isaacson, Steve Jobs (New York: Simon & Schuster, 2011). 18Daniel Kahneman, Thinking Fast and Slow (New York: Farrar, Straus and Giroux, 2011). Chapter 2: The Third Wave 1John B. Judis, “Newt’s not-so-weird gurus,” New Republic, October 9, 1995. 2http://www.alvintoffler.net/?fa=biospartnership. 3Nathan Gardels, “Lunch with the FT: He has seen the future,” Financial Times, August 19, 2006. 4Alvin Toffler, The Third Wave (New York: Bantam Books, 1981), 9–11. 5http://www.presidency.ucsb.edu/ws/?


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Deep Thinking: Where Machine Intelligence Ends and Human Creativity Begins by Garry Kasparov

3D printing, Ada Lovelace, AI winter, Albert Einstein, AltaVista, barriers to entry, Berlin Wall, business process, call centre, clean water, computer age, Daniel Kahneman / Amos Tversky, David Brooks, Donald Trump, Douglas Hofstadter, Drosophila, Elon Musk, Erik Brynjolfsson, factory automation, Freestyle chess, Gödel, Escher, Bach, job automation, Leonard Kleinrock, Mikhail Gorbachev, Nate Silver, Norbert Wiener, packet switching, pattern recognition, Ray Kurzweil, Richard Feynman, Richard Feynman, rising living standards, rolodex, Second Machine Age, self-driving car, Silicon Valley, Silicon Valley startup, Skype, speech recognition, stem cell, Stephen Hawking, Steven Pinker, technological singularity, The Coming Technological Singularity, The Signal and the Noise by Nate Silver, Turing test, Vernor Vinge, Watson beat the top human players on Jeopardy!, zero-sum game

This hypothesis was proposed by Murray Campbell at least as early as Monty Newborn’s 2002 book on Deep Blue. The punch line to his theory was that Deep Blue’s mysterious move wasn’t profound at all; it was a blunder and the result of a yet another bug. Per Campbell and Hsu, the move was “random,” the result of a known bug they had failed to kill before the match began. This tale acquired new life when election analyst Nate Silver used it as the centerpiece for an entire chapter of his 2012 book, The Signal and the Noise. The narrative suggested by Frederic and spread by Campbell was irresistible: Kasparov lost to Deep Blue because of a bug! Writes Silver, “The bug was anything but unfortunate for Deep Blue: it was likely what allowed the computer to beat Kasparov.” TIME, Wired, and other outlets ran with breathless variations on this theme, each story containing more errors about chess and more silly assumptions about my mental state than the last.

I will not repeat here the stream of profanities in Russian, English, and languages not yet invented that escaped my lips when I first read that paragraph. What in the hell was this? Two paragraphs after Illescas says IBM had hired Russian speakers to spy on me, he says the team entered this critical line into Deep Blue’s book that morning? An obscure variation that I had only discussed with my team in the privacy of our suite at the Plaza Hotel that week in New York? I’m no Nate Silver, but the odds of winning the lottery are quite attractive in comparison to those of the Deep Blue team entering a specific variation I had never played before in my life into the computer’s book on the very same day it appeared on the board in the final game. And not only preparing the machine for the 4..Nd7 Caro-Kann—even during my brief dalliance with the Caro-Kann as a fifteen-year-old I played the 4..Bf5 line exclusively—but also forcing it to play 8.Nxe6 and doing this despite generally giving Deep Blue “a lot of freedom to play,” in Illescas’s own words.


pages: 356 words: 91,157

The New Urban Crisis: How Our Cities Are Increasing Inequality, Deepening Segregation, and Failing the Middle Class?and What We Can Do About It by Richard Florida

affirmative action, Airbnb, basic income, Bernie Sanders, blue-collar work, business climate, Capital in the Twenty-First Century by Thomas Piketty, clean water, Columbine, congestion charging, creative destruction, David Ricardo: comparative advantage, declining real wages, deindustrialization, Donald Trump, East Village, edge city, Edward Glaeser, failed state, Ferguson, Missouri, Gini coefficient, Google bus, high net worth, income inequality, income per capita, industrial cluster, informal economy, Jane Jacobs, jitney, Kitchen Debate, knowledge economy, knowledge worker, land value tax, low skilled workers, Lyft, megacity, Menlo Park, mortgage tax deduction, Nate Silver, New Economic Geography, new economy, New Urbanism, occupational segregation, Paul Graham, Plutocrats, plutocrats, RAND corporation, rent control, rent-seeking, Richard Florida, rising living standards, Ronald Reagan, secular stagnation, self-driving car, Silicon Valley, sovereign wealth fund, superstar cities, the built environment, The Chicago School, The Death and Life of Great American Cities, the High Line, The Wealth of Nations by Adam Smith, Thorstein Veblen, trickle-down economics, Uber and Lyft, universal basic income, upwardly mobile, urban decay, urban planning, urban renewal, urban sprawl, white flight, young professional

Such efforts are sorely needed, given the extent to which blacks are underrepresented in the creative class. Ironically—and troublingly—cities and metro areas can be both more diverse and more segregated at the same time. My own analysis shows that segregation is positively associated with two common measures of diversity: the concentration of gay and lesbian people and the share of the population that is foreign-born.35 A 2015 analysis by Nate Silver comparing the overall ethnic and racial diversity of the nation’s one hundred largest cities to the racial and ethnic segregation of their neighborhoods found segregation to be higher in more racially and ethnically diverse cities.36 Ultimately, the one-two punch of race and economic segregation hits hardest at poor African American neighborhoods. Black Americans are much more likely to live in areas of concentrated poverty than their white peers.

There is no statistical association between the black creative class and income inequality based on the Gini coefficient, compared to a correlation of 0.40 for the white creative class. The black creative class is modestly associated with my measure of overall economic segregation (0.20), but this correlation is much more modest than that for the white creative class (0.66). 35. The Overall Segregation Index is positively associated with the concentration of gay and lesbian households (0.42) and the share of adults who are foreign-born (0.38). 36. Nate Silver, “The Most Diverse Cities Are Often the Most Segregated,” FiveThirtyEight, May 1, 2015, http://fivethirtyeight.com/features/the-most-diverse-cities-are-often-the-most-segregated. 37. Paul A. Jargowsky, “Architecture of Segregation: Civil Unrest, the Concentration of Poverty, and Public Policy,” Century Foundation, August 9, 2015, http://apps.tcf.org/architecture-of-segregation. 38. Racially concentrated areas of poverty are defined as census tracts where more than half of the population is non-white and more than 40 percent live below the poverty line.


pages: 588 words: 131,025

The Patient Will See You Now: The Future of Medicine Is in Your Hands by Eric Topol

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23andMe, 3D printing, Affordable Care Act / Obamacare, Anne Wojcicki, Atul Gawande, augmented reality, bioinformatics, call centre, Clayton Christensen, clean water, cloud computing, commoditize, computer vision, conceptual framework, connected car, correlation does not imply causation, creative destruction, crowdsourcing, dark matter, data acquisition, disintermediation, don't be evil, Edward Snowden, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Firefox, global village, Google Glasses, Google X / Alphabet X, Ignaz Semmelweis: hand washing, information asymmetry, interchangeable parts, Internet of things, Isaac Newton, job automation, Joseph Schumpeter, Julian Assange, Kevin Kelly, license plate recognition, lifelogging, Lyft, Mark Zuckerberg, Marshall McLuhan, meta analysis, meta-analysis, microbiome, Nate Silver, natural language processing, Network effects, Nicholas Carr, obamacare, pattern recognition, personalized medicine, phenotype, placebo effect, RAND corporation, randomized controlled trial, Second Machine Age, self-driving car, Silicon Valley, Skype, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, Snapchat, social graph, speech recognition, stealth mode startup, Steve Jobs, the scientific method, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, Turing test, Uber for X, Watson beat the top human players on Jeopardy!, X Prize

Although Eisenstein stopped short of claiming that the first industrial revolution was an outgrowth of the printing press, many others have claimed this. Marshall McLuhan, in The Gutenberg Galaxy, wrote: “The invention of typography confirmed and extended the new visual stress of applied knowledge, providing the first uniformly repeatable commodity, the first assembly-line, and the first mass-production.”11 More recently, Nate Silver, in The Signal and the Noise, asserted that the industrial revolution of 1775 was sparked by the printing press, whereby the economic growth rate that was stagnant at 0.1 percent per year then grew faster than the growth rate of the population.12 But I prefer to principally assess the Gutenberg transformative effects by the specific attributes that they induced or cultivated instead of as a precursor for subsequent momentous periods in history.

Table 3.1 summarizes the predominant attributes affected by Gutenberg’s press and compares them to the smartphone, or what some term as the “phablet” (a combination of smartphone and tablet). At first glance you will note a check mark in every box. But here I’ll explain why the parallels can be seen as striking. Without question, APP was associated with an explosion of knowledge and too much information. So too is our era. Back in the fifteenth century, as Nate Silver summed up, “the amount of information was increasing much more rapidly than our understanding of what to do with it, or our ability to differentiate the useful information from the mistruths.”13 Here in the twenty-first century, we call that “big data,” with more data generated in the past two years than in the history of humankind. And an ever-increasing proportion of that is derived from and is passing through mobile devices.


pages: 500 words: 145,005

Misbehaving: The Making of Behavioral Economics by Richard H. Thaler

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3Com Palm IPO, Albert Einstein, Alvin Roth, Amazon Mechanical Turk, Andrei Shleifer, Apple's 1984 Super Bowl advert, Atul Gawande, Berlin Wall, Bernie Madoff, Black-Scholes formula, capital asset pricing model, Cass Sunstein, Checklist Manifesto, choice architecture, clean water, cognitive dissonance, conceptual framework, constrained optimization, Daniel Kahneman / Amos Tversky, delayed gratification, diversification, diversified portfolio, Edward Glaeser, endowment effect, equity premium, Eugene Fama: efficient market hypothesis, experimental economics, Fall of the Berlin Wall, George Akerlof, hindsight bias, Home mortgage interest deduction, impulse control, index fund, information asymmetry, invisible hand, Jean Tirole, John Nash: game theory, John von Neumann, Kenneth Arrow, late fees, law of one price, libertarian paternalism, Long Term Capital Management, loss aversion, market clearing, Mason jar, mental accounting, meta analysis, meta-analysis, money market fund, More Guns, Less Crime, mortgage debt, Myron Scholes, Nash equilibrium, Nate Silver, New Journalism, nudge unit, Paul Samuelson, payday loans, Ponzi scheme, presumed consent, pre–internet, principal–agent problem, prisoner's dilemma, profit maximization, random walk, randomized controlled trial, Richard Thaler, Robert Shiller, Robert Shiller, Ronald Coase, Silicon Valley, South Sea Bubble, statistical model, Steve Jobs, technology bubble, The Chicago School, The Myth of the Rational Market, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, transaction costs, ultimatum game, Vilfredo Pareto, Walter Mischel, zero-sum game

But a snappy retort to the “as if” critique was far from sufficient; to win the argument I would need hard empirical evidence that would convince economists. To this day, the phrase “survey evidence” is rarely heard in economics circles without the necessary adjective “mere,” which rhymes with “sneer.” This disdain is simply unscientific. Polling data, which just comes from asking people whether they are planning to vote and for whom, when carefully used by skilled statisticians such as Nate Silver, yield remarkably accurate predictions of elections. The most amusing aspect of this anti-survey attitude is that many important macroeconomic variables are produced by surveys! For instance, in America the press often obsesses over the monthly announcement of the latest “jobs” data, with serious-looking economists asked to weigh in about how to interpret the figures. Where do these jobs numbers come from?

Fans can follow the “New York Times 4th Down Bot” in real time and see what the math says a team should be doing. So what effect has this research plus a free app had on the behavior of football coaches? Essentially none. Since Romer wrote his paper, the frequency of going for it on fourth down has marginally gone down, meaning that teams have gotten dumber! (Similarly, there has been no noticeable change in teams’ draft strategy since our paper came out.) Nate Silver, the ex–sports analytics junkie who became famous for his political forecasts and for the excellent book The Signal and the Noise, estimates that bad fourth-down decisions cost a football team an average of half a win per season. The Times analysts estimate it to be closer to two-thirds of a win per year. That may not seem like a lot, but the season is only sixteen games. A team can win an extra game every other year just by making the smart decision two or three times a game, one they can even check online if they need help.¶ Of course, coaches are Humans.


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Warnings by Richard A. Clarke

active measures, Albert Einstein, algorithmic trading, anti-communist, artificial general intelligence, Asilomar, Asilomar Conference on Recombinant DNA, Bernie Madoff, cognitive bias, collateralized debt obligation, complexity theory, corporate governance, cuban missile crisis, data acquisition, discovery of penicillin, double helix, Elon Musk, failed state, financial thriller, fixed income, Flash crash, forensic accounting, friendly AI, Intergovernmental Panel on Climate Change (IPCC), Internet of things, James Watt: steam engine, Jeff Bezos, John Maynard Keynes: Economic Possibilities for our Grandchildren, knowledge worker, Maui Hawaii, megacity, Mikhail Gorbachev, money market fund, mouse model, Nate Silver, new economy, Nicholas Carr, nuclear winter, pattern recognition, personalized medicine, phenotype, Ponzi scheme, Ray Kurzweil, Richard Feynman, Richard Feynman, Richard Feynman: Challenger O-ring, risk tolerance, Ronald Reagan, Search for Extraterrestrial Intelligence, self-driving car, Silicon Valley, smart grid, statistical model, Stephen Hawking, Stuxnet, technological singularity, The Future of Employment, the scientific method, The Signal and the Noise by Nate Silver, Tunguska event, uranium enrichment, Vernor Vinge, Watson beat the top human players on Jeopardy!, women in the workforce, Y2K

However, such a response does little to help prepare for future disaster or to ensure that Cassandra’s warnings do not again go unheeded. As it seemed we weren’t the only ones who had noticed Cassandras in our midst, we then wondered if there existed any scholarly research on the topic of predictions. In fact, prediction is something that academics have spent a lot of time studying and considering. The statistician Nate Silver has taken a highly quantitative approach to prediction, one that works for a certain class of event. The jurist Richard Posner examined the phenomenon of catastrophes in the years after 9/11. Psychologists like Dan Ariely and Tsachi Ein-Dor have probed the way our brains work (and don’t) through empirical observation and the study of warnings. Unquestionably one of the foundational works in this area, predictions within the social sciences, is Philip Tetlock’s Expert Political Judgment.

They did perform somewhat better than undergraduates subjected to the same exercises, and they outperformed the proverbial “chimp with a dart board,” but they didn’t come close to the predictive accuracy of formal statistical models. Later books have looked at Tetlock’s foundational results in some additional detail. Dan Gardner’s 2012 Future Babble draws on recent research in psychology, neuroscience, and behavioral economics to detail the biases and other cognitive processes that skew our judgment when we try to make predictions about the future. And building on a successful career in sports and political forecasting, Nate Silver discusses in his book, The Signal and the Noise, how thinking more probabilistically can help us distill more accurate predictions from a sea of raw data. Fundamentally, these books all identify the difficulties inherent in trying to see into the future. Predicting natural phenomena is stymied by the chaotic nature of the universe: natural processes are nonlinear systems driven by feedback loops that are often inherently unpredictable themselves.


pages: 184 words: 53,625

Future Perfect: The Case for Progress in a Networked Age by Steven Johnson

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Airbus A320, airport security, algorithmic trading, banking crisis, barriers to entry, Bernie Sanders, call centre, Captain Sullenberger Hudson, Cass Sunstein, cognitive dissonance, credit crunch, crowdsourcing, dark matter, Dava Sobel, David Brooks, Donald Davies, future of journalism, hive mind, Howard Rheingold, HyperCard, Jane Jacobs, John Gruber, John Harrison: Longitude, Kevin Kelly, Kickstarter, lone genius, Mark Zuckerberg, mega-rich, meta analysis, meta-analysis, Naomi Klein, Nate Silver, Occupy movement, packet switching, peer-to-peer, Peter Thiel, planetary scale, pre–internet, RAND corporation, risk tolerance, shareholder value, Silicon Valley, Silicon Valley startup, social graph, Steve Jobs, Steven Pinker, Stewart Brand, The Death and Life of Great American Cities, Tim Cook: Apple, urban planning, US Airways Flight 1549, WikiLeaks, William Langewiesche, working poor, X Prize, your tax dollars at work

Sites such as Talking Points Memo and Politico did extensive direct reporting. Daily Kos provided in-depth surveys and field reports on state races that the Times would never have had the ink to cover. Individual bloggers such as Andrew Sullivan responded to each twist in the news cycle; The Huffington Post culled the most provocative opinion pieces from the rest of the blogosphere. The statistician Nate Silver at the website Five Thirty Eight did meta-analysis of polling that exceeded anything Bill Schneider dreamed of doing on CNN in 1992. When the banking crisis erupted in September 2008, I followed economist bloggers such as Brad DeLong to get their expert take on the candidates’ responses to the crisis. I watched the debates with a thousand virtual friends live-tweeting alongside me on the couch.


pages: 268 words: 75,850

The Formula: How Algorithms Solve All Our Problems-And Create More by Luke Dormehl

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3D printing, algorithmic trading, Any sufficiently advanced technology is indistinguishable from magic, augmented reality, big data - Walmart - Pop Tarts, call centre, Cass Sunstein, Clayton Christensen, commoditize, computer age, death of newspapers, deferred acceptance, Edward Lorenz: Chaos theory, Erik Brynjolfsson, Filter Bubble, Flash crash, Florence Nightingale: pie chart, Frank Levy and Richard Murnane: The New Division of Labor, Google Earth, Google Glasses, High speed trading, Internet Archive, Isaac Newton, Jaron Lanier, Jeff Bezos, job automation, John Markoff, Kevin Kelly, Kodak vs Instagram, lifelogging, Marshall McLuhan, means of production, Nate Silver, natural language processing, Netflix Prize, pattern recognition, price discrimination, recommendation engine, Richard Thaler, Rosa Parks, self-driving car, sentiment analysis, Silicon Valley, Silicon Valley startup, Slavoj Žižek, social graph, speech recognition, Steve Jobs, Steven Levy, Steven Pinker, Stewart Brand, the scientific method, The Signal and the Noise by Nate Silver, upwardly mobile, Wall-E, Watson beat the top human players on Jeopardy!, Y Combinator

While I was first coming up with formulas at college, trying to mathematically determine whether we should go to the library to get some work done, deep down in the recesses of our dorky ids I think that what we were saying is that life is uncertain and we were trying to make it more certain. I’m not as disturbed by numbers providing answers as I am by the potential that there might not be answers.” What is it about the modern world that makes us demand easy answers? Is it that we are naturally pattern-seeking creatures, as the statistician Nate Silver argues in The Signal and the Noise? Or is there something about the effects of the march of technology that demands the kind of answers only an algorithm can provide? “[The algorithm does] seem to be a key metaphor for what matters now in terms of organizing the world,” acknowledges McKenzie Wark, a media theorist who has written about digital technologies for the last 20 years. “If one thinks of algorithms as processes which terminate and generate a result, there’s a moment when the process ceases and you have your answer.


pages: 294 words: 82,438

Simple Rules: How to Thrive in a Complex World by Donald Sull, Kathleen M. Eisenhardt

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Affordable Care Act / Obamacare, Airbnb, asset allocation, Atul Gawande, barriers to entry, Basel III, Berlin Wall, carbon footprint, Checklist Manifesto, complexity theory, Craig Reynolds: boids flock, Credit Default Swap, Daniel Kahneman / Amos Tversky, diversification, drone strike, en.wikipedia.org, European colonialism, Exxon Valdez, facts on the ground, Fall of the Berlin Wall, haute cuisine, invention of the printing press, Isaac Newton, Kickstarter, late fees, Lean Startup, Louis Pasteur, Lyft, Moneyball by Michael Lewis explains big data, Nate Silver, Network effects, obamacare, Paul Graham, performance metric, price anchoring, RAND corporation, risk/return, Saturday Night Live, sharing economy, Silicon Valley, Startup school, statistical model, Steve Jobs, TaskRabbit, The Signal and the Noise by Nate Silver, transportation-network company, two-sided market, Wall-E, web application, Y Combinator, Zipcar

., “Health on Impulse: When Low Self-Control Promotes Healthy Food Choices,” Health Psychology 33, no. 2 (2013): 103–9, http://www.medscape.com/medline/abstract/2347758. [>] In contrast, people: Brian Wansink, David R. Rust, and Collin R. Payne, “Mindless Eating and Healthy Heuristics for the Irrational,” American Economic Review: Papers and Proceedings 99, no. 2 (2009): 165–69. [>] Meteorologists make: Nate Silver, The Signal and the Noise (New York: Penguin, 2012), 126–27. [>] Japanese honeybees: Atsushi Ugajin et al., “Detection of Neural Activity in the Brains of Japanese Honeybee Workers During the Formation of a ‘Hot Defensive Bee Ball,’” PLoS One 7, no. 3 (2012), available at the website of the National Center for Biotechnology Information, http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3303784/. [>] As an example of: Our account of the bees’ choice of new nest is based on the research of Thomas Seeley, especially Thomas D.

Everydata: The Misinformation Hidden in the Little Data You Consume Every Day by John H. Johnson

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Affordable Care Act / Obamacare, Black Swan, business intelligence, Carmen Reinhart, cognitive bias, correlation does not imply causation, Daniel Kahneman / Amos Tversky, Donald Trump, en.wikipedia.org, Kenneth Rogoff, labor-force participation, lake wobegon effect, Long Term Capital Management, Mercator projection, Mercator projection distort size, especially Greenland and Africa, meta analysis, meta-analysis, Nate Silver, obamacare, p-value, PageRank, pattern recognition, publication bias, QR code, randomized controlled trial, risk-adjusted returns, Ronald Reagan, selection bias, statistical model, The Signal and the Noise by Nate Silver, Thomas Bayes, Tim Cook: Apple, wikimedia commons, Yogi Berra

“There is no scientifically plausible way of predicting the occurrence of a particular earthquake,” they note, adding that “prediction, as people expect it, requires predicting the magnitude, timing, and location of the future earthquake, which is not currently possible.”17 We simply don’t have the data, nor do we have the technology, to accurately predict quakes at this time. That said, the USGS does describe the places “most likely to produce earthquakes in the long term.” They call this forecasting, when they estimate the likelihood of a seismic event occurring over a period of time. This brings us to the ­distinction—​­or lack ­thereof—​­between a prediction and a forecast. As Nate Silver notes in The Signal and the Noise, the terms are used differently by some (most notably seismologists, who study earthquakes) but interchangeably by others. Some would argue that predictions are ­binary—​­something will or won’t ­happen—​­while forecasts are more ­probabilistic—​­there’s an X percent chance that something will happen. (To further complicate the issue, an estimate may be used when talking about past, current, or future data.)


pages: 558 words: 168,179

Dark Money: The Hidden History of the Billionaires Behind the Rise of the Radical Right by Jane Mayer

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affirmative action, Affordable Care Act / Obamacare, American Legislative Exchange Council, anti-communist, Bakken shale, bank run, battle of ideas, Berlin Wall, Capital in the Twenty-First Century by Thomas Piketty, carried interest, centre right, clean water, Climategate, Climatic Research Unit, collective bargaining, corporate raider, crony capitalism, David Brooks, desegregation, diversified portfolio, Donald Trump, energy security, estate planning, Fall of the Berlin Wall, George Gilder, housing crisis, hydraulic fracturing, income inequality, Intergovernmental Panel on Climate Change (IPCC), invisible hand, job automation, low skilled workers, mandatory minimum, market fundamentalism, mass incarceration, Mont Pelerin Society, More Guns, Less Crime, Nate Silver, New Journalism, obamacare, Occupy movement, offshore financial centre, oil shale / tar sands, oil shock, Plutocrats, plutocrats, Powell Memorandum, Ralph Nader, Renaissance Technologies, road to serfdom, Ronald Reagan, school choice, school vouchers, The Bell Curve by Richard Herrnstein and Charles Murray, The Chicago School, the scientific method, University of East Anglia, Unsafe at Any Speed, War on Poverty, working poor

A series of loudspeakers formed a fence around an outdoor pavilion in which the donors met, emitting static toward the outside world, to prevent eavesdropping. Or so they thought until a reporter for Mother Jones, Brad Friedman, obtained an audio recording of the weekend’s highlights and published a transcript. As they gathered in the foothills of the Rockies, the donors had ample reason for optimism. The New York Times’s resident number cruncher, Nate Silver, who handicapped political odds with the unsentimental eye of a racetrack bookie, was openly asking, “Is Obama toast?” After analyzing Obama’s sagging approval rating and the economy’s lagging indicators, he concluded that Obama had gone from “a modest favorite to win re-election to, probably, a slight underdog.” If the Republicans chose a weak candidate or the economy miraculously revived, he noted, this could change.

“With no basis in fact”: Mann and Ornstein, It’s Even Worse Than It Looks, 23. Cantor later told: Ryan Lizza, “The House of Pain,” New Yorker, March 4, 2013. “I think he came in truly trying”: Neera Tanden, interview with author. CHAPTER TWELVE: MOTHER OF ALL WARS Or so they thought: Brad Friedman, “Inside the Koch Brothers’ 2011 Summer Seminar,” The Brad Blog, June 26, 2011. The New York Times’s resident: Nate Silver, “Is Obama Toast? Handicapping the 2012 Election,” New York Times Magazine, Nov. 3, 2011. “Wouldn’t it be easier”: Halperin and Heilemann, Double Down, 345. Four years later: For more on Christie’s record, see Cezary Podkul and Allan Sloan, “Christie Closed Budget Gaps with One-Shot Maneuvers,” Washington Post, April 18, 2015, A1. “Who knows?”: Friedman, “Inside the Koch Brothers’ 2011 Summer Seminar.”


pages: 269 words: 104,430

Carjacked: The Culture of the Automobile and Its Effect on Our Lives by Catherine Lutz, Anne Lutz Fernandez

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barriers to entry, car-free, carbon footprint, collateralized debt obligation, failed state, feminist movement, fudge factor, Gordon Gekko, housing crisis, illegal immigration, income inequality, inventory management, market design, market fundamentalism, mortgage tax deduction, Naomi Klein, Nate Silver, New Urbanism, oil shock, peak oil, Ralph Nader, Ralph Waldo Emerson, ride hailing / ride sharing, Thorstein Veblen, traffic fines, Unsafe at Any Speed, urban planning, white flight, women in the workforce, working poor, Zipcar

John Pucher and Lewis Dijkstra, “Promoting Safe Walking and Cycling to Improve Public Health: Lessons from the Netherlands and Germany,” American Journal of Public Health, 2004, 93 (9): 1509–16. Evans, Traffic Safety. CHAPTER 10 1. “Edmunds.com Forecasts December Auto Sales: SUV and Truck Sales to Outpace Cars for First Time,” December 19, 2008, www.edmunds.com NOTES 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 245 Nate Silver, “The End of Car Culture,” Esquire, May 6, 2009. “Recovery Accountability and Transparency Board. $8.4 Billion for Public Transit,” March 5, 2009, www.recovery.gov. Dylan Rivera, “U.S. Transportation Secretary Calls Portland’s Streetcar, Light Rail a ‘Model’ for Nation,” The Oregonian, April 14, 2009. Use the Edmunds.com’s True Cost to Own Calculator to see annual dollar depreciation on your current vehicle or a vehicle you are planning to buy in order to calculate exactly how much you would save by postponing trading it in or selling it to buy a new car.


pages: 361 words: 81,068

The Internet Is Not the Answer by Andrew Keen

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3D printing, A Declaration of the Independence of Cyberspace, Airbnb, AltaVista, Andrew Keen, augmented reality, Bay Area Rapid Transit, Berlin Wall, bitcoin, Black Swan, Bob Geldof, Burning Man, Cass Sunstein, citizen journalism, Clayton Christensen, clean water, cloud computing, collective bargaining, Colonization of Mars, computer age, connected car, creative destruction, cuban missile crisis, David Brooks, disintermediation, Donald Davies, Downton Abbey, Edward Snowden, Elon Musk, Erik Brynjolfsson, Fall of the Berlin Wall, Filter Bubble, Francis Fukuyama: the end of history, Frank Gehry, Frederick Winslow Taylor, frictionless, full employment, future of work, gig economy, global village, Google bus, Google Glasses, Hacker Ethic, happiness index / gross national happiness, income inequality, index card, informal economy, information trail, Innovator's Dilemma, Internet of things, Isaac Newton, Jaron Lanier, Jeff Bezos, job automation, Joseph Schumpeter, Julian Assange, Kevin Kelly, Kickstarter, Kodak vs Instagram, Lean Startup, libertarian paternalism, lifelogging, Lyft, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, Martin Wolf, Metcalfe’s law, move fast and break things, move fast and break things, Nate Silver, Network effects, new economy, Nicholas Carr, nonsequential writing, Norbert Wiener, Norman Mailer, Occupy movement, packet switching, PageRank, Paul Graham, peer-to-peer, peer-to-peer rental, Peter Thiel, Plutocrats, plutocrats, Potemkin village, precariat, pre–internet, RAND corporation, Ray Kurzweil, ride hailing / ride sharing, Robert Metcalfe, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Silicon Valley ideology, Skype, smart cities, Snapchat, social web, South of Market, San Francisco, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, TaskRabbit, Ted Nelson, telemarketer, The Future of Employment, the medium is the message, the new new thing, Thomas L Friedman, Tyler Cowen: Great Stagnation, Uber for X, urban planning, Vannevar Bush, Whole Earth Catalog, WikiLeaks, winner-take-all economy, working poor, Y Combinator

“So much for the borderless, gender-blind, class-blind and bank account–blind MOOCs,” notes the technology writer Jessica McKenzie. “If anything, this shows that MOOCs are widening the educational divide, not leveling the playing field.”19 This unequal economy is particularly pronounced in online journalism, where, amid the massive layoffs at regional newspapers, highly paid American reporters like Nate Silver, Ezra Klein, Matt Taibbi, and Glenn Greenwald represent what Emily Bell, the director of the Tow Center for Digital Journalism at Columbia University, calls “a one percent economy.”20 Ironically, for all the talk of how the Internet was supposed to diversify the news industry, the end result of the combination of a one percent economy and massive layoffs is less diversity in the newsroom, with minority employment for American journalists down almost 6% between 2006 and 2012.21 And as Bell also notes, the most recent wave of venture-capital-funded “personal brand” journalist startups are almost all supporting white male superstars like Greenwald, Taibbi, Silver, and Klein.22 But the most damaging discrimination is against paid work.


pages: 339 words: 88,732

The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies by Erik Brynjolfsson, Andrew McAfee

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2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 3D printing, access to a mobile phone, additive manufacturing, Airbnb, Albert Einstein, Amazon Mechanical Turk, Amazon Web Services, American Society of Civil Engineers: Report Card, Any sufficiently advanced technology is indistinguishable from magic, autonomous vehicles, barriers to entry, basic income, Baxter: Rethink Robotics, British Empire, business intelligence, business process, call centre, Chuck Templeton: OpenTable, clean water, combinatorial explosion, computer age, computer vision, congestion charging, corporate governance, creative destruction, crowdsourcing, David Ricardo: comparative advantage, digital map, employer provided health coverage, en.wikipedia.org, Erik Brynjolfsson, factory automation, falling living standards, Filter Bubble, first square of the chessboard / second half of the chessboard, Frank Levy and Richard Murnane: The New Division of Labor, Freestyle chess, full employment, game design, global village, happiness index / gross national happiness, illegal immigration, immigration reform, income inequality, income per capita, indoor plumbing, industrial robot, informal economy, intangible asset, inventory management, James Watt: steam engine, Jeff Bezos, jimmy wales, job automation, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joseph Schumpeter, Kevin Kelly, Khan Academy, knowledge worker, Kodak vs Instagram, law of one price, low skilled workers, Lyft, Mahatma Gandhi, manufacturing employment, Marc Andreessen, Mark Zuckerberg, Mars Rover, mass immigration, means of production, Narrative Science, Nate Silver, natural language processing, Network effects, new economy, New Urbanism, Nicholas Carr, Occupy movement, oil shale / tar sands, oil shock, pattern recognition, Paul Samuelson, payday loans, price stability, Productivity paradox, profit maximization, Ralph Nader, Ray Kurzweil, recommendation engine, Report Card for America’s Infrastructure, Robert Gordon, Rodney Brooks, Ronald Reagan, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Simon Kuznets, six sigma, Skype, software patent, sovereign wealth fund, speech recognition, statistical model, Steve Jobs, Steven Pinker, Stuxnet, supply-chain management, TaskRabbit, technological singularity, telepresence, The Bell Curve by Richard Herrnstein and Charles Murray, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, total factor productivity, transaction costs, Tyler Cowen: Great Stagnation, Vernor Vinge, Watson beat the top human players on Jeopardy!, winner-take-all economy, Y2K

., “Grading Student Loans,” Liberty Street Economics blog, Federal Reserve Bank of New York, March 5, 2012, http://libertystreeteconomics.newyorkfed.org/2012/03/grading-student-loans.html?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed:+LibertyStreetEconomics+(Liberty+Street+Economics). 21. Tim Hornyak, “Towel-folding Robot Won’t Do the Dishes,” CNET, March 31, 2010, http://news.cnet.com/8301-17938_105-10471898-1.html. 22. Nate Silver, The Signal and the Noise: Why So Many Predictions Fail—But Some Don’t, 1st ed. (New York: Penguin, 2012). Chapter 13 POLICY RECOMMENDATIONS 1. “Employment Level,” Economic Research—Federal Reserve Bank of St. Louis (U.S. Department of Labor, Bureau of Labor Statistics, August 2, 2013), http://research.stlouisfed.org/fred2/series/LNU02000000. 2. Claudia Goldin and Lawrence F. Katz, The Race Between Education and Technology (Cambridge, MA: Belknap Press of Harvard University Press, 2010). 3.


pages: 336 words: 113,519

The Undoing Project: A Friendship That Changed Our Minds by Michael Lewis

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Albert Einstein, availability heuristic, Cass Sunstein, choice architecture, complexity theory, Daniel Kahneman / Amos Tversky, Donald Trump, Douglas Hofstadter, endowment effect, feminist movement, framing effect, hindsight bias, John von Neumann, Kenneth Arrow, loss aversion, medical residency, Menlo Park, Murray Gell-Mann, Nate Silver, New Journalism, Paul Samuelson, Richard Thaler, Saturday Night Live, statistical model, the new new thing, Thomas Bayes, Walter Mischel, Yom Kippur War

In 2004, after aping Oakland’s approach to baseball decision making, the Boston Red Sox won their first World Series in nearly a century. Using the same methods, they won it again in 2007 and 2013. But in 2016, after three disappointing seasons, they announced that they were moving away from the data-based approach and back to one where they relied upon the judgment of baseball experts. (“We have perhaps overly relied on numbers . . . ,” said owner John Henry.) The writer Nate Silver for several years enjoyed breathtaking success predicting U.S. presidential election outcomes for the New York Times, using an approach to statistics he learned writing about baseball. For the first time in memory, a newspaper seemed to have an edge in calling elections. But then Silver left the Times, and failed to predict the rise of Donald Trump—and his data-driven approach to predicting elections was called into question . . . by the New York Times!


pages: 285 words: 86,174

Twilight of the Elites: America After Meritocracy by Chris Hayes

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affirmative action, Affordable Care Act / Obamacare, asset-backed security, barriers to entry, Berlin Wall, Bernie Madoff, carried interest, circulation of elites, Climategate, Climatic Research Unit, collapse of Lehman Brothers, collective bargaining, creative destruction, Credit Default Swap, dark matter, David Brooks, David Graeber, deindustrialization, Fall of the Berlin Wall, financial deregulation, fixed income, full employment, George Akerlof, Gunnar Myrdal, hiring and firing, income inequality, Jane Jacobs, jimmy wales, Julian Assange, Kenneth Arrow, Mark Zuckerberg, mass affluent, mass incarceration, means of production, meta analysis, meta-analysis, money market fund, moral hazard, Naomi Klein, Nate Silver, peak oil, Plutocrats, plutocrats, Ponzi scheme, Ralph Waldo Emerson, rolodex, The Spirit Level, too big to fail, University of East Anglia, Vilfredo Pareto, We are the 99%, WikiLeaks, women in the workforce

Acknowledgments One of the more insidious aspects of meritocratic indoctrination is that it teaches you to believe that you wholly own your accomplishments. As I’ve tried to make clear in the book, it’s a tempting notion but a dangerous one. As is the case with any project of this size, this book is the product of the labor of far, far more people than the one person whose name appears on the cover. A Nate Silver post at his old site FiveThirtyEight, that showed General Social Survey data about America’s declining trust in their institutions over time, first crystallized the idea for the book. And it was during a long, loquacious walk I took with Dan Benaim through Washington, DC, in 2009 that I was first able to articulate just what it was I wanted to write a book about. Throughout the development of the book, I’ve had hundreds of conversations with friends and colleagues about its main themes, and those conversations inform every page of the work.

The Data Revolution: Big Data, Open Data, Data Infrastructures and Their Consequences by Rob Kitchin

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Bayesian statistics, business intelligence, business process, cellular automata, Celtic Tiger, cloud computing, collateralized debt obligation, conceptual framework, congestion charging, corporate governance, correlation does not imply causation, crowdsourcing, discrete time, George Gilder, Google Earth, Infrastructure as a Service, Internet Archive, Internet of things, invisible hand, knowledge economy, late capitalism, lifelogging, linked data, Masdar, means of production, Nate Silver, natural language processing, openstreetmap, pattern recognition, platform as a service, recommendation engine, RFID, semantic web, sentiment analysis, slashdot, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, smart grid, smart meter, software as a service, statistical model, supply-chain management, the scientific method, The Signal and the Noise by Nate Silver, transaction costs

Rubinstein, I.S. (2013) ‘Big data: the end of privacy or a new beginning?’, International Data Privacy Law, online first, http://idpl.oxfordjournals.org/content/early/2013/01/24/idpl.ips036.short (last accessed 15 July 2013). Ruppert, E. (2012) ‘The governmental topologies of database devices’, Theory, Culture Society, 29: 116–36. Ruppert, E. (2013) ‘Rethinking empirical social sciences’, Dialogues in Human Geography, 3(3): 268–73. Salmon, F. (2014) ‘Why the Nate Silvers of the world don’t know everything’, Wired, 7 January, http://www.wired.com/business/2014/01/quants-dont-know-everything/ (last accessed 8 January 2014). Salus, P. (1995) Casting the Net: From Arpanet to Internet and Beyond. Addison Wesley, Reading, MA. Sawyer, S. (2008) ‘Data wealth, data poverty, science and cyberinfrastructure’, Prometheus: Critical Studies in Innovation, 26(4): 355–71. Schnapp, J. and Presner, P. (2009) Digital Humanities Manifesto 2.0. http://www.humanitiesblast.com/manifesto/Manifesto_V2.pdf (last accessed 13 March 2013).


pages: 340 words: 92,904

Street Smart: The Rise of Cities and the Fall of Cars by Samuel I. Schwartz

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2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, active transport: walking or cycling, Affordable Care Act / Obamacare, American Society of Civil Engineers: Report Card, autonomous vehicles, car-free, City Beautiful movement, collaborative consumption, congestion charging, crowdsourcing, desegregation, Enrique Peñalosa, Ford paid five dollars a day, Frederick Winslow Taylor, if you build it, they will come, Induced demand, intermodal, invention of the wheel, lake wobegon effect, Loma Prieta earthquake, Lyft, Masdar, megacity, meta analysis, meta-analysis, moral hazard, Nate Silver, oil shock, Productivity paradox, Ralph Nader, rent control, ride hailing / ride sharing, Rosa Parks, self-driving car, skinny streets, smart cities, smart grid, smart transportation, the built environment, the map is not the territory, transportation-network company, Uber and Lyft, Uber for X, Unsafe at Any Speed, urban decay, urban planning, urban renewal, walkable city, Wall-E, white flight, white picket fence, Works Progress Administration, Yogi Berra, Zipcar

It works at almost every level of granularity: until a community—a county, a city, a town, or even a voting precinct—reaches a density of about eight hundred people a square mile, it’s as reliably Republican as Fox News. Once it exceeds that number, though, the voting patterns do a somersault. Anywhere under eight hundred people a square mile, there’s a two-thirds chance that a randomly selected voter went Republican; above it, that hypothetical voter pulled a Democratic lever two-thirds of the time. As the political prediction machine Nate Silver of 538.com tweeted in 2012, “If a place has sidewalks, it votes Democratic.” It’s not totally obvious whether people vote a certain way because of where they live, or whether they move to places where everyone votes the way they do. What is obvious though is that all the elements of a Street Smart transportation system depend on density. At first glance, this would appear to be a giant advantage for a Street Smart future, since every demographic indicator shows that America and the world are headed for a much more urbanized future.


pages: 357 words: 94,852

No Is Not Enough: Resisting Trump’s Shock Politics and Winning the World We Need by Naomi Klein

Airbnb, basic income, battle of ideas, Berlin Wall, Bernie Sanders, Brewster Kahle, Celebration, Florida, clean water, collective bargaining, Corrections Corporation of America, desegregation, Donald Trump, drone strike, Edward Snowden, Elon Musk, energy transition, financial deregulation, greed is good, high net worth, Howard Zinn, illegal immigration, income inequality, Internet Archive, late capitalism, Mark Zuckerberg, market bubble, market fundamentalism, mass incarceration, Mikhail Gorbachev, moral panic, Naomi Klein, Nate Silver, new economy, Occupy movement, offshore financial centre, oil shale / tar sands, open borders, Peter Thiel, Plutocrats, plutocrats, private military company, profit motive, race to the bottom, Ralph Nader, Ronald Reagan, Saturday Night Live, sexual politics, sharing economy, Silicon Valley, too big to fail, trade liberalization, transatlantic slave trade, transatlantic slave trade, Triangle Shirtwaist Factory, trickle-down economics, Upton Sinclair, urban decay, women in the workforce, working poor

Trump and sexual harassment and assault allegations Megan Twohey, “Former ‘Apprentice’ Contestant Files Defamation Suit Against Trump,” New York Times, January 17, 2017, Trump and Ivana rape allegation Jane Mayer, “Documenting Trump’s Abuse of Women,” New Yorker, October 24, 2016, http://www.newyorker.com/​magazine/​2016/​10/​24/​documenting-trumps-abuse-of-women. The Problem with “Jobs Voters” Past 40 years has seen number of people behind bars in US increase by 500 percent Carl Vogel, Prison Brake, University of Chicago School of Social Service Administration, accessed April 11, 2017, https://ssa.uchicago.edu/​end-mass-incarceration. Trump voters: earn $50,000–$200,000 Nate Silver, “The Mythology of Trump’s ‘Working Class’ Support,” FiveThirtyEight, May 3, 2016, https://fivethirtyeight.com/​features/​the-mythology-of-trumps-working-class-support/. CNN analysis of exit polls “Exit polls,” CNN.com, November 23, 2016, http://www.cnn.com/​election/​results/​exit-polls. Insecure on Every Front Anne Case and Angus Deaton: “deaths of despair” Anne Case and Angus Deaton, “Mortality and Morbidity in the 21st Century,” Brookings Papers on Economic Activity, 2017, https://www.brookings.edu/​wp-content/​uploads/​2017/​03/​6_casedeaton.pdf.


pages: 602 words: 120,848

Winner-Take-All Politics: How Washington Made the Rich Richer-And Turned Its Back on the Middle Class by Paul Pierson, Jacob S. Hacker

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accounting loophole / creative accounting, active measures, affirmative action, asset allocation, barriers to entry, Bonfire of the Vanities, business climate, carried interest, Cass Sunstein, clean water, collective bargaining, corporate governance, Credit Default Swap, David Brooks, desegregation, employer provided health coverage, financial deregulation, financial innovation, financial intermediation, fixed income, full employment, Home mortgage interest deduction, Howard Zinn, income inequality, invisible hand, knowledge economy, laissez-faire capitalism, Martin Wolf, medical bankruptcy, moral hazard, Nate Silver, new economy, night-watchman state, offshore financial centre, oil shock, Powell Memorandum, Ralph Nader, Ronald Reagan, shareholder value, Silicon Valley, The Wealth of Nations by Adam Smith, too big to fail, trickle-down economics, union organizing, very high income, War on Poverty, winner-take-all economy, women in the workforce

On the conflicting estimates of the crowd size, see www.politifact.com/truth-o-meter/article/2009/sep/14/tea-party-photo-shows-large-crowd-different-event/. 53 CNN Opinion Research Poll of 1,023 adult Americans, including 954 registered voters, February 12–15, 2010, http://i2.cdn.turner.com/cnn/2010/images/02/17/rel4b.pdf. 54 Pew Research Center survey of 1,003 adult Americans, January 14–17, 2010, http://people-press.org/reports/questionnaires/586.pdf. 55 CNN Opinion Research Poll of 1,160 adult Americans, December 16–20, 2009, http://i2.cdn.turner.com/cnn/2009/images/12/21/rel19a.pdf. 56 Kaiser Health Tracking Poll of 2,002 American adults, January 7–12, 2010, ww.kff.org/kaiserpolls/upload/8042-C.pdf; Nate Silver, “Health Care Polls: Opinion Gap or Information Gap?” FiveThirtyEight.com, January 23, 2010, www.fivethirtyeight.com/2010/01/health-care-polls-opinion-gap-or.html. Conclusion: Beating Winner-Take-All 1 The golden ticket analogy has been offered by Gregory Mankiw, “The Wealth Trajectory: Rewards for the Few,” New York Times, April 20, 2008. 2 Ronald D. Orol, “If Senate OKs Bank Bill, Expect a Year of Debate,” Marketwatch.com, March 17, 2010. 3 “Gohmert Calls for Amendment Convention by States,” March 23, 2010, http://gohmert.house.gov/index.cfm?


pages: 561 words: 120,899

The Theory That Would Not Die: How Bayes' Rule Cracked the Enigma Code, Hunted Down Russian Submarines, and Emerged Triumphant From Two Centuries of Controversy by Sharon Bertsch McGrayne

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Bayesian statistics, bioinformatics, British Empire, Claude Shannon: information theory, Daniel Kahneman / Amos Tversky, double helix, Edmond Halley, Fellow of the Royal Society, full text search, Henri Poincaré, Isaac Newton, John Markoff, John Nash: game theory, John von Neumann, linear programming, meta analysis, meta-analysis, Nate Silver, p-value, Pierre-Simon Laplace, placebo effect, prediction markets, RAND corporation, recommendation engine, Renaissance Technologies, Richard Feynman, Richard Feynman, Richard Feynman: Challenger O-ring, Ronald Reagan, speech recognition, statistical model, stochastic process, Thomas Bayes, Thomas Kuhn: the structure of scientific revolutions, traveling salesman, Turing machine, Turing test, uranium enrichment, Yom Kippur War

As a result, the only large computerized Bayesian study of a practical problem in the public domain during the Bayesian revival of the 1960s was the Mosteller–Wallace study of The Federalist in 1964. It would be 11 years before the next major Bayesian application appeared in public. And after Tukey stopped consulting for NBC in 1980, it would be 28 years before a presidential election poll utilized Bayesian techniques again. When Nate Silver at FiveThirtyEight.com used hierarchical Bayes during the presidential race in November 2008, he combined information from outside areas to strengthen small samples from low-population areas and from exit polls with low response rates. He weighted the results of other pollsters according to their track records and sample size and how up to date their data were. He also combined them with historical polling data.


pages: 503 words: 131,064

Liars and Outliers: How Security Holds Society Together by Bruce Schneier

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airport security, barriers to entry, Berlin Wall, Bernie Madoff, Bernie Sanders, Brian Krebs, Broken windows theory, carried interest, Cass Sunstein, Chelsea Manning, commoditize, corporate governance, crack epidemic, credit crunch, crowdsourcing, cuban missile crisis, Daniel Kahneman / Amos Tversky, David Graeber, desegregation, don't be evil, Double Irish / Dutch Sandwich, Douglas Hofstadter, experimental economics, Fall of the Berlin Wall, financial deregulation, George Akerlof, hydraulic fracturing, impulse control, income inequality, invention of agriculture, invention of gunpowder, iterative process, Jean Tirole, John Nash: game theory, joint-stock company, Julian Assange, mass incarceration, meta analysis, meta-analysis, microcredit, moral hazard, mutually assured destruction, Nate Silver, Network effects, Nick Leeson, offshore financial centre, patent troll, phenotype, pre–internet, principal–agent problem, prisoner's dilemma, profit maximization, profit motive, race to the bottom, Ralph Waldo Emerson, RAND corporation, rent-seeking, RFID, Richard Thaler, risk tolerance, Ronald Coase, security theater, shareholder value, slashdot, statistical model, Steven Pinker, Stuxnet, technological singularity, The Market for Lemons, The Nature of the Firm, The Spirit Level, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, theory of mind, too big to fail, traffic fines, transaction costs, ultimatum game, UNCLOS, union organizing, Vernor Vinge, WikiLeaks, World Values Survey, Y2K, zero-sum game

strip-search every Electronic Privacy Information Center (10 Mar 2011), “DHS: We Have the Authority to Routinely Strip-Search Air Travelers,” press release. Electronic Privacy Information Center (15 Jul 2011), “Federal Appeals Court: TSA Violated Federal Law, Must Take Public Comment on Body Scanners,” press release. EPIC v. DHS (15 Jul 2011), Opinion, Case No. 10N1157. DC Circuit Court of Appeals, filed November 1, 2010. September 11 attacks Nate Silver (4 Jan 2010), “The Skies Are as Friendly as Ever: 9/11, Al Qaeda Obscure Statistics on Airline Safety,” FiveThirtyEight.com. scale is too large Bruce Schneier (2008), “Seven Habits of Highly Unsuccessful Terrorists,” Wired News. Max Abrams (2008), “What Terrorists Really Want,” International Security, 32:78–105. regulatory capture Jean J. Laffont and Jean Tirole (1991), “The Politics of Government Decision-Making: A Theory of Regulatory Capture,” The Quarterly Journal of Economics, 106:1089–127.


pages: 598 words: 134,339

Data and Goliath: The Hidden Battles to Collect Your Data and Control Your World by Bruce Schneier

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23andMe, Airbnb, airport security, AltaVista, Anne Wojcicki, augmented reality, Benjamin Mako Hill, Black Swan, Brewster Kahle, Brian Krebs, call centre, Cass Sunstein, Chelsea Manning, citizen journalism, cloud computing, congestion charging, disintermediation, drone strike, Edward Snowden, experimental subject, failed state, fault tolerance, Ferguson, Missouri, Filter Bubble, Firefox, friendly fire, Google Chrome, Google Glasses, hindsight bias, informal economy, Internet Archive, Internet of things, Jacob Appelbaum, Jaron Lanier, John Markoff, Julian Assange, Kevin Kelly, license plate recognition, lifelogging, linked data, Lyft, Mark Zuckerberg, moral panic, Nash equilibrium, Nate Silver, national security letter, Network effects, Occupy movement, payday loans, pre–internet, price discrimination, profit motive, race to the bottom, RAND corporation, recommendation engine, RFID, self-driving car, Shoshana Zuboff, Silicon Valley, Skype, smart cities, smart grid, Snapchat, social graph, software as a service, South China Sea, stealth mode startup, Steven Levy, Stuxnet, TaskRabbit, telemarketer, Tim Cook: Apple, transaction costs, Uber and Lyft, urban planning, WikiLeaks, zero day

Stewart (2011), Terror, Security, and Money: Balancing the Risks, Benefits, and Costs of Homeland Security, Oxford University Press, chap. 9, http://books.google.com/books? id=l1IrmjCdguYC&pg=PA172. it’s well past time to move beyond fear: I even wrote a book with that title. Bruce Schneier (2003), Beyond Fear: Thinking Sensibly about Security in an Uncertain World, Wiley, http://books.google.com/books/about/? id=wuNImmQufGsC. shift in Americans’ perceptions: Nate Silver (10 Jul 2013), “Public opinion shifts on security-liberty balance,” Fivethirtyeight, New York Times, http://fivethirtyeight.blogs.nytimes.com/2013/07/10/public-opinion-shifts-onsecurity-liberty-balance. Our personal definitions of privacy: New York University law professor Helen Nissenbaum argues that privacy can only be properly understood in terms of context and expectations. Helen Nissenbaum (Fall 2011), “A contextual approach to privacy online,” Daedalus 11, http://www.amacad.org/publications/daedalus/11_fall_nissenbaum.pdf.

The End of Power: From Boardrooms to Battlefields and Churches to States, Why Being in Charge Isn’t What It Used to Be by Moises Naim

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additive manufacturing, barriers to entry, Berlin Wall, bilateral investment treaty, business process, business process outsourcing, call centre, citizen journalism, Clayton Christensen, clean water, collapse of Lehman Brothers, collective bargaining, colonial rule, conceptual framework, corporate governance, creative destruction, crony capitalism, deskilling, disintermediation, don't be evil, failed state, Fall of the Berlin Wall, financial deregulation, Francis Fukuyama: the end of history, illegal immigration, immigration reform, income inequality, income per capita, intangible asset, intermodal, invisible hand, job-hopping, Joseph Schumpeter, Julian Assange, Kickstarter, liberation theology, Martin Wolf, mega-rich, megacity, Naomi Klein, Nate Silver, new economy, Northern Rock, Occupy movement, open borders, open economy, Peace of Westphalia, Plutocrats, plutocrats, price mechanism, price stability, private military company, profit maximization, Ronald Coase, Ronald Reagan, Silicon Valley, Skype, Steve Jobs, The Nature of the Firm, Thomas Malthus, too big to fail, trade route, transaction costs, Washington Consensus, WikiLeaks, World Values Survey, zero-sum game

(It should be noted, however, that David Wood, the Pulitzer Prize–winner at The Huffington Post, has decades of reporting experience.) Meanwhile, the ease of publishing on the Internet has turned blogs on everything from electoral politics to fiscal policy, rock music, and business travel into credible and revenue-earning specialty sources that often outperform beat reporters and magazine analysts. Consider the case of statistics geek Nate Silver, who applied the skills he honed crunching baseball numbers to the 2008 and 2012 US presidential campaigns on his site fivethirtyeight.com. Using his own model to aggregate polling data, Silver was able to predict the outcome of the Super Tuesday primaries between Barack Obama and Hillary Clinton; he went on to predict Obama’s defeat of John McCain as early as March 2008, and his detailed predictions on Election Night got forty-nine out of fifty states right, and in the 2012 elections also predicted accurately the results.


pages: 677 words: 206,548

Future Crimes: Everything Is Connected, Everyone Is Vulnerable and What We Can Do About It by Marc Goodman

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23andMe, 3D printing, active measures, additive manufacturing, Affordable Care Act / Obamacare, Airbnb, airport security, Albert Einstein, algorithmic trading, artificial general intelligence, Asilomar, Asilomar Conference on Recombinant DNA, augmented reality, autonomous vehicles, Baxter: Rethink Robotics, Bill Joy: nanobots, bitcoin, Black Swan, blockchain, borderless world, Brian Krebs, business process, butterfly effect, call centre, Chelsea Manning, cloud computing, cognitive dissonance, computer vision, connected car, corporate governance, crowdsourcing, cryptocurrency, data acquisition, data is the new oil, Dean Kamen, disintermediation, don't be evil, double helix, Downton Abbey, drone strike, Edward Snowden, Elon Musk, Erik Brynjolfsson, Filter Bubble, Firefox, Flash crash, future of work, game design, Google Chrome, Google Earth, Google Glasses, Gordon Gekko, high net worth, High speed trading, hive mind, Howard Rheingold, hypertext link, illegal immigration, impulse control, industrial robot, Intergovernmental Panel on Climate Change (IPCC), Internet of things, Jaron Lanier, Jeff Bezos, job automation, John Harrison: Longitude, John Markoff, Jony Ive, Julian Assange, Kevin Kelly, Khan Academy, Kickstarter, knowledge worker, Kuwabatake Sanjuro: assassination market, Law of Accelerating Returns, Lean Startup, license plate recognition, lifelogging, litecoin, M-Pesa, Mark Zuckerberg, Marshall McLuhan, Menlo Park, Metcalfe’s law, mobile money, more computing power than Apollo, move fast and break things, move fast and break things, Nate Silver, national security letter, natural language processing, obamacare, Occupy movement, Oculus Rift, off grid, offshore financial centre, optical character recognition, Parag Khanna, pattern recognition, peer-to-peer, personalized medicine, Peter H. Diamandis: Planetary Resources, Peter Thiel, pre–internet, RAND corporation, ransomware, Ray Kurzweil, refrigerator car, RFID, ride hailing / ride sharing, Rodney Brooks, Satoshi Nakamoto, Second Machine Age, security theater, self-driving car, shareholder value, Silicon Valley, Silicon Valley startup, Skype, smart cities, smart grid, smart meter, Snapchat, social graph, software as a service, speech recognition, stealth mode startup, Stephen Hawking, Steve Jobs, Steve Wozniak, strong AI, Stuxnet, supply-chain management, technological singularity, telepresence, telepresence robot, Tesla Model S, The Future of Employment, The Wisdom of Crowds, Tim Cook: Apple, trade route, uranium enrichment, Wall-E, Watson beat the top human players on Jeopardy!, Wave and Pay, We are Anonymous. We are Legion, web application, Westphalian system, WikiLeaks, Y Combinator, zero day

On a daily basis, cyber attacks disrupt our financial system, thieves steal billions in intellectual property, foreign nations pilfer our military weapons plans, and hackers share online tips with one another on how to take over the industrial control systems that run everything from power plants to water and sewage treatment facilities. To paraphrase the renowned statistician and editor of the FiveThirtyEight blog, Nate Silver, our current lackadaisical approach to cyber security and the profound technological vulnerabilities before us has been until this point akin to applying sunscreen and claiming it protects us from a nuclear meltdown—wholly inadequate to the scale of the problem. It is time for a stone-cold somber rethinking of our current state of affairs. It’s time for a Manhattan Project for cyber security.


pages: 593 words: 189,857

Stress Test: Reflections on Financial Crises by Timothy F. Geithner

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Affordable Care Act / Obamacare, asset-backed security, Atul Gawande, bank run, banking crisis, Basel III, Bernie Madoff, Bernie Sanders, break the buck, Buckminster Fuller, Carmen Reinhart, central bank independence, collateralized debt obligation, correlation does not imply causation, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, currency manipulation / currency intervention, David Brooks, Doomsday Book, eurozone crisis, financial innovation, Flash crash, Goldman Sachs: Vampire Squid, housing crisis, Hyman Minsky, illegal immigration, implied volatility, London Interbank Offered Rate, Long Term Capital Management, margin call, market fundamentalism, Martin Wolf, McMansion, Mexican peso crisis / tequila crisis, money market fund, moral hazard, mortgage debt, Nate Silver, negative equity, Northern Rock, obamacare, paradox of thrift, pets.com, price stability, profit maximization, pushing on a string, quantitative easing, race to the bottom, RAND corporation, regulatory arbitrage, reserve currency, Saturday Night Live, savings glut, selection bias, short selling, sovereign wealth fund, The Great Moderation, The Signal and the Noise by Nate Silver, Tobin tax, too big to fail, working poor

But the investors, reaching for yield, had shown little interest in the safest tranches, the “super-senior” CDOs that would pay out in full unless mortgage losses were so severe that investors in every tranche below them were wiped out. That seemed highly unlikely, so Merrill usually kept the super-seniors on its balance sheet. Their modest returns were still more than the cost of financing them, and they seemed almost bulletproof. Standard & Poor’s estimated a mere 0.12 percent chance that one of its AAA-rated CDOs would fail to pay out over five years—and super-seniors were considered safer than typical AAAs. But as Nate Silver noted in The Signal and the Noise, his excellent book about why many predictions fail, the actual default rate for AAA-rated tranches of CDOs would be 28 percent, more than two hundred times higher than S&P had predicted. Their perceived safety rested on all kinds of flawed assumptions, starting with the notion that housing prices would never fall simultaneously across the country. CDOs were often spliced together from geographically diverse piles of subprime mortgages, which was supposed to mitigate the effects of a housing slump in any one region.


pages: 554 words: 167,247

Money, Politics, Back-Room Deals, and the Fight to Fix Our Broken Healthcare System by Steven Brill

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Affordable Care Act / Obamacare, barriers to entry, Bernie Sanders, business process, call centre, collapse of Lehman Brothers, collective bargaining, crony capitalism, desegregation, Donald Trump, Edward Snowden, employer provided health coverage, medical malpractice, Menlo Park, Nate Silver, obamacare, Potemkin village, Ronald Reagan, Saturday Night Live, side project, Silicon Valley, the payments system, young professional

It sounds like the Obama campaign. And administration officials don’t shy away from the comparison. Even Jeanne Lambrew—who was supposed to be the White House official overseeing the website build—agreed that Simas’s work was what the launch was all about: “When I hear the conventional wisdom about Obamacare,” she told the Post, “this is the difference between the Karl Roves who put their fingers to the wind and the Nate Silvers of the world who looked at the numbers.” Implementing President Obama’s most important domestic policy seemed to be all about campaigning, not about governing. The officials at CMS and HHS whom I interviewed during the summer of 2013 were similarly focused. I was regaled with stories about the demographic targeting being done. In fact, the CMS staff claimed that its data, more than that supplied by Civis, was fueling the campaign.


pages: 554 words: 167,247

America's Bitter Pill: Money, Politics, Backroom Deals, and the Fight to Fix Our Broken Healthcare System by Steven Brill

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Affordable Care Act / Obamacare, barriers to entry, Bernie Sanders, business process, call centre, collapse of Lehman Brothers, collective bargaining, crony capitalism, desegregation, Donald Trump, Edward Snowden, employer provided health coverage, medical malpractice, Menlo Park, Nate Silver, obamacare, Potemkin village, Ronald Reagan, Saturday Night Live, side project, Silicon Valley, the payments system, young professional

It sounds like the Obama campaign. And administration officials don’t shy away from the comparison. Even Jeanne Lambrew—who was supposed to be the White House official overseeing the website build—agreed that Simas’s work was what the launch was all about: “When I hear the conventional wisdom about Obamacare,” she told the Post, “this is the difference between the Karl Roves who put their fingers to the wind and the Nate Silvers of the world who looked at the numbers.” Implementing President Obama’s most important domestic policy seemed to be all about campaigning, not about governing. The officials at CMS and HHS whom I interviewed during the summer of 2013 were similarly focused. I was regaled with stories about the demographic targeting being done. In fact, the CMS staff claimed that its data, more than that supplied by Civis, was fueling the campaign.