Robert Mercer

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pages: 407 words: 104,622

The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution by Gregory Zuckerman

affirmative action, Affordable Care Act / Obamacare, Alan Greenspan, Albert Einstein, Andrew Wiles, automated trading system, backtesting, Bayesian statistics, Bear Stearns, beat the dealer, behavioural economics, Benoit Mandelbrot, Berlin Wall, Bernie Madoff, Black Monday: stock market crash in 1987, blockchain, book value, Brownian motion, butter production in bangladesh, buy and hold, buy low sell high, Cambridge Analytica, Carl Icahn, Claude Shannon: information theory, computer age, computerized trading, Credit Default Swap, Daniel Kahneman / Amos Tversky, data science, diversified portfolio, Donald Trump, Edward Thorp, Elon Musk, Emanuel Derman, endowment effect, financial engineering, Flash crash, George Gilder, Gordon Gekko, illegal immigration, index card, index fund, Isaac Newton, Jim Simons, John Meriwether, John Nash: game theory, John von Neumann, junk bonds, Loma Prieta earthquake, Long Term Capital Management, loss aversion, Louis Bachelier, mandelbrot fractal, margin call, Mark Zuckerberg, Michael Milken, Monty Hall problem, More Guns, Less Crime, Myron Scholes, Naomi Klein, natural language processing, Neil Armstrong, obamacare, off-the-grid, p-value, pattern recognition, Peter Thiel, Ponzi scheme, prediction markets, proprietary trading, quantitative hedge fund, quantitative trading / quantitative finance, random walk, Renaissance Technologies, Richard Thaler, Robert Mercer, Ronald Reagan, self-driving car, Sharpe ratio, Silicon Valley, sovereign wealth fund, speech recognition, statistical arbitrage, statistical model, Steve Bannon, Steve Jobs, stochastic process, the scientific method, Thomas Bayes, transaction costs, Turing machine, Two Sigma

He was aware of the accomplishments of the computer giant’s speech-recognition group and thought their work bore similarity to what Renaissance was doing. In early 1993, Patterson sent separate letters to Peter Brown and Robert Mercer, deputies of the group, inviting them to visit Renaissance’s offices to discuss potential positions. Brown and Mercer both reacted the exact same way—depositing Patterson’s letter in the closest trash receptacle. They’d reconsider after experiencing family upheaval, laying the groundwork for dramatic change at Jim Simons’s company, and the world as a whole. * * * = Robert Mercer’s lifelong passion had been sparked by his father. A brilliant scientist with a dry wit, Thomas Mercer was born in Victoria, British Columbia, later becoming a world expert on aerosols, the tiny particles suspended in the atmosphere that both contribute to air pollution and cool the earth by blocking the sun.

Sebastian Mallaby, More Money Than God: Hedge Funds and the Making of a New Elite (New York: Penguin Press, 2010). 3. Michael Coleman, “Influential Conservative Is Sandia, UNM Grad,” Albuquerque Journal, November 5, 2017, https://www.abqjournal.com/1088165/influential-conservative-is-sandia-unm-grad-robert-mercer-trump-fundraiser-breitbart-investor-has-nm-roots.html. 4. Robert Mercer, “A Computational Life” (speech, Association for Computational Linguistics Lifetime Achievement Award, Baltimore, Maryland, June 25, 2014), http://techtalks.tv/talks/closing-session/60532. 5. Stephen Miller, “Co-Inventor of Money-Market Account Helped Serve Small Investors’ Interest,” Wall Street Journal, August 16, 2008, https://www.wsj.com/articles/SB121884007790345601. 6.

Feng-Hsiung Hsu, Behind Deep Blue: Building the Computer That Defeated the World Chess Champion (Princeton, NJ: Princeton University Press, 2002). Chapter Ten 1. Peter Brown and Robert Mercer, “Oh, Yes, Everything’s Right on Schedule, Fred” (lecture, Twenty Years of Bitext Workshop, Empirical Methods in Natural Language Processing Conference, Seattle, Washington, October 2013), http://cs.jhu.edu/~post/bitext. Chapter Eleven 1. Hal Lux, “The Secret World of Jim Simons,” Institutional Investor, November 1, 2000, https://www.institutionalinvestor.com/article/b151340bp779jn/the-secret-world-of-jim-simons. 2. Robert Mercer interviewed by Sharon McGrayne for her book, The Theory Would Not Die: How Bayes’ Rule Cracked the Enigma Code, Hunted Down Russian Submarines, and Emerged Triumphant from Two Centuries of Controversy (New Haven, CT: Yale University Press, 2011). 3.


pages: 296 words: 78,112

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

4chan, Affordable Care Act / Obamacare, Ayatollah Khomeini, Bernie Sanders, 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

The film debuted during the Cannes Film Festival,* on the French Riviera, where Rebekah Mercer entertained guests, including Bannon, aboard the family’s 203-foot luxury super yacht, Sea Owl. The fourth Mercer-funded outfit was a business after Robert Mercer’s own heart, the U.S. offshoot of a British data analytics company, Strategic Communication Laboratories, that advised foreign governments and militaries on influencing elections and public opinion using the tools of psychological warfare. The American affiliate of SCL, of which Robert Mercer became principal owner, was christened Cambridge Analytica. (Bannon, too, took an ownership stake and a seat on the company’s board.) The purpose of acquiring a major stake in a data company was to equip the Mercer network with the kind of state-of-the-art technology that had been glaringly absent from Mitt Romney’s campaign.

He was dressed up as one of his favorite movie characters of all-time, Brigadier General Frank Savage, the tough-as-nails commander, played by Gregory Peck, who takes over a demoralized World War II bombing unit and whips them into fighting shape in the 1949 classic Twelve O’Clock High. Ordinarily, Bannon wasn’t big into cosplay. But this was a special occasion: the annual Christmas party thrown by the reclusive billionaire Robert Mercer, an eccentric computer scientist who was co-CEO of the fabled quantitative hedge fund Renaissance Technologies. As introverted and private as Bannon was voluble and outspoken, Mercer was nonetheless a man of ardent passions. He collected machine guns and owned the gas-operated AR-18 assault rifle that Arnold Schwarzenegger wielded in The Terminator.

But the evening’s buzz was all about politics. With the presidential election less than a year away, Rebekah Mercer, who was dressed as Rita Hayworth, stood to be a figure of consequence. Texas senator Ted Cruz, dressed as Winston Churchill, was especially solicitous of her. As everyone gathered on the lush grounds of Robert Mercer’s estate was keenly aware, the Mercer family had given away more than $77 million to conservative politicians and organizations since 2008. You didn’t have to be a brilliant scientist to see the joy Bob Mercer derived from his annual Christmas pageant, or to understand that anyone hoping to curry favor with him would be wise to play along.


pages: 174 words: 56,405

Machine Translation by Thierry Poibeau

Alignment Problem, AlphaGo, AltaVista, augmented reality, call centre, Claude Shannon: information theory, cloud computing, combinatorial explosion, crowdsourcing, deep learning, DeepMind, easy for humans, difficult for computers, en.wikipedia.org, geopolitical risk, Google Glasses, information retrieval, Internet of things, language acquisition, machine readable, machine translation, Machine translation of "The spirit is willing, but the flesh is weak." to Russian and back, natural language processing, Necker cube, Norbert Wiener, RAND corporation, Robert Mercer, seminal paper, Skype, speech recognition, statistical model, technological singularity, Turing test, wikimedia commons

On the other hand, with the increasing amount of translations available on the Internet, it is now possible to directly design statistical models for machine translation. This approach, known as statistical machine translation, is the most popular today. Unlike a translation memory, which can be relatively small, automatic processing presumes the availability of an enormous amount of data. Robert Mercer, one of the pioneers of statistical translation,1 proclaimed: “There is no data like more data.” In other words, for Mercer as well as followers of the statistical approach, the best strategy for developing a system consists in accumulating as much data as possible. These data must be representative and diversified, but as these are qualitative criteria that are difficult to evaluate, it is the quantitative criterion that continues to prevail.

These data must be representative and diversified, but as these are qualitative criteria that are difficult to evaluate, it is the quantitative criterion that continues to prevail. In fact, it has been proven that the systems’ performance regularly improves as more bi-texts are available to develop it. “There is no data like more data.” [Robert Mercer] Availability of Parallel Corpora There are two major sources of bi-texts: on the one hand, corpora already available for two or more languages; the bi-texts may be aligned or not. On the other hand, for pairs of languages without adequate corpora, techniques have been developed to automatically develop such corpora, generally by collecting texts available on the web.

Nano Gough and Andy Way (2004). “Robust large-scale EBMT with marker-based segmentation.” Proceedings of the Tenth International Conference on Theoretical and Methodological Issues in Machine Translation, 95–104. Baltimore, MD. Peter Brown, John Cocke, Stephen Della Pietra, Vincent Della Pietra, Frederick Jelinek, Robert Mercer, and Paul Roossin (1988). “A statistical approach to language translation.” In Proceedings of the Twelfth Conference on Computational Linguistics, Vol. 1, 71–76. Association for Computational Linguistics, Stroudsburg, PA. http://dx.doi.org/10.3115/991635.991651/. Peter F. Brown, John Cocke, Stephen A.


pages: 276 words: 81,153

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

The origins of Cambridge Analytica has all the ingredients of a modern conspiracy story. It involves Ted Cruz, Donald Trump, data security, the psychology of personality, Facebook, underpaid Mechanical Turk workers, big data, Cambridge University academics, right-wing populist Steve Bannon who sits on the board, right-wing financier Robert Mercer who is one of its biggest investors, one-time national security advisor Michael Flynn who has acted as consultant, and (in some less reliable versions of the story) Russian-sponsored trolls. I can imagine it as a film with Jesse Eisenberg playing a psychologist who gradually uncovers the true motives of the company he works for: to manipulate our every emotion for political means.

‘Advanced mouse-tracking analytic techniques for enhancing psychological science.’ Group Processes & Intergroup Relations 18, no. 3: 384–401. Chapter 5 : Cambridge Hyperbolytica 1 The most recent article had been the subject of a legal challenge by the company: www.theguardian.com/technology/2017/may/14/robert-mercer-cambridge-analytica-leave-eu-referendum-brexit-campaigns 2 This is, of course, an example of one such binary statement. They are hard to avoid. 3 https://d25d2506sfb94s.cloudfront.net/cumulus_uploads/document/0q7lmn19of/TimesResults_160613_EUReferendum_W_Headline.pdf 4 The opinion poll does not have the exact age of the people interviewed, so in fitting the model I assumed that each person had the median reported age.

Candid here, here Fair Housing Act (US) here fairness here fake news here, here, here feedback loops here MacronLeaks here post-truth world here, here, here false negatives here, here false positives here, here, here, here Fark here Feedly here Feller, Avi here Fergus, Rob here Ferrara, Emilio here filter bubbles here, here, here FiveThirtyEight here, here, here, here Flipboard here Flynn, Michael here football here, here robot players here, here Fortunato, Santo here, here Fowler, James here Franks, Nigel here Frostbite here Future of Life Institute here, here Gates, Bill here Gelade, Garry here gender bias here, here, here GloVe (global vectors for word representation) here Genter, Katie here Gentzkow, Matthew here, here Geoengineering Watch here, here Glance, Natalie here GloVe (global vectors for word representation) here Go here, here, here, here Goel, Sharad here Google here, here, here, here, here, here, here, here, here, here, here, here, here, here, here, here artificial intelligence (AI) here, here, here black hats here, here, here DeepMind here, here, here, here, here, here, here, here ‘Don’t be evil’ here Google autocomplete here, here Google News here Google Scholar here, here, here, here Google Search here Google+ here personalised adverts here, here, here, here SharedCount here Gore, Al here Grammatas, Angela here, here Guardian here, here, here, here, here, here, here, here, here, here, here, here, here, here Guardian US here, here h-index here, here Häggström, Olle here, here, here Here Be Dragons here Hassabis, Demis here, here, here Hawking, Stephen here, here, here He, Kaiming here Her here Higginson, Andrew here Hinton, Geoffrey here HotUKDeal here Huckfeldt, Bob here, here, here, here Huffington Post here, here, here Independent here Instagram here Internet here, here, here, here Internet service providers (ISPs) here Intrade here Ishiguro, Kazuo Never Let Me Go here iTunes here, here James Webb Sapce Telescope here Jie, Ke here job matching here Johansson, Joakim here, here Journal of Spatial Science here Kaminski, Juliane here Kasparov, Garry here, here Keith, David here Kerry, John here Keuschnigg, Marc here Kleinberg, Jon here Kluemper, Donald here Kogan, Alex here, here, here Kosinski, Michal here, here, here, here, here, here, here Kramer, Adam here, here Krizhevsky, Alex here Kulsrestha, Juhi here Kurzweil, Ray here Labour Party here, here Momentum here Lake, Brenden here language here Laue, Tim here Le Comber, Steve here Le Cun, Yan here Le Pen, Marine here Le, Quoc here Lerman, Kristina here, here, here Levin, Simon here Libratus here LinkedIn here, here, here, here literature here logic gates here Luntz, Frank here Machine Bias here Macron, Emmanuel here Major League Soccer (MLS) here, here Mandela effect here, here Mandela, Nelson here Martin, Erik here matchmaking here mathematics here, here assessing bias here mathematical models here, here, here power laws here Matrix, The here May, Lord Robert here McDonald, Glenn here, here Mechanical Turk here, here, here, here, here Medium here Mercer, Robert here Microsoft here, here, here, here, here, here Mikolov, Tomas here, here Minecraft here Mosseri, Adam here, here, here Mrsic-Flogel, Thomas here Ms Pac-Man here, here, here Munafò, Marcus here Musk, Elon here, here, here myPersonality project here National Health Service (NHS) here, here National Women’s Soccer League (NWSL) here, here Nature here, here, here Natusch, Waffles Pi here Netflix here neural networks here, here convolutional neural networks here limitations here recurrent neural networks here New York Times here, here, here, here, here, here, here, here The Upshot here, here news aggregators here Nix, Alexander here, here, here, here Noiszy here Northpointe here, here, here, here O’Neil, Cathy here Weapons of Math Destruction here Obama, Barack here, here Observer here online data collection here, here gender bias here preventing here principal component analysis (PCA) here online help services here OpenWorm here Overwatch here, here Pasquale, Frank The Black Box Society here, here Paul, Jake here, here, here, here Pennington, Jeffrey here personality analysis here Big Five here, here, here, here PewDiePie here Pierson, Emma here Pittsburgh Post-Gazette here political blogs here political discussions here, here, here PolitiFact here polls here, here, here, here Popular Mechanics here post-truth world here, here, here power laws here Pratt, Stephen here, here PredictIt here, here, here, here, here, here Prince here principal component analysis (PCA) here categorising personalities here COMPAS algorithm here probability distributions here ProPublica here, here, here, here, here, here Pundit here Q*bert 214, here Qualtrics here racial bias here, here, here, here, here GloVe (global vectors for word representation) here randomness here Reddit here, here, here, here, here regression models here, here Republican Party here, here, here, here, here RiceGum here, here Richardson, Kathleen here Road Runner here Robotank here, here robots here, here, here, here, here, here Russian interference here, here, here Salganik, Matthew here, here Sanders, Bernie here Scholz, Monika here Science here SCL here, here search histories here Silver, David here Silver, Nate here, here, here The Signal and the Noise here Silverman, Craig here Simonyan, Karen here singularity hypothesis here Skeem, Jen here Sky Sports here slime moulds (Physarum polycephulum) here, here, here Snapchat here Snopes here social feedback here Space Invaders here, here, here, here Spotify here, here, here, here, here, here, here Stack Exchange here StarCraft here statistics here, here, here, here, here regression models here, here Stillwell, David here, here Sullivan, Andrew here, here Sumpter, David Soccermatics here, here, here, here, here, here, here Sun, The here superforecasters here, here superintelligence here, here Szorkovszky, Alex here, here, here, here, here, here Taleb, Nassim here, here, here Tegmark, Max here, here, here, here Telegraph here, here, here, here Tesla here, here, here, here Tetlock, Philip here, here Texas, Virgil here, here, here The Gateway here TIDAL here Times, The here, here Tinder here, here, here Tolstoy, Leo here, here, here Anna Karenina here trolls here true positives here, here Trump, Donald here, here, here, here, here, here election campaign here, here, here, here, here, here election outcome here, here, here Twitter here, here TUI here, here Turing, Alan here Twitter here, here, here, here, here, here, here, here, here, here, here, here, here, here MacronLeaks here Tyson, Gareth here van Seijen, Harm here, here Vinyals, Oriol here vloggers here voter analysis here, here, here Wall Street Journal here Ward, Ashley here Washington Post here, here, here, here Watts, Duncan here, here Which?


pages: 317 words: 84,400

Automate This: How Algorithms Came to Rule Our World by Christopher Steiner

23andMe, Ada Lovelace, airport security, Al Roth, algorithmic trading, Apollo 13, backtesting, Bear Stearns, big-box store, Black Monday: stock market crash in 1987, Black-Scholes formula, call centre, Charles Babbage, cloud computing, collateralized debt obligation, commoditize, Credit Default Swap, credit default swaps / collateralized debt obligations, delta neutral, Donald Trump, Douglas Hofstadter, dumpster diving, financial engineering, Flash crash, G4S, Gödel, Escher, Bach, Hacker News, High speed trading, Howard Rheingold, index fund, Isaac Newton, Jim Simons, John Markoff, John Maynard Keynes: technological unemployment, knowledge economy, late fees, machine translation, Marc Andreessen, Mark Zuckerberg, market bubble, Max Levchin, medical residency, money market fund, Myron Scholes, Narrative Science, PageRank, pattern recognition, Paul Graham, Pierre-Simon Laplace, prediction markets, proprietary trading, quantitative hedge fund, Renaissance Technologies, ride hailing / ride sharing, risk tolerance, Robert Mercer, Sergey Aleynikov, side project, Silicon Valley, Skype, speech recognition, Spread Networks laid a new fibre optics cable between New York and Chicago, transaction costs, upwardly mobile, Watson beat the top human players on Jeopardy!, Y Combinator

The software that did exist for the purpose was buggy and often wildly inaccurate. But in the early 1990s, two scientists at IBM’s research center dove into computerized speech recognition and translation, a field that had long failed to produce anything robust enough to be used in everyday situations. Peter Brown and Robert Mercer started by working on programs that translated one language to another, starting with French to English. Most hackers working on the problem up to that point knew both languages and wrote programs that translated words directly: the English ham is, in French, jambon; cheese is, of course, fromage; and so on.

When his Hollywood luck ran out, Capers spent the requisite years in school to become a psychiatrist. He met Kahler in San Diego, where he proved a quick learner of the theory Kahler, McGuire, and NASA had developed. 5. Sebastian Mallaby, More Money Than God: Hedge Funds and the Making of a New Elite (New York: Penguin Press, 2010). 6. Peter Brown, Robert Mercer, Stephen Della Pietra, and Vincent J. Della Pietra, “The Mathematics of Statistical Machine Translation: Parameter Estimation,” Journal of Computational Linguistics 19, no. 2 (1993): 263–311. 7. Ingfei Chen, “Scientist at Work: Nick Patterson,” New York Times, December 12, 2006. CHAPTER 8: WALL STREET VERSUS SILICON VALLEY 1.

., 217–18 McCartney, Paul, 104, 105, 107 “In My Life” claimed by, 110–11 as math savant, 103 McCready, Mike, 78–83, 85–89 McGuire, Terry, 145, 168–72, 174–76 machine-learning algorithms, 79, 100 Magnetar Capital, 3–4, 10 Mahler, Gustav, 98 Major Market Index, 40, 41 Making of a Fly, The (Lawrence), prices of, 1–2 Malyshev, Mikhail, 190 management consultants, 189 margin, trading with, 51 market cap, price swings and, 49 market makers: bids and offers by, 35–36 Peterffy as, 31, 35–36, 38, 51 market risk, 66 Maroon 5, 85 Marseille, 147, 149 Marshall, Andrew, 140 Martin, George, 108–10 Martin, Max (Martin Sandberg), 88–89 math: behind algorithms, 6, 53 education in, 218–20 mathematicians: algorithms and, 6, 71 online, 53 on Wall Street, 13, 23, 24, 27, 71, 179, 185, 201–3 Mattingly, Ken, 167 MBAs: eLoyalty’s experience with, 187 Peterffy’s refusal to hire, 47 MDCT scans, 154 measurement errors, distribution of, 63 medical algorithms, 54, 146 in diagnosis and testing, 151–56, 216 in organ sharing, 147–51 patient data and home monitoring in, 158–59 physicians’ practice and, 156–62 medical residencies, game theory and matching for, 147 medicine, evidence-based, 156 Mehta, Puneet, 200, 201 melodies, 82, 87, 93 Mercer, Robert, 178–80 Merrill Lynch, 191, 192, 200 Messiah, 68 metal: trading of, 27 volatility of, 22 MGM, 135 Miami University, 91 Michigan, 201 Michigan, University of, 136 Microsoft, 67, 124, 209 microwaves, 124 Midas (algorithm), 134 Miller, Andre, 143 mind-reading bots, 178, 181–83 Minneapolis, Minn., 192–93 minor-league statistics, baseball, 141 MIT, 24, 73, 128, 160, 179, 188, 217 Mocatta & Goldsmid, 20 Mocatta Group, 20, 21–25, 31 model building, predictive, 63 modifiers, 71 Boolean, 72–73 Mojo magazine, 110 Moneyball (Lewis), 141 money markets, 214 money streams, present value of future, 57 Montalenti, Andrew, 200–201 Morgan Stanley, 116, 128, 186, 191, 200–201, 204 mortgage-backed securities, 203 mortgages, 57 defaults on, 65 quantitative, 202 subprime, 65, 202, 216 Mosaic, 116 movies, algorithms and, 75–76 Mozart, Wolfgang Amadeus, 77, 89, 90, 91, 96 MP3 sharing, 83 M Resort Spa, sports betting at, 133–35 Mubarak, Hosni, 140 Muller, Peter, 128 music, 214 algorithms in creation of, 76–77, 89–103 decoding Beatles’, 70, 103–11 disruptors in, 102–3 homogenization or variety in, 88–89 outliers in, 102 predictive algorithms for success of, 77–89 Music X-Ray, 86–87 Musikalisches Würfelspiel, 91 mutual funds, 50 MyCityWay, 200 Najarian, John A., 119 Naples, 121 Napoleon I, emperor of France, 121 Napster, 81 Narrative Science, 218 NASA: Houston mission control of, 166, 175 predictive science at, 61, 164, 165–72, 174–77, 180, 194 Nasdaq, 177 algorithm dominance of, 49 Peterffy and, 11–17, 32, 42, 47–48, 185 terminals of, 14–17, 42 trading method at, 14 National Heart, Lung, and Blood Institute, 159 Nationsbank, Chicago Research and Trading Group bought by, 46 NBA, 142–43 Neanderthals, human crossbreeding with, 161 Nebraska, 79–80, 85 Netflix, 112, 207 Netherlands, 121 Netscape, 116, 188 Nevermind, 102 New England Patriots, 134 New Jersey, 115, 116 Newsweek, 126 Newton, Isaac, 57, 58, 59, 64, 65 New York, N.Y., 122, 130, 192, 201–2, 206 communication between markets in Chicago and, 42, 113–18, 123–24 financial markets in, 20, 198 high school matching algorithm in, 147–48 McCready’s move to, 85 Mocatta’s headquarters in, 26 Peterffy’s arrival in, 19 tech startups in, 210 New York Commodities Exchange (NYCE), 26 New Yorker, 156 New York Giants, 134 New York Knicks, 143 New York magazine, 34 New York State, health department of, 160 New York Stock Exchange (NYSE), 3, 38–40, 44–45, 49, 83, 123, 184–85 New York Times, 123, 158 New York University, 37, 132, 136, 201, 202 New Zealand, 77, 100, 191 Nietzsche, Friedrich, 69 Nirvana, 102 Nixon, Richard M., 140, 165 Nobel Prize, 23, 106 North Carolina, 48, 204 Northwestern University, 145, 186 Kellogg School of Management at, 10 Novak, Ben, 77–79, 83, 85, 86 NSA, 137 NuclearPhynance, 124 nuclear power, 139 nuclear weapons, in Iran, 137, 138–39 number theory, 65 numerals: Arabic-Indian, 56 Roman, 56 NYSE composite index, 40, 41 Oakland Athletics, 141 Obama, Barack, 46, 218–19 Occupy Wall Street, 210 O’Connor & Associates, 40, 46 OEX, see S&P 100 index Ohio, 91 oil prices, 54 OkCupid, 144–45 Olivetti home computers, 27 opera, 92, 93, 95 Operation Match, 144 opinions-driven people, 173, 174, 175 OptionMonster, 119 option prices, probability and statistics in, 27 options: Black-Scholes formula and, 23 call, 21–22 commodities, 22 definition of, 21 pricing of, 22 put, 22 options contracts, 30 options trading, 36 algorithms in, 22–23, 24, 114–15 Oregon, University of, 96–97 organ donor networks: algorithms in, 149–51, 152, 214 game theory in, 147–49 oscilloscopes, 32 Outkast, 102 outliers, 63 musical, 102 outputs, algorithmic, 54 Pacific Exchange, 40 Page, Larry, 213 PageRank, 213–14 pairs matching, 148–51 pairs trading, 31 Pakistan, 191 Pandora, 6–7, 83 Papanikolaou, Georgios, 153 Pap tests, 152, 153–54 Parham, Peter, 161 Paris, 56, 59, 121 Paris Stock Exchange, 122 Parse.ly, 201 partial differential equations, 23 Pascal, Blaise, 59, 66–67 pathologists, 153 patient data, real-time, 158–59 patterns, in music, 89, 93, 96 Patterson, Nick, 160–61 PayPal, 188 PCs, Quotron data for, 33, 37, 39 pecking orders, social, 212–14 Pennsylvania, 115, 116 Pennsylvania, University of, 49 pension funds, 202 Pentagon, 168 Perfectmatch.com, 144 Perry, Katy, 89 Persia, 54 Peru, 91 Peterffy, Thomas: ambitions of, 27 on AMEX, 28–38 automated trading by, 41–42, 47–48, 113, 116 background and early career of, 18–20 Correlator algorithm of, 42–45 early handheld computers developed by, 36–39, 41, 44–45 earnings of, 17, 37, 46, 48, 51 fear that algorithms have gone too far by, 51 hackers hired by, 24–27 independence retained by, 46–47 on index funds, 41–46 at Interactive Brokers, 47–48 as market maker, 31, 35–36, 38, 51 at Mocatta, 20–28, 31 Nasdaq and, 11–18, 32, 42, 47–48, 185 new technology innovated by, 15–16 options trading algorithm of, 22–23, 24 as outsider, 31–32 profit guidelines of, 29 as programmer, 12, 15–16, 17, 20–21, 26–27, 38, 48, 62 Quotron hack of, 32–35 stock options algorithm as goal of, 27 Timber Hill trading operation of, see Timber Hill traders eliminated by, 12–18 trading floor methods of, 28–34 trading instincts of, 18, 26 World Trade Center offices of, 11, 39, 42, 43, 44 Petty, Tom, 84 pharmaceutical companies, 146, 155, 186 pharmacists, automation and, 154–56 Philips, 159 philosophy, Leibniz on, 57 phone lines: cross-country, 41 dedicated, 39, 42 phones, cell, 124–25 phosphate levels, 162 Physicians’ Desk Reference (PDR), 146 physicists, 62, 157 algorithms and, 6 on Wall Street, 14, 37, 119, 185, 190, 207 pianos, 108–9 Pincus, Mark, 206 Pisa, 56 pitch, 82, 93, 106 Pittsburgh International Airport, security algorithm at, 136 Pittsburgh Pirates, 141 Pius II, Pope, 69 Plimpton, George, 141–42 pneumonia, 158 poetry, composed by algorithm, 100–101 poker, 127–28 algorithms for, 129–35, 147, 150 Poland, 69, 91 Polyphonic HMI, 77–79, 82–83, 85 predictive algorithms, 54, 61, 62–65 prescriptions, mistakes with, 151, 155–56 present value, of future money streams, 57 pressure, thriving under, 169–70 prime numbers, general distribution pattern of, 65 probability theory, 66–68 in option prices, 27 problem solving, cooperative, 145 Procter & Gamble, 3 programmers: Cope as, 92–93 at eLoyalty, 182–83 Peterffy as, 12, 15–16, 17, 20–21, 26–27, 38, 48, 62 on Wall Street, 13, 14, 24, 46, 47, 53, 188, 191, 203, 207 programming, 188 education for, 218–20 learning, 9–10 simple algorithms in, 54 Progress Energy, 48 Project TACT (Technical Automated Compatibility Testing), 144 proprietary code, 190 proprietary trading, algorithmic, 184 Prussia, 69, 121 PSE, 40 pseudocholinesterase deficiency, 160 psychiatry, 163, 171 psychology, 178 Pu, Yihao, 190 Pulitzer Prize, 97 Purdue University, 170, 172 put options, 22, 43–45 Pythagorean algorithm, 64 quadratic equations, 63, 65 quants (quantitative analysts), 6, 46, 124, 133, 198, 200, 202–3, 204, 205 Leibniz as, 60 Wall Street’s monopoly on, 183, 190, 191, 192 Queen’s College, 72 quizzes, and OkCupid’s algorithms, 145 Quotron machine, 32–35, 37 Rachmaninoff, Sergei, 91, 96 Radiohead, 86 radiologists, 154 radio transmitters, in trading, 39, 41 railroad rights-of-way, 115–17 reactions-based people, 173–74, 195 ReadyForZero, 207 real estate, 192 on Redfin, 207 recruitment, of math and engineering students, 24 Redfin, 192, 206–7, 210 reflections-driven people, 173, 174, 182 refraction, indexes of, 15 regression analysis, 62 Relativity Technologies, 189 Renaissance Technologies, 160, 179–80, 207–8 Medallion Fund of, 207–8 retirement, 50, 214 Reuter, Paul Julius, 122 Rhode Island hold ‘em poker, 131 rhythms, 82, 86, 87, 89 Richmond, Va., 95 Richmond Times-Dispatch, 95 rickets, 162 ride sharing, algorithm for, 130 riffs, 86 Riker, William H., 136 Ritchie, Joe, 40, 46 Rochester, N.Y., 154 Rolling Stones, 86 Rondo, Rajon, 143 Ross, Robert, 143–44 Roth, Al, 147–49 Rothschild, Nathan, 121–22 Royal Society, London, 59 RSB40, 143 runners, 39, 122 Russia, 69, 193 intelligence of, 136 Russian debt default of 1998, 64 Rutgers University, 144 Ryan, Lee, 79 Saint Petersburg Academy of Sciences, 69 Sam Goody, 83 Sandberg, Martin (Max Martin), 88–89 Sandholm, Tuomas: organ donor matching algorithm of, 147–51 poker algorithm of, 128–33, 147, 150 S&P 100 index, 40–41 S&P 500 index, 40–41, 51, 114–15, 218 Santa Cruz, Calif., 90, 95, 99 satellites, 60 Savage Beast, 83 Saverin, Eduardo, 199 Scholes, Myron, 23, 62, 105–6 schools, matching algorithm for, 147–48 Schubert, Franz, 98 Schwartz, Pepper, 144 science, education in, 139–40, 218–20 scientists, on Wall Street, 46, 186 Scott, Riley, 9 scripts, algorithms for writing, 76 Seattle, Wash., 192, 207 securities, 113, 114–15 mortgage-backed, 203 options on, 21 Securities and Exchange Commission (SEC), 185 semiconductors, 60, 186 sentence structure, 62 Sequoia Capital, 158 Seven Bridges of Königsberg, 69, 111 Shannon, Claude, 73–74 Shuruppak, 55 Silicon Valley, 53, 81, 90, 116, 188, 189, 215 hackers in, 8 resurgence of, 198–211, 216 Y Combinator program in, 9, 207 silver, 27 Simons, James, 179–80, 208, 219 Simpson, O.


pages: 382 words: 105,819

Zucked: Waking Up to the Facebook Catastrophe by Roger McNamee

"Susan Fowler" uber, "World Economic Forum" Davos, 4chan, Albert Einstein, algorithmic trading, AltaVista, Amazon Web Services, Andy Rubin, barriers to entry, Bernie Sanders, Big Tech, Bill Atkinson, Black Lives Matter, Boycotts of Israel, Brexit referendum, Cambridge Analytica, carbon credits, Cass Sunstein, cloud computing, computer age, cross-subsidies, dark pattern, data is the new oil, data science, disinformation, Donald Trump, Douglas Engelbart, Douglas Engelbart, driverless car, Electric Kool-Aid Acid Test, Elon Musk, fake news, false flag, Filter Bubble, game design, growth hacking, Ian Bogost, income inequality, information security, Internet of things, It's morning again in America, Jaron Lanier, Jeff Bezos, John Markoff, laissez-faire capitalism, Lean Startup, light touch regulation, Lyft, machine readable, Marc Andreessen, Marc Benioff, Mark Zuckerberg, market bubble, Max Levchin, Menlo Park, messenger bag, Metcalfe’s law, minimum viable product, Mother of all demos, move fast and break things, Network effects, One Laptop per Child (OLPC), PalmPilot, paypal mafia, Peter Thiel, pets.com, post-work, profit maximization, profit motive, race to the bottom, recommendation engine, Robert Mercer, Ronald Reagan, Russian election interference, Sand Hill Road, self-driving car, Sheryl Sandberg, Silicon Valley, Silicon Valley startup, Skype, Snapchat, social graph, software is eating the world, Stephen Hawking, Steve Bannon, Steve Jobs, Steven Levy, Stewart Brand, subscription business, TED Talk, The Chicago School, The future is already here, Tim Cook: Apple, two-sided market, Uber and Lyft, Uber for X, uber lyft, Upton Sinclair, vertical integration, WikiLeaks, Yom Kippur War

The Guardian story opened with a bang: The data analytics firm that worked with Donald Trump’s election team and the winning Brexit campaign harvested millions of Facebook profiles of US voters, in one of the tech giant’s biggest ever data breaches, and used them to build a powerful software program to predict and influence choices at the ballot box. A whistleblower has revealed to the Observer how Cambridge Analytica—a company owned by the hedge fund billionaire Robert Mercer, and headed at the time by Trump’s key adviser Steve Bannon—used personal information taken without authorisation in early 2014 to build a system that could profile individual US voters, in order to target them with personalised political advertisements. Christopher Wylie, who worked with a Cambridge University academic to obtain the data, told the Observer: “We exploited Facebook to harvest millions of people’s profiles.

In the world of market research, there is considerable doubt about how well psychographics work in their current form, but that issue did not prevent Cambridge Analytica from finding clients, mostly on the far right. To serve the US market, SCL needed to obey federal election laws. It created a US affiliate staffed by US citizens and legal residents. Reports indicated that Cambridge Analytica took a casual approach to regulations. The team of Robert Mercer and Steve Bannon financed and organized Cambridge Analytica, with Alexander Nix as CEO. The plan was to get into the market within a few months, test capabilities during the 2014 US midterm elections, and, if successful, transform American politics in 2016. To be confident that their models would work, Nix and his team needed a ton of data.

Kaiser transferred into Cambridge Analytica and went to work bringing in clients. Her early clients were in Africa, but in 2015 she and Nix shifted their focus to the United States in anticipation of the presidential election cycle. Kaiser asserted that Nix was not a political ideologue—unlike his patrons Robert Mercer and Steve Bannon—and hoped to create a “famous advertising company in the US market.” As quoted in The Guardian: “Corporations like Google, Facebook, Amazon, all of these large companies, are making tens or hundreds of billions of dollars off of monetising people’s data,” Kaiser says. “I’ve been telling companies and governments for years that data is probably your most valuable asset.


pages: 399 words: 114,787

Dark Towers: Deutsche Bank, Donald Trump, and an Epic Trail of Destruction by David Enrich

"World Economic Forum" Davos, Affordable Care Act / Obamacare, Alan Greenspan, anti-globalists, Asian financial crisis, banking crisis, Bear Stearns, Berlin Wall, buy low sell high, collateralized debt obligation, commoditize, corporate governance, Credit Default Swap, credit default swaps / collateralized debt obligations, Donald Trump, East Village, estate planning, Fall of the Berlin Wall, financial innovation, forensic accounting, high net worth, housing crisis, interest rate derivative, interest rate swap, Jeffrey Epstein, junk bonds, London Interbank Offered Rate, low interest rates, Lyft, Mikhail Gorbachev, NetJets, obamacare, offshore financial centre, post-materialism, proprietary trading, Quicken Loans, Ralph Waldo Emerson, Renaissance Technologies, risk tolerance, Robert Mercer, rolodex, SoftBank, sovereign wealth fund, Steve Bannon, too big to fail, transcontinental railway, Vision Fund, yield curve

Since the late 1990s, Deutsche had been peddling products to hedge funds, including the enormous Renaissance Technologies, that helped them avoid taxes. Founded by a former government code-breaker, Renaissance specialized in using computer programs to scout out tiny market inefficiencies that could be exploited. The firm recruited engineers and mathematicians, including an IBM programmer named Robert Mercer, a right-wing zealot who once noted that he enjoyed spending time with cats more than with people. Mercer eventually rose to the top of Renaissance, helping it become one of the world’s most successful hedge funds. Renaissance was always looking for a new, sharper edge, and that’s where Deutsche came in.

He peppered the lawyer with questions about what he needed to do next. The way Broeksmit talked, he seemed to be bracing for a world of shit to land on him at any moment. The Senate’s report was unveiled with fanfare in July 2014, paired with congressional hearings—just as the co-head of Renaissance, Robert Mercer, was beginning to bankroll a series of right-wing initiatives, such as Breitbart News, aimed at upending the Western political order. Senator Carl Levin, the chairman of the investigations committee, convened the first public hearing at 9:30 one July morning in the Hart Senate Office Building.

“Any Russia stuff at all,” Simpson requested. He added that he was eager for emails or documents related to Renaissance Technologies—the huge hedge fund that Deutsche had worked with to help save it billions in taxes. Simpson was especially curious about any materials on Renaissance’s enigmatic leader, Robert Mercer, who along with his daughter Rebekah had become a leading financier of Trump, Steve Bannon, and Breitbart News. “Be safe and I will see you tomorrow,” Simpson signed off. The weather in Saint Thomas was balmy, and Val and Glenn alternated between sifting through Bill’s files in a hotel suite and sitting at a picnic table on the beach, drinking beers and smoking cigarettes.


pages: 301 words: 85,263

New Dark Age: Technology and the End of the Future by James Bridle

AI winter, Airbnb, Alfred Russel Wallace, AlphaGo, Anthropocene, Automated Insights, autonomous vehicles, back-to-the-land, Benoit Mandelbrot, Bernie Sanders, bitcoin, Boeing 747, British Empire, Brownian motion, Buckminster Fuller, Cambridge Analytica, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, coastline paradox / Richardson effect, cognitive bias, cognitive dissonance, combinatorial explosion, computer vision, congestion charging, cryptocurrency, data is the new oil, disinformation, Donald Trump, Douglas Engelbart, Douglas Engelbart, Douglas Hofstadter, Dr. Strangelove, drone strike, Edward Snowden, Eyjafjallajökull, Fairchild Semiconductor, fake news, fear of failure, Flash crash, fulfillment center, Google Earth, Greyball, Haber-Bosch Process, Higgs boson, hive mind, income inequality, informal economy, Internet of things, Isaac Newton, ITER tokamak, James Bridle, John von Neumann, Julian Assange, Kickstarter, Kim Stanley Robinson, Large Hadron Collider, late capitalism, Laura Poitras, Leo Hollis, lone genius, machine translation, mandelbrot fractal, meta-analysis, Minecraft, mutually assured destruction, natural language processing, Network effects, oil shock, p-value, pattern recognition, peak oil, recommendation engine, road to serfdom, Robert Mercer, Ronald Reagan, security theater, self-driving car, Seymour Hersh, Silicon Valley, Silicon Valley ideology, Skype, social graph, sorting algorithm, South China Sea, speech recognition, Spread Networks laid a new fibre optics cable between New York and Chicago, stem cell, Stuxnet, technoutopianism, the built environment, the scientific method, Uber for X, undersea cable, University of East Anglia, uranium enrichment, Vannevar Bush, warehouse robotics, WikiLeaks

In the run-up to the EU referendum in the United Kingdom, a fifth of the electorate believed that the poll would be rigged in collusion with the security services.24 Leave campaigners advised voters to take pens with them to vote, in order to ensure pencil votes weren’t erased.25 In the aftermath, attention focused on the work of Cambridge Analytica – a company owned by Robert Mercer, former AI engineer, hedge fund billionaire and Donald Trump’s most powerful supporter. Cambridge Analytica’s employees have described what they do as ‘psychological warfare’ – leveraging vast amounts of data in order to target and persuade voters. And of course it turned out that the election really was rigged by the security services, in the way that rigging actually happens: the board and staff of Cambridge Analytica, which ‘donated’ its services to the Leave campaign, includes former British military personnel – notably the former director of psychological operations for British forces in Afghanistan.26 In both the EU referendum and the US election, military contractors used military intelligence technologies to influence democratic elections in their own countries.

., 11, 249 ‘low-hanging fruit,’ 93–4 M Macedonia, 233–4 machine learning algorithms, 222 machine thought, 146 machine translation, 147 magnetism, 77 Malaysian Airlines, 66 manganese noodles, 163–4 Manhattan Project, 24–30, 248 Mara, Jane Muthoni, 170 Mark I Perceptron, 136–8, 137 Maslow’s hierarchy of needs, 128–9 Matthews, James Tilly, 208–10, 209 Mauro, Ian, 199 McCarthy, Joe, 205 McGovern, Thomas, 57–8 McKay Brothers, 107, 110 memex, 24 Mercer, Robert, 236 Merkel, Angela, 174 metalanguage, 3, 5 middens, 56 migrated archive, 170–1 Minds, 150 miniaturisation principle, 81 Mirai, 129 mobile phones, 126 The Modern Prometheus (Shelley), 201 monoculture, 55–6 Moore, Gordon, 80, 80, 83 Moore’s law, 80–3, 92–4 Mordvintsev, Alexander, 154 Morgellons, 211, 214 Morrison, Grant The Invisibles, 196–7 Morton, Timothy, 73, 194 Mount Tambora, eruption of, 201 Moynihan, Daniel Patrick, 169 Munch, Edvard The Scream, 202 Mutua, Ndiku, 170 N NarusInsight, 177 NASA Ames Advanced Concepts Flight Simulator, 42 Natanz Nuclear Facility, 129 National Centre for Atmospheric Science, 68–9 National Geospatial-Intelligence Agency, 243 National Health Service (NHS), 110 National Mining Association, 64 National Reconnaissance Office, 168, 243 National Security Agency (NSA), 167, 174, 177–8, 183, 242–3, 249–50 National Security Strategy, 59 natural gas, 48 neoliberalism, 138–9 network, 5, 9 networks, 249 Newton, Isaac, 78 NewYorkTimesPolitics.com, 221 New York World’s Fair, 30–1 NHS (National Health Service), 110 9/11 terrorist attacks, 203–4, 206 ‘Nine Eyes,’ 174 1984 (Orwell), 242 NORAD (North American Air Defense Command), 33 North American Air Defense Command (NORAD), 33 ‘The Nor’ project, 104 Not Aviation, 190–1 NSA (National Security Agency), 167, 174, 177–8, 183, 242–3, 249–50 nuclear fusion, 97–8, 100 nuclear warfare, 28 Numerical Prediction (Richardson), 45 Nyingi, Wambugu Wa, 170 Nzili, Paulo Muoka, 170 O Obama, Barack, 180, 206, 231 Official Secrets Act, 189 Omori, Fusakichi, 145 Omori’s Law, 145 Operation Castle, 97 Operation Legacy, 171–2 Optic Nerve programme, 174 Optometrist Algorithm, 99–101, 160 O’Reilly, James, 185–6 Orwell, George 1984, 242 ‘Outline of Weather Proposal’ (Zworykin), 25–6 P Paglen, Trevor, 144 ‘paranoid style,’ 205–6 Patriot Act, 178 Penrose, Roger, 20 Perceptron, 136–8, 137 permafrost, 47–9, 56–7 p-hacking, 89–91 Phillippi, Harriet Ann, 165 photophone, 19–20 Pichai, Sundar, 139 Piketty, Thomas Capital in the Twenty-First Century, 112 Pincher, Chapman, 175–6 Pitt, William, 208 Plague-Cloud, 195, 202 Poitras, Laura, 175 Polaroid, 143 ‘predictive policing’ systems, 144–6 PredPol software, 144, 146 Priestley, Joseph, 78, 208, 209 prion diseases, 50, 50–1 PRISM operation, 173 product spam, 125–6 Project Echelon, 190 Prometheus, 132–4, 198 psychogeography, 103 public key cryptography, 167–8 pure language, 156 Putin, Vladimir, 235 Pynchon, Thomas Gravity’s Rainbow, 128 Q Qajaa, 56, 57 quality control failure of, 92–3 in science, 91 Quidsi, 113–4 R racial profiling, 143–4 racism, 143–4 ‘radiation cats,’ 251 raw computing, 82–3 Reagan, Ronald, 36–7 Reed, Harry, 29 refractive index of the atmosphere, 62 Regin malware, 175 replicability, 88–9 Reproducibility Project, 89 resistance, modes of, 120 Reuter, Paul, 107 Review Group on Intelligence and Communications Technologies, 181 Richardson, Lewis Fry, 20–1, 29, 68 Numerical Prediction, 45 Weather Prediction by Numerical Process, 21–3 Richardson number, 68 The Road to Serfdom (Hayek), 139 Robinson, Kim Stanley Aurora, 128 robots, workers vs., 116 ‘Rogeting,’ 88 Romney, Mitt, 206–7 Rosenblatt, Frank, 137 Roy, Arundhati, 250 Royal Aircraft Establishment, 188–9 Ruskin, John, 17–20, 195, 202 Rwanda, 243, 244, 245 S Sabetta, 48 SABRE (Semi-Automated Business Research Environment), 35, 38 SAGE (Semi-Automatic Ground Environment), 33, 34, 35 Samsung, 127 Scheele, Carl Wilhelm, 78 Schmidt, Eric, 241–5 The Scream (Munch), 202 Sedol, Lee, 149, 157–8 seed banks, 52–6 Seed Vault, 55 seismic sensors, 48 self-excitation, 145 ‘semantic analyser,’ 177 Semi-Automated Business Research Environment (SABRE), 35, 38 Semi-Automatic Ground Environment (SAGE), 33, 34, 35 semiconductors, 82 The Sensory Order: An Inquiry into the Foundations of Theoretical Psychology (Hayek), 138–9 Shelley, Mary Frankenstein, 201 The Modern Prometheus, 201 SIGINT Seniors Europe, 174 simulation, conflating approximation with, 34–5 Singapore Exchange, 122–3 smart products, 127–8, 131 Smith, Robert Elliott, 152 smoking gun, 183–4, 186 Snowden, Edward, 173–5, 178 software about, 82–3 AlphaGo, 149, 156–8 Assistant, 152 AutoAwesome, 152 DeepFace, 140 Greyball programme, 119, 120 Hippo programme, 32 How-Old.net facial recognition programme, 141 Optic Nerve programme, 174 PredPol, 144, 146 Translate, 146 Solnit, Rebecca, 11–2 solutionism, 4 space telescopes, 168–9 speed of light, 107 Spread Networks, 107 SSEC (IBM Selective Sequence Electronic Calculator), 30, 30–2, 31, 146 Stapel, Diederik, 87–8 Stapledon, Olaf, 20 steam engines, 77 Stellar Wind, 176 Stewart, Elizabeth ‘Betsy,’ 30–1, 31 Steyerl, Hito, 126 stock exchanges, 108 ‘The Storm-Cloud of the Nineteenth Century’ lecture series, 17–9 Stratus homogenitus, 195–6 studios, 130 Stuxnet, 129–30 surveillance about, 243–4 complicity in, 185 computational excesses of, 180–1 devices for, 104 Svalbard archipelago, 51–2, 54 Svalbard Global Seed Vault, 52–3 Svalbard Treaty (1920), 52 Swiss National Bank, 123 Syed, Omar, 158–9 systemic literacy, 5–6 T Taimyr Peninsula, 47–8 Targeted Individuals, 210–1 The Task of the Translator (Benjamin), 147, 155–6 TCP (Transmission Control Protocol), 79 technology acceleration of, 2 complex, 2–3 opacity of, 119 Teletubbies, 217 television, children’s, 216–7 Tesco Clubcard, 245 thalidomide, 95 Thatcher, Margaret, 177 theory of evolution, 78 thermal power plants, 196 Three Guineas (Woolf), 12 Three Laws of Robotics (Asimov), 157 Tillmans, Wolfgang, 71 tools, 13–4 To Photograph the Details of a Dark Horse in Low Light exhibition, 143 totalitarianism, collectivism vs., 139 Toy Freaks, 225–6 transistors, 79, 80 Translate software, 146 translation algorithms, 84 Transmission Control Protocol (TCP), 79 Tri Alpha Energy, 98–101 Trinity test, 25 trolling, 231 Trump, Donald, 169–70, 194–5, 206, 207, 236 trust, science and, 91 trusted source, 220 Tuktoyaktuk Peninsula, 49 turbulence, 65–9 tyranny of techne, 132 U Uber, 117–9, 127 UberEats app, 120–1 unboxing videos, 216, 219 United Airlines, 66–7 Uniting and Strengthening America by Fulfilling Rights and Ending Eavesdropping, Dragnet-collection and Online Monitoring Act (USA FREEDOM Act), 178 USA FREEDOM Act (2015), 178 US Drug Efficacy Amendment (1962), 95 V van Helden, Albert, 102 Veles, objectification of, 235 Verizon, 173 VHF omnidirectional radio range (VOR) installations, 104 Vigilant Telecom, 110–1 Volkswagen, 119–20 von Neumann, John about, 25 ‘Can We Survive Technology?


pages: 282 words: 81,873

Live Work Work Work Die: A Journey Into the Savage Heart of Silicon Valley by Corey Pein

"World Economic Forum" Davos, 23andMe, 4chan, affirmative action, Affordable Care Act / Obamacare, Airbnb, Amazon Mechanical Turk, Anne Wojcicki, artificial general intelligence, bank run, barriers to entry, Benevolent Dictator For Life (BDFL), Bernie Sanders, Big Tech, bitcoin, Bitcoin Ponzi scheme, Build a better mousetrap, California gold rush, cashless society, colonial rule, computer age, cryptocurrency, data is the new oil, deep learning, digital nomad, disruptive innovation, Donald Trump, Douglas Hofstadter, driverless car, Elon Musk, Evgeny Morozov, Extropian, fail fast, fake it until you make it, fake news, gamification, gentrification, gig economy, Google bus, Google Glasses, Google X / Alphabet X, Greyball, growth hacking, hacker house, Hacker News, hive mind, illegal immigration, immigration reform, independent contractor, intentional community, Internet of things, invisible hand, Isaac Newton, Jeff Bezos, job automation, Kevin Kelly, Khan Academy, Larry Ellison, Law of Accelerating Returns, Lean Startup, life extension, Lyft, Mahatma Gandhi, Marc Andreessen, Mark Zuckerberg, Menlo Park, minimum viable product, move fast and break things, mutually assured destruction, Neal Stephenson, obamacare, Parker Conrad, passive income, patent troll, Patri Friedman, Paul Graham, peer-to-peer lending, Peter H. Diamandis: Planetary Resources, Peter Thiel, platform as a service, plutocrats, Ponzi scheme, post-work, public intellectual, Ray Kurzweil, regulatory arbitrage, rent control, RFID, Robert Mercer, rolodex, Ronald Reagan, Ross Ulbricht, Ruby on Rails, Sam Altman, Sand Hill Road, Scientific racism, self-driving car, selling pickaxes during a gold rush, sharing economy, side project, Silicon Valley, Silicon Valley billionaire, Silicon Valley startup, Singularitarianism, Skype, Snapchat, Social Justice Warrior, social software, software as a service, source of truth, South of Market, San Francisco, Startup school, stealth mode startup, Steve Bannon, Steve Jobs, Steve Wozniak, TaskRabbit, tech billionaire, tech bro, tech worker, TechCrunch disrupt, technological singularity, technoutopianism, telepresence, too big to fail, Travis Kalanick, tulip mania, Tyler Cowen, Uber for X, uber lyft, ubercab, unit 8200, upwardly mobile, Vernor Vinge, vertical integration, Virgin Galactic, X Prize, Y Combinator, Zenefits

All the same, Thiel said, “You could never disown anything that you’ve written.” * * * The rise of the neoreactionaries was not exclusively a coup orchestrated from above with the help of powerful, well-connected hyperlibertarians like Thiel, Patri Friedman, and Trump’s campaign financier, the tech billionaire Robert Mercer. It was also a movement from below, embraced by thousands—and eventually perhaps by millions—of disaffected young people. While the neoreactionaries expounded at tiresome length about their aims, they revealed their individual motivations only in glimpses. Justine Tunney, the Google engineer–cum–Moldbug booster, provided one such peek inside the neoreactionary mind.

See PewDiePie Klein, Michael Klein, Roxanne Kleiner Perkins Kurzweil, Ray Laborize Land, Nick Lee, Rhoda Lifeboat Foundation Lifehacker Lifograph LinkedIn Lockheed Lockheed Martin Lombardi, Steven Lucas, George Luckey, Palmer Lyft Machine Intelligence Research Institute MacLeod, Ken Marshall, Brad Mason, Andrew McCauley, Raymond MCI Communications Mechanical Turk Meetup.com Mercer, Robert Microsoft Millionaires Society Miner, Bob Mishra, Pankaj Modi, Narendra Moldbug, Mencius. See Yarvin, Curtis Guy Monkeywrench International Moore, Gordon More, Max More Right Moritz, Michael Morozov, Evgeny Mossberg, Walt Muck Rack Musk, Elon Myers, PZ MySocialPetwork.com Nail, Rob NASA National Review National Science Foundation NerdWallet Netflix Netscape Newbridge Capital Newsweek New Yorker New York Times Nike Nimoy, Leonard Nissan Northrup Grumman Obama, Barack Odierno, Raymond Omni OpenBazaar Operation SLOG Oracle Othman, Ghazi Ben Outbrain Page, Larry Palantir Pando Pandora Patchwork Paul, Terry PayPal Paytm Pelosi, Nancy PepsiCo Petbu PewDiePie PharmaBot Plouffe, David Polous, James Poole, Chris Prabhakar, Hitha Procter & Gamble Product Hunt Quinn, Zoe Rand, Ayn Reagan, Ronald Reddit RentAFriend.com Reuters Rodger, Elliot Roof, Dylann Runway Sacks, David SAIC Samsung Sanders, Bernie San Francisco Chronicle San Jose Mercury News Sarkeesian, Anita SBIR Scalia, Antonin Schmidt, Eric Schulte, Todd Seasteading Institute SENS Research Foundation Sequoia Capital SF Weekly Shockley, William Silicon Valley Index Silk Road Singularity Singularity Is Near, The (Kurzweil) Singularity Summit Singularity University Sjöblad, Hannes Skinner, B.


pages: 307 words: 88,180

AI Superpowers: China, Silicon Valley, and the New World Order by Kai-Fu Lee

"World Economic Forum" Davos, AI winter, Airbnb, Albert Einstein, algorithmic bias, algorithmic trading, Alignment Problem, AlphaGo, artificial general intelligence, autonomous vehicles, barriers to entry, basic income, bike sharing, business cycle, Cambridge Analytica, cloud computing, commoditize, computer vision, corporate social responsibility, cotton gin, creative destruction, crony capitalism, data science, deep learning, DeepMind, Demis Hassabis, Deng Xiaoping, deskilling, Didi Chuxing, Donald Trump, driverless car, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, fake news, full employment, future of work, general purpose technology, Geoffrey Hinton, gig economy, Google Chrome, Hans Moravec, happiness index / gross national happiness, high-speed rail, if you build it, they will come, ImageNet competition, impact investing, income inequality, informal economy, Internet of things, invention of the telegraph, Jeff Bezos, job automation, John Markoff, Kickstarter, knowledge worker, Lean Startup, low skilled workers, Lyft, machine translation, mandatory minimum, Mark Zuckerberg, Menlo Park, minimum viable product, natural language processing, Neil Armstrong, new economy, Nick Bostrom, OpenAI, pattern recognition, pirate software, profit maximization, QR code, Ray Kurzweil, recommendation engine, ride hailing / ride sharing, risk tolerance, Robert Mercer, Rodney Brooks, Rubik’s Cube, Sam Altman, Second Machine Age, self-driving car, sentiment analysis, sharing economy, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, Skype, SoftBank, Solyndra, special economic zone, speech recognition, Stephen Hawking, Steve Jobs, strong AI, TED Talk, The Future of Employment, Travis Kalanick, Uber and Lyft, uber lyft, universal basic income, urban planning, vertical integration, Vision Fund, warehouse robotics, Y Combinator

Using internet AI, Alibaba can recommend products you’re more likely to buy, Google can target you with ads you’re more likely to click on, and YouTube can suggest videos that you’re more likely to watch. Adopting those same methods in a different context, a company like Cambridge Analytica used Facebook data to better understand and target American voters during the 2016 presidential campaign. Revealingly, it was Robert Mercer, founder of Cambridge Analytica, who reportedly coined the famous phrase, “There’s no data like more data.” ALGORITHMS AND EDITORS First-wave AI has given birth to entirely new, AI-driven internet companies. China’s leader in this category is Jinri Toutiao (meaning “today’s headlines”; English name: “ByteDance”).

See also algorithms, AI chips and, 96 data and, 56 deep learning as part of, 6, 94 economy driven by, 25, 84, 91, 94–95 social investment stipend and, 221–22 machine reading, 161 machine translation, 104, 161 Manhattan Project, 85 Manpower, 47–48 market-driven startups, 26–27, 45 mass entrepreneurship and mass innovation, 54, 62–68, 99 McAfee, Andrew, 148–49, 150 McCarthy, John, 7 McKinsey Global Institute, 159–60 medical diagnosis, 113–15, 167, 195, 211. See also healthcare Meituan (Groupon clone), 23–24, 46–49, 72 Meituan Dianping, 49, 69, 70, 72 Mercer, Robert, 108 Messenger, 70 Mi AI speaker, 127 micro-finance, 112–13, 138 Microsoft AI chips and, 96 antitrust policy and, 28 China at time of founding of, 33 as dominant AI player, 83, 91 Face++ and, 90 Lee at, 28, 33, 105, 184 speech recognition, 93 Tencent and, 93 top researchers at, 93 Microsoft Research, 91 Microsoft Research Asia (formerly Microsoft Research China), 89–90, 105 Middle East, 137, 139, 169 mini-iPhones, 32 Minsky, Marvin, 7 mission-driven startups, 26, 45 MIT, 30 Mobike, 77–78 mobile payments, 16, 54–55, 60–61, 73–78, 79, 110 Momenta, 135 monopolies, 20, 96, 168–69, 170–71, 172, 229 Moravec, Hans, 166 Moravec’s Paradox, 166–67 Musical.ly, 109 Musk, Elon, 49, 131, 141 N Nanjing, China, 99 narrow AI, 10, 142 National Aeronautics and Space Administration (NASA), 3 natural-language processing, 105, 108, 115 Netherlands, 229 neural networks approach to AI, 7, 8–10, 89 new world order, 18–19, 20–21, 138–39 Ng, Andrew, 13, 44, 88, 93, 113–14, 144 99 Taxi, 137 Nixon, Richard, 207 North Africa, 138 Nuance, 105 Nuomi (group buying affiliate), 48–49 Nvidia, 96, 97, 135 O Obama, Barack, 97–98, 100, 104 object recognition, 9, 90, 94, 117.


pages: 334 words: 91,722

Brexit Unfolded: How No One Got What They Want (And Why They Were Never Going To) by Chris Grey

"World Economic Forum" Davos, anti-communist, Berlin Wall, Boris Johnson, Brexit referendum, coronavirus, COVID-19, deindustrialization, Dominic Cummings, Donald Trump, failed state, Fall of the Berlin Wall, first-past-the-post, game design, global pandemic, imperial preference, Jeremy Corbyn, John Bercow, lockdown, non-tariff barriers, open borders, post-truth, reserve currency, Robert Mercer

In particular, it’s instructive to recall how in the 1980s writers on the left, especially the sociologist Professor Stuart Hall, started to explain that Thatcher kept winning elections because contrary to the assumption of economic primacy, in Hall’s words, ‘material interests … are not escalators which automatically deliver people to their appointed destinations, “in place”, within the political ideological spectrum’.128 It’s an important insight that remains true. Coming to Brexit specifically, viewing leave voters as the unwitting dupes of ‘warlord’ or ‘disaster’ capitalism, funded by the likes of US hedge fund mogul Robert Mercer and supported by a network of libertarian think tanks, doesn’t take us anywhere. For whilst (some) remainers may believe that to be so, it has a precise mirror-image in the repeated claim made by (some) leavers that remainers are the mouthpieces of the ‘global elite’, funded by the likes of financier George Soros, one of the donors to the People’s Vote campaign, and supported by numerous liberal think tanks.

The Age of Britain in Europe’ 31 January 2020 The Gladstone Diaries (blog) http://gladstonediaries.blogspot.com/2020/01/brexit-in-historical-perspective-age-of.html 135 Stefan Stern, ‘The great Brexit “up yours”: How three decades of Euroscepticism made the UK go full tabloid’ Politics.co.uk 21 August 2019 https://www.politics.co.uk/comment-analysis/2019/08/21/the-great-brexit-up-yours-how-three-decades-of-euroscepticism-made-the-uk-go-full-tabloid/ 136 Margaret Thatcher, ‘Speech to the College of Europe (“The Bruges speech”)’ Margaret Thatcher Foundation 20 September 1988 https://www.margaretthatcher.org/document/107332 137 Anushka Asthana and Rowena Mason, ‘UK must leave European convention on human rights, says Theresa May’ The Guardian 25 April 2016 https://www.theguardian.com/politics/2016/apr/25/uk-must-leave-european-convention-on-human-rights-theresa-may-eu-referendum 138 James Blitz, ‘UK’s Brexit officials targeted with death threats and personal slurs’ Financial Times 20 October 2018 https://www.ft.com/content/a1def03a-d2fb-11e8-a9f2-7574db66bcd5 INDEX air travel 1 Article 1 ECJ ruling 1 extensions to leaving process 1, 2, 3, 4, 5, 6, 7 formally triggered 1 legal challenge 1, 2 not immediately triggered 1 parliamentary vote 1, 2 terms 1 time pressures 1, 2, 3 authenticity 1 automobile industry 1, 2, 3, 4 Baker, Steve 1, 2, 3 Barnier, Michel 1, 2, 3, 4, 5, 6 Barnier staircase 1, 2 Barwell, Gavin 1 Basu, Neil 1 BBC, Daily Politics 1 Benn Act (‘Surrender Act’) 1, 2, 3, 4 Benn, Hilary 1, 2, 3 Benn, Tony 1 Bercow, John 1, 2, 3 Bettel, Xavier 1 Biden, Joe 1 Blair, Tony 1, 2 Brady, Graham 1 Braverman, Suella 1 Brexit incompatibility of nationalist vs globalist ideas 1, 2 minimal scrutiny (2017 election campaign) 1 multiple models 1, 2, 3, 4, 5, 6 shifting terminology 1 symbolic act 1 see also outcome of Brexit; preparations for Brexit; process of Brexit; transition period ‘Brexit means Brexit’ 1 Brexit in name only (BRINO) 1, 2 Brexit Party 1, 2, 3, 4, 5, 6, 7 Brexit Ultras dissatisfaction with outcome 1, 2, 3, 4, 5 and the Irish border 1 repudiation of Withdrawal Agreement 1 Withdrawal Agreement Bill debate 1 see also European Research Group (ERG); UKIP; Brexit Party Brexiters definition 1n ill-equipped for delivering Brexit 1 misconceptions 1 motivations 1 privileged elite 1 promises 1, 2, 3, 4, 5 psychology of betrayal and victimhood 1, 2, 3, 4 Brown, Gordon 1, 2 budget contributions see financial settlement Cable, Sir Vince 1 Cameron, David 1, 2, 3, 4, 5 Canada, CETA (Comprehensive Economic and Trade Agreement) 1 Canada option see hard Brexit (Canada option) CANZUK (Canada, Australia, New Zealand and United Kingdom) confederation 1 care system, EU workers 1 Carney, Mark 1, 2 Carswell, Douglas 1 Chequers proposal (July 2018) 1, 2, 3, 4 China, global rise 1 citizens’ rights 1, 2, 3, 4 see also free movement of people civil service, Brexiter criticisms 1, 2 Clarke, Kenneth 1, 2, 3 Cockfield, Lord 1 Connelly, Tony 1 Conservative Party election manifesto (2017) 1, 2 internal divisions 1, 2, 3 leadership contest 1 loss of whip for rebels 1, 2 Malthouse Compromise (January 2019) 1, 2 May’s conference speech (2016) 1 single market enthusiasm 1 Thatcher’s Bruges speech 1, 2 see also Brexit Ultras; European Research Group (ERG) Cooper, Yvette 1, 2, 3 Corbyn, Jeremy ambiguous Brexit role 1, 2, 3, 4 Brexiter enabler 1, 2, 3 election campaign (2019) 1 meetings with May 1 coronavirus pandemic 1, 2 Cox, Geoffrey 1 culture war (Brexiter/remainer) 1, 2 Cummings, Dominic 1, 2, 3, 4, 5, 6, 7 Customs Bill 1 customs union background 1 Chequers proposal 1 EU Withdrawal Bill 1 possible UK membership 1 UK membership ruled out 1 UK white paper (February 2017) 1 Daily Mail 1, 2 Davis, David 1 Brexit promises 1, 2 on free trade agreement 1, 2 and Irish border 1 on Joint Report 1 negotiating failures 1, 2, 3 resignation 1 single market 1 on transition period 1 white paper (February 2017) 1 Democratic Unionist Party (DUP) Conservative government support 1, 2 election manifesto (2017) 1 Irish border issue 1, 2 objections to Withdrawal Agreement 1 potential threats from Brexit 1, 2 support for Brexit 1 Department for Exiting the European Union (DExEU) 1, 2, 3n disaster capitalism 1 Duncan Smith, Iain 1 economy business concerns 1 claims of Brexit benefits 1 coronavirus impacts 1 effects of referendum result 1 long-term prospects 1 minimal general election scrutiny 1 Project Fear 1, 2 Elliott, Larry 1 England, referendum result 1 Euratom 1 European Banking Authority (EBA) 1 European Capital of Culture (2023) 1 European Convention on Human Rights (ECHR) 1 European Court of Justice (ECJ) citizens’ rights 1, 2, 3 negotiations 1, 2, 3, 4, 5 role 1 single market rules 1 UK and Article 1 ruling 2 UK jurisdiction 1, 2, 3 white paper (February 2017) 1 European Economic Community, UK membership 1, 2 European Free Trade Association (EFTA) 1 European Medicines Agency (EMA) 1 European Parliament elections 1 ratification of exit deal 1, 2 European Research Group (ERG) and Covid Recovery Group 1, 2 demands for true Brexit 1, 2 and the Irish border 1 and May’s proposals 1 parliamentary scrutiny 1, 2 proposals 1 see also Brexit Ultras European Union Cameron renegotiation 1 hypothetical negotiating scenario 1 negotiating as a bloc 1, 2 UK future relations 1 UK membership benefits 1 experts 1, 2 Farage, Nigel 1 changing definition of true Brexit 1, 2, 3, 4 on Corbyn 1 coronavirus restrictions 1 election (2019) 1, 2 European election (2019) 1, 2 privileged elite 1 referendum result 1 financial settlement hypothetical scenario 1 negotiations 1, 2, 3 UK’s budget contributions 1, 2 fisheries 1 Flexcit (flexible continuous exit) 1 Florence speech (September 2017) 1 Fox, Liam 1, 2, 3, 4, 5, 6, 7, 8 Francois, Mark 1 free movement of people 1, 2, 3, 4, 5 see also citizens’ rights; immigration Frost, David 1, 2 General Agreement on Tariffs and Trade, Article XXIV 1, 2, 3 general election (2017) 1 general election (2019) 1 Germany, automobile industry 1, 2 Gibraltar 1 Global Britain 1 Good Friday (Belfast) Agreement (GFA) 1, 2 Gove, Michael 1, 2, 3, 4, 5, 6, 7 Green, Damian 1 Green, David Allen 1 Green Party 1 Greening, Justine 1 Greenland, EU departure 1 Grieve, Dominic 1 Hall, Stuart 1 Hammond, Philip 1, 2, 3, 4 Hannan, Daniel 1 hard Brexit (Canada option) ‘Canada-style’ deal confusion 1 definition 1 draft Withdrawal Agreement (November 2018) 1 first hints 1 mandate claimed by Brexiters 1 May’s Lancaster House speech (January 2017) 1 Hargreaves, Peter 1 Hartley-Brewer, Julia 1 Heaton-Harris, Chris 1 High Court, ruling on EU leaving process 1 Hill, Fiona 1 Hoey, Kate 1 House of Commons Benn Act (‘Surrender Act’) 1, 2, 3, 4 Brady amendment 1 Cooper Act 1 Customs Bill 1 gridlock 1 Grieve amendment 1 indicative votes 1 Johnson’s deal defeated 1 Kyle–Wilson plan 1, 2 Letwin motions 1, 2, 3 meaningful vote debate and rebellions 1 meaningful vote deferral 1 meaningful vote on Johnson deal disallowed 1, 2 meaningful votes defeated 1, 2, 3 no confirmatory vote on referendum result 1, 2 Parliament takes control of business 1 prorogation 1 provision of meaningful vote on final terms 1 third meaningful vote disallowed 1 Trade and Cooperation Agreement vote 1 vote on triggering Article 1 55, 2 see also Withdrawal Agreement Bill Howard of Lympne, Lord 1 Hungary 1 Hunt, Jeremy 1 immigration 1, 2, 3, 4, 5, 6 see also free movement of people Internal Market Bill (IMB) 1, 2 Ireland Common Travel Area 1 economic effects of Brexit 1 Irish reunification prospect 1, 2 support for EU membership 1 see also Irish border Irexit 1 Irish border backstop arrangements 1, 2, 3, 4 backstop legal advice 1 backstop renegotiations 1 Brexiter misconceptions 1, 2 differences between May and Johnson deals 1 draft Withdrawal Agreement (November 2018) 1, 2 ‘dual customs solution’ 1 frontstop 1, 2, 3, 4 historical background 1 insoluble problem 1 Johnson deal 1, 2 negotiations 1, 2 no preparations necessary 1 referendum campaign warnings 1 technological solutions 1, 2, 3, 4, 5 ‘two customs’ solution 1 Withdrawal Agreement Bill 1 Irish Times 1 Johnson, Boris 1, 2 Brexit promises 1, 2 election campaign (2019) 1 Foreign Secretary 1 on Irish backstop 1 on Irish border 1, 2 misunderstanding of Brexit complexities 1, 2, 3 opposition to Article 1 extension 2 ‘oven-ready’ Brexit 1, 2 party leader and Prime Minister 1 privileged elite 1 reaction to prorogation failure 1 reputation as untrustworthy 1, 2, 3 resigns as Foreign Secretary 1, 2, 3 Vote Leave Cabinet and advisers 1, 2, 3 votes for Withdrawal Agreement 1 Johnson, Jo 1 Juncker, Jean-Claude 1, 2, 3 Kawczynski, Daniel 1 Kwarteng, Kwasi 1 Kyle–Wilson plan 1, 2 Labour Party Article 1 Commons vote 2 Brexit policy 1, 2, 3, 4 election campaign (2019) 1 election manifesto (2017) 1 historical relations with EU 1, 2, 3 and immigration 1 on transition period 1 Lancaster House speech (January 2017) 1 Lawson, Nigel 1 Leave Alliance 1 Lee, Phillip 1 Letwin, Sir Oliver 1, 2, 3, 4 Level Playing Field (LPF) 1, 2, 3 Lewis, Brandon 1, 2 Lexiters (left-wing Brexiters) 1, 2, 3, 4, 5 Liberal Democrats 1, 2, 3, 4 Longworth, John 1, 2 Major, Sir John 1, 2 Malthouse Compromise (January 2019) 1, 2 ‘managed no deal’ 1, 2, 3 May, Theresa calls general election 1 character 1, 2 Chequers proposal (July 2018) 1 Commons vote on Article 1 2 conference speech (2016) 1 criticism 1 duty to deliver Brexit 1, 2 on financial settlement 1 Florence speech (September 2017) 1 Lancaster House speech (January 2017) 1 leadership style 1, 2 national tour 1 no confidence leadership vote 1 ‘no deal is better than a bad deal’ 1, 2 Prime Minister 1 reliance on DUP 1, 2 remain campaigner 1 request for EU to suggest terms 1, 2 resignation 1 sequenced vs parallel talks 1 televised address 1 media 1 Mercer, Robert 1 Merkel, Angela 1, 2 Middle England (Coe) 1 Miller, Gina 1 Monbiot, George 1 Morgan, Nicky 1 MPs, abuse and intimidation 1 NAFTA (North American Free Trade Agreement) 1 negotiations British unpreparedness 1, 2 Chequers proposal (July 2018) 1, 2 Chequers proposal rejected by EU 1, 2 conflation of exit and future terms deals 1, 2, 3, 4, 5, 6, 7, 8 draft Withdrawal Agreement (November 2018) 1 EU draft guidelines (March 2017) 1 EU draft Withdrawal Agreement rejected (February 2018) 1 hypothetical scenario 1 Joint Report (December 2017) 1 lack of clarity from UK 1, 2 May’s Florence speech (September 2017) 1 mistrust of British 1, 2, 3, 4, 5 phase one agreement 1 Political Declaration 1, 2, 3 Tusk’s comments 1 UK position papers (2017) 1 UK white paper (February 2017) 1, 2, 3, 4 see also trade negotiations Nixon, Richard 1 ‘no deal is better than a bad deal’ 1, 2 no-deal Brexit (WTO option) Brexiter demand 1 change in meaning 1 damage to EU–UK trade 1 definition 1 ‘Go WTO’ 1 Letwin amendment 1 ‘managed no deal’ 1, 2, 3 misunderstandings and contradictions 1, 2 terms 1 UK enthusiasm 1 UK preparations 1 non-tariff barriers (NTBs) 1, 2 North, Richard 1 Northern Ireland historical background 1 Irish reunification prospect 1, 2 referendum result 1, 2 security situation 1 see also Irish border Northern Ireland Assembly 1, 2, 3n Northern Ireland Protocol 1, 2, 3, 4 Norway 1, 2 Norway option see soft Brexit (Norway option) Operation Yellowhammer 1 O’Toole, Fintan 1 outcome of Brexit Brexiter victimhood psychology 1, 2, 3, 4 Brexiter/remainer culture war 1, 2 expectation that things would carry on as usual 1 future prospects 1 misleading and false claims 1, 2, 3, 4 never predetermined 1, 2 ‘oven-ready’ Brexit 1, 2 Paterson, Owen 1 Patten, Chris 1 People’s Vote campaign 1, 2, 3, 4, 5 Plaid Cymru 1 planning for Brexit, contradictory and ambiguous 1 Poland 1 Political Declaration 1, 2, 3, 4, 5 political integration 1 populist authenticity 1 preparations for Brexit business advice 1 customs and regulatory checks 1 hampered 1 for individuals 1 information campaigns 1 military planning 1 Operation Yellowhammer 1 Private Eye 1 process of Brexit extensions to leaving process 1, 2, 3, 4, 5, 6, 7 impatience with time taken 1, 2 lack of definition 1 ongoing 1 sequenced vs parallel talks (withdrawal and future terms agreements) 1, 2, 3, 4, 5, 6, 7, 8 time pressure of Article 1 process 2, 3, 4 Project Fear 1, 2, 3, 4, 5 prorogation 1 public opinion ambivalence over Brexit 1 on Brexit negotiations 1 economic damage of Brexit 1 polarisation 1, 2, 3, 4 Second World War nostalgia 1 on single market membership 1 Raab, Dominic 1, 2, 3, 4, 5 Redwood, John 1, 2 Rees-Mogg, Jacob 1, 2, 3, 4, 5 referendum (1975) 1 referendum (June 2016) advisory nature 1, 2 claims of irregularities 1 government leaflet 1 immediate economic effects 1 leave/remain voter demographics 1 no Commons confirmatory vote 1, 2 Project Fear 1, 2, 3, 4 result 1 Robbins, Olly 1 Rogers, Sir Ivan 1 Saunders, Robert 1 Schengen Area 1 Scotland 1, 2 Scottish National Party (SNP) 1 Second World War nostalgia 1, 2 security cooperation 1 services trade 1, 2, 3 single market Chequers proposal 1 confusion with free trade agreement 1, 2, 3, 4 EFTA member state access 1 four freedoms of movement 1 hypothetical scenario 1 prior UK enthusiasm 1 public preference 1 UK access debate 1, 2 UK membership rejected 1 UK white paper (February 2017) 1 soft Brexit ‘Brexit in name only’ (BRINO) 1 Flexcit (flexible continuous exit) 1 viability 1 soft Brexit (Norway option) 1, 2, 3, 4, 5 Soros, George 1 Soubry, Anna 1 sovereign equality 1, 2 sovereignty 1, 2, 3, 4, 5 Spain, Gibraltar issue 1 Starmer, Sir Keir 1, 2 state aid 1, 2 Stewart, Rory 1 Supreme Court rulings EU leaving process 1 prorogation 1, 2 Switzerland 1, 2, 3 terrorism threat 1 Thatcher, Margaret 1, 2 Timothy, Nick 1, 2 trade customs and regulatory checks 1 possible UK–US deal 1, 2 potential damage to EU–UK trade from hard Brexit 1 UK–EU trade statistics 1, 2 UK/non-EU countries 1 Trade and Cooperation Agreement (2020) Commons vote 1 conflation with Withdrawal Agreement 1, 2, 3, 4 confusion over timing 1 fisheries 1 governance 1 outstanding issues 1 terms 1 trade negotiations Barnier staircase 1 ‘final’ deadlines 1 governance mechanism 1 impossibility of frictionless trade 1, 2 ‘last-minute blink’ theory 1, 2 Level Playing Field 1, 2 possible options 1 single market membership vs free trade agreement 1, 2, 3, 4 third-country precedents 1 UK–EU deal 1, 2, 3 UK Future Relationship document 1 UK as ‘sovereign equal’ 1, 2 Vote Leave free zone promises 1, 2 zero tariff, zero quotas 1, 2, 3, 4 transition period differences over length 1 draft Withdrawal Agreement (November 2018) 1 expiry date 1 May’s acceptance 1 UK refusal to extend 1, 2, 3 Withdrawal Agreement 1 Trump, Donald 1, 2, 3 Turkey 1 Tusk, Donald 1, 2, 3, 4 UKIP (United Kingdom Independence Party) 1, 2, 3 Umunna, Chuka 1 United States, relations with UK 1, 2 Varadkar, Leo 1, 2 Villiers, Theresa 1 Vote Leave campaign and controlled immigration 1 free trade zone promises 1, 2 future terms promise 1 misleading economic claims 1 promises 1 slogan 1 time-frame claims 1 version of Brexit not specified 1, 2 Wales, referendum result 1 Weyand, Sabine 1 white paper (February 2017) 1, 2, 3, 4 Withdrawal Agreement Brexit Ultra repudiation 1 conflation with future terms agreement 1, 2, 3, 4, 5 draft (November 2018) 1 signature 1 UK’s lack of clarity on terms 1 UK’s unilateral change proposals 1 Withdrawal Agreement Bill Commons amendment 1 customs arrangement 1 enacted 1 government loses on meaningful vote requirement 1 Lords amendment 1 passes second reading 1 timescale for debate 1, 2 WTO (World Trade Organization) most favoured nation (MFN) terms 1 see also no-deal Brexit (WTO option) COPYRIGHT First published in Great Britain in 2021 by Biteback Publishing Ltd, London Copyright © Chris Grey 2021 Chris Grey has asserted his right under the Copyright, Designs and Patents Act 1988 to be identified as the author of this work.


The Unknowers: How Strategic Ignorance Rules the World by Linsey McGoey

Alan Greenspan, An Inconvenient Truth, anti-globalists, antiwork, battle of ideas, behavioural economics, Big Tech, Black Lives Matter, Branko Milanovic, British Empire, Cambridge Analytica, carbon tax, Cass Sunstein, Clive Stafford Smith, conceptual framework, Corn Laws, corporate governance, corporate raider, Credit Default Swap, David Ricardo: comparative advantage, Donald Trump, drone strike, en.wikipedia.org, European colonialism, fake news, Frances Oldham Kelsey, hiring and firing, Howard Zinn, income inequality, it is difficult to get a man to understand something, when his salary depends on his not understanding it, joint-stock company, junk bonds, knowledge economy, market fundamentalism, mass incarceration, Michael Milken, minimum wage unemployment, Naomi Klein, new economy, Nick Leeson, p-value, Paul Samuelson, Peter Thiel, plutocrats, post-truth, public intellectual, race to the bottom, randomized controlled trial, rent-seeking, road to serfdom, Robert Mercer, Ronald Reagan, Scientific racism, selective serotonin reuptake inhibitor (SSRI), Social Justice Warrior, Steven Pinker, Suez crisis 1956, The Chicago School, The Wealth of Nations by Adam Smith, union organizing, Upton Sinclair, W. E. B. Du Bois, Washington Consensus, wealth creators

Buchanan’s defining character trait is that he is too insulated by his own wealth to recognize his own ignorance: he has no knowledge of how much he does not know. If we take a look around, we can recognize the Tom Buchanans and the Henry Fords of today. Take, for example, the big money support for right-wing publications like Breitbart and Fox News. Both in the past and now, it’s figures such as Ford in the 1920s and people such as Robert Mercer and Rupert Murdoch today whose money is used to fuel racially charged hostility in towns and cities across America and Britain. Mercer is a computer scientist who made a fortune through a hedge fund and used his money to back alt-right media vehicles such as Breitbart. Whether or not Mercer or Murdoch personally hold racist views is not certain: Mercer has strongly denied this.

., 26–7, 28, 313 McIntosh, Glenn, 288–90 macro-ignorance, 12–15, 169, 225–6 Madison, James, 47 Mandeville, Bernard, 248 Mankiw, Gregory, 132; Macroeconomics, 152–3, 216 marginal productivity theory, 76, 130–5, 152–3 market fundamentalism, 4–5, 6–7, 13 Mason, Paul, 43 Mazzucato, Mariana, 152, 304; The Value of Everything, 134–5 meat industry, 255 medical experiments, 72 Medicines Act (1968) (UK), 291–2 Medicines and Healthcare Products Regulatory Agency (MHRA): antidepressant reviews, 282–6; dependence on pharmaceutical companies, 278, 284–5; GlaxoSmithKlein investigation, 252, 290, 291–2; non-prosecutions, 252, 253, 278, 291, 292; unpublished medical trials, 251–2, 286; useful unknowns, 51 Meikson Woods, Ellen, 296 Mens Rea Reform Act (US), 236–44 mental health: National Collaborating Centre, 249–50; see also antidepressants Mercer, Robert, 85–6, 87 Merck, 258–61 Merrell, 256, 257 Meyer, Eugene, 219 MHRA see Medicines and Healthcare Products Regulatory Agency (MHRA) micro-ignorance, 12–15, 141–2, 168, 225–6 Middle East, 14–15, 68–9, 202–3 Mill, George, 159 Mill, James, 161 Mill, John Stuart, 37, 41; as an ‘unknower’, 156–7, 162, 299; Autobiography, 157–60; Britain’s peaceful global dominance, 202, 203; co-authorship with wife and stepdaughter, 7, 60–1, 153, 157–60; Considerations on Representative Government, 161; and the coolie trade, 155–6; On Liberty, 7, 60–1, 153, 158, 166; Principles of Political Economy, 158; The Subjection of Women, 202, 203; voter franchise limitations, 156 Mills, Charles, 45, 304 mining companies, 185, 222–4 Miranda, Lin-Manuel, 193 Mishra, Pankaj, 44, 304 Monod, Jacques, 6 Montesquieu, Albert de Secondat, 29 Mosholder, Andrew, 287–8 Mulcaire, Glenn, 104, 105, 106, 112–13 multinational companies, 185, 219, 222–4 Murdoch, Elisabeth, 101, 115–16, 117 Murdoch, James, 100, 102 Murdoch, Lachlan, 102 Murdoch, Rupert: ignorance of phone hacking, 19; and racist news outlets, 85–6; select committee appearance, 99, 100–1, 114; Sun office meeting, 114–15; wilful blindness, 101–2 Muttitt, Greg, 32 Nasaw, David, 207, 208, 210 Nazism, 72, 74 neoclassical theory, 130–3, 303 Nevsun Resources, 223–4 New York Times, 54–5, 87, 238 News Corporation, 115–16, 117, 119–20, 274–5; see also phone hacking News of the World: Gordon Taylor lawsuit, 105–6; phone hacking, 19, 99, 101, 102–3; use of private investigators, 103–4 Nobel prize, 60–1 Nuremberg Code, 72 Obama, Barack, 82, 91–2, 148–9 oil companies: and Iraq war, 31–2; Standard Oil, 4, 211–14 On Liberty (Mill), 7, 60–1, 153, 158, 166 Open Society (Popper), 164 Operation Motorman, 107–8 oracular power: Brennan’s ‘simulated oracle’ test, 66–7, 95–6; concept, 16, 61–2; divine providence, 67–9; financial advisors, 67; historical context, 62–4; mainstream economic theories, 217; natural and social scientists, 64–7 Orwell, George, 129, 131–2, 164, 168, 225, 309–10 Ostrich instruction, 21, 228, 231–2; see also wilful ignorance Owens, Alec, 109–11 Paine, Thomas: ‘Agrarian Justice’, 183–4; blame-shifting, 180, 307; on divine providence, 174; and elite ignorance, 18–19; on hereditary privilege, 182–4, 308; Rights of Man, 149, 183 Patnaik, Utsa, 44, 304 pharmaceutical industry: damage settlements, 261; distortion of evidence, 11–12, 75; fear of reputational damage, 263–4; fraud, 22; medical trial data, 250–2, 259–60, 262; Merck settlement, 261; presumption of innocence, 291, 292–3; regulation seen as barrier to progress, 257–8; UK’s weak regulatory system, 252–3, 278, 291, 292; useful unknowns, 51, 257; Vioxx and heart failure, 258–62; see also drug trials; drugs philanthropy, 97–8, 204, 308 phone hacking: Caryatid Operation, 112–13; and corporate ignorance, 19; Culture, Media and Sport Committee report, 99–101; Gordon Taylor lawsuit, 105–6; ICO failure to pursue journalists, 109–12; method, 104–5; News of the World, 19, 99, 101, 102–3; victims, 19, 100, 105–6, 112 Pinker, Steven: Bannon-Pinker conundrum, 34–5; Enlightenment Now, 20, 36, 37, 135–6, 142, 202, 203, 224; globalization, 175; information avoidance theories, 37–8; poverty and in-country inequality, 36–7; on wealth distribution, 147–8 Plato, 164, 296, 297 plausible deniability, 56, 120 political deceptions, 30–1 political liberalism, 41 Popper, Karl, 163–5, 297–8; Open Society, 164 positive-sum theory, 123, 136, 147 Powell, Enoch, 68 press freedom, 199 Preston, Lewis, 219 prisoners of war, 72–3 private investigators, 103–4, 107–8 Proctor, Robert, 11 The Protocols of the Elders of Zion, 79–81 Prozac, 280–1, 289, 290 Pulquero, Ramiro Obrajero, 272 Puri, Poonam, 222–3, 304 race realism, 48 racial exploitation, 304 racism, 45, 48, 84–7, 319 Rampell, Catherine, 171, 217 rational ignorance, 46–7 Rawls, John, ‘veil of ignorance’, 8–9, 46 Reagan, Ronald, 68 reckless ignorance, 54–6, 235, 304 regulation: Adam Smith legacy, 20–1, 121, 126–7, 136–7, 140–1; anti-regulation stance, 246–8, 258, 303, 307; Hayek’s disdain, 248, 301, 303; pharmaceutical industry, 252–3, 257–8, 278, 291, 292; Tocqueville’s recommendations, 20–1, 197–200, 301 rent, 128 rent-seeking, 127–8, 131, 132 Rhodes, Cecil, 313 Ricardo, David, 186–7 Robbins, Lionel, 146 Robins, Nick, 180–1 Robinson, Joan, 133, 135, 147, 152 Rockefeller, John D.: belief in self-made success, 205, 214; beneficiary of laissez-faire practices, 205–6; deceitful opposition to anti-monopoly legislation, 4; master of ignorance, 20; new cooperation principle, 215; philanthropy, 204; secretive railroad deals, 211–13; South Improvement Company cartel, 213; Standard Oil, 4, 211–14; strategic ignorance of business takeovers, 213–14 Roosevelt, Franklin D., 196 Rosenfeld, Sophia, 58 Ross, David, 269–70, 272–3 Rumsfeld, Donald, 52 Samuelson, Paul, 134, 152 sanctioned ignorance, 40–2 Sand, George, 166–7, 324–6 Sanofi-Aventis, 269–77 Sarch, Alexander, 231–2, 233–5, 304 Sartre, Jean-Paul, 293–4 Schiebinger, Londa, 11 Schwartz, Anna, 54–5, 59–61 science, 8, 64–7 scientific racism, 48, 319 Scotland Yard, 112–14 Scott, Tom, 207, 212 Securities and Exchange Commission (SEC), 53–4 self-interest, 125–6, 126, 136, 139–40 Seroxat, 250–2, 282 servitude, 41–2, 44, 155–6 Shapiro, Aaron, 79 shared prosperity theory, 123, 136, 147 Sherman, Rachel, 117–18 Shine lawsuit, 115–16, 117 Simons, Henry, 246 Simpson, Jeffrey, 28 Sinclair, Niigaanwewidam James, 27 Sinclair, Upton, The Jungle, 255 slavery, 43–4, 205; see also servitude Smarsh, Sarah, 84 smarts see strong/smart groups Smith, Adam, 9; Britain a nation of shopkeepers, 192; criticism of monopoly protections, 127–9; criticisms of merchants, 247, 320; economic classes of society, 138–40, 143; and economic inequality, 136; on government regulation, 20–1, 121, 126–7, 136–7, 140–1; his mother’s influence, 125; inevitability of conflict, 186; misrepresentation of his ideas, 142–6, 310–12; on relative poverty, 142–3; on self-interest, 126, 136; strategic and wilful ignorance of, 122–3; tiered justice system, 121; timing and motives for helping the poor, 245; trade protectionism, 186, 190–1; on wealth distribution, 142–4, 191; Wealth of Nations, 6–7, 121, 125–6, 136, 169, 189, 245; Wealth of Nations abridged versions, 144–6 Smith, David, 109–10 snowmobile fallacy, 241–3 social silence, 53 Société Générale, 120 Socrates, 45, 63 Somin, Ilya, 94–5, 96 Sorel, Georges, 17 Soviet Union, uncomfortable facts, 5, 13 Spivak, Gayatri, 40–1 SSRI drugs see antidepressants Standard Oil, 4, 211–14 Steinzor, Rena, 244–5 Stewart, Maria W., 130–1 Stigler, George, 133, 246–7, 248 strategic ignorance: autocratic exploitation, 69–71; business practices, 20, 205; Carnegie, 208–10; corporate anonymity, 45–6; definition, 3; of drone strikes, 91–2; economic theory, 122–3; emancipatory nature, 315–17; exposure efforts treated as inexcusable, 269–70; Ford, 79–81, 98; MHRA’s non-prosecution record, 291–2, 293–4; and political networks, 22; Rockefeller, 213–14 strong/smart groups, 16–17, 69–71, 77, 173–4, 312–13 student loans, 185 Suez crisis, 31 suicide rates, 307 Sun, 114–15 Sutherland, Kathryn, 145–6, 159 Syll, Lars, 187 Symons, Baroness, 32 taxation, Paine’s proposals, 184, 308 Taylor, Gordon, 105–6 Taylor, Harriet, 7, 60–1, 153, 157–60, 166, 299 Taylor, Helen, 157–60 Taylor, Keeanga-Yamahtta, 68 Teicher, Martin, 280 Temple, Robert, 287–8 Tett, Gillian, 53 Thalidomide, 254, 256–8 think tanks, 65 Thomas, Richard, 110, 111 Tillerson, Rex, 214 tobacco industry, 51 Tocqueville, Alexis de: Democracy in America, 197–200, 309, 322–3; and divine providence, 322–4; French workers, 325–6; government regulation of industry, 20–1, 197–200, 301; prejudice against women, 166–7, 324–6 torture, 72–5 trade: free trade, 17–13, 57, 200–1; mercantilism, 169–70, 171; protectionism, 186, 188, 190–1; Ricardo’s comparative advantage theory, 186–8; US policy, 171, 188, 190, 217 Trefgarne, George, 179–80 Trump, Donald: class myths of voter support, 81–4, 162, 163; elite ignorance, 90–1, 93–4; on history, 314; on Obama, 82, 148–9; presidential election, 19; selective use of facts, 92–4; on torture, 73–4; and truth, 17; wealthy backers, 83–4 truth, liberating potential, 9–10 United Kingdom: male enfranchisement, 42; market interventionism, 43–4; military interventions, 14–15; Suez crisis, 31; trade policies, 44, 57, 186, 190–1; weak regulation of pharmaceutical companies, 252–3, 278, 291–2 United States: conscription, 14–15; drone strikes, 91–2; in-country inequality, 14–15, 36–7; labour oppression, 129–30; laissez-faire policies, 194–5; military interventions, 14–15, 68–9, 185; New Deal, 196; origins myths, 169; suicide rates, 307; trade policies, 171, 188, 190, 217; War Crimes Act (1996), 73; workplace deaths, 219–20 United States Department of Justice, 102, 238, 252, 261 Unser, Bobby, 242–3 unwitting ignorance, 42, 122–3 useful unknowns, 51–6, 257, 277 utilitarianism, 8, 155 ‘veil of ignorance’, 8–9, 46 Viner, Jacob, 300, 302–3 Vinson and Elkins, 235 Vioxx, 258–62 von Eschenbach, Andrew, 273 voter ignorance: Brexit, 82–3, 89–90, 162; collective, shared problem, 243–4; definition, 94; justification for disenfranchisement, 70, 156, 174; political knowledge test, 66–7, 95–6; solutions, 94–5; Trump election, 19, 162; see also democracy, and disenfranchisement War Crimes Act (1996) (US), 73 Washington Consensus, 34 Washington Post, 89, 171, 217, 257 Watkins, Sherron, 235 Watson, Mathew, 187, 188 wealth: evidence of intelligence, 77, 81; financial oligarchy, 65; ignorance and inherited wealth, 139; inherited wealth, 117–18; and morality, 162–3; and racism, 84–7; US voter support for Trump, 83–4, 162, 163 wealth inequality: effect on social wellbeing, 135, 147; God’s will, 75–7; growth, 137; in-country inequality, 36–7; India-England, 129; legitimisation, 75–6; as natural law, 71; relative poverty, 143 Wealth of Nations (Smith), 6–7, 121, 125–6, 136, 169, 189; abridged versions, 144–6 Weber, Max The Protestant Ethic and the Spirit of Capitalism, 67 welfare systems, 185–6 wellbeing, and inequality, 135, 147 whistle-blowers, 40, 262–3 White, William Allen, 81, 97, 111–12 white-collar crime, Mens Rea Reform Act, 236–44 Whittam Smith, Andreas, 102 Whittamore, Steve, 107–8, 109, 110 wilful ignorance: definition, 21–2, 228–9; difficult to prove, 22; Enron, 21–2; equal culpability thesis, 233–5; financial law, 239–40; first court appearances, 227–8; Grenfell Tower fire, 24–6; ‘ignorance doesn’t excuse’ principle, 231–3, 239–40; News International, 274–5; and reckless ignorance, 235; Rupert Murdoch, 101–2; suspected fraud Ketek trials fraud, 271–2, 274–7 Williams, Zoe, 90 Williamson, Kevin, 83 Wollstonecraft, Mary, 20–1, 163, 317; economic fairness, 122; family background and social norms, 268, 269; legacy, 151–2; on mixed education, 312; ‘Rights of Men’ rebuttal of Burke, 149, 150–1 women: domestic violence, 59; ignorance of co-authorship, 7, 60–1; minority women, 59 Woods, Kent, 285–6, 290–1, 292 workplace health and safety, 217, 218–19, 238 World Bank: disputed assumption of neutrality, 221–2; Employing Workers Indicator, 225; institutional ignorance, 33–4; presidents, 219–20; weakened labour protection, 137, 218–20 Zinn, Howard, 196


pages: 706 words: 202,591

Facebook: The Inside Story by Steven Levy

active measures, Airbnb, Airbus A320, Amazon Mechanical Turk, AOL-Time Warner, Apple's 1984 Super Bowl advert, augmented reality, Ben Horowitz, Benchmark Capital, Big Tech, Black Lives Matter, Blitzscaling, blockchain, Burning Man, business intelligence, Cambridge Analytica, cloud computing, company town, computer vision, crowdsourcing, cryptocurrency, data science, deep learning, disinformation, don't be evil, Donald Trump, Dunbar number, East Village, Edward Snowden, El Camino Real, Elon Musk, end-to-end encryption, fake news, Firefox, Frank Gehry, Geoffrey Hinton, glass ceiling, GPS: selective availability, growth hacking, imposter syndrome, indoor plumbing, information security, Jeff Bezos, John Markoff, Jony Ive, Kevin Kelly, Kickstarter, lock screen, Lyft, machine translation, Mahatma Gandhi, Marc Andreessen, Marc Benioff, Mark Zuckerberg, Max Levchin, Menlo Park, Metcalfe’s law, MITM: man-in-the-middle, move fast and break things, natural language processing, Network effects, Oculus Rift, operational security, PageRank, Paul Buchheit, paypal mafia, Peter Thiel, pets.com, post-work, Ray Kurzweil, recommendation engine, Robert Mercer, Robert Metcalfe, rolodex, Russian election interference, Salesforce, Sam Altman, Sand Hill Road, self-driving car, sexual politics, Sheryl Sandberg, Shoshana Zuboff, side project, Silicon Valley, Silicon Valley startup, skeuomorphism, slashdot, Snapchat, social contagion, social graph, social software, South of Market, San Francisco, Startup school, Steve Ballmer, Steve Bannon, Steve Jobs, Steven Levy, Steven Pinker, surveillance capitalism, tech billionaire, techlash, Tim Cook: Apple, Tragedy of the Commons, web application, WeWork, WikiLeaks, women in the workforce, Y Combinator, Y2K, you are the product

Somehow the gay nerd and the proto–white nationalist bonded. “It felt like we were flirting,” Wylie would later write about their data-wonky intellectual jam sessions. Soon they were hatching a plan for SCL to enter America. Bannon set up a meeting with a wealthy funder of right-wing causes named Robert Mercer. Before making his fortune in hedge funds, Mercer had been a celebrated IBM researcher, so SCL’s promise to change voting behavior resonated with him. He agreed to fund the subsidiary. In December 2013, “Cambridge Analytica” was registered in Delaware. The name came from Bannon, who liked the implication that it was involved with the university.

(Later, a Cambridge Analytica executive would explain that the team was headed to a party in Washington, DC, and the random person left in the office hung up on Davies.) He put the story aside. But in the fall of 2015, Davies came across a Politico article that explained the relationship between SCL and Cambridge Analytica, the connection to Robert Mercer, and that the Ted Cruz presidential campaign was using the data. Davies dug back into the documents and in spare time from his researching duties, put together the story: how Kogan had gathered the data for a research project and then, violating Facebook’s standards, sold it to Cambridge Analytica.

A feature writer and investigative journalist known for deep dives into her topics, often with a participatory twist (like working in an Amazon warehouse), Cadwalladr had become fascinated with what she perceived as the pernicious influence of big tech companies. In 2016, she began investigating Cambridge Analytica. She wrote a series of articles about the company—its involvement in Brexit, its methods, its ties to Robert Mercer and the ultraconservative movement that had backed Trump. And the Facebook data that Kogan had been called out for in December 2015. She lit on Wylie as the key to the story. When she first contacted him in March 2017, he was wary, but eventually he handed over documents that helped inform her stories.


Falter: Has the Human Game Begun to Play Itself Out? by Bill McKibben

"Hurricane Katrina" Superdome, 23andMe, Affordable Care Act / Obamacare, Airbnb, Alan Greenspan, American Legislative Exchange Council, An Inconvenient Truth, Anne Wojcicki, Anthropocene, Apollo 11, artificial general intelligence, Bernie Sanders, Bill Joy: nanobots, biodiversity loss, Burning Man, call centre, Cambridge Analytica, carbon footprint, carbon tax, Charles Lindbergh, clean water, Colonization of Mars, computer vision, CRISPR, David Attenborough, deep learning, DeepMind, degrowth, disinformation, Donald Trump, double helix, driverless car, Easter island, Edward Snowden, Elon Musk, ending welfare as we know it, energy transition, Extinction Rebellion, Flynn Effect, gigafactory, Google Earth, Great Leap Forward, green new deal, Greta Thunberg, Hyperloop, impulse control, income inequality, Intergovernmental Panel on Climate Change (IPCC), James Bridle, Jane Jacobs, Jaron Lanier, Jeff Bezos, job automation, Kim Stanley Robinson, life extension, light touch regulation, Mark Zuckerberg, mass immigration, megacity, Menlo Park, moral hazard, Naomi Klein, Neil Armstrong, Nelson Mandela, Nick Bostrom, obamacare, ocean acidification, off grid, oil shale / tar sands, paperclip maximiser, Paris climate accords, pattern recognition, Peter Thiel, plutocrats, profit motive, Ralph Waldo Emerson, Ray Kurzweil, Robert Mercer, Ronald Reagan, Sam Altman, San Francisco homelessness, self-driving car, Silicon Valley, Silicon Valley startup, smart meter, Snapchat, stem cell, Stephen Hawking, Steve Jobs, Steve Wozniak, Steven Pinker, strong AI, supervolcano, tech baron, tech billionaire, technoutopianism, TED Talk, The Wealth of Nations by Adam Smith, traffic fines, Tragedy of the Commons, Travis Kalanick, Tyler Cowen, urban sprawl, Virgin Galactic, Watson beat the top human players on Jeopardy!, Y Combinator, Y2K, yield curve

But as we now know, Trump was simply bringing something new to the game: not clever messaging, but brazen lying. And arriving in Washington with no existing ideology except feeding his narcissism and enriching his family, Trump proved the perfect president finally to enact the full government-hating agenda. Robert Mercer, who’d funded not only Trump’s campaign but also Cambridge Analytica, the source of so much Facebook skullduggery, was a key figure—and a classic Randian. As one colleague explained, “Bob believes that human beings have no inherent value other than how much money they make. A cat has value, he’s said, because it provides pleasure to humans.

Koch, Mary Koch, William “Bill” Kodas, Michael Kona Korea Krueger, Alan Kumkum Bhagya (soap opera) Kurzweil, Fredric Kurzweil, Ray Kyoto Protocol labor law labor unions Lahore, Pakistan laissez-faire Lanier, Jaron Las Vegas lead poisoning Leap Manifesto Lear, Norman Leary, Timothy Lee, Kai-fu LeFevre, Robert leukemia leverage Lewis, Seko Serge Lexington, Battle of libertarianism Libertarian Party life expectancy lightning strikes limestone limits Limits to Growth, The (Meadows) Lindbergh, Charles lobster fisheries Locklear, Samuel Lomé, Togo London Los Angeles Los Angeles Times Louisiana Lovelock, James Lowndes County, Alabama Luntz, Frank Lyme disease Machine Intelligence Research Institute MacLean, Nancy Maduro malaria Mallory, George Maltese Falcon (yacht) Mann, Michael Manson, Charles manufacturing MAOA gene variant marine species Maris, Bill markets marlin Mars Marsh, George Perkins Marshall Islands mass extinctions Matchright maturity Mauryan Empire Mayans Mayer, Jane McArthur Forest Fire Danger Index McCain, John Medicaid Medicare Megafire (Kodas) Mehlman, Maxwell Mekong Delta meltwater pulse 1A Mercer, Robert Merkle, Ralph Merritt Island Wildlife Refuge methane Mexico Miami Beach Microsoft migration Mill, John Stuart Miller, Dean Milner, Yuri Milosevic, Slobodan Minsky, Marvin Mises, Ludwig von Mississippi Delta MIT Technology Review Mongolia Monsanto Montgomery Bus Boycott Mont Pelerin movement Montreal Montreal Protocol More, Max mortality Moses, Robert Mount Kenya MSTN gene Muir, John Mumbai Murdoch, Rupert Musk, Elon Nabokov, Vladimir nanobot blood cells National Academy of Medicine National Academy of Sciences National Aeronautics and Space Administration (NASA) National Cancer Institute National Coal Association National Energy Policy Act (proposed) National Geographic National Governors Association National Journal National Oceanic and Atmospheric Administration (NOAA) national parks and monuments Native Americans natural gas Nature Nawabshah, Pakistan Nazi Germany Nectome neoliberalism Neolithic period Nepal Netherlands New Deal NewsCorp New York New Yorker New York Times Magazine Nietzsche, Friedrich Niviana, Aka Nixon, Richard Nokia nonviolence North America North American Free Trade Agreement (NAFTA) North Carolina North Korea Norway Novartis nuclear power Nuclear Test Ban Treaty nuclear weapons nutrition Obama, Barack Obamacare Objectivist oceans.


pages: 349 words: 98,868

Nervous States: Democracy and the Decline of Reason by William Davies

active measures, Affordable Care Act / Obamacare, Amazon Web Services, Anthropocene, bank run, banking crisis, basic income, Black Lives Matter, Brexit referendum, business cycle, Cambridge Analytica, Capital in the Twenty-First Century by Thomas Piketty, citizen journalism, Climategate, Climatic Research Unit, Colonization of Mars, continuation of politics by other means, creative destruction, credit crunch, data science, decarbonisation, deep learning, DeepMind, deindustrialization, digital divide, discovery of penicillin, Dominic Cummings, Donald Trump, drone strike, Elon Musk, failed state, fake news, Filter Bubble, first-past-the-post, Frank Gehry, gig economy, government statistician, housing crisis, income inequality, Isaac Newton, Jeff Bezos, Jeremy Corbyn, Johannes Kepler, Joseph Schumpeter, knowledge economy, loss aversion, low skilled workers, Mahatma Gandhi, Mark Zuckerberg, mass immigration, meta-analysis, Mont Pelerin Society, mutually assured destruction, Northern Rock, obamacare, Occupy movement, opioid epidemic / opioid crisis, Paris climate accords, pattern recognition, Peace of Westphalia, Peter Thiel, Philip Mirowski, planetary scale, post-industrial society, post-truth, quantitative easing, RAND corporation, Ray Kurzweil, Richard Florida, road to serfdom, Robert Mercer, Ronald Reagan, sentiment analysis, Silicon Valley, Silicon Valley billionaire, Silicon Valley startup, smart cities, Social Justice Warrior, statistical model, Steve Bannon, Steve Jobs, tacit knowledge, the scientific method, Turing machine, Uber for X, universal basic income, University of East Anglia, Valery Gerasimov, W. E. B. Du Bois, We are the 99%, WikiLeaks, women in the workforce, zero-sum game

Granted this, it would be unreasonable to deny that a society is likely to get a better elite if ascent is not limited to one generation, if individuals are not deliberately made to start from the same level.27 In our new age of extreme personal wealth, billionaire owners of private companies such as the Koch brothers or Robert Mercer, the hedge-fund billionaire who has backed various populist and alt-right campaigns including Breitbart media, have huge political autonomy, without needing to be public about how they’re using it. Facebook and Google are now listed on the stock market, yet their founders retain majority shareholding rights.

., Martin Luther, 21, 224 knowledge economy, 84, 85, 88, 151–2, 217 known knowns, 132, 138 Koch, Charles and David, 154, 164, 174 Korean War (1950–53), 178 Kraepelin, Emil, 139 Kurzweil, Ray, 183–4 Labour Party, 5, 6, 65, 80, 81, 221 Lagarde, Christine, 64 Le Bon, Gustave, 8–12, 13, 15, 16, 20, 24, 25, 38 Le Pen, Marine, 27, 79, 87, 92, 101–2 Leadbeater, Charles, 84 Leeds, West Yorkshire, 85 Leicester, Leicestershire, 85 Leviathan (Hobbes), 34, 39, 45 liberal elites, 20, 58, 88, 89, 161 libertarianism, 15, 151, 154, 158, 164, 173, 196, 209, 226 Liberty Fund, 158 Libya, 143 lie-detection technology, 136 life expectancy, 62, 68–71, 72, 92, 100–101, 115, 224 Lindemann, Frederick Alexander, 1st Viscount Cherwell, 138 Lloyds Bank, 29 London, England bills of mortality, 68–71, 75, 79–80, 81, 89, 127 Blitz (1940–41), 119, 143, 180 EU referendum (2016), 85 Great Fire (1666), 67 Grenfell Tower fire (2017), 10 and gross domestic product (GDP), 77, 78 housing crisis, 84 insurance sector, 59 knowledge economy, 84 life expectancy, 100 newspapers, early, 48 Oxford Circus terror scare (2017), ix–x, xiii, 41 plagues, 67–71, 75, 79–80, 81, 89, 127 Unite for Europe march (2017), 23 London School of Economics (LSE), 160 loss aversion, 145 Louis XIV, King of France, 73, 127 Louisiana, United States, 151, 221 Ludwig von Mises Institute, 154 MacLean, Nancy, 158 Macron, Emmanuel, 33 mainstream media, 197 “Make America Great Again,” 76, 145 Manchester, England, 85 Mann, Geoff, 214 maps, 182 March For Our Lives (2018), 21 March for Science (2017), 23–5, 27, 28, 210, 211 marketing, 14, 139–41, 143, 148, 169 Mars, 175, 226 Marxism, 163 Massachusetts Institute of Technology (MIT), 179 Mayer, Jane, 158 McCarthy, Joseph, 137 McGill Pain Questionnaire, 104 McKibben, William “Bill,” 213 Megaface, 188–9 memes, 15, 194 Menger, Carl, 154 mental illness, 103, 107–17, 139 mercenaries, 126 Mercer, Robert, 174, 175 Mexico, 145 Million-Man March (1995), 4 mind-reading technology, 136 see also telepathy Mirowski, Philip, 158 von Mises, Ludwig, 154–63, 166, 172, 173 Missing Migrants Project, 225 mobilization, 5, 7, 126–31 and Corbyn, 81 and elections, 81, 124 and experts, 27–8 and Internet, 15 and Le Bon’s crowd psychology, 11, 12, 16, 20 and loss, 145 and Napoleonic Wars, xv, 127–30, 141, 144 and Occupy movement, 5 and populism, 16, 22, 60 and violence, opposition to, 21 Moniteur Universel, Le, 142 monopoly on violence, 42 Mont Pelerin Society, 163, 164 moral emotion, 21 morphine, 105 multiculturalism, 84 Murs, Oliver “Olly,” ix Musk, Elon, 175, 176, 178, 183, 226 Nanchang, Jiangxi, 13 Napoleonic Wars (1803–15), 126–30 chappe system, 129, 182 and conscription, 87, 126–7, 129 and disruption, 170–71, 173, 174, 175, 226 and great leader ideal, 146–8 and intelligence, 134 and mobilization, xv, 126–30, 141, 144 and nationalism, 87, 128, 129, 144, 183, 211 and propaganda, 142 Russia, invasion of (1812), 128, 133 Spain, invasion of (1808), 128 National Aeronautics and Space Administration (NASA), 23, 175 National Audit Office (NAO), 29–30 national citizenship, 71 National Defense Research Committee, 180 National Health Service (NHS), 30, 93 National Park Service, 4 National Security Agency (NSA), 152 national sovereignty, 34, 53 nationalism, 87, 141, 210–12 and conservatism, 144 and disempowerment, 118–19 and elites, 22–3, 60–61, 145 ethnic, 15 and health, 92, 211–12, 224 and imagined communities, 87 and inequality, 78 and loss, 145 and markets, 167 and promises, 221 and resentment, 145, 197, 198 and war, 7, 20–21, 118–19, 143–6, 210–11 nativism, 61 natural philosophy, 35–6 nature, 86 see also environment Nazi Germany (1933–45), 137, 138, 154 Netherlands, 48, 56, 129 Neurable, 176 neural networking, 216 Neuralink, 176 neurasthenia, 139 Neurath, Otto, 153–4, 157, 160 neurochemistry, 108, 111, 112 neuroimaging, 176–8, 181 Nevada, United States, 194 new atheism, 209 New Orleans, Louisiana, 151 New Right, 164 New York, United States and climate change, 205 and gross domestic product (GDP), 78 housing crisis, 84 JFK Airport terror scare (2016), x, xiii, 41 knowledge economy, 84 September 11 attacks (2001), 17, 18 New York Times, 3, 27, 85 newspapers, 48, 71 Newton, Isaac, 35 Nietzsche, Friedrich, 217 Nixon, Robert, 206 no-platforming, 22, 208 Nobel Prize, 158–9 non-combatants, 43, 143, 204 non-violence, 224 North Atlantic Treaty Organization (NATO), 123, 145, 214 North Carolina, United States, 84 Northern Ireland, 43, 85 Northern League, 61 Northern Rock, 29 Norwich, Norfolk, 85 nostalgia, xiv, 143, 145, 210, 223 “Not in my name,” 27 nuclear weapons, 132, 135, 137, 180, 183, 192, 196, 204 nudge techniques, 13 Obama, Barack, 3, 24, 76, 77, 79, 158, 172 Obamacare, 172 objectivity, xiv, 13, 75, 136, 223 and crowd-based politics, 5, 7, 24–5 and death, 94 and Descartes, 37 and experts, trust in, 28, 32, 33, 51, 53, 64, 86, 89 and Hayek, 163, 164, 170 and markets, 169, 170 and photography, 8 and Scientific Revolution, 48, 49 and statistics, 72, 74, 75, 82, 88 and telepathic communication, 179 and war, 58, 125, 134, 135, 136, 146 Occupy movement, 5, 10, 24, 61 Oedipus complex, 109 Office for National Statistics, 63, 133 Ohio, United States, 116 oil crisis (1973), 166 “On Computable Numbers” (Turing), 181 On War (Clausewitz), 130 Open Society and Its Enemies, The (Popper), 171 opiates, 105, 116, 172–3 opinion polling, 65, 80–81, 191 Orbán, Viktor, 87, 146 Organisation for Economic Co-operation and Development (OECD), 72 Oxford, Oxfordshire, 85 Oxford Circus terror scare (2017), ix–x, xiii, 41 Oxford University, 56, 151 OxyContin, 105, 116 pacifism, 8, 20, 44, 151 pain, 102–19, 172–3, 224 see also chronic pain painkillers, 104, 105, 116, 172–3 Palantir, 151, 152, 175, 190 parabiosis, 149 Paris climate accord (2015), 205, 207 Paris Commune (1871), 8 Parkland attack (2018), 21 Patriot Act (2001), 137 Paul, Ronald, 154 PayPal, 149 Peace of Westphalia (1648), 34, 53 peer reviewing, 48, 139, 195, 208 penicillin, 94 Pentagon, 130, 132, 135, 136, 214, 216 pesticides, 205 Petty, William, 55–9, 67, 73, 85, 167 pharmacology, 142 Pielke Jr., Roger, 24, 25 Piketty, Thomas, 74 Pinker, Stephen, 207 plagues, 56, 67–71, 75, 79–80, 81, 89, 95 pleasure principle, 70, 109, 110, 224 pneumonia, 37, 67 Podemos, 5, 202 Poland, 20, 34, 60 Polanyi, Michael, 163 political anatomy, 57 Political Arithmetick (Petty), 58, 59 political correctness, 20, 27, 145 Popper, Karl, 163, 171 populism xvii, 211–12, 214, 220, 225–6 and central banks, 33 and crowd-based politics, 12 and democracy, 202 and elites/experts, 26, 33, 50, 152, 197, 210, 215 and empathy, 118 and health, 99, 101–2, 224–5 and immediate action, 216 in Kansas (1880s), 220 and markets, 167 and private companies, 174 and promises, 221 and resentment, 145 and statistics, 90 and unemployment, 88 and war, 148, 212 Porter, Michael, 84 post-traumatic stress disorder (PTSD), 111–14, 117, 209 post-truth, 167, 224 Potsdam Conference (1945), 138 power vs. violence, 19, 219 predictive policing, 151 presidential election, US (2016), xiv and climate change, 214 and data, 190 and education, 85 and free trade, 79 and health, 92, 99 and immigration, 79, 145 and inequality, 76–7 and Internet, 190, 197, 199 “Make America Great Again,” 76, 145 and opinion polling, 65, 80 and promises, 221 and relative deprivation, 88 and Russia, 199 and statistics, 63 and Yellen, 33 prisoners of war, 43 promises, 25, 31, 39–42, 45–7, 51, 52, 217–18, 221–2 Propaganda (Bernays), 14–15 propaganda, 8, 14–16, 83, 124–5, 141, 142, 143 property rights, 158, 167 Protestantism, 34, 35, 45, 215 Prussia (1525–1947), 8, 127–30, 133–4, 135, 142 psychiatry, 107, 139 psychoanalysis, 107, 139 Psychology of Crowds, The (Le Bon), 9–12, 13, 15, 16, 20, 24, 25 psychosomatic, 103 public-spending cuts, 100–101 punishment, 90, 92–3, 94, 95, 108 Purdue, 105 Putin, Vladimir, 145, 183 al-Qaeda, 136 quality of life, 74, 104 quantitative easing, 31–2, 222 quants, 190 radical statistics, 74 RAND Corporation, 183 RBS, 29 Reagan, Ronald, 15, 77, 154, 160, 163, 166 real-time knowledge, xvi, 112, 131, 134, 153, 154, 165–70 Reason Foundation, 158 Red Vienna, 154, 155 Rees-Mogg, Jacob, 33, 61 refugee crisis (2015–), 60, 225 relative deprivation, 88 representative democracy, 7, 12, 14–15, 25–8, 61, 202 Republican Party, 77, 79, 85, 154, 160, 163, 166, 172 research and development (R&D), 133 Research Triangle, North Carolina, 84 resentment, 5, 226 of elites/experts, 32, 52, 61, 86, 88–9, 161, 186, 201 and nationalism/populism, 5, 144–6, 148, 197, 198 and pain, 94 Ridley, Matt, 209 right to remain silent, 44 Road to Serfdom, The (Hayek), 160, 166 Robinson, Tommy, ix Roosevelt, Franklin Delano, 52 Royal Exchange, 67 Royal Society, 48–52, 56, 68, 86, 133, 137, 186, 208, 218 Rumsfeld, Donald, 132 Russian Empire (1721–1917), 128, 133 Russian Federation (1991–) and artificial intelligence, 183 Gerasimov Doctrine, 43, 123, 125, 126 and information war, 196 life expectancy, 100, 115 and national humiliation, 145 Skripal poisoning (2018), 43 and social media, 15, 18, 199 troll farms, 199 Russian Revolution (1917), 155 Russian SFSR (1917–91), 132, 133, 135–8, 155, 177, 180, 182–3 safe spaces, 22, 208 Sands, Robert “Bobby,” 43 Saxony, 90 scarlet fever, 67 Scarry, Elaine, 102–3 scenting, 135, 180 Schneier, Bruce, 185 Schumpeter, Joseph, 156–7, 162 Scientific Revolution, 48–52, 62, 66, 95, 204, 207, 218 scientist, coining of term, 133 SCL, 175 Scotland, 64, 85, 172 search engines, xvi Second World War, see World War II securitization of loans, 218 seismology, 135 self-employment, 82 self-esteem, 88–90, 175, 212 self-harm, 44, 114–15, 117, 146, 225 self-help, 107 self-interest, 26, 41, 44, 61, 114, 141, 146 Semi-Automatic Ground Environment (SAGE), 180, 182, 200 sentiment analysis, xiii, 12–13, 140, 188 September 11 attacks (2001), 17, 18 shell shock, 109–10 Shrecker, Ted, 226 Silicon Fen, Cambridgeshire, 84 Silicon Valley, California, xvi, 219 and data, 55, 151, 185–93, 199–201 and disruption, 149–51, 175, 226 and entrepreneurship, 149–51 and fascism, 203 and immortality, 149, 183–4, 224, 226 and monopolies, 174, 220 and singularity, 183–4 and telepathy, 176–8, 181, 185, 186, 221 and weaponization, 18, 219 singularity, 184 Siri, 187 Skripal poisoning (2018), 43 slavery, 59, 224 smallpox, 67 smart cities, 190, 199 smartphone addiction, 112, 186–7 snowflakes, 22, 113 social indicators, 74 social justice warriors (SJWs), 131 social media and crowd psychology, 6 emotional artificial intelligence, 12–13, 140–41 and engagement, 7 filter bubbles, 66 and propaganda, 15, 18, 81, 124 and PTSD, 113 and sentiment analysis, 12 trolls, 18, 20–22, 27, 40, 123, 146, 148, 194–8, 199, 209 weaponization of, 18, 19, 22, 194–5 socialism, 8, 20, 154–6, 158, 160 calculation debate, 154–6, 158, 160 Socialism (Mises), 160 Society for Freedom in Science, 163 South Africa, 103 sovereignty, 34, 53 Soviet Russia (1917–91), 132, 133, 135–8, 177, 180, 182–3 Spain, 5, 34, 84, 128, 202 speed of knowledge, xvi, 112, 124, 131, 134, 136, 153, 154, 165–70 Spicer, Sean, 3, 5 spy planes, 136, 152 Stalin, Joseph, 138 Stanford University, 179 statactivism, 74 statistics, 62–91, 161, 186 status, 88–90 Stoermer, Eugene, 206 strong man leaders, 16 suicide, 100, 101, 115 suicide bombing, 44, 146 superbugs, 205 surveillance, 185–93, 219 Sweden, 34 Switzerland, 164 Sydenham, Thomas, 96 Syriza, 5 tacit knowledge, 162 talking cure, 107 taxation, 158 Tea Party, 32, 50, 61, 221 technocracy, 53–8, 59, 60, 61, 78, 87, 89, 90, 211 teenage girls, 113, 114 telepathy, 39, 176–9, 181, 185, 186 terrorism, 17–18, 151, 185 Charlottesville attack (2017), 20 emergency powers, 42 JFK Airport terror scare (2016), x, xiii, 41 Oxford Circus terror scare (2017), ix–x, xiii, 41 September 11 attacks (2001), 17, 18 suicide bombing, 44, 146 vehicle-ramming attacks, 17 war on terror, 131, 136, 196 Thames Valley, England, 85 Thatcher, Margaret, 154, 160, 163, 166 Thiel, Peter, 26, 149–51, 153, 156, 174, 190 Thirty Years War (1618–48), 34, 45, 53, 126 Tokyo, Japan, x torture, 92–3 total wars, 129, 142–3 Treaty of Westphalia (1648), 34, 53 trends, xvi, 168 trigger warnings, 22, 113 trolls, 18, 20–22, 27, 40, 123, 146, 148, 194–8, 199, 209 Trump, Donald, xiv and Bannon, 21, 60–61 and climate change, 207 and education, 85 election campaign (2016), see under presidential election, US and free trade, 79 and health, 92, 99 and immigration, 145 inauguration (2017), 3–5, 6, 9, 10 and inequality, 76–7 “Make America Great Again,” 76, 145 and March for Science (2017), 23, 24, 210 and media, 27 and opinion polling, 65, 80 and Paris climate accord, 207 and promises, 221 and relative deprivation, 88 and statistics, 63 and Yellen, 33 Tsipras, Alexis, 5 Turing, Alan, 181, 183 Twitter and Corbyn’s rallies, 6 and JFK Airport terror scare (2016), x and Oxford Circus terror scare (2017), ix–x and Russia, 18 and sentiment analysis, 188 and trends, xvi and trolls, 194, 195 Uber, 49, 185, 186, 187, 188, 191, 192 UK Independence Party, 65, 92, 202 underemployment, 82 unemployment, 61, 62, 72, 78, 81–3, 87, 88, 203 United Kingdom austerity, 100 Bank of England, 32, 33, 64 Blitz (1940–41), 119, 143, 180 Brexit (2016–), see under Brexit Cameron government (2010–16), 33, 73, 100 Center for Policy Studies, 164 Civil Service, 33 climate-gate (2009), 195 Corbyn’s rallies, 5, 6 Dunkirk evacuation (1940), 119 education, 85 financial crisis (2007–9), 29–32, 100 first past the post, 13 general election (2015), 80, 81 general election (2017), 6, 65, 80, 81, 221 Grenfell Tower fire (2017), 10 gross domestic product (GDP), 77, 79 immigration, 63, 65 Irish hunger strike (1981), 43 life expectancy, 100 National Audit Office (NAO), 29 National Health Service (NHS), 30, 93 Office for National Statistics, 63, 133 and opiates, 105 Oxford Circus terror scare (2017), ix–x, xiii, 41 and pain, 102, 105 Palantir, 151 Potsdam Conference (1945), 138 quantitative easing, 31–2 Royal Society, 138 Scottish independence referendum (2014), 64 Skripal poisoning (2018), 43 Society for Freedom in Science, 163 Thatcher government (1979–90), 154, 160, 163, 166 and torture, 92 Treasury, 61, 64 unemployment, 83 Unite for Europe march (2017), 23 World War II (1939–45), 114, 119, 138, 143, 180 see also England United Nations, 72, 222 United States Bayh–Dole Act (1980), 152 Black Lives Matter, 10, 225 BP oil spill (2010), 89 Bush Jr. administration (2001–9), 77, 136 Bush Sr administration (1989–93), 77 Bureau of Labor, 74 Central Intelligence Agency (CIA), 3, 136, 151, 199 Charlottesville attack (2017), 20 Civil War (1861–5), 105, 142 and climate change, 207, 214 Clinton administration (1993–2001), 77 Cold War, see Cold War Defense Advanced Research Projects Agency (DARPA), 176, 178 Defense Intelligence Agency, 177 drug abuse, 43, 100, 105, 115–16, 131, 172–3 education, 85 Federal Bureau of Investigation (FBI), 137 Federal Reserve, 33 Fifth Amendment (1789), 44 financial crisis (2007–9), 31–2, 82, 158 first past the post, 13 Government Accountability Office, 29 gross domestic product (GDP), 75–7, 82 health, 92, 99–100, 101, 103, 105, 107, 115–16, 158, 172–3 Heritage Foundation, 164, 214 Iraq War (2003–11), 74, 132 JFK Airport terror scare (2016), x, xiii, 41 Kansas populists (1880s), 220 libertarianism, 15, 151, 154, 158, 164, 173 life expectancy, 100, 101 March For Our Lives (2018), 21 March for Science (2017), 23–5, 27, 28, 210 McCarthyism (1947–56), 137 Million-Man March (1995), 4 National Aeronautics and Space Administration (NASA), 23, 175 National Defense Research Committee, 180 National Park Service, 4 National Security Agency (NSA), 152 Obama administration (2009–17), 3, 24, 76, 77, 79, 158 Occupy Wall Street (2011), 5, 10, 61 and opiates, 105, 172–3 and pain, 103, 105, 107, 172–3 Palantir, 151, 152, 175, 190 Paris climate accord (2015), 205, 207 Parkland attack (2018), 21 Patriot Act (2001), 137 Pentagon, 130, 132, 135, 136, 214, 216 presidential election (2016), see under presidential election, US psychiatry, 107, 111 quantitative easing, 31–2 Reagan administration (1981–9), 15, 77, 154, 160, 163, 166 Rumsfeld’s “unknown unknowns” speech (2002), 132 Semi-Automatic Ground Environment (SAGE), 180, 182, 200 September 11 attacks (2001), 17, 18 Tea Party, 32, 50, 61, 221 and torture, 93 Trump administration (2017–), see under Trump, Donald unemployment, 83 Vietnam War (1955–75), 111, 130, 136, 138, 143, 205 World War I (1914–18), 137 World War II (1939–45), 137, 180 universal basic income, 221 universities, 151–2, 164, 169–70 University of Cambridge, 84, 151 University of Chicago, 160 University of East Anglia, 195 University of Oxford, 56, 151 University of Vienna, 160 University of Washington, 188 unknown knowns, 132, 133, 136, 138, 141, 192, 212 unknown unknowns, 132, 133, 138 “Use of Knowledge in Society, The” (Hayek), 161 V2 flying bomb, 137 vaccines, 23, 95 de Vauban, Sébastien Le Prestre, Marquis de Vauban, 73 vehicle-ramming attacks, 17 Vesalius, Andreas, 96 Vienna, Austria, 153–5, 159 Vietnam War (1955–75), 111, 130, 136, 138, 143, 205 violence vs. power, 19, 219 viral marketing, 12 virtual reality, 183 virtue signaling, 194 voice recognition, 187 Vote Leave, 50, 93 Wainright, Joel, 214 Wales, 77, 90 Wall Street, New York, 33, 190 War College, Berlin, 128 “War Economy” (Neurath), 153–4 war on drugs, 43, 131 war on terror, 131, 136, 196 Watts, Jay, 115 weaponization, 18–20, 22, 26, 75, 118, 123, 194, 219, 223 weapons of mass destruction, 132 wearable technology, 173 weather control, 204 “What Is An Emotion?”


pages: 372 words: 100,947

An Ugly Truth: Inside Facebook's Battle for Domination by Sheera Frenkel, Cecilia Kang

"World Economic Forum" Davos, 2021 United States Capitol attack, affirmative action, augmented reality, autonomous vehicles, Ben Horowitz, Bernie Sanders, Big Tech, Black Lives Matter, blockchain, Cambridge Analytica, clean water, coronavirus, COVID-19, data science, disinformation, don't be evil, Donald Trump, Edward Snowden, end-to-end encryption, fake news, George Floyd, global pandemic, green new deal, hockey-stick growth, Ian Bogost, illegal immigration, immigration reform, independent contractor, information security, Jeff Bezos, Kevin Roose, Marc Andreessen, Marc Benioff, Mark Zuckerberg, Menlo Park, natural language processing, offshore financial centre, Parler "social media", Peter Thiel, QAnon, RAND corporation, ride hailing / ride sharing, Robert Mercer, Russian election interference, Salesforce, Sam Altman, Saturday Night Live, Sheryl Sandberg, Shoshana Zuboff, Silicon Valley, Snapchat, social web, Steve Bannon, Steve Jobs, Steven Levy, subscription business, surveillance capitalism, TechCrunch disrupt, TikTok, Travis Kalanick, WikiLeaks

Chapter 8 Delete Facebook On March 17, 2018, the New York Times and the Observer of London broke front-page stories about a company called Cambridge Analytica that had obtained profile information, records of likes and shares, photo and location tags, and the lists of friends of tens of millions of Facebook users. A whistleblower within the UK-based political consulting firm had brought the story to the news organizations with a stunning claim that the firm, funded by Trump supporter Robert Mercer and led by Trump’s senior adviser, Stephen K. Bannon, had created a new level of political ad targeting using Facebook data on personality traits and political values. But the jaw-dropping detail was that Cambridge Analytica had harvested the Facebook data without users’ permission. “The breach allowed the company to exploit the private social media activity of a huge swath of the American electorate, developing techniques that underpinned its work on President Trump’s campaign in 2016,” the New York Times reported.1 The Observer wrote that the “unprecedented data harvesting, and the use to which it was put, raises urgent new questions about Facebook’s role in targeting voters in the US presidential election.”2 It was the latest breach of trust in Facebook’s repeated pattern of data privacy abuses.

See freedom of speech issues Hemphill, Scott, 229–232, 261 Hertz, Jessica, 297 Hoefflinger, Mike, 55 Holocaust deniers, Facebook policy and, 205–207, 276–278, 281 Holt, Lester, 257–258 Horowitz, Ben, 191–192 Hughes, Chris New York Times op-ed, 219–222 on origins of Facebook, 253 Wu and, 231–232 Zuckerberg’s “pivot to privacy” and, 224–227 Ifill, Sherrilyn, 255 Independent Investigative Mechanism for Myanmar, of UN, 186 Information Technology Industry Council, 165 Infowars, 204 Instagram, 7, 8, 166, 193–194, 221, 222, 253, 259, 295 Facebook’s “pivot to privacy” and, 222–224 Federal Trade Commission (FTC) and, 68 interoperability of messaging apps and, 227–228 Russian Internet Research Agency and, 133 Trump and, 267, 288–290, 292 Wu and Hemphill’s evaluation of Facebook’s acquisition of, 230–231 Zuckerberg’s broken commitment to founders of, 2, 194, 227–229 International Association of Privacy Professionals, 64–65 International Criminal Court, 185–186 Internet Association, 241 Internet Research Agency (IRA), of Russia, 130–134, 137, 143, 144–145 Internet.org, 175–177 iSEC Partners, 101 James, Letitia, 1–2, 3 “JJDIDTIEBUCKLE” (leadership principle), 246 Jobs, Steve, 48, 51, 174 Jones, Alex, 82, 204–205, 206 Kalanick, Travis, 207 Kang-Xing Jin, 51 Kaplan, Joel, 197, 241, 260, 276, 278 Biden administration and, 297–298 Cambridge Analytica and, 150 election of 2016 and, 81, 108–109, 111–112, 123, 125 Kavanaugh hearings and, 200–203 manipulated video of Pelosi and, 236, 238 personality of, 14 political contributions and, 164–165 Sandberg and, 14, 87 Trump administration and, 161, 243–247 Trump and COVID-19, 267–268, 269 Trump’s anti-Muslim rhetoric and hate speech issues, 11–15 Kaplan, Laura Cox, 200 Kavanaugh, Ashley Estes, 200 Kavanaugh, Brett, 200–203 Kaye, David, 174–175 Kellogg, Hansen law firm, 295 Kendall, Tim, 36–37, 51 Kennedy, John, 153 Kenosha Guard, 279–281 Kimmel, Jimmy, 166 King, Bernice, 254, 259 Kirkpatrick, David, 114–115 Klobuchar, Amy, 153 Kogan, Aleksandr, 152–153, 155 Koum, Jan, 194, 229 Kraff, Brian, 41 Krieger, Mike, 228–229 Kushner, Jared, 15, 243–244, 256 Kustomer, acquired by Facebook, 299 Le Pen, Marine, 118 Lean In (Sandberg), 79, 127, 157–158 Leibowitz, Jonathan, 67, 154, 199 Leone, Isabella, 131 Lewandowski, Corey, 112–113 Libra (blockchain currency), 241–242, 256–257, 300 LinkedIn, 175 London, Eric, 155 Losse, Katherine, 49, 50, 124 Lynton, Michael, 56 Ma, Olivia, 26 Mac, Ryan, 272 Macron, Emmanuel, 118, 124–125, 219, 221, 237 Martin, Jenny Beth, 81 Martin, Kevin, 80, 112 Mauer, Greg, 80, 112, 140 Mayer, Marissa, 102–103 McKinsey and Company, 41, 50 McNamee, Roger, 44, 232 Mercer, Robert, 149 MeToo movement, 150, 200–201, 203 Microsoft, 31, 165, 174, 175, 241 advertising and, 51, 53, 54 Modi, Narenda, 106 Montgomery, Kathryn, 58, 60 Moran, Ned, 95–98, 100–101, 105, 129–132, 147 Moskovitz, Dustin, 31 Mossberg, Walt, 43 Mosseri, Adam, 114, 228, 261 Moveon.org, 59 Mubarak, Hosni, 157 Mueller, Robert, 147 Murphy, Laura, 248, 249 Myanmar, hate speech against Rohingya and, 85, 169–173, 176, 178–182, 185–187, 293–294 Narendra, Divya, 21 “net neutrality,” 230 Netscape, 25, 52 New Republic, The, 287 New York Times, 88, 272, 285 Cambridge Analytica and, 149 Chester on behavioral advertising and, 59 Clegg’s op-ed in, 240 Federal Trade Commission (FTC) and, 1 Hughes’ op-ed in, 219–222 Myanmar and, 186 Russian election interference and, 130, 215 New Yorker, The, 66 Newsom, Gavin, 266 Next One Billion project, of Facebook, 176–177 Nielsen, 56 Nuland, William, 147 Nuñez, Michael, 70–79 Oath Keepers, 287–288 Obama, Barack and administration of, 11, 67, 82, 118, 121, 138, 146, 184, 230, 236, 248, 251, 252, 255 Observer, 149 Ocasio-Cortez, Alexandria, 257 Oculus VR headset, 80, 81, 190 O’Donnell, Nora, 157–159 Olivan, Javier, 194, 195, 260 Onavo, 195–196, 260 O’Neill, Catlin, 140, 236, 297 Only the Paranoid Survive (Grove), 192 Open Society Foundation, 108 Option B (Sandberg), 79, 258 Overstock, 59–60 Page, Larry, 43, 44, 65, 192 Palihapitiya, Chamath, 51 Parakilas, Sandy, 152, 164 Parikh, Jay, 9, 10 Parker, Sean, 26, 28, 44, 221 Parscale, Brad, 15, 247 Pearlman, Leah, 62–63 Pelosi, Nancy, 233–234, 297 Facebook and manipulated video of, 234–240 Pence, Mike, 290 Philippines, 85, 106, 177, 291 Phillips Exeter Academy, 19–20 Pichai, Sundar, 198 “Pizzagate,” 278 Podesta, John, 100 politics, and Facebook Biden administration and, 286, 296–298 Clegg’s policy of not fact-checking political ads, 249–252 Facebook’s PAC for political contributions, 164–165 liberal favoritism at Facebook, 12–13, 74–75, 78 political ads on Facebook, 212–214 Trump administration and Facebook executives, 243–247 see also election of 2016; election of 2020; freedom of speech issues Price, Bill, 89–92 Pritchett, Lant, 41 Proceedings of the National Academy of Sciences, 182–183 Proud Boys, 288 Putin, Vladimir, 121, 123 QAnon, 278–279, 281 Red-State Secession group, 288 Reich, Robert, 226 Reynolds, Tom, 141, 145 Rice, Brian, 141 Robinson, Rashad, 249, 251, 276–277 Rose, Dan, 44, 45, 46, 51 Rosen, Guy, 195, 260, 285 Rosensweig, Dan, 43–44 Rubio, Marco, 161 Russian disinformation, on Facebook platform, 3, 282 Congressional interest in, 127–128, 133–134, 139–145 Facebook board of director’s interest in, 134–137 Facebook employees and, 190 Facebook public relations team and, 208–215 Facebook’s security team’s investigation of, 117–127 French election of 2017 and, 118, 121 Russian Internet Research Agency and, 130–134, 137, 143, 144–145 Sandberg and, 215–217 U.S. election campaign of 2016 and, 95–101, 105–109, 124–125, 248 Zuckerberg and, 196, 204, 215–217 Ryan, Paul, 78 Sai Sitt Thway Aung, 169 Sandberg, Michelle, 43, 44 Sandberg, Sheryl backlash to Lean In and, 157–158 behavioral advertising and data collecting, at Facebook, 2–3, 45–46, 51–56, 59, 60–63, 67, 87, 225 Biden administration and, 297 books by, 79, 127, 157–158, 258 Cambridge Analytica and, 153, 154–156, 159, 160–161 Capital Building storming in January 2021 and, 286–287 Congress and, 153, 170–171, 197–200 Couric’s interview of, 258–260 cyber security and, 97–98, 210 diversity and gender equity and, 50, 202–203, 273 education and professional positions before Facebook, 39–43, 46–47, 50, 52–53 election of 2016 and conservatives, 82–83 election security and, 210 Facebook and privacy, 67 Facebook’s earnings call in 2021 and, 298–299 Federal Trade Commission (FTC) and, 45, 295, 296 Goldberg’s death and, 79–81, 233 hate speech issues and, 11–14, 275–277 Hillary Clinton and, 79, 111–112, 243–244 Instagram and WhatsApp and, 228–229 Kaplan and, 14, 87 Kaplan and Kavanaugh hearings and, 201–202 manipulated video of Pelosi and Facebook debates about, 234–240 meets Zuckerberg, 4 Nuñez’s reporting and, 79 organizational changes in 2018 and, 194 parents and siblings of, 41, 44 Pelosi and, 233–234 personal life of, 41, 43, 258, 295 personality of, 2, 45, 199–200 as protective of her image, 4 reaction to emotional contagion research, 183 response to criticisms of Facebook, 156–157 responsible growth and, 86 Russian disinformation investigation and, 118–119, 120, 121, 122–123, 126, 127–128, 134, 136, 139, 143–144, 147, 196–197 Schrage and, 87–88, 89–92 Stamos and, 10–11, 103–104 Zuckerberg hires, 43–48 Zuckerberg’s working relationship with, 54–57, 86–87, 190, 260–261 Sanders, Bernie, 100, 132, 140, 221, 226 Sandy Hook Elementary School, shooting at, 82, 157, 204–205 Sanghvi, Ruchi, 32, 34, 274 Saverin, Eduardo, 30 Scavino, Dan, 243 Schatz, Brian, 166, 236 Schiff, Adam, 140, 142–144 Schissler, Matt, 171–173, 177–182 Schmidt, Eric, 42, 44, 46, 62, 192, 207 Schrage, Elliot Definers Public Affairs and, 216–217 Russian disinformation and, 119, 123, 125–126, 134–135 Sandberg and, 87–88, 89–92 Schumer and, 66–67, 88 Trump’s 2015 anti-Muslim rhetoric and hate speech issues, 12, 13 Schroepfer, Mike, 194, 291 Schumer, Chuck, 66–67, 68, 88 Scott, Kim, 47 Secureworks, 98 Segall, Laurie, 160 Sidley Austin law firm, 295 Smith, Matthew, 185–187, 294 Snapchat, 240, 253 Snowden, Edward, 8 Sorkin, Andrew Ross, 156 Soros, George, 108, 156–157, 215–216, 226 South Park Commons, 274 Sparapani, Tim, 65, 66 Sperling, Gene, 248 Stamos, Alex background before Facebook, 101–103 election of 2020 and, 283–284 investigation and report on Russian meddling and disinformation, 97, 100, 103–107, 116, 117–127, 130, 132, 145–147 2015 report on security of user’s information, 7–11 2018 Facebook reorganization and, 194 as “warranty canary,” 103, 134, 145 Standard Oil, Facebook’s parallel with, 230 Steyer, Jim, 89, 91, 232, 261, 275–276 Stop the Hate for Profit, 275 “Stop the Steal” groups, 288, 292 Stretch, Colin Cambridge Analytica and, 150 Russian disinformation and, 97, 100, 107, 119–120, 125, 135, 144–145, 146, 147 Students Against Facebook News Feed, 34, 35 Sullivan, Joe, 103–104 Summers, Lawrence, 39-42, 47 Swisher, Kara, 29–30, 43, 203–208 Systrom, Kevin, 194, 228–229 Talking Back to Facebook (Steyer), 89, 91 TechCrunch, 64, 65 TechCrunch Disrupt conference, 88, 174 Thiel, Peter Facebook’s board of directors and, 30, 81, 86, 202 Gawker lawsuit and, 202 Zuckerberg and, 25, 29, 31, 206, 244, 256 ThreatConnect, 98 Tiger, Roi, 195 TikTok, 240, 245, 253 Tillery, Kristopher, 20 Time magazine, 127, 177 TPG Capital, 89 Traynham, Robert, 271 Trump, Donald J., 213, 221, 232 Access Hollywood tape and, 100 accusations of voter fraud in 2020 election and, 273–275, 283–285, 290 accused of inciting violence in January 2021 and banned from Facebook, 286–292, 294 anti-Muslim rhetoric and hate speech and, 11–17, 85, 249 comments after George Floyd’s death, 268–273 Facebook and COVID-19 and, 267–268 hackers and 2016 campaign, 105–106, 140 meeting with Facebook executives, 161, 243–247 number of Facebook followers and interactions with, 244, 283 Pelosi and, 234, 235 on Twitter, 232, 244–245, 268–271, 276 Zuckerberg and, 256 Twitter, 15, 37, 63, 75, 98, 231, 240, 253, 287 Cambridge Analytica and, 153 election interference and, 98, 142, 144–145 privacy and, 56, 63–64 Sandberg and, 197–198 Trump and, 232, 244–245, 268–271, 276 Ukraine, Bidens and, 251 United Kingdom, Brexit and, 154 Vaidhyanathan, Siva, 61 Vargas, Jose Antonio, 66 Verge, the, 272 Villarreal, Ryan, 73, 76 Vladeck, David, 199 Vox, 154, 166 Walk Away campaign, 292 Wall Street Journal, 1, 43, 47–48, 88 Walz, Tim, 268 Warner, Mark, 127–128, 132, 246 Warren, Elizabeth, 221, 226, 242, 259, 295 Washington Post, 24, 26–29, 30, 47, 84, 141, 164–165, 234, 236, 272 Wasserman Schultz, Debbie, 100 Waters, Maxine, 256–257 WeChat, 175, 245 Weedon, Jen, 108–109, 129, 147 Weibo, 175 Wexler, Nu, 83 What You Do Is Who You Are (Horowitz), 191–192 WhatsApp, 71–72, 166, 193–194, 221 data security and, 8, 222 Facebook’s acquisition of, 196, 295 Federal Trade Commission and, 68 interoperability of messaging apps and, 227 “pivot to privacy” and, 222–224 Wu and Hemphill’s evaluation of Facebook’s acquisition of, 230–231 Zuckerberg’s broken commitment to founders of, 2, 194, 227–229 Whetstone, Rachel, 204, 206–207 Wicker, Roger, 162 Williams, Maxine, 272–273 Willner, Dave, 92–93 WilmerHale law firm, 160, 197 Winklevoss, Cameron, 21 Winklevoss, Tyler, 21 Wirathu, Ashin, 172 Women@Google, 50 World Anti-Doping Agency, data stolen from, 99 Wu, Tim, 229–232, 261 Xi Jingping, 176 Yahoo, 8, 26–27 global expansion and, 42, 175 Goldberg and, 43–44 offer to buyout Facebook declined by Zuckerman, 30–32, 44 Stamos and, 101–103 Yang, Jerry, 42 Zients, Jeff, 297 Zuboff, Shoshana, 3, 61 Zucked (McNamee), 232 Zuckerberg, Ethan, 163 Zuckerberg, Mark Beacon feature and, 57–63 Black Lives Matter memo and, 71–73 Cambridge Analytica and, 16, 153, 154–156, 160, 204 coding at Phillips Exeter, 19–20 “company over country” and, 124 cyber security and, 97–98 decline of Yahoo’s buyout offer, 30–32, 44 earnings call in 2021 and, 298–299 election of 2016, 113–116 election security and, 210 employees’ internal conversations and, 70 Federal Trade Commission (FTC) and, 295–296 free speech issues and, 74–75, 252–261, 263, 269, 281 goals of global expansion and end of economic inequality, 173–177 Goldberg’s death and, 79 hate speech and disinformation issues, 11, 193, 204–208, 275–277 hearing regarding Libra and, 256–257 Kaplan and Kavanaugh hearings and, 201–202 Kaplan’s organization of dinners with politicians, 243–247 manipulated video of Pelosi and, 236–240 meets Sandberg, 4 News Feed and apology for, 32–36 Nuñez’s reporting and, 79 personal privacy and image guarded by, 4, 65–66 personality of, 29–30, 45–46, 48–49 philanthropy of, 174, 262 “pivot to privacy” and reactions to, 222–227, 235 plans for Facebook’s future, 299–300 portrayed in attorneys general complaint, 2 public opinion and, 257–258 reaction to Hughes’ New York Times op-ed, 219–222 reaction to Stamos’ 2015 report on data security, 7, 8–10 reorganization of Facebook in 2018 and, 193–194 responsible growth and, 86 reversing of promises made when acquiring Instagram and WhatsApp, 2, 194, 227–229 Russian disinformation investigation and, 117, 118–119, 120, 121, 126, 134, 136–137, 139, 142, 147, 196, 204 Sandberg’s hiring and, 43–47 testimony before Congress, 150–151, 153, 160–167, 210 Trump banned by, 290–292, 294 “wartime” leadership philosophy and, 189–193, 207 working relationship with Sandberg, 54–57, 86–87, 190, 260–261 yearly goals of, 261–263 About the Authors Sheera Frenkel covers cybersecurity from San Francisco for the New York Times.


Reset by Ronald J. Deibert

23andMe, active measures, air gap, Airbnb, Amazon Web Services, Anthropocene, augmented reality, availability heuristic, behavioural economics, Bellingcat, Big Tech, bitcoin, blockchain, blood diamond, Brexit referendum, Buckminster Fuller, business intelligence, Cal Newport, call centre, Cambridge Analytica, carbon footprint, cashless society, Citizen Lab, clean water, cloud computing, computer vision, confounding variable, contact tracing, contact tracing app, content marketing, coronavirus, corporate social responsibility, COVID-19, crowdsourcing, data acquisition, data is the new oil, decarbonisation, deep learning, deepfake, Deng Xiaoping, disinformation, Donald Trump, Doomsday Clock, dual-use technology, Edward Snowden, Elon Musk, en.wikipedia.org, end-to-end encryption, Evgeny Morozov, failed state, fake news, Future Shock, game design, gig economy, global pandemic, global supply chain, global village, Google Hangouts, Great Leap Forward, high-speed rail, income inequality, information retrieval, information security, Internet of things, Jaron Lanier, Jeff Bezos, John Markoff, Lewis Mumford, liberal capitalism, license plate recognition, lockdown, longitudinal study, Mark Zuckerberg, Marshall McLuhan, mass immigration, megastructure, meta-analysis, military-industrial complex, move fast and break things, Naomi Klein, natural language processing, New Journalism, NSO Group, off-the-grid, Peter Thiel, planetary scale, planned obsolescence, post-truth, proprietary trading, QAnon, ransomware, Robert Mercer, Sheryl Sandberg, Shoshana Zuboff, Silicon Valley, single source of truth, Skype, Snapchat, social distancing, sorting algorithm, source of truth, sovereign wealth fund, sparse data, speech recognition, Steve Bannon, Steve Jobs, Stuxnet, surveillance capitalism, techlash, technological solutionism, the long tail, the medium is the message, The Structural Transformation of the Public Sphere, TikTok, TSMC, undersea cable, unit 8200, Vannevar Bush, WikiLeaks, zero day, zero-sum game

Before it was kicked off Facebook’s platforms for breaching the company’s terms of service (and let’s face it, Facebook probably kicked it off only because of the bad publicity), it vacuumed up data on hundreds of thousands of unwitting users and 87 million of their even less witting networks of friends to fine-tune precision messaging and behaviour manipulation of tiny segments of target populations. Cambridge Analytica had the support of a group of wealthy but highly dubious backers, including conservative muckraker and Trump supporter Steve Bannon and billionaire right-winger Robert Mercer. More ominously, it also had links to the U.K. and U.S. defence establishments. These political and financial supporters helped the company recognize that their psychometric profiling expertise, normally applied to digital marketing, could easily be repurposed for political campaigns, however unethically or illegally.

., 221 Lynch, Jim, 248 Machiavelli, Niccolò, 279 Madison, James, 282 Madonna, Richard, 175 Malaysia, 68, 150–151, 221, 302 Mansoor, Ahmed, 151–152, 197 Marczak, Bill, 144 The Markup, 130–131 Mastodon (search engine), 270–271 Maya (app), 57 McConnell, Mitch, 278 McDonald’s, 64 McGill University, 116 McKibben, Bill, 262 McKinsey & Company, 141, 142 McLuhan, Marshall, 21–22, 209, 263, 268 McMaster University, 234 media ecology, 21–22, 24 media literacy, 268–269 Mercer, Robert, 119 Mexico, 150–151, 152–153, 176, 261 Microsoft, 77 data sharing by, 43, 56 and the environment, 239, 241 security/privacy issues, 59, 175–176, 231–232 Miller, James Grier, 107 Mindstrong Health (app), 54–55 mining, 221–224 Bitcoin, 234–235 for rare earth elements, 218–221 for tin, 224–225 Modi, Narendra, 202–203 monopolies.


Traffic: Genius, Rivalry, and Delusion in the Billion-Dollar Race to Go Viral by Ben Smith

2021 United States Capitol attack, 4chan, Affordable Care Act / Obamacare, AOL-Time Warner, behavioural economics, Bernie Sanders, Big Tech, blockchain, Cambridge Analytica, citizen journalism, COVID-19, cryptocurrency, data science, David Brooks, deplatforming, Donald Trump, drone strike, fake news, Filter Bubble, Frank Gehry, full stack developer, future of journalism, hype cycle, Jeff Bezos, Kevin Roose, Larry Ellison, late capitalism, lolcat, Marc Andreessen, Mark Zuckerberg, Menlo Park, moral panic, obamacare, paypal mafia, Peter Thiel, post-work, public intellectual, reality distortion field, Robert Mercer, Sand Hill Road, Saturday Night Live, sentiment analysis, side hustle, Silicon Valley, Silicon Valley billionaire, skunkworks, slashdot, Snapchat, social web, Socratic dialogue, SoftBank, Steve Bannon, Steven Levy, subscription business, tech worker, TikTok, traveling salesman, WeWork, WikiLeaks, young professional, Zenefits

“If it does bring down our company, it would be a funny way to go out,” Nolan mused. 21 Upworthy As Nick and Jonah’s competition intensified in the beginning of 2012, Andrew Breitbart felt he’d finally found his footing. Anthony Weiner’s dick, his downfall, and the election of a Republican to replace him had combined for Andrew to wash away the stain left by the Shirley Sherrod incident. Breitbart had brought a new wave of money into the company too: A low-profile hedge fund billionaire, Robert Mercer, had been taken with this new source of power, and invested $10 million. They’d put some of the cash into a splashy redesign, just like the one Nick Denton had done a year earlier to make the Gawker Media brands look bolder and less bloggy. (This stylish redesign had cost the site valuable page views.

See also MIT Media Lab “matchmaking” events, 15–16 Mayer, Kevin, 196, 199–200 Mayer, Marissa, 64–65 McCain, John, 167, 248–49, 251 McCain Institute, 250 McCarthy, Megan, 85 McCollum, Ashley, 193 McEnroe, John, 28 McInnes, Gavin, 97, 139, 184, 290 McKinsey consulting firm, 225 McNeill, Caitlin, 209–10 “meaningful social interactions” metric, 272–75, 284 Media Matters, 191 Meier, Barry, 249, 258 memes and Bannon’s political activism, 117 and BuzzFeed’s competition, 196, 284 and BuzzFeed’s journalism, 280 and BuzzFeed’s news and social content, 151, 167 and BuzzFeed’s traffic sources, 123, 126–27, 153 and Contagious Media Showdown, 48–49 and Gionet, 295 and political campaigns, 254 and right-wing media, 186, 188, 192 and social engagement on Facebook, 276–77 and “the Dress” viral post, 210–11 Mensch, Louise, 255–56 Mercer, Robert, 177 Merkley, Jeff, 295 MetaFilter, 3 #MeToo movement, 100 Millard, Wenda Harris, 106, 169 Miller, Katherine, 194, 240 Miller, Zeke, 166 Mini Cooper, 47 misogyny, 143, 184 MIT Media Lab, 1–2, 8, 11, 47 mobile phones, 151, 262 Modi, Narendra, 243 Morales, Oscar, 179, 240 Moreover, 16–18, 20, 51, 138 Morgan Stanley, 120 Morin, Dave, 216 Moss, Kate, 57 Mosseri, Adam, 211 Movable Type software, 34 MoveOn.org, 180–81, 237 Moyers, Bill, 98 MSN, 196 MSNBC, 255–56 MTV, 73, 110, 127–28, 154–55, 269 Mucha, Zenia, 117 mullet strategy, 79–80 Murdoch, Rupert, 53, 56, 255, 272 mybarackobama.com, 111, 114 MySpace, 93, 111 N NAACP, 135 National Review, 167 National Rifle Association (NRA), 25–28, 129, 187 native advertising, 130, 266 NBC, 268–69, 279–80, 283, 301, 303 NBCUniversal, 238, 300 Negations, 7 nepotism, 283 netroots, 29 Netscape, 207 New Black Panther Party, 187 Newmark, Craig, 281 new Right, 41, 43 NewsBlogger, 16 News Feed (Facebook) and BuzzFeed’s news and social content, 160–62 and BuzzFeed’s traffic growth, 205 and BuzzFeed’s traffic sources, 152 and funding for Ratter, 216 and origin of social media politics, 115 and social engagement on Facebook, 273 and “the Dress” viral post, 211 and Upworthy, 182–83 NewsGuild, 282 Newsweek, 33, 70 New Yorker, 207, 249 New York magazine, 54, 181 New York Observer, 57, 156 New York Post, 86 New York Times and anti-NRA efforts, 28–29 and BuzzFeed’s influence, 186 and BuzzFeed’s layoffs, 280–82 and BuzzFeed’s SPAC deal, 301 and BuzzFeed’s traffic growth, 167 and changing media environment, 218 and coverage of Trump presidency, 269 and Denton’s wedding, 213–14 and Disney’s bid to buy BuzzFeed, 196 and Facebook’s dominance of social media, 270 and Facebook’s political content, 238 on Gawker scandals, 54 and news aggregation–distribution startups, 15 Peretti’s address to board, 218–20 and political blogs, 33 and revival of legacy media, 220–30 and shifting strategy at Huffington Post, 81 and social engagement on Facebook, 275–76 and social media politics, 115 and splintering of internet media, 298 and the Steele Dossier, 248–49, 255, 256 and traffic monitoring tools, 105 Wirecutter acquisition, 287 Nguyen, Dao, 192, 244, 267, 288 Nielsen ratings, 150 Nike, 2–4, 7–8, 10–11, 27, 149, 288, 300, 302 Nisenholtz, Martin, 222, 223 Nolan, Hamilton, 176 NowThisNews, 283 “Numa Numa Dance” (video), 72 O Obama, Barack and Breitbart’s political background, 43 and BuzzFeed’s traffic sources, 155–56 and Facebook’s influence, 152, 177 and Facebook’s political content, 240 and Harman’s investment in Huffington Post, 120 and Harman’s support, 118–19 and Huffington Post’s political content, 107–8 and Huffington Post’s traffic, 70, 116 Iger’s access to, 197 and Lerer’s political clout, 149 Obamacare, 158 and online political activism, 132, 134–35, 152 and Pariser’s background, 180 presidential campaign, 102–3, 106, 109–15 and right-wing media, 186, 191 and shape of today’s internet media, 304 and the Steele Dossier, 250 Tkacik’s support for, 94, 97 and Wonkette’s political content, 31 Ocasio-Cortez, Alexandria, 277, 284 Occupy Wall Street, 166 Ochs, Adolph, 222 Oddjack blog, 55–56 OkCupid, 149 O’Keefe, James, 133–34, 135 O’Malley, Martin, 168 One D at a Time (Egan), 92 One Million Voices Against FARC, 113, 131–32 The Onion, 180 Openbook, 206 O’Reilly, Bill, 135 Oxfeld, Jesse, 56 Ozy, 195, 284–85, 286, 299 P pac-manning, 81–82 Page, Larry, 64 Palihotel, 197 Palin, Sarah, 82 Paltrow, Gwyneth, 46 paparazzi, 141–42 Pariser, Eli, 179–81, 183, 237, 269 Parsons, Richard, 25 Paul, Ron, 166 Paulson, Hank, 118 PayPal mafia, 85 paywalls, 224–26, 229, 269 Peacock streaming platform, 300 Pelosi, Nancy, 277 Peretti, Chelsea, 24, 47, 49, 58–59 Peretti, Della, 4–5 Peretti, Jonah acquisition of HuffPost, 286–87 and Arianna Huffington’s influence, 34 arrival in New York, 10, 12 and author’s background, 157–64, 247 background and education, 1–9 bet with Marlow, 1, 9, 49, 302–3 and Breitbart’s death, 178–79 and Breitbart’s departure from Huffington Post, 131–32 and Breitbart’s political background, 43 and Breitbart’s role at Huffington Post, 40 and BuzzFeed’s labor tensions, 280–86 and BuzzFeed’s news and social content, 167–69 and BuzzFeed’s office leases, 204–5, 319n204 and BuzzFeed’s SPAC deal, 300–303, 324n302 and BuzzFeed’s traffic, 122–29, 152–54, 154–56, 203–8 and competition with Huffington Post, 67–77 and Contagious Media Showdown, 51 and Daulerio’s background, 139 and Denton’s arrival in New York, 18 and Denton’s parties, 52, 58, 59 and devaluation of traffic, 264–70 and Disney’s bid to buy BuzzFeed, 196–202 and early virality projects, 24–29 and Facebook’s political content, 237–38, 244–45 and Gionet, 292 and Huffington Post’s investors, 116–18, 120 and Huffington Post’s launch, 44–50 and Huffington Post’s political content, 313n102 and Huffington Post’s strategy, 78–82 and launch of Upworthy, 180–83 meeting with New York Times board, 219–20, 222 and New York blogging scene, 21 Nike sweatshop email prank, 2–4, 7–8, 10–11, 27, 302 and political engagement, 102–8 and product marketing, 287–89 and revival of legacy media, 230 and right-wing media, 185, 191, 290 and rise of New York tech companies, 61–62 rivalry with Denton, 170–72, 177, 206, 315n126 and sale of Huffington Post, 147–51 and social engagement on Facebook, 272–74 and social media politics, 111 and the Steele Dossier, 248, 258 and “the Dress” viral post, 210–11 and venture capital investments, 213 and Zuckerberg’s purchase offer for BuzzFeed, 160–62, 165 Perpich, David, 220–27, 229–30 Perry, Rick, 158, 160 PETA, 153 Petraeus, David, 180 PewDiePie, 201 Philadelphia magazine, 138 photoshopping (photo retouching), 93 Pinterest, 182, 267, 269 Pitney, Nico, 159 plagiarism, 187, 193–94 Politico, 156, 158, 165, 180, 246 Pollak, Joel, 145 Poochareon, Ann, 47–48 Poole, Chris (“moot”), 117, 126–27, 290 populism, 166, 191, 238, 240, 243, 255, 302, 304 pornography, 57, 97–98.


pages: 394 words: 112,770

Fire and Fury: Inside the Trump White House by Michael Wolff

Affordable Care Act / Obamacare, barriers to entry, Bernie Sanders, Biosphere 2, Carl Icahn, centre right, disinformation, disintermediation, Donald Trump, drone strike, Edward Snowden, Elon Musk, fake news, false flag, forensic accounting, illegal immigration, impulse control, Jeff Bezos, Jeffrey Epstein, obamacare, open immigration, opioid epidemic / opioid crisis, Paris climate accords, Peter Thiel, Renaissance Technologies, ride hailing / ride sharing, Robert Mercer, Ronald Reagan, Russian election interference, Saturday Night Live, self-driving car, Sheryl Sandberg, Silicon Valley, single-payer health, Steve Bannon, Travis Kalanick, WikiLeaks, zero-sum game

Bannon met Breitbart News founder Andrew Breitbart at a screening of one of the Bannon-Bossie documentaries In the Face of Evil (billed as “Ronald Reagan’s crusade to destroy the most tyrannical and depraved political systems the world has ever known”), which in turn led to a relationship with the man who offered Bannon the ultimate opportunity: Robert Mercer. * * * In this regard, Bannon was not so much an entrepreneur of vision or even business discipline, he was more simply following the money—or trying to separate a fool from his money. He could not have done better than Bob and Rebekah Mercer. Bannon focused his entrepreneurial talents on becoming courtier, Svengali, and political investment adviser to father and daughter.

., 74 Manigault, Omarosa, 109 Mar-a-Lago, 4, 69, 99, 106, 159, 189, 193–94, 210, 228, 248–49 Marcus, Bernie, 309 Mattis, James, 4, 21, 103, 109, 188, 264–65, 288, 296, 304–5 May, Theresa, 258 McCain, John, 112, 306 McCarthy, Joe, 73 McConnell, Mitch, 32, 117, 301–2 McCormick, John, 167 McGahn, Don, 95, 212–14, 217 McLaughlin, John, 10 McMaster, H. R., 109, 176, 185, 188–93, 211, 235, 258, 263–68, 276–77, 288–89, 298–99, 304–5 McNerney, Jim, 88 Meadows, Mark, 161, 163, 171 Medicare, 165 Melton, Carol, 78 Mensch, Louise, 160 Mercer, Rebekah, 12, 58–59, 121, 127, 135, 139, 177–80, 201, 208, 309 Mercer, Robert, 12, 58–59, 112, 177–80, 201, 309 Mexico, 39, 62, 77, 93, 228 Middle East, 29, 70, 140, 145, 157, 190, 211, 224–33, 242, 264 Mighty Ducks, The (TV show), 56 military contractors, 265, 267 Miller, Jason, 234, 237–38, 299 Miller, Stephen, 61, 64–65, 89, 133, 148, 209, 213, 229, 258, 307 Mnuchin, Steve, 13, 133, 290, 296, 304 Mohammed bin Nayef, crown prince of Saudi Arabia (MBN), 228, 231 Mohammed bin Salman, crown prince of Saudi Arabia (MBS), 224–31 Moore, Roy, 302–4 Morgan, Piers, 22 Morning Joe (TV show), 32, 66–67, 121, 189, 247–48 MSNBC, 66, 106, 247 Ms.


pages: 419 words: 119,476

Posh Boys: How English Public Schools Ruin Britain by Robert Verkaik

accounting loophole / creative accounting, Alistair Cooke, banking crisis, Berlin Wall, Boris Johnson, Brexit referendum, British Empire, Brixton riot, Bullingdon Club, Cambridge Analytica, data science, disinformation, Dominic Cummings, Donald Trump, Etonian, G4S, gender pay gap, God and Mammon, income inequality, Jeremy Corbyn, Khartoum Gordon, Kickstarter, knowledge economy, Livingstone, I presume, loadsamoney, mega-rich, Neil Kinnock, offshore financial centre, old-boy network, Piers Corbyn, place-making, plutocrats, Robert Gordon, Robert Mercer, school vouchers, Stephen Fry, Steve Bannon, Suez crisis 1956, The Bell Curve by Richard Herrnstein and Charles Murray, trade route, traveling salesman, unpaid internship

Billionaire hedge-fund owner and former futures trader David Harding (Pangbourne) donated £3.5 million to the same campaign. Before the country went to the polls, the Leave campaigners had one more card to play in the battle to persuade the British people to support Brexit. Some believe it may have even been a decisive factor. In the summer of 2015, US billionaire Robert Mercer, a close friend of Donald Trump and an investor in alt-right media company Breitbart News, introduced Farage to a data company set up by two Old Etonian brothers who had cut their teeth on controversial military style ‘psy-ops’ which they ran in election campaigns in the developing world.15 Nigel and Alex Oakes were colourful businessmen with a special interest in psychological profiling.

INDEX Abbott, Diane 181 Abromovich, Roman 197 abuse 207–20, 254 Adams’ Grammar School 172–3, 184 Addrison, John 210 Adonis, Andrew 240–1, 333 Africa 53–4, 314–15 Ahmad, Muhammad 37, 38–9 Aitken, Jonathan 255 Aldridge, Sir Rod 318 Alexander, Danny 148 Alfred the Great, King 14 Allan, Tim 169 Alpha Plus 316–18 Ametistova, Ekaterina 200–1 Ampleforth College 219, 237, 250–1 Anderson, Bruce 146 Andersdon, Dr Eric 105, 106, 115, 137 Anne, HRH Princess 110 Anthony, Vivian 108–9 Apostles Club 306 aristocracy 18, 22, 28 Arkwright, Richard 32 Arnold, Matthew 66 Arnold, Thomas 31, 67 Aspinall, John 156 Asquith, Herbert 64 al-Assad, Bashar 128, 196, 202 Attlee, Clement 87, 88, 89, 99, 180 Augustine, St 13–14 Australia 283 Baddiel, David 263–5 Bailey, Mark 227 Balfour, Arthur 33 Ball, Peter 216–19 banking 295–9 Banks, Arron 163, 164, 165 Bannon, Steve 164, 282 Barrington, Robert 202 Barton, Laura 305 Barttelot, Sir Brian 38, 40–1 Barttelot, Maj Edmund Musgrave 38–40 Barttelot, Sir Walter 40–1, 60–1 Bash camps 212–13, 216 BBC 298–300 beatings 21, 30, 211, 213–14, 215 Beckett, Andy 304–5 Bedales 182–3 Beefsteak Club 291–2 Bellak, Benjamin 138 Benn, Melissa 255, 268, 323–4, 339 Benn, Tony 96–7, 174, 175, 176, 180, 255–6 Bennett, Alan 1, 336–7 Bentham, Jeremy 66 Berezovsky, Boris 199 Beveridge, William 89 Blackadder Goes Forth (TV show) 62 Blair, Tony 103–6, 107, 109, 111, 179, 180–1 Blunkett, David 106–8, 109, 111 Blunt, Anthony 133 Bo Xilai 198 Board of Education 68–9, 69 ‘Boarding School Syndrome’ 270–1 Boarding Schools Corporation 98 Boer War 40, 52–4 Bonar Law, Andrew 64 Borwick, Tom 165 Bracken, Brendan 85–6 Brexit 127, 151, 161–3, 164–70; see also Farage, Nigel Bridgeman, Luke 292–3 British Army 36, 40–2, 55–64, 72–3, 224, 225 British Empire 30, 32, 33–5, 36–7, 38–40, 42–3, 44–5 and Second World War 74–5 British Expeditionary Force (BEF) 52 Brodie, Stanley 116 Brooke, Rupert 62 Brook’s 291 Brooks, Charlie 147 Brougham, Henry 29 Brown, Gordon 107, 287 Bruce, Charles 136 Brunel, Isambard Kingdom 32 Bryant, Chris 128 Buchanan, Mike 119 Buffet, Warren 329 Bullingdon Club 137, 141–2, 306 bullying 271, 273 Burgess, Guy 133 bursaries 226–35, 321–2, 332 Butler, Rab 77, 78–9, 81, 82 Butler, Robin, Lord 193 Byers, Stephen 107–8 Cable, Vince 167 Caldicott prep school 209–10, 215, 219 Callaghan, James 99, 180 Cambridge Analytica (CA) 164–6 Cambridge, HRH Catherine, Duchess of 191 Cambridge Spy Ring 133 Cambridge University 1, 25 Cameron, David 6, 105, 133–8, 139, 140, 274 and ‘big society’ 313, 315 and Conservative Party 143, 144–8 and Eton 119, 190 and EU Referendum 127, 161, 162, 166–7, 169, 170 and government 148–54 and Oxford 141–2, 143 and psychology 271, 273 and Russia 132 camps 212–16 Canning, George 33 Card, Tim 61 Cardigan, James Brudenell, 7th Earl of 56 Carey, George, Lord 217 Carpenter, John 17 Carswell, Douglas 161 Cash, Bill 161 Castle House Preparatory School 172 Catling, Susan 95, 96 Chakrabarti, Shami 181–3 Chamberlain, Neville 72 chantry schools 15, 24, 26 Charitable Uses Act (1601) 109 Charities Act (2006) 114–16, 223 charity 17, 47, 88–9, 114–21, 341 and law 109–10, 111 Charles, HRH Prince of Wales 105, 110, 143, 216, 217, 283 Charterhouse School 19–20, 195–6, 233, 257 China 197–8, 200, 203, 204 Christianity 13–14, 15, 24, 215–16 and muscular 35–8, 44, 67, 211 church, the 2, 13–15, 24, 211–19 Churchill, Winston 40, 72, 74, 78, 84, 286 and Bracken 86 and Eden 91 and Harrow 33, 77, 82–3 City, the 4, 292–3, 295–7 City of London School 17, 181 Clarendon, George Villiers, 4th Earl of 48, 49–51 Clark, Alan 62 Clark, Ross 194 Clarke, Kenneth 146, 147 class 22, 65–6, 86–7, 95, 237–8, 315–16 and the army 55–6 and government 91–3 and grammar schools 67–8 and the media 298–300 classics 30–1 Clegg, Nick 147–8, 181, 209–10, 327–8 Clifford, Adm Sir Augustus 34 Clive, Robert 42–3 Comenius, John 27 comprehensive schools 94–5, 255–6 Conrad, Joseph 39–40 conscription 52–3 Conservative Party 69, 86, 90, 92, 99–100, 101–2 and Cameron 143, 144–8 Cook, Henry 169 Cooke, Alistair 143 Coombs, Mark 163 Corbet, Richard 23 Corbyn, Ben 178 Corbyn, Jeremy 17, 121, 171–5, 176–80, 186, 314 Corbyn, Sebastian 178 corporal punishment 21 Cranmer, Thomas 11–12, 14 Crawford, David Lindsay, 27th Earl of 59–60 Crimean War 56 Cromwell, Oliver 27 Crosland, Anthony 95–6, 97, 255 Cruz, Ted 164 Cumberbatch, Benedict 252 Cummings, Dominic 165–6 Cust, Sir Lionel Henry 222 Czerin, Peter 144 Dacre, Paul 147 Daffarn, Edward 318 Dalton, Hugh 180 Damasio, Antonio 276 D’Ancona, Matthew 144 Darwin, Charles 30–1 Davidson, Jim 261–3, 266–7 Davison, Dick 108 De Carvalho, Alexander 168–9 De Freitas, Geoffrey 89 Deakin, Chloe 157, 158 Dean, Victoria 169 Debrett’s 289 Derham, Patrick 120 Dimbleby, David 149, 251 Disraeli, Benjamin 42 Doggart, Simon 215 donations 228–9 Dorries, Nadine 250–1 Dowding, Hugh 83 Duff, Grant 47–9, 50 Duffell, Nick 271, 272–3, 276–7, 284 Dulwich College 90, 156–61, 181–2, 192, 248, 330–1 and overseas franchises 203, 204 and sponsorships 239–42 Duncan, Alan 167 Eden, Anthony 64, 90–2 Edinburgh Academy 47 Edmiston, Robert, Lord 163 education 11–12, 13–15, 27, 321–4, 327–9 and Ragged Schools 37 and reforms 65–6 and rights 337–8 and Scotland 43–4 see also grammar schools; public schools; state schools Education Acts: 1902: 69 1918: 65 1944: 82, 87, 93 Education Review Group 117 Edward III, King 16 Edward IV, King 26 11-plus exam 82, 93 Elizabeth I, Queen 18, 19 Elizabeth II, Queen 133 Elliott, Matthew 165 Emms, David 157 employment 341–3 End of the ‘Old School Tie’, The (Worsley) 75–6 Endowed Schools Commission 50 English Civil War 27 entry requirements 18–19 Establishment, the 125–6 Eton College 3, 17, 19, 22, 204, 278–9 and admission 189–90 and alumni 33, 140–1 and bursaries 228–9, 230 and Cameron 119, 136–8, 140 and charity 99, 115, 221–3, 235–6 and Eden 91, 92 and exams 257 and fees 113, 188–9, 227 and foundation boys 50 and Goldsmith 155 and government 134 and grants 238 and international students 198–9 and Leggatt 293 and masters 46–7 and Oxbridge 25, 301 and poor boys 28–9 and Putin 127–32 and reforms 26–7 and Rifles 52, 53, 59 and sponsorships 242 and sport 35 and town 187–8 and Wellington 33, 41–2 see also Old Etonians EU Referendum 127, 150–1, 161–3, 164–70 Evans, Chris 298–9 exams 82, 93, 257, 267–8 Fabian Society 180 fagging 22, 29, 98, 104 faith schools 180–1 Fallon, Michael 62 Faraday, Michael 32 Farage, Nigel 156–9, 160–1, 162, 163, 167, 169, 248 and the establishment 283 and psychology 273 and Trump 282 Farr, Clarissa 278 Farron, Tim 153 fascism 157, 158 federations 238 fees 13, 19, 67, 69, 111–13, 194 and Eton 188–9 and subsidies 221–2, 224–35, 245–9 and university 260–1 Fettes College 103–6, 211 Finkelstein, Daniel 146 Finland 268, 344 First World War 54–64, 65–6 Fisher, Herbert 68–9 Fleming, David Pinkerton, Lord 79–81, 90 Fletcher, David 200, 201 Fletcher, Frank 68, 69 Foot, Michael 106, 180 Fox, Edward 156 Fox, Laurence 252–3 France 268–9 Fraser, Giles 211, 216 free scholars 16, 17, 18, 23, 50–1 Freemasons 193 French, John 61 French Revolution 28 Freud, Matthew 147 Gaitskell, Hugh 180 Galsworthy, John 66–7 Gascoigne, Michael 104 Gates, Bill 329 Geelong Grammar School 283 GEMS Education 111, 113–14, 204–6 gender pay gap 298, 299 gentlemen’s clubs 143–4, 169, 291–2 Germany 196, 268–9, 344 Ghosh, Helen 149 Gibb, Dame Moira 217, 218 Gill, Ameet 168 Girls’ Public Days School Trust 68 girls’ schools 229 Girls’ Schools Association 108 Gladstone, William 33, 37, 48 Goldsmith, James 155–6 Goodall, Lewis 298–9 Goodhart, David 320–1 Gordon, Gen Charles 36–8, 53 Gordonstoun 110, 211 Goschen, Giles, Viscount 135–6 Gove, Michael 144, 149, 161, 282, 322 and Brexit 166, 168 and psychology 273 and sponsorships 238 and subsidies 247–9 government 4–5, 6, 148–54 Gracie, Carrie 298 grammar schools 14, 15, 24, 30, 44, 56–7 and grants 93–4, 100–1 and Labour 183–5 and reforms 49–50, 67–8 Granville, Granville George Leveson-Gower, 2nd Earl of 48 Gray, Herbert Branston 45 Grayling, Chris 161 Great Depression 69–70 Green, Francis 307 Green, Michael 145 Greenwood, David 208, 219 Gregory, Pope 13 Grenfell Tower 316, 317–19 Greville, Fulke 22 Guppy, Darius 289–90 Guru-Murthy, Krishnan 234–5 Haberdashers’ Aske’s 263–5, 300 Haig, Gen Douglas 61 Haileybury College 88, 89 Haldane, Richard Burdon 53 Halfon, Robert 249, 311, 333, 336 Halls, Andrew 194 Hammond, Richard 67 Hancock, Matt 342 Hannan, Daniel 161 Hanson, David 219 Harding, David 163, 168 Hardman, Robert 144 Hargreaves, Peter 163 Harman, Harriet 181 Harrison, Rupert 144, 153, 275 Harrow School 17, 23, 24, 29, 31–2, 68 and alumni 33, 34, 252–3 and bursaries 233–4 and Churchill 83 and foundation boys 50 and overseas franchises 203 and soldiers 52, 53 Hart, Basil Liddel 62 Hasan, Mehdi 327 Hastings, Max 277 Hastings, Warren 43 Haynes, Tim 227 Headmasters’ and Headmistresses’ Conference (HMC) 51, 119 Healey, Denis 175, 176 Heart of Darkness (Conrad) 39–40 Heath, Edward 99, 287 Heath, Lt Gen Sir Lewis ‘Piggy’ Macclesfield 74 Heatherdown 135–6 Henderson, Simon 235 Hendon County Grammar School 183–5 Henry, Hugh 210 Henry VI, King 19, 26, 221, 301 Henry VIII, King 18, 26 Henty, G.A. 53 Heseltine, Michael 145, 167 Higgins, Matthew James 46–7 Hillman, Nick 99, 100, 255, 302–3 Hilton, Steve 144, 153 Hitler, Adolf 3, 73 Hobsbawm, Eric 34 Hoey, Kate 161 Hogg, Charlotte 295–6 Hogg, Dame Mary 294 Hogg, Douglas 294–5 Hogg, Quintin 97, 294, 295 Hogg, Sarah 294–5 Holle, Arnold 196 homosexuality 35–6 Hong Chin 201 Hosking, Jeremy 163 Howard, Adam 283–4 Howard, Michael 146 Howard, Nicholas 152 Howe, Geoffrey 101–2 Howell, Steve 183–5 Hughes, Billy 90 Hughes, Thomas 35 Huhne, Chris 148 Hunt, Jeremy 271, 273 Hurtwood House 225 Hutton, Will 274 Huxley, Thomas 66 Ibori, James 201 immigration 156, 157, 162, 168, 264 imperialism 33–4, 53–4; see also British Empire Independent Inquiry into Child Abuse 210–11 Independent Schools Council (ISC) 110, 113, 116, 120, 288, 325–7 and charity 223, 224, 226 and sponsorships 238 India 42–3, 53 industrial revolution 32 inequality 306–12, 314–16, 321–4, 327–9 initiation ceremonies 21 international students 196–202 internships 341–2 Iremonger, William 91 Itoje, Maro 234 Iwerne Trust 212, 214 Jameson, James Sligo 39 Japan 73–4 Jardine, Cassandra 94–5 Johnson, Boris 6, 31, 128, 142, 150–1, 272 and Brexit 162, 166, 167, 168, 169 and bursaries 321–2 and the Establishment 125–6 and Eton 136, 190 and Guppy 289–90 and psychology 271, 273, 276–7 Johnson, Jo 149 Johnson, Stanley 292 Jones, Owen 274–5, 328 Jonson, Ben 23 journalism 274–5, 297–8 Journey’s End (Sherriff) 58 judiciary 5, 292–3 Keir Hardie, James 180 Kensington Aldridge Academy (KAA) 318–19 KGB 132, 133 King Edward’s School 68, 93–4 Kingston Grammar School 56, 57 Kinnock, Neil 180 Kipling, Rudyard 53, 64 Kitchener, Gen Herbert 54–5, 57 Korski, Daniel 168–9 Kynaston, David 328–9, 337 Labour Party 6, 69, 86–8, 99, 100–1 and Corbyn 171, 174–5, 176–80 and education 180–6, 328–9 see also New Labour Lammy, David 303–4, 343 Lamont, Norman 143, 145 Lampl, Sir Peter 116 Landale, James 150 language 20–1, 277 Lansman, Jon 175–6, 178–9 Lansman, Max 178 Latin 14, 30 Laws, David 148 Leach, Arthur 14, 27 Leach, Sir John 109–10 league tables 267–8 Leanders, Rocky 214–15 Leather, Suzi 114–15, 117 Leggatt, George 292–3 Lenon, Barnaby 226–7, 228, 233–4, 258–61, 279, 303, 325–7 Leonard, Richard 186 Leslie, Chris 179 Letwin, Oliver 148, 149, 271 Levellers 27 Lewis, Sir George 48–9 Li Wei Gao 201 Liddle, Rod 299–300 Lineker, Gary 195, 298–9 literacy 14, 15, 43 Little, Steven 231–2 Little, Tony 190, 193–4, 198, 199, 205–6, 278–9 and assisted places 226, 230, 235 and parents 256 Litvinenko, Alexander 128 Livingstone, David 43, 44 Llewellyn, Ed 144, 148, 152 Lloyd George, David 65 local education authorities (LEAs) 80–1, 89–90, 98 Lockwood, Chris 144 London 316–19, 334; see also City, the London Oratory 180–1 Loom of Youth, The (Waugh) 63, 70 Lyon, John 17 Macdonald, Ramsay 180 McDonnell, John 174–5, 178–9, 186 McGovern, Steph 298 McKenna, Alison 116 Maclean, Donald 133 Macmillan, Harold 92 McNeil, Rosamund 120 Madders, Justin 185, 311–12 Made in Chelsea (TV show) 325 Magnitsky, Sergei 128 Major, John 321 Major, Lee Elliott 305 Mallinckrodt, Edward 135 Manchester Grammar School 27–8, 68 Mandelson, Peter 88, 183 Marathon Asset Management 292–3 Marlborough College 52, 55, 79, 192, 232 Marshall, Patrick 209 Marshall, Sir Paul 167–8 Marxism 177–8 Mason, A.E.W. 53 Masonic lodges 145, 193 May, Theresa 69, 118–19, 121, 127, 129 and internships 341–2 and ‘shared society’ 313–14, 322–3 and sponsorships 243 Meacher, Michael 176 media 297–300 Mercer, Robert 163, 164 Merchant Taylors’ School 17, 21, 28, 42–3, 140, 300–1 Merivale, Charles 22–3 Middleton, Kate, see Cambridge, Duchess of Milburn, Alan 315, 336 Military Cross 59 Millar, Fiona 109, 185–6, 324 Millfield School 247–8 Milne, Seumas 17, 177–9 Milton, John 27 Mitchell, Andrew 237, 271 Momentum 175–7, 178–9 monasteries 14, 15, 18, 24, 25, 26–7 money-laundering 201–2 Montgomery, Bernard 83 Moore, Thomas 42 morality 273–4 Morrison, Herbert 88 Mosley, Oswald 143, 158, 159 Mount, Ferdinand 139, 143 Mount, Harry 328 Mulcaster, Richard 20 Mumsnet 258 Murdoch, Rupert 147, 282–3 Murray, Andrew 178–9 Murray, Charles 334 Murray, Laura 178 Nash, Eric ‘Bash’ 212–13 Nash, Paul 62 National Front 157, 158 Neile, Richard 23 Nelson, Lord Horatio 44 New Labour 105, 106–7, 111 New York Military Academy (NYMA) 280–2 Newbolt, Sir Henry 55 Newmark, Brooks 292 Newsom, Sir John 97, 246 Newsome, David 273 newspapers 46–7, 297–8 Nix, Alexander 164, 165 non-cognitive skills 276 North Foreland Lodge 110 north–south divide 310–11 Norwood, Cyril 67, 70 Notting Hill Prep 316–18 Nyachuru, Guide 215 Oakes, Alex 163, 164 Oakes, Nigel 163–4 O’Brien, James 237, 250–1 Odey, Crispin 163, 167, 193 O’Dowda, Brendan 198 Office of Fair Trading (OFT) 112, 113 Officer Training Corps (OTC) 52, 53, 55, 62 old boys’ networks 21–2, 289–91 Old Etonians (OEs) 136, 140–1, 149, 192, 224, 228–9 Oldfield, Bruce 68 oligarchs 129–30, 140, 194, 197, 199, 202 Olympic Games 36 Onyeama, Dillibe 254 Operation Winthorpe 209 Organ, Bill 111–12 Orwell, George 3, 74, 76, 77, 254 and democracy 286, 309 Osborne, George 6, 144, 146, 147, 148, 153 and Brexit 162 and politics 274–5 and psychology 273 overseas franchises 202–6, 329 Oxbridge 1–2, 5, 264–5, 279, 300–6, 342–3; see also Cambridge University; Oxford University Oxford University 2, 16, 17, 18, 25, 107 and Cameron 141–2 and Union 125–6 Pakenham, Frank 180 Palmerston, Lord 33, 48 parents 194–6, 251–6, 257–8, 261–3, 265–7 and failure 278 and rights 337–8 Parker, Peter 62–3 Parris, Matthew 306, 314–15 Pasha, Emin 39 Patel, Priti 162 Patrick, Andrew 277 Paxman, Jeremy 223–4, 273 pay 298–9, 306–7 Peasants’ Revolt 16 Peat, Sir Michael 205 Peel, Robert 33 Percival, Arthur Ernest 73–4 Perry, Tom 210 Philby, Kim 133 Piers Gaveston Club 137, 141, 142–3 Pitt the Elder, William 28 Plato 313 Pleming, Richard 195 politics 91–3, 271–3, 274–5, 303–5; see also Conservative Party; government; Labour Party poor, the 16–17, 19–20, 22, 24, 28–9 and subsidised places 221–2, 224–7 Portillo, Michael 146 Portland Communications 169 ‘posh bashing’ 252–3 Powell, Enoch 93, 156–7 Powell, Hugh 138–40 prefects 21 Price, Leolin 115–16 Priestley, J.B. 76–7 private education, see public schools Profumo, John 92 property 310 psychology 270–3, 275–7 Public School Lodges’ Council 145, 193 public schools 2–7, 66–7, 258–61, 286–9, 324–5 and abolition 336–44 and abuse 207–20 and actors 252–3 and alumni 1–2, 140 and assisted places 87–8, 90, 101, 321–2, 329–33 and beginnings 15–20 and Brexit 161–2, 163, 165–6, 167, 170 and British Empire 33–4, 41, 42–3, 44–5 and business rates 243–4 and charity 88–9, 107–11, 114–21, 221–35 and class 22–4 and criticism 46–7 and demand 70–1 and entitlement 283–5 and espionage 132–3 and Europe 268–9 and facilities 193–4 and fees 111–14, 245–9 and funding 68–70 and government 91–3 and inequality 306–9 and international students 196–202 and Labour Party 180–3, 185–6 and London 316–18 and the media 297–300 and networks 21–2, 191–3, 289–91 and overseas franchises 202–6 and Oxbridge 300–6 and parents 194–6, 251–2, 253–6, 257–8, 261–3, 265–7 and psychology 270–3, 275–7 and reforms 25–7, 29–32, 47–51, 79–82, 95–100 and revolts 27–9 and Second World War 75–9 and slang 20–1 and society 334–6 and soldiers 52–64 and state schools 236–43, 326–7 Public Schools Act (1868) 51 Public Schools Commission 97–100 Puritans 27 Putin, Vladimir 127–32, 133, 154 Pyper, Mark 110 Queen’s Scholarship 19 Raab, Dominic 322 racism 156, 157, 162 Rae, John 101, 274, 302 Ragged School movement 29, 37, 38 Ranger, Terence 34 Rawls, John 5 Ray, Christopher 115 Reay, Diane 268, 269, 284–5, 335 Reckless, Mark 161 Redwood, John 161 Rees-Mogg, Jacob 31, 154, 161, 193, 251, 282 Referendum Party 155, 156 Reform Act (1832) 47 Reformation, the 26 Remain Vote 162, 163, 166, 168 Renton, Alex 219–20, 254 Repton School 302–3 Reznikov, Peter 131 Rhodes, Cecil 33, 43 Rich, Richard 11–12, 14 Richards, Amy 169 Richardson, Ed 197 Ripon Grammar School 67–8 Roberts, Frederick, Field Marshal Lord 52–3 Rock, Patrick 151–2 Roman Empire 13 Romilly, Peter 135 Rooney, Wayne 191 Rothermere, Jonathan Harmsworth, Lord 147 royal family 133, 134 Royal Military Academy Sandhurst 36, 38, 40, 56 Royal Military Academy Woolwich 36, 56 Royal Navy 44, 73 rugby 35 Rugby School 28, 31, 52, 53, 73 Ruskin, John 66 Russia 127–34, 139–40, 199–200, 202 Ruston, Mark 214 Sainsbury, David 163 St Paul’s School 14, 17, 18, 209, 227 Sandel, Michael J. 315–16 Sandhurst, see Royal Military Academy Sandhurst Sansom-Mallett, David 209 Sassoon, Siegfried 62 Sawar, Anas 186 Schaverien, Joy 270–1 Schellenberg, Walter Friedrich 3 Schneider, James 17, 177 scholarships 226–8, 240 School Teachers Superannuation Act (1918) 68 science 30 Scotland 43–4, 47, 186, 211, 341 Second World War 3, 40–1, 72–9, 82–4, 86–7 secondary schools 82, 90, 94–5 Sedbergh School 85 segregation 316 Seldon, Sir Anthony 192, 230, 242, 261, 331–3 serfdom 15 Sevenoaks School 111–12 sexual assault 207–20 Shaw, George Bernard 66 Shawcross, Hartley 99 Shawcross, William 117 Sherborne School 55, 70 Sherriff, Robert 56–7, 58 Shevkunov, Father Tikhon 130–1 Shrewsbury School 21–2, 30, 58 Shrosbree, Colin 31 Sidney, Sir Philip 21–2 Singapore 73–5 Sked, Alan 155 Smith, Ian Duncan 146, 161 Smith, Zadie 328 Smyth, John 211–12, 213–15, 216, 219 Soames, Nicholas 167 social media 165, 166 social mobility 93–4, 196, 311, 315, 321–2, 330–3 and Commission 336 socialism 86–7, 88, 95–6, 177–8 Socrates 313 song schools 14, 15 Spence, Dr Joseph 159, 160, 204, 241–2, 330–1 Spencer, Charles, 9th Earl 317 Spencer, Herbert 66 Spender, Stephen 70 Spielman, Amanda 252 spies 132–3 sponsorships 238–43 sport 20, 35–6, 233–4, 236–8 Stanley, Henry Morton 39, 40 Starkie, James 169 state schools 2, 6, 68, 83–4, 149, 318–20 and business rates 244 and Europe 268–9 and exams 257 and funds 265, 267 and Oxbridge 301–2 and parents 255–6 and public schools 120, 236–43, 326–7 Stephenson, George 32 Stephenson, Paul 168 Stewart, Rory 292 Stoics Club 142 Stowe School 233 Strachey, Lytton 38 Strategic Communication Laboratories (SCL) 164 Sudan 37, 38–40 Suez Crisis 91–2 super-rich 196–7 Sutton, Thomas 19, 233 Sutton Trust 116, 287, 296, 297, 303 Sweden 344 Taunton Commission 50 Tawney, R.H. 66, 89 taxation 243, 244–7, 248–9, 338–9; see also VAT teachers 257, 340 Thatcher, Margaret 93, 100, 101–2, 136, 138–9, 323 Thorn, John 213, 214 Timothy, Nick 121, 326 Titus Trust 215–16 Tom Brown’s School Days (Hughes) 35 Trades Union Congress 81 Transparency International 201–2 Trump, Donald 127, 163, 164, 280–2, 329 Turner, Andrew 233 Uber 151 UK Independence Party (UKIP) 155, 156, 157, 161 Ukraine 127, 128, 139–40 Ummuna, Chuka 179 United States of America 84, 164, 229, 280–2, 329 universities 260–1, 306, 308, 342–3; see also Oxbridge Utley, Tom 265–6 Vaizey, Ed 99 VAT (value added tax) 69, 107, 121, 183, 243, 247 Vereker, John 72–3 Victoria Cross (VC) 58–9 Villiers, Barbara 91 Villiers, Theresa 161–2 Viner, Katharine 67 Vote Leave 161–3, 164–6, 167–8 Vunipola, Billy 234 Wade, Rebekah 147 Waldegrave, William 342 Wang Sicong 198 Warre, Edmond 53 Warre-Dymond, Capt Godfrey 58 Warren, Justice 116 Wasserman, Gordon, Lord 102 Waterloo, Battle of 33, 42 Watson, Andrew 213 Waugh, Alec 55, 58, 59, 63, 67, 70, 254 wealth gap 309–10 Webb, Sidney 66 Welby, Justin, Archbishiop of Canterbury 79, 193, 212, 214, 216 Weller, Paul 136, 251–2 Wellington, Arthur Wellesley, Duke of 33, 41–2, 53 Wellington College 242 Westminster, Gerald Grosvenor, 6th Duke of 254 Westminster School 17, 18–19, 23, 43, 204 and Oxbridge 300, 302 Whetstone, Rachel 144, 145 Whitehouse, Mary 212 White’s 143–4, 169 Whittingdale, John 161, 177 Who’s Who 289, 292 Wilkinson, Ellen 87–8, 90 Willetts, David 93–4, 307–8 Wilshaw, Sir Michael 120, 205, 240, 340 Wilson, Harold 25, 95, 99, 180, 287 Winchester College 15–17, 23, 28, 81, 257 and abuse 212–14, 215 and bursaries 229, 230–2 and fees 111–12, 113 and international students 199–200 and Oxford 25, 301 and soldiers 52, 53 Witheridge, Rev.


pages: 462 words: 129,022

People, Power, and Profits: Progressive Capitalism for an Age of Discontent by Joseph E. Stiglitz

affirmative action, Affordable Care Act / Obamacare, Alan Greenspan, AlphaGo, antiwork, barriers to entry, basic income, battle of ideas, behavioural economics, Berlin Wall, Bernie Madoff, Bernie Sanders, Big Tech, business cycle, Cambridge Analytica, Capital in the Twenty-First Century by Thomas Piketty, carbon tax, carried interest, central bank independence, clean water, collective bargaining, company town, corporate governance, corporate social responsibility, creative destruction, Credit Default Swap, crony capitalism, DeepMind, deglobalization, deindustrialization, disinformation, disintermediation, diversified portfolio, Donald Trump, driverless car, Edward Snowden, Elon Musk, Erik Brynjolfsson, fake news, Fall of the Berlin Wall, financial deregulation, financial innovation, financial intermediation, Firefox, Fractional reserve banking, Francis Fukuyama: the end of history, full employment, George Akerlof, gig economy, Glass-Steagall Act, global macro, global supply chain, greed is good, green new deal, income inequality, information asymmetry, invisible hand, Isaac Newton, Jean Tirole, Jeff Bezos, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John von Neumann, Joseph Schumpeter, labor-force participation, late fees, low interest rates, low skilled workers, Mark Zuckerberg, market fundamentalism, mass incarceration, meta-analysis, minimum wage unemployment, moral hazard, new economy, New Urbanism, obamacare, opioid epidemic / opioid crisis, patent troll, Paul Samuelson, pension reform, Peter Thiel, postindustrial economy, price discrimination, principal–agent problem, profit maximization, purchasing power parity, race to the bottom, Ralph Nader, rent-seeking, Richard Thaler, Robert Bork, Robert Gordon, Robert Mercer, Robert Shiller, Robert Solow, Ronald Reagan, Savings and loan crisis, search costs, secular stagnation, self-driving car, shareholder value, Shoshana Zuboff, Silicon Valley, Simon Kuznets, South China Sea, sovereign wealth fund, speech recognition, Steve Bannon, Steve Jobs, surveillance capitalism, TED Talk, The Chicago School, The Future of Employment, The Great Moderation, the market place, The Rise and Fall of American Growth, the scientific method, The Wealth of Nations by Adam Smith, too big to fail, trade liberalization, transaction costs, trickle-down economics, two-sided market, universal basic income, Unsafe at Any Speed, Upton Sinclair, uranium enrichment, War on Poverty, working-age population, Yochai Benkler

But we have seen a far more sinister side, as, for instance, Russia has repeatedly interfered in democratic elections, seemingly in an attempt to undermine confidence in Western democracy. The new technologies can be used for manipulation, not only to enhance economic profits, but also to foster certain views, and cast doubt on others. Those with more money can do this better—and the family of Robert Mercer and others who funded Cambridge Analytica in their secretive and subversive attempt to manipulate the 2016 election have shown how it can be done. Thus, the new technologies have opened a new avenue through which power and money begets more power and money. A host of reforms have been proposed, none convincingly up to the task.

., 176, 180 knowledge and growth, 183–86 and productivity, xxiv as public good, 141 Trump’s disdain for, xvii and wealth of nations, 9 knowledge-based economy, 237 knowledge gap, 96, 98 knowledge institutions, undermining of, 233–34 Koch brothers, 20, 43, 279n40 Krueger, Alan, 42 Kurz, Mordecai, 54 Kuznets, Simon, 258n9 Kuznets’s Law, 258n9 labeling of food, 88 labor contracts, 73 labor force participation, 42, 181–83, 193 labor income, 51, 54 labor markets, atomistic, 64–66 Land O’Lakes, 352n23 learning society, creating, 183–86 Lee Se-dol, 315n1 legal system, bypassing by arbitration panels, 56–57 lending, 110–11; See also credit Levin, Carl, 311n6 liberalization of markets, See market liberalization life, quality of, 209–21; See also standards of living life expectancy, 14, 41 Lighthizer, Robert, xvi living standards, See standards of living loans, See credit lobbyists, 85, 102, 107, 206, 220 local market power, 61 location-based policies, 187–88 long-term investors, 106 long-term savers, 106 long-term unemployment, insurance for, 189 loopholes, in 2017 tax bill, xvii–xix, 85, 194, 206, 237 low-income trap, 44 low-skilled workers automation and, 118, 119, 122 competitive labor markets and, 198 globalization and, 21, 82, 86 job polarization and, 119 social justice and, 198 trade agreements and, 80 Luther, Martin, 10 machines, as workers, 119 MacLean, Nancy, 160 macroeconomic factors, 89, 190 macro economy, 194 Madoff, Bernie, 145, 311n4 majority rights, voting reform and, 161 Malthus, Thomas Robert, 9 Manchester, England, 188 mandatory voting, 172 manufacturing, tariffs and, 91 March on Washington for Jobs and Freedom (1963), 176 market concentration, 55–57, 108 market economy, 30 market failures, 209–10, 214–16 market forces, as impersonal, 51 market fundamentalism, 150, 239 market liberalization, xiii, 4, 21–22 marketplace of ideas, 75–76 market power, 47–78 and AI, 123–35 antitrust laws to curb, 68–76 and Big Data, 128 creating wealth vs. taking wealth, 49–50 diminishing share of labor and capital, 52–54 and division of national income pie, 51–52 of employers over workers, 64–67 implicit rules of economic game, 62 increase in, 54–62 as inimical to growth, 62–64, 183 and innovation, 57–60, 63–64 and intellectual property rights, 74–75 and labor markets, 64–67 in marketplace of ideas, 75–76 and mergers, 72–73, 108 need to constrain excesses of, 70–72 and political divide, 234 and private investment in research, 184 reasons for increases in, 61 and rents, 54 and technology, 73–74, 122 and wage suppression, 65–66 markets as basis for economy, xii–xiii excessive faith in, 154 failure to achieve full employment, 193–94 failure to address work–life balance, 192 failure to create prosperity, xxii–xxiv failure to provide public goods, 140–41 government’s role in managing, 180 limits of, 24 as means rather than ends, 24 need to restructure, 244 markups, 55, 62 Marshall, John, 241 mass incarceration, See incarceration MasterCard, 60 materialism, 30 media and marketplace of ideas, 75–76 and myth of American Dream, 225 and society’s checks and balances, 11 Trump’s attacks on, 15 Medicare, 13, 142, 168, 210 men, in labor force, 38, 42 mercantilism, 8, 240 Mercer, Robert, 132 merchant fees, 60, 70 mergers banks’ profits from, 107–8 and market power, 72–73 in media outlets, 75 preemptive, 60–61, 70, 73 vertical, 325n17 Merkel, Angela, 268n42 “Mickey Mouse” provision, 74 Microsoft, 58, 75, 325n17 middle-class societies, 13 migrant labor, 163 minimum wage, 86, 87, 199, 274n21 MIT (Massachusetts Institute of Technology), 16 moats, 48, 57–58, 62–63; See also barriers to entry/competition mobility, place-based policies and, 188 monetary policy, 83, 121 money in politics, 167–70; See also campaign spending agenda for reducing power of, 171–74 campaign spending, 171–73 as cause of current problems, 239 Citizens United case, 166, 169–70, 172 curbing influence of, 176–78 disclosure laws, 171 revolving doors and, 173–74 technology and, 132, 246 voting reform and, 162–63 money laundering, 168, 169 monopoly defined, 55 and income inequities, 198 and intellectual property rights, 74–75 natural, 61, 134 and net neutrality, 148 perfect competition vs., 56 and rents, 52 tech companies and Big Data, 131 monopsony, 64, 198 moral sentiments, 229 moral turpitude, 7, 30, 103, 240 mortgage risk, 107 mortgage system, 216–18 movements, need for new, 174–76 multilateral trade deficit, 90–91 multinational corporations, tax avoidance by, 85, 99, 108 multinational development banks, 106 Murdoch, Robert, 133, 177 Musk, Elon, 266n33 Muslim travel ban, 165 Myriad, 126–27 myths, failings masked by, 224–26 National Defense Education Act, 210 National Federation of Independent Business v.


Mindf*ck: Cambridge Analytica and the Plot to Break America by Christopher Wylie

4chan, affirmative action, Affordable Care Act / Obamacare, air gap, availability heuristic, Berlin Wall, Bernie Sanders, Big Tech, big-box store, Boris Johnson, Brexit referendum, British Empire, call centre, Cambridge Analytica, Chelsea Manning, chief data officer, cognitive bias, cognitive dissonance, colonial rule, computer vision, conceptual framework, cryptocurrency, Daniel Kahneman / Amos Tversky, dark pattern, dark triade / dark tetrad, data science, deep learning, desegregation, disinformation, Dominic Cummings, Donald Trump, Downton Abbey, Edward Snowden, Elon Musk, emotional labour, Etonian, fake news, first-past-the-post, gamification, gentleman farmer, Google Earth, growth hacking, housing crisis, income inequality, indoor plumbing, information asymmetry, Internet of things, Julian Assange, Lyft, Marc Andreessen, Mark Zuckerberg, Menlo Park, move fast and break things, Network effects, new economy, obamacare, Peter Thiel, Potemkin village, recommendation engine, Renaissance Technologies, Robert Mercer, Ronald Reagan, Rosa Parks, Sand Hill Road, Scientific racism, Shoshana Zuboff, side project, Silicon Valley, Skype, Stephen Fry, Steve Bannon, surveillance capitalism, tech bro, uber lyft, unpaid internship, Valery Gerasimov, web application, WikiLeaks, zero-sum game

He was fully on board. In fact, he called the SCL office after reading the report and was almost giddy. “This is so great, guys,” he kept saying. Now we just had to persuade Robert Mercer. * * * — A COUPLE OF WEEKS after this, one evening in late November 2013, Nix called me at home. “Pack a bag,” he said. “You’re flying to New York tomorrow.” He, Tadas Jucikas, and I were going to present our findings to Robert Mercer and his daughter Rebekah. Nix flew out first thing in the morning, but for some reason he’d booked Jucikas and me on a later flight. We landed at JFK around four in the afternoon, with our meeting scheduled to start at five.

I called Nix to tell him how everything had gone—and that I needed a new ticket. “Chris, I’m busy, sort it out yourself.” * * * — BANNON’S INTEREST IN OUR work wasn’t merely academic; he had big ideas for SCL. He told Nix of a major right-wing donor who might be persuaded to make an investment in the firm. Robert Mercer was unusual for a billionaire. He’d gotten a Ph.D. in computer science in the early 1970s, then went on to become a cog in the wheel at IBM for twenty-some years. In 1993, he joined a hedge fund called Renaissance Technologies, where he used data science and algorithms to inform his investments—and made a stupid amount of money doing it.

This was a no-brainer. I asked Stillwell if I could run some tests on their data. I wanted to see if we could replicate our results from Trinidad, where we had access to similar types of Internet browsing data. If the Facebook profiles proved as valuable as I hoped, we would not only be able to fulfill Robert Mercer’s desire to create a powerful tool—what was even cooler was that we could mainstream a whole new field of academia: computational psychology. We were standing at the frontier of a new science of behavioral simulation and I was bursting with excitement at the prospect. * * * — FACEBOOK LAUNCHED IN 2004 as a platform to connect students and peers in college.


pages: 388 words: 111,099

Democracy for Sale: Dark Money and Dirty Politics by Peter Geoghegan

4chan, Adam Curtis, Affordable Care Act / Obamacare, American Legislative Exchange Council, anti-globalists, basic income, Berlin Wall, Big Tech, Black Lives Matter, Boris Johnson, Brexit referendum, British Empire, Cambridge Analytica, centre right, corporate raider, crony capitalism, data science, deepfake, deindustrialization, demographic winter, disinformation, Dominic Cummings, Donald Trump, East Village, Etonian, F. W. de Klerk, fake news, first-past-the-post, Francis Fukuyama: the end of history, Frank Gehry, Greta Thunberg, invisible hand, James Dyson, Jeremy Corbyn, John Bercow, Mark Zuckerberg, market fundamentalism, military-industrial complex, moral panic, Naomi Klein, Nelson Mandela, obamacare, offshore financial centre, open borders, Overton Window, Paris climate accords, plutocrats, post-truth, post-war consensus, pre–internet, private military company, Renaissance Technologies, Robert Mercer, Ronald Reagan, Silicon Valley, Snapchat, special economic zone, Steve Bannon, surveillance capitalism, tech billionaire, technoutopianism, Torches of Freedom, universal basic income, WikiLeaks, Yochai Benkler, éminence grise

The Koch brothers, David and Charles, co-owners of the second-largest private company in the United States with strong interests in coal and petroleum, spent more than $1.5 billion on Republican political causes until David’s death in 2019. The pair bankrolled countless conservative think tanks and politicians. Trump’s biggest backers included hedge fund billionaire Robert Mercer, whose data firm Cambridge Analytica also worked on Trump’s presidential campaign. In America, elections involving hundreds of millions of voters have become contests decided, in key constituencies, by a handful of plutocrats. In Britain, money has long played a determining role in politics. The ‘rotten boroughs’ of the 18th and 19th centuries were notoriously crooked, and their tiny electorates could be bought by influential patrons.

In an October 2015 diary entry in The Bad Boys of Brexit, Banks writes that Leave.EU had “hired Cambridge Analytica, an American company that uses ‘big data and advanced psychographics’ to influence people”.40 Cambridge Analytica, which went on to work for the Trump campaign, had a burgeoning reputation as the cutting edge in election black-ops. It was bankrolled by radical libertarian hedge fund billionaire and Trump backer Robert Mercer. His daughter Rebekah sat on the board, alongside Nigel Farage’s friend Steve Bannon. At the time, Cambridge Analytica was working on Republican presidential hopeful Ted Cruz’s campaign, boasting of using psychological data gleaned from tens of millions of Facebook users.41 This would later be at the centre of the scandal that brought down the company.

The firm later went into administration.27) This faith in monetarism brought him into the orbit of dark money-funded US conservative groups. In 2015, American Principles in Action paid for Baker to attend a conference on global finance in Jackson Hole, Wyoming. The conservative think tank has received funding from Robert Mercer and the Koch brothers. Another libertarian outfit, the American Liberty Fund, picked up the tab for Baker’s attendance at similar events in Britain, Italy and the US.28 Baker has also spoken at the Antigua Forum in Guatemala. Billed as “the accelerator for freedom”, this invitation-only gathering has featured an unlikely smattering of libertarians from around the world.


pages: 391 words: 123,597

Targeted: The Cambridge Analytica Whistleblower's Inside Story of How Big Data, Trump, and Facebook Broke Democracy and How It Can Happen Again by Brittany Kaiser

"World Economic Forum" Davos, Albert Einstein, Amazon Mechanical Turk, Asian financial crisis, Bernie Sanders, Big Tech, bitcoin, blockchain, Boris Johnson, Brexit referendum, Burning Man, call centre, Cambridge Analytica, Carl Icahn, centre right, Chelsea Manning, clean water, cognitive dissonance, crony capitalism, dark pattern, data science, disinformation, Dominic Cummings, Donald Trump, Edward Snowden, Etonian, fake news, haute couture, illegal immigration, Julian Assange, Mark Zuckerberg, Menlo Park, Nelson Mandela, off grid, open borders, public intellectual, Renaissance Technologies, Robert Mercer, rolodex, Russian election interference, sentiment analysis, Sheryl Sandberg, Silicon Valley, Silicon Valley startup, Skype, Snapchat, statistical model, Steve Bannon, subprime mortgage crisis, TED Talk, the High Line, the scientific method, WeWork, WikiLeaks, you are the product, young professional

“The Facebook Dilemma,” Frontline, PBS, October 29, 2018. 6.Ibid. 7.Ibid. 8.Ibid. 9: PERSUASION 1.James Swift, “Contagious Interviews Alexander Nix,” Contagious.com, September 28, 2016, https://www.contagious.com/news-and-views/interview-alexander-nix. 10: UNDER THE INFLUENCE 1.Jane Mayer, “The Reclusive Hedge-Fund Tycoon Behind the Trump Presidency,” The New Yorker, March 27, 2017, https://www.newyorker.com/magazine/2017/03/27/the-reclusive-hedge-fund-tycoon-behind-the-trump-presidency. 2.Jim Zarroli, “Robert Mercer Is a Force to Be Reckoned with in Finance and Conservative Politics,” NPR.org, May 26, 2017, https://www.npr.org/2017/05/26/530181660/robert-mercer-is-a-force-to-be-reckoned-with-in-finance-and-conservative-politic?t=1562072425069. 3.Gray, “What Does the Billionaire Family Backing Donald Trump Really Want?” 4.Matt Oczkowski, Molly Schweickert, “DJT Debrief Document.

What was more, according to the article, Cambridge was using that data as a weapon to affect the outcome of the Republican primaries and make Ted Cruz the GOP nominee.1 The story read like the plot of a spy novel. In it, reporter Harry Davies alleged that Cambridge had covertly acquired the Facebook data set and was now “embedded” in the Cruz campaign and deploying a powerful secret psyops weapon for targeting vulnerable voters. Behind the plot was the owner of Cambridge Analytica, Robert Mercer, who was, according to the Davies piece, a Dr. Evil–like American billionaire whose motivation was to disrupt the U.S. political system and advance a fringe right-wing agenda. The method Cambridge had used to acquire the data put it in direct violation of Facebook’s terms of service. CA had contracted with a man who himself violated Facebook’s service agreement when he used a third-party app, the infamous Friends API, to “hoover up” vast amounts of private information.

As it was, the ICO’s investigation determined there was “no evidence of a working relationship between [Cambridge Analytica] and Leave.EU proceeding beyond this initial phase.”2 A few days later, on a Saturday, an investigative journalist named Carole Cadwalladr published an article in the Guardian that took a long, hard look at what she alleged was a connection between Cambridge Analytica, Leave.EU, and Robert Mercer. Coming hot on the heels of the Das Magazin piece, which had slightly rattled Cambridge’s cage with claims that we had stolen user data and weaponized it to unethical ends, the Cadwalladr article was a hard blow. Cadwalladr’s article focused on campaign spending issues in general, including a potential violation even by Vote Leave, the Brexit campaign that had won the designation over Leave.EU.


pages: 918 words: 257,605

The Age of Surveillance Capitalism by Shoshana Zuboff

"World Economic Forum" Davos, algorithmic bias, Amazon Web Services, Andrew Keen, augmented reality, autonomous vehicles, barriers to entry, Bartolomé de las Casas, behavioural economics, Berlin Wall, Big Tech, bitcoin, blockchain, blue-collar work, book scanning, Broken windows theory, California gold rush, call centre, Cambridge Analytica, Capital in the Twenty-First Century by Thomas Piketty, Cass Sunstein, choice architecture, citizen journalism, Citizen Lab, classic study, cloud computing, collective bargaining, Computer Numeric Control, computer vision, connected car, context collapse, corporate governance, corporate personhood, creative destruction, cryptocurrency, data science, deep learning, digital capitalism, disinformation, dogs of the Dow, don't be evil, Donald Trump, Dr. Strangelove, driverless car, Easter island, Edward Snowden, en.wikipedia.org, Erik Brynjolfsson, Evgeny Morozov, facts on the ground, fake news, Ford Model T, Ford paid five dollars a day, future of work, game design, gamification, Google Earth, Google Glasses, Google X / Alphabet X, Herman Kahn, hive mind, Ian Bogost, impulse control, income inequality, information security, Internet of things, invention of the printing press, invisible hand, Jean Tirole, job automation, Johann Wolfgang von Goethe, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joseph Schumpeter, Kevin Kelly, Kevin Roose, knowledge economy, Lewis Mumford, linked data, longitudinal study, low skilled workers, Mark Zuckerberg, market bubble, means of production, multi-sided market, Naomi Klein, natural language processing, Network effects, new economy, Occupy movement, off grid, off-the-grid, PageRank, Panopticon Jeremy Bentham, pattern recognition, Paul Buchheit, performance metric, Philip Mirowski, precision agriculture, price mechanism, profit maximization, profit motive, public intellectual, recommendation engine, refrigerator car, RFID, Richard Thaler, ride hailing / ride sharing, Robert Bork, Robert Mercer, Salesforce, Second Machine Age, self-driving car, sentiment analysis, shareholder value, Sheryl Sandberg, Shoshana Zuboff, Sidewalk Labs, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, slashdot, smart cities, Snapchat, social contagion, social distancing, social graph, social web, software as a service, speech recognition, statistical model, Steve Bannon, Steve Jobs, Steven Levy, structural adjustment programs, surveillance capitalism, technological determinism, TED Talk, The Future of Employment, The Wealth of Nations by Adam Smith, Tim Cook: Apple, two-sided market, union organizing, vertical integration, Watson beat the top human players on Jeopardy!, winner-take-all economy, Wolfgang Streeck, work culture , Yochai Benkler, you are the product

This process begins with business plans and marketing messages, new products and services, and journalistic representations that appear to accept the new facts as given.73 Among this new cohort of mercenaries was Cambridge Analytica, the UK consulting firm owned by the reclusive billionaire and Donald Trump backer Robert Mercer. The firm’s CEO, Alexander Nix, boasted of its application of personality-based “micro-behavioral targeting” in support of the “Leave” and the Trump campaigns during the ramp-up to the 2016 Brexit vote and the US presidential election.74 Nix claimed to have data resolved “to an individual level where we have somewhere close to four or five thousand data points on every adult in the United States.”75 While scholars and journalists tried to determine the truth of these assertions and the role that these techniques might have played in both 2016 election upsets, the firm’s new chief revenue officer quietly announced the firm’s less glamorous but more lucrative postelection strategy: “After this election, it’ll be full-tilt into the commercial business.”

“Introducing FBLearner Flow: Facebook’s AI Backbone,” Facebook Code, April 16, 2018, https://code.facebook.com/posts/1072626246134461/introducing-fblearner-flow-facebook-s-ai-backbone. 79. Andy Kroll, “Cloak and Data: The Real Story Behind Cambridge Analytica’s Rise and Fall,” Mother Jones, March 24, 2018, https://www.motherjones.com/politics/2018/03/cloak-and-data-cambridge-analytica-robert-mercer. 80. Carole Cadwalladr, “‘I Made Steve Bannon’s Psychological Warfare Tool’: Meet the Data War Whistleblower,” Guardian, March 18, 2018, http://www.the guardian.com/news/2018/mar/17/data-war-whistleblower-christopher-wylie-faceook-nix-bannon-trump; Kroll, “Cloak and Data.” 81. Matthew Rosenberg, Nicholas Confessore, and Carole Cadwalladr, “How Trump Consultants Exploited the Facebook Data of Millions,” New York Times, March 17, 2018, https://www.nytimes.com/2018/03/17/us/politics/cambridge-analytica-trump-campaign.html; Emma Graham-Harrison and Carole Cadwalladr, “Revealed: 50 Million Facebook Profiles Harvested for Cambridge Analytica in Major Data Breach,” Guardian, March 17, 2018, http://www.theguardian.com/news/2018/mar/17/cambridge-analytica-facebook-influence-us-election; Julia Carrie Wong and Paul Lewis, “Facebook Gave Data About 57bn Friendships to Academic,” Guardian, March 22, 2018, http://www.theguardian.com/news/2018/mar/22/facebook-gave-data-about-57bn-friendships-to-academic-aleksandr-kogan; Olivia Solon, “Facebook Says Cambridge Analytica May Have Gained 37m More Users’ Data,” Guardian, April 4, 2018, http://www.theguardian.com/technology/2018/apr/04/facebook-cambridge-analytica-user-data-latest-more-than-thought. 82.

See also means of behavioral modification Meckling, William, 38 media use, international study of “unplugging” from, 445, 446 medical fields: and emotion analytics, 288; and internet of things, 247–251 mental health: depression, 275, 287, 446, 464–465; and Facebook use, 446, 463–465; monitoring of, 412; predictions of, 275 Mercer, Robert, 278 Mercury News, 116 meta-data, 117–118, 245, 272–273, 275 Meyer, Max, 362–363, 363–364, 364–366, 372, 412, 633n39, 634n42, 634n44, 635n45 Meyer, Michelle, 304 m-health (mobile health apps), 248–251 Michaels, Jon, 119 Microsoft, 24, 400; Bing search engine, 95, 162, 163; collaboration with metal-cutting factory, 407–409; Cortana digital assistant, 163–164, 165, 255, 400; Inktomi search engine, 71; and insurers, 217; patents filed by, 411–412; revenues of, 165–166, 405; surveillance capitalism spreads to, 9, 162–163; and voice recognition, 263; Windows 10 operating system, 164–165.


pages: 533

Future Politics: Living Together in a World Transformed by Tech by Jamie Susskind

3D printing, additive manufacturing, affirmative action, agricultural Revolution, Airbnb, airport security, algorithmic bias, AlphaGo, Amazon Robotics, Andrew Keen, Apollo Guidance Computer, artificial general intelligence, augmented reality, automated trading system, autonomous vehicles, basic income, Bertrand Russell: In Praise of Idleness, Big Tech, bitcoin, Bletchley Park, blockchain, Boeing 747, brain emulation, Brexit referendum, British Empire, business process, Cambridge Analytica, Capital in the Twenty-First Century by Thomas Piketty, cashless society, Cass Sunstein, cellular automata, Citizen Lab, cloud computing, commons-based peer production, computer age, computer vision, continuation of politics by other means, correlation does not imply causation, CRISPR, crowdsourcing, cryptocurrency, data science, deep learning, DeepMind, digital divide, digital map, disinformation, distributed ledger, Donald Trump, driverless car, easy for humans, difficult for computers, Edward Snowden, Elon Musk, en.wikipedia.org, end-to-end encryption, Erik Brynjolfsson, Ethereum, ethereum blockchain, Evgeny Morozov, fake news, Filter Bubble, future of work, Future Shock, Gabriella Coleman, Google bus, Google X / Alphabet X, Googley, industrial robot, informal economy, intangible asset, Internet of things, invention of the printing press, invention of writing, Isaac Newton, Jaron Lanier, John Markoff, Joseph Schumpeter, Kevin Kelly, knowledge economy, Large Hadron Collider, Lewis Mumford, lifelogging, machine translation, Metcalfe’s law, mittelstand, more computing power than Apollo, move fast and break things, natural language processing, Neil Armstrong, Network effects, new economy, Nick Bostrom, night-watchman state, Oculus Rift, Panopticon Jeremy Bentham, pattern recognition, payday loans, Philippa Foot, post-truth, power law, price discrimination, price mechanism, RAND corporation, ransomware, Ray Kurzweil, Richard Stallman, ride hailing / ride sharing, road to serfdom, Robert Mercer, Satoshi Nakamoto, Second Machine Age, selection bias, self-driving car, sexual politics, sharing economy, Silicon Valley, Silicon Valley startup, Skype, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, smart contracts, Snapchat, speech recognition, Steve Bannon, Steve Jobs, Steve Wozniak, Steven Levy, tech bro, technological determinism, technological singularity, technological solutionism, the built environment, the Cathedral and the Bazaar, The Structural Transformation of the Public Sphere, The Wisdom of Crowds, Thomas L Friedman, Tragedy of the Commons, trolley problem, universal basic income, urban planning, Watson beat the top human players on Jeopardy!, work culture , working-age population, Yochai Benkler

Peter Martinez, ‘Study Reveals Whopping 48M Twitter Accounts Are Actually Bots’, CBS News, 10 March 2017 <http://www.cbsnews. com/news/48-million-twitter-accounts-bots-university-ofsouthern-california-study/?ftag=CNM-00-10aab7e&linkId= 35386687> (accessed 1 December 2017). 18. Carole Cadwalladr, ‘Robert Mercer:The Big Data Billionaire Waging War on Mainstream Media’, The Guardian, 26 February 2017 <https:// www.theguardian.com/politics/2017/feb/26/robert-mercer-breitbart-war-on-media-steve-bannon-donald-trump-nigel-farage> (accessed 1 December 2017). 19. See Leo Kelion and Shiroma Silva, ‘Pro-Clinton Bots “Fought Back but Outnumbered in Second Debate” ’, BBC News, 19 October 2016<http://www.bbc.com/news/technology-37703565> (accessed 1 December 2017); Amanda Hess, ‘On Twitter, a Battle Among Political Bots’, New York Times, 14 December 2016 <https://mobile. nytimes.com/2016/12/14/arts/on-twitter-a-battle-among-politicalbots.html?

MIT Technology Review, 7 Feb. 2017 <https://www.technologyreview.com/s/603431/as-goldman-embracesautomation-even-the-masters-of-the-universe-are-threatened/ ? s e t = 6 0 3 5 8 5 & u t m _ c o n t e n t = bu f f e rd 5 a 8 f & u t m _ m e d i u m = social&utm_source=twitter.com&utm_campaign=buffer> (accessed 1 Dec. 2017). Cadwalladr, Carole. ‘Robert Mercer: The Big Data Billionaire Waging War on Mainstream Media’. The Guardian, 26 Feb. 2017 <https://www. theguardian.com/politics/2017/feb/26/robert-mercer-breitbart-war-onmedia-steve-bannon-donald-trump-nigel-farage> (accessed 1 Dec. 2017). Calabresi, Guido, and Philip Bobbit. Tragic Choices: The Conflicts Society Confronts in the Allocation of Tragically Scarce Resources.

‘Joseph Schumpeter’, Wikipedia, last edited 23 December 2017 <https://en.wikipedia.org/wiki/Joseph_Schumpeter> (accessed 21 January 2018). 35. Pedro Domingos, The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World (London: Allen Lane, 2015), 17. 36. Carole Cadwalladr, ‘Robert Mercer:The Big Data Billionaire Waging War on Mainstream Media’, The Guardian, 26 February 2017 <https:// www.theguardian.com/politics/2017/feb/26/robert-mercerbreitbart-war-on-media-steve-bannon-donald-trump-nigel-farage> (accessed 1 December 2017). 37. Edward L. Bernays, ‘The Engineering of Consent’, ANNALS of the American Academy of Political and Social Science 250, no. 1 (1947), 113–20, cited in Zeynep Tufekci, ‘Engineering the Public: Big Data, Surveillance and Computational Politics’, First Monday 19, no. 7 (7 July 2014). 38.


pages: 170 words: 49,193

The People vs Tech: How the Internet Is Killing Democracy (And How We Save It) by Jamie Bartlett

Ada Lovelace, Airbnb, AlphaGo, Amazon Mechanical Turk, Andrew Keen, autonomous vehicles, barriers to entry, basic income, Bernie Sanders, Big Tech, bitcoin, Black Lives Matter, blockchain, Boris Johnson, Californian Ideology, Cambridge Analytica, central bank independence, Chelsea Manning, cloud computing, computer vision, creative destruction, cryptocurrency, Daniel Kahneman / Amos Tversky, data science, deep learning, DeepMind, disinformation, Dominic Cummings, Donald Trump, driverless car, Edward Snowden, Elon Musk, Evgeny Morozov, fake news, Filter Bubble, future of work, general purpose technology, gig economy, global village, Google bus, Hans Moravec, hive mind, Howard Rheingold, information retrieval, initial coin offering, Internet of things, Jeff Bezos, Jeremy Corbyn, job automation, John Gilmore, John Maynard Keynes: technological unemployment, John Perry Barlow, Julian Assange, manufacturing employment, Mark Zuckerberg, Marshall McLuhan, Menlo Park, meta-analysis, mittelstand, move fast and break things, Network effects, Nicholas Carr, Nick Bostrom, off grid, Panopticon Jeremy Bentham, payday loans, Peter Thiel, post-truth, prediction markets, QR code, ransomware, Ray Kurzweil, recommendation engine, Renaissance Technologies, ride hailing / ride sharing, Robert Mercer, Ross Ulbricht, Sam Altman, Satoshi Nakamoto, Second Machine Age, sharing economy, Silicon Valley, Silicon Valley billionaire, Silicon Valley ideology, Silicon Valley startup, smart cities, smart contracts, smart meter, Snapchat, Stanford prison experiment, Steve Bannon, Steve Jobs, Steven Levy, strong AI, surveillance capitalism, TaskRabbit, tech worker, technological singularity, technoutopianism, Ted Kaczynski, TED Talk, the long tail, the medium is the message, the scientific method, The Spirit Level, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, theory of mind, too big to fail, ultimatum game, universal basic income, WikiLeaks, World Values Survey, Y Combinator, you are the product

In 2008, for example, analysts working for Barack Obama assigned a pair of scores to every voter in the country that predicted how likely they were to cast a ballot, and whether they supported his campaign.7 Hillary Clinton, too, had an extremely sophisticated system of targeting voters online.8 Every election now is a mini arms race. And this time the Republican Party turned to a company, Cambridge Analytica, in order to get the edge on the opposition. It was not a coincidental choice. One of Cambridge Analytica’s key investors is the billionaire businessman and Trump backer Robert Mercer, a famously reclusive computer programmer who made his fortune as co-chief executive of the New York-based hedge fund, Renaissance Technologies. RenTech, as it is known, uses big data and sophisticated algorithms to predict trends in global markets and place winning bets on them. In this world tiny gains, a fraction of a per cent here or there, can yield huge rewards.

But the more politics becomes a question of smart analysis and nudges rather than argument, the further power will shift away from those with good ideas and towards those with good data and lots of money. * * * • • • It turned out that Project Alamo was a small piece of a much bigger puzzle in which influential people battled over the shape of reality. Robert Mercer had also invested in Breitbart News – best described as a right-wing Huffington Post that specialises in stories castigating liberals, bad Muslims, and the ‘mainstream media’ – which became a highly influential source of anti-Clinton and pro-Trump news. According to the academic Jonathan Albright, the US election was dominated by a ‘micro-propaganda machine’, a network of thousands of web pages from the radical right hyper-linking to each other and spreading ‘false, hyper-biased, and politically loaded information’.


pages: 1,294 words: 210,361

The Emperor of All Maladies: A Biography of Cancer by Siddhartha Mukherjee

Apollo 11, Barry Marshall: ulcers, belling the cat, conceptual framework, discovery of penicillin, experimental subject, government statistician, Great Leap Forward, Gregor Mendel, Helicobacter pylori, iterative process, Joan Didion, life extension, longitudinal study, Louis Pasteur, medical residency, meta-analysis, mouse model, New Journalism, phenotype, Plato's cave, randomized controlled trial, Recombinant DNA, Robert Mercer, scientific mainstream, Silicon Valley, social contagion, social web, statistical model, stem cell, women in the workforce, Year of Magical Thinking, éminence grise

By the early winter of 1948, more children were at his clinic: a three-year-old boy brought with a sore throat, a two-and-a-half-year-old girl with lumps in her head and neck, all eventually diagnosed with childhood ALL. Deluged with antifolates from Yella and with patients who desperately needed them, Farber recruited additional doctors to help him: a hematologist named Louis Diamond, and a group of assistants, James Wolff, Robert Mercer, and Robert Sylvester. Farber had infuriated the authorities at Children’s Hospital with his first clinical trial. With this, the second, he pushed them over the edge. The hospital staff voted to take all the pediatric interns off the leukemia chemotherapy unit (the atmosphere in the leukemia wards, it was felt, was far too desperate and experimental and thus not conducive to medical education)—in essence, leaving Farber and his assistants to perform all the patient care themselves.

., 26 Marlboro Man, 251 Marmite, 28 Marshall, Barry, 276, 281, 282–84, 456 Martin, Steve, 358 Masi, Phil, 97–98 Massachusetts, 325 Massachusetts General Hospital, 3, 56, 223, 320, 390, 398, 403, 437, 451 mastectomies, 49, 419 of Atossa, 5, 41–42, 463 disfigurement from, 65–66, 294 prophylactic, 457–58, 464 radical, 23, 64–72, 73, 109–10, 173, 193–95, 196, 197, 198–201, 202, 218, 219, 225, 294, 463 simple (local), 67, 197, 201, 464 success rate of, 66–69 Master Settlement Agreement (MSA), 273 Matter, Alex, 432–33 mauve, 81–82 Mayer, Robert, 130–31, 311, 326, 328 Mayfield, Jerry, 441, 442–43 MD Anderson Cancer Center, 147, 366, 438 measurement: of leukemia, 19 of negative claims, 167–68 of radiation, 74 in War on Cancer, 227, 231, 232–33 Medical and Chirurgical Society, 157 Medical Journal of Australia, 283 Medical Research Council (British), 131, 243–44 Medical World News, 349 medicine: synthetic chemistry and, 83–84 as technological art, 462 Mek protein, 387, 454 melanoma, 451 Memorial Sloan-Kettering, 92, 135, 138, 167n, 184, 234, 424 Mendel, Gregor, 343–44, 346, 364, 366, 369 meningiomas, 71 menopausal symptoms, 456 Mercer, Robert, 34 Merck, 21 Meselson, Matthew, 345 meta-analysis, 261 metastasis, metastases, 16, 38, 39, 55, 58, 123, 135, 136, 154, 161, 196–97, 204, 223, 391, 442, 465, 467 of breast cancer, 67, 76, 161, 217, 218, 302–3, 314, 322, 325, 329, 419, 422, 424, 463, 465 of Hodgkin’s lymphoma, 163 as inevitable, 79 of lung cancer, 208, 256, 267, 268, 307, 389–90, 403 methotrexate, 127, 132–33, 137, 138, 140, 162, 164, 219, 220, 338 Mexico, cigarette regulation in, 274 Meyer, Willy, 65, 78–79, 80, 219 mice, transgenic, 382–83, 384 microtubules, 140 Middle Ages, medical knowledge in, 49–50, 51–53 Million Women Study, 456 Milosz, Czeslaw, 116 Milstein, Cesar, 417, 419 Ministry of Health, British, 243 Ministry of Health, Mexican, 274 Minot, George, 27–28, 29 Mississippi, antitobacco lawsuit of, 272–73 mitosis, 451 mitosis, pathological, 348, 351, 355, 359, 387, 391 see also hyperplasia, pathological Mizutani, Satoshi, 353 molecular biology, “central dogma” of, 346, 352, 354, 357 molecular pumps, 442 molecules: decoy, 31, 87 structural view of, 432 as switches, 28 see also receptors Moloney, William, 143 Monod, Jacques, 20, 345, 346 mononucleosis, 175 Montagnier, Luc, 318 Moore, Charles, 64 Moore, Michael, 272–73 MOPP, 164–66, 208 Morbid Anatomy of Some of the Most Important Parts of the Human Body, The (Baillie), 53 Morgan, Thomas Hunt, 344, 346, 347–48, 364 Morison, Robert, 116 morphine, 63, 149, 225 mortality rates, of cancer, xi, 25, 105, 228–30, 293, 401 age-adjusted, 230–31, 232–33, 330 of breast cancer, 296, 297, 300–301, 401–2 dynamic equilibrium in, 330–31 mortality rates, of tuberculosis, 229 Morton, William, 56 motility, of cancer cells, 386, 387, 388 see also metastasis, metastases MRIs, 457, 464 Mukherjee, Leela, 398 Mukherjee, Siddhartha: Berne and, 467–70 and daughter’s birth, 398–99 as oncology fellow, 2–5, 168, 190, 305–6, 307–8, 337, 390, 398–99, 437–38, 467 Orman and, 152–53, 399–400 palliative care suggested by, 223–24 Reed and, 2–3, 7, 17–18, 127, 168–69, 190, 337, 338–39, 400, 448–49 Sorenson and, 153–55 tobacco-cancer link in patients of, 274–75 Muller, Hermann Joseph, 347–48 multidose regimens, see chemotherapy, high-dose multidrug regimens in multiple myeloma, 309, 443–44 mummies, cancer in, 43, 45 Murayama, Hashime, 288 Murphy, Mary Lois, 92 mustard gas, see nitrogen mustard mutagens, mutagenesis, 278, 303, 347, 348, 362, 364, 406, 456 mutation, genetic, 377 in bacteria, 277–78 Cancer Genome Atlas and, 450–54 causes of, see mutagens, mutagenesis driver (active), 453 frequency of, 451–52 in fruit flies, 347 functional vs. structural view of, 455 as governing all aspects of cancer, 387–88, 462 as mechanism of carcinogenesis, 6, 39, 176, 278, 357, 362, 370, 380–83, 384–88, 390–92, 403, 406, 449–50, 462, 464–65 passenger (passive), 452–53 see also oncogenes myc (c-myc) gene, 382–83, 384, 391, 410, 412, 453–54, 458 mycobacteria, 84, 131 myelodysplasia, 306, 309, 312 myeloid cells, 16–17 Myriad Genetics, 381 Nathan, David, 140 National Alliance of Breast Cancer Organizations (NABCO), 327 National Breast Cancer Coalition (NBCC), 426, 429 National Cancer Act (1971), 188, 189 National Cancer Institute (NCI), 15, 114, 130, 158, 159, 166, 177, 188, 228, 231, 318, 325, 330, 339, 374, 393, 443 chemotherapy protocols of, 132–42, 143–50, 164–66, 206–8, 219–20, 232, 310, 317 Clinical Center of, 128–29, 139, 145, 162, 165, 260 creation of, 25–26 Institutional Board of, 137 mammography project (BCDDP) of, 296–98, 302 Pap smear trial of, 289–90 preventative strategies neglected by, 233–34 Special Virus Cancer Program of, 175–76, 280–81, 356, 357 National Cancer Institute Act (1937), 25 National Health Service, British, 294 National Institutes of Health (NIH), 25n, 121, 187, 188, 202–3, 260, 319 National Library of Medicine, 261 National Program for the Conquest of Cancer, 184 National Science Foundation (NSF), 121 National Surgical Adjuvant Breast and Bowel Project (NSABP), 200–201 National Tuberculosis Association, 259 natural selection, 248 Nature, 354, 379 Nature Medicine, 435 nausea, from chemotherapy, 165, 205–6, 209, 226, 305 Nazis, 290 Neely, Matthew, 25, 173 negative statistical claims, 197–98 Nelson, Marti, 424–25, 429 “funeral procession” for, 425–26 neoplasia, 16, 42, 385 neu, 410–11, 412, 413, 420 neuroblastomas, 410, 413 New England Journal of Medicine, 35–36, 161, 229, 330, 385 Newton, Isaac, 370 New York, HIP in, 294–96, 297 New York, N.Y., AIDS in, 316, 318 New York Amsterdam News, 286 New York Times, 24, 26–27, 105, 117, 119–20, 180–81, 183, 319, 327, 455 Neyman, Jerzy, 197–98 nicotine: addictive properties of, 270–71 see also cigarettes; smoking; tobacco; tobacco industry Nisbet, Robert, 193 nitrogen mustard, 207, 220, 257 bone marrow affected by, 88, 90 DNA damaged by, 163, 406 hyperplasia as halted by, 163, 406 as mustard gas, 87–88, 89–90, 162–63 nitrosoguanidine derivatives, 278 Nixon, Richard M., 180–81, 183, 184, 187–88 Nobel Prize, 28, 87, 91, 176, 348, 363 Norris Center, 323 Norton, Larry, 327, 426 Novartis, 436, 439 Nowell, Peter, 365 NSABP-04 trial, 200–201, 203, 220 Nuland, Sherwin, 38 Ochsner, Alton, 256–57 Oedipus the King (Sophocles), 321 Office of Scientific Research and Development (OSRD), 90, 119 Oliver Twist (Dickens), 239 oncogenes, 363, 366, 370–71, 380, 384, 402, 409–11, 412, 415, 431, 439, 443, 450, 453, 454, 462, 466 amplification of, 416 pathological hyperplasia induced by, 357–59, 372, 431 proto-, see proto-oncogenes see also specific genes oncology, oncologists, 304, 433 AIDS and, 316–17 death and, 4, 306–8, 337–38 fellowships in, 2–5, 168 origin of term, 47 overconfidence of, 223, 226, 231–32, 234, 308, 310 palliative care and, 224–26, 307 patients’ relationships with, 199, 202, 209, 306–8, 449 radiation, see radiation therapy OncoMouse, 382–83, 384 onkos, 47 etymology of, 466–67 “On Some Morbid Appearances of the Absorbent Glands and Spleen” (Hodgkin), 157 opiates, 226 Oregon Health and Science University (OHSU), 434 Orman, Ben, 151–53, 155, 399–400 Osler, William, 45 osteosarcomas (bone tumors), 43 ovarian cancer, 59, 162, 346, 381, 450, 451, 457 ovaries, removal of, 214, 215 Pacific yew tree, 206 Pack, George, 70–71 Padhy, Lakshmi Charon, 410–11 Page, Irvine, 187 paleopathology, 42 palliative care, 223–26, 231, 307 drug trials for, 226 pancreas, 154, 414 pancreatic cancer, 154, 158, 450, 451, 465 Panel of Consultants, 184, 188 Panzer, Fred, 270 Papanicolaou, George, 286–90, 291, 384–85, 386, 401 Papanicolaou, Maria, 287 papillomavirus, 174, 349n, 381n Pap smears, 228, 286, 287–90, 296, 303, 331, 381, 385, 401 Paré, Ambroise, 49 Paris, University of, 51 Park, Roswell, 24, 45 Parliament cigarettes, 269 Pasteur, Louis, 57 pathology, pathologists, 11–12, 14 Hodgkin’s approach to, 156–57 Patterson, James, 183 PCP (Pneumocystis carinii), 165, 315–16 Pearson, Egon, 197–98 pectoralis major, 64–65 pectoralis minor, 64 pellagra, 110 penicillin, 21–22, 122, 129, 465–66 Penicillium, 122 Pepper, Claude, 26n peptic ulcers, 281–84 Perkin, William, 81–82, 83 pernicious anemia, 27–28, 31 Peru, 42–43 pesticides, 456–57 Peters, Vera, 159–60 Peters, William, 311–15, 319–20, 321, 325, 326, 329 Peto, Richard, 241, 249, 273–74, 462 pharmaceutical industry, 426 see also specific companies Philadelphia chromosome, 365, 430–31 Philip Morris, 251, 269–71, 273 phlegm, 48 phosphorylation, 358–59, 361, 380, 418, 431–32 Piccolo, Brian, 181 Pim, Isabella, 58 Pinkel, Donald, 123, 167–68, 170, 178 pitchblende, 74 pituitary cells, 414 placebos, in randomized trials, 131–32, 319 placenta, 135, 219 platelets, 18 Plato, 370 Pneumocystis carinii (PCP), 165, 315–16 pneumonectomy, 242 pneumonia, 45 PCP, 165, 315–16 Poet Physicians, 60 polio, 22, 229, 342, 466 national campaign against, 93–94, 175 Popper, Karl, 370 population, U.S., aging of, 230 Postmortem Examination, The (Farber), 19 Pott, Percivall, 173, 237–39, 241, 276, 447 precancer, 286, 306, 455 Auerbach’s research on, 258–59, 284, 289 prednisone, 127, 140, 143, 149 see also VAMP regimen Premarin, 213 preventive medicine, 281 epidemiology and, 290 see also cancer prevention procarbazine, 162, 164 product-liability lawsuits, 269–73, 401 progesterone, 456 “Progress Against Cancer?”


pages: 305 words: 79,303

The Four: How Amazon, Apple, Facebook, and Google Divided and Conquered the World by Scott Galloway

"Susan Fowler" uber, activist fund / activist shareholder / activist investor, additive manufacturing, Affordable Care Act / Obamacare, Airbnb, Amazon Robotics, Amazon Web Services, Apple II, autonomous vehicles, barriers to entry, Ben Horowitz, Bernie Sanders, Big Tech, big-box store, Bob Noyce, Brewster Kahle, business intelligence, California gold rush, Cambridge Analytica, cloud computing, Comet Ping Pong, commoditize, cuban missile crisis, David Brooks, Didi Chuxing, digital divide, disintermediation, don't be evil, Donald Trump, Elon Musk, fake news, follow your passion, fulfillment center, future of journalism, future of work, global supply chain, Google Earth, Google Glasses, Google X / Alphabet X, Hacker Conference 1984, Internet Archive, invisible hand, Jeff Bezos, Jony Ive, Khan Academy, Kiva Systems, longitudinal study, Lyft, Mark Zuckerberg, meta-analysis, Network effects, new economy, obamacare, Oculus Rift, offshore financial centre, passive income, Peter Thiel, profit motive, race to the bottom, RAND corporation, ride hailing / ride sharing, risk tolerance, Robert Mercer, Robert Shiller, Search for Extraterrestrial Intelligence, self-driving car, sentiment analysis, shareholder value, Sheryl Sandberg, Silicon Valley, Snapchat, software is eating the world, speech recognition, Stephen Hawking, Steve Ballmer, Steve Bannon, Steve Jobs, Steve Wozniak, Stewart Brand, supercomputer in your pocket, Tesla Model S, the long tail, Tim Cook: Apple, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, undersea cable, vertical integration, warehouse automation, warehouse robotics, Wayback Machine, Whole Earth Catalog, winner-take-all economy, working poor, you are the product, young professional

Grassegger, Hannes, and Mikael Krogerus. “The Data That Turned the World Upside Down.” Motherboard. January 28, 2017. https://motherboard.vice.com/en_us/article/how-our-likes-helped-trump-win. 19. Cadwalladr, Carole. “Robert Mercer: The big data billionaire waging war on mainstream media.” Guardian. February 26, 2017. https://www.theguardian.com/politics/2017/feb/26/robert-mercer-breitbart-war-on-media-steve-bannon-donald-trump-nigel-farage. 20. “As many as 48 million Twitter accounts aren’t people, says study.” CNBC. April 12, 2017. http://www.cnbcafrica.com/news/technology/2017/04/10/many-48-million-twitter-accounts-arent-people-says-study/. 21.


pages: 558 words: 168,179

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

Soon after, Democrats began criticizing the carried-interest tax loophole and other accounting gimmicks that helped financiers amass so much wealth. In the wake of the 2008 market crash, as Obama and the Democrats began talking increasingly about Wall Street reforms, financiers like Schwarzman, Cohen, and Singer who flocked to the Koch seminars had much to lose. The hedge fund run by another of the Kochs’ major investors, Robert Mercer, an eccentric computer scientist who made a fortune using sophisticated mathematical algorithms to trade stocks, also seemed a possible government target. Democrats in Congress were considering imposing a tax on stock trading, which the firm he co-chaired, Renaissance Technologies, did in massive quantities at computer-driven high frequency.

(After The New Yorker published my investigative article on the Kochs, “Covert Operations,” that August, The Daily Caller was the chosen receptacle for the retaliatory opposition research on me, although, after it proved false, the Web site decided not to run it.) Only in 2011 did it surface that in New York, at least, the “Ground Zero mosque” controversy had been stirred up for political gain in part by money from Robert Mercer, the co-CEO of the $15 billion Long Island hedge fund Renaissance Technologies. To aid a conservative candidate in New York, Mercer gave $1 million to help pay for ads attacking supporters of the “Ground Zero mosque.” A former computer programmer who had a reputation as a brilliant mathematician and an eccentric loner, Mercer was a relative newcomer to the Koch summits.

The club had developed the use of fratricide as a tactic to keep officeholders in line after becoming frustrated that many candidates it backed became more moderate in office. It discovered that all it had to do was threaten a primary challenge, and “they start wetting their pants,” one founder joked. Its top funders included many in the Koch network, including the billionaire hedge fund managers Robert Mercer and Paul Singer and the private equity tycoon John Childs. The Young Guns portrayed their opposition to compromise as a matter of pure principle, but beneath the surface huge vested interests were at play. The president and Boehner were close to negotiating what they called a “grand bargain” that anticipated closing some tax loopholes.


pages: 788 words: 223,004

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

The day after Coppins’s piece was published, Trump’s handler Sam Nunberg, who had granted the reporter access, resigned, calling the story “an incredible pejorative hit piece” and wishfully declaring the BuzzFeed writer’s “professional reputation . . . null and void.” Trump had already blacklisted the site. In mounting his counterstrike, Trump would call upon a new ally, one who was itching to make use of a well-stocked arsenal. He enlisted Bannon, who had positioned himself to play a big role in politics with funding from Robert Mercer. Mercer wanted to expand Breitbart, and Bannon, seeing his opportunity, wrote up a business plan on his friend’s behalf. That summer Mercer ponied up the $10 million and made Bannon a co-owner and director of the company. In the immediate aftermath of the Coppins piece, Bannon’s Breitbart marshalled an impressive multipronged takedown of the BuzzFeed author.

., 402 Knight Ridder newspaper chain, 26, 67, 226 sale of, 235–36 Knoxville, Johnny, 51, 57, 180 Koch brothers, 382 Kosinski, Michal, 278–79 Kurtz, Howard, 92, 93 Kushner, Jared, 224, 416 Laessig, Gavon, 314–15 Landman, Jon, 192 Larry King Live (TV show), 92 Larsen, Kaj, 355, 362 Last Week Tonight (TV show), 389 Lattman, Peter, 343–44 Laurence, Guy, 358 Law of the Few, 112 Leen, Jeff, 233 Lelyveld, Joe, 8, 152, 191, 372, 375, 429 Lennard, Natasha, 361–62 Leonhardt, David, 212, 381 Leopold, Jason, 178, 345 Lerer, Kenneth, 20–23, 24, 25, 31, 103, 123, 328, 344 Levien, Meredith Kopit, 375, 376 Levy, Cliff, 172 Lewandowski, Corey, 409 Lewinsky, Monica, 195, 239, 284 Lewis, Anthony, 421 Lewis, Luke, 311 Lexington Herald-Leader, 235 LGBT rights, 140 Libby, Lewis “Scooter,” 93, 198 Liberman, Megan, 135 Liberty Film Festival, 285 Libya, kidnapping of correspondents in, 208 Lichtblau, Eric, 215, 383–85 Lieberman, Joseph, 51–52 Lifetime, 335 Lily, The, 425 Lipton, Eric, 390 Lipton, Martin, 63 Lockheed Martin, 54–55 London Underground, 2005 terrorist attack in, 55 long-form journalism: as Marilyn Thompson’s specialty, 233–37 Post’s reputation for, 233 speeded-up news cycle as enemy of, 237, 417 Los Angeles Times, 3–4, 25, 236, 383 Baquet as editor of, 199 Tribune company’s purchase of, 226 wall between news and advertising departments crossed by, 71 Love, Reggie, 177 Loxodo (Post metrics tool), 267, 414 Luo, Patrick, 206 Lytvynenko, Jane, 340–41 Ma, Christopher, 95–96 Ma, Olivia, 95 McCain, John, 131, 132 McChrystal, Stanley, 130 McClatchy newspaper chain, 80, 94, 226, 236 McConnell, Mitch, 236 Macedonia, fake news industry in, 297–98 machine learning, 34–35, 109, 330–31 McInnes, Gavin, 42–43, 147, 148 American Conservative column of, 50 in buyback of Vice, 47 in exit from Vice, 58, 181, 369 as Proud Boys founder, 368 racism and misogyny of, 43–44, 46, 48–49, 50, 59 as Vice Media cofounder, 43–44 McIntire, Mike, 379 McKinsey & Company, 68–69, 71, 72, 193, 213 Magazine, Das, 279 Maher, Bill, 44, 178, 347 Mainland, Lexi, 203–4 Manafort, Paul, 382 Mansformation (TV show), 335 Marlow, Alex, 287 Marlow, Cameron, 16, 17, 104 Marra, Greg, 105 Marshall, Josh, 73, 94 Martel, Ned, 250 Martin, Trayvon, 111 Mashable, 344, 367 Massie, Chris, 313, 316 Mastromonaco, Alyssa, 177, 348, 363 Mayer, Jane, 196, 307, 382 Meet the Press (TV show), 339 Meme Magic Secrets Revealed (Gionet), 312 memes, definition of, 17 Menkes, Suzy, 211 Mercer, Robert, 306, 307 Mercer family, 279, 298, 307, 374, 382 Me Too movement, 210, 361, 392, 425, 426 metrics: Chartbeat and, 243–47, 262, 266 Post’s use of, 266–68, 414, 416 Times’s use of, 267, 425 Meyer, Eugene, 83 Miami Herald, 201 Mic, 275 Miller, Judith, 79, 80, 93, 385 Miller, Katherine, 305, 308–9, 316–17, 321 Miller, Zeke, 129, 135, 339 mimetic desire, 273 MIT Media Lab, 16, 18 Mohonk Group, 76 Mojica, Jason: journalistic credibility of, 356 sexual harassment accusations against, 361–63 Veltroni’s affair with, 359–61, 362 as Vice News head, 352, 356–57 Monde, Le, 113 Moore, Roy, 416, 425 Moretti, Eddy, 50, 160 Morgenson, Gretchen, 190 Morris, Errol, 180 Morris, Hamilton, 180–81 Morton, John, 261 Morton, Thomas, 148 appointed Vice website editor, 150 as archetypical Vice reader, 147 Gross Jar and, 149–50 Gullah moonshine video of, 155–56 and HBO weekly Vice show, 355 immersive videos of, 155–58, 171–72 inaccurate Uganda documentary by, 172 as media star, 180–81 on-air persona of, 155 Vice articles by, 150 Vice articles of, 151–52 Vice’s hiring of, 147–48 Mossberg, Walt, 240 Mother Jones, 324 Moynihan, Michael, 351 MSNBC, 377 MTV, 51–52, 57, 152–53, 154 Mueller, Robert, 382, 416 Muir, David, 427 Murdoch, Rupert, 28, 60, 67, 154, 177, 229, 420, 427 Vice investment of, 366 Wall Street Journal acquired by, 183, 229 Murphy, Eileen, 203 MySpace, 154 Narisetti, Raju, 266 digitally-experienced news staff hired by, 247–48, 249 in exit from Post, 251 named Post managing editor, 238 revenue-generating projects pushed by, 250 staff cuts by, 243 website metrics as focus of, 242–43, 245 website traffic increased by, 250–51 National Public Radio, 77 National Security Agency (NSA), Snowden leaks and, 80, 215, 259–60, 268, 382 native advertising, 40–41, 52, 71, 412–13 Abramson’s opposition to, 214, 215 authenticity and, 160 BuzzFeed’s use of, 120–23, 136–37, 337, 343 importance of verisimilitude in, 121, 136 as needing to harmonize with surrounding content, 161 Obama 2012 campaign and, 136–37 Vice Media and, 158–59 virality and, 122–23 Needleman, Deborah, 210 Negroponte, Nicholas, 16 Netflix, 329, 344 network news, declining audience for, 153 Nevins, Sheila, 178 NewFronts, 336 New Museum of Contemporary Art, 19 New Republic, 135, 139 News about the News, The (Downie and Kaiser), 89 news cycle, speeding up of, 5, 32–33, 98, 133–34, 185, 237 accuracy as victim of, 238 as enemy of investigative journalism, 383 internet and, 239–40 news fatigue, 26 NewsFeed (podcast), 342 news media: cuts to foreign desks by, 174 digital, see digital news media emotionally charged stories in, 111 female-centric projects of, 425 imperilled watchdog function of, 89 internet and unbundling of, 52 loss of public trust in, 3, 4, 80, 95, 185, 386–87, 424, 426–27 news media (cont.)


pages: 584 words: 187,436

More Money Than God: Hedge Funds and the Making of a New Elite by Sebastian Mallaby

Alan Greenspan, Andrei Shleifer, Asian financial crisis, asset-backed security, automated trading system, bank run, barriers to entry, Bear Stearns, Benoit Mandelbrot, Berlin Wall, Bernie Madoff, Big bang: deregulation of the City of London, Bonfire of the Vanities, book value, Bretton Woods, business cycle, buy and hold, capital controls, Carmen Reinhart, collapse of Lehman Brothers, collateralized debt obligation, computerized trading, corporate raider, Credit Default Swap, credit default swaps / collateralized debt obligations, crony capitalism, currency manipulation / currency intervention, currency peg, deal flow, do well by doing good, Elliott wave, Eugene Fama: efficient market hypothesis, failed state, Fall of the Berlin Wall, financial deregulation, financial engineering, financial innovation, financial intermediation, fixed income, full employment, German hyperinflation, High speed trading, index fund, Jim Simons, John Bogle, John Meriwether, junk bonds, Kenneth Rogoff, Kickstarter, Long Term Capital Management, low interest rates, machine translation, margin call, market bubble, market clearing, market fundamentalism, Market Wizards by Jack D. Schwager, Mary Meeker, merger arbitrage, Michael Milken, money market fund, moral hazard, Myron Scholes, natural language processing, Network effects, new economy, Nikolai Kondratiev, operational security, pattern recognition, Paul Samuelson, pre–internet, proprietary trading, public intellectual, quantitative hedge fund, quantitative trading / quantitative finance, random walk, Renaissance Technologies, Richard Thaler, risk-adjusted returns, risk/return, Robert Mercer, rolodex, Savings and loan crisis, Sharpe ratio, short selling, short squeeze, Silicon Valley, South Sea Bubble, sovereign wealth fund, statistical arbitrage, statistical model, survivorship bias, tail risk, technology bubble, The Great Moderation, The Myth of the Rational Market, the new new thing, too big to fail, transaction costs, two and twenty, uptick rule

The Renaissance researchers built systems that were in a class of their own. “I can only look at them and realize that you have the gods of the business and then you have mere mortals like me,” Wadhwani said, echoing the view of the entire industry.20 IN 1993 SIMONS MADE TWO IMPORTANT ADDITIONS TO HIS brain trust: Peter Brown and Robert Mercer. They came from IBM’s research center, and they drove much of the success of Medallion over the next years, eventually taking the reins when Simons opted for retirement. The two men complemented each other well. Brown was a magnesium flare of energy: He slept five hours per night, riffed passionately on every topic of the day, and for a while got around the office on a unicycle.

Shaw grew out of statistical arbitrage in equities, with strong roots in fundamental intuitions about stocks, Renaissance grew out of technical trading in commodities, a tradition that treats price data as paramount.28 Whereas D. E. Shaw hired quants of all varieties, usually recruiting them in their twenties, the crucial early years at Renaissance were largely shaped by established cryptographers and translation programmers—experts who specialized in distinguishing fake ghosts from real ones. Robert Mercer echoes some of Wepsic’s wariness about false correlations: “If somebody came with a theory about how the phases of Venus influence markets, we would want a lot of evidence.” But he adds that “some signals that make no intuitive sense do indeed work.” Indeed, it is the nonintuitive signals that often prove the most lucrative for Renaissance.

John Magee, a leading technician of the 1950s, made a point of reading the newspapers two weeks late in order to be sure that knowledge of the economy would not cloud his judgment. 29. Mercer says, “We will contemplate any proposed signal. But if somebody comes with a theory that does not make intuitive sense, we would examine it especially carefully.” (Robert Mercer, interview with the author, July 28, 2008.) The same willingness to trade on statistical evidence was shared by earlier contributors to Medallion’s success. For example, Elwyn Berlekamp recalls, “Mostly we looked at statistics at Medallion. We found that attempts to look at fundamentals did not get us very far.”


pages: 374 words: 114,600

The Quants by Scott Patterson

Alan Greenspan, Albert Einstein, AOL-Time Warner, asset allocation, automated trading system, Bear Stearns, beat the dealer, Benoit Mandelbrot, Bernie Madoff, Bernie Sanders, Black Monday: stock market crash in 1987, Black Swan, Black-Scholes formula, Blythe Masters, Bonfire of the Vanities, book value, Brownian motion, buttonwood tree, buy and hold, buy low sell high, capital asset pricing model, Carl Icahn, centralized clearinghouse, Claude Shannon: information theory, cloud computing, collapse of Lehman Brothers, collateralized debt obligation, commoditize, computerized trading, Credit Default Swap, credit default swaps / collateralized debt obligations, diversification, Donald Trump, Doomsday Clock, Dr. Strangelove, Edward Thorp, Emanuel Derman, Eugene Fama: efficient market hypothesis, financial engineering, Financial Modelers Manifesto, fixed income, Glass-Steagall Act, global macro, Gordon Gekko, greed is good, Haight Ashbury, I will remember that I didn’t make the world, and it doesn’t satisfy my equations, index fund, invention of the telegraph, invisible hand, Isaac Newton, Jim Simons, job automation, John Meriwether, John Nash: game theory, junk bonds, Kickstarter, law of one price, Long Term Capital Management, Louis Bachelier, low interest rates, mandelbrot fractal, margin call, Mark Spitznagel, merger arbitrage, Michael Milken, military-industrial complex, money market fund, Myron Scholes, NetJets, new economy, offshore financial centre, old-boy network, Paul Lévy, Paul Samuelson, Ponzi scheme, proprietary trading, quantitative hedge fund, quantitative trading / quantitative finance, race to the bottom, random walk, Renaissance Technologies, risk-adjusted returns, Robert Mercer, Rod Stewart played at Stephen Schwarzman birthday party, Ronald Reagan, Savings and loan crisis, Sergey Aleynikov, short selling, short squeeze, South Sea Bubble, speech recognition, statistical arbitrage, The Chicago School, The Great Moderation, The Predators' Ball, too big to fail, transaction costs, value at risk, volatility smile, yield curve, éminence grise

Renaissance has applied that skill to enormous strings of market numbers, such as tick-by-tick data in oil prices, while looking at other relationships the data have with assets such as the dollar or gold. Another clue can be found in the company’s decision in the early 1990s to hire several individuals with expertise in the obscure, decidedly non–Wall Street field of speech recognition. In November 1993, Renaissance hired Peter Brown and Robert Mercer, founders of a speech recognition group at IBM’s Thomas J. Watson Research Center in Yorktown Heights, New York, in the hills of Westchester County. Brown came to be known as a freakishly hard worker at the fund, often spending the night at Renaissance’s East Setauket headquarters on a Murphy bed with a whiteboard tacked to the bottom of it.

In 2008, he’d traveled to China to propose a sale of part of Renaissance to the China Investment Corp., the $200 billion fund owned and run by the Chinese government. No deal was struck, but it was a clear sign that the aging math whiz was ready to step aside. Indeed, later in the year Simons retired as CEO of Renaissance, replaced by the former IBM voice recognition gurus Peter Brown and Robert Mercer. Perhaps most shocking of all, the three-pack-a-day Simons had quit smoking. Meanwhile, other top quants mixed and mingled. Neil Chriss, whose wedding had seen the clash of Taleb and Muller over whether it was possible to beat the market, held session at a table with several friends. Chriss was a fast-rising and brilliant quant, a true mathematician who’d taught for a time at Harvard.


pages: 486 words: 150,849

Evil Geniuses: The Unmaking of America: A Recent History by Kurt Andersen

"Friedman doctrine" OR "shareholder theory", "World Economic Forum" Davos, affirmative action, Affordable Care Act / Obamacare, air traffic controllers' union, airline deregulation, airport security, Alan Greenspan, always be closing, American ideology, American Legislative Exchange Council, An Inconvenient Truth, anti-communist, Apple's 1984 Super Bowl advert, artificial general intelligence, autonomous vehicles, basic income, Bear Stearns, Bernie Sanders, blue-collar work, Bonfire of the Vanities, bonus culture, Burning Man, call centre, Capital in the Twenty-First Century by Thomas Piketty, carbon tax, Cass Sunstein, centre right, computer age, contact tracing, coronavirus, corporate governance, corporate raider, cotton gin, COVID-19, creative destruction, Credit Default Swap, cryptocurrency, deep learning, DeepMind, deindustrialization, Donald Trump, Dr. Strangelove, Elon Musk, ending welfare as we know it, Erik Brynjolfsson, feminist movement, financial deregulation, financial innovation, Francis Fukuyama: the end of history, future of work, Future Shock, game design, General Motors Futurama, George Floyd, George Gilder, Gordon Gekko, greed is good, Herbert Marcuse, Herman Kahn, High speed trading, hive mind, income inequality, industrial robot, interchangeable parts, invisible hand, Isaac Newton, It's morning again in America, James Watt: steam engine, Jane Jacobs, Jaron Lanier, Jeff Bezos, jitney, Joan Didion, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joseph Schumpeter, junk bonds, Kevin Roose, knowledge worker, lockdown, low skilled workers, Lyft, Mark Zuckerberg, market bubble, mass immigration, mass incarceration, Menlo Park, Naomi Klein, new economy, Norbert Wiener, Norman Mailer, obamacare, Overton Window, Peter Thiel, Picturephone, plutocrats, post-industrial society, Powell Memorandum, pre–internet, public intellectual, Ralph Nader, Right to Buy, road to serfdom, Robert Bork, Robert Gordon, Robert Mercer, Ronald Reagan, Saturday Night Live, Seaside, Florida, Second Machine Age, shareholder value, Silicon Valley, social distancing, Social Responsibility of Business Is to Increase Its Profits, Steve Jobs, Stewart Brand, stock buybacks, strikebreaker, tech billionaire, The Death and Life of Great American Cities, The Future of Employment, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, Tim Cook: Apple, too big to fail, trickle-down economics, Tyler Cowen, Tyler Cowen: Great Stagnation, Uber and Lyft, uber lyft, union organizing, universal basic income, Unsafe at Any Speed, urban planning, urban renewal, very high income, wage slave, Wall-E, War on Poverty, We are all Keynesians now, Whole Earth Catalog, winner-take-all economy, women in the workforce, working poor, young professional, éminence grise

The first Bush administration had suspended the federal antitrust rule forbidding networks from also owning the shows they aired, then New York’s Mayor Rudy Giuliani successfully pressured the local cable operator, owned by Time Warner, to carry Fox News. Soon Murdoch also had conservative media’s high end covered with The Weekly Standard, cofounded by Irving Kristol’s son, Bill. In 2007, Murdoch added The Wall Street Journal to his portfolio and Breitbart News launched, funded by the financial billionaire (and Koch associate) Robert Mercer. The elite would be conscripted (and coopted) at scale on college campuses and in Washington, but now through every medium the rabble would be roused as well, 24/7. * * * — Around 1980, donations by business PACs to candidates for Congress started exceeding those made by unions, but never by more than half until 2000, after which the corporate sums were twice those of organized labor, then more than triple.

So why, according to polls, were two-thirds of Americans in favor of the national quasi-quarantine? Because, this presidential adviser and would-be Fed governor said, “the American people are sheep.” The two Koch-created enterprises and Moore were joined by a newer organization also devoted to promoting right-wing economics, the Convention of States, funded by Robert Mercer—hedge fund billionaire, early Breitbart News investor, Trump’s biggest 2016 donor—and overseen by a cofounder of the Tea Party Patriots and (such a long game) a strategist for David Koch’s 1980 Libertarian vice-presidential campaign. In Michigan, the protests were organized and promoted by existing Republican groups, one connected to the right-wing billionaire DeVos family, and in Idaho by a group funded by a new Coors, the son of the counter-Establishment founder Joseph.*6 The mission of those demonstrations, as The Washington Post reported, was “making opposition to stay-at-home orders—which had been in place in most states for only a couple of weeks or less—appear more widespread than is suggested by polling.”


pages: 210 words: 65,833

This Is Not Normal: The Collapse of Liberal Britain by William Davies

Airbnb, basic income, Bernie Sanders, Big bang: deregulation of the City of London, Black Lives Matter, Boris Johnson, Cambridge Analytica, central bank independence, centre right, Chelsea Manning, coronavirus, corporate governance, COVID-19, credit crunch, data science, deindustrialization, disinformation, Dominic Cummings, Donald Trump, double entry bookkeeping, Edward Snowden, fake news, family office, Filter Bubble, Francis Fukuyama: the end of history, ghettoisation, gig economy, global pandemic, global village, illegal immigration, Internet of things, Jeremy Corbyn, late capitalism, Leo Hollis, liberal capitalism, loadsamoney, London Interbank Offered Rate, mass immigration, moral hazard, Neil Kinnock, Northern Rock, old-boy network, post-truth, postnationalism / post nation state, precariat, prediction markets, quantitative easing, recommendation engine, Robert Mercer, Ronald Reagan, sentiment analysis, sharing economy, Silicon Valley, Slavoj Žižek, statistical model, Steve Bannon, Steven Pinker, surveillance capitalism, technoutopianism, The Chicago School, Thorstein Veblen, transaction costs, universal basic income, W. E. B. Du Bois, web of trust, WikiLeaks, Yochai Benkler

As long as nothing ever stays the same, you can exit better off than when you entered. The only unprofitable scenario is stasis. Private investment funds have been a constant feature of Britain’s descent into political turmoil, though their precise role remains murky. The American hedge fund billionaire Robert Mercer, a friend of Nigel Farage, was accused of aiding the Leave campaign with data analytics expertise, via the now defunct company Cambridge Analytica. Hedge funds were generous backers of both the Leave and Remain campaigns in 2016, but both sides extracted handsome rewards from the financial turmoil that immediately followed the result.


pages: 302 words: 85,877

Cult of the Dead Cow: How the Original Hacking Supergroup Might Just Save the World by Joseph Menn

"World Economic Forum" Davos, 4chan, A Declaration of the Independence of Cyberspace, Andy Rubin, Apple II, autonomous vehicles, Berlin Wall, Bernie Sanders, Big Tech, bitcoin, Black Lives Matter, Cambridge Analytica, Chelsea Manning, Citizen Lab, commoditize, corporate governance, digital rights, disinformation, Donald Trump, dumpster diving, Edward Snowden, end-to-end encryption, fake news, Firefox, Gabriella Coleman, Google Chrome, Haight Ashbury, independent contractor, information security, Internet of things, Jacob Appelbaum, Jason Scott: textfiles.com, John Gilmore, John Markoff, John Perry Barlow, Julian Assange, Laura Poitras, machine readable, Mark Zuckerberg, military-industrial complex, Mitch Kapor, Mondo 2000, Naomi Klein, NSO Group, Peter Thiel, pirate software, pre–internet, Ralph Nader, ransomware, Richard Stallman, Robert Mercer, Russian election interference, self-driving car, Sheryl Sandberg, side project, Silicon Valley, Skype, slashdot, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, Stuxnet, tech worker, Whole Earth Catalog, WikiLeaks, zero day

See software programs, malicious Mandiant, 134 Mann, Sally, 22–23 Manning, Chelsea (formerly Bradley), 143–144 Marlinspike, Moxie, 152, 162, 178 Masters of Deception (MoD), 25–29, 32, 54 Matasano Security, 125 Mathewson, Nick, 129, 140, 155 Matlock. See Noonan, Timothy Mayer, Marissa, 198 McAfee, 29, 107 McGill University, 166 MCI, 10, 12–13 media, cDc relationship with, 58–62, 67–68, 80. See also Hong Kong Blondes Medium (website), 99 Mentor, the, 44 Mercer, Rebekah, 196 Mercer, Robert, 196 Merry Pranksters, 22–23 Messiah Village, 48–49 Metasploit, 177 #MeToo, 158 Microsoft, 37, 63, 108, 196, 212 BackOffice software, 66, 69 Back Orifice, response to, 67–69, 77, 82–83, 96–97 hackers working for, 38, 50, 111–112, 122–124, 193 security vulnerabilities, 45, 56, 72–73, 82–83, 85, 111–112 See also Back Orifice; Windows military, 74, 78, 117–118, 136, 185, 209 See also United States government Miller, Charlie, 178–179 Miloševic, Slobodan, 102–103 MindSpring, 68 MindVox, 30–32, 63, 145 MIT, 37–38, 40, 45–46, 50, 53, 72–73 Mitnick, Kevin, 35, 44 Mixter.


pages: 283 words: 87,166

Reaching for Utopia: Making Sense of an Age of Upheaval by Jason Cowley

"World Economic Forum" Davos, anti-communist, Berlin Wall, Bernie Sanders, Big bang: deregulation of the City of London, Boris Johnson, Brexit referendum, Bullingdon Club, Cambridge Analytica, centre right, Charles Lindbergh, coherent worldview, Corn Laws, corporate governance, crony capitalism, David Brooks, deindustrialization, deskilling, Donald Trump, Etonian, eurozone crisis, fake news, Fall of the Berlin Wall, illegal immigration, Jeremy Corbyn, liberal world order, Neil Kinnock, Occupy movement, offshore financial centre, old-boy network, open borders, open immigration, plutocrats, post-war consensus, public intellectual, Right to Buy, Robert Mercer, Ronald Reagan, Russell Brand, technological determinism, University of East Anglia

In this country, they put it down to lies, and in America, it’s the Russians!’ Ah, the Russians – let’s hope they love their children, too, as Sting once sang. Carole Cadwalladr, an Observer feature writer, has been determinedly investigating the operations of the data mining and analytics firm Cambridge Analytica and its connections to Robert Mercer, an American hedge fund billionaire and libertarian, who is a prominent Trump supporter. Cadwalladr is convinced that Mercer and Farage are at the centre of a network of alt-right white nationalists and libertarian billionaires who are intent not only on destabilising the West but engendering hate and overturning the liberal order.


pages: 332 words: 93,672

Life After Google: The Fall of Big Data and the Rise of the Blockchain Economy by George Gilder

23andMe, Airbnb, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, AlphaGo, AltaVista, Amazon Web Services, AOL-Time Warner, Asilomar, augmented reality, Ben Horowitz, bitcoin, Bitcoin Ponzi scheme, Bletchley Park, blockchain, Bob Noyce, British Empire, Brownian motion, Burning Man, business process, butterfly effect, carbon footprint, cellular automata, Claude Shannon: information theory, Clayton Christensen, cloud computing, computer age, computer vision, crony capitalism, cross-subsidies, cryptocurrency, Danny Hillis, decentralized internet, deep learning, DeepMind, Demis Hassabis, disintermediation, distributed ledger, don't be evil, Donald Knuth, Donald Trump, double entry bookkeeping, driverless car, Elon Musk, Erik Brynjolfsson, Ethereum, ethereum blockchain, fake news, fault tolerance, fiat currency, Firefox, first square of the chessboard, first square of the chessboard / second half of the chessboard, floating exchange rates, Fractional reserve banking, game design, Geoffrey Hinton, George Gilder, Google Earth, Google Glasses, Google Hangouts, index fund, inflation targeting, informal economy, initial coin offering, Internet of things, Isaac Newton, iterative process, Jaron Lanier, Jeff Bezos, Jim Simons, Joan Didion, John Markoff, John von Neumann, Julian Assange, Kevin Kelly, Law of Accelerating Returns, machine translation, Marc Andreessen, Mark Zuckerberg, Mary Meeker, means of production, Menlo Park, Metcalfe’s law, Money creation, money: store of value / unit of account / medium of exchange, move fast and break things, Neal Stephenson, Network effects, new economy, Nick Bostrom, Norbert Wiener, Oculus Rift, OSI model, PageRank, pattern recognition, Paul Graham, peer-to-peer, Peter Thiel, Ponzi scheme, prediction markets, quantitative easing, random walk, ransomware, Ray Kurzweil, reality distortion field, Recombinant DNA, Renaissance Technologies, Robert Mercer, Robert Metcalfe, Ronald Coase, Ross Ulbricht, Ruby on Rails, Sand Hill Road, Satoshi Nakamoto, Search for Extraterrestrial Intelligence, self-driving car, sharing economy, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, Singularitarianism, Skype, smart contracts, Snapchat, Snow Crash, software is eating the world, sorting algorithm, South Sea Bubble, speech recognition, Stephen Hawking, Steve Jobs, Steven Levy, Stewart Brand, stochastic process, Susan Wojcicki, TED Talk, telepresence, Tesla Model S, The Soul of a New Machine, theory of mind, Tim Cook: Apple, transaction costs, tulip mania, Turing complete, Turing machine, Vernor Vinge, Vitalik Buterin, Von Neumann architecture, Watson beat the top human players on Jeopardy!, WikiLeaks, Y Combinator, zero-sum game

The author of the Chern-Simons formula in string theory, a performer of secret cerebrations for IDA, and the genius behind this greatest of hedge funds, Simons has performed a world-beating demonstration of practical mathematics, massive computational power, and entrepreneurship. Spinning out of the IDA, Renaissance began in 1978 as “Monemetrics” and was mostly devoted to trading currencies with Baum’s hidden Markov modeling techniques still in formation at IDA. This first version was modestly successful. The major breakthroughs came when Simons hired Robert Mercer and Peter Brown from the IBM speech-recognition group in 1993 and unleashed them to create a vast Siren Server designed to make money out of Markov and derivative algorithms. The entire big data movement has its roots in the research of that industry-leading cohort at IBM, which took advantage of the company’s vast troves of speech examples and world-class computer power to recognize human language better than anyone else.


pages: 382 words: 105,657

Flying Blind: The 737 MAX Tragedy and the Fall of Boeing by Peter Robison

"Friedman doctrine" OR "shareholder theory", air traffic controllers' union, Airbnb, Airbus A320, airline deregulation, airport security, Alvin Toffler, Boeing 737 MAX, Boeing 747, call centre, chief data officer, contact tracing, coronavirus, corporate governance, COVID-19, Donald Trump, flag carrier, Future Shock, interest rate swap, Internet Archive, knowledge worker, lockdown, low cost airline, low interest rates, medical residency, Neil Armstrong, performance metric, Ralph Nader, RAND corporation, Robert Mercer, Ronald Reagan, shareholder value, Silicon Valley, Silicon Valley startup, single-payer health, Social Responsibility of Business Is to Increase Its Profits, stock buybacks, too big to fail, Unsafe at Any Speed, vertical integration, éminence grise

After the ValuJet crash in 1996, when it emerged that the FAA had failed to implement NTSB recommendations on storage of flammable materials, DeFazio pushed for a law changing the agency’s mission from “promoting” aviation to merely “encouraging” it. In 2009, his proposal for a one-quarter of 1 percent tax on stock transactions drew the attention of Robert Mercer, the wealthy financier who later backed Trump. Mercer funded a research chemist who believes that climate change is a hoax to challenge DeFazio in subsequent elections. They’d been some of the closest of his career. Already inclined to be skeptical of the FAA, DeFazio was even more irked after what he’d heard from safety chief Ali Bahrami, who had assured him in February there was nothing to worry about with the MAX.


The Road to Unfreedom: Russia, Europe, America by Timothy Snyder

active measures, affirmative action, Affordable Care Act / Obamacare, American ideology, anti-globalists, Bellingcat, Bernie Sanders, Brexit referendum, centre right, Charles Lindbergh, crony capitalism, disinformation, Dissolution of the Soviet Union, Donald Trump, fake news, gentrification, hiring and firing, income inequality, Jeremy Corbyn, John Markoff, means of production, Mikhail Gorbachev, military-industrial complex, New Journalism, obamacare, offshore financial centre, opioid epidemic / opioid crisis, pill mill, Robert Mercer, sexual politics, Steve Bannon, Transnistria, W. E. B. Du Bois, WikiLeaks, women in the workforce, zero-sum game

Bannon, David Bossie, and Citizens United: Michael Wolff, “Ringside with Steve Bannon at Trump Tower as the President-Elect’s Strategist Plots ‘An Entirely New Political Movement,’ ” Hollywood Reporter, Nov. 18, 2016. Bannon and Mercers: Matthew Kelly, Kate Goldstein, and Nicholas Confessore, “Robert Mercer, Bannon Patron, Is Leaving Helm of $50 Billion Hedge Fund,” NYT, Nov. 2, 2017. Bannon’s extreme-Right ideology Bannon quotation: Owen Matthews, “Alexander Dugin and Steve Bannon’s Ideological Ties to Vladimir Putin’s Russia,” NW, April 17, 2017. Bannon’s ideology and films: Ronald Radosh, “Steve Bannon, Trump’s Top Guy, Told Me He Was ‘A Leninist’ Who Wants to ‘Destroy the State,’ ” DB, Aug. 22, 2016; Jeremy Peters, “Bannon’s Views Can be Traced to a Book That Warns, ‘Winter Is Coming,’ ” NYT, April 8, 2017; Owen Matthews, “Alexander Dugin and Steve Bannon’s Ideological Ties to Vladimir Putin’s Russia,” NW, April 17, 2017; Christopher Dickey and Asawin Suebsaeng, “Steve Bannon’s Dream: A Worldwise Ultra-Right,” DB, Nov. 13, 2016.


pages: 561 words: 120,899

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

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

See also Markov chains Monte Carlo simulation McNamara, Robert, 194 means, 130–32 medical devices, 228–29 medicine: cancer, x, 108–9, 110–14, 215–16, 227–28, 235, 255–57 diagnosis in, 135, 226–29, 255–57 heart attacks, x, 114–16 strokes, 226–27, 244 treatment in, 116, 235 X-rays, 53 Mercer, Robert L., 237–38, 245–47 Meshenberg, M. P., 101 meta-analysis, 215–16 metric system, 29 Metropolis, Nicholas, 222–23, 224 Michie, Donald, 81, 82 Microsoft, 242–43 military: asteroids and, 209 in Cold War, generally, 164–65, 173–75, 215 equal probabilities and, 38, 73 of France, 29, 38–40 image analysis and, 240, 241 inverse probability and, 38 mathematics and, 97 nuclear weapons and, 119–28, 182–95 robotics and, 240 of Russia, 72–73 satellites and, 209 statistics and, 97 submarines and, 194–203, 206–8 translation and, 247 weapons systems and, 241.


pages: 426 words: 136,925

Fulfillment: Winning and Losing in One-Click America by Alec MacGillis

"RICO laws" OR "Racketeer Influenced and Corrupt Organizations", Airbnb, Amazon Web Services, Bernie Sanders, Big Tech, Black Lives Matter, call centre, carried interest, cloud computing, cognitive dissonance, company town, coronavirus, COVID-19, data science, death of newspapers, deindustrialization, Donald Trump, edge city, fulfillment center, future of work, gentrification, George Floyd, Glass-Steagall Act, global pandemic, Great Leap Forward, high net worth, housing crisis, Ida Tarbell, income inequality, information asymmetry, Jeff Bezos, Jeffrey Epstein, Jessica Bruder, jitney, Kiva Systems, lockdown, Lyft, mass incarceration, McMansion, megaproject, microapartment, military-industrial complex, new economy, Nomadland, offshore financial centre, Oklahoma City bombing, opioid epidemic / opioid crisis, plutocrats, Ralph Nader, rent control, Richard Florida, ride hailing / ride sharing, Robert Mercer, Ronald Reagan, San Francisco homelessness, shareholder value, Silicon Valley, social distancing, strikebreaker, tech worker, Travis Kalanick, uber lyft, uranium enrichment, War on Poverty, warehouse robotics, white flight, winner-take-all economy, women in the workforce, working-age population, Works Progress Administration

A day later, Jay Carney, the journalist turned influencer-in-chief, called up Mayor Bill de Blasio and Governor Andrew Cuomo and told them the company was pulling out. Not entirely—there would still be several thousand white-collar Amazonians in the city, clustered mostly at Hudson Yards, the giant new development on the West Side of Manhattan. But there would be no HQ2 extravaganza. A group funded by Robert Mercer, the hedge-fund billionaire, paid for a billboard in Times Square blaming the loss on Ocasio-Cortez: THANKS FOR NOTHING, AOC! So there would be a lone big winner after all. Washington and Northern Virginia had mustered nothing close to the resistance in New York. Maybe it was that the tax subsidies offered by Virginia had been less offensively gargantuan—about $750 million.


pages: 458 words: 132,912

The Dying Citizen: How Progressive Elites, Tribalism, and Globalization Are Destroying the Idea of America by Victor Davis Hanson

"World Economic Forum" Davos, 2021 United States Capitol attack, 23andMe, affirmative action, Affordable Care Act / Obamacare, airport security, Bernie Sanders, Big Tech, Black Lives Matter, Boeing 737 MAX, borderless world, bread and circuses, British Empire, business climate, business cycle, carbon footprint, centre right, clean water, coronavirus, COVID-19, creative destruction, currency manipulation / currency intervention, defund the police, deindustrialization, deplatforming, disinformation, Donald Trump, Dr. Strangelove, drone strike, El Camino Real, fake news, Ferguson, Missouri, fixed income, Francis Fukuyama: the end of history, future of work, George Floyd, Gini coefficient, global pandemic, Herbert Marcuse, high-speed rail, Honoré de Balzac, illegal immigration, immigration reform, income inequality, Jeff Bezos, Joseph Schumpeter, laissez-faire capitalism, lockdown, Mark Zuckerberg, mass immigration, mass incarceration, Menlo Park, microaggression, military-industrial complex, mortgage debt, Nate Silver, new economy, New Urbanism, obamacare, old-boy network, Paris climate accords, Parler "social media", peak oil, Potemkin village, Ralph Waldo Emerson, Robert Mercer, Ronald Reagan, school choice, Silicon Valley, Silicon Valley billionaire, Skype, social distancing, Social Justice Warrior, tech worker, Thomas L Friedman, transcontinental railway, upwardly mobile, vertical integration, WikiLeaks, working poor, Yom Kippur War, zero-sum game

I thank supporters of the Hoover Institution, Stanford University, and others for allowing me time to write this book, especially Martin Anderson, Beatrice and Jim Bennet, Will Edwards, Roger and Susan Hertog, Lew Davies, Jim Jameson, John and Carole Harris, Mary Myers Kauppila, Rebekah, Jennifer, and Robert Mercer, Roger and Martha Mertz, Jeremiah Milbank, Tom and Diane Smith, Richard F. and Karen Spencer, Victor Trione, and Kay Woods. CONTENTS Cover Title Page Copyright Acknowledgments Dedication Introduction PRE– AND POST–AMERICAN CITIZENS Part 1: Precitizens Chapter One PEASANTS Chapter Two RESIDENTS Chapter Three TRIBES Part 2: Postcitizens Chapter Four UNELECTED Chapter Five EVOLUTIONARIES Chapter Six GLOBALISTS Epilogue CITIZENSHIP, THE ANNUS HORRIBILIS, AND THE NOVEMBER 2020 ELECTION Discover More About the Author Also by Victor Davis Hanson Praise for The Dying Citizen Notes For Jennifer Explore book giveaways, sneak peeks, deals, and more.


pages: 519 words: 155,332

Tailspin: The People and Forces Behind America's Fifty-Year Fall--And Those Fighting to Reverse It by Steven Brill

"Friedman doctrine" OR "shareholder theory", "World Economic Forum" Davos, 2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, activist fund / activist shareholder / activist investor, affirmative action, Affordable Care Act / Obamacare, airport security, American Society of Civil Engineers: Report Card, asset allocation, behavioural economics, Bernie Madoff, Bernie Sanders, Blythe Masters, Bretton Woods, business process, call centre, Capital in the Twenty-First Century by Thomas Piketty, carbon tax, Carl Icahn, carried interest, clean water, collapse of Lehman Brothers, collective bargaining, computerized trading, corporate governance, corporate raider, corporate social responsibility, Credit Default Swap, currency manipulation / currency intervention, deal flow, Donald Trump, electricity market, ending welfare as we know it, failed state, fake news, financial deregulation, financial engineering, financial innovation, future of work, ghettoisation, Glass-Steagall Act, Gordon Gekko, hiring and firing, Home mortgage interest deduction, immigration reform, income inequality, invention of radio, job automation, junk bonds, knowledge economy, knowledge worker, labor-force participation, laissez-faire capitalism, low interest rates, Mahatma Gandhi, Mark Zuckerberg, Michael Milken, military-industrial complex, mortgage tax deduction, Neil Armstrong, new economy, Nixon triggered the end of the Bretton Woods system, obamacare, old-boy network, opioid epidemic / opioid crisis, paper trading, Paris climate accords, performance metric, post-work, Potemkin village, Powell Memorandum, proprietary trading, quantitative hedge fund, Ralph Nader, ride hailing / ride sharing, Robert Bork, Robert Gordon, Robert Mercer, Ronald Reagan, Rutger Bregman, Salesforce, shareholder value, Silicon Valley, Social Responsibility of Business Is to Increase Its Profits, stock buybacks, Tax Reform Act of 1986, tech worker, telemarketer, too big to fail, trade liberalization, union organizing, Unsafe at Any Speed, War on Poverty, women in the workforce, working poor

“Before Citizens United,” Israel explained, “you at least had a good view of what the opponent would spend and what you would need to spend. Now, you’re flying blind, because in the last two or three weeks some super PAC could come in with $20 million and wipe you out. You always have to keep raising money, just in case.” Super PACs raised $1.8 billion in the 2016 election cycle, as people such as Robert Mercer on the right and Tom Steyer on the left became the most important political power players most Americans had never heard of. That does not count at least $250 million in “dark money” raised by tax-exempt entities that did not call themselves political action committees, but made their own independent expenditures without even having to reveal donors because they instead declared that they were social welfare or educational organizations.


pages: 574 words: 148,233

Sandy Hook: An American Tragedy and the Battle for Truth by Elizabeth Williamson

"World Economic Forum" Davos, 2021 United States Capitol attack, 4chan, Affordable Care Act / Obamacare, Airbnb, anti-communist, anti-globalists, Asperger Syndrome, Big Tech, Black Lives Matter, Cambridge Analytica, citizen journalism, Columbine, Comet Ping Pong, coronavirus, COVID-19, crisis actor, critical race theory, crowdsourcing, dark triade / dark tetrad, deplatforming, disinformation, Donald Trump, Dr. Strangelove, estate planning, fake news, false flag, Ferguson, Missouri, fulfillment center, illegal immigration, index card, Internet Archive, Jon Ronson, Jones Act, Kevin Roose, Mark Zuckerberg, medical malpractice, messenger bag, multilevel marketing, obamacare, Oklahoma City bombing, Parler "social media", post-truth, QAnon, Robert Mercer, Russian election interference, Saturday Night Live, Sheryl Sandberg, Silicon Valley, source of truth, Steve Bannon, Susan Wojcicki, TED Talk, TikTok, Timothy McVeigh, traveling salesman, Twitter Arab Spring, We are Anonymous. We are Legion, WikiLeaks, work culture , Works Progress Administration, yellow journalism

In April 2018, the same month Lenny, Veronique, and Neil filed their lawsuits against Jones, Facebook founder Mark Zuckerberg testified before Congress amid the biggest crisis in his company’s history. The New York Times, with London’s Observer and The Guardian, had written a series of stories[4] based on a trove of documents proving that Cambridge Analytica, a company controlled by right-wing megadonor Robert Mercer, improperly accessed the personal data of tens of millions of Facebook users in 2014. The harvesting amounted to the largest known leak in the company’s history. Stephen K. Bannon, a top Trump campaign official and later White House adviser, sat on Cambridge Analytica’s board. The company used the information it collected to construct psychological profiles of potential voters, which it then tried to sell in the run-up to the 2016 presidential election.


pages: 510 words: 163,449

How the Scots Invented the Modern World: The True Story of How Western Europe's Poorest Nation Created Our World and Everything in It by Arthur Herman

British Empire, California gold rush, classic study, creative destruction, do-ocracy, Edward Jenner, financial independence, gentleman farmer, global village, invisible hand, Isaac Newton, James Watt: steam engine, Joan Didion, joint-stock company, laissez-faire capitalism, land tenure, mass immigration, means of production, new economy, New Urbanism, North Sea oil, oil shale / tar sands, Republic of Letters, Robert Mercer, spinning jenny, The Wealth of Nations by Adam Smith, tontine, transcontinental railway, trickle-down economics, urban planning, urban renewal, vertical integration, working poor

There the old chieftain, who had once boasted of having five hundred warriors at his beck and call, expired, surrounded by the clansmen he had led to defeat and death. The slaughter among the clan leadership was heavy. Grapeshot had shattered both of Lord Lochiel’s ankles, and he had to be carried off the field. The only regimental commanders to escape unwounded were Lord George Murray, Lord Ardshiel, and Lord Nairne—although Nairne’s brother, Robert Mercer of Aldie, was killed, as was Mercer’s son Thomas. Their bodies were never found. Only three of the Mackintosh officers survived. But if the Jacobite chieftains and their tacksmen paid a heavy price for their misplaced loyalties, it was their followers who suffered most from the retributions of Cumberland and his soldiers.


pages: 864 words: 272,918

Palo Alto: A History of California, Capitalism, and the World by Malcolm Harris

2021 United States Capitol attack, Aaron Swartz, affirmative action, air traffic controllers' union, Airbnb, Alan Greenspan, Alvin Toffler, Amazon Mechanical Turk, Amazon Web Services, Apple II, Apple's 1984 Super Bowl advert, back-to-the-land, bank run, Bear Stearns, Big Tech, Bill Gates: Altair 8800, Black Lives Matter, Bob Noyce, book scanning, British Empire, business climate, California gold rush, Cambridge Analytica, capital controls, Charles Lindbergh, classic study, cloud computing, collective bargaining, colonial exploitation, colonial rule, Colonization of Mars, commoditize, company town, computer age, conceptual framework, coronavirus, corporate personhood, COVID-19, cuban missile crisis, deindustrialization, Deng Xiaoping, desegregation, deskilling, digital map, double helix, Douglas Engelbart, Edward Snowden, Elon Musk, Erlich Bachman, estate planning, European colonialism, Fairchild Semiconductor, financial engineering, financial innovation, fixed income, Frederick Winslow Taylor, fulfillment center, future of work, Garrett Hardin, gentrification, George Floyd, ghettoisation, global value chain, Golden Gate Park, Google bus, Google Glasses, greed is good, hiring and firing, housing crisis, hydraulic fracturing, if you build it, they will come, illegal immigration, immigration reform, invisible hand, It's morning again in America, iterative process, Jeff Bezos, Joan Didion, John Markoff, joint-stock company, Jony Ive, Kevin Kelly, Kickstarter, knowledge worker, land reform, Larry Ellison, Lean Startup, legacy carrier, life extension, longitudinal study, low-wage service sector, Lyft, manufacturing employment, Marc Andreessen, Marc Benioff, Mark Zuckerberg, Marshall McLuhan, Max Levchin, means of production, Menlo Park, Metcalfe’s law, microdosing, Mikhail Gorbachev, military-industrial complex, Monroe Doctrine, Mont Pelerin Society, moral panic, mortgage tax deduction, Mother of all demos, move fast and break things, mutually assured destruction, new economy, Oculus Rift, off grid, oil shale / tar sands, PageRank, PalmPilot, passive income, Paul Graham, paypal mafia, Peter Thiel, pets.com, phenotype, pill mill, platform as a service, Ponzi scheme, popular electronics, power law, profit motive, race to the bottom, radical life extension, RAND corporation, Recombinant DNA, refrigerator car, Richard Florida, ride hailing / ride sharing, rising living standards, risk tolerance, Robert Bork, Robert Mercer, Robert Metcalfe, Ronald Reagan, Salesforce, San Francisco homelessness, Sand Hill Road, scientific management, semantic web, sexual politics, Sheryl Sandberg, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, social web, SoftBank, software as a service, sovereign wealth fund, special economic zone, Stanford marshmallow experiment, Stanford prison experiment, stem cell, Steve Bannon, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, stock buybacks, strikebreaker, Suez canal 1869, super pumped, TaskRabbit, tech worker, Teledyne, telemarketer, the long tail, the new new thing, thinkpad, Thorstein Veblen, Tim Cook: Apple, Tony Fadell, too big to fail, Toyota Production System, Tragedy of the Commons, transcontinental railway, traumatic brain injury, Travis Kalanick, TSMC, Uber and Lyft, Uber for X, uber lyft, ubercab, union organizing, Upton Sinclair, upwardly mobile, urban decay, urban renewal, value engineering, Vannevar Bush, vertical integration, Vision Fund, W. E. B. Du Bois, War on Poverty, warehouse robotics, Wargames Reagan, Washington Consensus, white picket fence, William Shockley: the traitorous eight, women in the workforce, Y Combinator, Y2K, Yogi Berra, éminence grise

Soon after, a right-wing media impresario named Steve Bannon approached SCL with an idea for a U.S. spin-off. SCL was used to manage election propaganda campaigns for the ruling cliques in England’s former colonies, but the United States was a whole new market. When Bannon suggested that his Breitbart News Network funders Robert Mercer and his daughter Rebekah were interested in financing the effort, anything seemed possible. Like the SCL boss, Alexander Nix, Bannon and Bob Mercer were big admirers of Thiel’s project. As the young SCL research head, Christopher Wylie, later wrote, it seemed to him that “these men wanted to create their own private Palantir” at the consultancy—the Mercers promised $15–20 million.61 The use for Bob Mercer, an IBM engineer turned hedge-fund guru, seemed obvious: modeling the future for profit.