Nate Silver

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

8-hour work day, Albert Einstein, barriers to entry, behavioural economics, Bluma Zeigarnik, business climate, Cal Newport, Capital in the Twenty-First Century by Thomas Piketty, Clayton Christensen, David Brooks, David Heinemeier Hansson, deliberate practice, digital divide, disruptive innovation, do what you love, Donald Knuth, Donald Trump, Downton Abbey, en.wikipedia.org, Erik Brynjolfsson, Evgeny Morozov, experimental subject, follow your passion, Frank Gehry, Hacker News, Higgs boson, informal economy, information retrieval, Internet Archive, Jaron Lanier, knowledge worker, Mark Zuckerberg, Marshall McLuhan, Merlin Mann, Nate Silver, Neal Stephenson, new economy, Nicholas Carr, popular electronics, power law, remote working, Richard Feynman, Ruby on Rails, seminal paper, Silicon Valley, Silicon Valley startup, Snapchat, statistical model, the medium is the message, Tyler Cowen, Watson beat the top human players on Jeopardy!, web application, winner-take-all economy, work culture , 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?”

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“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. Information about David Heinemeier Hansson comes from the following websites: • David Heinemeier Hanson. http://david.heinemeierhansson.com/. • Lindberg, Oliver. “The Secrets Behind 37signals’ Success.” TechRadar, September 6, 2010. http://www.techradar.com/us/news/internet/the-secrets-behind-37signals-success-712499

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“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

Strength in Numbers: How Polls Work and Why We Need Them by G. Elliott Morris

affirmative action, call centre, Cambridge Analytica, commoditize, coronavirus, COVID-19, critical race theory, data science, Donald Trump, Francisco Pizarro, green new deal, lockdown, Moneyball by Michael Lewis explains big data, Nate Silver, random walk, Ronald Reagan, selection bias, Silicon Valley, Socratic dialogue, statistical model, Works Progress Administration

Blumenthal, “Polls, Forecasts, and Aggregators.” 4. Charles Franklin, interview with the author, February 3, 2021. 5. Mark Blumenthal, interview with the author, February 3, 2021. 6. Blumenthal, interview, February 3, 2021. 7. Nate Silver, “General Election Projections, Beta Version,” Daily Kos, February 26, 2008, https://www.dailykos.com/stories/2008/2/26/464643/-General-Election-Projections-Beta-Version. 8. Nate Silver (@natesilver538), “Today is the 10-year anniversary of http://FiveThirtyEight.com! Can’t believe I’ve been doing this for a decade now. Thanks to y’all for reading and here’s to 10 more years ahead,” Twitter, March 7, 2018, https://twitter.com/natesilver538/status/971422777235226624?

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Shirani-Mehr Houshmand, David Rothschild, Sharad Goel, and Andrew Gelman, “Disentangling Bias and Variance in Election Polls,” Journal of the American Statistical Association 113 (2018): 522: 607–14. CHAPTER 7: TAKING THE PULSE OF THE PULSE OF DEMOCRACY 1. Jamelle Bouie, “There Is No Horse Race,” Slate, August 24, 2016, https://slate.com/news-and-politics/2016/08/there-is-no-clinton-trump-horce-race.html. 2. Ryan Grim, “Nate Silver Is Unskewing Polls—All of Them—in Trump’s Direction,” Huffington Post, November 5, 2016, https://www.huffpost.com/entry/nate-silver-election-forecast_n_581e1c33e4b0d9ce6fbc6f7f. 3. Nolan McCaskill, “Trump Tells Wisconsin: Victory Was a Surprise,” Politico, December 13, 2016, https://slate.com/news-and-politics/2016/08/there-is-no-clinton-trump-horce-race.html. 4.

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As Cohn put it, “the problem is that it’s very difficult to distinguish these statements from weighting toward a desired result,” something Cohn acknowledged it was impossible to prove—but troubling because it was “totally possible.”25 Public Policy Polling is hardly the only public polling company that has been scrutinized for allegedly tweaking their methodology to stay close to polling averages. Take the case of the right-leaning pollster Rasmussen Reports, which puzzlingly deleted a poll of the 2014 Kansas Senate race from its website shortly after it was released. At the time, political blogger Harry Enten and FiveThirtyEight’s Nate Silver wondered whether the firm did so because they “got cold feet” when CNN and Fox News published polls with which Rasmussen’s was far out of line. Confronted by Enten, a representative for the firm said the numbers were actually deleted because they were “basically raw data”—unpublished numbers that hadn’t been weighted or checked for errors—that had been published inadvertently.

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

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

When the victory failed to materialise, the New York Times published an article (headlined: ‘How data failed us in calling an election’) that proclaimed the number crunchers had had a rough night.3 It listed supposed problems in both their own model (the newspaper’s Upshot model had given Clinton a 91 per cent chance of winning) and the approach taken by Nate Silver and FiveThirtyEight. The newspaper was blaming statisticians for its own inability to account for uncertainty. For Silver, this was just one example of how the media finds it very difficult to write sensible articles based on probabilistic reasoning.4 What struck me, looking at how FiveThirtyEight had evolved over the past 10 years, was that the site provides a powerful case study of the limits of mathematical models. Nate Silver had been propelled to a position of authority. He had accumulated financial resources (FiveThirtyEight is owned by ESPN) that had allowed him to build sophisticated models based on large quantities of reliable data.

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But I was falling into the same trap as Nate Silver. I was forgetting that the outcome of the US presidential election was crucial to the lives of so many people. Mona told me that the real danger is that, ‘FiveThirtyEight potentially influences voter behaviour. The millions of people visiting the site on election day aren’t reading through Nate’s model to find out how it works. These are people who are looking at those two numbers for Clinton and Trump, and they are concluding that Clinton is going to win.’ We are outnumbered by statistical experts like Nate Silver because we believe that they have a better answer than we do.

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Also available in the Bloomsbury Sigma series: Sex on Earth by Jules Howard p53: The Gene that Cracked the Cancer Code by Sue Armstrong Atoms Under the Floorboards by Chris Woodford Spirals in Time by Helen Scales Chilled by Tom Jackson A is for Arsenic by Kathryn Harkup Breaking the Chains of Gravity by Amy Shira Teitel Suspicious Minds by Rob Brotherton Herding Hemingway’s Cats by Kat Arney Electronic Dreams by Tom Lean Sorting the Beef from the Bull by Richard Evershed and Nicola Temple Death on Earth by Jules Howard The Tyrannosaur Chronicles by David Hone Soccermatics by David Sumpter Big Data by Timandra Harkness Goldilocks and the Water Bears by Louisa Preston Science and the City by Laurie Winkless Bring Back the King by Helen Pilcher Furry Logic by Matin Durrani and Liz Kalaugher Built on Bones by Brenna Hassett My European Family by Karin Bojs 4th Rock from the Sun by Nicky Jenner Patient H69 by Vanessa Potter Catching Breath by Kathryn Lougheed PIG/PORK by Pía Spry-Marqués The Planet Factory by Elizabeth Tasker Wonders Beyond Numbers by Johnny Ball Immune by Catherine Carver I, Mammal by Liam Drew Reinventing the Wheel by Bronwen and Francis Percival Making the Monster by Kathryn Harkup Best Before by Nicola Temple Catching Stardust by Natalie Starkey Seeds of Science by Mark Lynas Contents PART 1: ANALYSING US Chapter 1: Finding Banksy Chapter 2: Make Some Noise Chapter 3: The Principal Components of Friendship Chapter 4: One Hundred Dimensions of You Chapter 5: Cambridge Hyperbolytica Chapter 6: Impossibly Unbiased Chapter 7: The Data Alchemists PART 2: INFLUENCING US Chapter 8: Nate Silver vs the Rest of Us Chapter 9: We ‘Also Liked’ the Internet Chapter 10: The Popularity Contest Chapter 11: Bubbling Up Chapter 12: Football Matters Chapter 13: Who Reads Fake News? PART 3: BECOMING US Chapter 14: Learning to be Sexist Chapter 15: The Only Thought Between the Decimal Chapter 16: Kick Your Ass at Space Invaders Chapter 17: The Bacterial Brain Chapter 18: Back to Reality Notes Acknowledgements Index PART ONE Analysing Us CHAPTER ONE Finding Banksy In March 2016, three researchers from London and a criminologist from Texas published a paper in the Journal of Spatial Science.

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

airport security, Alan Greenspan, Alvin Toffler, An Inconvenient Truth, availability heuristic, Bayesian statistics, Bear Stearns, behavioural economics, Benoit Mandelbrot, Berlin Wall, Bernie Madoff, big-box store, Black Monday: stock market crash in 1987, Black Swan, Boeing 747, book value, Broken windows theory, business cycle, buy and hold, Carmen Reinhart, Charles Babbage, classic study, 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, disinformation, 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, Ford Model T, Freestyle chess, fudge factor, Future Shock, George Akerlof, global pandemic, Goodhart's law, haute cuisine, Henri Poincaré, high batting average, housing crisis, income per capita, index fund, information asymmetry, Intergovernmental Panel on Climate Change (IPCC), Internet Archive, invention of the printing press, invisible hand, Isaac Newton, James Watt: steam engine, Japanese asset price bubble, John Bogle, John Nash: game theory, John von Neumann, Kenneth Rogoff, knowledge economy, Laplace demon, 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, Oklahoma City bombing, PageRank, pattern recognition, pets.com, Phillips curve, Pierre-Simon Laplace, Plato's cave, power law, prediction markets, Productivity paradox, proprietary trading, public intellectual, random walk, Richard Thaler, Robert Shiller, Robert Solow, Rodney Brooks, Ronald Reagan, Saturday Night Live, savings glut, security theater, short selling, SimCity, 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, Timothy McVeigh, too big to fail, transaction costs, transfer pricing, University of East Anglia, Watson beat the top human players on Jeopardy!, Wayback Machine, 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.

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Douglas Harper, Online Etymology Dictionary. http://www.etymonline.com/index.php?term=objective. CHAPTER 3: ALL I CARE ABOUT IS W’S AND L’S 1. Nate Silver in Jonah Keri, et al., Baseball Between the Numbers: Why Everything You Know About the Game Is Wrong (New York: Basic Books, 2006). 2. Danny Knobler, “The Opposite of a ‘Tools Guy,’ Pedroia’s Simply a Winner,” CBSSports.com, November 18, 2008. http://www.cbssports.com/mlb/story/11116048. 3. Nate Silver, “Lies, Damned Lies: PECOTA Takes on Prospects, Wrap-up,” BaseballProspectus.com, March 8, 2006. http://www.baseballprospectus.com/article.php?

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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?

Thinking in Bets by Annie Duke

banking crisis, behavioural economics, Bernie Madoff, Cass Sunstein, cognitive bias, cognitive dissonance, cognitive load, Daniel Kahneman / Amos Tversky, delayed gratification, Demis Hassabis, disinformation, Donald Trump, Dr. Strangelove, en.wikipedia.org, endowment effect, Estimating the Reproducibility of Psychological Science, fake news, Filter Bubble, Herman Kahn, hindsight bias, Jean Tirole, John Nash: game theory, John von Neumann, loss aversion, market design, mutually assured destruction, Nate Silver, p-value, phenotype, prediction markets, Richard Feynman, ride hailing / ride sharing, Stanford marshmallow experiment, Stephen Hawking, Steven Pinker, systematic bias, TED Talk, the scientific method, The Signal and the Noise by Nate Silver, urban planning, Walter Mischel, Yogi Berra, zero-sum game

Hillary Clinton had been favored going into the election, and her probability of winning, based on an accumulation of the polls, was somewhere between 60% and 70%, according to FiveThirtyEight.com. When Donald Trump won, pollsters got the Pete Carroll treatment, maybe no one more than Nate Silver, founder of FiveThirtyEight.com and a thoughtful analyzer of polling data. (“Nate Silver was wrong.” “The pollsters missed it.” “Just like Brexit, the bookies blew it.” Etc.) The press spun this as a certain win for Clinton, despite the Trump branch of the tree being no mere twig at 30%–40%. By the day after the election, the Clinton branch had been severed, only the Trump branch remained, and how could pollsters and the polling process have been so blind?

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Mistaking Odds for Wrong When the Underdog Wins,” Huffington Post, September 21, 2016, http://www.huffingtonpost.com/annie-duke/even-dershowitz-mistaking_b_12120592.html. Nate Silver and his website, FiveThirtyEight.com, bore the brunt of the criticism for pollsters and forecasters after the 2016 presidential election. Silver’s site updated, in real time, polling and forecasting data on the election and had (depending on the date) the probability of a Clinton victory at approximately 60%–70%. If you Google (without the quotation marks) “Nate Silver got it wrong election,” 465,000 results come up. Politico’s November 9 headline was “How Did Everyone Get It So Wrong?

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Politico’s November 9 headline was “How Did Everyone Get It So Wrong?,” http://www.politico.com/story/2016/11/how-did-everyone-get-2016-wrong-presidential-election-231036. Gizmodo.com jumped on Silver even before the election, in a November 4 article by Matt Novak titled “Nate Silver’s Very Very Wrong Predictions About Donald Trump Are Terrifying,” http://paleofuture.gizmodo.com/nate-silvers-very-very-wrong-predictions-about-donald-t-1788583912, including the declaration, “Silver has no f**king idea.” CHAPTER 2: WANNA BET? Hearing is believing: The quote about baldness is from Susan Scutti, “Going Bald Isn’t Your Mother’s Fault; Maternal Genetics Are Not to Blame,” Medical Daily, May 18, 2015, http://www.medicaldaily.com/going-bald-isnt-your-mothers-fault-maternal-genetics-are-not-blame-333668.

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, Black Lives Matter, Cass Sunstein, computer vision, content marketing, correlation does not imply causation, crowdsourcing, Daniel Kahneman / Amos Tversky, data science, desegregation, Donald Trump, Edward Glaeser, Filter Bubble, game design, happiness index / gross national happiness, income inequality, Jeff Bezos, Jeff Seder, John Snow's cholera map, longitudinal study, Mark Zuckerberg, Nate Silver, Nick Bostrom, 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

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.

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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?

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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.

Dataclysm: Who We Are (When We Think No One's Looking) by Christian Rudder

4chan, Affordable Care Act / Obamacare, bitcoin, cloud computing, correlation does not imply causation, crowdsourcing, cuban missile crisis, data science, Donald Trump, Edward Snowden, en.wikipedia.org, fake it until you make it, Frank Gehry, Howard Zinn, Jaron Lanier, John Markoff, John Snow's cholera map, lifelogging, Mahatma Gandhi, Mikhail Gorbachev, Nate Silver, Nelson Mandela, new economy, obamacare, Occupy movement, p-value, power law, pre–internet, prosperity theology / prosperity gospel / gospel of success, race to the bottom, retail therapy, Salesforce, selection bias, Snapchat, social graph, Steve Jobs, the scientific method, the strength of weak ties, Twitter Arab Spring, two and twenty

If men from such different environments as Mississippi and Massachusetts are looking for gay porn at equal rates, that’s strong evidence that supposed external forces have little effect on same-sex attraction. The second implication of the state-by-state sameness in the data—that is, what it reveals not so much about gay people but about intolerance—needs a little time to unfurl. In early 2013, when he was still covering politics for the Times, Nate Silver applied his famous poll-modeling technique to same-sex-marriage ballot initiatives across the country. As he had done in the presidential elections, he aggregated data to get a snapshot of public opinion in each state, and then he performed some forward-looking analysis to guess how those attitudes might evolve.

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On the other, it means that for every person picking up and moving to a San Francisco or a New York City to live life fully, there are likely dozens still living in self-negation. If you accept these two independent estimates of 5 percent, arrived at using three of the biggest forces in modern data—Nate Silver, Google, and Facebook, with an assist from that standby of old-school polling, Gallup—you begin to see those self-reported numbers in a different light. When Gallup tells us that, for example, 1.7 percent of North Dakotans are gay, then perhaps something like 3.3 percent of the state is gay and unwilling to acknowledge it.

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That said, for all the crassness of sexual-identity-as-business-plan, it’s a hopeful sign when a minority identity is something the mainstream thinks is worth co-opting instead of suppressing. Indeed, for sexuality, we see that things are changing, and quickly. Devising the projections we looked at above, Nate Silver clocked a marked change in American attitudes in the last decade. Acceptance of gay marriage accelerated markedly in 2004—and he determined, “One no longer needs to make optimistic assumptions to conclude that same-sex marriage supporters will probably soon constitute a national majority.” Thus, it all comes back to counting, and the fraction is going our way.

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

Affordable Care Act / Obamacare, Any sufficiently advanced technology is indistinguishable from magic, availability heuristic, behavioural economics, Black Swan, butterfly effect, buy and hold, cloud computing, cognitive load, cuban missile crisis, Daniel Kahneman / Amos Tversky, data science, desegregation, drone strike, Edward Lorenz: Chaos theory, forward guidance, Freestyle chess, fundamental attribution error, germ theory of disease, hindsight bias, How many piano tuners are there in Chicago?, index fund, Jane Jacobs, Jeff Bezos, Kenneth Arrow, Laplace demon, longitudinal study, Mikhail Gorbachev, Mohammed Bouazizi, Nash equilibrium, Nate Silver, Nelson Mandela, obamacare, operational security, pattern recognition, performance metric, Pierre-Simon Laplace, place-making, placebo effect, precautionary principle, prediction markets, quantitative easing, random walk, randomized controlled trial, Richard Feynman, Richard Thaler, Robert Shiller, Ronald Reagan, Saturday Night Live, scientific worldview, Silicon Valley, Skype, statistical model, stem cell, Steve Ballmer, Steve Jobs, Steven Pinker, tacit knowledge, tail risk, 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!

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.

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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!”

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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.

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

Alan Greenspan, Albert Einstein, algorithmic trading, Amazon Mechanical Turk, Apollo 11, Apple's 1984 Super Bowl advert, backtesting, Black Swan, book scanning, bounce rate, business intelligence, business process, butter production in bangladesh, call centre, Charles Lindbergh, commoditize, computer age, conceptual framework, correlation does not imply causation, crowdsourcing, dark matter, data is the new oil, data science, driverless car, en.wikipedia.org, Erik Brynjolfsson, Everything should be made as simple as possible, experimental subject, Google Glasses, happiness index / gross national happiness, information security, job satisfaction, Johann Wolfgang von Goethe, lifelogging, machine readable, 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, Shai Danziger, software as a service, SpaceShipOne, speech recognition, statistical model, Steven Levy, supply chain finance, text mining, the scientific method, The Signal and the Noise by Nate Silver, The Wisdom of Crowds, Thomas Bayes, Thomas Davenport, Turing test, Watson beat the top human players on Jeopardy!, X Prize, Yogi Berra, zero-sum game

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.”

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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!”

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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!

Occupy by Noam Chomsky

Alan Greenspan, corporate governance, corporate personhood, deindustrialization, high-speed rail, 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.

Why We're Polarized by Ezra Klein

affirmative action, Affordable Care Act / Obamacare, barriers to entry, Bernie Sanders, Black Lives Matter, Cass Sunstein, centre right, Climategate, collapse of Lehman Brothers, currency manipulation / currency intervention, David Brooks, demographic transition, desegregation, disinformation, Donald Trump, ending welfare as we know it, fake news, Ferguson, Missouri, illegal immigration, immigration reform, microaggression, Nate Silver, no-fly zone, obamacare, Ralph Nader, Ronald Reagan, Silicon Valley, single-payer health, source of truth, systems thinking

Lamar Smith of Texas,” Vox, January 27, 2017, vox.com/science-and-health/2017/1/27/14395978/donald-trump-lamar-smith. 16 David Hookstead, “This Sexy Model Is Blowing Up the Internet [SLIDESHOW],” Daily Caller, December 16, 2016, dailycaller.com/2016/12/16/this-sexy-model-is-blowing-up-the-internet-slideshow/; David Hookstead, “This UFC Octagon Girl’s Instagram Account Is Sizzling Hot [SLIDESHOW],” Daily Caller, December 24, 2016, dailycaller.com/2016/12/24/this-ufc-octagon-girls-instagram-account-is-sizzling-hot-slideshow/; Kaitlan Collins, “13 Syrian Refugees We’d Take Immediately [PHOTOS],” Dailey Caller, November 18, 2015, dailycaller.com/2015/11/18/13-syrian-refugees-wed-take-immediately-photos/. 17 Jonathan A. Rodden, Why Cities Lose: The Deep Roots of the Urban-Rural Political Divide (New York: Basic Books, 2019). 18 Ezra Klein, “What Nate Silver’s Learned Abouty Forecasting Elections,” Vox, October 23, 2018, vox.com/ezra-klein-show-podcast/2018/10/23/18014156/nate-silver-538-forecasting-2018-2020-ezra-klein-podcast. 19 Osita Nwanevu, “How Much Do Democrats Need to Win By?” Slate, March 27, 2018, slate.com/news-and-politics/2018/03/how-much-do-democrats-need-to-win-by.html. 20 Michael Geruso, Dean Spears, and Ishaana Talesara, “Inversions in US Presidential Elections: 1836–2016,” National Bureau of Economics Research, Working Paper No. 26247 (September 2019), nber.org/papers/w26247. 21 “Morning Consult’s Governor Approval Rankings,” Morning Consult, Q2 2019, morningconsult.com/governor-rankings-q2-19/. 22 Theda Skocpol and Vanessa Williamson, The Tea Party and the Remaking of Republican Conservatism (New York: Oxford University Press, 2012). 23 Publius Decius Mus [Michael Anton], “The Flight 93 Election,” Claremont Review of Books, September 5, 2016, claremont.org/crb/basicpage/the-flight-93-election. 24 Megan Brenan, “Democrats Favor More Moderate Party; GOP, More Conservative,” Gallup, December 12, 2018, news.gallup.com/poll/245462/democrats-favor-moderate-party-gop-conservative.aspx.

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I launched Wonkblog, the online policy vertical at the Washington Post, and I was a cofounder and the first editor in chief of the explanatory news organization Vox, which now reaches more than 50 million people each month. When I was launching Vox, I often got asked who our competitors were.I The answer people expected me to give was other politics-heavy news and analysis sites. The Atlantic. Nate Silver’s FiveThirtyEight. The Washington Post. But the truth was that other news sites were less competitors than they were collaborators in a shared effort to engage people in politics. If Silver converted a sports fan into a politics junkie, that person became instantly more likely to read Vox’s political coverage.

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My point here is not that this is unjust, though I believe it is. Instead, I want to focus on the way this system restrains polarization among Democrats and unleashes it among Republicans. To win, Democrats don’t just need to appeal to the voter in the middle. They need to appeal to voters well to the right of the middle. In the Senate, FiveThirtyEight’s Nate Silver estimates the average state is six points more Republican than the average voter.18 So when Democrats compete for the Senate, they are forced to appeal to an electorate that is far more conservative than the country as a whole. Similarly, it’s estimated that Democrats need to win a substantial majority in the House popular vote to take the gavel.19 And the fact that Democrats have lost two of the last five presidential elections due to the electoral college—the only times that’s happened in American history—signals a growing imbalance there also.

Hate Inc.: Why Today’s Media Makes Us Despise One Another by Matt Taibbi

4chan, affirmative action, anti-communist, Berlin Wall, Bernie Sanders, Chelsea Manning, commoditize, crack epidemic, David Brooks, disinformation, Donald Trump, drone strike, failed state, fake news, Fall of the Berlin Wall, false flag, financial deregulation, Francis Fukuyama: the end of history, Glass-Steagall Act, Gordon Gekko, greed is good, green new deal, Howard Zinn, illegal immigration, immigration reform, interest rate swap, Julian Assange, Kickstarter, Marshall McLuhan, microdosing, moral panic, Nate Silver, no-fly zone, Parents Music Resource Center, Peter Thiel, pink-collar, Ponzi scheme, pre–internet, profit motive, quantitative easing, Ralph Nader, rent-seeking, rolodex, Ronald Reagan, Rubik’s Cube, Saturday Night Live, Seymour Hersh, Silicon Valley, social contagion, Stephen Hawking, Steve Bannon, Steven Pinker, Tipper Gore, traveling salesman, unpaid internship, WikiLeaks, working poor, Y2K

The presidential election especially was reconfigured into a sports coverage saga. It was perfect: eighteen months of scheduled contests, a preseason (straw polls), regular season (primaries), and playoffs (the general), stadium events, a sub-genre of data reporting (it’s not an accident that sabermetrics guru Nate Silver fit so seamlessly into political coverage). TV news stations baldly copied visual “live variety” sports formats for coverage of primary elections, debates, election night, and soon enough, Sunday “discussion” shows like Meet the Press. If you’ve noticed, the sets bear an eerie resemblance to NFL pre-game shows.

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The flip side of the Bias con—why it works, despite its pretty transparent stupidity—is that most working journalists are too self-serious to admit the true part of it. We constantly validate right-wing caricatures of us as humorless upper-class snobs. Here’s the argument espoused by most working reporters on the Why Do They Hate Us? debate: 1.Most of the distrust of the media is found among conservatives. Statistician/poll guru Nate Silver, a onetime baseball stats nerd who has somehow become the High Data Mullah of All Things since he began writing about politics, summed it up in simple terms. “Republicans hate the media a lot, and Democrats hate the media a little.” 2.Those discontented Republican voters, the thinking goes, are really upset because they just can’t deal with reality.

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He had no “ground game,” a characteristic normally cited as a crucial factor. He was also an adulterer and ignorant of the Bible, running in a primary whose constituents supposedly treasured religion. By every conceivable standard of conventional wisdom, Trump had no shot. Even data journalists laughed at the notion that he could win.1 Nate Silver, the former baseball stats guru turned National Oracle™ (as Gizmodo called him), said Trump had a better shot of “cameoing in another Home Alone movie with Macaulay Culkin (or playing in the NBA Finals) than winning the Republican nomination.” But he won anyway. This should have proved “electability” was a crock, and killed it forever as a form of campaign analysis.

Radical Uncertainty: Decision-Making for an Unknowable Future by Mervyn King, John Kay

Airbus A320, Alan Greenspan, Albert Einstein, Albert Michelson, algorithmic trading, anti-fragile, Antoine Gombaud: Chevalier de Méré, Arthur Eddington, autonomous vehicles, availability heuristic, banking crisis, Barry Marshall: ulcers, battle of ideas, Bear Stearns, behavioural economics, Benoit Mandelbrot, bitcoin, Black Swan, Boeing 737 MAX, Bonfire of the Vanities, Brexit referendum, Brownian motion, business cycle, business process, capital asset pricing model, central bank independence, collapse of Lehman Brothers, correlation does not imply causation, credit crunch, cryptocurrency, cuban missile crisis, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, DeepMind, demographic transition, discounted cash flows, disruptive innovation, diversification, diversified portfolio, Donald Trump, Dutch auction, easy for humans, difficult for computers, eat what you kill, Eddington experiment, Edmond Halley, Edward Lloyd's coffeehouse, Edward Thorp, Elon Musk, Ethereum, Eugene Fama: efficient market hypothesis, experimental economics, experimental subject, fear of failure, feminist movement, financial deregulation, George Akerlof, germ theory of disease, Goodhart's law, Hans Rosling, Helicobacter pylori, high-speed rail, Ignaz Semmelweis: hand washing, income per capita, incomplete markets, inflation targeting, information asymmetry, invention of the wheel, invisible hand, Jeff Bezos, Jim Simons, Johannes Kepler, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Snow's cholera map, John von Neumann, Kenneth Arrow, Kōnosuke Matsushita, Linda problem, Long Term Capital Management, loss aversion, Louis Pasteur, mandelbrot fractal, market bubble, market fundamentalism, military-industrial complex, Money creation, Moneyball by Michael Lewis explains big data, Monty Hall problem, Nash equilibrium, Nate Silver, new economy, Nick Leeson, Northern Rock, nudge theory, oil shock, PalmPilot, Paul Samuelson, peak oil, Peter Thiel, Philip Mirowski, Phillips curve, Pierre-Simon Laplace, popular electronics, power law, price mechanism, probability theory / Blaise Pascal / Pierre de Fermat, quantitative trading / quantitative finance, railway mania, RAND corporation, reality distortion field, rent-seeking, Richard Feynman, Richard Thaler, risk tolerance, risk-adjusted returns, Robert Shiller, Robert Solow, Ronald Coase, sealed-bid auction, shareholder value, Silicon Valley, Simon Kuznets, Socratic dialogue, South Sea Bubble, spectrum auction, Steve Ballmer, Steve Jobs, Steve Wozniak, Suez crisis 1956, Tacoma Narrows Bridge, Thales and the olive presses, Thales of Miletus, The Chicago School, the map is not the territory, The Market for Lemons, The Nature of the Firm, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Thomas Bayes, Thomas Davenport, Thomas Malthus, Toyota Production System, transaction costs, ultimatum game, urban planning, value at risk, world market for maybe five computers, World Values Survey, Yom Kippur War, zero-sum game

And with good reason, as we will now see. The probability of an attack on the Twin Towers ‘We may treat people as if they assigned numerical probabilities to every conceivable event.’ So what was the probability that terrorists would fly passenger planes into the World Trade Center on 11 September 2001? Nate Silver, a well-known political pundit in the United States and a devotee of subjective probabilities and Bayesian reasoning, has attempted to answer that question. According to Silver, ‘most of us would have assigned almost no probability to terrorists crashing planes into buildings in Manhattan when we woke up that morning . . .

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If you crumple a piece of paper, it makes some shape; but the probability that it would make that particular shape is infinitesimally low. 14 It would be absurd, or at least trivial, to conclude that one has observed a 25 standard deviation occurrence. Crimes are rare and unique events. In chapter 5 we saw Nate Silver fail to make sense of the question ‘What is the probability that an unlikely and unique event would occur?’ when we know that the event has in fact happened. Silver was writing in the context of the attack on the World Trade Center; David Viniar struggled similarly in relation to probabilities in the global financial crisis.

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But this confronts the pollsters, and those who want to use their results, with the Viniar problem: the probability derived from the model has to be compounded with the probability that the model is itself true. We can usefully say things like ‘the pollsters are very experienced’, or ‘the model has worked well in the past’ – as we could of Nate Silver before 2016. But these are judgements, not statements about probabilities. It is thus very difficult to justify the attachment of a statistical confidence interval to an opinion poll result. Nor is this the last of the problems. The answer to a question about voting intentions needs to be translated into a prediction of voting behaviour.

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

"World Economic Forum" Davos, Alan Greenspan, banking crisis, big-box store, bike sharing, blue-collar work, business cycle, car-free, carbon footprint, collapse of Lehman Brothers, company town, congestion charging, congestion pricing, creative destruction, deskilling, edge city, Edward Glaeser, falling living standards, financial engineering, financial innovation, Ford paid five dollars a day, high net worth, high-speed rail, 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, Lewis Mumford, low skilled workers, manufacturing employment, McMansion, megaproject, 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, scientific management, secular stagnation, Silicon Valley, Silicon Valley startup, social intelligence, sovereign wealth fund, starchitect, 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

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?”

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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.

The Behavioral Investor by Daniel Crosby

affirmative action, Asian financial crisis, asset allocation, availability heuristic, backtesting, bank run, behavioural economics, Black Monday: stock market crash in 1987, Black Swan, book value, buy and hold, cognitive dissonance, colonial rule, compound rate of return, correlation coefficient, correlation does not imply causation, Daniel Kahneman / Amos Tversky, disinformation, diversification, diversified portfolio, Donald Trump, Dunning–Kruger effect, endowment effect, equity risk premium, fake news, feminist movement, Flash crash, haute cuisine, hedonic treadmill, housing crisis, IKEA effect, impact investing, impulse control, index fund, Isaac Newton, Japanese asset price bubble, job automation, longitudinal study, loss aversion, market bubble, market fundamentalism, mental accounting, meta-analysis, Milgram experiment, moral panic, Murray Gell-Mann, Nate Silver, neurotypical, Nick Bostrom, passive investing, pattern recognition, Pepsi Challenge, Ponzi scheme, prediction markets, random walk, Reminiscences of a Stock Operator, Richard Feynman, Richard Thaler, risk tolerance, Robert Shiller, science of happiness, Shai Danziger, short selling, South Sea Bubble, Stanford prison experiment, Stephen Hawking, Steve Jobs, stocks for the long run, sunk-cost fallacy, systems thinking, TED Talk, Thales of Miletus, The Signal and the Noise by Nate Silver, Tragedy of the Commons, trolley problem, tulip mania, Vanguard fund, When a measure becomes a target

Several experiments suggest that when those presented with an extensive array of options make fewer purchases and are less happy with the purchases they make than those operating from a more limited decisional universe. Another consequence of financial information overload is that it leads to drawing spurious correlations between variables. As Nate Silver reports, the government produces data on 45,000 economic variables each year!44 Pair this reality with the fact that there are relatively few dramatic economic events (e.g., there have been 11 recessions since the end of World War II) and you get what Silver refers to as putting data into a blender and calling the result haute cuisine.

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Noise is what makes markets possible. It is also what makes them almost impossible to beat. Notes 42 Zweig, Your Money and Your Brain, p. 22. 43 Greg B. Davies, Behavioral Investment Management: An Efficient Alternative to Modern Portfolio Theory (McGraw-Hill, 2012), p. 53. 44 Nate Silver, The Signal and the Noise: Why So Many Predictions Fail – but Some Don’t (Penguin, 2015), p. 185. Chapter 7. Emotion “The world is a tragedy to those who feel, but a comedy to those who think.” — Horace Walpole Emotion: friend or foe? It must be stated from the outset that there is some disagreement within the behavioral finance community about whether emotion is a help or hindrance when making investment decisions.

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Not only did the simple model outperform the psychologists’ intuition head-to-head, but it also bested psychologists who were given access to the model.109 Models have also been shown to outperform human intuition in predicting the outcomes of Supreme Court decisions,110 Presidential elections (Nate Silver), movie preferences, prison recidivism, wine quality, marital satisfaction and military success, to name just a few of the over 45 domains in which they have demonstrated their superiority.111 A meta-analysis performed by William Grove, David Zald, Boyd Lebow, Beth Snitz and Chad Nelson found that models equal or beat expert decision-making a whopping 94.12% of the time, meaning that they are only defeated by human discretion 5.88% of the time.112 Moreover, many of the domains in which algorithms greatly outperformed had human behavior as a central component (as do financial markets).

Merchants of Truth: The Business of News and the Fight for Facts by Jill Abramson

"World Economic Forum" Davos, 23andMe, 4chan, Affordable Care Act / Obamacare, Alexander Shulgin, Apple's 1984 Super Bowl advert, barriers to entry, Bernie Madoff, Bernie Sanders, Big Tech, Black Lives Matter, Cambridge Analytica, Charles Lindbergh, Charlie Hebdo massacre, Chelsea Manning, citizen journalism, cloud computing, commoditize, content marketing, corporate governance, creative destruction, crowdsourcing, data science, death of newspapers, digital twin, diversified portfolio, Donald Trump, East Village, Edward Snowden, fake news, Ferguson, Missouri, Filter Bubble, future of journalism, glass ceiling, Google Glasses, haute couture, hive mind, income inequality, information asymmetry, invisible hand, Jeff Bezos, Joseph Schumpeter, Khyber Pass, late capitalism, Laura Poitras, Marc Andreessen, Mark Zuckerberg, move fast and break things, Nate Silver, new economy, obamacare, Occupy movement, Paris climate accords, performance metric, Peter Thiel, phenotype, pre–internet, race to the bottom, recommendation engine, Robert Mercer, Ronald Reagan, Saturday Night Live, self-driving car, sentiment analysis, Sheryl Sandberg, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, skunkworks, Snapchat, social contagion, social intelligence, social web, SoftBank, Steve Bannon, Steve Jobs, Steven Levy, tech billionaire, technoutopianism, telemarketer, the scientific method, The Wisdom of Crowds, Tim Cook: Apple, too big to fail, vertical integration, WeWork, WikiLeaks, work culture , Yochai Benkler, you are the product

So it wasn’t surprising that the Post: Tom McCarthy, “Washington Post’s Ezra Klein Leaving Newspaper to Start ‘New Venture,’ ” Guardian, January 21, 2014, https://www.theguardian.com/media/2014/jan/21/washington-posts-ezra-klein-leaving-news-organisation. The Times too lost Silver: John McDuling, “ ‘The Upshot’ Is the New York Times’ Replacement for Nate Silver’s FiveThirtyEight,” Quartz, March 10, 2014, https://qz.com/185922/the-upshot-is-the-new-york-times-replacement-for-nate-silvers-fivethirtyeight/. There were bound to be problems: Trevor Butterworth, “The Latest Sad Fate of an Aggregation Serf,” Awl, April 24, 2012, https://www.theawl.com/2012/04/the-latest-sad-fate-of-an-aggregation-serf/. One story BlogPOST recycled: Patrick B.

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After the financial crisis, she argued, the last thing the Times needed was to go soft on Wall Street. But DealBook, replete with a conference headlined by Sorkin, launched with the publisher’s keen support, despite the objections from Morgenson and others who saw the venture as driven more by financial than journalism goals. Nate Silver, a popular political blogger who created FiveThirtyEight, licensed his site to the Times, and alongside Sorkin would come to represent a new breed of reporter, better known as individuals than belonging to the institution. Both stars negotiated special pay-for-performance packages under a new system that Sulzberger and Robinson had installed.

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They would edit the information and present coherent information bullets on individual “cards.” Readers loved them. Many people thought Klein had the best coverage of President Obama’s complex health overhaul. Klein’s fluid writing and original takes quickly made Wonkblog a major attraction on WashingtonPost.com. Like Nate Silver, who had established his FiveThirtyEight blog before he joined the Times, Klein attracted a different audience to the Post. But also like Silver, Klein wanted to be his own brand. He was allowed to hire a staff of eight, while the rest of the staffing at the Post tightened. As his blog became better known, he also appeared in the New Yorker and on CNN.

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

Albert Einstein, Amazon Mechanical Turk, Arthur Eddington, backpropagation, basic income, Bayesian statistics, Benoit Mandelbrot, bioinformatics, Black Swan, Brownian motion, cellular automata, Charles Babbage, Claude Shannon: information theory, combinatorial explosion, computer vision, constrained optimization, correlation does not imply causation, creative destruction, crowdsourcing, Danny Hillis, data is not the new oil, data is the new oil, data science, deep learning, DeepMind, double helix, Douglas Hofstadter, driverless car, Erik Brynjolfsson, experimental subject, Filter Bubble, future of work, Geoffrey Hinton, global village, Google Glasses, Gödel, Escher, Bach, Hans Moravec, incognito mode, information retrieval, Jeff Hawkins, job automation, John Markoff, John Snow's cholera map, John von Neumann, Joseph Schumpeter, Kevin Kelly, large language model, lone genius, machine translation, mandelbrot fractal, Mark Zuckerberg, Moneyball by Michael Lewis explains big data, Narrative Science, Nate Silver, natural language processing, Netflix Prize, Network effects, Nick Bostrom, NP-complete, off grid, P = NP, PageRank, pattern recognition, phenotype, planetary scale, power law, pre–internet, random walk, Ray Kurzweil, recommendation engine, Richard Feynman, scientific worldview, Second Machine Age, self-driving car, Silicon Valley, social intelligence, speech recognition, Stanford marshmallow experiment, statistical model, Stephen Hawking, Steven Levy, Steven Pinker, superintelligent machines, the long tail, 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, yottabyte, zero-sum game

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.

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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.

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(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.

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, Biosphere 2, Black Lives Matter, business climate, Cambridge Analytica, Carl Icahn, centre right, Charles Lindbergh, coherent worldview, collateralized debt obligation, conceptual framework, corporate raider, crony capitalism, currency manipulation / currency intervention, data science, Donald Trump, Dr. Strangelove, fake news, Fractional reserve banking, Glass-Steagall Act, Goldman Sachs: Vampire Squid, Gordon Gekko, guest worker program, hype cycle, illegal immigration, immigration reform, Jim Simons, junk bonds, liberation theology, low skilled workers, machine translation, Michael Milken, Nate Silver, Nelson Mandela, nuclear winter, obamacare, open immigration, Peace of Westphalia, Peter Thiel, quantitative hedge fund, Renaissance Technologies, Robert Mercer, Ronald Reagan, Silicon Valley, social intelligence, speech recognition, Steve Bannon, urban planning, vertical integration

“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/.

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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.

Stuffocation by James Wallman

3D printing, Abraham Maslow, Adam Curtis, Airbnb, Alvin Toffler, 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, Future Shock, Great Leap Forward, happiness index / gross national happiness, hedonic treadmill, 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, planned obsolescence, post-industrial society, post-materialism, public intellectual, retail therapy, Richard Florida, Richard Thaler, sharing economy, Silicon Valley, Simon Kuznets, Skype, spinning jenny, Streisand effect, The future is already here, The Signal and the Noise by Nate Silver, The Theory of the Leisure Class by Thorstein Veblen, Thorstein Veblen, Tyler Cowen, Tyler Cowen: Great Stagnation, World Values Survey, Zipcar

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).

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Forecasts Are Not Facts, They Are Maps For Nassim Nicholas Taleb’s dismal view of forecasting, read Nassim Nicholas Taleb, The Black Swan (New York: Penguin, 2007). The story of the turkey is borrowed, as Taleb notes, from the philosopher Bertrand Russell. 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.

The Art of Statistics: Learning From Data by David Spiegelhalter

Abraham Wald, algorithmic bias, Anthropocene, Antoine Gombaud: Chevalier de Méré, Bayesian statistics, Brexit referendum, Carmen Reinhart, Charles Babbage, complexity theory, computer vision, confounding variable, correlation coefficient, correlation does not imply causation, dark matter, data science, deep learning, DeepMind, Edmond Halley, Estimating the Reproducibility of Psychological Science, government statistician, Gregor Mendel, Hans Rosling, Higgs boson, Kenneth Rogoff, meta-analysis, Nate Silver, Netflix Prize, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, p-value, placebo effect, probability theory / Blaise Pascal / Pierre de Fermat, publication bias, randomized controlled trial, recommendation engine, replication crisis, self-driving car, seminal paper, sparse data, speech recognition, statistical model, sugar pill, systematic bias, TED Talk, The Design of Experiments, The Signal and the Noise by Nate Silver, The Wisdom of Crowds, Thomas Bayes, Thomas Malthus, Two Sigma

CODE FOR EXAMPLES R code and data for reproducing most of the analyses and Figures are available from https://github.com/dspiegel29/ArtofStatistics. I am grateful for the assistance received in preparing this material. Introduction The numbers have no way of speaking for themselves. We speak for them. We imbue them with meaning. — Nate Silver, The Signal and the Noise1 Why We Need Statistics Harold Shipman was Britain’s most prolific convicted murderer, though he does not fit the archetypal profile of a serial killer. A mild-mannered family doctor working in a suburb of Manchester, between 1975 and 1998 he injected at least 215 of his mostly elderly patients with a massive opiate overdose.

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The choice of the start of the horizontal axis, here 86%, can have a crucial effect on the impression given by the graphic. If the axis starts at 0%, all the hospitals will look indistinguishable, whereas if we started at 95% the differences would look misleadingly dramatic. I began this book with a quotation from Nate Silver, the founder of data-based platform FiveThirtyEight and first famous for accurately predicting the 2008 US presidential election, who eloquently expressed the idea that numbers do not speak for themselves – we are responsible for giving them meaning. This implies that communication is a key part of the problem-solving cycle, and I have shown in this section how the message from a set of simple proportions can be influenced by our choices of presentation.

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An observation with a Z-score of 3 corresponds to being 3 standard deviations above the mean, which is a fairly extreme outlier. A Z-score can also be defined in terms of a population mean μ and standard deviation σ, in which case zi = (xi – μ)/σ. Notes INTRODUCTION 1. The Signal and the Noise by Nate Silver (Penguin, 2012) is an excellent introduction to how statistical science can be applied to making predictions in sport and other domains. 2. The Shipman data is discussed in more detail in D. Spiegelhalter and N. Best, ‘Shipman’s Statistical Legacy’, Significance1:1 (2004), 10–12. All documents for the public inquiry are available from http://webarchive.nationalarchives.gov.uk/20090808155110/http://www.the-shipman-inquiry.org.uk/reports.asp. 3.

The Art of Statistics: How to Learn From Data by David Spiegelhalter

Abraham Wald, algorithmic bias, Antoine Gombaud: Chevalier de Méré, Bayesian statistics, Brexit referendum, Carmen Reinhart, Charles Babbage, complexity theory, computer vision, confounding variable, correlation coefficient, correlation does not imply causation, dark matter, data science, deep learning, DeepMind, Edmond Halley, Estimating the Reproducibility of Psychological Science, government statistician, Gregor Mendel, Hans Rosling, Higgs boson, Kenneth Rogoff, meta-analysis, Nate Silver, Netflix Prize, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, p-value, placebo effect, probability theory / Blaise Pascal / Pierre de Fermat, publication bias, randomized controlled trial, recommendation engine, replication crisis, self-driving car, seminal paper, sparse data, speech recognition, statistical model, sugar pill, systematic bias, TED Talk, The Design of Experiments, The Signal and the Noise by Nate Silver, The Wisdom of Crowds, Thomas Bayes, Thomas Malthus, Two Sigma

CODE FOR EXAMPLES R code and data for reproducing most of the analyses and Figures are available from https://github.com/dspiegel29/ArtofStatistics. I am grateful for the assistance received in preparing this material. Introduction The numbers have no way of speaking for themselves. We speak for them. We imbue them with meaning. —Nate Silver, The Signal and the Noise1 Why We Need Statistics Harold Shipman was Britain’s most prolific convicted murderer, though he does not fit the archetypal profile of a serial killer. A mild-mannered family doctor working in a suburb of Manchester, between 1975 and 1998 he injected at least 215 of his mostly elderly patients with a massive opiate overdose.

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The choice of the start of the horizontal axis, here 86%, can have a crucial effect on the impression given by the graphic. If the axis starts at 0%, all the hospitals will look indistinguishable, whereas if we started at 95% the differences would look misleadingly dramatic. I began this book with a quotation from Nate Silver, the founder of data-based platform FiveThirtyEight and first famous for accurately predicting the 2008 US presidential election, who eloquently expressed the idea that numbers do not speak for themselves—we are responsible for giving them meaning. This implies that communication is a key part of the problem-solving cycle, and I have shown in this section how the message from a set of simple proportions can be influenced by our choices of presentation.

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An observation with a Z-score of 3 corresponds to being 3 standard deviations above the mean, which is a fairly extreme outlier. A Z-score can also be defined in terms of a population mean μ and standard deviation σ, in which case zi = (xi–μ)/σ. Also by David Spiegelhalter The Norm Chronicles Notes INTRODUCTION 1. The Signal and the Noise by Nate Silver (Penguin, 2012) is an excellent introduction to how statistical science can be applied to making predictions in sport and other domains. 2. The Shipman data is discussed in more detail in D. Spiegelhalter and N. Best, ‘Shipman’s Statistical Legacy’, Significance 1:1 (2004), 10–12. All documents for the public inquiry are available from http://webarchive.nationalarchives.gov.uk/20090808155110/http://www.the-shipman-inquiry.org.uk/reports.asp. 3.

The Revolt of the Public and the Crisis of Authority in the New Millennium by Martin Gurri

Affordable Care Act / Obamacare, Alan Greenspan, Albert Einstein, anti-communist, Arthur Eddington, Ayatollah Khomeini, bitcoin, Black Monday: stock market crash in 1987, Black Swan, Burning Man, business cycle, citizen journalism, Climategate, Climatic Research Unit, collective bargaining, creative destruction, crowdsourcing, currency manipulation / currency intervention, dark matter, David Graeber, death of newspapers, disinformation, Eddington experiment, en.wikipedia.org, Erik Brynjolfsson, facts on the ground, Francis Fukuyama: the end of history, Frederick Winslow Taylor, full employment, Great Leap Forward, housing crisis, income inequality, Intergovernmental Panel on Climate Change (IPCC), invention of writing, job-hopping, military-industrial complex, Mohammed Bouazizi, Nate Silver, Occupy movement, Port of Oakland, Republic of Letters, Ronald Reagan, scientific management, Skype, Steve Jobs, the scientific method, The Signal and the Noise by Nate Silver, too big to fail, traveling salesman, University of East Anglia, urban renewal, War on Poverty, We are the 99%, WikiLeaks, Yochai Benkler, young professional

Here was a bold attempt at prophecy by the new team of experts: in the event, it was wildly over-optimistic. Unemployment peaked at 10.1 percent after the stimulus bill passed, and didn’t touch 8 percent until late 2012 – much worse than the worst-case projections without the stimulus.[137] In human terms, the White House numbers had missed the plight of over 3 million unemployed Americans. Nate Silver offered two reasons for Romer and Bernstein’s disconcerting failure at prediction, and neither of them seemed flattering to the expert class. The first was ignorance of actual economic conditions. The economy in 2009 happened to be in far worse shape than the experts, for all their statistical wizardry, had realized.

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[112] Dollar, “Man Who Predicted Earthquake” and Pielke, “Lessons of L’Aquila Lawsuit.” [113] Ibid. [114] “L’Aquila quake: Italy scientists guilty of manslaughter,” BBC, October 27, 2012, http://www.bbc. co.uk/news/world-europe-20025626. [115] An excellent evaluation of the state of the art in the forecasting of earthquakes is found in Nate Silver’s The Signal and the Noise: Why So Many Predictions Fail – But Some Don’t (The Penguin Press, 2012), 142-175. [116] Climategate Emails, 84. [117] Wikipedia Commons. [118] Bob Woodward, Maestro: Greenspan’s Fed and the American Boom (Simon and Schuster, 2000), Kindle location 507. [119] Ibid., Kindle location 602-609, 641

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[193] “Public Trust in Government: 1958-2013,” Pew Research Center for the People and the Press, October 18, 2013, http://www.people-press.org/2013/10/18/trust-in-government-interactive/. [194] Ormerod belongs to a group of thinkers who in the last decade have thrown much light on the boundary conditions of what human beings can and can’t know, predict, or ordain: N. N. Taleb, Duncan Watts, James C. Scott, Philip Tetlock, Nate Silver. [195] Ormerod, Why Most Things Fail, Kindle location 66. [196] Ibid., 38. [197] Ibid., 236. [198] Ibid., 67-68. [199] Ibid., 99. [200] I urge the reader to browse the many job postings for “community organizer” on the web, which add up to a familiar portrait. [201] Melissa McEwan, “President Obama at Planned Parenthood,” Shakesville, April 26, 2013, http://www.shakesville.com/2013/04/president-obama-at-planned-parenthood.html

The New Class War: Saving Democracy From the Metropolitan Elite by Michael Lind

"World Economic Forum" Davos, affirmative action, anti-communist, basic income, Bernie Sanders, Boris Johnson, Bretton Woods, Brexit referendum, business cycle, Cambridge Analytica, capital controls, Cass Sunstein, central bank independence, centre right, collective bargaining, commoditize, corporate governance, cotton gin, crony capitalism, deindustrialization, disinformation, Doha Development Round, Donald Trump, Edward Snowden, export processing zone, fake news, future of work, gentrification, global supply chain, guest worker program, Haight Ashbury, illegal immigration, immigration reform, independent contractor, invisible hand, Jeremy Corbyn, knowledge economy, Les Trente Glorieuses, liberal world order, low skilled workers, low-wage service sector, manufacturing employment, Mark Zuckerberg, mass immigration, means of production, Michael Milken, moral panic, Nate Silver, new economy, offshore financial centre, oil shock, open borders, plutocrats, Ponzi scheme, purchasing power parity, Ralph Nader, regulatory arbitrage, rent-seeking, Richard Florida, Ronald Reagan, scientific management, Silicon Valley, SoftBank, The Wealth of Nations by Adam Smith, Thorstein Veblen, Timothy McVeigh, trade liberalization, union organizing, universal basic income, upwardly mobile, WikiLeaks, Wolfgang Streeck, working poor

In the 2016 US presidential election, among counties with a population of fifty thousand or more, Hillary Clinton won forty-eight of the fifty counties that had the highest percentage of voters with at least a four-year bachelor’s degree. Support for her presidential bid “collapsed” (to use the pollster Nate Silver’s term) in the fifty counties with the lowest educational levels. Political differences correlated with education can be found among racial and ethnic minority populations as well.16 The same pattern is evident in Europe. In Britain, for example, the chief trait predicting support for the Leave side in the Brexit referendum in 2016 was lower educational qualifications—a trait that was more important than others, including race and ethnicity.17 Because the possession of a diploma tends to indicate birth into the economic elite, these figures manifest conflict among largely hereditary social classes, not a clash between knowledge and ignorance or intelligence and stupidity.

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Quinn, and Kathryn Peltier Campbell, Born to Win, Schooled to Lose: Why Talented Students Don’t Get Equal Chances to Be All They Can Be, Georgetown University Center on Education and the Workforce report, 2019. 14. UNCTAD, “Annex Table 24. The World’s Top 100 Non-Financial MNE’s, Ranked by Foreign Assets, 2016.” 15. George Davis, “Boards Aren’t as Global as Their Businesses,” Harvard Business Review, October 28, 2014. 16. Nate Silver, “Education, Not Income, Predicted Who Would Vote for Trump,” FiveThirtyEight.com, November 22, 2016. 17. Martin Rosenbaum, “Local Voting Figures Shed New Light on EU Referendum,” BBC News, February 6, 2017. 18. Edna Bonacich, “A Theory of Ethnic Antagonism: The Split Labor Market,” American Sociological Review 37, no. 5 (October 1972), pp. 547–59. 19.

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

Affordable Care Act / Obamacare, Amazon Mechanical Turk, big data - Walmart - Pop Tarts, bitcoin, Cass Sunstein, Claude Shannon: information theory, cognitive load, crowdsourcing, data science, Edward Snowden, Firefox, Google Glasses, hive mind, income inequality, Internet of things, John von Neumann, meta-analysis, Nate Silver, new economy, Nick Bostrom, Panopticon Jeremy Bentham, 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, Twitter Arab Spring, WikiLeaks

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.

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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.

Shape: The Hidden Geometry of Information, Biology, Strategy, Democracy, and Everything Else by Jordan Ellenberg

Albert Einstein, AlphaGo, Andrew Wiles, autonomous vehicles, British Empire, Brownian motion, Charles Babbage, Claude Shannon: information theory, computer age, coronavirus, COVID-19, deep learning, DeepMind, Donald Knuth, Donald Trump, double entry bookkeeping, East Village, Edmond Halley, Edward Jenner, Elliott wave, Erdős number, facts on the ground, Fellow of the Royal Society, Geoffrey Hinton, germ theory of disease, global pandemic, government statistician, GPT-3, greed is good, Henri Poincaré, index card, index fund, Isaac Newton, Johannes Kepler, John Conway, John Nash: game theory, John Snow's cholera map, Louis Bachelier, machine translation, Mercator projection, Mercator projection distort size, especially Greenland and Africa, Milgram experiment, multi-armed bandit, Nate Silver, OpenAI, Paul Erdős, pets.com, pez dispenser, probability theory / Blaise Pascal / Pierre de Fermat, Ralph Nelson Elliott, random walk, Rubik’s Cube, self-driving car, side hustle, Snapchat, social distancing, social graph, transcontinental railway, urban renewal

See also a popular writeup of this paper by two more of its authors, David Rothschild and Sharad Goel, “When You Hear the Margin of Error Is Plus or Minus 3 Percent, Think 7 Instead,” New York Times, Oct. 5, 2016. “Just last week”: A. Prokop, “Nate Silver’s Model Gives Trump an Unusually High Chance of Winning. Could He Be Right?,” Vox, Nov. 3, 2016. https://www.vox.com/2016/11/3/13147678/nate-silver-fivethirtyeight-trump-forecast. “After 2016”: The New Republic, Dec. 14, 2016. “Mr. Pearson would”: Egon S. Pearson, “Karl Pearson: An Appreciation of Some Aspects of His Life and Work,” Biometrika 28, no. 3/4 (Dec. 1936): 206.

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.* Which brings us to Donald Trump. As the 2016 U.S. presidential election neared, one thing everyone agreed on was that Hillary Clinton was running ahead. But just how much of a chance Donald Trump had was in great dispute. The newsmagazine Vox wrote on November 3: Just last week, Nate Silver’s polls-only forecast gave Hillary Clinton an overwhelming 85 percent chance of winning. But as of Thursday morning, her odds have fallen down to 66.9 percent—suggesting that while Donald Trump is still the underdog, there’s a one-in-three shot he’ll end up the next president. Liberals have tried to comfort themselves with the knowledge that FiveThirtyEight is an outlier among the six major forecasts, and that the other five give Trump between a 16 percent and a sub-1 percent chance of winning.

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You might estimate this chance—or Sam Wang, the cricket-eater-to-be, might estimate this chance—as being 0.45 × 0.45 × 0.23 × 0.21 × 0.17 which is about 1 in 600. Trump’s chance of winning even three or four of these states, under the same kind of computation, is pretty small. Nate Silver saw things differently. His model built in a healthy amount of correlation between the different states, based on the undeniable fact that pollsters could unknowingly be making design choices that biased the sample toward one candidate or the other. Yes, our best estimate was that Trump was behind in Florida, and in North Carolina, and in each of the other swing states.

The Hacker and the State: Cyber Attacks and the New Normal of Geopolitics by Ben Buchanan

active measures, air gap, Bernie Sanders, bitcoin, blockchain, borderless world, Brian Krebs, British Empire, Cass Sunstein, citizen journalism, Citizen Lab, credit crunch, cryptocurrency, cuban missile crisis, data acquisition, disinformation, Donald Trump, drone strike, Edward Snowden, fake news, family office, Hacker News, hive mind, information security, Internet Archive, Jacob Appelbaum, John Markoff, John von Neumann, Julian Assange, Kevin Roose, Kickstarter, kremlinology, Laura Poitras, MITM: man-in-the-middle, Nate Silver, operational security, post-truth, profit motive, RAND corporation, ransomware, risk tolerance, Robert Hanssen: Double agent, rolodex, Ronald Reagan, Russian election interference, seminal paper, Silicon Valley, South China Sea, Steve Jobs, Stuxnet, subscription business, technoutopianism, undersea cable, uranium enrichment, Vladimir Vetrov: Farewell Dossier, Wargames Reagan, WikiLeaks, zero day

Also see Adam Gabbatt, “Trump Says Russia Helped Elect Him—Then Quickly Backtracks,” Guardian, May 30, 2019. 82. Nate Silver, “How Much Did Russian Interference Affect The 2016 Election?,” FiveThirtyEight, February 16, 2018; Lucam Ahmad Way and Adam Casey, “Russia Has Been Meddling in Foreign Elections for Decades. Has It Made a Difference?,” Washington Post, January 8, 2018; Jane Mayer, “How Russia Helped Swing the Election for Trump,” New Yorker, September 24, 2018. 83. For an analysis of the Comey letter, see Nate Silver, “The Comey Letter Probably Cost Clinton The Election,” FiveThirtyEight, May 3, 2017. Among other possibly serious missteps, Clinton never campaigned in Wisconsin during the general election, a state she narrowly lost.

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Among other possibly serious missteps, Clinton never campaigned in Wisconsin during the general election, a state she narrowly lost. Nate Silver, “Donald Trump Had a Superior Electoral College Strategy,” FiveThirtyEight, February 6, 2017. For a discussion of turnout in various demographic groups, see Bernard L. Fraga, Sean McElwee, Jesse Rhodes, and Brian Schaffner, “Why Did Trump Win? More Whites—and Fewer Blacks—Actually Voted,” Washington Post Monkey Cage Blog, May 8, 2017. 84. For the definitive history of Soviet active measures, see Thomas Rid, Active Measures: The Secret History of Disinformation and Political Warfare (New York: Farrar, Strauss, and Giroux, 2020). 85.

Prediction Machines: The Simple Economics of Artificial Intelligence by Ajay Agrawal, Joshua Gans, Avi Goldfarb

Abraham Wald, Ada Lovelace, AI winter, Air France Flight 447, Airbus A320, algorithmic bias, AlphaGo, Amazon Picking Challenge, artificial general intelligence, autonomous vehicles, backpropagation, basic income, Bayesian statistics, Black Swan, blockchain, call centre, Capital in the Twenty-First Century by Thomas Piketty, Captain Sullenberger Hudson, carbon tax, Charles Babbage, classic study, collateralized debt obligation, computer age, creative destruction, Daniel Kahneman / Amos Tversky, data acquisition, data is the new oil, data science, deep learning, DeepMind, deskilling, disruptive innovation, driverless car, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, everywhere but in the productivity statistics, financial engineering, fulfillment center, general purpose technology, Geoffrey Hinton, Google Glasses, high net worth, ImageNet competition, income inequality, information retrieval, inventory management, invisible hand, Jeff Hawkins, job automation, John Markoff, Joseph Schumpeter, Kevin Kelly, Lyft, Minecraft, Mitch Kapor, Moneyball by Michael Lewis explains big data, Nate Silver, new economy, Nick Bostrom, On the Economy of Machinery and Manufactures, OpenAI, paperclip maximiser, pattern recognition, performance metric, profit maximization, QWERTY keyboard, race to the bottom, randomized controlled trial, Ray Kurzweil, ride hailing / ride sharing, Robert Solow, Salesforce, Second Machine Age, self-driving car, shareholder value, Silicon Valley, statistical model, Stephen Hawking, Steve Jobs, Steve Jurvetson, Steven Levy, strong AI, The Future of Employment, the long tail, The Signal and the Noise by Nate Silver, Tim Cook: Apple, trolley problem, Turing test, Uber and Lyft, uber lyft, US Airways Flight 1549, Vernor Vinge, vertical integration, warehouse automation, warehouse robotics, Watson beat the top human players on Jeopardy!, William Langewiesche, Y Combinator, zero-sum game

Kelly Gonsalves, “Google Has More Than 1,000 Artificial Intelligence Projects in the Works,” The Week, October 18, 2016, http://theweek.com/speedreads/654463/google-more-than-1000-artificial-intelligence-projects-works. 5. A rich, entertaining, and ultimately useless debate rages about whether these sabermetric analysts are better or worse than the scouts. As Nate Silver highlights, both the Moneyball types and the scouts have important roles to play. Nate Silver, The Signal and the Noise (New York: Penguin Books, 2015), chapter 3. 6. You may counter and say that surely, in order to improve, the prediction machine needs that past repository of data? This is a subtle issue. Prediction works best when adding new data does not change algorithms too much—that stability is an outcome of good statistical practice.

Escape From Model Land: How Mathematical Models Can Lead Us Astray and What We Can Do About It by Erica Thompson

Alan Greenspan, Bayesian statistics, behavioural economics, Big Tech, Black Swan, butterfly effect, carbon tax, coronavirus, correlation does not imply causation, COVID-19, data is the new oil, data science, decarbonisation, DeepMind, Donald Trump, Drosophila, Emanuel Derman, Financial Modelers Manifesto, fudge factor, germ theory of disease, global pandemic, hindcast, I will remember that I didn’t make the world, and it doesn’t satisfy my equations, implied volatility, Intergovernmental Panel on Climate Change (IPCC), John von Neumann, junk bonds, Kim Stanley Robinson, lockdown, Long Term Capital Management, moral hazard, mouse model, Myron Scholes, Nate Silver, Neal Stephenson, negative emissions, paperclip maximiser, precautionary principle, RAND corporation, random walk, risk tolerance, selection bias, self-driving car, social distancing, Stanford marshmallow experiment, statistical model, systematic bias, tacit knowledge, tail risk, TED Talk, The Great Moderation, The Great Resignation, the scientific method, too big to fail, trolley problem, value at risk, volatility smile, Y2K

The US presidential elections have been the subject of quantitative forecasting by bodies such as Nate Silver’s FiveThirtyEight, which on 8 November 2016 predicted a 71% chance of Hillary Clinton winning that year’s presidential vote based on analysis of polling data, corrected for expected sampling biases. Of course, she did not win, and there followed a lot of discussion about why the predictions had been so wrong, what had happened to the polling, etc. FiveThirtyEight’s take on it, predictably, was that a 71% chance of one candidate winning still left a 29% chance of the other winning, with Nate Silver then writing articles like ‘Why FiveThirtyEight Gave Trump a Better Chance Than Almost Anyone Else’ (published 11 November 2016), arguing that, based on the forecast, the result should not have been as shocking as it was.

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

barriers to entry, basic income, behavioural economics, 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, Edward Jenner, 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, Lean Startup, M-Pesa, mass immigration, meta-analysis, microcredit, Nate Silver, Peter Singer: altruism, power law, public intellectual, 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, Tyler Cowen, universal basic income, William MacAskill, women in the workforce

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.

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“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.

How Democracies Die by Steven Levitsky, Daniel Ziblatt

Affordable Care Act / Obamacare, Ayatollah Khomeini, basic income, Berlin Wall, Bernie Sanders, Black Lives Matter, Capital in the Twenty-First Century by Thomas Piketty, Cass Sunstein, centre right, Charles Lindbergh, clean water, David Brooks, Donald Trump, fake news, Fall of the Berlin Wall, Gunnar Myrdal, illegal immigration, immigration reform, income inequality, Jeff Bezos, Nate Silver, Norman Mailer, old-boy network, Robert Gordon, Ronald Reagan, single-payer health, The Rise and Fall of American Growth, universal basic income

Even after Trump began to surge in the polls, few people took his candidacy seriously. In August 2015, two months after Trump declared his candidacy, Las Vegas bookmakers gave him one-hundred-to-one odds of winning the White House. And in November 2015, as Trump sat high atop the Republican polls, Nate Silver, founder of the FiveThirtyEight blog, whose uncannily accurate predictions in the 2008 and 2012 elections had earned him fame and prestige, wrote an article titled “Dear Media: Stop Freaking Out About Donald Trump’s Poll Numbers.” The article predicted that Trump’s weakness among party insiders would spell his demise.

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skip the “invisible primary”: For a detailed explanation of why this was the case, see Cohen, Karol, Noel, and Zaller, The Party Decides. Las Vegas bookmakers: James Ceaser, Andrew Busch, and John Pitney Jr., Defying the Odds: The 2016 Elections and American Politics (Washington, DC: Rowman & Littlefield, 2017), p. 69. “considerably less than 20 percent”: Nate Silver, “Dear Media: Stop Freaking Out About Donald Trump’s Polls,” FiveThirtyEight, November 23, 2015, http://fivethirtyeight.com/​features/​dear-media-stop-freaking-out-about-donald-trumps-polls/. Citizens United ruling: Marty Cohen, David Karol, Hans Noel, and John Zaller, “Party Versus Faction in the Reformed Presidential Nominating System, PS (October 2016), pp. 704–5; Theda Skocpol and Alex Hertel-Fernandez, “The Koch Network and Republican Party Extremism,” Perspectives on Politics 14, no. 3 (2016), pp. 681–99.

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

23andMe, Affordable Care Act / Obamacare, airport security, Apollo 11, barriers to entry, Berlin Wall, big data - Walmart - Pop Tarts, Black Swan, book scanning, book value, business intelligence, business process, call centre, cloud computing, computer age, correlation does not imply causation, dark matter, data science, double entry bookkeeping, Eratosthenes, Erik Brynjolfsson, game design, hype cycle, IBM and the Holocaust, index card, informal economy, intangible asset, Internet of things, invention of the printing press, Jeff Bezos, Joi Ito, lifelogging, Louis Pasteur, machine readable, machine translation, Marc Benioff, Mark Zuckerberg, Max Levchin, Menlo Park, Moneyball by Michael Lewis explains big data, Nate Silver, natural language processing, Netflix Prize, Network effects, obamacare, optical character recognition, PageRank, paypal mafia, performance metric, Peter Thiel, Plato's cave, post-materialism, random walk, recommendation engine, Salesforce, self-driving car, sentiment analysis, Silicon Valley, Silicon Valley startup, smart grid, smart meter, social graph, sparse data, speech recognition, Steve Jobs, Steven Levy, systematic bias, the scientific method, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, Thomas Davenport, Turing test, vertical integration, Watson beat the top human players on Jeopardy!

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.

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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.

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, back-to-the-city movement, basic income, Bernie Sanders, bike sharing, 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, gentrification, Gini coefficient, Google bus, high net worth, high-speed rail, 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, megaproject, Menlo Park, mortgage tax deduction, Nate Silver, New Economic Geography, new economy, New Urbanism, occupational segregation, off-the-grid, opioid epidemic / opioid crisis, Paul Graham, plutocrats, RAND corporation, rent control, rent-seeking, restrictive zoning, Richard Florida, rising living standards, Ronald Reagan, secular stagnation, self-driving car, Silicon Valley, SimCity, sovereign wealth fund, streetcar suburb, superstar cities, tech worker, the built environment, The Chicago School, The Death and Life of Great American Cities, the High Line, The Rise and Fall of American Growth, The Theory of the Leisure Class by Thorstein Veblen, The Wealth of Nations by Adam Smith, Thorstein Veblen, trickle-down economics, Tyler Cowen, Uber and Lyft, uber lyft, universal basic income, upwardly mobile, urban decay, urban planning, urban renewal, urban sprawl, white flight, young professional

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.

…

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.

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

Abraham Maslow, adjacent possible, Affordable Care Act / Obamacare, Albert Einstein, assortative mating, Berlin Wall, big-box store, blue-collar work, Bretton Woods, Broken windows theory, business cycle, call centre, clean water, company town, cuban missile crisis, dark matter, David Brooks, delayed gratification, different worldview, double helix, Downton Abbey, Dunbar number, Edward Jenner, Fall of the Berlin Wall, Filter Bubble, Francis Fukuyama: the end of history, gentrification, 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, Khyber Pass, Lewis Mumford, Louis Pasteur, Marshall McLuhan, McMansion, Nate Silver, obamacare, Occupy movement, off-the-grid, Peter Thiel, post-industrial society, Richard Florida, rolodex, Saturday Night Live, Silicon Valley, Skype, social intelligence, Stanford marshmallow experiment, Steve Jobs, TED Talk, telemarketer, The Chicago School, The Death and Life of Great American Cities, the medium is the message, the strength of weak ties, Tyler Cowen, Tyler Cowen: Great Stagnation, urban decay, urban planning, Walter Mischel, War on Poverty, women in the workforce, World Values Survey, zero-sum game

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.

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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/?

The Joys of Compounding: The Passionate Pursuit of Lifelong Learning, Revised and Updated by Gautam Baid

Abraham Maslow, activist fund / activist shareholder / activist investor, Airbnb, Alan Greenspan, Albert Einstein, Alvin Toffler, Andrei Shleifer, asset allocation, Atul Gawande, availability heuristic, backtesting, barriers to entry, beat the dealer, Benoit Mandelbrot, Bernie Madoff, bitcoin, Black Swan, book value, business process, buy and hold, Cal Newport, Cass Sunstein, Checklist Manifesto, Clayton Christensen, cognitive dissonance, collapse of Lehman Brothers, commoditize, corporate governance, correlation does not imply causation, creative destruction, cryptocurrency, Daniel Kahneman / Amos Tversky, deep learning, delayed gratification, deliberate practice, discounted cash flows, disintermediation, disruptive innovation, Dissolution of the Soviet Union, diversification, diversified portfolio, dividend-yielding stocks, do what you love, Dunning–Kruger effect, Edward Thorp, Elon Musk, equity risk premium, Everything should be made as simple as possible, fear index, financial independence, financial innovation, fixed income, follow your passion, framing effect, George Santayana, Hans Rosling, hedonic treadmill, Henry Singleton, hindsight bias, Hyman Minsky, index fund, intangible asset, invention of the wheel, invisible hand, Isaac Newton, it is difficult to get a man to understand something, when his salary depends on his not understanding it, Jeff Bezos, John Bogle, Joseph Schumpeter, junk bonds, Kaizen: continuous improvement, Kickstarter, knowledge economy, Lao Tzu, Long Term Capital Management, loss aversion, Louis Pasteur, low interest rates, Mahatma Gandhi, mandelbrot fractal, margin call, Mark Zuckerberg, Market Wizards by Jack D. Schwager, Masayoshi Son, mental accounting, Milgram experiment, moral hazard, Nate Silver, Network effects, Nicholas Carr, offshore financial centre, oil shock, passive income, passive investing, pattern recognition, Peter Thiel, Ponzi scheme, power law, price anchoring, quantitative trading / quantitative finance, Ralph Waldo Emerson, Ray Kurzweil, Reminiscences of a Stock Operator, reserve currency, Richard Feynman, Richard Thaler, risk free rate, risk-adjusted returns, Robert Shiller, Savings and loan crisis, search costs, shareholder value, six sigma, software as a service, software is eating the world, South Sea Bubble, special economic zone, Stanford marshmallow experiment, Steve Jobs, Steven Levy, Steven Pinker, stocks for the long run, subscription business, sunk-cost fallacy, systems thinking, tail risk, Teledyne, the market place, The Signal and the Noise by Nate Silver, The Wisdom of Crowds, time value of money, transaction costs, tulip mania, Upton Sinclair, Walter Mischel, wealth creators, Yogi Berra, zero-sum game

Judge them based on their execution track record and do not get influenced by the use of superlatives and adjectives by other people (which is usually more of a persuasion technique than anything else). 4. Distinguish between the signal and the noise. The signal is the truth. The noise is what distracts us from seeing it. In his book The Signal and the Noise, Nate Silver writes, “There isn’t any more truth in the world than there was before the Internet or the printing press. Most of the data is just noise, as most of the universe is filled with empty space.”23 If we want to increase the signal-to-noise ratio, we need to first cut out the cacophony of all the noise surrounding us.

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Herbert Simon enlightened me on bounded rationality, that is, the cognitive limitations of our minds. Fred Schwed made me aware of the inherent conflicts of interest in the investment industry. Robert Cialdini made me aware of the various psychological tactics used by compliance practitioners. Nate Silver and Philip Tetlock educated me on the follies of forecasting and how we can improve our skills at making estimates through probabilistic thinking, Bayesian belief updating, and the use of relevant base rates. John Allen Paulos, Barbara Oakley, and Jana Vembunarayanan taught me how to engage in intelligent mathematical thinking.

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Warren Buffett, Berkshire Hathaway 1979 Annual Letter to Shareholders, March 3, 1980, http://www.berkshirehathaway.com/letters/1979.html. 20. Warren Buffett, Berkshire Hathaway 1987 Annual Letter to Shareholders, February 29, 1988, http://www.berkshirehathaway.com/letters/1987.html. 21. Tetlock and Gardner, Superforecasting. 22. Harvey S. Firestone, Men and Rubber: The Story of Business (Whitefish, MT: Kessinger, 2003). 23. Nate Silver, The Signal and the Noise: Why So Many Predictions Fail—but Some Don’t (London: Penguin, 2015). 24. Goodreads.com, accessed December 10, 2019, https://www.goodreads.com/quotes/393102-when-information-is-cheap-attention-becomes-expensive. 25. Ian Cassel, “Paul Lountzis on Differential Insights,” MicroCapClub, October 10, 2016, https://microcapclub.com/2016/10/paul-lountzis-differential-insights/. 26.

The Theft of a Decade: How the Baby Boomers Stole the Millennials' Economic Future by Joseph C. Sternberg

Affordable Care Act / Obamacare, Airbnb, Alan Greenspan, American Legislative Exchange Council, Asian financial crisis, banking crisis, Basel III, Bear Stearns, Bernie Sanders, blue-collar work, centre right, corporate raider, Detroit bankruptcy, Donald Trump, Edward Glaeser, employer provided health coverage, Erik Brynjolfsson, eurozone crisis, financial engineering, future of work, gig economy, Gordon Gekko, hiring and firing, Home mortgage interest deduction, housing crisis, independent contractor, job satisfaction, job-hopping, labor-force participation, low interest rates, low skilled workers, Lyft, Marc Andreessen, Mark Zuckerberg, minimum wage unemployment, mortgage debt, mortgage tax deduction, Nate Silver, new economy, obamacare, oil shock, payday loans, pension reform, quantitative easing, Richard Florida, Ronald Reagan, Saturday Night Live, Second Machine Age, sharing economy, Silicon Valley, sovereign wealth fund, Steve Bannon, stop buying avocado toast, TaskRabbit, total factor productivity, Tyler Cowen, Tyler Cowen: Great Stagnation, uber lyft, unpaid internship, women in the workforce

Wright, One Nation Under Debt: Hamilton, Jefferson, and the History of What We Owe [New York: McGraw-Hill, 2008]). † Policy wonk Nate Silver draws an interesting connection between this phenomenon and changing public attitudes toward the government over the latter part of the twentieth century: “We may have gone from conceiving of government as an entity that builds roads, dams and airports, provides shared services like schooling, policing and national parks, and wages wars, into the world’s largest insurance broker. Most of us don’t much care for our insurance broker” (Nate Silver, “Health Care Drives Increase in Government Spending,” New York Times, January 17, 2013)

The Coming of Neo-Feudalism: A Warning to the Global Middle Class by Joel Kotkin

"RICO laws" OR "Racketeer Influenced and Corrupt Organizations", "World Economic Forum" Davos, Admiral Zheng, Alvin Toffler, Andy Kessler, autonomous vehicles, basic income, Bernie Sanders, Big Tech, bread and circuses, Brexit referendum, call centre, Capital in the Twenty-First Century by Thomas Piketty, carbon credits, carbon footprint, Cass Sunstein, clean water, company town, content marketing, Cornelius Vanderbilt, creative destruction, data science, deindustrialization, demographic transition, deplatforming, don't be evil, Donald Trump, driverless car, edge city, Elon Musk, European colonialism, Evgeny Morozov, financial independence, Francis Fukuyama: the end of history, Future Shock, gentrification, gig economy, Gini coefficient, Google bus, Great Leap Forward, green new deal, guest worker program, Hans Rosling, Herbert Marcuse, housing crisis, income inequality, informal economy, Jane Jacobs, Jaron Lanier, Jeff Bezos, Jeremy Corbyn, job automation, job polarisation, job satisfaction, Joseph Schumpeter, land reform, liberal capitalism, life extension, low skilled workers, Lyft, Marc Benioff, Mark Zuckerberg, market fundamentalism, Martin Wolf, mass immigration, megacity, Michael Shellenberger, Nate Silver, new economy, New Urbanism, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, Occupy movement, Parag Khanna, Peter Thiel, plutocrats, post-industrial society, post-work, postindustrial economy, postnationalism / post nation state, precariat, profit motive, public intellectual, RAND corporation, Ray Kurzweil, rent control, Richard Florida, road to serfdom, Robert Gordon, Salesforce, Sam Altman, San Francisco homelessness, Satyajit Das, sharing economy, Sidewalk Labs, Silicon Valley, smart cities, Social Justice Warrior, Steve Jobs, Stewart Brand, superstar cities, technological determinism, Ted Nordhaus, The Death and Life of Great American Cities, The future is already here, The Future of Employment, The Rise and Fall of American Growth, Thomas L Friedman, too big to fail, trade route, Travis Kalanick, Uber and Lyft, uber lyft, universal basic income, unpaid internship, upwardly mobile, Virgin Galactic, We are the 99%, Wolfgang Streeck, women in the workforce, work culture , working-age population, Y Combinator

., 511, 551; Dmitri Volkogonov, Autopsy for Empire: The Seven Leaders Who Built the Soviet Regime (New York: Free Press, 1998), 63. 27 Eric D. Weitz, Weimar Germany: Promise and Tragedy (Princeton: Princeton University Press, 2007), 334. 28 Frederic Spotts, Hitler and the Power of Aesthetics (New York: Overlook Press, 2003), 30, 79–82, 98. 29 Klaus P. Fischer, Nazi Germany: A New History (New York: Continuum, 1996), 17. 30 Nate Silver, “There Really Was a Liberal Media Bubble,” FiveThirtyEight, March 10, 2017, https://fivethirtyeight.com/features/there-really-was-a-liberal-media-bubble/; “Media Bias: Pretty Much All of Journalism Now Leans Left, Study Shows,” Investor’s Business Daily, November 16, 2018, https://www.investors.com/politics/editorials/media-bias-left-study/. 31 Christopher M.

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Malcolm Debevoise (New Haven: Yale University Press, 2019), 24. 25 “The far right’s new fascination with the Middle Ages,” Economist, January 2, 2017, https://www.economist.com/blogs/democracyinamerica/2017/01/medieval-memes. 26 Guilluy, Twilight of the Elites, 43. 27 Neil Munro, “Billionaire Steve Case says immigrants will offset middle class job losses,” Daily Caller, December 5, 2013, https://dailycaller.com/2013/12/05/billionaire-steve-case-says-immigrants-will-offset-middle-class-job-losses/. 28 Alex Pfeiffer, “Bill Kristol Says ‘Lazy’ White Working Class Should Be Replaced by ‘New Americans,’” Daily Caller, February 8, 2017, https://dailycaller.com/2017/02/08/bill-kristol-says-lazy-white-working-class-should-be-replaced-by-new-americans/. 29 Geoff Colvin, “Donald Trump’s Immigration Ban Ushers In a New Era of CEO Activism,” Fortune, February 7, 2017, http://fortune.com/2017/02/07/donald-trumps-immigration-ban-ushers-in-a-new-era-of-ceo-activism/. 30 Douglas Murray, The Strange Death of Europe: Immigration, Identity, Islam (London: Bloomsbury, 2017), 99, 226. 31 Giles Kepel, remarks at the Tocqueville Conversations, Château de Tocqueville, Normandy, France, June 7–8, 2018. 32 Goodhart, The Road to Somewhere, 3–4, 100; “The Brexit Index: a who’s who of Remain and Leave supporters,” Populus, https://www.populus.co.uk/insights/2016/05/the-brexit-index-a-whos-who-of-remain-and-leave-supporters/; House of Commons Library, “General Election 2019: Results and Analysis,” Number CBP 8749, 28 January 2020. 33 Peter Foster, “Denmark’s EU referendum is a blow to David Cameron,” Telegraph, December 4, 2015, https://www.telegraph.co.uk/news/worldnews/europe/denmark/12032958/Denmarks-EU-referendum-is-a-blow-to-David-Cameron.html; “Dutch referendum voters overwhelmingly reject closer EU links to Ukraine,” Guardian, April 7, 2016, https://www.theguardian.com/world/2016/apr/06/dutch-voters-reject-closer-eu-links-to-ukraine-in-referendum; Nick Gutteridge, “European Superstate to be unveiled: EU nations ‘to be morphed into one’ post-Brexit,” Express, June 29, 2016, https://www.express.co.uk/news/politics/683739/EU-referendum-German-French-European-superstate-Brexit; Project 28, “Handling the Immigration Crisis,” Századvég Foundation, http://project28.eu/. 34 Matthew Karnitschnig, “Cologne puts Germany’s ‘lying press’ on defensive,” Politico, January 25, 2016, https://www.politico.eu/article/cologne-puts-germany-lying-media-press-on-defensive-migration-refugees-attacks-sex-assault-nye/; Robert Spencer, “Google manipulates Search Results to Conceal Criticism of Islam and Jihad,” PJ Media, August 2, 2017, https://pjmedia.com/homeland-security/2017/08/02/google-manipulates-search-results-to-conceal-criticism-of-islam-and-jihad/; “Rome opens its gates to the modern barbarians,” Financial Times, May 15, 2018, https://www.ft.com/content/6348cc64-5764-11e8-b8b2-d6ceb45fa9d0. 35 Goodhart, The Road to Somewhere, 14. 36 Robert Samuelson, “The Middle Class Rocks—Again,” Real Clear Politics, September 18, 2017, https://www.realclearpolitics.com/articles/2017/09/18/the_middle_class_rocks-again_135014.html; Nate Silver, “Silver Bulletpoints: The Union Vote Could Swing the Election,” FiveThirtyEight, May 2, 2019, https://fivethirtyeight.com/features/silver-bulletpoints-the-union-vote-could-swing-the-election/. 37 Richard Florida, “Why Is Your State Red or Blue? Look to the Dominant Occupational Class,” City Lab, November 28, 2018, https://www.citylab.com/life/2018/11/state-voting-patterns-occupational-class-data-politics/575047/. 38 John Daniel Davidson, “Trump is no fascist.

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

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

Buzzwords have changed, but the major fad pushing Big Data AI as a panacea threatens pro­g ress in fundamental areas like neuroscience, in spite of bold claims made by enthusiasts like Markram and ­others. The takeaway ­here is that the myth ­really does have practical consequences for our h­ uman f­ utures—in a­ ctual science. OV ER F IT T I NG Statistician Nate Silver has also pointed out the inherent danger of overfitting theories (models) to data, where “overfitting” ­here means spuriously matching a set of data points to a description that contains no genuine explanatory power, ­because the description does not generalize to new, unseen data points in the under­lying distribution in question.

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Lee Gomes, “Machine-­Learning Maestro Michael Jordan on the Delusions of Big Data and Other Huge Engineering Efforts,” IEEE Spectrum, October 20, 2014, https://­spectrum​.­ieee​.­org​/­robotics​/­a rtificial​-­i ntelligence​ /­machinelearning​-­maestro​-­m ichael​-­jordan​-­on​-­t he​-­delusions​-­of​-­big​-­d ata​ -­a nd​-­other​-­huge​-­engineering​-­efforts. 12. Ibid. 13. Gary Marcus and Ernest Davis, “Eight (No Nine!) Prob­lems with Big Data,” New York Times, April 6, 2014. 14. Nate Silver, The Signal and the Noise: Why So Many Predictions Fail—­But Some D ­ on’t (New York: Penguin Books, 2015). Chapter 17: Neocortical Theories of H ­ uman Intelligence 1. Jeff Hawkins, On Intelligence: How a New Understanding of the Brain ­ ill Lead to the Creation of Truly Intelligent Machines (New York: St.

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

3D printing, Ada Lovelace, AI winter, Albert Einstein, AlphaGo, AltaVista, Apple Newton, barriers to entry, Berlin Wall, Bletchley Park, business process, call centre, Charles Babbage, Charles Lindbergh, clean water, computer age, cotton gin, Daniel Kahneman / Amos Tversky, David Brooks, DeepMind, Donald Trump, Douglas Hofstadter, driverless car, Drosophila, Elon Musk, Erik Brynjolfsson, factory automation, Freestyle chess, gamification, Gödel, Escher, Bach, Hans Moravec, job automation, Ken Thompson, Leonard Kleinrock, low earth orbit, machine translation, Max Levchin, Mikhail Gorbachev, move 37, Nate Silver, Nick Bostrom, Norbert Wiener, packet switching, pattern recognition, Ray Kurzweil, 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

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.”

…

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.

Zero to One: Notes on Startups, or How to Build the Future by Peter Thiel, Blake Masters

Airbnb, Alan Greenspan, Albert Einstein, Andrew Wiles, Andy Kessler, Berlin Wall, clean tech, cloud computing, crony capitalism, discounted cash flows, diversified portfolio, do well by doing good, don't be evil, Elon Musk, eurozone crisis, Fairchild Semiconductor, heat death of the universe, income inequality, Jeff Bezos, Larry Ellison, Lean Startup, life extension, lone genius, Long Term Capital Management, Lyft, Marc Andreessen, Mark Zuckerberg, Max Levchin, minimum viable product, Nate Silver, Network effects, new economy, Nick Bostrom, PalmPilot, paypal mafia, Peter Thiel, pets.com, power law, profit motive, Ralph Waldo Emerson, Ray Kurzweil, self-driving car, shareholder value, Sheryl Sandberg, Silicon Valley, Silicon Valley startup, Singularitarianism, software is eating the world, Solyndra, Steve Jobs, strong AI, Suez canal 1869, tech worker, Ted Kaczynski, Tesla Model S, uber lyft, Vilfredo Pareto, working poor

Indefinite Politics Politicians have always been officially accountable to the public at election time, but today they are attuned to what the public thinks at every moment. Modern polling enables politicians to tailor their image to match preexisting public opinion exactly, so for the most part, they do. Nate Silver’s election predictions are remarkably accurate, but even more remarkable is how big a story they become every four years. We are more fascinated today by statistical predictions of what the country will be thinking in a few weeks’ time than by visionary predictions of what the country will look like 10 or 20 years from now.

Warnings by Richard A. Clarke

"Hurricane Katrina" Superdome, active measures, Albert Einstein, algorithmic trading, anti-communist, artificial general intelligence, Asilomar, Asilomar Conference on Recombinant DNA, Bear Stearns, behavioural economics, Bernie Madoff, Black Monday: stock market crash in 1987, carbon tax, cognitive bias, collateralized debt obligation, complexity theory, corporate governance, CRISPR, cuban missile crisis, data acquisition, deep learning, DeepMind, discovery of penicillin, double helix, Elon Musk, failed state, financial thriller, fixed income, Flash crash, forensic accounting, friendly AI, Hacker News, 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, Nick Bostrom, nuclear winter, OpenAI, pattern recognition, personalized medicine, phenotype, Ponzi scheme, Ray Kurzweil, Recombinant DNA, Richard Feynman, Richard Feynman: Challenger O-ring, risk tolerance, Ronald Reagan, Sam Altman, Search for Extraterrestrial Intelligence, self-driving car, Silicon Valley, smart grid, statistical model, Stephen Hawking, Stuxnet, subprime mortgage crisis, tacit knowledge, technological singularity, The Future of Employment, the scientific method, The Signal and the Noise by Nate Silver, Tunguska event, uranium enrichment, Vernor Vinge, WarGames: Global Thermonuclear War, 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.

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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.

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

3Com Palm IPO, Alan Greenspan, Albert Einstein, Alvin Roth, Amazon Mechanical Turk, Andrei Shleifer, Apple's 1984 Super Bowl advert, Atul Gawande, behavioural economics, Berlin Wall, Bernie Madoff, Black-Scholes formula, book value, business cycle, 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, equity risk 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, Kickstarter, late fees, law of one price, libertarian paternalism, Long Term Capital Management, loss aversion, low interest rates, market clearing, Mason jar, mental accounting, meta-analysis, money market fund, More Guns, Less Crime, mortgage debt, Myron Scholes, Nash equilibrium, Nate Silver, New Journalism, nudge unit, PalmPilot, Paul Samuelson, payday loans, Ponzi scheme, Post-Keynesian economics, presumed consent, pre–internet, principal–agent problem, prisoner's dilemma, profit maximization, random walk, randomized controlled trial, Richard Thaler, risk free rate, Robert Shiller, Robert Solow, Ronald Coase, Silicon Valley, South Sea Bubble, Stanford marshmallow experiment, statistical model, Steve Jobs, sunk-cost fallacy, Supply of New York City Cabdrivers, systematic bias, 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

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.

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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.

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

23andMe, 3D printing, Affordable Care Act / Obamacare, Anne Wojcicki, Atul Gawande, augmented reality, Big Tech, 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, data science, deep learning, digital divide, disintermediation, disruptive innovation, don't be evil, driverless car, Edward Snowden, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Firefox, gamification, global village, Google Glasses, Google X / Alphabet X, Ignaz Semmelweis: hand washing, information asymmetry, interchangeable parts, Internet of things, Isaac Newton, it's over 9,000, job automation, Julian Assange, Kevin Kelly, license plate recognition, lifelogging, Lyft, Mark Zuckerberg, Marshall McLuhan, meta-analysis, microbiome, Nate Silver, natural language processing, Network effects, Nicholas Carr, obamacare, pattern recognition, personalized medicine, phenotype, placebo effect, quantum cryptography, RAND corporation, randomized controlled trial, Salesforce, 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, synthetic biology, the scientific method, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, traumatic brain injury, Turing test, Uber for X, uber lyft, Watson beat the top human players on Jeopardy!, WikiLeaks, 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.

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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.

The Hype Machine: How Social Media Disrupts Our Elections, Our Economy, and Our Health--And How We Must Adapt by Sinan Aral

Airbnb, Albert Einstein, algorithmic bias, AlphaGo, Any sufficiently advanced technology is indistinguishable from magic, AOL-Time Warner, augmented reality, behavioural economics, Bernie Sanders, Big Tech, bitcoin, Black Lives Matter, Cambridge Analytica, carbon footprint, Cass Sunstein, computer vision, contact tracing, coronavirus, correlation does not imply causation, COVID-19, crowdsourcing, cryptocurrency, data science, death of newspapers, deep learning, deepfake, digital divide, digital nomad, disinformation, disintermediation, Donald Trump, Drosophila, Edward Snowden, Elon Musk, en.wikipedia.org, end-to-end encryption, Erik Brynjolfsson, experimental subject, facts on the ground, fake news, Filter Bubble, George Floyd, global pandemic, hive mind, illegal immigration, income inequality, Kickstarter, knowledge worker, lockdown, longitudinal study, low skilled workers, Lyft, Mahatma Gandhi, Mark Zuckerberg, Menlo Park, meta-analysis, Metcalfe’s law, mobile money, move fast and break things, multi-sided market, Nate Silver, natural language processing, Neal Stephenson, Network effects, performance metric, phenotype, recommendation engine, Robert Bork, Robert Shiller, Russian election interference, Second Machine Age, seminal paper, sentiment analysis, shareholder value, Sheryl Sandberg, skunkworks, Snapchat, social contagion, social distancing, social graph, social intelligence, social software, social web, statistical model, stem cell, Stephen Hawking, Steve Bannon, Steve Jobs, Steve Jurvetson, surveillance capitalism, Susan Wojcicki, Telecommunications Act of 1996, The Chicago School, the strength of weak ties, The Wisdom of Crowds, theory of mind, TikTok, Tim Cook: Apple, Uber and Lyft, uber lyft, WikiLeaks, work culture , Yogi Berra

The twin reports highlight, but do not answer, perhaps the most important question facing democracy in the digital age: to what extent are democratic elections vulnerable to social media manipulation? Journalists and academics have weighed in on this question, often with confident yet contradictory conclusions. Nate Silver, founder and editor in chief of the site FiveThirtyEight, remarked that “if you wrote out a list of the most important factors in the 2016 election, I’m not sure that Russian social media memes would be among the top 100.” Some academics are similarly skeptical, arguing that “Russia-sponsored content on social media likely did not decide the election” because Russian-linked spending and exposure to fake news were relatively small-scale.

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., The IRA, Social Media and Political Polarization in the United States, 2012–2018, Investigation of Russian Interference prepared for the U.S. Senate Select Committee on Intelligence (Graphika, 2019), https://int.nyt.com/​data/​documenthelper/​534-oxford-russia-internet-research-agency/​c6588b4a7b940c551c38/​optimized/​full.pdf. “if you wrote out a list of the most important factors”: Nate Silver, tweet, December 17, 2018, https://twitter.com/​natesilver538/​status/​1074833714931224582?lang=en. “Russia-sponsored content on social media likely”: John Sides, Michael Tesler, and Lynn Vavreck, Identity Crisis: The 2016 Presidential Campaign and the Battle for the Meaning of America (Princeton: Princeton University Press, 2018).

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

Airbus A320, airport security, algorithmic trading, banking crisis, barriers to entry, Bernie Sanders, call centre, Captain Sullenberger Hudson, Cass Sunstein, Charles Lindbergh, classic study, cognitive dissonance, credit crunch, crowdsourcing, dark matter, Dava Sobel, David Brooks, Donald Davies, Evgeny Morozov, Fairchild Semiconductor, future of journalism, Great Leap Forward, high-speed rail, hive mind, Howard Rheingold, HyperCard, Jane Jacobs, John Gruber, John Harrison: Longitude, Joi Ito, Kevin Kelly, Kickstarter, lone genius, Mark Zuckerberg, mega-rich, meta-analysis, Naomi Klein, Nate Silver, Occupy movement, packet switching, peer-to-peer, Peter Thiel, planetary scale, pre–internet, private spaceflight, radical decentralization, RAND corporation, risk tolerance, seminal paper, shareholder value, Silicon Valley, Silicon Valley startup, social graph, SpaceShipOne, Steve Jobs, Steven Pinker, Stewart Brand, systems thinking, techno-determinism, The Death and Life of Great American Cities, the long tail, Tim Cook: Apple, urban planning, US Airways Flight 1549, WikiLeaks, William Langewiesche, working poor, X Prize, Yochai Benkler, your tax dollars at work

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.

Army of None: Autonomous Weapons and the Future of War by Paul Scharre

"World Economic Forum" Davos, active measures, Air France Flight 447, air gap, algorithmic trading, AlphaGo, Apollo 13, artificial general intelligence, augmented reality, automated trading system, autonomous vehicles, basic income, Black Monday: stock market crash in 1987, brain emulation, Brian Krebs, cognitive bias, computer vision, cuban missile crisis, dark matter, DARPA: Urban Challenge, data science, deep learning, DeepMind, DevOps, Dr. Strangelove, drone strike, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, facts on the ground, fail fast, fault tolerance, Flash crash, Freestyle chess, friendly fire, Herman Kahn, IFF: identification friend or foe, ImageNet competition, information security, Internet of things, Jeff Hawkins, Johann Wolfgang von Goethe, John Markoff, Kevin Kelly, Korean Air Lines Flight 007, Loebner Prize, loose coupling, Mark Zuckerberg, military-industrial complex, moral hazard, move 37, mutually assured destruction, Nate Silver, Nick Bostrom, PalmPilot, paperclip maximiser, pattern recognition, Rodney Brooks, Rubik’s Cube, self-driving car, sensor fusion, South China Sea, speech recognition, Stanislav Petrov, Stephen Hawking, Steve Ballmer, Steve Wozniak, Strategic Defense Initiative, Stuxnet, superintelligent machines, Tesla Model S, The Signal and the Noise by Nate Silver, theory of mind, Turing test, Tyler Cowen, universal basic income, Valery Gerasimov, Wall-E, warehouse robotics, William Langewiesche, Y2K, zero day

Later that evening while pouring over a recreation of the final moves, Kasparov discovered that in 20 moves he would have checkmated Deep Blue. The implication was that Deep Blue made a nonsense move and resigned because it could see 20 moves ahead, a staggering advantage in chess. Nate Silver reports that this bug may have irreparably shaken Kasparov’s confidence. Nate Silver, The Signal and the Noise: Why So Many Predictions Fail (New York: Penguin, 2015), 276–289. 150 recent UNIDIR report on autonomous weapons and risk: UN Institute for Disarmament Research, “Safety, Unintentional Risk and Accidents in the Weaponization of Increasingly Autonomous Technologies,” 2016, http://www.unidir.org/files/publications/pdfs/safety-unintentional-risk-and-accidents-en-668.pdf.

Coders: The Making of a New Tribe and the Remaking of the World by Clive Thompson

"Margaret Hamilton" Apollo, "Susan Fowler" uber, 2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 4chan, 8-hour work day, Aaron Swartz, Ada Lovelace, AI winter, air gap, Airbnb, algorithmic bias, AlphaGo, Amazon Web Services, Andy Rubin, Asperger Syndrome, augmented reality, Ayatollah Khomeini, backpropagation, barriers to entry, basic income, behavioural economics, Bernie Sanders, Big Tech, bitcoin, Bletchley Park, blockchain, blue-collar work, Brewster Kahle, Brian Krebs, Broken windows theory, call centre, Cambridge Analytica, cellular automata, Charles Babbage, Chelsea Manning, Citizen Lab, clean water, cloud computing, cognitive dissonance, computer vision, Conway's Game of Life, crisis actor, crowdsourcing, cryptocurrency, Danny Hillis, data science, David Heinemeier Hansson, deep learning, DeepMind, Demis Hassabis, disinformation, don't be evil, don't repeat yourself, Donald Trump, driverless car, dumpster diving, Edward Snowden, Elon Musk, Erik Brynjolfsson, Ernest Rutherford, Ethereum, ethereum blockchain, fake news, false flag, Firefox, Frederick Winslow Taylor, Free Software Foundation, Gabriella Coleman, game design, Geoffrey Hinton, glass ceiling, Golden Gate Park, Google Hangouts, Google X / Alphabet X, Grace Hopper, growth hacking, Guido van Rossum, Hacker Ethic, hockey-stick growth, HyperCard, Ian Bogost, illegal immigration, ImageNet competition, information security, Internet Archive, Internet of things, Jane Jacobs, John Markoff, Jony Ive, Julian Assange, Ken Thompson, Kickstarter, Larry Wall, lone genius, Lyft, Marc Andreessen, Mark Shuttleworth, Mark Zuckerberg, Max Levchin, Menlo Park, meritocracy, microdosing, microservices, Minecraft, move 37, move fast and break things, Nate Silver, Network effects, neurotypical, Nicholas Carr, Nick Bostrom, no silver bullet, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, Oculus Rift, off-the-grid, OpenAI, operational security, opioid epidemic / opioid crisis, PageRank, PalmPilot, paperclip maximiser, pattern recognition, Paul Graham, paypal mafia, Peter Thiel, pink-collar, planetary scale, profit motive, ransomware, recommendation engine, Richard Stallman, ride hailing / ride sharing, Rubik’s Cube, Ruby on Rails, Sam Altman, Satoshi Nakamoto, Saturday Night Live, scientific management, self-driving car, side project, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, single-payer health, Skype, smart contracts, Snapchat, social software, software is eating the world, sorting algorithm, South of Market, San Francisco, speech recognition, Steve Wozniak, Steven Levy, systems thinking, TaskRabbit, tech worker, techlash, TED Talk, the High Line, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, universal basic income, urban planning, Wall-E, Watson beat the top human players on Jeopardy!, WeWork, WikiLeaks, women in the workforce, Y Combinator, Zimmermann PGP, éminence grise

the general population: Peter Ryan, “Left, Right and Center: Crypto Isn’t Just for Libertarians Anymore,” CoinDesk, July 27, 2018, https://www.coindesk.com/no-crypto-isnt-just-for-libertarians-anymore; Nate Silver, “There Are Few Libertarians. But Many Americans Have Libertarian Views,” FiveThirtyEight, April 9, 2015, https://fivethirtyeight.com/features/there-are-few-libertarians-but-many-americans-have-libertarian-views/; both accessed October 7, 2018">https://www.coindesk.com/no-crypto-isnt-just-for-libertarians-anymore; Nate Silver, “There Are Few Libertarians. But Many Americans Have Libertarian Views,” FiveThirtyEight, April 9, 2015, https://fivethirtyeight.com/features/there-are-few-libertarians-but-many-americans-have-libertarian-views/; both accessed October 7, 2018.

Spies, Lies, and Algorithms by Amy B. Zegart

2021 United States Capitol attack, 4chan, active measures, air gap, airport security, Apollo 13, Bellingcat, Bernie Sanders, Bletchley Park, Chelsea Manning, classic study, cloud computing, cognitive bias, commoditize, coronavirus, correlation does not imply causation, COVID-19, crowdsourcing, cryptocurrency, cuban missile crisis, Daniel Kahneman / Amos Tversky, deep learning, deepfake, DeepMind, disinformation, Donald Trump, drone strike, dual-use technology, Edward Snowden, Elon Musk, en.wikipedia.org, end-to-end encryption, failed state, feminist movement, framing effect, fundamental attribution error, Gene Kranz, global pandemic, global supply chain, Google Earth, index card, information asymmetry, information security, Internet of things, job automation, John Markoff, lockdown, Lyft, Mark Zuckerberg, Nate Silver, Network effects, off-the-grid, openstreetmap, operational security, Parler "social media", post-truth, power law, principal–agent problem, QAnon, RAND corporation, Richard Feynman, risk tolerance, Robert Hanssen: Double agent, Ronald Reagan, Rubik’s Cube, Russian election interference, Saturday Night Live, selection bias, seminal paper, Seymour Hersh, Silicon Valley, Steve Jobs, Stuxnet, synthetic biology, uber lyft, unit 8200, uranium enrichment, WikiLeaks, zero day, zero-sum game

In 2016, pollsters with advanced data analytics didn’t do any better. Four models tracked by the New York Times gave Republican candidate Donald Trump a 15 percent, 8 percent, 2 percent, and less than 1 percent chance of winning against Democratic candidate Hillary Clinton. Even statistics guru Nate Silver put the odds of a Trump victory at just 29 percent.15 But we often forget that some things are much easier to predict than others. The foreseeability of the world out there varies in systematic ways for systematic reasons. The Predictability Spectrum: Four Key Factors As figure 5.1 shows, predictability lies along a spectrum.

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William Stueck, Rethinking the Korean War: A New Diplomatic and Strategic History (Princeton, N.J.: Princeton University Press, 2002), 113. 14. Elizabeth Mix, “Dewey Defeats Truman Election Headline Gaffe,” History, November 1, 2018, (updated November 4, 2019), https://www.history.com/news/dewey-defeats-truman-election-headline-gaffe. 15. Nate Silver, “Why FiveThirtyEight Gave Trump a Better Chance Than Almost Anyone Else,” FiveThirtyEight, November 11, 2016, https://fivethirtyeight.com/features/why-fivethirtyeight-gave-trump-a-better-chance-than-almost-anyone-else/. 16. “Baseball Stats and History,” Baseball Reference, https://www.baseball-reference.com/. 17.

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

Adam Curtis, affirmative action, Affordable Care Act / Obamacare, Alan Greenspan, American Legislative Exchange Council, An Inconvenient Truth, anti-communist, Bakken shale, bank run, battle of ideas, Berlin Wall, Capital in the Twenty-First Century by Thomas Piketty, carbon tax, carried interest, centre right, clean water, Climategate, Climatic Research Unit, collective bargaining, company town, corporate raider, crony capitalism, David Brooks, desegregation, disinformation, diversified portfolio, Donald Trump, energy security, estate planning, Fall of the Berlin Wall, financial engineering, George Gilder, high-speed rail, housing crisis, hydraulic fracturing, income inequality, independent contractor, Intergovernmental Panel on Climate Change (IPCC), invisible hand, job automation, low skilled workers, mandatory minimum, market fundamentalism, mass incarceration, military-industrial complex, Mont Pelerin Society, More Guns, Less Crime, multilevel marketing, Nate Silver, Neil Armstrong, New Journalism, obamacare, Occupy movement, offshore financial centre, oil shale / tar sands, oil shock, plutocrats, Powell Memorandum, Ralph Nader, Renaissance Technologies, road to serfdom, Robert Mercer, Ronald Reagan, school choice, school vouchers, Solyndra, 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.”

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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.

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

Affordable Care Act / Obamacare, autism spectrum disorder, Black Swan, business intelligence, Carmen Reinhart, cognitive bias, correlation does not imply causation, Daniel Kahneman / Amos Tversky, data science, 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, 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

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.

Bulletproof Problem Solving by Charles Conn, Robert McLean

active transport: walking or cycling, Airbnb, Amazon Mechanical Turk, asset allocation, availability heuristic, Bayesian statistics, behavioural economics, Big Tech, Black Swan, blockchain, book value, business logic, business process, call centre, carbon footprint, cloud computing, correlation does not imply causation, Credit Default Swap, crowdsourcing, David Brooks, deep learning, Donald Trump, driverless car, drop ship, Elon Musk, endowment effect, fail fast, fake news, future of work, Garrett Hardin, Hyperloop, Innovator's Dilemma, inventory management, iterative process, loss aversion, megaproject, meta-analysis, Nate Silver, nudge unit, Occam's razor, pattern recognition, pets.com, prediction markets, principal–agent problem, RAND corporation, randomized controlled trial, risk tolerance, Silicon Valley, SimCity, smart contracts, stem cell, sunk-cost fallacy, the rule of 72, the scientific method, The Signal and the Noise by Nate Silver, time value of money, Tragedy of the Commons, transfer pricing, Vilfredo Pareto, walkable city, WikiLeaks

Todd, and the ABC Research Group, Simple Heuristics That Make Us Smart (Oxford University Press, 2000). 3  Report prepared for the United Kingdom's Department of International Development by The Nature Conservancy, WWF, and the University of Manchester, “Improving Hydropower Outcomes through System Scale Planning, An Example from Myanmar,” 2016. 4  Warren Buffett, “My Philanthropic Pledge,” Fortune, June 16, 2010. 5  Our friend Barry Nalebuff of Yale points out that the actual rule is 69.3, but is usually rounded up to 72 because it is easier to do the division in your head. 6  CB Insights, May 25, 2015, www.cbinsights.com. 7  Nate Silver, The Signal and the Noise (Penguin, 2012). 8  Dan Lovallo, Carmina Clarke, and Colin Camerer, “Robust Analogizing and the Outside View: Two Empirical Tests of Case Based Decision Making,” Strategic Management Journal 33, no. 5 (2012): 496–512. 9  “‘Chainsaw Al’ Axed,” CNN Money, June 15, 1998. 10  This problem was suggested by Barry Nalebuff of Yale University. 11  Nicklas Garemo, Stefan Matzinger, and Robert Palter, “Megaprojects: The Good, the Bad, and the Better,” McKinsey Quarterly, July 2015 (quoting Bent Flyvberg, Oxford Saïd Business School). 12  Daniel Kahneman, Dan Lovallo, and Olivier Sibony, “Before You Make that Big Decision,” Harvard Business Review, June 2011. 13  Gerd Gigerenzer, Peter M.

Whiplash: How to Survive Our Faster Future by Joi Ito, Jeff Howe

3D printing, air gap, Albert Michelson, AlphaGo, Amazon Web Services, artificial general intelligence, basic income, Bernie Sanders, Big Tech, bitcoin, Black Lives Matter, Black Swan, Bletchley Park, blockchain, Burning Man, business logic, buy low sell high, Claude Shannon: information theory, cloud computing, commons-based peer production, Computer Numeric Control, conceptual framework, CRISPR, crowdsourcing, cryptocurrency, data acquisition, deep learning, DeepMind, Demis Hassabis, digital rights, disruptive innovation, Donald Trump, double helix, Edward Snowden, Elon Musk, Ferguson, Missouri, fiat currency, financial innovation, Flash crash, Ford Model T, frictionless, game design, Gerolamo Cardano, informal economy, information security, interchangeable parts, Internet Archive, Internet of things, Isaac Newton, Jeff Bezos, John Harrison: Longitude, Joi Ito, Khan Academy, Kickstarter, Mark Zuckerberg, microbiome, move 37, Nate Silver, Network effects, neurotypical, Oculus Rift, off-the-grid, One Laptop per Child (OLPC), PalmPilot, pattern recognition, peer-to-peer, pirate software, power law, pre–internet, prisoner's dilemma, Productivity paradox, quantum cryptography, race to the bottom, RAND corporation, random walk, Ray Kurzweil, Ronald Coase, Ross Ulbricht, Satoshi Nakamoto, self-driving car, SETI@home, side project, Silicon Valley, Silicon Valley startup, Simon Singh, Singularitarianism, Skype, slashdot, smart contracts, Steve Ballmer, Steve Jobs, Steven Levy, Stewart Brand, Stuxnet, supply-chain management, synthetic biology, technological singularity, technoutopianism, TED Talk, The Nature of the Firm, the scientific method, The Signal and the Noise by Nate Silver, the strength of weak ties, There's no reason for any individual to have a computer in his home - Ken Olsen, Thomas Kuhn: the structure of scientific revolutions, Two Sigma, universal basic income, unpaid internship, uranium enrichment, urban planning, warehouse automation, warehouse robotics, Wayback Machine, WikiLeaks, Yochai Benkler

., 13 34 Page is referring to the famous scene in the mockumentary This Is Spinal Tap in which the mentally addled lead guitarist, Nigel Tufnel, tries to explain the significance of an amplifier with the capacity to exceed the conventional 10 on the volume knob. “Well, it’s one louder, isn’t it?” 35 Quoted in Joichi Ito and Jeff Howe, “The Future: An Instruction Manual,” LinkedIn Pulse, October 2, 2012, https://www.linkedin.com/pulse/20121002120301-1391-the-future-an-instruction-manual. 36 Nate Silver, The Signal and the Noise: Why So Many Predictions Fail (New York: Penguin, 2012); Louis Menand, “Everybody’s an Expert,” New Yorker, December 5, 2005, http://www.newyorker.com/magazine/2005/12/05/everybodys-an-expert; Stephen J. Dubner, “The Folly of Prediction,” Freakonomics podcast, September 14, 2011, http://freakonomics.com/2011/09/14/new-freakonomics-radio-podcast-the-folly-of-prediction/. 37 National Council for Science and the Environment, The Climate Solutions Consensus: What We Know and What to Do About It, edited by David Blockstein and Leo Wiegman (Washington, D.C.: Island Press, 2012), 3. 38 Oxford Advanced Learner’s Dictionary, http://www.oxforddictionaries.com/us/definition/learner/medium. 39 The Media Lab’s website includes a comprehensive overview of the Lab’s funding model, current research, and history. http://media.mit.edu/about/about-the-lab. 40 Olivia Vanni.

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

3D printing, algorithmic bias, algorithmic trading, Alvin Toffler, Any sufficiently advanced technology is indistinguishable from magic, augmented reality, big data - Walmart - Pop Tarts, call centre, Cass Sunstein, classic study, Clayton Christensen, commoditize, computer age, death of newspapers, deferred acceptance, disruptive innovation, Edward Lorenz: Chaos theory, Erik Brynjolfsson, Evgeny Morozov, Filter Bubble, Flash crash, Florence Nightingale: pie chart, Ford Model T, Frank Levy and Richard Murnane: The New Division of Labor, fulfillment center, Google Earth, Google Glasses, High speed trading, Internet Archive, Isaac Newton, Jaron Lanier, Jeff Bezos, job automation, John Markoff, Kevin Kelly, Kodak vs Instagram, Lewis Mumford, lifelogging, machine readable, machine translation, Marshall McLuhan, means of production, Nate Silver, natural language processing, Netflix Prize, Panopticon Jeremy Bentham, Paradox of Choice, pattern recognition, price discrimination, recommendation engine, Richard Thaler, Rosa Parks, scientific management, self-driving car, sentiment analysis, Silicon Valley, Silicon Valley startup, Slavoj Žižek, social graph, speech recognition, stable marriage problem, Steve Jobs, Steven Levy, Steven Pinker, Stewart Brand, technological determinism, technological solutionism, TED Talk, the long tail, 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.

Trumpocalypse: Restoring American Democracy by David Frum

Affordable Care Act / Obamacare, anti-globalists, Bernie Sanders, carbon tax, centre right, coronavirus, currency manipulation / currency intervention, decarbonisation, deplatforming, disinformation, Donald Trump, Edward Snowden, employer provided health coverage, fake news, green new deal, Greta Thunberg, illegal immigration, immigration reform, labor-force participation, manufacturing employment, mass immigration, microaggression, Mikhail Gorbachev, Nate Silver, obamacare, offshore financial centre, open immigration, Paris climate accords, Peter Thiel, plutocrats, QAnon, rent-seeking, Ronald Reagan, Saturday Night Live, Silicon Valley, Steve Bannon, W. E. B. Du Bois

“Generic Congressional Ballot,” Rasmussen Reports, November 5, 2018, http://www.rasmussenreports.com/public_content/politics/mood_of_america/generic_congressional_ballot_nov05. President Trump has sometimes tweeted 50 percent numbers generated by the Rasmussen poll, but Rasmussen habitually screens for “likely” voters in a way that favors Republicans. This method produces headlines very appealing to Fox News between elections, but poor accuracy at elections. Nate Silver has rated Rasmussen consistently the least accurate of the major pollsters. Rasmussen enjoyed a fleeting triumph in 2016. That year its persistent habit of overestimating white turnout for once paid off. Driven by a surge in voting by white noncollege graduates, white turnout actually increased between 2012 and 2016, something that has not happened in memory: normally the US electorate becomes about slightly less white each election than the election before.

Pivot: The Only Move That Matters Is Your Next One by Jenny Blake

Airbnb, Albert Einstein, Cal Newport, cloud computing, content marketing, data is the new oil, diversified portfolio, do what you love, East Village, en.wikipedia.org, Erik Brynjolfsson, fear of failure, future of work, high net worth, Jeff Bezos, job-hopping, Kevin Kelly, Khan Academy, knowledge worker, Lao Tzu, Lean Startup, minimum viable product, Nate Silver, passive income, Ralph Waldo Emerson, risk tolerance, Second Machine Age, sharing economy, side hustle, side project, Silicon Valley, Silicon Valley startup, Skype, Snapchat, software as a service, solopreneur, Startup school, stem cell, TED Talk, too big to fail, Tyler Cowen, white picket fence, young professional, zero-sum game

Aggregating and analyzing data, conducting original research: With increasingly more data available on everything from how many steps we take, to our heart rate, to mapping our genome, people will need help making sense of this data, “separating the signal from the noise,” as political pollster Nate Silver does. Some say that “data is the new oil” in our digital economy, and must be refined in order to add value. REVEL IN THE WORK OTHERS REJECT After four years at her PR firm, Amy Schoenberger, who you met in the introduction, started feeling uninspired. She knew that it was time to make a change; however, she loved her company, the culture, and the people, and she did not want to leave.

Cogs and Monsters: What Economics Is, and What It Should Be by Diane Coyle

3D printing, additive manufacturing, Airbnb, Al Roth, Alan Greenspan, algorithmic management, Amazon Web Services, autonomous vehicles, banking crisis, barriers to entry, behavioural economics, Big bang: deregulation of the City of London, biodiversity loss, bitcoin, Black Lives Matter, Boston Dynamics, Bretton Woods, Brexit referendum, business cycle, call centre, Carmen Reinhart, central bank independence, choice architecture, Chuck Templeton: OpenTable:, cloud computing, complexity theory, computer age, conceptual framework, congestion charging, constrained optimization, coronavirus, COVID-19, creative destruction, credit crunch, data science, DeepMind, deglobalization, deindustrialization, Diane Coyle, discounted cash flows, disintermediation, Donald Trump, Edward Glaeser, en.wikipedia.org, endogenous growth, endowment effect, Erik Brynjolfsson, eurozone crisis, everywhere but in the productivity statistics, Evgeny Morozov, experimental subject, financial deregulation, financial innovation, financial intermediation, Flash crash, framing effect, general purpose technology, George Akerlof, global supply chain, Goodhart's law, Google bus, haute cuisine, High speed trading, hockey-stick growth, Ida Tarbell, information asymmetry, intangible asset, Internet of things, invisible hand, Jaron Lanier, Jean Tirole, job automation, Joseph Schumpeter, Kenneth Arrow, Kenneth Rogoff, knowledge economy, knowledge worker, Les Trente Glorieuses, libertarian paternalism, linear programming, lockdown, Long Term Capital Management, loss aversion, low earth orbit, lump of labour, machine readable, market bubble, market design, Menlo Park, millennium bug, Modern Monetary Theory, Mont Pelerin Society, multi-sided market, Myron Scholes, Nash equilibrium, Nate Silver, Network effects, Occupy movement, Pareto efficiency, payday loans, payment for order flow, Phillips curve, post-industrial society, price mechanism, Productivity paradox, quantitative easing, randomized controlled trial, rent control, rent-seeking, ride hailing / ride sharing, road to serfdom, Robert Gordon, Robert Shiller, Robert Solow, Robinhood: mobile stock trading app, Ronald Coase, Ronald Reagan, San Francisco homelessness, savings glut, school vouchers, sharing economy, Silicon Valley, software is eating the world, spectrum auction, statistical model, Steven Pinker, tacit knowledge, The Chicago School, The Future of Employment, The Great Moderation, the map is not the territory, The Rise and Fall of American Growth, the scientific method, The Signal and the Noise by Nate Silver, the strength of weak ties, The Wealth of Nations by Adam Smith, total factor productivity, transaction costs, Uber for X, urban planning, winner-take-all economy, Winter of Discontent, women in the workforce, Y2K

We are typically trying to test hypotheses about a small number of variables in a complex world of millions of variables, with a huge amount of two-way feedback or simultaneity, and using a relatively small amount of data, sometimes of dubious quality. It is difficult in the extreme to establish causality rather than correlation. Neither RCTs nor more realistic assumptions in economic models make a difference to the sheer difficulty of the empirical challenge. Nate Silver writes in his bestseller The Signal and the Noise: The government produces data on literally 45,000 economic indicators each year. Private data providers track as many as four million statistics. The temptation that some economists succumb to is to put all this data into a blender and claim that the resulting gruel is haute cuisine.

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

Affordable Care Act / Obamacare, Airbnb, Apollo 13, asset allocation, Atul Gawande, barriers to entry, Basel III, behavioural economics, Berlin Wall, carbon footprint, Checklist Manifesto, complexity theory, Craig Reynolds: boids flock, Credit Default Swap, Daniel Kahneman / Amos Tversky, democratizing finance, diversification, drone strike, en.wikipedia.org, European colonialism, Exxon Valdez, facts on the ground, Fall of the Berlin Wall, Glass-Steagall Act, Golden age of television, haute cuisine, invention of the printing press, Isaac Newton, Kickstarter, late fees, Lean Startup, Louis Pasteur, Lyft, machine translation, 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, seminal paper, 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.

The New Class Conflict by Joel Kotkin

2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, affirmative action, Affordable Care Act / Obamacare, Alvin Toffler, American Society of Civil Engineers: Report Card, back-to-the-city movement, Bob Noyce, Boston Dynamics, California gold rush, Californian Ideology, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, classic study, Cornelius Vanderbilt, creative destruction, crony capitalism, David Graeber, degrowth, deindustrialization, do what you love, don't be evil, Downton Abbey, driverless car, Edward Glaeser, Elon Musk, energy security, falling living standards, future of work, Future Shock, Gini coefficient, Google bus, Herman Kahn, housing crisis, income inequality, independent contractor, informal economy, Internet of things, Jane Jacobs, Jaron Lanier, Jeff Bezos, job automation, John Markoff, John von Neumann, Joseph Schumpeter, Kevin Kelly, Kevin Roose, labor-force participation, Larry Ellison, Lewis Mumford, low interest rates, low-wage service sector, Marc Andreessen, Mark Zuckerberg, Mary Meeker, mass affluent, McJob, McMansion, medical bankruptcy, microapartment, Nate Silver, National Debt Clock, New Economic Geography, new economy, New Urbanism, obamacare, offshore financial centre, Paul Buchheit, payday loans, Peter Calthorpe, plutocrats, post-industrial society, public intellectual, RAND corporation, Ray Kurzweil, rent control, rent-seeking, Report Card for America’s Infrastructure, Richard Florida, Sheryl Sandberg, Silicon Valley, Silicon Valley billionaire, Silicon Valley ideology, Solyndra, Steve Jobs, stock buybacks, tech worker, techlash, technoutopianism, The Death and Life of Great American Cities, Thomas L Friedman, Tony Fadell, too big to fail, transcontinental railway, trickle-down economics, Tyler Cowen, Tyler Cowen: Great Stagnation, upwardly mobile, urban planning, urban sprawl, Virgin Galactic, War on Poverty, women in the workforce, working poor, young professional

Hall, “With Help from Silicon Valley, America to Dominate the 21st Century,” Tech.pinions, August 12, 2013, http://techpinions.com/help-silicon-valley-america-dominate-21st-century/21550. 101. John B. Judis, “The GOP Plan to Crush Silicon Valley What Will Become of Steve Jobs’s Angel?” New Republic, August 20, 2013, http://www.newrepublic.com/article/114329/republican-budget-cut-would-crush-silicon-valley; Nate Silver, “In Silicon Valley, Technology Talent Gap Threatens G.O.P. Campaigns,” FiveThirtyEight (blog), New York Times, November 28, 2012, http://fivethirtyeight.blogs.nytimes.com/2012/11/28/in-silicon-valley-technology-talent-gap-threatens-g-o-p-campaigns. 102. Matthew Continetti, “The California Captivity of the Democratic Party,” Washington Free Beacon, May 31, 2013, http://freebeacon.com/columns/the-california-captivity-of-the-democratic-party. 103.

Twilight of the Elites: America After Meritocracy by Chris Hayes

"Hurricane Katrina" Superdome, "World Economic Forum" Davos, affirmative action, Affordable Care Act / Obamacare, Alan Greenspan, asset-backed security, barriers to entry, Bear Stearns, 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, meritocracy, meta-analysis, military-industrial complex, money market fund, moral hazard, Naomi Klein, Nate Silver, peak oil, plutocrats, Ponzi scheme, post-truth, radical decentralization, Ralph Waldo Emerson, rolodex, Savings and loan crisis, 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.

The Internet Is Not the Answer by Andrew Keen

"World Economic Forum" Davos, 3D printing, A Declaration of the Independence of Cyberspace, Airbnb, AltaVista, Andrew Keen, AOL-Time Warner, augmented reality, Bay Area Rapid Transit, Berlin Wall, Big Tech, bitcoin, Black Swan, Bob Geldof, Boston Dynamics, Burning Man, Cass Sunstein, Charles Babbage, citizen journalism, Clayton Christensen, clean water, cloud computing, collective bargaining, Colonization of Mars, computer age, connected car, creative destruction, cuban missile crisis, data science, David Brooks, decentralized internet, DeepMind, digital capitalism, disintermediation, disruptive innovation, Donald Davies, Downton Abbey, Dr. Strangelove, driverless car, Edward Snowden, Elon Musk, Erik Brynjolfsson, fail fast, Fall of the Berlin Wall, Filter Bubble, Francis Fukuyama: the end of history, Frank Gehry, Frederick Winslow Taylor, frictionless, fulfillment center, full employment, future of work, gentrification, gig economy, global village, Google bus, Google Glasses, Hacker Ethic, happiness index / gross national happiness, holacracy, income inequality, index card, informal economy, information trail, Innovator's Dilemma, Internet of things, Isaac Newton, Jaron Lanier, Jeff Bezos, job automation, John Perry Barlow, Joi Ito, Joseph Schumpeter, Julian Assange, Kevin Kelly, Kevin Roose, Kickstarter, Kiva Systems, Kodak vs Instagram, Lean Startup, libertarian paternalism, lifelogging, Lyft, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, Martin Wolf, Mary Meeker, Metcalfe’s law, military-industrial complex, move fast and break things, Nate Silver, Neil Armstrong, Nelson Mandela, Network effects, new economy, Nicholas Carr, nonsequential writing, Norbert Wiener, Norman Mailer, Occupy movement, packet switching, PageRank, Panopticon Jeremy Bentham, Patri Friedman, Paul Graham, peer-to-peer, peer-to-peer rental, Peter Thiel, plutocrats, Potemkin village, power law, precariat, pre–internet, printed gun, Project Xanadu, RAND corporation, Ray Kurzweil, reality distortion field, ride hailing / ride sharing, Robert Metcalfe, Robert Solow, San Francisco homelessness, scientific management, Second Machine Age, self-driving car, sharing economy, Sheryl Sandberg, Silicon Valley, Silicon Valley billionaire, Silicon Valley ideology, Skype, smart cities, Snapchat, social web, South of Market, San Francisco, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, subscription business, TaskRabbit, tech bro, tech worker, TechCrunch disrupt, Ted Nelson, telemarketer, The future is already here, The Future of Employment, the long tail, the medium is the message, the new new thing, Thomas L Friedman, Travis Kalanick, Twitter Arab Spring, Tyler Cowen, Tyler Cowen: Great Stagnation, Uber for X, uber lyft, urban planning, Vannevar Bush, warehouse robotics, Whole Earth Catalog, WikiLeaks, winner-take-all economy, work culture , 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.

Artificial Unintelligence: How Computers Misunderstand the World by Meredith Broussard

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

It used to be that you would get stories by chatting to people in bars, and it still might be that you’ll do it that way some times. But now it’s also going to be about poring over data and equipping yourself with the tools to analyse it and picking out what’s interesting. And keeping it in perspective, helping people out by really seeing where it all fits together, and what’s going on in the country.”19 By the time Nate Silver launched FiveThirtyEight.com and published his book The Signal and the Noise in 2012, the term data journalism was in widespread use among investigative journalists.20 As computers have evolved, human nature has not. People need to be kept honest. I hope that this book will help you think like a data journalist so that you can challenge false claims about technology and uncover injustice and inequality embedded in today’s computational systems.

Ten Lessons for a Post-Pandemic World by Fareed Zakaria

"there is no alternative" (TINA), 15-minute city, AlphaGo, An Inconvenient Truth, anti-fragile, Asian financial crisis, basic income, Bernie Sanders, Boris Johnson, butterfly effect, Capital in the Twenty-First Century by Thomas Piketty, car-free, carbon tax, central bank independence, clean water, cloud computing, colonial rule, contact tracing, coronavirus, COVID-19, Credit Default Swap, David Graeber, Day of the Dead, deep learning, DeepMind, deglobalization, Demis Hassabis, Deng Xiaoping, digital divide, Dominic Cummings, Donald Trump, Edward Glaeser, Edward Jenner, Elon Musk, Erik Brynjolfsson, failed state, financial engineering, Francis Fukuyama: the end of history, future of work, gentrification, George Floyd, gig economy, Gini coefficient, global pandemic, global reserve currency, global supply chain, green new deal, hiring and firing, housing crisis, imperial preference, income inequality, Indoor air pollution, invention of the wheel, Jane Jacobs, Jeff Bezos, Jeremy Corbyn, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Snow's cholera map, junk bonds, lockdown, Long Term Capital Management, low interest rates, manufacturing employment, Marc Andreessen, Mark Zuckerberg, Martin Wolf, means of production, megacity, Mexican peso crisis / tequila crisis, middle-income trap, Monroe Doctrine, Nate Silver, Nick Bostrom, oil shock, open borders, out of africa, Parag Khanna, Paris climate accords, Peter Thiel, plutocrats, popular capitalism, Productivity paradox, purchasing power parity, remote working, reserve currency, reshoring, restrictive zoning, ride hailing / ride sharing, Ronald Reagan, secular stagnation, Silicon Valley, social distancing, software is eating the world, South China Sea, Steve Bannon, Steve Jobs, Steven Pinker, Suez crisis 1956, TED Talk, the built environment, The Death and Life of Great American Cities, The inhabitant of London could order by telephone, sipping his morning tea in bed, the various products of the whole earth, The Spirit Level, The Wealth of Nations by Adam Smith, Thomas L Friedman, Tim Cook: Apple, trade route, UNCLOS, universal basic income, urban planning, Washington Consensus, white flight, Works Progress Administration, zoonotic diseases

xItem=54929&ctNode=2198&=9. 90 around a third of the public: 33.4% of the US population have college degrees as of 2016: US Census Bureau, “Educational Attainment in the United States: 2016,” https://www.census.gov/newsroom/press-releases/2017/cb17-51.html; “31% of 25–64 Year Olds Achieved Tertiary Level Study,” European Commission, Eurostat, https://ec.europa.eu/eurostat/web/products-eurostat-news/-/EDN-20181008-1. 90 barely 13%: 13.1% have a master’s, professional degree, or doctorate: US Census Bureau, “Educational Attainment in the United States: 2018,” https://www.census.gov/library/stories/2019/02/number-of-people-with-masters-and-phd-degrees-double-since-2000.html. 90 10% of China’s population: As of 2010 Chinese Census, Education at a Glance: OECD Indicators 2016, “People’s Republic of China,” https://gpseducation.oecd.org/Content/EAGCountryNotes/EAG2016_CN_CHN.pdf. 90 99%: 99.2% of the Chinese Community Party’s 18th Central Committee attended some college as of 2016: Cheng Li, Table 4.1, “Percentage of College-Educated Members on the 8th–18th Central Committees,” Chinese Politics in the Xi Jinping Era: Reassessing Collective Leadership (Washington, DC: Brookings Institution Press, 2016). 91 3.7 times as high: US Census Bureau, “Educational Attainment in the United States: 2018.” 91 Clinton won most of the first group: Nate Silver, “Education, Not Income, Predicted Who Would Vote for Trump,” FiveThirtyEight, November 22, 2016, https://fivethirtyeight.com/features/education-not-income-predicted-who-would-vote-for-trump/. 91 two-thirds of rural Americans approve: Nathaniel Rakich and Dhrumil Mehta, “Trump Is Only Popular in Rural Areas,” FiveThirtyEight, December 7, 2018, https://fivethirtyeight.com/features/trump-is-really-popular-in-rural-areas-other-places-not-so-much/. 91 “no such thing as a Republican city”: Will Wilkinson, “The Density Divide: Urbanization, Polarization, and Populist Backlash,” Niskanen Center, June 2019, https://www.niskanencenter.org/wp-content/uploads/2019/09/Wilkinson-Density-Divide-Final.pdf. 91 those without university degrees: Anushka Asthana, “People Who Felt Marginalised Drove Brexit Vote, Study Finds,” Guardian, August 31, 2016. 91 “yellow vest” protests were powered: Marie Dupin, “Jeunes, Précaires, Ruraux: Qui Sont Les Gilets Jaunes?

A Hacker's Mind: How the Powerful Bend Society's Rules, and How to Bend Them Back by Bruce Schneier

4chan, Airbnb, airport security, algorithmic trading, Alignment Problem, AlphaGo, Automated Insights, banking crisis, Big Tech, bitcoin, blockchain, Boeing 737 MAX, Brian Krebs, Capital in the Twenty-First Century by Thomas Piketty, cloud computing, computerized trading, coronavirus, corporate personhood, COVID-19, cryptocurrency, dark pattern, deepfake, defense in depth, disinformation, Donald Trump, Double Irish / Dutch Sandwich, driverless car, Edward Thorp, Elon Musk, fake news, financial innovation, Financial Instability Hypothesis, first-past-the-post, Flash crash, full employment, gig economy, global pandemic, Goodhart's law, GPT-3, Greensill Capital, high net worth, Hyman Minsky, income inequality, independent contractor, index fund, information security, intangible asset, Internet of things, Isaac Newton, Jeff Bezos, job automation, late capitalism, lockdown, Lyft, Mark Zuckerberg, money market fund, moral hazard, move fast and break things, Nate Silver, offshore financial centre, OpenAI, payday loans, Peter Thiel, precautionary principle, Ralph Nader, recommendation engine, ride hailing / ride sharing, self-driving car, sentiment analysis, Skype, smart cities, SoftBank, supply chain finance, supply-chain attack, surveillance capitalism, systems thinking, TaskRabbit, technological determinism, TED Talk, The Wealth of Nations by Adam Smith, theory of mind, TikTok, too big to fail, Turing test, Uber and Lyft, uber lyft, ubercab, UNCLOS, union organizing, web application, WeWork, When a measure becomes a target, WikiLeaks, zero day

FEAR AND RISK 195very basic brain functions: Bruce Schneier (3 Apr 2000), “The difference between feeling and reality in security,” Wired, https://www.wired.com/2008/04/securitymatters-0403. 196Terrorism directly hacks: Bruce Schneier (17 May 2007), “Virginia Tech lesson: Rare risks breed irrational responses,” Wired, https://www.wired.com/2007/05/securitymatters-0517. 196“When people are insecure”: Nate Silver (1 Feb 2010), “Better to be strong and wrong—especially when you’re actually right,” FiveThirtyEight, https://fivethirtyeight.com/features/better-to-be-strong-and-wrong. 197“immigrants are going to take your jobs”: Fox News (26 Jan 2017), “The truth about jobs in America,” The O’Reilly Factor (transcript), https://www.foxnews.com/transcript/the-truth-about-jobs-in-america. 197“[this or that city] is crime-ridden”: Audrey Conklin (21 Feb 2022), “Homicides, rapes in Atlanta soar despite other decreasing violent crime,” Fox News, https://www.foxnews.com/us/homicides-rapes-atlanta-soar-2022. 197“ISIS is a threat to Americans”: Ronn Blitzer (26 Oct 2021), “Top Pentagon official confirms ISIS-K could have capability to attack US in ‘6 to 12 months,’ ” Fox News, https://www.foxnews.com/politics/pentagon-official-isis-k-us-attack-6-to-12-months. 197“Democrats are going to take your guns”: Tucker Carlson (9 Apr 2021), “Biden wants to take your guns, but leave criminals with theirs,” Fox News, https://www.foxnews.com/opinion/tucker-carlson-biden-gun-control-disarm-trump-voters. 48.

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

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, bike sharing, car-free, City Beautiful movement, collaborative consumption, congestion charging, congestion pricing, crowdsourcing, desegregation, Donald Shoup, driverless car, Enrique Peñalosa, Ford Model T, Ford paid five dollars a day, Frederick Winslow Taylor, high-speed rail, if you build it, they will come, Induced demand, intermodal, invention of the wheel, lake wobegon effect, Lewis Mumford, Loma Prieta earthquake, longitudinal study, Lyft, Masdar, megacity, meta-analysis, moral hazard, Nate Silver, oil shock, parking minimums, Productivity paradox, Ralph Nader, rent control, ride hailing / ride sharing, Rosa Parks, scientific management, self-driving car, skinny streets, smart cities, smart grid, smart transportation, TED Talk, the built environment, the map is not the territory, transportation-network company, Uber and Lyft, Uber for X, uber lyft, 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

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.

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

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

Something of this knowing spectacle remained in Kasparov’s matches with Deep Blue, including his persistent efforts to deploy openings and play styles that would throw off IBM’s algorithms.53 The human engineer was never entirely hidden behind the mechanism, as IBM employees tweaked the system between every game. Perhaps the best example of this relationship was a highly scrutinized move near the end of game one, the truth of which was only revealed in 2012 when IBM researcher Murray Campbell was interviewed by the popular statistician Nate Silver. The move in question had sent Kasparov “into a tizzy” as it seemed to reflect the ambiguity and refinement of a human-level intelligence, and many have suggested it threw off the grandmaster’s concentration for the second game, which he proceeded to lose.54 In fact, as Campbell revealed, the move had been a bug, one the engineers corrected after the first match.55 Kasparov himself had made magic out of the algorithm, inventing a sophisticated cultural explanation for what was in the end a random computational artifact.

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

2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 3D printing, access to a mobile phone, additive manufacturing, Airbnb, Alan Greenspan, 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, Boston Dynamics, British Empire, business cycle, business intelligence, business process, call centre, carbon tax, Charles Lindbergh, Chuck Templeton: OpenTable:, clean water, combinatorial explosion, computer age, computer vision, congestion charging, congestion pricing, corporate governance, cotton gin, creative destruction, crowdsourcing, data science, David Ricardo: comparative advantage, digital map, driverless car, employer provided health coverage, en.wikipedia.org, Erik Brynjolfsson, factory automation, Fairchild Semiconductor, 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, G4S, game design, general purpose technology, global village, GPS: selective availability, Hans Moravec, 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, Jevons paradox, 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, Kiva Systems, 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, One Laptop per Child (OLPC), pattern recognition, Paul Samuelson, payday loans, post-work, power law, price stability, Productivity paradox, profit maximization, Ralph Nader, Ray Kurzweil, recommendation engine, Report Card for America’s Infrastructure, Robert Gordon, Robert Solow, Rodney Brooks, Ronald Reagan, search costs, 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 Cathedral and the Bazaar, the long tail, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, total factor productivity, transaction costs, Tyler Cowen, Tyler Cowen: Great Stagnation, Vernor Vinge, warehouse robotics, 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.

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

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, data science, discrete time, disruptive innovation, George Gilder, Google Earth, hype cycle, Infrastructure as a Service, Internet Archive, Internet of things, invisible hand, knowledge economy, Large Hadron Collider, late capitalism, lifelogging, linked data, longitudinal study, machine readable, Masdar, means of production, Nate Silver, natural language processing, openstreetmap, pattern recognition, platform as a service, recommendation engine, RFID, semantic web, sentiment analysis, SimCity, 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, technological solutionism, the scientific method, The Signal and the Noise by Nate Silver, transaction costs

, 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.

We Need New Stories: Challenging the Toxic Myths Behind Our Age of Discontent by Nesrine Malik

"World Economic Forum" Davos, affirmative action, Affordable Care Act / Obamacare, barriers to entry, Bernie Sanders, Black Lives Matter, Boris Johnson, Brexit referendum, British Empire, centre right, cognitive dissonance, continuation of politics by other means, currency peg, disinformation, Donald Trump, fake news, feminist movement, financial independence, Francis Fukuyama: the end of history, gender pay gap, gentrification, ghettoisation, glass ceiling, illegal immigration, invisible hand, Jeremy Corbyn, mass immigration, moral panic, Nate Silver, obamacare, old-boy network, opioid epidemic / opioid crisis, Overton Window, payday loans, planetary scale, Ponzi scheme, public intellectual, race to the bottom, Ronald Reagan, Saturday Night Live, sexual politics, Steve Bannon, Steven Pinker, The Bell Curve by Richard Herrnstein and Charles Murray, Thomas L Friedman, transatlantic slave trade

In June 2017, Stephens publicly forswore Twitter, saying that the medium debased politics and that he would ‘intercede only to say nice things about the writing I admire, the people I like and the music I love’. In response to criticism of an article of his that misread the success of Democrats in the midterms (and which had to be quietly amended, twice, after more results came in, invalidating his thesis), Stephens tweeted at statistician Nate Silver of 538, ‘too bad you’re a Twitter troll’. Unprovoked, he tweeted at James Zogby, founder and president of the Arab American Institute, who took issue with a chef calling hummus Israeli food, saying it was part of a history of ‘cultural appropriation’ and a systematic effort to erase Palestinian history and culture.

Good to Go: What the Athlete in All of Us Can Learn From the Strange Science of Recovery by Christie Aschwanden

An Inconvenient Truth, fake news, gamification, lifelogging, longitudinal study, meta-analysis, multilevel marketing, Nate Silver, placebo effect, randomized controlled trial, Richard Feynman, Silicon Valley, TED Talk, Watson beat the top human players on Jeopardy!

Anna Barry-Jester fed me almost daily affirmations and was always willing to listen to my ramblings. A woman of a million talents, she also took my author photo. Chad Matlin has been a steadfast supporter of this book from the start. His contention that a book is simply an “idea vehicle” proved surprisingly useful in the project’s early stages. Nate Silver offered helpful advice on book writing, and Blythe Terrell cut me a little slack when I needed it in the final push to finish the manuscript. Working with Maggie Koerth-Baker and my other FiveThirtyEight colleagues has pushed me to become better in every way. Laura Helmuth convinced me I was on track when I wasn’t sure where I was going with this, and Farai Chideya offered helpful advice on how to balance book writing with everything else.

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

"Hurricane Katrina" Superdome, "World Economic Forum" Davos, Airbnb, antiwork, basic income, battle of ideas, Berlin Wall, Bernie Sanders, Black Lives Matter, Brewster Kahle, carbon tax, Carl Icahn, Celebration, Florida, clean water, collective bargaining, Corrections Corporation of America, data science, desegregation, Donald Trump, drone strike, Edward Snowden, Elon Musk, end-to-end encryption, energy transition, extractivism, fake news, financial deregulation, gentrification, Global Witness, greed is good, green transition, high net worth, high-speed rail, Howard Zinn, illegal immigration, impact investing, income inequality, Internet Archive, Kickstarter, late capitalism, Mark Zuckerberg, market bubble, market fundamentalism, mass incarceration, megaproject, Mikhail Gorbachev, military-industrial complex, moral panic, Naomi Klein, Nate Silver, new economy, Occupy movement, ocean acidification, offshore financial centre, oil shale / tar sands, open borders, Paris climate accords, Patri Friedman, Peter Thiel, plutocrats, private military company, profit motive, race to the bottom, Ralph Nader, Ronald Reagan, Saturday Night Live, sexual politics, sharing economy, Silicon Valley, Steve Bannon, subprime mortgage crisis, tech billionaire, too big to fail, trade liberalization, transatlantic slave trade, Triangle Shirtwaist Factory, trickle-down economics, Upton Sinclair, urban decay, W. E. B. Du Bois, women in the workforce, working poor

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.

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

"Hurricane Katrina" Superdome, barriers to entry, Bear Stearns, book value, car-free, carbon footprint, collateralized debt obligation, congestion pricing, failed state, feminist movement, Ford Model T, fudge factor, Gordon Gekko, housing crisis, illegal immigration, income inequality, inventory management, Lewis Mumford, 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, The Theory of the Leisure Class by Thorstein Veblen, Thorstein Veblen, traffic fines, traumatic brain injury, 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.

The Tyranny of Merit: What’s Become of the Common Good? by Michael J. Sandel

affirmative action, Affordable Care Act / Obamacare, anti-communist, Berlin Wall, Bernie Sanders, Boris Johnson, Brexit referendum, Capital in the Twenty-First Century by Thomas Piketty, centre right, coronavirus, COVID-19, Credit Default Swap, Deng Xiaoping, Donald Trump, ending welfare as we know it, facts on the ground, Fall of the Berlin Wall, financial deregulation, financial engineering, financial innovation, global supply chain, helicopter parent, High speed trading, immigration reform, income inequality, Khan Academy, laissez-faire capitalism, meritocracy, meta-analysis, Nate Silver, new economy, obamacare, Occupy movement, open immigration, Paris climate accords, plutocrats, prosperity theology / prosperity gospel / gospel of success, Rishi Sunak, Ronald Reagan, smart grid, social distancing, Steve Jobs, Steven Levy, the market place, The Wealth of Nations by Adam Smith, W. E. B. Du Bois, Washington Consensus, Yochai Benkler

On Trump share of non-college white voters, see 2016 exit polls, CNN, cnn.com/election/2016/results/exit-polls ; Clinton share of advanced degree holders is from Thomas Piketty, “Brahmin Left vs. Merchant Right: Rising Inequality & the Changing Structure of Political Conflict,” wid.world Working Paper Series, March 2018, piketty.pse.ens.fr/files/Piketty2018.pdf , Figure 3.3b; on education versus income, see Nate Silver, “Education, Not Income, Predicted Who Would Vote for Trump,” November 22, 2016, FiveThirtyEight.com , fivethirtyeight.com/features/education-not-income-predicted-who-would-vote-for-trump . 60. Silver, “Education, Not Income, Predicted Who Would Vote for Trump.” Trump quoted in Susan Page, “Trump Does the Impossible—Again,” USA Today , February 25, 2016, usatoday.com/story/news/politics/elections/2016/02/24/analysis-donald-trump-does-impossible-again/80843932 . 61.

Uncharted: How to Map the Future by Margaret Heffernan

"World Economic Forum" Davos, 23andMe, Affordable Care Act / Obamacare, Airbnb, Alan Greenspan, Anne Wojcicki, anti-communist, Atul Gawande, autonomous vehicles, banking crisis, Berlin Wall, Boris Johnson, Brexit referendum, chief data officer, Chris Urmson, clean water, complexity theory, conceptual framework, cosmic microwave background, creative destruction, CRISPR, crowdsourcing, data science, David Attenborough, discovery of penicillin, driverless car, epigenetics, Fall of the Berlin Wall, fear of failure, George Santayana, gig economy, Google Glasses, Greta Thunberg, Higgs boson, index card, Internet of things, Jaron Lanier, job automation, Kickstarter, Large Hadron Collider, late capitalism, lateral thinking, Law of Accelerating Returns, liberation theology, mass immigration, mass incarceration, megaproject, Murray Gell-Mann, Nate Silver, obamacare, oil shale / tar sands, passive investing, pattern recognition, Peter Thiel, prediction markets, RAND corporation, Ray Kurzweil, Rosa Parks, Sam Altman, scientific management, Shoshana Zuboff, Silicon Valley, smart meter, Stephen Hawking, Steve Ballmer, Steve Jobs, surveillance capitalism, TED Talk, The Signal and the Noise by Nate Silver, Tim Cook: Apple, twin studies, University of East Anglia

., 2010 11 Author interview with Robert Skidelsky, 2 August 2018 12 Engelberg, Joseph, Sasseville, Caroline and Williams, Jared, ‘Market Madness? The Case of Mad Money’, Management Science, Vol. 58, Iss. 2, 2012 13 This is one reason why Warren Buffett has advised his wife to invest in tracker funds after this death. The pollster Nate Silver makes the challenging observation that the rare group that does outperform the market is US senators, raising all kinds of questions about inside information. See Silver, Nate, The Signal and the Noise: The Art and Science of Prediction, Penguin Books, London, 2013 14 See The Economist, 17 March 2018, p.39 15 I’m indebted to David Kedmey for pointing this out 16 ‘The Risk of Automation for Jobs in OECD Countries’, www.oecd-ilibrary.org/­social-issues-migration-health/­the-risk-of-automation-for-jobs-in-oecd-countries_5jlz9h56dvq7-en, accessed 14 October 2018 and 27 October 2019 17 ‘5 Things to Know about the Future of Jobs’, www.weforum.org/­agenda/­2018/­09/­future-of-jobs-2018-things-to-know/ 18 Google’s Chris Urmson suggested that the autonomous vehicle ‘has the potential to reduce current Federal spending pressures for roadways, parking and public transit’.

Artificial Whiteness by Yarden Katz

affirmative action, AI winter, algorithmic bias, AlphaGo, Amazon Mechanical Turk, autonomous vehicles, benefit corporation, Black Lives Matter, blue-collar work, Californian Ideology, Cambridge Analytica, cellular automata, Charles Babbage, cloud computing, colonial rule, computer vision, conceptual framework, Danny Hillis, data science, David Graeber, deep learning, DeepMind, desegregation, Donald Trump, Dr. Strangelove, driverless car, Edward Snowden, Elon Musk, Erik Brynjolfsson, European colonialism, fake news, Ferguson, Missouri, general purpose technology, gentrification, Hans Moravec, housing crisis, income inequality, information retrieval, invisible hand, Jeff Bezos, Kevin Kelly, knowledge worker, machine readable, Mark Zuckerberg, mass incarceration, Menlo Park, military-industrial complex, Nate Silver, natural language processing, Nick Bostrom, Norbert Wiener, pattern recognition, phenotype, Philip Mirowski, RAND corporation, recommendation engine, rent control, Rodney Brooks, Ronald Reagan, Salesforce, Seymour Hersh, Shoshana Zuboff, Silicon Valley, Silicon Valley billionaire, Silicon Valley ideology, Skype, speech recognition, statistical model, Stephen Hawking, Stewart Brand, Strategic Defense Initiative, surveillance capitalism, talking drums, telemarketer, The Signal and the Noise by Nate Silver, W. E. B. Du Bois, Whole Earth Catalog, WikiLeaks

See the controversy surrounding Cambridge Analytica as reported, for instance, in “Cambridge Analytica Files,” Guardian, https://www.theguardian.com/news/series/cambridge-analytica-files.     9.   Nick Bilton, “Google Buys A.I. Company for Search, Not Robots,” New York Times, January 28, 2014.   10.   David Ignatius, “A Tech Bridge from the Pentagon to Silicon Valley,” Washington Post, January 25, 2019.   11.   See, for example, Nate Silver, The Signal and the Noise: Why So Many Predictions Fail—but Some Don’t (New York: Penguin, 2012), 264.   12.   The Global Artificial Intelligence Conference of 2018 invited participants to “hear from AI pioneers representing: Google, Capital One, Johnson & Johnson, Bloomberg, Facebook, Amazon, McKinsey, SAP, Microsoft, Biogen, Royal Caribbean Cruise Line, Uber, IBM, The Boston Consulting Group, Trulia Teradata, Columbia Sportswear Company etc.”

Enlightenment Now: The Case for Reason, Science, Humanism, and Progress by Steven Pinker

3D printing, Abraham Maslow, access to a mobile phone, affirmative action, Affordable Care Act / Obamacare, agricultural Revolution, Albert Einstein, Alfred Russel Wallace, Alignment Problem, An Inconvenient Truth, anti-communist, Anton Chekhov, Arthur Eddington, artificial general intelligence, availability heuristic, Ayatollah Khomeini, basic income, Berlin Wall, Bernie Sanders, biodiversity loss, Black Swan, Bonfire of the Vanities, Brexit referendum, business cycle, capital controls, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, carbon tax, Charlie Hebdo massacre, classic study, clean water, clockwork universe, cognitive bias, cognitive dissonance, Columbine, conceptual framework, confounding variable, correlation does not imply causation, creative destruction, CRISPR, crowdsourcing, cuban missile crisis, Daniel Kahneman / Amos Tversky, dark matter, data science, decarbonisation, degrowth, deindustrialization, dematerialisation, demographic transition, Deng Xiaoping, distributed generation, diversified portfolio, Donald Trump, Doomsday Clock, double helix, Eddington experiment, Edward Jenner, effective altruism, Elon Musk, en.wikipedia.org, end world poverty, endogenous growth, energy transition, European colonialism, experimental subject, Exxon Valdez, facts on the ground, fake news, Fall of the Berlin Wall, first-past-the-post, Flynn Effect, food miles, Francis Fukuyama: the end of history, frictionless, frictionless market, Garrett Hardin, germ theory of disease, Gini coefficient, Great Leap Forward, Hacker Conference 1984, Hans Rosling, hedonic treadmill, helicopter parent, Herbert Marcuse, Herman Kahn, Hobbesian trap, humanitarian revolution, Ignaz Semmelweis: hand washing, income inequality, income per capita, Indoor air pollution, Intergovernmental Panel on Climate Change (IPCC), invention of writing, Jaron Lanier, Joan Didion, job automation, Johannes Kepler, John Snow's cholera map, Kevin Kelly, Khan Academy, knowledge economy, l'esprit de l'escalier, Laplace demon, launch on warning, life extension, long peace, longitudinal study, Louis Pasteur, Mahbub ul Haq, Martin Wolf, mass incarceration, meta-analysis, Michael Shellenberger, microaggression, Mikhail Gorbachev, minimum wage unemployment, moral hazard, mutually assured destruction, Naomi Klein, Nate Silver, Nathan Meyer Rothschild: antibiotics, negative emissions, Nelson Mandela, New Journalism, Norman Mailer, nuclear taboo, nuclear winter, obamacare, ocean acidification, Oklahoma City bombing, open economy, opioid epidemic / opioid crisis, paperclip maximiser, Paris climate accords, Paul Graham, peak oil, Peter Singer: altruism, Peter Thiel, post-truth, power law, precautionary principle, precision agriculture, prediction markets, public intellectual, purchasing power parity, radical life extension, Ralph Nader, randomized controlled trial, Ray Kurzweil, rent control, Republic of Letters, Richard Feynman, road to serfdom, Robert Gordon, Rodney Brooks, rolodex, Ronald Reagan, Rory Sutherland, Saturday Night Live, science of happiness, Scientific racism, Second Machine Age, secular stagnation, self-driving car, sharing economy, Silicon Valley, Silicon Valley ideology, Simon Kuznets, Skype, smart grid, Social Justice Warrior, sovereign wealth fund, sparse data, stem cell, Stephen Hawking, Steve Bannon, Steven Pinker, Stewart Brand, Stuxnet, supervolcano, synthetic biology, tech billionaire, technological determinism, technological singularity, Ted Kaczynski, Ted Nordhaus, TED Talk, The Rise and Fall of American Growth, the scientific method, The Signal and the Noise by Nate Silver, The Spirit Level, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, Thomas Malthus, total factor productivity, Tragedy of the Commons, union organizing, universal basic income, University of East Anglia, Unsafe at Any Speed, Upton Sinclair, uranium enrichment, urban renewal, W. E. B. Du Bois, War on Poverty, We wanted flying cars, instead we got 140 characters, women in the workforce, working poor, World Values Survey, Y2K

In the American election, voters in the two lowest income brackets voted for Clinton 52–42, as did those who identified “the economy” as the most important issue. A majority of voters in the four highest income brackets voted for Trump, and Trump voters singled out “immigration” and “terrorism,” not “the economy,” as the most important issues.34 The twisted metal has turned up more promising clues. An article by the statistician Nate Silver began, “Sometimes statistical analysis is tricky, and sometimes a finding just jumps off the page.” That finding jumped right off the page and into the article’s headline: “Education, Not Income, Predicted Who Would Vote for Trump.”35 Why should education have mattered so much? Two uninteresting explanations are that the highly educated happen to affiliate with a liberal political tribe, and that education may be a better long-term predictor of economic security than current income.

…

“How many additional countries will report cases of the Ebola virus in the next eight months?”) and having them write down numerical probabilities. Tetlock also avoided the common fallacy of praising or ridiculing a single probabilistic prediction after the fact, as when the poll aggregator Nate Silver of FiveThirtyEight came under fire for giving Donald Trump just a 29 percent chance of winning the 2016 election.45 Since we cannot replay the election thousands of times and count up the number of times that Trump won, the question of whether the prediction was confirmed or disconfirmed is meaningless.

Hit Makers: The Science of Popularity in an Age of Distraction by Derek Thompson

Airbnb, Albert Einstein, Alexey Pajitnov wrote Tetris, always be closing, augmented reality, Clayton Christensen, data science, Donald Trump, Downton Abbey, Ford Model T, full employment, game design, Golden age of television, Gordon Gekko, hindsight bias, hype cycle, indoor plumbing, industrial cluster, information trail, invention of the printing press, invention of the telegraph, Jeff Bezos, John Snow's cholera map, Kevin Roose, Kodak vs Instagram, linear programming, lock screen, Lyft, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, Mary Meeker, Menlo Park, Metcalfe’s law, Minecraft, Nate Silver, Network effects, Nicholas Carr, out of africa, planned obsolescence, power law, prosperity theology / prosperity gospel / gospel of success, randomized controlled trial, recommendation engine, Robert Gordon, Ronald Reagan, Savings and loan crisis, Silicon Valley, Skype, Snapchat, social contagion, statistical model, Steve Ballmer, Steve Jobs, Steven Levy, Steven Pinker, subscription business, TED Talk, telemarketer, the medium is the message, The Rise and Fall of American Growth, Tyler Cowen, Uber and Lyft, Uber for X, uber lyft, Vilfredo Pareto, Vincenzo Peruggia: Mona Lisa, women in the workforce

Thanks to those whose work inspired this book, directly and implicitly: Raymond Loewy, Stanley Lieberson, Michael Kaminiski, Chris Taylor, Bill Bryson, Malcolm Gladwell, Jonah Berger, Steven Johnson, Tom Vanderbilt, Robert Gordon, David Suisman, Paul Barber, Elizabeth Margulis, John Seabrook, Charles Duhigg, Daniel Kahneman, Steven Pinker, Oliver Sacks, Michael Wolff, Nate Silver, Dan Ariely, Jonathan Franzen, Conor Sen, Felix Salmon, Matthew Yglesias, Ezra Klein, Chris Martin, Marc Andreessen, and Umberto Eco. Thanks to those whose conversations inspired this book, directly and implicitly: Drew Durbin, Lincoln Quirk, Michael Diamond, Jordan Weissmann, Robbie dePicciotto, Laura Martin, Maria Konnikova, Mark Harris, Spencer Kornhaber, Rececca Rosen, Alexis Madrigal, Bob Cohn, John Gould, Don Peck, James Bennet, Kevin Roose, Gabriel Rossman, Jesse Prinz, Duncan Watts, Anne Messitte, Andrew Golis, Aditya Sood, Nicholas Jackson, Seth Godin, the Diamonds, the Durbins, and Kira Thompson.

Machine Learning for Hackers by Drew Conway, John Myles White

call centre, centre right, correlation does not imply causation, data science, Debian, Erdős number, Nate Silver, natural language processing, Netflix Prize, off-by-one error, p-value, pattern recognition, Paul Erdős, recommendation engine, social graph, SpamAssassin, statistical model, text mining, the scientific method, traveling salesman

Given what we have already learned about Drew’s bifurcated brain, this seems like a good match. Keeping this in mind, the rest of the recommendations fit one or both of Drew’s general interests. There is Danger Room (dangerroom); Wired’s National Security blog; Big Data (bigdata); and 538 (fivethirtyeight), the New York Times’ election forecasting blog by Nate Silver. And, of course, shitmydadsays. Although these recommendations are good—and since the writing of the first draft of this book, Drew has enjoyed following the names this engine presented—perhaps there is a better way to recommend people. Because we already know that a given seed user’s network has a lot of emergent structure, it might be useful to use this structure to recommend users that fit into those groups.

Team of Teams: New Rules of Engagement for a Complex World by General Stanley McChrystal, Tantum Collins, David Silverman, Chris Fussell

Airbus A320, Albert Einstein, Apollo 11, Atul Gawande, autonomous vehicles, bank run, barriers to entry, Black Swan, Boeing 747, butterfly effect, call centre, Captain Sullenberger Hudson, Chelsea Manning, clockwork universe, crew resource management, crowdsourcing, driverless car, Edward Snowden, Flash crash, Frederick Winslow Taylor, global supply chain, Henri Poincaré, high batting average, Ida Tarbell, information security, interchangeable parts, invisible hand, Isaac Newton, Jane Jacobs, job automation, job satisfaction, John Nash: game theory, knowledge economy, Mark Zuckerberg, Mohammed Bouazizi, Nate Silver, Neil Armstrong, Pierre-Simon Laplace, pneumatic tube, radical decentralization, RAND corporation, scientific management, self-driving car, Silicon Valley, Silicon Valley startup, Skype, Steve Jobs, supply-chain management, systems thinking, The Wealth of Nations by Adam Smith, urban sprawl, US Airways Flight 1549, vertical integration, WikiLeaks, zero-sum game

Quoted in Ben Ramalingam, Harry Jones, Toussaint Reba, and John Young, Exploring the Science of Complexity: Ideas and Implications for Development and Humanitarian Efforts, vol. 285 (London: Overseas Development Institute, 2008), 10. “The evidence on the folly” . . . Jonathan Davis, “Folly of Forecasting and Useless Data,” Financial Times, January 17, 2010, http://www.ft.com/intl/cms/s/0/b8c4adfe-0202-11df-8b56-00144feabdc0.html#axzz36R3YiZLR. one-in-five-hundred chance . . . Nate Silver, “The Weatherman Is Not a Moron,” New York Times, September 7, 2012, http://www.nytimes.com/2012/09/09/magazine/the-weatherman-is-not-a-moron.html?pagewanted=all. increasingly shorter lifespan . . . http://www.forbes.com/sites/stevedenning/2011/11/19/peggy-noonan-on-steve-jobs-and-why-big-companies-die/.

How to Run a Government: So That Citizens Benefit and Taxpayers Don't Go Crazy by Michael Barber

Affordable Care Act / Obamacare, anti-fragile, Atul Gawande, battle of ideas, Berlin Wall, Black Swan, Checklist Manifesto, collapse of Lehman Brothers, collective bargaining, deep learning, deliberate practice, facts on the ground, failed state, fear of failure, full employment, G4S, illegal immigration, invisible hand, libertarian paternalism, Mark Zuckerberg, Nate Silver, North Sea oil, obamacare, performance metric, Potemkin village, Ronald Reagan, school choice, The Signal and the Noise by Nate Silver, transaction costs, WikiLeaks

And, by the way, if I go down, you’re coming with me.’ In other words, reputations are at risk. But David’s point was right; if you want thousands of public servants to take responsibility for their part in achieving a goal, you need to make it clear that you take your responsibility seriously too. Nate Silver, in his magisterial survey of ‘the art and science of prediction’, The Signal and the Noise, urges us to think probabilistically when we forecast: rather than ‘it’s going to rain tomorrow’, ‘there is a 90 per cent chance of rain tomorrow’. This is, of course, the right way to think analytically when a target is being discussed.

How I Built This: The Unexpected Paths to Success From the World's Most Inspiring Entrepreneurs by Guy Raz

Airbnb, AOL-Time Warner, Apple II, barriers to entry, Bear Stearns, Ben Horowitz, Big Tech, big-box store, Black Monday: stock market crash in 1987, Blitzscaling, business logic, call centre, Clayton Christensen, commoditize, Cornelius Vanderbilt, Credit Default Swap, crowdsourcing, data science, East Village, El Camino Real, Elon Musk, fear of failure, glass ceiling, growth hacking, housing crisis, imposter syndrome, inventory management, It's morning again in America, iterative process, James Dyson, Jeff Bezos, Justin.tv, Kickstarter, low cost airline, Lyft, Marc Andreessen, Mark Zuckerberg, move fast and break things, Nate Silver, Paul Graham, Peter Thiel, pets.com, power law, rolodex, Ronald Reagan, Ruby on Rails, Salesforce, Sam Altman, Sand Hill Road, side hustle, Silicon Valley, software as a service, South of Market, San Francisco, Steve Jobs, Steve Wozniak, subprime mortgage crisis, TED Talk, The Signal and the Noise by Nate Silver, Tony Hsieh, Uber for X, uber lyft, Y Combinator, Zipcar

But it’s doable, particularly when you are able to build buzz among many possible customers while at the same time engineering word of mouth among your ideal customers. 13 Get Attention, Part 2: Engineering Word of Mouth In 2012, amidst an explosion of social networking platforms, smartphones, and big data, the statistician Nate Silver published a book titled The Signal and the Noise, about the difficulty of developing accurate predictions. Up until that point, “signal-to-noise ratio” was a term used primarily by scientists and engineers to describe the power of a desired bit of information in relationship to its surroundings.

Can It Happen Here?: Authoritarianism in America by Cass R. Sunstein

active measures, affirmative action, Affordable Care Act / Obamacare, airline deregulation, anti-communist, anti-globalists, availability heuristic, behavioural economics, Black Lives Matter, Brexit referendum, business cycle, Cambridge Analytica, Cass Sunstein, cognitive load, David Brooks, disinformation, Donald Trump, driverless car, Edward Snowden, Estimating the Reproducibility of Psychological Science, failed state, fake news, Filter Bubble, Francis Fukuyama: the end of history, Garrett Hardin, ghettoisation, illegal immigration, immigration reform, Isaac Newton, job automation, Joseph Schumpeter, Long Term Capital Management, microaggression, Nate Silver, Network effects, New Journalism, night-watchman state, nudge theory, obamacare, Paris climate accords, post-truth, Potemkin village, random walk, Richard Thaler, road to serfdom, Ronald Reagan, seminal paper, Steve Bannon, TED Talk, the scientific method, Tragedy of the Commons, Tyler Cowen, War on Poverty, WikiLeaks, World Values Survey

Shanto Iyengar, Gaurav Sood, and Yohtach Lelkes, “Affect, Not Ideology: A Social Identity Perspective on Polarization,” Public Opinion Quarterly 76 (2012): 405–31. 37. Václav Havel, “The Power of the Powerless,” in The Power of the Powerless: Citizens against the State in Central-Eastern Europe, ed. John Keane, trans. Paul Wilson from 1979 orig. (Armonk, NY: M.E. Sharpe, 1985), 27–28. For an interpretation, see Kuran, Private Truths, chaps. 7 and 13. 38. Nate Silver, “Education, Not Income, Predicted Who Would Vote for Trump,” FiveThirtyEight, November 22, 2016; Alec Tyson and Shiva Maniam, “Behind Trump’s Victory: Divisions by Race, Gender, Education,” Pew Research Center Fact Tank, November 9, 2016. 39. According to exit polls, 81 percent of white evangelicals voted for Trump (Gregory A.

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

"World Economic Forum" Davos, additive manufacturing, AOL-Time Warner, barriers to entry, Berlin Wall, bilateral investment treaty, business cycle, 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, disinformation, disintermediation, disruptive innovation, don't be evil, Evgeny Morozov, 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, Lewis Mumford, liberation theology, Martin Wolf, mega-rich, megacity, military-industrial complex, Naomi Klein, Nate Silver, new economy, Northern Rock, Occupy movement, open borders, open economy, Peace of Westphalia, plutocrats, price mechanism, price stability, private military company, profit maximization, prosperity theology / prosperity gospel / gospel of success, radical decentralization, Ronald Coase, Ronald Reagan, seminal paper, Silicon Valley, Skype, Steve Jobs, The Nature of the Firm, Thomas Malthus, too big to fail, trade route, transaction costs, Twitter Arab Spring, vertical integration, Washington Consensus, WikiLeaks, World Values Survey, zero-sum game

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.

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

Albert Einstein, availability heuristic, behavioural economics, 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, Linda problem, loss aversion, medical residency, Menlo Park, Murray Gell-Mann, Nate Silver, New Journalism, Paul Samuelson, peak-end rule, Richard Thaler, Saturday Night Live, Skinner box, Stanford marshmallow experiment, statistical model, systematic bias, the new new thing, Thomas Bayes, Walter Mischel, Yom Kippur War

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!

Designing Social Interfaces by Christian Crumlish, Erin Malone

A Pattern Language, Amazon Mechanical Turk, anti-pattern, barriers to entry, c2.com, carbon footprint, cloud computing, collaborative editing, commons-based peer production, creative destruction, crowdsourcing, en.wikipedia.org, Firefox, folksonomy, Free Software Foundation, game design, ghettoisation, Howard Rheingold, hypertext link, if you build it, they will come, information security, lolcat, Merlin Mann, Nate Silver, Network effects, Potemkin village, power law, recommendation engine, RFC: Request For Comment, semantic web, SETI@home, Skype, slashdot, social bookmarking, social graph, social software, social web, source of truth, stealth mode startup, Stewart Brand, systems thinking, tacit knowledge, telepresence, the long tail, the strength of weak ties, The Wisdom of Crowds, web application, Yochai Benkler

Remember, everyone is overwhelmed with information and reminders to revisit or share information. If users can send or share content on impulse with immediate gratification, it is much more likely they will take the action and learn to expect to be able to do so (Figure 8-5). Figure 8-5. A reader of Nate Silver’s Fivethirtyeight.com blog asks him to add a sharing widget to his blog template. As a designer of social experiences, you have several potential avenues for employing a Share This widget: • You can design and make your own widget, and use it throughout your service and/ or encourage others to adopt it, thus driving at least some traffic back to your service. • You can publish icons, methods, and APIs for adding your service to existing or incumbent widgets (see Chapter 17). • You can embrace someone else’s widget if you simply want to incorporate its functionality and aren’t using sharing to drive direct participation in your own network or application.

The Age of Entitlement: America Since the Sixties by Christopher Caldwell

1960s counterculture, affirmative action, Affordable Care Act / Obamacare, Alan Greenspan, Alvin Toffler, anti-communist, behavioural economics, Bernie Sanders, big data - Walmart - Pop Tarts, Black Lives Matter, blue-collar work, Cass Sunstein, choice architecture, classic study, computer age, crack epidemic, critical race theory, crony capitalism, Daniel Kahneman / Amos Tversky, David Attenborough, desegregation, disintermediation, disruptive innovation, Edward Snowden, Erik Brynjolfsson, Ferguson, Missouri, financial deregulation, financial innovation, Firefox, full employment, Future Shock, George Gilder, global value chain, Home mortgage interest deduction, illegal immigration, immigration reform, informal economy, James Bridle, Jeff Bezos, John Markoff, junk bonds, Kevin Kelly, Lewis Mumford, libertarian paternalism, Mark Zuckerberg, Martin Wolf, mass immigration, mass incarceration, messenger bag, mortgage tax deduction, Nate Silver, new economy, Norman Mailer, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, open immigration, opioid epidemic / opioid crisis, post-industrial society, pre–internet, profit motive, public intellectual, reserve currency, Richard Thaler, Robert Bork, Robert Gordon, Robert Metcalfe, Ronald Reagan, Rosa Parks, Silicon Valley, Skype, South China Sea, Steve Jobs, tech billionaire, Thomas Kuhn: the structure of scientific revolutions, Thomas L Friedman, too big to fail, transatlantic slave trade, transcontinental railway, W. E. B. Du Bois, War on Poverty, Whole Earth Catalog, zero-sum game

.: Urban-Brookings Tax Policy Center, 2018), 322–23. Online at taxpolicycenter.org/briefing-book. In addition to their liquid assets: Kaplan, Then Comes Marriage, 95. was bankrolled by: From the “HRC Story” page of the Human Rights Campaign, https://www.hrc.org/hrc-story/corporate-partners. Accessed January 4, 2019. Google’s employees gave: Nate Silver, “How Rare Are Anti-Gay-Marriage Donations in Silicon Valley?,” FiveThirtyEight, April 4, 2014. Online at fivethirtyeight.com. Reuters discovered in 2014: Darel E. Paul, “Culture War as Class War,” First Things 285 (August–September 2018): 42. it permitted Windsor to tap: Kaplan, Then Comes Marriage, 56.

Doing Data Science: Straight Talk From the Frontline by Cathy O'Neil, Rachel Schutt

Amazon Mechanical Turk, augmented reality, Augustin-Louis Cauchy, barriers to entry, Bayesian statistics, bike sharing, bioinformatics, computer vision, confounding variable, correlation does not imply causation, crowdsourcing, data science, distributed generation, Dunning–Kruger effect, Edward Snowden, Emanuel Derman, fault tolerance, Filter Bubble, finite state, Firefox, game design, Google Glasses, index card, information retrieval, iterative process, John Harrison: Longitude, Khan Academy, Kickstarter, machine translation, Mars Rover, Nate Silver, natural language processing, Netflix Prize, p-value, pattern recognition, performance metric, personalized medicine, pull request, recommendation engine, rent-seeking, selection bias, Silicon Valley, speech recognition, statistical model, stochastic process, tacit knowledge, text mining, the scientific method, The Wisdom of Crowds, Watson beat the top human players on Jeopardy!, X Prize

We see this in recommendation systems, ranking algorithms, friend suggestions, etc., and we will see it increasingly across sectors including education, finance, retail, and health. Things can go wrong with such feedback loops: keep the financial meltdown in mind as a cautionary example. Much is made about predicting the future (see Nate Silver), predicting the present (see Hal Varian), and exploring causal relationships from observed data (the past; see Sinan Aral). The next logical concept then is: models and algorithms are not only capable of predicting the future, but also of causing the future. That’s what we can look forward to, in the best of cases, and what we should fear in the worst.

The Plague Year: America in the Time of Covid by Lawrence Wright

"World Economic Forum" Davos, 2021 United States Capitol attack, Affordable Care Act / Obamacare, Bernie Sanders, Black Lives Matter, Black Monday: stock market crash in 1987, blockchain, business cycle, contact tracing, coronavirus, COVID-19, cryptocurrency, Donald Trump, Edward Jenner, fake news, full employment, George Floyd, global pandemic, Great Leap Forward, income inequality, jimmy wales, Kickstarter, lab leak, lockdown, Louis Pasteur, meta-analysis, mouse model, Nate Silver, opioid epidemic / opioid crisis, plutocrats, QAnon, RAND corporation, road to serfdom, Ronald Reagan, Silicon Valley, social distancing, Steve Bannon, the scientific method, TikTok, transcontinental railway, zoonotic diseases

seventeen-year-old Trump supporter: John Fritz, Kevin Johnson, and David Jackson, “Trump defends Kyle Rittenhouse on eve of visit to Kenosha,” USA Today, Aug. 31, 2020. widest margin: Alec Tyson and Shiva Maniam, “Behind Trump’s victory: Divisions by race, gender, education,” Pew Research Center, Nov. 9, 2016. “unbreakable lead”: Nate Silver, “The Comey Letter Probably Cost Clinton The Election,” FiveThirtyEight, May 3, 2016. opioid epidemic: Dean Reynolds, “Overdoses now leading cause of death of Americans under 50,” CBS News, June 6, 2017; Adam Dean and Simeon Kimmel, “Free trade and opioid overdose death in the United States,” SSM Population Health, Aug. 8, 2019.

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

accounting loophole / creative accounting, active measures, affirmative action, air traffic controllers' union, Alan Greenspan, asset allocation, barriers to entry, Bear Stearns, Bonfire of the Vanities, business climate, business cycle, 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, Glass-Steagall Act, Home mortgage interest deduction, Howard Zinn, income inequality, invisible hand, John Bogle, knowledge economy, laissez-faire capitalism, Martin Wolf, medical bankruptcy, moral hazard, Nate Silver, new economy, night-watchman state, offshore financial centre, oil shock, Paul Volcker talking about ATMs, Powell Memorandum, Ralph Nader, Ronald Reagan, Savings and loan crisis, shareholder value, Silicon Valley, Tax Reform Act of 1986, The Wealth of Nations by Adam Smith, three-martini lunch, 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.

Invisible Women by Caroline Criado Perez

"Hurricane Katrina" Superdome, Affordable Care Act / Obamacare, algorithmic bias, augmented reality, Bernie Sanders, Cambridge Analytica, collective bargaining, crowdsourcing, data science, Diane Coyle, Donald Trump, falling living standards, first-past-the-post, gender pay gap, gig economy, glass ceiling, Grace Hopper, Hacker Ethic, independent contractor, Indoor air pollution, informal economy, lifelogging, low skilled workers, mental accounting, meta-analysis, Nate Silver, new economy, obamacare, Oculus Rift, offshore financial centre, pattern recognition, phenotype, post-industrial society, randomized controlled trial, remote working, Sheryl Sandberg, Silicon Valley, Simon Kuznets, speech recognition, stem cell, Stephen Hawking, Steven Levy, tech bro, the built environment, urban planning, women in the workforce, work culture , zero-sum game

In fact the number of flexible workers in the US fell between 2015 and 2016 and several major US companies are rescinding their remote work policies.112 In the UK half of employees would like to work flexibly, but only 9.8% of job ads offer flexible working113 – and women in particular who request it report being penalised. Companies also still seem to conflate long hours in the office with job effectiveness, routinely and disproportionately rewarding employees who work long hours.114 This constitutes a bonus for men. Statistician Nate Silver found that in the US, the hourly wage for those working fifty hours or more – 70% of whom are men – has risen twice as fast since 1984 as hourly pay for those working a more typical thirty-five to forty-nine hours per week.115 And this invisible male bias is exacerbated in certain countries by tax systems that exempt overtime hours from tax116 – a bonus for being unencumbered117 that contrasts sharply with the tax relief on domestic services being trialled in Sweden.118 The long-hours bias is particularly acute in Japan where it is not unusual for employees to stay in the office past midnight.

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

Abraham Wald, Alan Greenspan, Bayesian statistics, bioinformatics, Bletchley Park, British Empire, classic study, Claude Shannon: information theory, Daniel Kahneman / Amos Tversky, data science, double helix, Dr. Strangelove, driverless car, Edmond Halley, Fellow of the Royal Society, full text search, government statistician, Henri Poincaré, Higgs boson, industrial research laboratory, Isaac Newton, Johannes Kepler, John Markoff, John Nash: game theory, John von Neumann, linear programming, longitudinal study, machine readable, machine translation, meta-analysis, Nate Silver, p-value, Pierre-Simon Laplace, placebo effect, prediction markets, RAND corporation, recommendation engine, Renaissance Technologies, Richard Feynman, Richard Feynman: Challenger O-ring, Robert Mercer, Ronald Reagan, seminal paper, speech recognition, statistical model, stochastic process, Suez canal 1869, Teledyne, the long tail, Thomas Bayes, Thomas Kuhn: the structure of scientific revolutions, traveling salesman, Turing machine, Turing test, uranium enrichment, We are all Keynesians now, 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.

The Wires of War: Technology and the Global Struggle for Power by Jacob Helberg

"World Economic Forum" Davos, 2021 United States Capitol attack, A Declaration of the Independence of Cyberspace, active measures, Affordable Care Act / Obamacare, air gap, Airbnb, algorithmic management, augmented reality, autonomous vehicles, Berlin Wall, Bernie Sanders, Big Tech, bike sharing, Black Lives Matter, blockchain, Boris Johnson, Brexit referendum, cable laying ship, call centre, Cambridge Analytica, Cass Sunstein, cloud computing, coronavirus, COVID-19, creative destruction, crisis actor, data is the new oil, data science, decentralized internet, deep learning, deepfake, deglobalization, deindustrialization, Deng Xiaoping, deplatforming, digital nomad, disinformation, don't be evil, Donald Trump, dual-use technology, Edward Snowden, Elon Musk, en.wikipedia.org, end-to-end encryption, fail fast, fake news, Filter Bubble, Francis Fukuyama: the end of history, geopolitical risk, glass ceiling, global pandemic, global supply chain, Google bus, Google Chrome, GPT-3, green new deal, information security, Internet of things, Jeff Bezos, Jeffrey Epstein, John Markoff, John Perry Barlow, knowledge economy, Larry Ellison, lockdown, Loma Prieta earthquake, low earth orbit, low skilled workers, Lyft, manufacturing employment, Marc Andreessen, Mark Zuckerberg, Mary Meeker, Mikhail Gorbachev, military-industrial complex, Mohammed Bouazizi, move fast and break things, Nate Silver, natural language processing, Network effects, new economy, one-China policy, open economy, OpenAI, Parler "social media", Peter Thiel, QAnon, QR code, race to the bottom, Ralph Nader, RAND corporation, reshoring, ride hailing / ride sharing, Ronald Reagan, Russian election interference, Salesforce, Sam Altman, satellite internet, self-driving car, Sheryl Sandberg, side project, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, Skype, smart grid, SoftBank, Solyndra, South China Sea, SpaceX Starlink, Steve Jobs, Steven Levy, Stuxnet, supply-chain attack, Susan Wojcicki, tech worker, techlash, technoutopianism, TikTok, Tim Cook: Apple, trade route, TSMC, Twitter Arab Spring, uber lyft, undersea cable, Unsafe at Any Speed, Valery Gerasimov, vertical integration, Wargames Reagan, Westphalian system, white picket fence, WikiLeaks, Y Combinator, zero-sum game

* * * By sheer coincidence, I became a Googler the day before Donald Trump was elected president. The night of November 8, I watched the election returns with a small group at the offices of a friend’s tech firm. The pundits had predicted a slam dunk election for Hillary. Like most people who took Nate Silver’s projections as gospel, I believed them. Peter Thiel was just about the Valley’s lone voice predicting—and championing—Trump’s success. But as state after state unexpectedly went red for Trump, I became more and more concerned. I kept telling myself that Hillary could still win. I was still clinging to that slender hope at 11:40 p.m., when CNN flashed the banner headline “Clinton Calls Trump to Concede Election.”4 Most of my friends watched in disbelief.

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

Abraham Maslow, airport security, Alvin Toffler, barriers to entry, behavioural economics, benefit corporation, Berlin Wall, Bernie Madoff, Bernie Sanders, Brian Krebs, Broken windows theory, carried interest, Cass Sunstein, Chelsea Manning, commoditize, corporate governance, crack epidemic, credit crunch, CRISPR, crowdsourcing, cuban missile crisis, Daniel Kahneman / Amos Tversky, David Graeber, desegregation, don't be evil, Double Irish / Dutch Sandwich, Douglas Hofstadter, Dunbar number, experimental economics, Fall of the Berlin Wall, financial deregulation, Future Shock, Garrett Hardin, George Akerlof, hydraulic fracturing, impulse control, income inequality, information security, invention of agriculture, invention of gunpowder, iterative process, Jean Tirole, John Bogle, John Nash: game theory, joint-stock company, Julian Assange, language acquisition, longitudinal study, mass incarceration, meta-analysis, microcredit, mirror neurons, moral hazard, Multics, mutually assured destruction, Nate Silver, Network effects, Nick Leeson, off-the-grid, offshore financial centre, Oklahoma City bombing, patent troll, phenotype, pre–internet, principal–agent problem, prisoner's dilemma, profit maximization, profit motive, race to the bottom, Ralph Waldo Emerson, RAND corporation, Recombinant DNA, 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, Timothy McVeigh, too big to fail, traffic fines, Tragedy of the Commons, transaction costs, ultimatum game, UNCLOS, union organizing, Vernor Vinge, WikiLeaks, World Values Survey, Y2K, Yochai Benkler, zero-sum game