Cambridge Analytica

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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

However, this subsidiary was bestowed the IP rights to SCL’s work, creating a bizarre situation where the subsidiary actually owned the core assets of its “parent.” SCL and Cambridge Analytica then signed an exclusivity agreement whereby Cambridge Analytica would transfer all of its contracts to SCL, and SCL’s personnel would service the actual delivery and work on behalf of Cambridge Analytica. And then, to allow SCL staff to use the IP that it originally gave to Cambridge Analytica, the IP was then licensed back to SCL. Nix initially explained how this labyrinthine setup was to allow us to operate under the radar. Mercer’s rivals in the finance sector watched his every move, and if they knew that he had acquired a psychological warfare firm, others in the industry might figure out his next play—to develop sophisticated trend-forecasting tools—or poach key staff.

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Now I understood that this was how Cummings had gotten around the fact that Cambridge Analytica was already working with Leave.EU—he just used one of CA’s subsidiaries, based in a different country, with a name that no one knew. AIQ had Cambridge Analytica’s infrastructure, handled all of its data, and could perform all the same functions, but without the label. (Vote Leave denies that it had access to Cambridge Analytica’s Facebook data.) Nobody had wanted to tell me because everyone knew that I had left Cambridge Analytica on such bad terms, as had many others. Silvester and Massingham chose to stay quiet because this was their biggest gig in politics.

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What, she asked me, is Cambridge Analytica? “It’s Steve Bannon’s psychological mindfuck tool,” I told her bluntly. Even a well-informed journalist like Cadwalladr struggled at first to understand all the layers and connections of the Cambridge Analytica narrative. Was SCL part of Cambridge Analytica, or the other way around? Where did AIQ fit in? And even when she had the basic details nailed down, there was still so much more to share. I told her about psychometric profiling, information warfare, and artificial intelligence. I explained Bannon’s role and how we had used Cambridge Analytica to build psychological warfare tools to fight his culture war.

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

“Ex-Daughter-in-Law of Vincente Fox Kidnapped,” Borderland Beat (blog), May 1, 2015, http://www.borderlandbeat.com/2015/05/ex-daughter-in-law-of-vincente-fox.html. 3.María Idalia Gómez, “Liberan a ex nuera de Fox: Mónica Jurado Maycotte Permaneció 8 Meses Secuestrada,” EJCentral, December 16, 2015, http://www.ejecentral.com.mx/liberan-a-ex-nuera-de-fox/. 4.Eugene Kiely, “Timeline of Russia Investigation,” FactCheck.org, April 22, 2019, https://www.factcheck.org/2017/06/timeline-russia-investigation/. 17: INQUIRY 1.Alexander Nix, “How Big Data Got the Better of Donald Trump,” Campaign, February 10, 2016, https://www.campaignlive.co.uk/article/big-data-better-donald-trump/1383025#bpBH5hbxRmLJyxh0.99. 18: RESTART 1.Paul Grewal, “Suspending Cambridge Analytica and SCL Group from Facebook,” Newsroom, Facebook, March 16, 2018, https://newsroom.fb.com/news/2018/03/suspending-cambridge-analytica/. 2.Alfred Ng, “Facebook’s ‘Proof’ Cambridge Analytica Deleted That Data? A Signature,” CNet.com, https://www.cnet.com/news/facebook-proof-cambridge-analytica-deleted-that-data-was-a-signature/. 3.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. 4.Carole Cadwalladr, “‘I Made Steve Bannon’s Psychological Warfare Tool’: Meet the Data War Whistleblower,” Guardian, March 18, 2018, https://www.theguardian.com/news/2018/mar/17/data-war-whistleblower-christopher-wylie-faceook-nix-bannon-trump. 19: OF TRUTH AND CONSEQUENCES 1.Matthew Weaver, “Facebook Scandal: I Am Being Used as a Scapegoat—Academic Who Mined Data,” Guardian, March 21, 2018, https://www.theguardian.com/uk-news/2018/mar/21/facebook-row-i-am-being-used-as-scapegoat-says-academic-aleksandr-kogan-cambridge-analytica. 2.Selena Larson, “Investors Sue Facebook Following Data Harvesting Scandal,” CNN, March 21, 2018, https://money.cnn.com/2018/03/20/technology/business/investors-sue-facebook-cambridge-analytica/index.html. 3.Andy Kroll, “Cloak and Data: The Real Story Behind Cambridge Analytica’s Rise and Fall,” Mother Jones, May/June 2018, https://www.motherjones.com/politics/2018/03/cloak-and-data-cambridge-analytica-robert-mercer/. 4.Ibid. 5.Ibid. 6.Joanna Walters, “Steve Bannon on Cambridge Analytica: ‘Facebook Data Is for Sale All over the World,’” Guardian, March 22, 1018, https://www.theguardian.com/us-news/2018/mar/22/steve-bannon-on-cambridge-analytica-facebook-data-is-for-sale-all-over-the-world.

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A Signature,” CNet.com, https://www.cnet.com/news/facebook-proof-cambridge-analytica-deleted-that-data-was-a-signature/. 3.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. 4.Carole Cadwalladr, “‘I Made Steve Bannon’s Psychological Warfare Tool’: Meet the Data War Whistleblower,” Guardian, March 18, 2018, https://www.theguardian.com/news/2018/mar/17/data-war-whistleblower-christopher-wylie-faceook-nix-bannon-trump. 19: OF TRUTH AND CONSEQUENCES 1.Matthew Weaver, “Facebook Scandal: I Am Being Used as a Scapegoat—Academic Who Mined Data,” Guardian, March 21, 2018, https://www.theguardian.com/uk-news/2018/mar/21/facebook-row-i-am-being-used-as-scapegoat-says-academic-aleksandr-kogan-cambridge-analytica. 2.Selena Larson, “Investors Sue Facebook Following Data Harvesting Scandal,” CNN, March 21, 2018, https://money.cnn.com/2018/03/20/technology/business/investors-sue-facebook-cambridge-analytica/index.html. 3.Andy Kroll, “Cloak and Data: The Real Story Behind Cambridge Analytica’s Rise and Fall,” Mother Jones, May/June 2018, https://www.motherjones.com/politics/2018/03/cloak-and-data-cambridge-analytica-robert-mercer/. 4.Ibid. 5.Ibid. 6.Joanna Walters, “Steve Bannon on Cambridge Analytica: ‘Facebook Data Is for Sale All over the World,’” Guardian, March 22, 1018, https://www.theguardian.com/us-news/2018/mar/22/steve-bannon-on-cambridge-analytica-facebook-data-is-for-sale-all-over-the-world.

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He was terribly busy, he said, so busy and so hopeful for the future that the SCL Group had had to spin off an entirely new company just to manage the work in the United States alone. That new company was called Cambridge Analytica. It had been in business for just under a year, but the world had best pay attention to it, Nix said. Cambridge Analytica was about to cause a revolution. The revolution Nix had in mind had to do with Big Data and analytics. In the digital age, data was “the new oil.” Data collection was an “arms race,” he said. Cambridge Analytica had amassed an arsenal of data on the American public of unprecedented size and scope, the largest, as far as he knew, anyone had ever assembled.

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

Chapter 8: Digital Gangsters 1 Stephanie Baker, ‘Cambridge Analytica Won’t Be Revived Under New Company Name’, Bloomberg, May 2018. 2 Katie French and Martin Robinson, ‘Information commissioners leave Cambridge Analytica with a van full of evidence after searching data firm’s London offices for seven hours amid Facebook privacy scandal’, Daily Mail, March 2018. 3 ‘Revealed: Trump’s election consultants filmed saying they use bribes and sex workers to entrap politicians’, Channel 4, March 2018. 4 ‘Facebook: Explaining the company’s massive share slump’, BBC, July 2018. 5 Rob Davies and Dominic Rushe, ‘Facebook to pay $5bn fine as regulator settles Cambridge Analytica complaint’, Guardian, July 2019. 6 Carole Cadwalladr, ‘Fresh Cambridge Analytica leak “shows global manipulation is out of control”’, Guardian, January 2020. 7 Carole Cadwalladr, ‘Cambridge Analytica’s ruthless bid to sway the vote in Nigeria’, Guardian, March 2018. 8 Larry Madowo, ‘How Cambridge Analytica poisoned Kenya’s democracy’, Washington Post, March 2018. 9 Holly Watt, ‘MoD granted “List X” status to Cambridge Analytica parent company’, Guardian, March 2018. 10 Jane Mayer, ‘The Reclusive Hedge-Fund Tycoon Behind the Trump Presidency’, New Yorker, March 2017. 11 Curt Devine, Donie O’Sullivan and Drew Griffin, ‘How Steve Bannon used Cambridge Analytica to further his alt-right vision for America’, CNN, May 2018. 12 Amber Macintyre, ‘Who’s Working for Your Vote’, Tactical Tech, November 2018.

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AggregateIQ largely disappeared too – until, in the spring of 2018, the company became embroiled in one of the most controversial political scandals of recent times: the operations of Cambridge Analytica. As Carole Cadwalladr revealed, Cambridge Analytica had illegally harvested millions of US Facebook users’ data for political advertising ahead of the 2016 US presidential campaign. The London-based company had also been involved in election ‘black ops’ around the world. Reports noted how closely connected AIQ was to Strategic Communications Laboratories, Cambridge Analytica’s parent company. AIQ had the same phone number as an SCL subsidiary and had worked with Cambridge Analytica on Republican Ted Cruz’s unsuccessful run for the US presidency in 2016.54 Amid a barrage of negative publicity, Facebook decided to suspend AIQ as it may “have improperly received FB user data”.

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Ashcroft demurred.45 (Ashcroft did not fund Leave.EU, but his imprint published The Bad Boys of Brexit, which was ghost-written by his close collaborator Isabel Oakeshott.) Cambridge Analytica appeared keener to help with US fundraising. On 25 October 2015, the day after Banks had emailed his advisors and Steve Bannon about attracting American donors for his campaign, a Cambridge Analytica employee replied, saying that the firm could develop a proposal that would include “US-based fundraising strategies”.46 (Banks said that this proposal was never followed up.) Leave.EU’s leadership had already met with senior Cambridge Analytica staff to discuss what Banks called a “two stage process” to “get CA on the team”. Cambridge Analytica also asked Leave.EU to “connect us” to Matthew Goodwin, a political scientist who had conducted extensive research on UKIP voters.

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

Speculation by journalists and pundits about legal issues that might arise from the Cambridge Analytica story lit up Twitter for hours. Legal analysts focused on the possibility of a data breach that might have placed Facebook in violation of state laws and FTC regulations. Failure to comply with the FTC consent decree carried a penalty as high as forty thousand dollars per offense. In the case of Cambridge Analytica, the penalty could potentially be measured in the trillions of dollars, far more than the value of Facebook. Cambridge Analytica might be vulnerable to prosecution for fraud and campaign finance violations. The Cambridge Analytica story transformed the conversation about Facebook, providing something to worry about for just about everyone.

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Three states, which Trump won by a total of 77,744 votes, provided more than the margin of victory in the electoral college. Is it possible that the Cambridge Analytica data set might have influenced the outcome? Yes. It’s virtually impossible that it didn’t. Targeting inside Facebook mattered because it works. Cambridge Analytica’s original client, the presidential campaign of Senator Ted Cruz, complained that the psychographic models sold by Cambridge Analytica did not work for them. In the end, psychographics probably didn’t matter to the Trump campaign. They had more powerful weapons available to them, in the form of Cambridge Analytica’s data set of thirty million enhanced voter files and Facebook’s targeting tools and employees.

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The UK’s ITN Channel 4 added to the story with a series of undercover exposés about Cambridge Analytica that reflected very badly on that company and, by extension, on Facebook. In one of the exposés, senior executives of Cambridge Analytica are captured on film bragging about their ability to use prostitutes to entrap politicians. The Guardian also reminded readers that it had previously revealed the connection between Kogan and Cambridge Analytica in a story in December 2015. Facebook claimed at the time not to have known that Cambridge Analytica had gained possession of Kogan’s data set. Citing a violation of its terms of service, Facebook sent letters to Cambridge Analytica and Kogan, insisting that they destroy all copies of the data set and certify that they had done so by checking off a box in a form.

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

CHAPTER SIXTEEN: Clown Show news of this broke: Though there had been previous reporting, the Cambridge Analytica/Facebook story broke through on March 17, 2018, with simultaneous publication in The Guardian/Observer (Carole Cadwalladr and Emma Harrison, “Revealed: 50 Million Facebook Profiles Harvested for Cambridge Analytica in Major Data Breach”) and the New York Times (Matthew Rosenberg, Nicholas Confessore, and Carole Cadwalladr, “How Trump Consultants Exploited the Facebook Data of Millions”). Psychometrics Centre: The best account of how the Cambridge Analytica scandal intertwined with the center is Issie Lapowsky, “The Man Who Saw the Dangers of Cambridge Analytica Years Ago,” Wired, June 19, 2018.

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for months: The internal email chain preceding and directly following the 2015 Guardian story was released in 2019 as a part of Cambridge Analytica civil litigation. Hendrix also contacted: Kaiser, Targeted, 159. deleted the data: In District of Columbia v. Facebook, the complaint cited the dates that Kogan and Cambridge Analytica affirmed that the data was deleted. In its response on July 8, 2019, Facebook conceded that those dates were accurate. The company has confirmed this to me directly. raw data in Cambridge Analytica’s files: Matthew Rosenberg and Gabriel J. X. Dance, “‘You Are the Product’: Targeted by Cambridge Analytica on Facebook,” New York Times, April 8, 2018.

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Again, Facebook took its word and did not use the opportunity to conduct an audit to verify the claim. A year later, the UK Information Commission searched CA’s computers and found that Cambridge Analytica might still have been using data models that benefited from the Facebook information. To this day, it isn’t clear whether the company’s election efforts used Facebook profiles, though The New York Times reported that it had seen the raw data in Cambridge Analytica’s files, and former Cambridge Analytica executive Brittany Kaiser says that the data was indeed part of the election targeting. And at no time during 2016 or 2017 did Facebook inform millions of users that their personal information had been operationalized—and their own News Feeds manipulated—for political purposes.

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

He next directed Sandberg and the legal and security teams to scour emails, memos, and messages among Facebook employees, Kogan, and Cambridge Analytica to figure out how the company had lost track of its own data. But the employees who knew about the arrangement with Cambridge Analytica had either left Facebook or lost contact with their business partners. On March 19, Facebook hired a digital forensics firm in London to try to access Cambridge Analytica’s servers. The UK Information Commissioner’s Office turned the staff away; it had already seized the servers.16 The little that Facebook knew was damning. The company had learned about Cambridge Analytica in December 2015, from a report in the Guardian on how the presidential campaign of Ted Cruz had hired the political consulting firm for its ability to use Facebook data to target voters.17 One of Facebook’s partnership managers had ordered the company to delete the data after the story was published, but no one had followed up for confirmation.

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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.

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“The FTC action will ensure it will not.” And yet, here they were, seven years later, in apparent violation of the decree. British authorities also opened an investigation into Facebook and seized Cambridge Analytica’s servers. The United Kingdom had already begun to investigate the political consulting firm over its alleged role in the 2016 referendum in which Britons voted to leave the European Union, a move known as “Brexit.” The new revelations about Cambridge Analytica’s harvesting of Facebook data fanned concerns in Great Britain over political targeting in the lead-up to that contentious vote.15 Facebook’s stock had dropped 10 percent since the news broke, wiping out $50 billion of the company’s market capitalization.

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

CHAPTER FIVE Cambridge Hyperbolytica After the 2016 US presidential election, a company called Cambridge Analytica announced that its data-driven campaign had been instrumental in Donald Trump’s victory. The front page of the company’s website featured a montage of clips from CNN, CBSN, Bloomberg and Sky News showing the story of how it had used targeted online marketing and micro-level polling data to influence voters. The film ended with a quote from the political pollster Frank Luntz: ‘There are no longer any experts except Cambridge Analytica. They were Trump’s team who figured out how to win.’ Cambridge Analytica (CA) gave a great deal of prominence to the Big Five personality model in its promotional material.

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These views came just as often from those with a more utopian vision, like COMPAS creator Tim Brennan who saw a future where algorithms help us with critical decisions, as those with a more dystopian view, like the people blogging angrily about Cambridge Analytica. Both sides believed that computers were either currently outperforming us or would soon outperform us in a large range of tasks. The impression that we are experiencing a massive change in what algorithms can achieve was reflected in the media. Reporting around the COMPAS algorithm, on Cambridge Analytica and on the power of targeted advertising on Google and Facebook were full of references to the potential dangers of AI. What I had found so far gave a different picture. When I looked more closely at Cambridge Analytica and political personalities, I’d found fundamental limitations of algorithm accuracy.

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The inputs to the regression model – gender, age, class and inflation perception – were fed into the model and the output was the probability that person voted Labour. Cambridge Analytica and other modern data analytics companies use more or less the same statistical techniques as were used in the 1980s. The major difference between now and then is the data they have access to. It is possible to feed Facebook likes, answers to online poll questions and data on the purchases we make into regression models. Instead of relying on just age, class and gender to characterise us, Cambridge Analytica claims to use these large data sets to establish an overall view of our personality and political standpoint.

How to Stand Up to a Dictator by Maria Ressa

2021 United States Capitol attack, activist lawyer, affirmative action, Affordable Care Act / Obamacare, airport security, anti-communist, Asian financial crisis, Big Tech, Brexit referendum, business process, business process outsourcing, call centre, Cambridge Analytica, citizen journalism, cognitive bias, colonial rule, commoditize, contact tracing, coronavirus, COVID-19, crowdsourcing, delayed gratification, disinformation, Donald Trump, fake news, future of journalism, iterative process, James Bridle, Kevin Roose, lockdown, lone genius, Mahatma Gandhi, Mark Zuckerberg, Marshall McLuhan, Menlo Park, Milgram experiment, move fast and break things, natural language processing, Nelson Mandela, Network effects, obamacare, performance metric, QAnon, recommendation engine, Sheryl Sandberg, Shoshana Zuboff, Silicon Valley, Steven Levy, surveillance capitalism, the medium is the message, The Wisdom of Crowds, TikTok, Twitter Arab Spring, work culture

v=7OLUfA6QJlE. 10.Christopher Wylie, Mindf*ck: Cambridge Analytica and the Plot to Break America (New York: Random House, 2019). 11.“EXCLUSIVE: Interview with Cambridge Analytica Whistle-Blower Christopher Wylie,” Rappler, September 12, 2019, https://www.rappler.com/technology/social-media/239972-cambridge-analytica-interview-christopher-wylie/. 12.Ibid. 13.Raissa Robles, “Cambridge Analytica Boss Alexander Nix Dined with Two of Rodrigo Duterte’s Campaign Advisers in 2015,” South China Morning Post, April 8, 2018, https://www.scmp.com/news/asia/southeast-asia/article/2140782/cambridge-analytica-boss-alexander-nix-dined-two-rodrigo. 14.

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Chris had learned data and targeting in the Obama campaign, taken it to Canada’s opposition, had taught himself to code, had gone to law school at the London School of Economics, and had been getting his PhD in fashion trend forecasting when he had gotten the idea for Cambridge Analytica’s “psychological warfare mindfuck tool,”10 as he would call it. When we talked, he was also able to fully explain the relationship between Cambridge Analytica and the Philippines. “When the Cambridge Analytica scandal broke,” I said to him at our first meeting, “the most number of compromised Facebook accounts was in the US, but the second most . . .” “. . . was in the Philippines,” he replied right away.11 The company Chris worked for was a company called SCL (Strategic Communications Laboratory) Group, the parent company of Cambridge Analytica, which had a relatively long history of working in Filipino politics.

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“Duterte Himself Banned Rappler Reporter from Malacañang Coverage,” Rappler, February 20, 2018, https://www.rappler.com/nation/196474-duterte-orders-psg-stop-rappler-reporter-malacanang/. 11.Pia Ranada, “Duterte Admits Role in Navy–Bong Go Frigates Issue,” Rappler, October 19, 2018, https://www.rappler.com/nation/214676-duterte-admits-role-philippine-navy-bong-go-frigates-issue/. 12.Miriam Grace A Go, “‘We’re Not Scared of These Things’: Rappler News Editor on How the Newsroom Continues Despite the Increasing Threats, Alongside Words from Their CEO Maria Ressa,” Index on Censorship 47, no. 2 (July 2018): 48–51, https://journals.sagepub.com/doi/10.1177/0306422018784531. 13.Lian Buan, “SC Allows Other Journalists to Join Rappler Petition vs Duterte Coverage Ban,” Rappler, August 15, 2019, https://www.rappler.com/nation/237722-supreme-court-allows-other-journalists-join-rappler-petition-vs-duterte-coverage-ban. 14.Mark Zuckerberg, Facebook, January 11, 2018, https://www.facebook.com/zuck/posts/one-of-our-big-focus-areas-for-2018-is-making-sure-the-time-we-all-spend-on-face/10104413015393571/. 15.Mike Isaac, “Facebook Overhauls News Feed to Focus on What Friends and Family Share,” New York Times, January 11, 2018, https://www.nytimes.com/2018/01/11/technology/facebook-news-feed.html. 16.Alex Hern, “Facebook Moving Non-promoted Posts Out of News Feed in Trial,” Guardian, October 23, 2017, https://www.theguardian.com/technology/2017/oct/23/facebook-non-promoted-posts-news-feed-new-trial-publishers. 17.Filip Struhárik, “Biggest Drop in Facebook Organic Reach We Have Ever Seen,” Medium, October 21, 2017, https://medium.com/@filip_struharik/biggest-drop-in-organic-reach-weve-ever-seen-b2239323413. 18.Steve Kovach, “Facebook Is Trying to Prove It’s Not a Media Company by Dropping the Guillotine on a Bunch of Media Companies,” Insider, January 13, 2018, https://www.businessinsider.com/facebooks-updated-news-feed-algorithm-nightmare-for-publishers-2018-1. 19.Adam Mosseri, “Facebook Recently Announced a Major Update to News Feed; Here’s What’s Changing,” Meta, April 18, 2018, https://about.fb.com/news/2018/04/inside-feed-meaningful-interactions/. 20.Sheera Frenkel, Nicholas Casey, and Paul Mozur, “In Some Countries, Facebook’s Fiddling Has Magnified Fake News,” New York Times, January 4, 2018, https://www.nytimes.com/2018/01/14/technology/facebook-news-feed-changes.html. 21.Mariella Mostof, “‘The Great Hack’ Features the Journalist Who Broke the Cambridge Analytica Story,” Romper, July 24, 2019, https://www.romper.com/p/who-is-carole-cadwalladr-the-great-hack-tells-the-investigative-journalists-explosive-story-18227928. 22.“Philippines’ Watchdog Probes Facebook over Cambridge Analytica Data Breach,” Reuters, April 13, 2018, https://www.reuters.com/article/us-facebook-privacy-philippines-idUSKBN1HK0QC. 23.Cambridge Analytica and its parent company, SCL, worked in the Philippines as early as 2013. These stories provide background: Natashya Gutierrez, “Did Cambridge Analytica Use Filipinos’ Facebook Data to Help Duterte Win?”

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

The resulting furore led to several days of front page media coverage, the UK’s Information Commissioner seeking a warrant to look at Cambridge Analytica’s databases, and billions of dollars being wiped off Facebook’s value.28 Shortly after returning from San Antonio I managed to secure an interview with Cambridge Analytica CEO Alexander Nix. As I walked in to the ordinary looking office in central London – all offices are normal looking, except those of tech firms – I spotted a framed posted with a picture of Trump and a quote from famed US pollster Frank Luntz: ‘There are no longer any experts except Cambridge Analytica. They were Trump’s digital team who figured out how to win.’

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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.

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The idea was to figure out how to apply these techniques to politics – and especially to help the Republican Party, which Mercer felt had fallen behind the Democrats in their digital campaigning.9 Mercer invested a load of money into the new company. Cambridge was also part of a tight pro-Trump network: Steve Bannon, until recently boss of Breitbart and Trump’s first head of strategy, was also a board member of Cambridge Analytica until he joined the administration. From their inception Cambridge Analytica followed the Mercer bible. They built up a database of around 5,000 data points on some 230 million Americans. Some of the data was purchased from commercially available sources – web browsing histories, purchasing, income and voter records, car ownership and so on – and some was collected through Facebook and telephone surveys.10 They were initially part of Ted Cruz’s campaign for the Republican nomination, but once he dropped out of the Republican race, the company transferred to Trump.

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

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

Kogan then developed his own app, called This Is Your Digital Life, which mimicked myPersonality, and shared the data and methods with Cambridge Analytica. In 2017, Cambridge Analytica told Das Magazin that it “has had no dealings” with Kosinski and “does not use the same methodology” as he did, although, as journalist John Morgan noted, Cambridge Analytica’s methods are “undeniably similar.” This cloak-and-dagger detour is important because it reveals that the Matz et al. study is as close to a systematic audit of the persuasive power of Cambridge Analytica’s methods and data as is publicly available. Facebook doesn’t allow marketers to target advertisements based on personality.

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So what does all this imply about Cambridge Analytica’s targeting? Can our personalities really reveal these niche interests and drive targeting performance? Cambridge Analytica Alexander Nix touted the importance of “psychographic profiling” onstage at the Concordia summit and conferences around the world. He suggested that knowing people’s psychographic profiles; that is, having “an understanding of your personality,” is the most important thing needed to manipulate voter behavior because “it’s personality that drives behavior and behavior that obviously influences how you vote.” Did Cambridge Analytica genuinely have a secret sauce, or was it selling snake oil?

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It’s impossible to tell this story without stopping for a moment to discuss the cloak-and-dagger intrigue connecting Kosinski, Stillwell, and the myPersonality app to the larger Cambridge Analytica scandal because, in an eyebrow-raising twist, Kosinski and Stillwell conducted their research while at Cambridge University, in the same department as Aleksandr Kogan, the now-infamous Cambridge University researcher who gave psychological profiles and Facebook data on 50 million Americans to Cambridge Analytica, which then sparked the scandal that landed Mark Zuckerberg in the hot seat. Investigative reporting on the relationships among these researchers suggests that Kogan approached Kosinski on behalf of an unnamed company (Cambridge Analytica) that was interested in his methods and wanted access to the myPersonality database.

Data Action: Using Data for Public Good by Sarah Williams

affirmative action, Amazon Mechanical Turk, Andrei Shleifer, augmented reality, autonomous vehicles, Brexit referendum, Cambridge Analytica, Charles Babbage, City Beautiful movement, commoditize, coronavirus, COVID-19, crowdsourcing, data acquisition, data is the new oil, data philanthropy, data science, digital divide, digital twin, Donald Trump, driverless car, Edward Glaeser, fake news, four colour theorem, global village, Google Earth, informal economy, Internet of things, Jane Jacobs, John Snow's cholera map, Kibera, Lewis Mumford, Marshall McLuhan, mass immigration, mass incarceration, megacity, military-industrial complex, Minecraft, neoliberal agenda, New Urbanism, Norbert Wiener, nowcasting, oil shale / tar sands, openstreetmap, place-making, precautionary principle, RAND corporation, ride hailing / ride sharing, selection bias, self-driving car, sentiment analysis, Sidewalk Labs, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, Steven Levy, the built environment, The Chicago School, The Death and Life of Great American Cities, transatlantic slave trade, Uber for X, upwardly mobile, urban planning, urban renewal, W. E. B. Du Bois, Works Progress Administration

Chapter 3 1 Steven Levy, Hackers: Heroes of the Computer Revolution, vol. 14 (Garden City, NY: Anchor Press/Doubleday, 1984). 2 Patrick Greenfield, “The Cambridge Analytica Files: The Story so Far,” Guardian, March 25, 2018, https://www.theguardian.com/news/2018/mar/26/the-cambridge-analytica-files-the-story-so-far. 3 Annabel Latham, “Cambridge Analytica Scandal: Legitimate Researchers Using Facebook Data Could Be Collateral Damage,” The Conversation, accessed July 6, 2019, http://theconversation.com/cambridge-analytica-scandal-legitimate-researchers-using-facebook-data-could-be-collateral-damage-93600. 4 “Reporter Shows the Links between the Men behind Brexit and the Trump Campaign,” NPR.org, accessed July 6, 2019, https://www.npr.org/2018/07/19/630443485/reporter-shows-the-links-between-the-men-behind-brexit-and-the-trump-campaign. 5 Matthew Rosenberg, “Academic behind Cambridge Analytica Data Mining Sues Facebook for Defamation,” New York Times, March 15, 2019, https://www.nytimes.com/2019/03/15/technology/aleksandr-kogan-facebook-cambridge-analytica.html. 6 Matthew Zook et al., “Ten Simple Rules for Responsible Big Data Research,” PLOS Computational Biology 13, no. 3 (March 30, 2017): e1005399, https://doi.org/10.1371/journal.pcbi.1005399. 7 One notable way of alienating entire communities is by crime mapping: creating hot-spot analyses to pinpoint where crimes take place is to mark clusters as criminal neighborhoods.

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The Ethics of Using Data We Find on the Web Among the most important ethical concerns about the use of big data today is one that involves the ubiquitous “terms of service” that companies all over the world ask us to “sign” before to using their online services: as a result we provide our consent for these companies to use the data we contribute to their sites; but that doesn't mean we approve of some of the ways the data is eventually used. Data sets amassed by private companies include vast amounts of detailed information about our personal habits and behaviors that can easily be turned against us. The Facebook/Cambridge Analytica scandal provides a smoking gun for how the data we contribute online is used without our explicit consent to sell us political agendas and offer fake news. Here's a brief recap of how the situation played out. Cambridge Analytica, a now-defunct British consulting firm, developed political ads for the Kenyan leader Uhuru Kenyatta, Donald Trump, and proponents of Brexit during its initial referendum, among others.

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Kogan used an app called “thisisyourdigitallife” to capture data on close to 275,000 Facebook users who consented to participate in a study but didn't know that the application was also capturing information about their friends. This allowed the firm that Kogan owned, Global Science Research (GSR) to amass data that Cambridge Analytica later purchased.3 While reporting on the unusual Brexit results, Carole Callwalladr stumbled upon the details that uncovered the Cambridge Analytica scandal, one of the biggest data scandals in history.4 Facebook pushed much of the blame for the misuse of data onto Kogan, saying he violated the terms of service without its knowledge. Kogan believes Facebook made him the fall guy and has started a defamation case against Facebook for its campaign against him during the scandal.5 Curiously, many of the characters in the scandal had previous relationships with each other long before the data was amassed, which has raised further questions during US congressional and UK parliamentary hearings about the complicity of the parties.

The Contrarian: Peter Thiel and Silicon Valley's Pursuit of Power by Max Chafkin

3D printing, affirmative action, Airbnb, anti-communist, bank run, Bernie Sanders, Big Tech, bitcoin, Black Lives Matter, Black Monday: stock market crash in 1987, Blitzscaling, Boeing 747, borderless world, Cambridge Analytica, charter city, cloud computing, cognitive dissonance, Cornelius Vanderbilt, coronavirus, COVID-19, Credit Default Swap, cryptocurrency, David Brooks, David Graeber, DeepMind, digital capitalism, disinformation, don't be evil, Donald Trump, driverless car, Electric Kool-Aid Acid Test, Elon Musk, Ethereum, Extropian, facts on the ground, Fairchild Semiconductor, fake news, Ferguson, Missouri, Frank Gehry, Gavin Belson, global macro, Gordon Gekko, Greyball, growth hacking, guest worker program, Hacker News, Haight Ashbury, helicopter parent, hockey-stick growth, illegal immigration, immigration reform, Internet Archive, Jeff Bezos, John Markoff, Kevin Roose, Kickstarter, Larry Ellison, life extension, lockdown, low interest rates, Lyft, Marc Andreessen, Mark Zuckerberg, Maui Hawaii, Max Levchin, Menlo Park, military-industrial complex, moral panic, move fast and break things, Neal Stephenson, Nelson Mandela, Network effects, off grid, offshore financial centre, oil shale / tar sands, open borders, operational security, PalmPilot, Paris climate accords, Patri Friedman, paypal mafia, Peter Gregory, Peter Thiel, pets.com, plutocrats, Ponzi scheme, prosperity theology / prosperity gospel / gospel of success, public intellectual, QAnon, quantitative hedge fund, quantitative trading / quantitative finance, randomized controlled trial, regulatory arbitrage, Renaissance Technologies, reserve currency, ride hailing / ride sharing, risk tolerance, Robinhood: mobile stock trading app, Ronald Reagan, Sam Altman, Sand Hill Road, self-driving car, sharing economy, Sheryl Sandberg, Silicon Valley, Silicon Valley billionaire, Silicon Valley ideology, Silicon Valley startup, skunkworks, social distancing, software is eating the world, sovereign wealth fund, Steve Bannon, Steve Jobs, Steven Levy, Stewart Brand, surveillance capitalism, TaskRabbit, tech billionaire, tech worker, TechCrunch disrupt, techlash, technology bubble, technoutopianism, Ted Kaczynski, TED Talk, the new new thing, the scientific method, Tim Cook: Apple, transaction costs, Travis Kalanick, Tyler Cowen, Uber and Lyft, uber lyft, Upton Sinclair, Vitalik Buterin, We wanted flying cars, instead we got 140 characters, Whole Earth Catalog, WikiLeaks, William Shockley: the traitorous eight, Y Combinator, Y2K, yellow journalism, Zenefits

The Facebook founder had insisted that his company had been the victim of Cambridge Analytica’s bad behavior as the Americans who’d had their data stolen, but this argument began to seem weaker when it became clear that a Facebook board member was connected to the scandal. Christopher Wylie, a former Cambridge Analytica employee who’d turned whistleblower, said that he’d seen Palantir engineers in the Cambridge Analytica offices, where they were given Cambridge Analytica logins and helped build additional apps, like Kogan’s quiz, to harvest more private data from Facebook users. If Facebook had been a victim, rather than a willing accomplice of Cambridge Analytica, why had the consultancy been working with a company controlled by Zuckerberg’s mentor? Chmieliauskas was eventually fired, and Palantir said that he was a rogue employee who’d been working “in an entirely personal capacity.”

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involved with political work: Nicholas Confessore and Matthew Rosenberg, “Spy Contractor’s Idea Helped Cambridge Analytica Harvest Facebook Data,” March 27, 2018, The New York Times, https://www.nytimes.com/2018/03/27/us/cambridge-analytica-palantir.html. on the social media platform: Connie Loizos, “ ’When you spend $100 Million on Social Media, It Comes with Help,’ Says Trump strategist,” Techcrunch, November 8, 2017, https://techcrunch.com/2017/11/08/when-you-spend-100-million-on-social-media-it-comes-with-help-says-trump-strategist/. the Cambridge Analytica offices: Christopher Wylie, Mindf*ck: Cambridge Analytica and the Plot to Break America (New York: Random House, 2019), 83, 112‒14.

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Chmieliauskas was, in other words, moving fast and breaking things—bigger things than he could’ve imagined. Because of Palantir’s association with the CIA, clients often assumed that the company specialized in counterintelligence, and Palantir was happy to at least try to oblige them if there was business to be won. “I’d worked on much shadier deals before Cambridge Analytica,” he said. Cambridge Analytica had been founded by an aristocratic Brit, Alexander Nix, whom Chmieliauskas met in 2013. Despite the haughty-sounding name, the company had little to do with Cambridge University—in fact, its office was in London—but Nix’s plan had been to market ideas that had been developed at Cambridge about using people’s Facebook data to guess their personality type.

Hello World: Being Human in the Age of Algorithms by Hannah Fry

23andMe, 3D printing, Air France Flight 447, Airbnb, airport security, algorithmic bias, algorithmic management, augmented reality, autonomous vehicles, backpropagation, Brixton riot, Cambridge Analytica, chief data officer, computer vision, crowdsourcing, DARPA: Urban Challenge, data science, deep learning, DeepMind, Douglas Hofstadter, driverless car, Elon Musk, fake news, Firefox, Geoffrey Hinton, Google Chrome, Gödel, Escher, Bach, Ignaz Semmelweis: hand washing, John Markoff, Mark Zuckerberg, meta-analysis, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, pattern recognition, Peter Thiel, RAND corporation, ransomware, recommendation engine, ride hailing / ride sharing, selection bias, self-driving car, Shai Danziger, Silicon Valley, Silicon Valley startup, Snapchat, sparse data, speech recognition, Stanislav Petrov, statistical model, Stephen Hawking, Steven Levy, systematic bias, TED Talk, Tesla Model S, The Wisdom of Crowds, Thomas Bayes, trolley problem, Watson beat the top human players on Jeopardy!, web of trust, William Langewiesche, you are the product

Which, of course, is precisely what happened with the British political consulting firm Cambridge Analytica. Cambridge Analytica You probably know most of the story by now. Since the 1980s, psychologists have been using a system of five characteristics to quantify an individual’s personality. You get a score on each of the following traits: openness to experience, conscientiousness, extraversion, agreeableness and neuroticism. Collectively, they offer a standard and useful way to describe what kind of a person you are. Back in 2012, a year before Cambridge Analytica came on the scene, a group of scientists from the University of Cambridge and Stanford University began looking for a link between the five personality traits and the pages people ‘liked’ on Facebook.18 They built a Facebook quiz with this purpose in mind, allowing users to take real psychometric tests, while hoping to find a connection between a person’s true character and their online persona.

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Stillwell, ‘Psychological targeting as an effective approach to digital mass persuasion’, Proceedings of the National Academy of Sciences, vol. 114, no. 48, 2017, 201710966. 22. Paul Lewis and Paul Hilder, ‘Leaked: Cambridge Analytica’s blueprint for Trump victory’, Guardian, 23 March 2018. 23. ‘Cambridge Analytica planted fake news’, BBC, 20 March 2018, http://www.bbc.co.uk/news/av/world-43472347/cambridge-analytica-planted-fake-news. 24. Adam D. I. Kramer, Jamie E. Guillory and Jeffrey T. Hancock, ‘Experimental evidence of massive-scale emotional contagion through social networks’, Proceedings of the National Academy of Sciences, vol. 111, no. 24, 2014, pp. 8788–90. 25.

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Overall, the team claimed that matching adverts to a person’s character led to 40 per cent more clicks and up to 50 per cent more purchases than using generic, unpersonalized ads. For an adver­tiser, that’s pretty impressive. All the while, as the academics were publishing their work, ­others were implementing their methods. Among them, so it is alleged, was Cambridge Analytica during their work for Trump’s election campaign. Now, let’s backtrack slightly. There is little doubt that Cambridge Analytica were using the same techniques as my imaginary luxury travel agency Fry’s. Their approach was to identify small groups of people who they believed to be persuadable and target them directly, rather than send out blanket advertising.

The Business of Platforms: Strategy in the Age of Digital Competition, Innovation, and Power by Michael A. Cusumano, Annabelle Gawer, David B. Yoffie

activist fund / activist shareholder / activist investor, Airbnb, AltaVista, Amazon Web Services, AOL-Time Warner, asset light, augmented reality, autonomous vehicles, barriers to entry, bitcoin, blockchain, business logic, Cambridge Analytica, Chuck Templeton: OpenTable:, cloud computing, collective bargaining, commoditize, CRISPR, crowdsourcing, cryptocurrency, deep learning, Didi Chuxing, distributed ledger, Donald Trump, driverless car, en.wikipedia.org, fake news, Firefox, general purpose technology, gig economy, Google Chrome, GPS: selective availability, Greyball, independent contractor, Internet of things, Jeff Bezos, Jeff Hawkins, John Zimmer (Lyft cofounder), Kevin Roose, Lean Startup, Lyft, machine translation, Mark Zuckerberg, market fundamentalism, Metcalfe’s law, move fast and break things, multi-sided market, Network effects, pattern recognition, platform as a service, Ponzi scheme, recommendation engine, Richard Feynman, ride hailing / ride sharing, Robert Metcalfe, Salesforce, self-driving car, sharing economy, Silicon Valley, Skype, Snapchat, SoftBank, software as a service, sovereign wealth fund, speech recognition, stealth mode startup, Steve Ballmer, Steve Jobs, Steven Levy, subscription business, Susan Wojcicki, TaskRabbit, too big to fail, transaction costs, transport as a service, Travis Kalanick, two-sided market, Uber and Lyft, Uber for X, uber lyft, vertical integration, Vision Fund, web application, zero-sum game

More recently, a Yale law student published a widely quoted treatise on why antitrust law must change to address the threats from Amazon and other platform businesses even if their shares in particular markets remain well below the usual thresholds for antitrust action.4 Still, antitrust concerns and signs of market power abuse are not the full story. The 2018 scandal involving Facebook and Cambridge Analytica, for example, revealed that 87 million Facebook users had their personal data accessed without their explicit consent. Cambridge Analytica exploited weak Facebook privacy controls and turned a list of 300,000 people who had voluntarily answered a personality quiz on Facebook into a weapon for manipulating voter perception on a national scale. Ultimately, the Cambridge Analytica debacle raised broader questions about who is responsible and liable for activities on a platform. Are the participants on the different “market sides” responsible for their specific actions?

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In effect, by not only policing but selecting content, Facebook backed further away from its identity as a neutral platform and took a step closer to acting as a publisher. Facebook already employed some 15,000 content moderators in early 2018, and Zuckerberg promised the U.S. Congress that number would grow to 20,000 by the year’s end.28 The Cambridge Analytica scandal further exacerbated Facebook’s legitimacy and trust problems. Cambridge Analytica collected its data by 2014, when Facebook’s rules permitted apps to collect private information from users of the app as well as their Facebook friends. By 2015, Facebook had already changed its policy to remove the ability of third-party developers to collect detailed data about app users’ friends, but for many of its users it was still unclear the extent to which third parties used personal data.

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Restricting access to data would limit Facebook’s usefulness to developers and could drive them to build on a rival platform instead.”30 Zuckerberg acknowledged the tension in a 2018 interview: “I do think early on on the platform we had this very idealistic vision around how data portability would allow all these different new experiences, and I think the feedback that we’ve gotten from our community and from the world is that privacy and having the data locked down is more important to people than maybe making it easier to bring more data and have different kinds of experiences.”31 Similar to Facebook’s problems with fake news, what Cambridge Analytica did pushed Facebook to engage in more robust oversight to enforce its rules around data sharing. When first informed of the data harvesting activity, Facebook asked for and received a legal certification from the developer that the data had been destroyed. Facebook also received assurances from Cambridge Analytica that they had not received raw Facebook data. Those assertions turned out to be false, and Zuckerberg would later acknowledge that accepting those assertions was a mistake.

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

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

fbclid=IwAR2XOal9c41fBx0dvkI1roYZYJgkn7G87r0P86ireEOrNVHE96wF8cgobi0#t67OIbjrsmqX. 66 David Sacks, “The Speech Cartel,” Medium, January 16, 2021, https://davidsacks.medium.com/the-speech-cartel-b3f5555f7787. 67 Indictment, U.S. Department of Justice, 18 U.S.C. §§ 2,371, 1349, 1028A. 68 “The Cambridge Analytica Files,” The Guardian, https://www.theguardian.com/news/series/cambridge-analytica-files; 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. 69 Brittany Kaiser, Targeted: The Cambridge Analytica Whistleblower’s Inside Story of How Big Data, Trump, and Facebook Broke Democracy and How It Can Happen Again (New York: HarperCollins, 2019), 78. 70 Singer and Brooking, LikeWar, 61. 71 Hannes Grassegger and Mikael Krogerus, “The Data That Turned the World Upside Down,” Vice, January 28, 2017, https://www.vice.com/en_us/article/mg9vvn/how-our-likes-helped-trump-win. 72 Grassegger and Krogerus, “The Data That Turned the World Upside Down.” 73 Paul Grewal, “Suspending Cambridge Analytica and SCL Group From Facebook,” Facebook, March 17, 2018, https://about.fb.com/news/2018/03/suspending-cambridge-analytica/. 74 “FTC Imposes $5 Billion Penalty and Sweeping New Privacy Restrictions on Facebook,” Federal Trade Commission, July 24, 2019, https://www.ftc.gov/news-events/press-releases/2019/07/ftc-imposes-5-billion-penalty-sweeping-new-privacy-restrictions. 75 “ICO investigation into use of personal information and political influence,” Information Commissioner’s Office, October 2, 2020, https://ico.org.uk/media/action-weve-taken/2618383/20201002_ico-o-ed-l-rtl-0181_to-julian-knight-mp.pdf. 76 “ICO investigation into use of personal information and political influence.” 77 Craig Timberg, Tony Romm, and Elizabeth Dwoskin, “Zuckerberg apologizes, promises reform as senators grill him over Facebook’s failings,” Washington Post, April 10, 2018, https://www.washingtonpost.com/business/technology/2018/04/10/b72c09e8-3d03-11e8-974f-aacd97698cef_story.html. 78 Drew Harwell, “Facebook is now in the data-privacy spotlight.

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Incredibly, 150 likes can reveal more about someone than their own parents would know.72 And Cambridge Analytica had 5,000 of these data points on each of the 240 million individuals in its database. Armed with this exceedingly detailed “psychographic” profile of each voter, Cambridge Analytica knew exactly what to say to encourage someone to vote—or, in the case of Black voters whose turnout they sought to suppress, to encourage them not to vote. If the IRA indictments had taken a sledgehammer to any remaining doubters in the Valley, the Cambridge Analytica revelations were like a nuclear explosion. Privacy advocates were outraged, as were Americans who’d unwittingly had their personal data turned over to unscrupulous political operatives.

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Then, a month later, new revelations turned the tech world upside down. On March 17, the Guardian and the New York Times simultaneously reported an explosive series of stories, based on whistleblower accounts, about a company called Cambridge Analytica and its work with the Trump campaign.68 According to Brittany Kaiser, one of the whistleblowers, the data scientists at Cambridge Analytica had taken advantage of lax privacy laws and Facebook loopholes to “scrape” up to 5,000 data points on every American older than eighteen—approximately 240 million people.69 This included data from public posts and ostensibly private direct messages.

War for Eternity: Inside Bannon's Far-Right Circle of Global Power Brokers by Benjamin R. Teitelbaum

Affordable Care Act / Obamacare, bitcoin, Black Lives Matter, Boris Johnson, Cambridge Analytica, creative destruction, crony capitalism, cryptocurrency, Donald Trump, Etonian, fake news, Francis Fukuyama: the end of history, illegal immigration, Joseph Schumpeter, liberal capitalism, liberal world order, mass immigration, mutually assured destruction, Network effects, public intellectual, Saturday Night Live, school choice, side project, Skype, South China Sea, Steve Bannon, Westphalian system, WikiLeaks

See Benjamin Teitelbaum, Lions of the North: Sounds of the New Nordic Radical Nationalism (Oxford: Oxford University Press, 2017). pull targeted individuals out of the mainstream: Christopher Wylie, Mindf•ck: Cambridge Analytica and the Plot to Break America (New York: Random House, 2019). an organization called Leave.EU: Peter Geoghegan, “Brexit Bankroller Arron Banks, Cambridge Analytica and Steve Bannon—Explosive Emails, Reveal Fresh Links,” Open Democracy, November 17, 2018, https://www.opendemocracy.net/en/dark-money-investigations/brexit-bankroller-arron-banks-cambridge-analytica-and-steve-bannon-expl/. channel money illegally: Jamie Ross, “It’s Official: The Brexit Campaign Cheated Its Way to Victory,” Daily Beast, July 17, 2018, https://www.thedailybeast.com/its-official-the-brexit-campaign-cheated-its-way-to-victory?

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With the backing of American billionaires Robert and Rebekah Mercer, he reached out to a data mining and behavioral science conglomerate based in the UK named Strategic Communication Laboratories (SCL) and, with an infusion of $20 million, created a new U.S.-linked subsidiary called Cambridge Analytica. There were various political interests riding the moneyed coattails of the Mercers: Christopher Wylie, former director of intelligence at Cambridge Analytica, would later recall that the initial meetings for planning the development of the company were attended by the Mercers, SCL executives, Steve Bannon, and representatives from UKIP—a British nationalist party working to break the UK off from the European Union.

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There he was again on the screen, a younger-looking version of the man I had just been interviewing. It was then late July 2014 and Steve was a little-known figure, the CEO of a right-wing media outlet called Breitbart. He had recently signed on as vice president of a voter data intelligence firm called Cambridge Analytica. He was speaking via video chat to a room full of conservative Christians gathered for a conference in Vatican City. What he began to describe was a nightmare. He spoke about a crisis in the West, about capitalism and the way it had morphed into two terrifying forms: a state-sponsored crony incarnation that enriched a select few with political connections, and a libertarian form of selfishness that took no care for community.

The Internet Trap: How the Digital Economy Builds Monopolies and Undermines Democracy by Matthew Hindman

A Declaration of the Independence of Cyberspace, accounting loophole / creative accounting, activist fund / activist shareholder / activist investor, AltaVista, Amazon Web Services, barriers to entry, Benjamin Mako Hill, bounce rate, business logic, Cambridge Analytica, cloud computing, computer vision, creative destruction, crowdsourcing, David Ricardo: comparative advantage, death of newspapers, deep learning, DeepMind, digital divide, discovery of DNA, disinformation, Donald Trump, fake news, fault tolerance, Filter Bubble, Firefox, future of journalism, Ida Tarbell, incognito mode, informal economy, information retrieval, invention of the telescope, Jeff Bezos, John Perry Barlow, John von Neumann, Joseph Schumpeter, lake wobegon effect, large denomination, longitudinal study, loose coupling, machine translation, Marc Andreessen, Mark Zuckerberg, Metcalfe’s law, natural language processing, Netflix Prize, Network effects, New Economic Geography, New Journalism, pattern recognition, peer-to-peer, Pepsi Challenge, performance metric, power law, price discrimination, recommendation engine, Robert Metcalfe, search costs, selection bias, Silicon Valley, Skype, sparse data, speech recognition, Stewart Brand, surveillance capitalism, technoutopianism, Ted Nelson, The Chicago School, the long tail, The Soul of a New Machine, Thomas Malthus, web application, Whole Earth Catalog, Yochai Benkler

Taken together, these cases tell us much about who will win, and who will lose, as recommender systems assume a growing role in the delivery of media content. These techniques, however, are not just for media organizations. The chapter concludes by looking at the Cambridge Analytica scandal, perhaps Facebook’s biggest public relations disaster to date. As the author was the first to report,10 Cambridge Analytica modeled Facebook user data using methods similar to those that won the Netflix Prize. Cambridge Analytica’s example shows that data held by digital giants, coupled with now-standard machine learning techniques, can be an important tool to match citizens with online political messages.

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Reporting by the author has revealed that techniques pioneered by the Netflix Prize have been adapted for online political targeting.45 Cambridge Analytica is a British political consulting firm best known for its role in the 2016 Donald Trump campaign and the 2015 Brexit campaign in the United Kingdom. For years Cambridge Analytica courted controversy—and garnered skepticism—by claiming that it used “psychographic” models that supposedly targeted voters based on personality traits. In March 2018 the Guardian reported that Cambridge Analytica had downloaded tens of millions of Facebook profiles using a personality test app, as part of a partnership with Cambridge University researchers Aleksandr Kogan and Joseph Chancellor.46 The revelation of this “data breach” sparked regulatory investigations on both sides of the Atlantic.

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Instead, he explained, “the technique was something we actually developed ourselves. . . . It’s not something that is in the public domain.” Yet he confirmed that his approach was a close cousin of svd. The same kinds of dimension reduction models that Funk had adapted for the Netflix Prize were the core of Cambridge Analytica’s Facebook models. Knowing the original approach of Cambridge Analytica’s model answers some long-standing questions. If Kogan’s account is accurate, the inferred categories that the model produces are not about personality per se. The Politics of Personalization • 59 Instead, they boil down demographics, social influences, personality, and everything else into a big correlated lump.

The Costs of Connection: How Data Is Colonizing Human Life and Appropriating It for Capitalism by Nick Couldry, Ulises A. Mejias

"World Economic Forum" Davos, 23andMe, Airbnb, Amazon Mechanical Turk, Amazon Web Services, behavioural economics, Big Tech, British Empire, call centre, Cambridge Analytica, Cass Sunstein, choice architecture, cloud computing, colonial rule, computer vision, corporate governance, dark matter, data acquisition, data is the new oil, data science, deep learning, different worldview, digital capitalism, digital divide, discovery of the americas, disinformation, diversification, driverless car, Edward Snowden, emotional labour, en.wikipedia.org, European colonialism, Evgeny Morozov, extractivism, fake news, Gabriella Coleman, gamification, gig economy, global supply chain, Google Chrome, Google Earth, hiring and firing, income inequality, independent contractor, information asymmetry, Infrastructure as a Service, intangible asset, Internet of things, Jaron Lanier, job automation, Kevin Kelly, late capitalism, lifelogging, linked data, machine readable, Marc Andreessen, Mark Zuckerberg, means of production, military-industrial complex, move fast and break things, multi-sided market, Naomi Klein, Network effects, new economy, New Urbanism, PageRank, pattern recognition, payday loans, Philip Mirowski, profit maximization, Ray Kurzweil, RFID, Richard Stallman, Richard Thaler, Salesforce, scientific management, Scientific racism, Second Machine Age, sharing economy, Shoshana Zuboff, side hustle, Sidewalk Labs, Silicon Valley, Slavoj Žižek, smart cities, Snapchat, social graph, social intelligence, software studies, sovereign wealth fund, surveillance capitalism, techlash, The Future of Employment, the scientific method, Thomas Davenport, Tim Cook: Apple, trade liberalization, trade route, undersea cable, urban planning, W. E. B. Du Bois, wages for housework, work culture , workplace surveillance

Only from better understanding can come the chance of resisting today’s terms of connection and the forging of better ones. Part I Extracting 1 The Capitalization of Life without Limit “THIS IS WHAT MODERN COLONIALISM LOOKS LIKE.” So tweeted Christopher Wylie, the whistle-blower who kicked off the Facebook/Cambridge Analytica scandal in March 2018.1 Wylie was referring to Cambridge Analytica’s plans to expand its operations in India for using social media targeting to influence the political process there. But the scale and scope of data colonialism is much wider than the malfeasance of a few overweening data marketers and their in-house psychologists.

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Such a model of the human subject, when combined with intense data collection, creates the possibility of “persuasion profiling”: data-driven persuasion that targets specific cognitive biases that marketers have tracked in data from their target groups.146 It was persuasion profiling that proved so controversial when it came directly to light in the Cambridge Analytica scandal in March 2018. Underlying persuasion profiling is a crude biologism. Michal Kosinski, the psychologist whose work inspired Cambridge Analytica, said recently that “I don’t believe in free will” since a person’s thoughts and behaviors “are fully biological. . . . They originate in the biological computer that you have in your head.”147 Neuroeconomics goes further, using brain science to dismember the model of individual cognitive functioning on which mainstream economics relies.148 Our concern here is not defending mainstream economics’ model of human rationality but rather noticing the tendency among mainstream economics’ critics to move ever further away from social explanation as previously understood.

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Part III Reconnecting 6 Decolonizing Data Anti-colonialism has been economically catastrophic for the Indian people for decades. Why stop now? —Mark Andreessen, Facebook board member1 THE BIG TECH BACKLASH, we are told, has already begun.2 Even before the eruption of the Facebook/Cambridge Analytica scandal, there were signals of a growing willingness of regulatory bodies, especially in Europe, to challenge the great powers of data colonialism (for example, Google and Facebook). But the Cambridge Analytica scandal provoked a crisis of higher intensity: instability in tech-sector share prices, a popular movement (on social media, of course) to #leavefacebook, calls in the mainstream press to learn again the lesson of how the nineteenth century restrained the raw injustices of early capitalism (shades of Polanyi), and even an editorial in the Financial Times that entertained the case for “everyone . . . to leave Facebook.” 3 Time, you might say, to step aside and let the more enlightened forces of capitalism fix the problem, with the help of robust regulation.

Snowden's Box: Trust in the Age of Surveillance by Jessica Bruder, Dale Maharidge

air gap, anti-communist, Bay Area Rapid Transit, Berlin Wall, Black Lives Matter, blockchain, Broken windows theory, Burning Man, Cambridge Analytica, cashless society, Chelsea Manning, citizen journalism, computer vision, crowdsourcing, deep learning, digital rights, disinformation, Donald Trump, Edward Snowden, Elon Musk, end-to-end encryption, Evgeny Morozov, Ferguson, Missouri, Filter Bubble, Firefox, information security, Internet of things, Jeff Bezos, Jessica Bruder, John Perry Barlow, Julian Assange, Laura Poitras, license plate recognition, Mark Zuckerberg, mass incarceration, medical malpractice, messenger bag, Neil Armstrong, Nomadland, Occupy movement, off grid, off-the-grid, pattern recognition, Peter Thiel, Robert Bork, Seymour Hersh, Shoshana Zuboff, Silicon Valley, Skype, social graph, Steven Levy, surveillance capitalism, tech bro, Tim Cook: Apple, web of trust, WikiLeaks

But recent history demonstrates that, once systems are already mining users’ data, sometimes a line gets crossed. Consider Cambridge Analytica, the political data firm hired by President Trump’s 2016 election campaign. The company illicitly obtained detailed Facebook information on as many as 87 million people whose votes it hoped to sway with targeted political ads. The potential abuse of profile data had long been debated, as everyone from credit card companies to health insurers showed a keen interest in Facebook. But this time the victim wasn’t just individuals. It was democracy. Two weeks after the New York Times and the Observer of London unearthed the Cambridge Analytica scandal, Swedish researchers exposed another case of disturbing data migration: Grindr, the gay dating app, had disclosed users’ HIV status to a pair of outside companies.

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p. 101 Amazon technology analyzes human voice to determine ethnic origin, gender, age, health, and mental state: Madison Malone Kircher, “I Don’t Want My Echo Dot to Be Able to Tell When I’m Sick,” New York, October 15, 2018; Belle Lin, “Amazon’s Accent Recognition Technology Could Tell the Government Where You’re From,” Intercept, November 15, 2018; Jon Brodkin, “Amazon Patents Alexa Tech to Tell if You’re Sick, Depressed and Sell You Meds,” Ars Technica, October 11, 2018, arstechnica.com. p. 102 Cambridge Analytica: Matthew Rosenberg, Nicholas Confessore, and Carole Cadwalladr, “How Trump Consultants Exploited the Facebook Data of Millions,” New York Times, March 17, 2018. p. 102 information on as many as eighty-seven million people: Paul Chadwick, “How Many People Had Their Data Harvested by Cambridge Analytica?” Guardian, April 16, 2018. p. 102 everyone from credit card companies to health insurers showed interest in Facebook: Astra Taylor and Jathan Sadowski, “How Companies Turn Your Facebook Activity into a Credit Score,” Nation, May 27, 2015; “Big Data, Financial Services and Privacy,” Economist, February 9, 2017.

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p. 102 everyone from credit card companies to health insurers showed interest in Facebook: Astra Taylor and Jathan Sadowski, “How Companies Turn Your Facebook Activity into a Credit Score,” Nation, May 27, 2015; “Big Data, Financial Services and Privacy,” Economist, February 9, 2017. p. 102 unearthing the Cambridge Analytica scandal: Nicholas Confessore, “Cambridge Analytica and Facebook: The Scandal and the Fallout So Far,” New York Times, April 4, 2018. p. 103 Grindr disclosed users’ HIV status: Azeen Ghorayshi and Sri Ray, “Grindr Is Letting Other Companies See User HIV Status and Location Data,” BuzzFeed, April 2, 2018. p. 103 police used an Ohio man’s pacemaker data: Ms. Smith, “Cops Use Pacemaker Data to Charge Homeowner with Arson, Insurance Fraud,” CSO, Jan 30, 2017, csoonline.com.

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

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.

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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. Paul Lewis and Julia Carrie Wong, “Facebook Employs Psychologist Whose Firm Sold Data to Cambridge Analytica,” Guardian, March 18, 2018, http://www.theguardian.com/news/2018/mar/18/facebook-cambridge-analytica-joseph-chancellor-gsr. 83. Kroll, “Cloak and Data.” 84. Frederik Zuiderveen Borgesius et al., “Online Political Microtargeting: Promises and Threats for Democracy” (SSRN Scholarly Paper, Rochester, NY: Social Science Research Network, February 9, 2018), https://papers.ssrn.com/abstract=3128787. 85.

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Indeed, the confidential document cites some of the key raw materials fed into this high-velocity, high-volume, and deeply scoped manufacturing operation, including not only location, Wi-Fi network details, and device information but also data from videos, analyses of affinities, details of friendships, and similarities with friends. It was probably no coincidence that the leaked Facebook presentation appeared around the same time that a young Cambridge Analytica mastermind-turned-whistleblower, Chris Wylie, unleashed a torrent of information on that company’s secret efforts to predict and influence individual voting behavior, quickly riveting the world on the small political analytics firm and the giant source of its data: Facebook. There are many unanswered questions about the legality of Cambridge Analytica’s complex subterfuge, its actual political impact, and its relationship with Facebook. Our interest here is restricted to how its machinations shine a bright light on the power of surveillance capitalism’s mechanisms, especially the determination to render data from the depth dimension.

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

Italian Yearbook of International Law Online, 28(1), 231–248; Vaidhyanathan, S. (2018). Antisocial media: How Facebook has disconnected citizens and undermined democracy. Oxford University Press. Shady data analytics companies like Cambridge Analytica: Cadwalladr, C., & Graham-Harrison, E. (2018). The Cambridge Analytica files. Retrieved from https://www.theguardian.com/news/series/cambridge-analytica-files; J. Isaak and M. J. Hanna, “User Data Privacy: Facebook, Cambridge Analytica, and Privacy Protection,” in Computer, vol. 51, no. 8, pp. 56-59, August 2018, doi: 10.1109/MC.2018.3191268 Indeed, for much of the 2000s, technology enthusiasts applauded: See Diamond, L. (2010).

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Probably the most well-known provider of these new types of commercial psy-op services is Cambridge Analytica, thanks to its prominent and controversial role in the U.K. Brexit and in the U.S. 2016 presidential election, as exposed in the documentary The Great Hack. Cambridge Analytica is very much representative on a number of levels of this type of emerging and dangerous marketplace. It applied the rigour and computing resources of social psychology, neuroscience, and engineering and computing sciences, but lacked any consideration whatsoever of the ethical rules that constrain bad behaviour around research on human subjects. Cambridge Analytica also tapped into the reservoirs of our digital exhaust, thanks to the freewheeling philosophy of social media platforms, like Facebook, that all too readily opened their vaults to third parties, who in turn readily shared that data with Cambridge Analytica.

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Cambridge Analytica also tapped into the reservoirs of our digital exhaust, thanks to the freewheeling philosophy of social media platforms, like Facebook, that all too readily opened their vaults to third parties, who in turn readily shared that data with Cambridge Analytica. 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.

User Friendly by Cliff Kuang, Robert Fabricant

A Pattern Language, Abraham Maslow, Airbnb, anti-communist, Any sufficiently advanced technology is indistinguishable from magic, Apple II, augmented reality, autonomous vehicles, behavioural economics, Bill Atkinson, Brexit referendum, Buckminster Fuller, Burning Man, business logic, call centre, Cambridge Analytica, Chuck Templeton: OpenTable:, cognitive load, computer age, Daniel Kahneman / Amos Tversky, dark pattern, data science, Donald Trump, Douglas Engelbart, Douglas Engelbart, driverless car, Elaine Herzberg, en.wikipedia.org, fake it until you make it, fake news, Ford Model T, Frederick Winslow Taylor, frictionless, Google Glasses, Internet of things, invisible hand, James Dyson, John Markoff, Jony Ive, knowledge economy, Kodak vs Instagram, Lyft, M-Pesa, Mark Zuckerberg, mobile money, Mother of all demos, move fast and break things, Norbert Wiener, Paradox of Choice, planned obsolescence, QWERTY keyboard, randomized controlled trial, replication crisis, RFID, scientific management, self-driving car, seminal paper, Silicon Valley, skeuomorphism, Skinner box, Skype, smart cities, Snapchat, speech recognition, Steve Jobs, Steve Wozniak, tacit knowledge, Tesla Model S, three-martini lunch, Tony Fadell, Uber and Lyft, Uber for X, uber lyft, Vannevar Bush, women in the workforce

Matthew Rosenberg, “Cambridge Analytica, Trump-Tied Political Firm, Of-fered to Entrap Politicians,” New York Times, March 19, 2018, www.nytimes.com/2018/03/19/us/cambridge-analytica-alexander-nix.html. 35. Interviews with Michal Kosinski, April 25, May 18, July 7, and December 4, 2017. 36. Michal Kosinski, David Stillwell, and Thore Graepel, “Private Traits and Attributes Are Predictable from Digital Records of Human Behavior,” Proceedings of the National Academy of Sciences 110, no. 15 (April 13, 2013): 5802–805, www.pnas.org/content/110/15/5802.full. 37. Sean Illing, “Cambridge Analytica, the Shady Data Firm That Might Be a Key Trump-Russia Link, Explained,” Vox, April 4, 2018, www.vox.com/policy-and-politics/2017/10/16/15657512/cambridge-analytica-facebook-alexander-nix-christopher-wylie. 38.

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But is a user-friendly world actually the best world we can create? In the months after the election, as flummoxed Hillary Clinton staffers were wondering how they’d so badly misunderstood the race they were running against Donald Trump, news reports began trickling out about Cambridge Analytica, a mysterious data-science company that had been paid millions to help Trump’s campaign in the run-up to the election.34 Cambridge Analytica itself wasn’t an innovator. It had been inspired by Michal Kosinski, a young psychologist at Cambridge University. Kosinski typically wears the uniform of a venture capitalist: pressed khakis, crisp button-down shirt tucked in.

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And if you knew their personality, then you could readily tailor messages to them—based on what made them angry or scared or motivated or lonely. It was perhaps only a matter of time until Cambridge Analytica approached Kosinski about a partnership, under the guise of a shell company. Kosinski turned the offer down, and then watched with alarm as reports emerged suggesting that Trump’s campaign was creating Facebook ads tuned to provoke outrage in microtargeted audiences. By 2016, Cambridge Analytica’s CEO was claiming that it had profiled the personalities of nearly every adult in the United States—220 million people. It has been estimated that during the election, the firm was testing 40,000 to 50,000 ads a day to better understand what would motivate voters—or keep voters who didn’t like Trump from voting at all.37 In one instance, Trump’s own digital operatives claimed that they’d targeted black voters in Miami’s Haitian community with stories about the Clinton Foundation’s supposedly corrupt efforts to deliver aid after Haiti’s catastrophic 2010 earthquake.38 Some months later, journalists began to question whether Cambridge Analytica’s data science really could be as advanced as it claimed.39 What no one questioned was that Facebook could easily do what Cambridge Analytica had boasted about.

Hiding in Plain Sight: The Invention of Donald Trump and the Erosion of America by Sarah Kendzior

4chan, Bear Stearns, Berlin Wall, Bernie Sanders, Black Lives Matter, borderless world, Brexit referendum, Cambridge Analytica, Carl Icahn, Chelsea Manning, Columbine, corporate raider, desegregation, disinformation, don't be evil, Donald Trump, drone strike, Edward Snowden, Evgeny Morozov, fake news, Ferguson, Missouri, Francis Fukuyama: the end of history, gentrification, Golden arches theory, hiring and firing, illegal immigration, income inequality, Jaron Lanier, Jeff Bezos, Jeffrey Epstein, Julian Assange, junk bonds, Michael Milken, military-industrial complex, Mohammed Bouazizi, Naomi Klein, Nelson Mandela, new economy, Oklahoma City bombing, opioid epidemic / opioid crisis, payday loans, plutocrats, public intellectual, QAnon, Robert Hanssen: Double agent, Ronald Reagan, side hustle, Silicon Valley, Skype, Steve Bannon, Thomas L Friedman, trickle-down economics, Twitter Arab Spring, unpaid internship, white flight, WikiLeaks, Y2K, zero-sum game

In summer 2014, writers Shafiqah Hudson and l’Nasah Crockett launched the hashtag #YourSlipIsShowing to expose accounts impersonating black users and making obnoxious political claims.16 Many of these accounts were later revealed to be Russian troll accounts seeking to map the US political landscape and prepare to influence the 2016 election.17 Other trolls were right-wing users in the United States linked to the Russian effort: Steve Bannon (then the editor of Breitbart) and Cambridge Analytica were experimenting with social media to see how social groups could be manipulated online for political gain. According to Cambridge Analytica whistle-blower Christopher Wylie, Bannon asked employees to “test messaging around Russian President Vladimir Putin and Russian expansion.”18 However, few in power paid attention—in part because social media companies almost never took seriously the most common targets, women of color.

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Brexit was a direct precursor of the US election, featuring not only the same largely unexpected result, but the same players behind the scenes. In early 2017, a tenacious UK journalist, Carole Cadwalladr, had started to investigate the role of social media in the Brexit referendum, especially the company Cambridge Analytica and the interlocking parties who benefited from it—Nigel Farage, Steve Bannon, Jared Kushner. Eventually, she got a whistle-blower from Cambridge Analytica to come forward about the extent of their data-mining and election-influencing operation, and both the whistle-blower and Cadwalladr received scorn and threats.32 She was not alone. A few other UK journalists were examining Russia’s influence over UK institutions that had been infiltrated by Russian mafia associates over decades, much in the same way our institutions in the United States had been.

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Charles Davis, “Jill Stein’s Recount Cash Pays for Her Russia Legal Defense,” Daily Beast, July 13, 2018, https://www.thedailybeast.com/jill-steins-recount-cash-pays-for-her-russia-legal-defense. 31.   “Sarah Kendzior Responds to Breitbart,” https://youtube.com/watch?v=1ZsJlLfGkkQ. 32.   Carole Cadwalladr, “Cambridge Analytica a Year On: ‘A Lesson in Institutional Failure,’” The Guardian, March 17, 2019, https://www.theguardian.com/uk-news/2019/mar/17/cambridge-analytica-year-on-lesson-in-institutional-failure-christopher-wylie. 33.   BBC News, “Salisbury Novichok Poisoning: Russian Nationals Named As Suspects,” September 5, 2018, https://www.bbc.com/news/uk-45421445. 34.   Ashifa Kassam, “Refugees Crossing into Canada from US on Foot Despite Freezing Temperatures,” The Guardian, February 7, 2017, https://www.theguardian.com/world/2017/feb/07/us-refugees-canada-border-trump-travel-ban. 35.   

Genius Makers: The Mavericks Who Brought A. I. To Google, Facebook, and the World by Cade Metz

AI winter, air gap, Airbnb, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, AlphaGo, Amazon Robotics, artificial general intelligence, Asilomar, autonomous vehicles, backpropagation, Big Tech, British Empire, Cambridge Analytica, carbon-based life, cloud computing, company town, computer age, computer vision, deep learning, deepfake, DeepMind, Demis Hassabis, digital map, Donald Trump, driverless car, drone strike, Elon Musk, fake news, Fellow of the Royal Society, Frank Gehry, game design, Geoffrey Hinton, Google Earth, Google X / Alphabet X, Googley, Internet Archive, Isaac Newton, Jeff Hawkins, Jeffrey Epstein, job automation, John Markoff, life extension, machine translation, Mark Zuckerberg, means of production, Menlo Park, move 37, move fast and break things, Mustafa Suleyman, new economy, Nick Bostrom, nuclear winter, OpenAI, PageRank, PalmPilot, pattern recognition, Paul Graham, paypal mafia, Peter Thiel, profit motive, Richard Feynman, ride hailing / ride sharing, Ronald Reagan, Rubik’s Cube, Sam Altman, Sand Hill Road, self-driving car, side project, Silicon Valley, Silicon Valley billionaire, Silicon Valley startup, Skype, speech recognition, statistical model, stem cell, Stephen Hawking, Steve Ballmer, Steven Levy, Steven Pinker, tech worker, telemarketer, The Future of Employment, Turing test, warehouse automation, warehouse robotics, Y Combinator

Others said his haircut: Max Lakin, “The $300 T-Shirt Mark Zuckerberg Didn’t Wear in Congress Could Hold Facebook’s Future,” W magazine, April 12, 2018, https://www.wmagazine.com/story/mark-zuckerberg-facebook-brunello-cucinelli-t-shirt/. reported that the British start-up Cambridge Analytica: 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. Zuckerberg endured ten hours of testimony over two days: Zach Wichter, “2 Days, 10 Hours, 600 Questions: What Happened When Mark Zuckerberg Went to Washington,” New York Times, April 12, 2018, https://www.nytimes.com/2018/04/12/technology/mark-zuckerberg-testimony.html.

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But when he testified before Congress in April 2018, he wore a navy suit and a Facebook-blue tie. Some called it his “I’m sorry” suit. Others said his haircut, strangely high on his forehead, made him look like a penitent monk. A month earlier, newspapers in the United States and Britain reported that the British start-up Cambridge Analytica had harvested private information from the Facebook profiles of more than 50 million people before using this data to target voters on behalf of the Trump campaign in the run-up to the 2016 election. The revelation let loose an avalanche of rebuke from the media, public advocates, and lawmakers that piled atop the criticism already aimed at Zuckerberg and Facebook over the past several months.

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The revelation let loose an avalanche of rebuke from the media, public advocates, and lawmakers that piled atop the criticism already aimed at Zuckerberg and Facebook over the past several months. Summoned to Capitol Hill, Zuckerberg endured ten hours of testimony over two days. He answered more than six hundred questions from nearly a hundred lawmakers on issues new and old, including the Cambridge Analytica data breach, Russian interference in the election, fake news, and the hate speech that frequently spread across Facebook, inciting violence in places like Myanmar and Sri Lanka. Zuckerberg apologized time and again, though he didn’t always seem apologetic. In private as well as in public, Zuckerberg has an almost robotic demeanor, blinking his eyes unusually often and, from time to time, making an unconscious clicking sound at the back of his throat that seems liked some sort of glitch in the machine.

This Is Not Propaganda: Adventures in the War Against Reality by Peter Pomerantsev

4chan, active measures, anti-communist, Bellingcat, Berlin Wall, Black Lives Matter, call centre, Cambridge Analytica, citizen journalism, data science, Day of the Dead, desegregation, disinformation, Donald Trump, Etonian, European colonialism, fake news, Fall of the Berlin Wall, feminist movement, illegal immigration, mass immigration, mega-rich, megacity, Mikhail Gorbachev, post-truth, side hustle, Skype, South China Sea

The display, which was called ‘Can Democracy Survive the Internet?’, was dedicated to a ‘global election management’ company called Cambridge Analytica. Cambridge Analytica claimed to have gathered 5,000 ‘data points’ on every American voter online: what you liked and what you shared on social media; how and where you shopped; who your friends were … They claimed to be able to take this imprint of your online self, use it to understand your deepest drives and desires, and then draw on that analysis to change your voting behaviour. The boast seemed to be backed up by success: Cambridge Analytica had worked on the victorious American presidential campaign of Donald Trump; it had also run successful campaigns for US Senator Ted Cruz (twice); and others all across Africa, Asia, the Caribbean, Latin America.

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He was a different type of Etonian to Oakes: he came from a fabulously wealthy background, had studied art history at university and his friends called him ‘Bertie’, a nickname out of Edwardian England. Oakes says Nix wanted to drag the research into the digital age, wanted to make money. He was better with clients. In 2012 Nix took the elections part of the company and made it his own, renaming it Cambridge Analytica (a whistle-blower would later claim that mentioning the prestigious university, which the company had no official affiliation to, impressed American clients). Cambridge Analytica furiously tested ways of replicating ‘behavioural change’ methodology by looking at people’s social media use. They explored the potential of ‘psychographics’: the idea that your social media preferences and language predict your personality.

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He called his part of the business SCL Defence. In 2018 Nix was recorded by journalists telling a prospective client from Kenya he could use prostitutes as a honeytrap for the man’s political rivals. It later transpired that Cambridge Analytica had access to the data of eighty-seven million Facebook users, without their consent. The sordid details seemed a far cry from the high-tech claims of psychographics. The scandal destroyed Cambridge Analytica. At SCL Defence Oakes’s military clients disappeared: no government would touch anyone even remotely associated with Analytica. But Oakes doesn’t sound bitter about Nix. They had been partners.

Always Day One: How the Tech Titans Plan to Stay on Top Forever by Alex Kantrowitz

accounting loophole / creative accounting, Albert Einstein, AltaVista, Amazon Robotics, Amazon Web Services, Andy Rubin, anti-bias training, augmented reality, Automated Insights, autonomous vehicles, Bernie Sanders, Big Tech, Cambridge Analytica, Clayton Christensen, cloud computing, collective bargaining, computer vision, Donald Trump, drone strike, Elon Musk, fake news, Firefox, fulfillment center, gigafactory, Google Chrome, growth hacking, hive mind, income inequality, Infrastructure as a Service, inventory management, iterative process, Jeff Bezos, job automation, Jony Ive, Kiva Systems, knowledge economy, Lyft, Mark Zuckerberg, Menlo Park, new economy, Nick Bostrom, off-the-grid, Peter Thiel, QR code, ride hailing / ride sharing, robotic process automation, Salesforce, self-driving car, Sheryl Sandberg, Silicon Valley, Skype, Snapchat, SoftBank, Steve Ballmer, Steve Jobs, Steve Wozniak, super pumped, tech worker, Tim Cook: Apple, uber lyft, warehouse robotics, wealth creators, work culture , zero-sum game

“An Update on Information Operations on Facebook.” Facebook Newsroom, September 6, 2017. https://newsroom.fb.com/news/2017/09/information-operations-update/. Cambridge Analytica, a data analytics firm, illicitly used: Rosenberg, Matthew, Nicholas Confessore, and Carole Cadwalladr. “How Trump Consultants Exploited the Facebook Data of Millions.” New York Times. New York Times, March 17, 2018. https://www.nytimes.com/2018/03/17/us/politics/cambridge-analytica-trump-campaign.html. best in “The Ugly”: Mac, Ryan, Charlie Warzel, and Alex Kantrowitz. “Growth at Any Cost: Top Facebook Executive Defended Data Collection in 2016 Memo—and Warned That Facebook Could Get People Killed.”

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Finally, Mark Zuckerberg walked in. It had been a rough fourteen months for Zuckerberg since our initial meeting in Menlo Park. In that time, Facebook revealed it had missed a large-scale Kremlin-sponsored misinformation campaign on its service during the 2016 election. And further reports showed that Cambridge Analytica, a data analytics firm, illicitly used millions of Facebook users’ data in its work for Donald Trump’s presidential campaign. These events damaged Facebook’s credibility, hurt its standing in the world, and landed Zuckerberg a date with the Senate Judiciary and Commerce committees. As Zuckerberg walked in, I wondered how this man, so driven by feedback, so determined to find out what others were thinking, could have been so blind to vulnerabilities in his service.

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If my colleague had been so sure that Facebook Live would air shootings, why hadn’t Zuckerberg anticipated them? If it was clear that Russia had engaged in a widespread campaign to undermine the US democratic process, why had he said it was a “crazy idea” that misinformation on Facebook could’ve impacted the 2016 election outcome? And why had he seemed so caught off guard when the Cambridge Analytica reports hit, spending multiple days in silence before responding? The answer is an essential lesson about the nature of feedback systems. Though Zuckerberg asks people for feedback, the simple act of asking is itself insufficient. Feedback systems, just like machine-learning systems, are only as good as their inputs.

No Filter: The Inside Story of Instagram by Sarah Frier

Airbnb, Amazon Web Services, Benchmark Capital, blockchain, Blue Bottle Coffee, Cambridge Analytica, Clayton Christensen, cloud computing, cryptocurrency, data science, disinformation, Donald Trump, Elon Musk, end-to-end encryption, fake news, Frank Gehry, growth hacking, Jeff Bezos, Marc Andreessen, Mark Zuckerberg, Menlo Park, Minecraft, move fast and break things, Network effects, new economy, Oculus Rift, Peter Thiel, ride hailing / ride sharing, Sheryl Sandberg, side project, Silicon Valley, Silicon Valley startup, Snapchat, Steve Jobs, TaskRabbit, TikTok, Tony Hsieh, Travis Kalanick, ubercab, Zipcar

On Friday, March 17, 2018, the New York Times: 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; and Carole Cadwalladr and Emma Graham-Harrison, “Revealed: 50 Million Facebook Profiles Harvested for Cambridge Analytica in Major Data Breach,” The Observer, March 17, 2018, https://www.theguardian.com/news/2018/mar/17/cambridge-analytica-facebook-influence-us-election. The average Facebook employee made: Casey Newton, “The Trauma Floor,” The Verge, February 25, 2019, https://www.theverge.com/2019/2/25/18229714/cognizant-facebook-content-moderator-interviews-trauma-working-conditions-arizona; and Munsif Vengatil and Paresh Dave, “Facebook Contractor Hikes Pay for Indian Content Reviewers,” Reuters, August 19, 2019, https://www.reuters.com/article/us-facebook-reviewers-wages/facebook-contractor-hikes-pay-for-indian-content-reviewers-idUSKCN1V91FK.

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* * * Then, as often happens with Facebook, a revelation in the media shifted everyone’s priorities. On Friday, March 17, 2018, the New York Times and the Observer simultaneously broke the news that years earlier, Facebook had allowed the developer of a personality quiz app to obtain data on tens of millions of users, which that developer then shared with a firm called Cambridge Analytica. Cambridge Analytica retained the data and used it to help build its political consultancy. The company aggregated information from several sources to build personality profiles on people who might be receptive to ads that would help conservatives win elections. Donald Trump’s campaign was a client. The story hit all of Facebook’s weak spots: shoddy data practices.

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Even WhatsApp cofounder Acton tweeted it, before deleting his Facebook account. A week later, Zuckerberg agreed to testify in front of U.S. Congress for the first time, on April 10 and 11, 2018, under interrogation by the Senate and then the House of Representatives. The questions weren’t about Cambridge Analytica as much as they were about Facebook’s power. Legislators were waking up to the fact that one company, in charge of entertaining and informing more than 2 billion people, was more influential in many ways than the government itself. Things that Facebook had done for years suddenly looked scandalous under this lens.

The Big Nine: How the Tech Titans and Their Thinking Machines Could Warp Humanity by Amy Webb

"Friedman doctrine" OR "shareholder theory", Ada Lovelace, AI winter, air gap, Airbnb, airport security, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, algorithmic bias, AlphaGo, Andy Rubin, artificial general intelligence, Asilomar, autonomous vehicles, backpropagation, Bayesian statistics, behavioural economics, Bernie Sanders, Big Tech, bioinformatics, Black Lives Matter, blockchain, Bretton Woods, business intelligence, Cambridge Analytica, Cass Sunstein, Charles Babbage, Claude Shannon: information theory, cloud computing, cognitive bias, complexity theory, computer vision, Computing Machinery and Intelligence, CRISPR, cross-border payments, crowdsourcing, cryptocurrency, Daniel Kahneman / Amos Tversky, data science, deep learning, DeepMind, Demis Hassabis, Deng Xiaoping, disinformation, distributed ledger, don't be evil, Donald Trump, Elon Musk, fail fast, fake news, Filter Bubble, Flynn Effect, Geoffrey Hinton, gig economy, Google Glasses, Grace Hopper, Gödel, Escher, Bach, Herman Kahn, high-speed rail, Inbox Zero, Internet of things, Jacques de Vaucanson, Jeff Bezos, Joan Didion, job automation, John von Neumann, knowledge worker, Lyft, machine translation, Mark Zuckerberg, Menlo Park, move fast and break things, Mustafa Suleyman, natural language processing, New Urbanism, Nick Bostrom, one-China policy, optical character recognition, packet switching, paperclip maximiser, pattern recognition, personalized medicine, RAND corporation, Ray Kurzweil, Recombinant DNA, ride hailing / ride sharing, Rodney Brooks, Rubik’s Cube, Salesforce, Sand Hill Road, Second Machine Age, self-driving car, seminal paper, SETI@home, side project, Silicon Valley, Silicon Valley startup, skunkworks, Skype, smart cities, South China Sea, sovereign wealth fund, speech recognition, Stephen Hawking, strong AI, superintelligent machines, surveillance capitalism, technological singularity, The Coming Technological Singularity, the long tail, theory of mind, Tim Cook: Apple, trade route, Turing machine, Turing test, uber lyft, Von Neumann architecture, Watson beat the top human players on Jeopardy!, zero day

Apple slowed down its older iPhones as its new models hit the shelves and apologized. Post–Cambridge Analytica, Facebook CEO Mark Zuckerberg published a general apology on his Facebook wall, writing, “For those I hurt this year, I ask for forgiveness and I will try to be better. For the ways my work was used to divide people rather than bring us together, I ask forgiveness.” Therefore, the G-MAFIA tend to move swiftly in developmental spurts until something bad happens, and then the government gets involved. Facebook’s data policies only attracted the attention of DC once a former Cambridge Analytica employee blew the whistle, explaining how easily our data had been scraped and shared.

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See also Turing, Alan ET City Brain, 69 Ethics: AI company culture and, 255; Baidu focus on, 129; IBM articles regarding, 129; integrating into non-ethics university courses, 256; screening for in G-MAFIA future hiring practices, 255; university courses, 61, 63 Euclid, first algorithm and, 18 Evolutionary algorithms, 144, 164–165; Darwinian natural selection and, 144, 145 Facebook, 3, 70, 85, 96, 154; adult users, 87; advertising revenue, 71; in catastrophic scenario of future, 209, 216, 223; Chinese ban, 76; core values, 100; data policies, 94; exclusion of conservative news on, 57; Intel partnership, 92; “move fast and break things” original motto, 53; number of users, 71; in optimistic scenario of future, 159, 171; Portal, 54; post-Cambridge Analytica debacle apology, 54, 94; post-Cambridge Analytica scandal ethics team, 129; in pragmatic scenario of future, 186, 187, 188, 193, 201–202; psychological experimentation on users, 138; RNC bias accusations against, 56–57; senior leadership, 56; 2016 Presidential election and, 138; Website logins and, 88 Fake news, proliferation of in pragmatic scenario of future, 198 Fan Hui, 43–44, 45; versus DeepMind, 43–44 Fifth Generation, 38 Filmmaking, optimistic scenario of future and, 165–166 Future and AI, catastrophic scenario of, 151–152, 207–229; AGI system lockouts, 224; AI totalitarianism, 223; Amazon-hosted Food Stamp Program, 218; Amazon households, 216, 217–218, 219, 224, 225; Amazon Housing/Homes, 217–218, 219; Americans geographically locked in by China, 227; Apple households, 216, 218, 219, 224, 225; Apple PDRs, 216; blue-collar job glut, 221; blurring of work and personal data, 208; Chief AI Officers, 226; Chinese hackers, 215; climate change consequences, 228–229; corporate ownership of PDRs, 209; crime, 222; digital caste system, 209, 218; economic chimera of humans, 225; education and Salesforce core values, 221–222; extermination of U.S. and allied populations by Chinese ASI, 229; G-MAFIA and preservation of democratic ideals, 211; G-MAFIA diversity mantra, 208; G-MAFIA nonexistent inclusion efforts, 208; G-MAFIA shrinkage to GAA, 223; G-MAFIA sole owners of PDRs, 208, 216; G-MAFIA transactional relationship with U.S. government, 212; GAA-U.S.

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Complicated technology like AI demands experimentation and the opportunity to fail over and over in pursuit of getting things right. But there’s a catch. The mantra is part of a troubling ideology that’s pervasive among the Big Nine: build it first, and ask for forgiveness later. Lately, we’ve been hearing a lot of requests for forgiveness. Facebook apologized for the outcome of its relationship with Cambridge Analytica. As that scandal was unfolding, Facebook announced in September 2018 that an attack has exposed the personal information of more than 50 million users, making it one of the largest security breaches in digital history. But it turns out that executives made a decision not to notify users right away.1 Just one month later, Facebook announced Portal, a video conferencing screen to rival Amazon’s Echo Show, and had to walk back the privacy promises it had made earlier.

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

In a 2019 email exchange with me, Auernheimer declined to answer questions about his activities in the French or American elections but said he did not work with Russia. He did work at times with right-wing troll Charles “Chuck” Johnson, whose startup WeSearchr coordinated bounty offers for the fruits of political opposition research, including “proof” Macron was gay and Clinton’s deleted emails. “network of companies including Cambridge Analytica”: Coverage of Cambridge Analytica, including the identification of a whistle-blower, was led by the Guardian. “I revealed that security company RSA had taken $10 million”: “Exclusive: Secret Contract Tied NSA and Security Industry Pioneer,” Reuters, December 20, 2013, www.reuters.com/article/us-usa-security-rsa-idUSBRE9BJ1C220131220.

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No Democrat had won a statewide Texas vote since 1994, and Cruz was one of the best-known and best-funded members of the Senate, the Republican runner-up when Trump won the national primaries in 2016. But Cruz also had a special resonance for anyone deeply informed about Facebook, the Mueller probe, or both, as Stamos was. Cruz once had been the top political client of Cambridge Analytica, which had siphoned off Facebook data on as many as 87 million mostly unwitting users as it coached Cruz, and then Trump, on how to target them with effective ads. Looking at the full electoral picture, Republicans held a slim Senate majority, and flipping just two seats would allow Democrats to block automatic approval for Trump’s Supreme Court and cabinet picks and, if necessary, protect Mueller’s probe.

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While cDc and a transformed NSF battled on Facebook’s pages, a more momentous conflict was brewing behind the scenes at Facebook the company, arguably ground zero for the election misinformation battle. Beyond overt support from Thiel, who spoke for Trump at the Republican National Convention, Facebook’s collection of data on its users, as well as its lax policies about what apps could collect from whom, allowed a secretive network of companies including Cambridge Analytica to collect material on as many as 87 million Americans. The companies, funded by billionaire Republican donors Robert and Rebekah Mercer, claimed they could tell from the psychological elements of that data which ads would be most effective to show to whom. Famously, the information went to help Trump.

The Open Revolution: New Rules for a New World by Rufus Pollock

Airbnb, Cambridge Analytica, discovery of penicillin, Donald Davies, Donald Trump, double helix, Free Software Foundation, Hush-A-Phone, informal economy, Internet of things, invention of the wheel, Isaac Newton, Kickstarter, Live Aid, openstreetmap, packet switching, RAND corporation, Richard Stallman, software patent, speech recognition, tech billionaire

Remuneration rights are technically feasibleWe already determine who owns innovations We already share rights between multiple innovators We can distribute funds between holders of remunerations rights We can evaluate how much should be spent on each kind of information Remuneration rights are politically feasibleSustainable funding can be ensured, nationally and globally Remuneration rights are compatible with national and international laws We can make a successful transition to an Open model with remuneration rights Help us Make it Happen Coda: The Original Copyfight Acknowledgements Cover Table of contents Prologue: Monopolies of Attention In March 2018, when the scandal broke around the political consulting firm Cambridge Analytica and Facebook, the Guardian in London quoted a former director of the consultancy: Corporations like Google, Facebook, Amazon, all of these large companies, are making tens or hundreds of billions of dollars [from] monetising people’s data … I’ve been telling companies and governments for years that data is probably your most valuable asset.

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Free enterprise and free markets are disintegrating in the face of international monopolies, free choice means little when there is only one to choose between, and even our political freedom and freedom of thought are threatened by powers that have the capacity to shape how we think and act. We should all be concerned by this, and the evidence from recent scandals such as Cambridge Analytica show that these concerns are increasingly shared. Yet if we were to open up to everyone all the information that is being produced – the software that now runs the world, all the riches and the Closed materials, the world’s literature and art and algorithms – then we could democratise the infotech revolution.

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Contrast this with Facebook and you can see how different things could be: Facebook provides media sharing, communication, identification and spam-management services, but its protocols and platform are largely proprietary and controlled by the company, which ultimately determines who uses them and for what. The difference between these two kinds of platform was made starkly clear in spring 2018 by the Cambridge Analytica scandal. Facebook took a large share of the blame for misuse of personal information; no one blamed the internet itself. There is no reason, though, why Facebook could not have been like the internet, with its protocols being Open and universally accessible. Instead of a proprietary social network controlled by one corporation, we could have had an Open social network, owned and controlled by its users – just like the internet itself.

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

That year, Rebekah stood up before a crowd of Romney supporters at the University Club of New York and delivered a scathing and detailed critique of the Republican Party, arguing that its poor data and canvassing operations held candidates back. Rebekah said it was time to “save America from becoming like socialist Europe.”12 Bannon helped broker a deal for Mercer to invest in an analytics firm called Cambridge Analytica, the US arm of the British behavioral research company SCL Group. Cambridge Analytica specialized in the kinds of advanced data Mercer was accustomed to parsing at Renaissance, and the type of information that Rebekah said the GOP lacked. She urged organizations that benefited from her family’s funds to tap Cambridge’s sophisticated technological capabilities.

…

After Breitbart started an office in London, in 2012, it began supporting politician and former commodity trader Nigel Farage’s fledgling efforts to catapult the idea of the UK leaving the European Union from a fringe issue to a mainstream one. At some point, Mercer and Farage became friendly. In 2015, Cambridge Analytica discussed ways to help the leaders of Leave.EU, the political group that supported the UK’s withdrawal from the European Union. Bannon was included as part of the email traffic between the two groups, though it’s not clear he read or responded to the emails. The following month, Leave.EU publicly launched a campaign to persuade British voters to support a referendum in favor of an exit from the European Union. Cambridge Analytica officials would deny charging for doing work for Leave.EU.14 “Even if the firm was not paid for its services, it laid some of the early groundwork for the Leave.EU campaign,” argues journalist Jane Mayer.15 In June 2016, the UK voted to exit the European Union.

…

Carole Cadwalladr, “Revealed: How US Billionaire Helped to Back Brexit,” Guardian, February 25, 2017, https://www.theguardian.com/politics/2017/feb/26/us-billionaire-mercer-helped-back-brexit. 15. Jane Mayer, “New Evidence Emerges of Steve Bannon and Cambridge Analytica’s Role in Brexit,” New Yorker, November 17, 2018, https://www.newyorker.com/news/news-desk/new-evidence-emerges-of-steve-bannon-and-cambridge-analyticas-role-in-brexit. 16. Nigel Farage, “Farage: ‘Brexit Could Not Have Happened without Breitbart,’” interview by Alex Marlow, Turning Point USA Student Action Summit, December 20, 2018, https://www.youtube.com/watch?

The Data Detective: Ten Easy Rules to Make Sense of Statistics by Tim Harford

Abraham Wald, access to a mobile phone, Ada Lovelace, affirmative action, algorithmic bias, Automated Insights, banking crisis, basic income, behavioural economics, Black Lives Matter, Black Swan, Bretton Woods, British Empire, business cycle, Cambridge Analytica, Capital in the Twenty-First Century by Thomas Piketty, Cass Sunstein, Charles Babbage, clean water, collapse of Lehman Brothers, contact tracing, coronavirus, correlation does not imply causation, COVID-19, cuban missile crisis, Daniel Kahneman / Amos Tversky, data science, David Attenborough, Diane Coyle, disinformation, Donald Trump, Estimating the Reproducibility of Psychological Science, experimental subject, fake news, financial innovation, Florence Nightingale: pie chart, Gini coefficient, Great Leap Forward, Hans Rosling, high-speed rail, income inequality, Isaac Newton, Jeremy Corbyn, job automation, Kickstarter, life extension, meta-analysis, microcredit, Milgram experiment, moral panic, Netflix Prize, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, opioid epidemic / opioid crisis, Paul Samuelson, Phillips curve, publication bias, publish or perish, random walk, randomized controlled trial, recommendation engine, replication crisis, Richard Feynman, Richard Thaler, rolodex, Ronald Reagan, selection bias, sentiment analysis, Silicon Valley, sorting algorithm, sparse data, statistical model, stem cell, Stephen Hawking, Steve Bannon, Steven Pinker, survivorship bias, systematic bias, TED Talk, universal basic income, W. E. B. Du Bois, When a measure becomes a target

(Perhaps my favorite was a CNN story: “Math Is Racist.”) The crisis reached a shrill pitch with the discovery that a political consulting firm, Cambridge Analytica, had exploited Facebook’s lax policies on data to slurp up information on about 50 million people, without those people knowing or meaningfully consenting to this, and show them personally targeted advertisements. It was briefly supposed by horrified commentators that these ads were so effective they essentially elected Donald Trump, though more sober analysis later concluded that Cambridge Analytica’s capabilities fell short of mind control.8 Each of us is sweating data, and those data are being mopped up and wrung out into oceans of information.

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., “Assessing Google Flu Trends Performance in the United States during the 2009 Influenza Virus A (H1N1) Pandemic,” PLoS ONE 6, no. 8: e23610 (2011), https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0023610. 7. Janelle Shane, You Look Like a Thing and I Love You (New York: Little, Brown, 2019). 8. For comprehensive reporting of this affair, see “The Cambridge Analytica Files,” on the Observer/Guardian website, https://www.theguardian.com/news/series/cambridge-analytica-files. 9. Charles Duhigg, “How Companies Learn Your Secrets,” New York Times Magazine, February 19, 2012, https://www.nytimes.com/2012/02/19/magazine/shopping-habits.html. 10. Hannah Fry, Hello World: Being Human in the Age of Computers (London: W.

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If Target can improve to guessing correctly 10 or 15 percent of the time, that’s already likely to be well worth doing. Even a modest increase in the accuracy of targeted special offers would help the bottom line. But profitability should not be conflated with omniscience. So let’s start by toning down the hype a little—both the apocalyptic idea that Cambridge Analytica can read your mind, and the giddy prospect that big data can easily replace more plodding statistical processes such as the CDC’s survey of influenza cases. When I first started grappling with big data, I called Cambridge University professor David Spiegelhalter, one of the UK’s leading statisticians and a brilliant statistical communicator.

Likewar: The Weaponization of Social Media by Peter Warren Singer, Emerson T. Brooking

4chan, active measures, Airbnb, augmented reality, barriers to entry, battle of ideas, Bellingcat, Bernie Sanders, Black Lives Matter, British Empire, Cambridge Analytica, Cass Sunstein, citizen journalism, Citizen Lab, Comet Ping Pong, content marketing, crony capitalism, crowdsourcing, data science, deep learning, digital rights, disinformation, disintermediation, Donald Trump, drone strike, Edward Snowden, en.wikipedia.org, Erik Brynjolfsson, Evgeny Morozov, fake news, false flag, Filter Bubble, global reserve currency, Google Glasses, Hacker Conference 1984, Hacker News, illegal immigration, information security, Internet Archive, Internet of things, invention of movable type, it is difficult to get a man to understand something, when his salary depends on his not understanding it, Jacob Silverman, John Gilmore, John Markoff, Kevin Roose, Kickstarter, lateral thinking, lolcat, Mark Zuckerberg, megacity, Menlo Park, meta-analysis, MITM: man-in-the-middle, Mohammed Bouazizi, Moneyball by Michael Lewis explains big data, moral panic, new economy, offshore financial centre, packet switching, Panopticon Jeremy Bentham, Parag Khanna, pattern recognition, Plato's cave, post-materialism, Potemkin village, power law, pre–internet, profit motive, RAND corporation, reserve currency, sentiment analysis, side project, Silicon Valley, Silicon Valley startup, Snapchat, social web, South China Sea, Steve Bannon, Steve Jobs, Steven Levy, Stewart Brand, systems thinking, too big to fail, trade route, Twitter Arab Spring, UNCLOS, UNCLOS, Upton Sinclair, Valery Gerasimov, We are Anonymous. We are Legion, We are as Gods, Whole Earth Catalog, WikiLeaks, Y Combinator, yellow journalism, Yochai Benkler

Flynn,” Young America’s Foundation, November 12, 2016, accessed March 20, 2018, https://www.yaf.org/videos/lieutenant-general-michael-t-flynn/. 176 its strategic efforts: Steven Bertoni, “Exclusive Interview: How Jared Kushner Won Trump the White House,” Forbes, November 22, 2016, https://www.forbes.com/sites/stevenbertoni/2016/11/22/exclusive-interview-how-jared-kushner-won-trump-the-white-house/#633d9c9a3af6. 176 his first $2 million: Sue Halpern, “How He Used Facebook to Win,” New York Review of Books, June 8, 2017, http://www.nybooks.com/articles/2017/06/08/how-trump-used-facebook-to-win/. 176 every last bit: Ibid. 177 8 trillion pieces: Ibid. 177 5,000 data points: Ibid. 177 “sex compass”: Alyssa Newcomb, “‘Sex Compass’ App Harvested User Data, Former Cambridge Analytica Employee Says,” NBC News, April 17, 2018, https://www.nbcnews.com/tech/tech-news/sex-compass-app-harvested-user-data-former-cambridge-analytica-employee-n866666. 177 not just 87 million users: Sean Burch, “Facebook Now Says 87 Million Users Hit by Cambridge Analytica Leak,” The Wrap, April 4, 2018, https://www.thewrap.com/facebook-87-million-cambridge-analytica-leak/. 177 direct messages: Alex Hern and Carole Cadwalladr, “Revealed: Aleksander Kogan Collected Facebook Users’ Direct Messages,” The Guardian, April 13, 2018, https://www.theguardian.com/uk-news/2018/apr/13/revealed-aleksandr-kogan-collected-facebook-users-direct-messages. 177 “gold mine”: Natasha Bertrand, “A Long-Overlooked Player Is Emerging as a Key Figure in the Trump-Russia Investigation,” Business Insider, June 23, 2017, http://www.businessinsider.com/brad-parscale-trump-russia-investigation-2017-6. 177 patterns of Facebook “likes”: Hannes Grassegger and Mikael Krogerus, “The Data That Turned the World Upside Down,” Motherboard (blog), Vice, January 28, 2017, https://motherboard.vice.com/en_us/article/mg9vvn/how-our-likes-helped-trump-win. 177 only ten “likes”: Ibid. 177 “We exploited Facebook”: Carole Cadwalladr and Emma Graham-Harrison, “Revealed: 50 Million Facebook Profiles Harvested for Cambridge Analytica in Major Data Breach,” The Guardian, March 17, 2018, https://www.theguardian.com/news/2018/mar/17/cambridge-analytica-facebook-influence-us-election. 177 Lookalike Audiences: Halpern, “How He Used Facebook to Win.” 178 “fifteen people”: Brad Parscale, interview, “How Facebook Ads Helped Elect Trump,” 60 Minutes, CBS, October 6, 2017, https://www.cbsnews.com/news/how-facebook-ads-helped-elect-trump/. 178 “perfect” messages: Issie Laprowsky, “Here’s How Facebook Actually Won Trump the Presidency,” Wired, November 15, 2016, https://www.wired.com/2016/11/facebook-won-trump-election-not-just-fake-news/. 178 almost 6 million different versions: Sarah Frier, “Trump’s Campaign Said It Was Better at Facebook.

…

Then there was the data archive of the Republican National Committee, which claimed to have nearly 8 trillion pieces of information spread across 200 million American voters. And, finally, came the massive data stores of a controversial company called Cambridge Analytica. A UK-based firm that Breitbart chairman and Trump campaign CEO Steve Bannon had helped form in 2013, Cambridge Analytica had previously been active in conducting information warfare–style efforts on behalf of clients ranging from corporations to the “Leave” side of Brexit. It would later be reported to have provided to the Trump campaign some 5,000 data points on 220 million Americans.

…

Flynn,” Young America’s Foundation, November 12, 2016, accessed March 20, 2018, https://www.yaf.org/videos/lieutenant-general-michael-t-flynn/. 176 its strategic efforts: Steven Bertoni, “Exclusive Interview: How Jared Kushner Won Trump the White House,” Forbes, November 22, 2016, https://www.forbes.com/sites/stevenbertoni/2016/11/22/exclusive-interview-how-jared-kushner-won-trump-the-white-house/#633d9c9a3af6. 176 his first $2 million: Sue Halpern, “How He Used Facebook to Win,” New York Review of Books, June 8, 2017, http://www.nybooks.com/articles/2017/06/08/how-trump-used-facebook-to-win/. 176 every last bit: Ibid. 177 8 trillion pieces: Ibid. 177 5,000 data points: Ibid. 177 “sex compass”: Alyssa Newcomb, “‘Sex Compass’ App Harvested User Data, Former Cambridge Analytica Employee Says,” NBC News, April 17, 2018, https://www.nbcnews.com/tech/tech-news/sex-compass-app-harvested-user-data-former-cambridge-analytica-employee-n866666. 177 not just 87 million users: Sean Burch, “Facebook Now Says 87 Million Users Hit by Cambridge Analytica Leak,” The Wrap, April 4, 2018, https://www.thewrap.com/facebook-87-million-cambridge-analytica-leak/. 177 direct messages: Alex Hern and Carole Cadwalladr, “Revealed: Aleksander Kogan Collected Facebook Users’ Direct Messages,” The Guardian, April 13, 2018, https://www.theguardian.com/uk-news/2018/apr/13/revealed-aleksandr-kogan-collected-facebook-users-direct-messages. 177 “gold mine”: Natasha Bertrand, “A Long-Overlooked Player Is Emerging as a Key Figure in the Trump-Russia Investigation,” Business Insider, June 23, 2017, http://www.businessinsider.com/brad-parscale-trump-russia-investigation-2017-6. 177 patterns of Facebook “likes”: Hannes Grassegger and Mikael Krogerus, “The Data That Turned the World Upside Down,” Motherboard (blog), Vice, January 28, 2017, https://motherboard.vice.com/en_us/article/mg9vvn/how-our-likes-helped-trump-win. 177 only ten “likes”: Ibid. 177 “We exploited Facebook”: Carole Cadwalladr and Emma Graham-Harrison, “Revealed: 50 Million Facebook Profiles Harvested for Cambridge Analytica in Major Data Breach,” The Guardian, March 17, 2018, https://www.theguardian.com/news/2018/mar/17/cambridge-analytica-facebook-influence-us-election. 177 Lookalike Audiences: Halpern, “How He Used Facebook to Win.” 178 “fifteen people”: Brad Parscale, interview, “How Facebook Ads Helped Elect Trump,” 60 Minutes, CBS, October 6, 2017, https://www.cbsnews.com/news/how-facebook-ads-helped-elect-trump/. 178 “perfect” messages: Issie Laprowsky, “Here’s How Facebook Actually Won Trump the Presidency,” Wired, November 15, 2016, https://www.wired.com/2016/11/facebook-won-trump-election-not-just-fake-news/. 178 almost 6 million different versions: Sarah Frier, “Trump’s Campaign Said It Was Better at Facebook.

If Then: How Simulmatics Corporation Invented the Future by Jill Lepore

A Declaration of the Independence of Cyberspace, Alvin Toffler, anti-communist, Apollo 11, Buckminster Fuller, Cambridge Analytica, company town, computer age, coronavirus, cuban missile crisis, data science, desegregation, don't be evil, Donald Trump, Dr. Strangelove, Elon Musk, fake news, game design, George Gilder, Grace Hopper, Hacker Ethic, Howard Zinn, index card, information retrieval, Jaron Lanier, Jeff Bezos, Jeffrey Epstein, job automation, John Perry Barlow, land reform, linear programming, Mahatma Gandhi, Marc Andreessen, Mark Zuckerberg, mass incarceration, Maui Hawaii, Menlo Park, military-industrial complex, New Journalism, New Urbanism, Norbert Wiener, Norman Mailer, packet switching, Peter Thiel, profit motive, punch-card reader, RAND corporation, Robert Bork, Ronald Reagan, Rosa Parks, self-driving car, Silicon Valley, SimCity, smart cities, social distancing, South China Sea, Stewart Brand, technoutopianism, Ted Sorensen, Telecommunications Act of 1996, urban renewal, War on Poverty, white flight, Whole Earth Catalog

It’s like a boomerang: you send your data out, it gets analyzed, and it comes back at you as targeted messaging to change your behavior.”17 Cambridge Analytica’s Facebook “likes”? That was Ithiel de Sola Pool’s “cross-cutting pressures.” Cambridge Analytica’s boomerang model? That was Bill McPhee’s “three-stage model of communication.” Faster, better, fancier, pricier, but the same hucksterism, and as for the claims of its daunting efficacy, the same flimflam. Donald Trump’s 2016 presidential campaign didn’t need Cambridge Analytica. Facebook, alone, could target specific voters with custom-made messages. Commentators accused the Trump campaign of using a “weaponized AI propaganda machine,” describing a new and “nearly impenetrable voter manipulation machine.”18 New?

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“Data without what-if modeling may be the database community’s past,” according to a 2011 journal article, “but data with what-if modeling must be its future.”15 A 2018 encyclopedia defined “what-if analysis” as “a data-intensive simulation,” describing it as “a relatively recent discipline.”16 What if, what if, what if: What if the future forgets its past? Behavioral data science didn’t spring from the head of Zeus. Cambridge Analytica used Facebook data in an attempt to influence the 2016 U.S. presidential election in a way that Bill McPhee and Ed Greenfield and Ithiel de Sola Pool and Joseph Hoc would have understood, even if they could only dream about its gargantuan quantity of data or the ability to run simulations in real time, dynamically. “The bulk of our resources went into targeting those whose minds we thought we could change,” former Cambridge Analytica executive Brittany Kaiser explained in 2019. “We called them ‘the persuadables.’ . . .

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The scientists of the Simulmatics Corporation spent the summer of 1961 on a beach on Long Island beneath a geodesic dome that looked as if it had landed there, amid the dunes, a spaceship gone to ground.1 Inside, they wrote mathematical formulas on blackboards. Chalk dusted their fingertips. Reams of perforated computer printouts unfurled across the floor. The Simulmatics Corporation, Cold War America’s Cambridge Analytica, claimed credit for having gotten John F. Kennedy elected president of the United States in November 1960. Months later, its scientists spent a summer at the beach planning new projects for their invention: a computer program designed to predict and manipulate human behavior, all sorts of human behavior, from buying a dishwasher to countering an insurgency to casting a vote.

When McKinsey Comes to Town: The Hidden Influence of the World's Most Powerful Consulting Firm by Walt Bogdanich, Michael Forsythe

"RICO laws" OR "Racketeer Influenced and Corrupt Organizations", "World Economic Forum" Davos, activist fund / activist shareholder / activist investor, Affordable Care Act / Obamacare, Alistair Cooke, Amazon Web Services, An Inconvenient Truth, asset light, asset-backed security, Atul Gawande, Bear Stearns, Boris Johnson, British Empire, call centre, Cambridge Analytica, carbon footprint, Citizen Lab, cognitive dissonance, collective bargaining, compensation consultant, coronavirus, corporate governance, corporate social responsibility, Corrections Corporation of America, COVID-19, creative destruction, Credit Default Swap, crony capitalism, data science, David Attenborough, decarbonisation, deindustrialization, disinformation, disruptive innovation, do well by doing good, don't be evil, Donald Trump, double entry bookkeeping, facts on the ground, failed state, financial engineering, full employment, future of work, George Floyd, Gini coefficient, Glass-Steagall Act, global pandemic, illegal immigration, income inequality, information security, interchangeable parts, Intergovernmental Panel on Climate Change (IPCC), invisible hand, job satisfaction, job-hopping, junk bonds, Kenneth Arrow, Kickstarter, load shedding, Mark Zuckerberg, megaproject, Moneyball by Michael Lewis explains big data, mortgage debt, Multics, Nelson Mandela, obamacare, offshore financial centre, old-boy network, opioid epidemic / opioid crisis, profit maximization, public intellectual, RAND corporation, Rutger Bregman, scientific management, sentiment analysis, shareholder value, Sheryl Sandberg, Silicon Valley, smart cities, smart meter, South China Sea, sovereign wealth fund, tech worker, The future is already here, The Nature of the Firm, too big to fail, urban planning, WikiLeaks, working poor, Yogi Berra, zero-sum game

To do that, they turned to McKinsey, Boston Consulting, and a third firm, the London-based SCL Group, better known through its subsidiary, Cambridge Analytica, notorious for influencing elections across the globe for any candidate willing to pay its fees. Cambridge Analytica’s CEO, Alexander Nix, boasted to undercover journalists from Britain’s Channel 4 News that the company could “send some girls around to the candidate’s house” to entrap them, saying he liked to use Ukrainian “girls” for the job. The company also improperly accessed Facebook data to help the Trump campaign create psychological profiles of millions of voters who were then bombarded with targeted content. In Saudi Arabia, SCL and Cambridge Analytica were essentially interchangeable: the work there was overseen by the person who succeeded Nix as Cambridge Analytica’s CEO.

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In Saudi Arabia, SCL and Cambridge Analytica were essentially interchangeable: the work there was overseen by the person who succeeded Nix as Cambridge Analytica’s CEO. The aim was to conduct focus groups across the kingdom, asking people how they would feel if the price of fuel increased. McKinsey and BCG would then process that information and present it to senior officials at the ministry. This deeply political work went far beyond the traditional McKinsey remit of providing advice to private companies on how to save money by being more efficient. One former Cambridge Analytica executive involved in the Saudi work with McKinsey said the purpose behind it was “to reduce the risk of unrest.”

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One former Cambridge Analytica executive involved in the Saudi work with McKinsey said the purpose behind it was “to reduce the risk of unrest.” McKinsey was helping ensure the viability of a brutal, authoritarian regime. “Putting the bits and pieces together, in hindsight I don’t feel good about it,” said another former Cambridge Analytica consultant whose work intersected with McKinsey’s. “It is a sort of reinforcement, or adding to their consolidation of power.” McKinsey said it did not work with Cambridge Analytica or the SCL Group for the Saudi Ministry of Economy and Planning. McKinsey’s work with the Saudis went far beyond focus groups. Saudi Arabia’s population is one of the youngest in the world and one of the most engaged on platforms like Twitter and Facebook.

System Error by Rob Reich

"Friedman doctrine" OR "shareholder theory", "World Economic Forum" Davos, 2021 United States Capitol attack, A Declaration of the Independence of Cyberspace, Aaron Swartz, AI winter, Airbnb, airport security, Alan Greenspan, Albert Einstein, algorithmic bias, AlphaGo, AltaVista, artificial general intelligence, Automated Insights, autonomous vehicles, basic income, Ben Horowitz, Berlin Wall, Bernie Madoff, Big Tech, bitcoin, Blitzscaling, Cambridge Analytica, Cass Sunstein, clean water, cloud computing, computer vision, contact tracing, contact tracing app, coronavirus, corporate governance, COVID-19, creative destruction, CRISPR, crowdsourcing, data is the new oil, data science, decentralized internet, deep learning, deepfake, DeepMind, deplatforming, digital rights, disinformation, disruptive innovation, Donald Knuth, Donald Trump, driverless car, dual-use technology, Edward Snowden, Elon Musk, en.wikipedia.org, end-to-end encryption, Fairchild Semiconductor, fake news, Fall of the Berlin Wall, Filter Bubble, financial engineering, financial innovation, fulfillment center, future of work, gentrification, Geoffrey Hinton, George Floyd, gig economy, Goodhart's law, GPT-3, Hacker News, hockey-stick growth, income inequality, independent contractor, informal economy, information security, Jaron Lanier, Jeff Bezos, Jim Simons, jimmy wales, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John Perry Barlow, Lean Startup, linear programming, Lyft, Marc Andreessen, Mark Zuckerberg, meta-analysis, minimum wage unemployment, Monkeys Reject Unequal Pay, move fast and break things, Myron Scholes, Network effects, Nick Bostrom, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, NP-complete, Oculus Rift, OpenAI, Panopticon Jeremy Bentham, Parler "social media", pattern recognition, personalized medicine, Peter Thiel, Philippa Foot, premature optimization, profit motive, quantitative hedge fund, race to the bottom, randomized controlled trial, recommendation engine, Renaissance Technologies, Richard Thaler, ride hailing / ride sharing, Ronald Reagan, Sam Altman, Sand Hill Road, scientific management, self-driving car, shareholder value, Sheryl Sandberg, Shoshana Zuboff, side project, Silicon Valley, Snapchat, social distancing, Social Responsibility of Business Is to Increase Its Profits, software is eating the world, spectrum auction, speech recognition, stem cell, Steve Jobs, Steven Levy, strong AI, superintelligent machines, surveillance capitalism, Susan Wojcicki, tech billionaire, tech worker, techlash, technoutopianism, Telecommunications Act of 1996, telemarketer, The Future of Employment, TikTok, Tim Cook: Apple, traveling salesman, Triangle Shirtwaist Factory, trolley problem, Turing test, two-sided market, Uber and Lyft, uber lyft, ultimatum game, union organizing, universal basic income, washing machines reduced drudgery, Watson beat the top human players on Jeopardy!, When a measure becomes a target, winner-take-all economy, Y Combinator, you are the product

When click-through rates increase on untruthful ads that question the integrity of election results without evidence or promote conspiracy theories about vaccines, revenues and market capitalizations may rise, but democracy and the well-being of hundreds of millions of people will suffer. Even when there is fallout for the companies responsible, it’s often short lived. Consider that Facebook’s stock price did not suffer any long-term damage from the Cambridge Analytica scandal in 2016. To the contrary, it has since soared. If the market rewards only revenue, where’s the incentive to protect democracy or other values we cherish? Hunting for Unicorns Just over fifty years ago, Milton Friedman—still six years shy of winning the Nobel Prize in Economics—penned an essay in the New York Times espousing the view that “The Social Responsibility of Business Is to Increase Its Profits.”

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The acquisition was a way for Facebook to cement itself as the dominant online messaging platform, bringing WhatsApp’s 450 million active monthly users at the time, many of them outside the United States, under the Facebook umbrella. Within a few years, both Acton and Koum would leave Facebook citing concerns over user privacy and the way Facebook was monetizing WhatsApp’s user base. In turn, in 2019, Mark Zuckerberg, still grappling with the privacy concerns heightened as a result of the Cambridge Analytica scandal, announced an intention to provide end-to-end encryption on all Facebook messaging services, including Facebook Messenger and Instagram Direct. If you care about privacy, this all sounds appealing unless you are the head of the FBI, trying to track down terrorist sympathizers who are plotting an attack in a major US city or a human rights campaigner in India who has discovered that political gangs are using encrypted communication technologies to organize anti-Muslim violence in advance of an election.

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The ballot initiative empowered California consumers to learn what personal information companies were collecting and how they were using it and gave them the option of preventing the selling and sharing of their data. Mactaggart’s ballot initiative garnered 629,000 signatures, double what was necessary. Enthusiasm for the effort mounted as Facebook confronted a scandal around Cambridge Analytica’s misuse of the personal data of 87 million people in 2018. By that point, legislators had taken note and the companies were far more open to compromise. Mactaggart agreed to hold off on his push to put the initiative onto the ballot, hoping that the state legislature could develop a comprehensive privacy bill.

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

When his campaign brass gathered down below on Election Night, plenty of them thought their boss needed a miracle to win. Trump’s team had access to three different sources of polling—its own, run by Conway and a trio of Republican pollsters; large-scale surveys conducted by the GOP firm TargetPoint that fed into the Republican National Committee’s micro-targeting model; and another set of surveys by Cambridge Analytica, a London data science outfit contracted by the campaign to build a sophisticated model of its own. None of them pointed toward victory. Outwardly, Trump’s team kept up appearances by mercilessly flaying Clinton and insisting that their man could win. But behind the scenes, some advisers had already begun positioning themselves for the knife fight that would immediately follow a loss.

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“Well, the numbers tell two different stories,” Bannon replied. “If you believe one set, we’re killing it, it’s a change election, and everything lines up exactly like we thought. But, man, if you believe the other one, we’re getting crushed.” It was a moment of truth—and a dilemma. The Cambridge Analytica model had picked up a late shift in the electorate toward Trump. But it was only a model. These exit polls were based on thousands of interviews with actual voters, and they were telling a much different story. Not knowing what else to do, Bannon called Matt Drudge to ask what he thought.

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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. It also allowed the Mercers to build out an infrastructure for sophisticated messaging and strategy that would be independent of the institutional Republican Party (an impulse shared by their fellow billionaires, David and Charles Koch, who also spent tens of millions of dollars building an alternative party structure, so disillusioned were they by the ineptitude of the GOP).

The Creativity Code: How AI Is Learning to Write, Paint and Think by Marcus Du Sautoy

3D printing, Ada Lovelace, Albert Einstein, algorithmic bias, AlphaGo, Alvin Roth, Andrew Wiles, Automated Insights, Benoit Mandelbrot, Bletchley Park, Cambridge Analytica, Charles Babbage, Claude Shannon: information theory, computer vision, Computing Machinery and Intelligence, correlation does not imply causation, crowdsourcing, data is the new oil, data science, deep learning, DeepMind, Demis Hassabis, Donald Trump, double helix, Douglas Hofstadter, driverless car, Elon Musk, Erik Brynjolfsson, Fellow of the Royal Society, Flash crash, Gödel, Escher, Bach, Henri Poincaré, Jacquard loom, John Conway, Kickstarter, Loebner Prize, machine translation, mandelbrot fractal, Minecraft, move 37, music of the spheres, Mustafa Suleyman, Narrative Science, natural language processing, Netflix Prize, PageRank, pattern recognition, Paul Erdős, Peter Thiel, random walk, Ray Kurzweil, recommendation engine, Rubik’s Cube, Second Machine Age, Silicon Valley, speech recognition, stable marriage problem, Turing test, Watson beat the top human players on Jeopardy!, wikimedia commons

But tell them a story about someone who has come down with measles or smallpox and combine that story with the data and you stand a chance of getting them to reconsider. As George Monbiot put it in Out of the Wreckage: ‘The only thing that can displace a story is a story.’ The fact that stories can be used to change opinions is something companies like Cambridge Analytica have exploited ruthlessly. By harvesting the personal information of 87 million Facebook users with an app called ‘This is your digital life’, Cambridge Analytica was able to draw up psychological profiles that could then be matched with news stories to influence the way people might vote. The algorithms started by randomly assigning stories, but they gradually learned which ones attracted clicks.

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It ensured that these stories were put in front of the people whose views were most likely to be changed by them and not wasted on those who were more likely to be unaffected. When the news broke that Cambridge Analytica had effectively manipulated the electorate, the backlash brought the company down – ironically revealing exactly what it had banked on: the power of a news story to influence events. While Cambridge Analytica may have folded, there are many other companies out there that continue to mine data to squeeze out strategic advantages for those willing to pay. If we want to retain a modicum of control over our lives, it is important that we understand how our emotions and political opinions are being pushed and pulled around by these algorithms, and how, given the same information, each one will spin its own particular yarn, tailored to fan our hang-ups and views.

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E. 139 Beveridge, Andrew 56 Beyond the Fence (musical) 290–1 Białystok University 236 biases and blind spots, algorithmic 91–5 Birtwistle, Harrison 193 Blake, William 279 Blombos Cave, South Africa 103 Bloom (app) 229 BOB (artificial life form) 146–8 Boden, Margaret 9, 10, 11, 16, 39, 209, 222 Boeing 114 Bonaparte, Napoleon 158 bone carvings 104–5 booksellers 62–5 bordeebook 62–5 Borges, Jorge Luis: ‘The Library of Babel’ 241–4, 253, 304 Botnik 284–6 Boulanger, Nadia 186, 189, 205, 209 Boulez, Pierre 11, 223 brachistochrone 244 Braff, Zach 284 brain: biases and blind spots 91–2; consciousness and 274, 304–5; fractals and 124–5; mathematics and 155, 156, 160–1, 171, 174, 177, 178; musical composition and 187, 189, 193, 203, 205, 231; neural networks and 68–71, 68, 70; pattern recognition and 6, 20–1, 99–101, 155; stroke and 133–4; visual recognition and 76, 79, 143–4 Breakout (game) 26–8, 91, 92, 210 Brew, Jamie 284 Brin, Sergey 48–9, 51–2, 57 Bronowski, Jacob 104 Brown, Glenn 141 Bruner, Jerome 303 Buolamwini, Joy 94 Cage, John 106, 206 Calculus of Constructions (CoC) 173–4 see also Coq Cambridge Analytica 296 Cambridge University 18–19, 23–4, 43, 72, 81, 150, 225, 240, 278, 290 Carpenter, Loren 114, 115 Carré, Benoit 224 cars, driverless 6, 29–30, 79, 91 Cartesian geometry 110–11 Catmull, Ed 115 cave art, ancient 103–4, 105, 156, 230 Cawelti, John: Adventure, Mystery and Romance 252–3 Chang, Alex 23 chaos theory 124 Cheng, Ian 146–8 chess 16, 18–20, 21, 22–3, 29, 32–3, 34, 97, 151, 153, 162, 163, 246, 260–1, 304 child pornography 77 Chilvers, Peter 229 Chinese Room experiment 164, 273–5 Chomsky, Noam 260 Chopin, Frédéric 13, 197, 200, 202, 204, 206–7, 304 Christie’s 141 classemes 138 Classical era of music 10, 12–13, 190, 199, 207 Classification of Finite Simple Groups 18, 172, 175, 177, 244 Coelho, Paulo 302 Cohen, Harold 116–17, 118, 121 Coleridge, Samuel Taylor: ‘Kubla Khan’ 14 Colton, Simon 119, 120, 121–2, 291, 292, 293 Coltrane, John 223 Commodore Amiga 23 Congo (chimp) 107 consciousness 107, 231, 232, 270, 274, 283, 300, 302–6 Continuator, The 218–21, 286 Conway, John 18–19 Cope, David 195–203, 207, 208, 210, 304 copyright ownership 108–9 Coq 173–6, 177, 184 Coquand, Thierry 173 correlation as causation, mistaking 92–4 Corresponding Society of Musical Sciences 193, 208 Coulom, Rémi 31 Crazy Stone 31 Creative Adversarial Networks 140–1 creativity: algorithmic and rule-based, as 5; animals and 107–9; art, definition of and 103–7; audiences and 303; coder to code, shifting from 7, 102–3, 116–22, 132–42, 219–20; combinational 10–11, 16, 181, 222, 299; commercial incentive and 131–2; competition and 132–42; consciousness and 301–2, 303–5; death and 304; definition of 3–5, 9–13, 301–2; drugs and 181–2; exploratory 9–10, 40, 181, 219, 299; failure as component part of 17; feedback from others and 132; flow and 221–4, 222; Go and see Go; human lives as act of 303–4; Lovelace Test and see Lovelace Test; mathematics and 3, 150–1, 153, 161, 167–8, 170, 181–2, 185, 245–8, 253, 279–80; mechanical nature of 298; music and see music; new/novelty and 3, 4, 7–8, 12, 13, 16, 17, 40–3, 102–3, 109, 138–41, 140, 167–8, 238–9, 291–3, 299, 301; origins of our obsession with 301; political role of 303; randomness and 117–18; romanticising 14–15; self-reflection and 300; storytelling and see storytelling; surprise and 4, 8, 40, 65, 66, 102–3, 148, 168, 202, 241, 248–9; teaching 13–17; three types of 9–13; transformational 11–13, 17, 39, 41, 181, 209, 299; value and 4, 8, 12, 16, 17, 40–1, 102–3, 167–8, 238–9, 301, 304 Csikszentmihalyi, Mihaly 221 Cubism 11, 138, 139 Cybernetic Poet 280–2 Cybernetic Serendipity (ICA exhibition, 1968) 118–19 Dahl, Roald: Tales of the Unexpected 276–7; ‘The Great Automatic Grammatizator’ 276–7, 297 dating/matching 57–61, 58, 59, 60 da Vinci, Leonardo 106, 118, 128; Treatise on Painting 117 Davis, Miles: Kind of Blue 214 Debussy, Claude 1 DeepBach 210–12, 232 DeepBlue 29, 214, 260–1 DeepMind 25–43, 65, 95, 97, 98, 131, 132, 151, 210, 233–9, 241, 266 Deep Watch 224 Delft University of Technology 127 democracy 165–6 Dennett, Daniel 147 Descartes, René 12, 110–11 Disney 289–90 Duchamp, Marcel 106 du Sautoy, Marcus: attempts to fake a Jackson Pollock 123–5; composes music 186–8; The Music of the Primes 285–6; uses AI to write section of this book 297 Dylan, Bob 223 EEG 125 Egyptians, Ancient 157, 165 eigenvectors of matrices 53 Eisen, Michael 62, 64 Elgammal, Ahmed 132–3, 134, 135, 139, 140, 141 Eliot, George 302 Eliot, T.

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

The billionaire Elon Musk, for example, seized the initiative from NASA and the European Space Agency and made traveling to Mars one of his entrepreneurial ambitions. Amazon’s relationship to retail markets is becoming closer to that of a regulator than a competitor. Companies such as Palantir and SCL, which founded the now defunct Cambridge Analytica with Mercer’s financial support, straddle commercial, political, and military domains of intelligence operations. The capacity for violence, which for Hobbes was the preserve of the “sovereign,” is shifting gradually into private hands, with war, prison systems, immigration enforcement, and border control increasingly delivered by commercial contractors.

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“Smart city” projects depend on data scientists to extract patterns of activity from the frenetic movements of urban populations, resources, and transport. Firms such as Peter Thiel’s Palantir help security services identify potential security threats, by isolating dangerous patterns of behavior. And then there are the murky cases of consultancies, such as Cambridge Analytica, who worked for political clients to help tailor messaging to particular voters. In every case, the data scientist can provide advice on what to do, to serve a particular interest or agenda, but they are rarely in the job of producing matters of consensual public fact. Commercial analytics companies are inevitably concerned with commercial secrecy and client confidentiality.

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This is why the specter of Russia and of private wealth haunt us, as we seek explanations for political upheavals and chaos: they offer the perfect base from which to wage informational war, being less constrained by public regulation. Reports of alliances between the Kremlin, billionaire owners of private companies (as opposed to shareholders of corporations), WikiLeaks, and firms, such as Cambridge Analytica, sometimes feel like conspiracy theories because—by definition and design—such entities are not subject to any expert or regulatory oversight. If the ideal of presenting facts in public in search of peaceful consensus has become a source of strategic vulnerability, then Western democracies are in serious trouble.

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

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

target political ads: Matthew Rosenberg, Nicholas Confessore, and Carole Cadwalladr, “How Trump Consultants Exploited the Facebook Data of Millions,” New York Times, March 17, 2018, accessed August 21, 2018, https://www.nytimes.com/2018/03/17/us/politics/cambridge-analytica-trump-campaign.html; Ian Sherr, “Facebook, Cambridge Analytica and Data Mining: What You Need to Know,” CNET, April 18, 2018, accessed August 21, 2018, https://www.cnet.com/news/facebook-cambridge-analytica-data-mining-and-trump-what-you-need-to-know/; “Full Text: Mark Zuckerberg’s Wednesday Testimony to Congress on Cambridge Analytica,” Politico, April 9, 2018, accessed August 21, 2018, https://www.politico.com/story/2018/04/09/transcript-mark-zuckerberg-testimony-to-congress-on-cambridge-analytica-509978. developing-news stories: Issie Lapowsky, “YouTube Debuts Plan to Promote and Fund ‘Authoritative’ News,” Wired, July 9, 2018, accessed August 21, 2018, https://www.wired.com/story/YouTube-debuts-plan-to-promote-fund-authoritative-news/.

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By the middle of 2018, the bloom was off the rose. The big social networks had been stung by a “techlash” of public criticism. Their top executives had all been dragged into Congress and berated over how Russian actors had used their systems to meddle in the 2016 election. The scandal over Cambridge Analytica had broken open, showing how the firm had scraped and used personal info on millions of Facebook users to target political ads. And so the big-tech firms had embarked on a campaign of offering apologies and, in fits and starts, launched more ambitious attempts to fix the problems they’d discovered.

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See minority coders Black Girls Code, ref1 #blacklivesmatter, ref1 Black Mirror (TV show), ref1 Blaze, Matt, ref1, ref2 “Bless” function, ref1 blockchain technology, ref1 Block Together app, ref1 blogging, ref1 Bloomberg, Michael, ref1 blue-collar coding, ref1 aptitude testing and, ref1 boot camps, ref1, ref2 children, computer programming education for, ref1 coal miners in KY learn coding at Bit Source, ref1 computer science degree programs, ref1 demand for coders, explosion in, ref1 job training, ref1, ref2 mainstreaming of coding, ref1 nontraditional fields, benefits of hiring workers from, ref1 self-taught coders, ref1, ref2 women and minorities and, ref1 Blue Gene, ref1 Blum, Lenore, ref1 Bogachev, Evgeniy Mikhailovich, ref1 Bogost, Ian, ref1, ref2 Booch, Grady, ref1 Boole, George, ref1 Boos, Hans-Christian, ref1 boot camps, ref1, ref2 Flatiron School, ref1, ref2, ref3 Geekskool, ref1 hiring rates for graduates of, ref1 types of coding graduates are prepared to do, ref1 vocational training nature of, ref1 Boston Globe, ref1 Bostrom, Nick, ref1, ref2 Bosworth, Andrew, ref1 botnets, ref1 boyd, danah, ref1, ref2, ref3 Braithwaite, Gwen, ref1 Brandeau, Greg, ref1 Brandon, Richard, ref1 break points, ref1 Breisacher, Tyler, ref1, ref2, ref3 Brewer, Johanna, ref1 Brin, Sergey, ref1 brogrammers, ref1, ref2 Broken Age (game), ref1 Brooks, Fred, ref1, ref2 Brotherhood, Oliver, ref1 Brotopia (Chang), ref1 Brown, Barrett, ref1, ref2 bug bounties, ref1 bugs, ref1 defined, ref1 examples of, ref1 fixing (See debugging) GetCalFresh app and, ref1 Netscape design and attitude regarding, ref1 origins of term, ref1 penetration testers and, ref1 self-esteem of coders and, ref1 triumph and elation in solving, ref1 unpredictability and abruptness of programming “wins,” ref1 user behavior and, ref1 Bulletin Board Systems (BBSes), ref1 Bunner, Andrew, ref1, ref2 Buolamwini, Joy, ref1 Burbn, ref1 Burke, Tarana, ref1 Burkhart, Annalise, ref1 Businessweek, ref1 Buyukkokten, Orkut, ref1 BuzzFeed, ref1, ref2 ByteDance, ref1 Cahill, Matt, ref1 Caldbeck, Justin, ref1 Callahan, Ezra, ref1 Cambridge Analytica scandal, ref1 Campbell, Donald, ref1 Campbell’s Law, ref1 Cannon, William, ref1 Cantrill, Bryan, ref1 capacity crisis, ref1 capitalism, and coding, ref1 CAPTCHA tests, ref1 Carmack, John, ref1 Carnegie Mellon University (CMU) computer science program, ref1, ref2, ref3, ref4 Carr, Nicholas, ref1 Catalyte, ref1 Cegłowski, Maciej, ref1 Chang, Emily, ref1, ref2, ref3 Chaos Monkeys (Martínez), ref1 Charlebois, Andrew, ref1 chatbots, ref1 Chawla, Rameet, ref1 children, computer programming education for, ref1 Choe, David, ref1 Chou, Tracy, ref1, ref2 Churchill, Elizabeth, ref1 Citizen Lab, ref1 Citron, Danielle, ref1 city planners, ref1 civic impacts of big tech, ref1, ref2 bias in algorithmic ranking systems and, ref1 coding employees power to pressure for change, ref1 engineers’/designers’ failure to see negative ways sites would be used, reasons for, ref1 free-to-use model, effects of, ref1 measures to combat harassment at big social networks, ref1 microtargeting and, ref1 presidential campaign of 2016, ref1, ref2 reforming big tech, ref1 Twitter and, ref1 civil engineers, ref1 civil liberties, hacking to protect.

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

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.

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BACK TO NOTE REFERENCE 2 Scott Travis, “For Parkland Shooting Victim Alaina Petty, the AR-15 Was Her Favorite Gun,” South Florida Sun-Sentinel, July 28, 2018, https://www.sun-sentinel.com/local/broward/parkland/florida-school-shooting/fl-ryan-petty-ar15-alaina-20180728-story.html. BACK TO NOTE REFERENCE 3 Nicholas Confessore, “Cambridge Analytica and Facebook: The Scandal and the Fallout So Far,” New York Times, April 4, 2018, https://www.nytimes.com/2018/04/04/us/politics/cambridge-analytica-scandal-fallout.html. BACK TO NOTE REFERENCE 4 “Mark Zuckerberg Testimony: Senators Question Facebook’s Commitment to Privacy,” New York Times, April 10, 2018, https://www.nytimes.com/2018/04/10/us/politics/mark-zuckerberg-testimony.html.

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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. Evidence emerged that Lukoil, a Kremlin-linked oil conglomerate, was among those interested in Cambridge Analytica’s targeting of U.S. voters. Congress summoned Zuckerberg for a couple of marathon hearings, during which he expressed regret and promised new tools to plug the data-protection gaps exploited by Russia and others. Lenny bristled at Zuckerberg’s threadbare apologies and glib nonanswers. It aggravated him that even in the light of a sweeping privacy scandal, Congress seemed not to fully grasp that Facebook profited by vacuuming up and selling a vast quantity of its users’ personal data, not by “connecting the world.”

Rage Inside the Machine: The Prejudice of Algorithms, and How to Stop the Internet Making Bigots of Us All by Robert Elliott Smith

"World Economic Forum" Davos, Ada Lovelace, adjacent possible, affirmative action, AI winter, Alfred Russel Wallace, algorithmic bias, algorithmic management, AlphaGo, Amazon Mechanical Turk, animal electricity, autonomous vehicles, behavioural economics, Black Swan, Brexit referendum, British Empire, Cambridge Analytica, cellular automata, Charles Babbage, citizen journalism, Claude Shannon: information theory, combinatorial explosion, Computing Machinery and Intelligence, corporate personhood, correlation coefficient, crowdsourcing, Daniel Kahneman / Amos Tversky, data science, deep learning, DeepMind, desegregation, discovery of DNA, disinformation, Douglas Hofstadter, Elon Musk, fake news, Fellow of the Royal Society, feminist movement, Filter Bubble, Flash crash, Geoffrey Hinton, Gerolamo Cardano, gig economy, Gödel, Escher, Bach, invention of the wheel, invisible hand, Jacquard loom, Jacques de Vaucanson, John Harrison: Longitude, John von Neumann, Kenneth Arrow, Linda problem, low skilled workers, Mark Zuckerberg, mass immigration, meta-analysis, mutually assured destruction, natural language processing, new economy, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, On the Economy of Machinery and Manufactures, p-value, pattern recognition, Paul Samuelson, performance metric, Pierre-Simon Laplace, post-truth, precariat, profit maximization, profit motive, Silicon Valley, social intelligence, statistical model, Stephen Hawking, stochastic process, Stuart Kauffman, telemarketer, The Bell Curve by Richard Herrnstein and Charles Murray, The Future of Employment, the scientific method, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, theory of mind, Thomas Bayes, Thomas Malthus, traveling salesman, Turing machine, Turing test, twin studies, Vilfredo Pareto, Von Neumann architecture, warehouse robotics, women in the workforce, Yochai Benkler

Livan, 2018, When Facts Fail: Bias, Polarisation and Truth in Social Networks, https://arxiv.org/abs/1808.08524 24Constructed by Orowa and my UCL colleagues Pierpaolo Vivo and Giacomo Livan, with some inputs from David and me. 25Sean Illing, 2018, Cambridge Analytica, the Shady Data Firm that Might Be a Key Trump–Russia Link, Explained. Vox, www.vox.com/policy-and-politics/2017/10/16/15657512/cambridge-analytica-facebook-alexander-nix-christopher-wylie 26Carole Cadwalladr, 2016, Google, Democracy and the Truth about Internet Search. Guardian, www.theguardian.com/technology/2016/dec/04/google-democracy-truth-internet-search-facebook 27Yochai Benkler, Robert Faris, Hal Roberts and Ethan Zuckerman, 2017, Study: Breitbart-Led Right-Wing Media Ecosystem Altered Broader Media Agenda.

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In 2016, Vox published a study indicating that membership in emergent ‘manosphere’ online communities, including those with hashtag-based identities #gamergate, #PUA (pick-up artists), ‘#incel (‘involuntarily celibates’) and #TheRedPill17’ are often precursors to interest in the #alt-right, a once obscure online political movement that is now familiar to everyone, having become an agent of international political change over the last few years.18 The ability of those with extreme views to find community online, and the radicalization of lonely, marginalized people, has certainly been enabled by the enhanced anonymity provided by the Internet. But recently a new power dynamic has emerged that originates not with isolated individuals, but powerful organizations. Developments like the Cambridge Analytica scandal, where the now defunct marketing and political consulting firm used stolen Facebook data to develop models used in influencing elections, illustrates another significant factor in the evolution of online community, one that plays a pivotal role in the direction it has recently taken.

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In this setting, online content-placing and ordering algorithms play the role of the ultimate motivated reasoners, reinforcing ‘points of view’ that satisfy their programmatic goals in the most simplified and dogmatic ways possible. Most of these algorithms are optimized for profit or are utilized for political gain. Consider the techniques of the now defunct marketing, political consulting and data brokerage firm Cambridge Analytica, who utilized big-data statistics to segment target audiences. By turning data into efficient statistical distributions, they were able to segment those distributions into atomic categories of people, who could then be targeted precisely with persuasive personalized adverts and editorial. During the American presidential election, they were reported to be using 40–50,000 different variants of adverts every day.

Don't Be Evil: How Big Tech Betrayed Its Founding Principles--And All of US by Rana Foroohar

"Susan Fowler" uber, "World Economic Forum" Davos, accounting loophole / creative accounting, Airbnb, Alan Greenspan, algorithmic bias, algorithmic management, AltaVista, Andy Rubin, autonomous vehicles, banking crisis, barriers to entry, behavioural economics, Bernie Madoff, Bernie Sanders, Big Tech, bitcoin, Black Lives Matter, book scanning, Brewster Kahle, Burning Man, call centre, Cambridge Analytica, cashless society, clean tech, cloud computing, cognitive dissonance, Colonization of Mars, computer age, corporate governance, creative destruction, Credit Default Swap, cryptocurrency, data is the new oil, data science, deal flow, death of newspapers, decentralized internet, Deng Xiaoping, digital divide, digital rights, disinformation, disintermediation, don't be evil, Donald Trump, drone strike, Edward Snowden, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Etonian, Evgeny Morozov, fake news, Filter Bubble, financial engineering, future of work, Future Shock, game design, gig economy, global supply chain, Gordon Gekko, Great Leap Forward, greed is good, income inequality, independent contractor, informal economy, information asymmetry, intangible asset, Internet Archive, Internet of things, invisible hand, Jaron Lanier, Jeff Bezos, job automation, job satisfaction, junk bonds, Kenneth Rogoff, life extension, light touch regulation, low interest rates, Lyft, Mark Zuckerberg, Marshall McLuhan, Martin Wolf, Menlo Park, military-industrial complex, move fast and break things, Network effects, new economy, offshore financial centre, PageRank, patent troll, Paul Volcker talking about ATMs, paypal mafia, Peter Thiel, pets.com, price discrimination, profit maximization, race to the bottom, recommendation engine, ride hailing / ride sharing, Robert Bork, Sand Hill Road, search engine result page, self-driving car, shareholder value, sharing economy, Sheryl Sandberg, Shoshana Zuboff, side hustle, Sidewalk Labs, Silicon Valley, Silicon Valley startup, smart cities, Snapchat, SoftBank, South China Sea, sovereign wealth fund, Steve Bannon, Steve Jobs, Steven Levy, stock buybacks, subscription business, supply-chain management, surveillance capitalism, TaskRabbit, tech billionaire, tech worker, TED Talk, Telecommunications Act of 1996, The Chicago School, the long tail, the new new thing, Tim Cook: Apple, too big to fail, Travis Kalanick, trickle-down economics, Uber and Lyft, Uber for X, uber lyft, Upton Sinclair, warehouse robotics, WeWork, WikiLeaks, zero-sum game

went the pitch), so would users of any app—which meant the app’s developer could eventually be able to extract information not only on those users, but also on any friends they “invited” to use the app.9 This is exactly the way that the now-infamous data leak with the British firm Cambridge Analytica happened. The academic Aleksandr Kogan created a survey app that was deployed on Facebook, and he used it to collect information not only on the 250,000 people who actually took the survey—but also on the 87 million more users they knew. Cambridge Analytica then used that information to deploy ads that may have helped tip the 2016 U.S. presidential election in favor of Donald Trump. That’s the network effect in action, at its most nefarious.

…

Such data is the oil of the information age, and it fuels the growth of those companies that can run on it—which is, nowadays, almost every company in almost every industry. This is a very important point—while the problems I’m outlining in this book (loss of privacy, corporate monopoly power, the decline of liberal democracy, and so on) are often best illustrated by the FAANGs, they certainly don’t end with them. It’s telling that Cambridge Analytica, the British political firm employed by the Trump campaign in the 2016 elections, leveraged information garnered not just from Facebook to create voter profiles, but from dozens of other sources as well, including educational institutions and church groups;34 in fact, you could argue that the tech companies are simply the canaries in the coal mine for what will eventually become a much larger shift toward a surveillance capitalism system in which businesses and organizations of all stripes will take part.

…

But simply making a few half-hearted efforts on the margins—adding a few human watchdogs here and there, or reiterating their supposed commitment to quality content over propaganda—is akin to trying to treat an aggressive cancer with a multivitamin. Why? Because these problems—filter bubbles, fake news, data breaches, and fraud—are all at the center of the most malignant—and profitable—business model in the world: that of data mining and hyper-targeted advertising.10 The Aura of Science The Cambridge Analytica scandal, whereby it was revealed that the Facebook platform had been exploited by foreign actors to influence the outcome of the 2016 presidential election—precipitated a huge rise in public awareness of how social media and its advertising-driven revenue model could pose a threat to liberal democracy.

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

Bannon wanted to close the gap and, by curating his clients, push a hard-right nationalist culture-war agenda within the GOP. The B2K world of online data could be his killer app. Backed by Mercer money, Bannon named this new Palantir-for-politics firm Cambridge Analytica, for the august university town where SCL’s Nix told the intellectually pretentious Bannon his firm was located, a straight-up lie that required SCL to assemble a fake office. Thanks to the cash infusion, it could afford that kind of behavior. In the early Cambridge Analytica tests, the firm relied on data brokers, including Acxiom. But Facebook data was the holy grail, and to get that, firms had to navigate a series of hoops, the combination of which gave Zuck and company a measure of plausible deniability.

…

Nix and Bannon took turns calling Americans, surveying them on their preferences, delighted to see the information match up with the profiles on the computer screen. Like Ferris Bueller convincing Cameron to steal his dad’s car, Palantir was happy to see the app plan work; now it wanted a ride. Cambridge Analytica’s success suggested that Palantir could get back in the Facebook-scraping game despite the RapLeaf debacle. The company started sending high-level employees to Cambridge off the books, getting pseudonymous log-in credentials for the Cambridge Analytica databases. They worked together to pinpoint holes in the Facebook data flow, designing seemingly innocent browser extensions such as calendars and calculators that took advantage of platform integration settings to siphon information.

…

Wylie doesn’t confirm that Palantir actually plugged the National Security Agency back into Facebook through Cambridge Analytica, but he was there when they planned to do it, and the way I read his account, that’s what happened. Nix regarded helping Palantir help the NSA as a North Atlantic patriotic obligation.63 Though Bannon’s Cambridge data efforts only became enduring headline news in 2018, the work didn’t stay secret for longer than a year. During the first days of the presidential primary, the Mercers backed Texas senator Ted Cruz, a right-winger with finance links, an elite legal background, and provocateur instincts. Considering the way Cambridge Analytica kicked into gear for Cruz during the primary, everything it did before that looks like a mere rehearsal for 2016.

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”).

…

Europe has taken the strictest approach to data protection by introducing the General Data Protection Regulation, a law that sets a variety of restrictions on the collection and use of data within the European Union. The United States continues to grapple with implementing appropriate protections to user privacy, a tension illustrated by Facebook’s Cambridge Analytica scandal and subsequent congressional hearings. China began implementing its own Cybersecurity Law in 2017, which included new punishments for the illegal collection or sale of user data. There’s no right answer to questions about what level of social surveillance is a worthwhile price for greater convenience and safety, or what level of anonymity we should be guaranteed at airports or subway stations.

…

See superintelligence Association for the Advancement of Artificial Intelligence, 88–89 Austria, 159 automation in factories and farms, 20, 165–66, 167–68 Fink’s letter and, 215, 216 intelligent vs. physical, 166, 167 jobs at risk of displacement by, 157–60, 162, 164, 165–67, 204 autonomous AI, 105–6, 128–36 Avenue of the Entrepreneurs (Chuangye Dajie), 53, 54, 61–62, 64, 68 B Baidu AI City and, 134 Chinese startups and, 58 as dominant AI player, 83, 91, 93 Google compared to, 37, 38, 109 Microsoft Research Asia and, 89 Ng, Andrew, and, 44 self-driving cars and, 131, 135 success of, 40, 66 Bain and Company, 164–65 banking industry, 110, 113, 116 BAT (Baidu, Alibaba, and Tencent), 58 battery approach, 95 beetle-like robots, 129–30 Beijing, China, 2–4, 28, 29, 51–52, 77–78, 99, 144–45 Bengio, Yoshua, 86 Bezos, Jeff, 33 Bhutan, 229 bicycle sharing, 77–78, 79 Bitmain, 97 blue-collar workers, 128–29, 165–66, 167, 168 Bostrom, Nick, 141, 142, 143 Brazil, 137, 138 Brin, Sergei, 33 Brooks, Rodney, 143 Brynjolfsson, Eric, 148–49, 150, 151 Buddhism, 187–90 business AI, 105–6, 110–17, 136 BuzzFeed, 40, 108, 109 ByteDance. See Toutiao (news platform) C Cambricon Technologies, 97 Cambridge Analytica, 107–8, 125 Canada AI superpowers and, 169 birth of AI and, 11, 13–14 business AI and, 111 new world order and, 20 volunteerism in, 229 cancer AI and diagnosis of, 167 Lee’s diagnosis with, 176–77, 181–83, 225 lymphoma, 176, 183, 190–92, 194 Care.com, 213 Careem, 137 care work and social investment stipend, 221, 222 Chan, Connie, 70 chess, 4–5 China AI, perspective on, and jobs, 202–3 AI deployment by, 18–19, 82–84, 132–33, 154–55 AI fever in, x, 1–6 conformity and deference to authority, cultural propensity for, 66 copycat era in.

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

mhq5j=e3; http://www.mirror.co.uk/news/politics/greedy-george-osborne-facing-furious-10049285 51 https://www.byline.com/column/67/article/2049 11 Boys’ Own Brexit 1 Stuart Jeffries, The Guardian, 26 May 2014. 2 http://www.dulwich.org.uk/college/about/history 3 http://www.telegraph.co.uk/news/politics/ukip/11291050/Nigel-Farage-and-Enoch-Powell-the-full-story-of-Ukips-links-with-the-Rivers-of-Blood-politician.html 4 https://www.channel4.com/news/nigel-farage-ukip-letter-school-concerns-racism-fascism 5 Michael Crick, Channel 4 News, 19 September 2013. 6 http://www.independent.co.uk/news/uk/politics/nigel-farage-open-letter-schoolfriend-brexit-poster-nazi-song-dulwich-college-gas-them-all-a7185336.html 7 http://www.independent.co.uk/news/uk/politics/nigel-farage-fascist-nazi-song-gas-them-all-ukip-brexit-schoolfriend-dulwich-college-a7185236.html 8 Interview with the author at Dulwich College, 12 January 2018. 9 www.facebook.com/myiannopuolos, accessed 24 January 2018. 10 https://www.linkedin.com/in/sam-farage-85b406b2; http://www.telegraph.co.uk/news/politics/nigel-farage/11467039/Nigel-Farage-My-public-school-had-a-real-social-mix-but-now-only-the-mega-rich-can-afford-the-fees.html 11 Simon Kupar, Financial Times, 7 July 2016. 12 http://www.telegraph.co.uk/news/2017/01/05/project-fear-brexit-predictions-flawed-partisan-new-study-says/; http://www.telegraph.co.uk/news/2016/06/25/how-project-fear-failed-to-keep-britain-in-the-eu--and-the-signs/ 13 Odey declined to be interviewed. 14 Sunday Times, 23 April 2017, p. 4; http://www.independent.co.uk/news/uk/politics/brexit-leave-eu-campaign-arron-banks-jeremy-hosking-five-uk-richest-businessmen-peter-hargreaves-a7699046.html 15 https://inews.co.uk/news/technology/cambridge-analytica-facebook-data-protection/ 16 http://www.bbc.co.uk/news/technology-43581892 17 https://inews.co.uk/news/technology/cambridge-analytica-facebook-data-protection/ 18 https://www.reuters.com/article/us-facebook-cambridge-analytica-leave-eu/what-are-the-links-between-cambridge-analytica-and-a-brexit-campaign-group-idUSKBN1GX2IO 19 https://www.theguardian.com/uk-news/2018/mar/24/aggregateiq-data-firm-link-raises-leave-group-questions https://www.businesstimes.com.sg/government-economy/brexit-campaigners-breached-uk-vote-rules-lawyers-say 20 https://dominiccummings.com/2016/10/29/on-the-referendum-20-the-campaign-physics-and-data-science-vote-leaves-voter-intention-collection-system-vics-now-available-for-all/ 21 A Very British Coup, BBC2, 22 Sepptember 2016. 22 http://www.standard.co.uk/business/business-focus-the-billionaire-hedge-fund-winners-who-braved-the-brexit-rollercoaster-a3284101.html 23 http://fortune.com/2014/12/03/heineken-charlene-de-carvalho-self-made-heiress/ 24 http://www.cityam.com/262239/david-camerons-ex-adviser-daniel-korski-launches-major 25 Tim Shipman, All Out War: Brexit and the Sinking of Britain’s Political Class (London: William Collins, 2017), p. 610. 12 For the Few, Not the Many 1 http://www.telegraph.co.uk/news/politics/Jeremy_Corbyn/11818744/Jeremy-Corbyn-the-boy-to-the-manor-born.html 2 http://www.castlehouseschool.co.uk/about-the-school/fees/ 3 Rosa Prince, Comrade Corbyn: A Very Unlikely Coup (London: Biteback Publishing, 2017), p. 29.

…

The company had even undertaken counter-terror operations on behalf of Britain’s Ministry of Defence and in 2015 secured a $750,000 contract to help NATO states in the Baltic counter Russian propaganda.16 At the height of their success the Oakes brothers decided to set up another company, Cambridge Analytica (CA), which would specialise in winning elections. The brothers teamed up with a third Etonian, Alexander Nix, who became CA’s chief executive. (It was the smooth-talking Nix who was later caught in a Channel 4 undercover reporting sting where he was recorded offering a range of dirty tricks to discredit a political candidate.)

…

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.

Tools and Weapons: The Promise and the Peril of the Digital Age by Brad Smith, Carol Ann Browne

"World Economic Forum" Davos, Affordable Care Act / Obamacare, AI winter, air gap, airport security, Alan Greenspan, Albert Einstein, algorithmic bias, augmented reality, autonomous vehicles, barriers to entry, Berlin Wall, Big Tech, Bletchley Park, Blitzscaling, Boeing 737 MAX, business process, call centre, Cambridge Analytica, Celtic Tiger, Charlie Hebdo massacre, chief data officer, cloud computing, computer vision, corporate social responsibility, data science, deep learning, digital divide, disinformation, Donald Trump, Eben Moglen, Edward Snowden, en.wikipedia.org, Hacker News, immigration reform, income inequality, Internet of things, invention of movable type, invention of the telephone, Jeff Bezos, Kevin Roose, Laura Poitras, machine readable, Mark Zuckerberg, minimum viable product, national security letter, natural language processing, Network effects, new economy, Nick Bostrom, off-the-grid, operational security, opioid epidemic / opioid crisis, pattern recognition, precision agriculture, race to the bottom, ransomware, Ronald Reagan, Rubik’s Cube, Salesforce, school vouchers, self-driving car, Sheryl Sandberg, Shoshana Zuboff, Silicon Valley, Skype, speech recognition, Steve Ballmer, Steve Jobs, surveillance capitalism, tech worker, The Rise and Fall of American Growth, Tim Cook: Apple, Wargames Reagan, WikiLeaks, women in the workforce

Grace Halden, Three Mile Island: The Meltdown Crisis and Nuclear Power in American Popular Culture (New York: Routledge, 2017), 65. Back to note reference 13. Julia Carrie Wong, “Mark Zuckerberg Apologises for Facebook’s ‘Mistakes’ over Cambridge Analytica,” Guardian, March 22, 2018, https://www.theguardian.com/technology/2018/mar/21/mark-zuckerberg-response-facebook-cambridge-analytica. Back to note reference 14. See Shoshana Zuboff, The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power (New York: PublicAffairs, 2019). Back to note reference 15. Julie Brill, “Millions Use Microsoft’s GDPR Privacy Tools to Control Their Data — Including 2 Million Americans,” Microsoft on the Issues (blog), Microsoft, September 17, 2018, https://blogs.microsoft.com/on-the-issues/2018/09/17/millions-use-microsofts-gdpr-privacy-tools-to-control-their-data-including-2-million-americans/.

…

As a result of the calamity, and unlike in other countries, the political fallout from Three Mile Island stopped American nuclear power construction in its tracks. It would take thirty-four years before construction would start on another nuclear power plant in the United States.13 I felt this was a historical lesson to learn from rather than repeat. In March 2018, the privacy equivalent of Three Mile Island arrived when the Cambridge Analytica controversy exploded. Facebook users learned that their personal data had been harvested by the political consulting firm to build a database targeting US voters with advertisements designed to support Donald Trump’s presidential campaign. While the usage itself violated Facebook’s policies, the company’s compliance systems had failed to detect the problem.

…

It helped fuel a public movement across the country that added momentum to Ronald Reagan’s Presidential election in 1980 and stronger national pressure to reduce the size of government and cut taxes. It created a watershed political moment, reflecting in part the fact that one in every eight Americans lives in California. If Cambridge Analytica could become the equivalent of Three Mile Island, could Alastair Mactaggart create the privacy equivalent of Proposition 13? It quickly seemed likely that the answer was yes. Mactaggart gathered more than double the signatures needed to put the measure on the ballot. His polling said that 80 percent of voters started out supportive of his proposal.

How Democracy Ends by David Runciman

barriers to entry, basic income, Bernie Sanders, Big Tech, bitcoin, blockchain, Brexit referendum, Cambridge Analytica, Capital in the Twenty-First Century by Thomas Piketty, centre right, crowdsourcing, cuban missile crisis, disinformation, Dominic Cummings, Donald Trump, Dr. Strangelove, Edward Snowden, fake news, first-past-the-post, Francis Fukuyama: the end of history, full employment, Internet of things, Jeremy Corbyn, Jon Ronson, Joseph Schumpeter, Kickstarter, Large Hadron Collider, loss aversion, Mahatma Gandhi, Mark Zuckerberg, money: store of value / unit of account / medium of exchange, mutually assured destruction, Network effects, Nick Bostrom, Norman Mailer, opioid epidemic / opioid crisis, Panopticon Jeremy Bentham, Paris climate accords, Peter Thiel, post-truth, power law, precautionary principle, quantitative easing, Russell Brand, self-driving car, Sheryl Sandberg, Silicon Valley, Steve Bannon, Steven Pinker, the long tail, The Wisdom of Crowds, Travis Kalanick, universal basic income, Yogi Berra

A sophisticated political news operation could ensure that elections become a version of price-fixing: we only get to see what they already know we are willing to buy. The election of Trump and the Brexit vote in the UK were both accompanied by scare stories of this kind. A mysterious firm called Cambridge Analytica, funded by some prominent Trump supporters, appeared to be in the business of supplying information about individual voters based on their online identities. News feeds could be targeted accordingly. It is hard to know if it made any difference. But the margin of Trump’s victory was sufficiently narrow – tens of thousands of voters in a few key states – to suggest that it just might have.

…

Bots that are very bad at impersonating human intelligence can still be very good at impersonating angry voters. All they have to do is make a lot of noise. Unquestionably there are serious risks to democracy here. But for now they may be overblown. The micro-manipulation of the electorate is almost certainly more difficult than it looks – a lot of what Cambridge Analytica is selling is simply hot air. We have a tendency to overstate the ease with which bad people can perform fiendishly complicated tasks. Fixing an election has always been hard work. Nerds tend to worry about James Bond villains taking over the world. But very few James Bond villains are actually nerds.

…

First radio and then television changed the terms of the metaphor. The underlying idea did not alter much. They produce the politics; we consume it. Elections are the final test of which product will sell, and fortunes have been made and lost providing politicians with a service to help them negotiate that marketplace. Are firms like Cambridge Analytica doing anything different? In one sense, no: this is just the latest version of the never-ending contest to see who is better at putting lipstick on the pig. But in another sense, something has fundamentally changed. Twentieth-century political salesmanship followed a distinctive rhythm. The goal was to close the deal at election time.

The AI Economy: Work, Wealth and Welfare in the Robot Age by Roger Bootle

"World Economic Forum" Davos, 3D printing, agricultural Revolution, AI winter, Albert Einstein, AlphaGo, Alvin Toffler, anti-work, antiwork, autonomous vehicles, basic income, Ben Bernanke: helicopter money, Bernie Sanders, Bletchley Park, blockchain, call centre, Cambridge Analytica, Capital in the Twenty-First Century by Thomas Piketty, Carl Icahn, Chris Urmson, computer age, Computing Machinery and Intelligence, conceptual framework, corporate governance, correlation does not imply causation, creative destruction, David Ricardo: comparative advantage, deep learning, DeepMind, deindustrialization, Demis Hassabis, deskilling, Dr. Strangelove, driverless car, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, everywhere but in the productivity statistics, facts on the ground, fake news, financial intermediation, full employment, future of work, Future Shock, general purpose technology, Great Leap Forward, Hans Moravec, income inequality, income per capita, industrial robot, Internet of things, invention of the wheel, Isaac Newton, James Watt: steam engine, Jeff Bezos, Jeremy Corbyn, job automation, job satisfaction, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Joseph Schumpeter, Kevin Kelly, license plate recognition, low interest rates, machine translation, Marc Andreessen, Mark Zuckerberg, market bubble, mega-rich, natural language processing, Network effects, new economy, Nicholas Carr, Ocado, Paul Samuelson, Peter Thiel, Phillips curve, positional goods, quantitative easing, RAND corporation, Ray Kurzweil, Richard Florida, ride hailing / ride sharing, rising living standards, road to serfdom, Robert Gordon, Robert Shiller, Robert Solow, Rutger Bregman, Second Machine Age, secular stagnation, self-driving car, seminal paper, Silicon Valley, Silicon Valley billionaire, Simon Kuznets, Skype, social intelligence, spinning jenny, Stanislav Petrov, Stephen Hawking, Steven Pinker, synthetic biology, technological singularity, The Future of Employment, The Wealth of Nations by Adam Smith, Thomas Malthus, trade route, universal basic income, US Airways Flight 1549, Vernor Vinge, warehouse automation, warehouse robotics, Watson beat the top human players on Jeopardy!, We wanted flying cars, instead we got 140 characters, wealth creators, winner-take-all economy, world market for maybe five computers, Y2K, Yogi Berra

Facebook and some other tech firms exist solely to gather and sell everyone’s data, exposing users’ lives in increasingly more granular detail.”22 There was a recent scandal involving the company Cambridge Analytica, which took data from Facebook and allegedly used it to try to influence voter opinion. A Facebook app, produced by a Cambridge University academic outside his work at Cambridge, collected data on around 87 million Facebook users.23 The company was then able to develop “sophisticated psychological profiling and personalization algorithms.”24 Politicians could then hire the company to try to influence voter opinion. Cambridge Analytica’s managing director told an undercover reporter that “it’s no good fighting an election campaign on the facts.”

…

., p. 18. 20 For an analysis of these issues, see (2017) Data Management and Use: Governance in the Twenty-first Century, London: British Academy and the Royal Society, https:/​/​royalsociety.​org/​~/​media/​policy/​projects/​data-governance/​data-management-governance.​pdf. 21 Globe editorial (2018) When tech companies collect data, bad things can happen, January 30, https:/​/​www.​theglobeandmail.​com/​opinion/​editorials/​globe-editorial-when-tech-companies-collect-data-bad-things-can-happen/​article37798038/​ 22 Baker, P. (2018) Reining In Data-Crazed Tech Companies, April 16, https:/​/​www.​ecommercetimes.​com/​story/​85278.​html 23 Solon, O. (2018) Facebook says Cambridge Analytica may have gained 37m more users data, The Guardian, April 4, https:/​/​www.​theguardian.​com/​technology/​2018/​apr/​04/​facebook-cambridge-analytica-user-data-latest-more-than-thought 24 Frischmann, B. (2018) Here’s why tech companies abuse our data: because we let them, The Guardian, April 10, https:/​/​www.​theguardian.​com/​commentisfree/​2018/​apr/​10/​tech-companies-data-online-transactions-friction 25 Stucke, M.

…

Typically, although the founders have become mega-rich by selling stakes in what they have created, they retain control. The 2012 presidential campaign by Barack Obama used machine learning and big data. As a result, the campaign was “highly successful in not only mobilizing, but also convincing voters to give Obama their support.”37 Then, during the 2016 US presidential election, the firm Cambridge Analytica used big data and machine learning to send voters different messages based on predictions about their susceptibility to different arguments.38 Another issue that has emerged recently is the use of fake news to influence election campaigns, arguably preventing a “fair” election. While “fake news” has to some extent always existed, social media and machine learning “allow fake news to be spread more deliberately and effectively.”39 Bots are often effective at targeting supporters of opposing parties and discouraging them from voting.

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.

…

., 176 Bush, Vannevar ‘As We May Think,’ 23–4 Bush Differential Analyser, 27 on hypertext, 79 Bush Differential Analyser, 27 Byron “Darkness,” 201–2 C Cadwalladr, Carole, 236 calculating machines, 27 calculation p-hacking, 89–91 raw computing, 82–3 replicability, 88–9 translation algorithms, 84 Cambridge Analytica, 236 Campbell, Duncan, 189 ‘Can We Survive Technology?’ (von Neumann), 28 Capital in the Twenty-First Century (Piketty), 112 carbon dioxide, 75 Catch-22 (Heller), 187–8 ‘cautious regulator’ theory, 94–5 CCTV, 181–2 centaur chess, 159 Chanarin, Oliver, 143 chaotic storage, 115–6 Chargaff, Erwin, 96–7 Charlie Hebdo attacks, 212 chemtrails, 192–5, 206–8, 214 children’s television, 216–7 children’s YouTube, 219, 238 Cirrus homogenitus, 196, 197 Civil Aviation Authority (CAA), 161–2 clear-air turbulence, 68 climate carbon dioxide, 75 global warming, 73, 193, 214 permafrost, 47–9, 56–7 seed banks, 52–6 turbulence, 65–9 climate change patterns disrupted by, 72–3 resilience against, 59 climate crisis, 56 Clinton, Bill, 243 Clinton, Hillary, 207, 232–3 cloning, 86–8 closed-circuit television, 181–2 cloud(s), 6–7, 8, 17, 195–6 ‘The Cloud Begins with Coal-Big Data, Big Networks, Big Infrastructure, and Big Power’ report, 64 ‘The Cloud of Unknowing,’ 9 cloudy thinking, 9 coal deposits, discovery of, 52 coastal installations, 62 Cocks, Clifford, 167 code/spaces, 37–9 code words, 175 cognition about, 135–6 artificial intelligence (AI), 139 facial recognition, 141 image recognition, 139–40 machine translation, 147 ‘predictive policing’ systems, 144–6 collectivism, totalitarianism vs., 139 Commission on Government Secrecy, 169 complex systems about, 2–3 aggregation of, 40 high-frequency trading, 14, 106–7, 108, 122, 124 complicity computational logic, 184–5 Freedom of Information, 161–2, 165, 192 global mass surveillance, 179–80 Glomar response, 165, 186 public key cryptography, 167–8 computation calculating machines, 27 Electronic Numerical Integrator and Computer (ENIAC), 27, 27–30, 33 flight trackers, 35–6, 36 IBM Selective Sequence Electronic Calculator (SSEC), 30, 30–2, 31, 146 opaqueness of, 40 computational logic, 184–5 computational thinking about, 4 evolution of, 248 importance of, 44–5 Concorde, 69, 70, 71 conspiracy chemtrails, 192–5, 206–8, 214 conspiracy theories, 195, 198–9, 205 contrails, 196–8, 197, 214 global warming, 73, 193, 214 9/11 terrorist attacks, 203–4, 206 ‘Conspiracy as Governance’ (Assange), 183 contrails, 196–8, 197, 214 Copenhagen Climate Change Conference (COP15), 199 Cowen, Deborah, 132 Credit Suisse, 109 cryptocurrency, 63 Cumulus homogenitus, 195–6 cyborg chess, 159 D Dabiq (online magazine), 212 Dallaire, Roméo, 243 darkness, 11–2 “Darkness” (poem), 201–2 dark pools, 108–9 DARPA (Defense Advanced Research Projects Agency), 33 Darwin, Charles, 78 data abundance of, 83–4, 131 big, 84 importance of, 245–6 realistic accounting of, 247 thirst for, 246 data dredging, 90–1 Debord, Guy, 103 DEC (Digital Equipment Corporation), 33 Decyben SAS, 110 Deep Blue, 148–9, 157–60 DeepDream, 153, 154–5 DeepFace software, 140 defeat devices, 120 Defense Advanced Research Projects Agency (DARPA), 33 de Solla Price, Derek, 91–2, 93 Diffie-Hellman key exchange, 167 digital culture, 64–5 Digital Equipment Corporation (DEC), 33 digital networks, mapping, 104 digitisation, 108 ‘Discussion of the Possibility of Weather Control’ lecture, 26 diurnal temperature range (DTR), 204 DNA sequencing, 93 D-Notices, 179 domain name system, 79 doomsday vault, 52–3 Dow Jones Industrial Average, 121–2 drones, 161–2 drug discovery/research, 94–5 DTR (diurnal temperature range), 204 Duffy, Carol Ann, 201 Dunne, Carey, 194–5 E Elberling, Bo, 57 electromagnetic networks, 104 Electronic Computer Project, 27 Electronic Frontier Foundation, 177 Electronic Numerical Integrator and Computer (ENIAC), 27, 27–30, 33 Elements of Chemistry (Lavoisier), 208–9 Elkins, Caroline, 183–4 Ellis, James, 167 encoded biases, 142 ‘End of Theory’ (Anderson), 83–4, 146 Engelbart, Douglas, 79 ENIAC (Electronic Numerical Integrator and Computer), 27, 27–30, 33 Enlightenment, 10 Environmental Protection Agency (EPA), 119–20 EPA (Environmental Protection Agency), 119–20 Epagogix, 130 epidemic type aftershock sequence (ETAS) model, 145–6 Epimetheus, 132–4 Equinix LD4, 104 Eroom’s law, 86, 93–6 ETAS (epidemic type aftershock sequence) model, 145–6 Euronext Data Center, 104, 105, 106 Evangelismos Hospital, 130–1 evolution, theory of, 78 exploitation, 229–30 Eyjafjallajökull, eruption of, 200–1, 202 F Facebook, 39–40, 156–7 facial recognition, 141 Fairchild Semiconductor, 80 Farage, Nigel, 194 Fat Man bomb, 25 Fermi, Enrico, 250 Ferranti Mark I, 78 fiat anima, 19–20 fiat lux, 19–20 Finger Family, 221–2, 224, 227 ‘Five Eyes,’ 174 Flash Boys (Lewis), 111–2 flash crash, 121–2, 130–1 FlightRadar24, 36, 189, 191 flight trackers, 35–6, 36 ‘Fourteen Eyes,’ 174 Fowler, R.H., 45 Frankenstein (Shelley), 201 fraud, 86–8, 91 Freedom of Information, 161–2, 165, 192 Friends’ Ambulance Unit, 20 Fuller, Buckminster, 71 Futurama exhibit, 30–1 ‘Future Uses of High Speed Computing in Meteorology’ lecture, 26 G Gail, William B., 72–3 Galton, Francis, 140 game developers, 130 Gates’s law, 83 GCHQ (Government Communications Headquarters), 167, 174, 176–9, 189 genocide, 243 ghost cars (Uber), 118–9 G-INFO, 190 global mass surveillance, 179–80 Global Positioning System (GPS), 36–7, 42–3 Global Seed Vault, 54 global warming, 73, 193, 214 Glomar response, 165, 186 Godard, Jean-Luc, 143 Google, 84, 139, 230, 242 Google Alerts, 190 Google Brain project, 139, 148, 149, 156 Google Earth, 35–6 Google Home, 128–9 Google Maps, 177 Google Translate, 147–8, 156 Government Communications Headquarters (GCHQ), 167, 174, 176–9, 189 GPS (Global Positioning System), 36–7, 42–3 Graves, Robert, 159 Gravity’s Rainbow (Pynchon), 128 gray zone, 212–4 Great Nōbi Earthquake, 145 Greenland, 57–8 Green Revolution, 53 Greyball programme, 119, 120 guardianship, 251–2 H Hankins, Thomas, 102 Haraway, Donna, 12 Harvard Mark I machine, 30 Hayek, Friedrich, 156–7 The Road to Serfdom, 139 The Sensory Order: An Inquiry into the Foundations of Theoretical Psychology, 138–9 HealthyFoodHouse.com (website), 231–2 Heller, Joseph Catch-22, 187–8 Hermes, 134 Hersh, Seymour, 164 Hewlett-Packard, 143 hidden technological processes, 120 high-frequency trading, 14, 106–7, 108, 122, 124 high-throughput screening (HTS), 95–6 Hillingdon Hospital, 110–1, 111 Hippo programme, 32 Hofstadter, Douglas, 205–6 Hola Massacre, 170 homogenitus, 195, 196 Horn, Roni, 50, 201 How-Old.net facial recognition programme, 141 ‘How the World Wide Web Just Happened’ lecture, 78 HTS (high-throughput screening), 95–6 Hughes, Howard, 163 Hughes Glomar Explorer, 163–5 human genome project, 93 Human Interference Task Force, 251 human violence, 202 Humby, Clive, 245, 246 Hwang Woo-suk, 86–8 hyperobjects, 73, 75, 76, 194 hypertext, 79 I IBM Selective Sequence Electronic Calculator (SSEC), 30, 30–2, 31, 146 ICAO (International Civil Aviation Organisation), 68 ICARDA (International Center for Agricultural Research in the Dry Areas), 53–4, 55 ICT, 60–2 image recognition, 139–40 Infinite Fun Space, 149–50, 156 information networks, 62 information superhighway, 10 Infowars (Jones), 207 In Place of Fear (Bevan), 110 Institute of the Aeronautical Sciences, 26 integrated circuits, 79, 80 Intel, 80 International Center for Agricultural Research in the Dry Areas (ICARDA), 53–4, 55 International Civil Aviation Organisation (ICAO), 68 International Cloud Atlas, 195 Internet Research Agency, 235, 237 Inuit Knowledge and Climate Change, 199 The Invisibles (Morrison), 196–7 Isaksen, Ketil, 54 ISIL, 212–3 J Jameson, Fredric, 205 Jelinek, Frederick, 146–7 Jones, Alex Infowars, 207 Joshi, Manoj, 68–9 journalism, automated, 123–4 just-in-time manufacturing, 117 K K-129, 162–3 Karma Police operation, 175 Kasparov, Garry, 148–9, 157–8 Keeling Curve, 74, 74 Kennedy, John F., 169–70 Kinder Eggs, 215–6 Kiva robots, 114 Klein, Mark, 176–7 Kodak, 143 Krakatoa, eruption of, 202 Kunuk, Zacharias, 199, 200 Kuznets curve, 113 L Large Hadron Collider, 93 Lavoisier, Antoine, 78 Elements of Chemistry, 208–9 Lawson, Robert, 175–6 LD4, 104, 105 Leave Campaign, 194 Leibniz, Gottfried Wilhelm, 78 Levy, David, 158, 159 Lewis, Michael Flash Boys, 111–2 LifeSphere, 125 literacy in systems, 3–4 Lockheed Ocean Systems, 163 Logan, Walt (pseudonym), 165 Lombroso, Cesare, 140 London Stock Exchange, 110–1 Lovecraft, H.P., 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?

The Great Firewall of China by James Griffiths;

A Declaration of the Independence of Cyberspace, activist fund / activist shareholder / activist investor, Albert Einstein, anti-communist, bike sharing, bitcoin, Black Lives Matter, borderless world, call centre, Cambridge Analytica, Chelsea Manning, Citizen Lab, Deng Xiaoping, digital divide, digital rights, disinformation, don't be evil, Donald Trump, Edward Snowden, end-to-end encryption, Evgeny Morozov, fake news, gig economy, Great Leap Forward, high-speed rail, jimmy wales, John Gilmore, John Perry Barlow, Mark Zuckerberg, megacity, megaproject, microaggression, Mikhail Gorbachev, Mitch Kapor, mobile money, Occupy movement, pets.com, profit motive, QR code, race to the bottom, RAND corporation, ride hailing / ride sharing, Ronald Reagan, Silicon Valley, Silicon Valley startup, Skype, Snapchat, South China Sea, Steve Jobs, Stewart Brand, Stuxnet, technoutopianism, The future is already here, undersea cable, WikiLeaks, zero day

Wu, ‘Former cybersecurity head who sought “personal fame” expelled from Party’, Caixin, 13 February 2018, https://www.caixinglobal.com/2018-02-13/former-cybersecurity-head-who-sought-personal-fame-expelled-from-party-101211314.html 15C. Cadwalladr and E. Graham-Harrison, ‘Revealed: 50 million Facebook profiles harvested for Cambridge Analytica in major data breach’, The Guardian, 17 March 2018, https://www.theguardian.com/news/2018/mar/17/cambridge-analytica-facebook-influence-us-election 16D. Lux, ‘Facebook’s hate speech policies censor marginalized users’, Wired, 14 August 2017, https://www.wired.com/story/facebooks-hate-speech-policies-censor-marginalized-users/; J. Angwin and H. Grassegger, ‘Facebook’s secret censorship rules protect white men from hate speech but not black children’, Pro Publica, 28 June 2017, https://www.propublica.org/article/facebook-hate-speech-censorship-internal-documents-algorithms; C.

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In a statement, China’s corruption watchdog said that Lu “did whatever he wanted, commenting on central government policies with bias and distortion, obstructing central government investigations, with his growing ambition he used public tools for personal interests and did whatever it took for personal fame”.14 Lu’s downfall was only the beginning of Facebook’s problems in 2018, as the company was also buffeted by revelations that Cambridge Analytica, a political consulting firm, had harvested the data of millions of users, helped by the social platform’s woeful privacy protections.15 That scandal came on the back of continuing concerns over fake news, of which Facebook users were among the biggest consumers and spreaders, further damaging the company’s public image and users’ confidence in the tech giants to protect them.

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Even those who have been censored by these platforms admit to still using them, as the costs and difficulties of not doing so are so great.25 This is even more the case in much of the developing world, where Facebook, for many users, is the internet. “If you pulled the plug on Facebook, there would literally be riots in the streets,” Antonio García Martínez, a former Facebook advertising executive told New York Magazine in the wake of the Cambridge Analytica scandal. “So in the back of Facebook’s mind, they know that they’re stepping on people’s toes. But in the end, people are happy to have the product, so why not step on toes?”26 As journalist Mark Scott has written, “tough calls will have to be made between free speech and online safety, and elected officials, not opaque tech companies, must be the ones to judge what content crosses the line.

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

They also defend notions of national supremacy and sovereignty while, somewhat ironically, meddling in foreign elections and referendums. Investigative work by the British reporter Carole Cadwalladr unearthed the connections proving that Cambridge Analytica, a firm then partly owned by Mercer, provided ongoing assistance to Leave campaigners during Britain’s EU referendum vote. ‘In-kind’ support provided by Cambridge Analytica should have been declared to UK regulators but was not. Cadwalladr made this point to Leave.eu co-founder Aaron Banks, whose reply was curt: ‘I don’t give a monkey’s about the Electoral Commission.’9 Speaking to Cadwalladr, individual staff at the Electoral Commission expressed anger at their Commission’s impotency when it came to punishing infringements of electoral rules: penalties permitted by law are so minor they ‘offered no deterrent to political parties.’

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INDEX Ackerman, Spencer, 91 agnotology, 11, 29–30, 39, 188–9, 221 Andrews, Samuel, 210–11 antidepressants: dosage level concerns, 283–5; FDA black box warning, 288; FDA investigations, 281, 287–8; information dissemination, 285–6; lack of effectiveness for children, 250, 251–2; MHRA reviews, 282–6; off-label prescribing for children, 250–1, 292; patient information labels, 281, 282; popularity, 280, 290; suicide and other side effects, 280–1, 282, 287–90; unpublished trials data, 250, 281, 286–7 Arendt, Hannah, 45, 62, 179, 220–1, 309 Arthur Anderson, 235 auditors, 234–5 Aventis, 269–77 Bacevich, Andrew, 13–14, 68–9 Bachelet, Michelle, 221–2 Bain, Alexander, 159–60 banks, corporate ignorance, 120 Bannon, Stephen, 34–5, 87, 93–4, 175 Barings, 120 Bassel, Leah, 59 Bastiat, Frédéric, 168, 200–1 Bentham, Jeremy, 8, 37, 155, 299 Bernanke, Ben, 55 Bignell, Paul, 32 black Americans, 196, 237, 238, 241 Black, Eugene, 219 Blair, Tony, 31–2 Blankfein, Lloyd, 76–7 Brandeis, Louis, 65 Breitbart, 34, 85–6 Brennan, Jason, 93–4, 95–6, 243; Against Democracy, 66–7, 96 Brexit vote: Cambridge Analytica Leave campaign assistance, 86; half-truths, 89–90; Leave campaign claims, 30–1; and low-income voters, 19; support from wealthy, 90; supposed ignorance of leave voters, 82–3, 89–90, 162; voter turnout, 31 Briggs, Asa, 159–60 Brink, André, A Dry White Season, 268–9 Britain, nation of shopkeepers, 192 Brook, Richard, 283–5, 295 Brooks, Rebekah, 100, 103, 113–14 Buchanan, James, 246–7 Buffett, Warren, 55, 67 Burke, Edmund, 9, 317; background, 148; condemnation of French Revolution, 149–51, 182; and the divine, 77; and East India Company, 10, 122, 175, 176, 180–1; government regulation, 20–1; Warren Hastings prosecution, 180, 182 Bush, George W., 72–3 business: collusion, 141–2; economics teaching, 205, 215–16, 304; government intervention, 43; labour practices, 13; preoccupation with self-interest, 139–40; strategic ignorance, 20; useful unknowns, 51–6, 277; see also regulation business schools, 118–19 Cadwalladr, Carole, 86 Calais Jungle, 1–3 Cambridge Analytica, 86 Cambridge University, 67–8 Canada: indigenous groups, 26–9, 58; mining companies, 185, 222–4 Carnegie, Andrew: belief in self-made competitive success, 205, 214; beneficiary of laissez-faire business practices, 205–6; beneficiary of steel industry tariffs, 206, 210; deception and lies, 207, 209; Edgar Thomson strike, 208; master of ignorance, 20; philanthropy, 204; professed support for workers’ rights, 207–8, 210, 215; stock market trading, 206–7; strategic ignorance of Homestead crisis, 208–10, 214 Carpenter, Daniel, 263–4, 265 Carter, Zachary, 217, 236 Caryatid Operation, 112–14 Chandler, Alfred, The Visible Hand, 195 Chang, Ha-Joon, 187–8 Chernow, Ron, 211, 212, 213–14 Chicago, meat plants, 255 Chicago School, 246–7, 300, 303 children: Canada’s indigenous children, 27, 58; family reunions, 2–3; obesity, 51–2, 65; see also antidepressants Chile, 221–2 Cisneros, Ann Marie, 271–2, 274 Clark, John Bates, 133–4 Clark, Maurice, 210–11 Clinton Foundation, 87 Clive, Robert, 177–8, 179, 205 Cobain, Ian, The History Thieves, 42 Coca-Cola, 51–2, 65 Cohen, Stanley, 57 colonialism: Britain’s defence of American colonies, 191–2; and Canada’s indigenous groups, 26–9; destruction/falsification of files, 42, 58; in India, 44; indigenous rights, 28–9; see also East India Company confirmation bias, 37–8, 151 conscription, 14–15 contingency, 6 corporate veil, 46, 222–3, 311–12 Coulson, Andy, 102–3, 113 credibility deficits/excess, 25–6, 77 Dalrymple, William, 177, 178 Daschuk, James, Clearing the Plains, 26–7 Davies, Nick, 103–6 Davies, Sharon, 239–40 The Dearborn Independent, 79–81 deaths, workplace, 218, 219, 238 democracy: choice by algorithm, 66–7; and disenfranchisement, 16, 66, 70, 96, 156, 174; epistemological strengths, 297–8; Greek democracy, 296–7; low-income voters, 19, 78; male enfranchisement, 42; online campaign infringements, 86; see also voter ignorance Deng, Wendi, 101 denial, 56, 57, 120 Dewdney, Edgar, 28 disenfranchisement, 16, 66, 70, 96, 156, 174 displaced people, 202–3 divine providence, 67–9, 174, 176, 318–19, 322–4 Dobbin, Frank, 194–5 Dowd, Timothy, 194–5 Dower, John, 202–3 Dowler, Milly, 19, 100 Downs, Anthony, 46 drone strikes, 91–2 drug trials: Ketek, 271–2, 274–7; testing methods, 264–7; Vioxx, 262; Vioxx/naproxen, 259–60 drugs: naproxen, 259–60; patient information labels, 273, 281, 282; rare adverse effects, 265–7; rational response to adverse effects, 266–7; Thalidomide, 254, 256–8; Vioxx, 258–62, 269, 270; see also antidepressants; Ketek Dunlavy, Colleen, 194 East India Company: monopoly privileges, 128–9, 145; parliamentary accountability efforts, 175, 176, 179, 180–1; public-private hybrid, 176–7, 178; state protection, 5; tax collection, 178; territorial control, 177–8; treatment of Indians, 10, 122, 127, 161, 176, 180; wealth extraction, 178, 180 economic justice, 174–5, 184–6 economics teaching, 205, 215–16, 304 Economist, 165, 171 Eden, Anthony, 31 Edgar Thomson steel works strike, 208 Eli Lilly, 280 elite ignorance, 18–19, 41, 43, 90–4, 160–1, 166; see also epistocracy; wealth Elliot, Larry, 34 Emejulu, Akwugo, 59 Enlightenment, 9, 148, 150, 173, 175, 183, 186 Enron, 21–2, 230–1, 234–5 environmental groups, 3–4 epistocracy, 17, 93, 95–6, 163, 165, 267–70 equal culpability thesis, 233–5 Eritrea, Bisha Mining, 223–4 Ernst, David, 261 expert ignorance, 24–5, 33–4, 64–6, 266–70, 275–7, 295 experts, not necessarily better leaders, 97 Exxon Mobil, 214 fake news, 79–81, 88–90 FDA see Food and Drug Administration (FDA) Federal Reserve Board, 53–4, 55 feminist theory, 317–18 financial advisors, 67 financial crisis (2007-8), 33, 52–6, 306–8 Fitzgerald, F.

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., 72–3 business: collusion, 141–2; economics teaching, 205, 215–16, 304; government intervention, 43; labour practices, 13; preoccupation with self-interest, 139–40; strategic ignorance, 20; useful unknowns, 51–6, 277; see also regulation business schools, 118–19 Cadwalladr, Carole, 86 Calais Jungle, 1–3 Cambridge Analytica, 86 Cambridge University, 67–8 Canada: indigenous groups, 26–9, 58; mining companies, 185, 222–4 Carnegie, Andrew: belief in self-made competitive success, 205, 214; beneficiary of laissez-faire business practices, 205–6; beneficiary of steel industry tariffs, 206, 210; deception and lies, 207, 209; Edgar Thomson strike, 208; master of ignorance, 20; philanthropy, 204; professed support for workers’ rights, 207–8, 210, 215; stock market trading, 206–7; strategic ignorance of Homestead crisis, 208–10, 214 Carpenter, Daniel, 263–4, 265 Carter, Zachary, 217, 236 Caryatid Operation, 112–14 Chandler, Alfred, The Visible Hand, 195 Chang, Ha-Joon, 187–8 Chernow, Ron, 211, 212, 213–14 Chicago, meat plants, 255 Chicago School, 246–7, 300, 303 children: Canada’s indigenous children, 27, 58; family reunions, 2–3; obesity, 51–2, 65; see also antidepressants Chile, 221–2 Cisneros, Ann Marie, 271–2, 274 Clark, John Bates, 133–4 Clark, Maurice, 210–11 Clinton Foundation, 87 Clive, Robert, 177–8, 179, 205 Cobain, Ian, The History Thieves, 42 Coca-Cola, 51–2, 65 Cohen, Stanley, 57 colonialism: Britain’s defence of American colonies, 191–2; and Canada’s indigenous groups, 26–9; destruction/falsification of files, 42, 58; in India, 44; indigenous rights, 28–9; see also East India Company confirmation bias, 37–8, 151 conscription, 14–15 contingency, 6 corporate veil, 46, 222–3, 311–12 Coulson, Andy, 102–3, 113 credibility deficits/excess, 25–6, 77 Dalrymple, William, 177, 178 Daschuk, James, Clearing the Plains, 26–7 Davies, Nick, 103–6 Davies, Sharon, 239–40 The Dearborn Independent, 79–81 deaths, workplace, 218, 219, 238 democracy: choice by algorithm, 66–7; and disenfranchisement, 16, 66, 70, 96, 156, 174; epistemological strengths, 297–8; Greek democracy, 296–7; low-income voters, 19, 78; male enfranchisement, 42; online campaign infringements, 86; see also voter ignorance Deng, Wendi, 101 denial, 56, 57, 120 Dewdney, Edgar, 28 disenfranchisement, 16, 66, 70, 96, 156, 174 displaced people, 202–3 divine providence, 67–9, 174, 176, 318–19, 322–4 Dobbin, Frank, 194–5 Dowd, Timothy, 194–5 Dower, John, 202–3 Dowler, Milly, 19, 100 Downs, Anthony, 46 drone strikes, 91–2 drug trials: Ketek, 271–2, 274–7; testing methods, 264–7; Vioxx, 262; Vioxx/naproxen, 259–60 drugs: naproxen, 259–60; patient information labels, 273, 281, 282; rare adverse effects, 265–7; rational response to adverse effects, 266–7; Thalidomide, 254, 256–8; Vioxx, 258–62, 269, 270; see also antidepressants; Ketek Dunlavy, Colleen, 194 East India Company: monopoly privileges, 128–9, 145; parliamentary accountability efforts, 175, 176, 179, 180–1; public-private hybrid, 176–7, 178; state protection, 5; tax collection, 178; territorial control, 177–8; treatment of Indians, 10, 122, 127, 161, 176, 180; wealth extraction, 178, 180 economic justice, 174–5, 184–6 economics teaching, 205, 215–16, 304 Economist, 165, 171 Eden, Anthony, 31 Edgar Thomson steel works strike, 208 Eli Lilly, 280 elite ignorance, 18–19, 41, 43, 90–4, 160–1, 166; see also epistocracy; wealth Elliot, Larry, 34 Emejulu, Akwugo, 59 Enlightenment, 9, 148, 150, 173, 175, 183, 186 Enron, 21–2, 230–1, 234–5 environmental groups, 3–4 epistocracy, 17, 93, 95–6, 163, 165, 267–70 equal culpability thesis, 233–5 Eritrea, Bisha Mining, 223–4 Ernst, David, 261 expert ignorance, 24–5, 33–4, 64–6, 266–70, 275–7, 295 experts, not necessarily better leaders, 97 Exxon Mobil, 214 fake news, 79–81, 88–90 FDA see Food and Drug Administration (FDA) Federal Reserve Board, 53–4, 55 feminist theory, 317–18 financial advisors, 67 financial crisis (2007-8), 33, 52–6, 306–8 Fitzgerald, F.

Magic Internet Money: A Book About Bitcoin by Jesse Berger

Alan Greenspan, barriers to entry, bitcoin, blockchain, Bretton Woods, Cambridge Analytica, capital controls, carbon footprint, correlation does not imply causation, cryptocurrency, diversification, diversified portfolio, Ethereum, ethereum blockchain, fiat currency, Firefox, forward guidance, Fractional reserve banking, George Gilder, inflation targeting, invisible hand, Johann Wolfgang von Goethe, liquidity trap, litecoin, low interest rates, Marshall McLuhan, Metcalfe’s law, Money creation, money: store of value / unit of account / medium of exchange, moral hazard, Network effects, Nixon shock, Nixon triggered the end of the Bretton Woods system, oil shale / tar sands, planned obsolescence, price mechanism, Ralph Waldo Emerson, rent-seeking, reserve currency, ride hailing / ride sharing, risk tolerance, Robert Metcalfe, Satoshi Nakamoto, the medium is the message, Vitalik Buterin

To wit, in a famous exchange from 2013,27 US Senator Elizabeth Warren told JP Morgan CEO, Jamie Dimon, “I think you guys are breaking the law.” To which Dimon slyly replied, “So hit me with a fine. We can afford it.” The technology sector is no different. In 2019, Facebook was fined $5 billion for personal data privacy violations related to its work with Cambridge Analytica,28 and despite many other known instances of major data leaks and abuses, violations continue mostly unabated today. 10.3 Home of the Brave “Freedom and responsibility aren’t interconnected things. They are the same thing.” Harry Browne, Writer & Politician Circumstances may have been fertile for the growth of influential third parties in the not-so-distant past, but those conditions are changing.

…

Chapter 10: Freedom 25PwC’s Global Economic Crime and Fraud Survey, “Fighting Fraud: A never-ending battle” (2020). 26See the Violation Tracker Industry Summary Page, specifying the financial services industry, produced by the Corporate Research Project of Good Jobs First at: https://violationtracker.goodjobsfirst.org/prog.php?major_industry_ sum=financial+services 27Julia La Roche, “JP Morgan CEO Jamie Dimon once told Elizabeth Warren to ‘hit’ him with a fine because the bank could ‘afford it’” Insider (March 31, 2015). 28Rob Davies and Dominic Rushe, “Facebook to pay $5bn fine as regulator settles Cambridge Analytica complaint” The Guardian (July 24, 2019). Chapter 11: Drawbacks 29Nicola Jones, “How to stop data centres from gobbling up the world’s electricity” Nature 561, pp. 163-166 (2018). 30Naomi Xu Elegant, “The Internet Cloud Has a Dirty Secret” Fortune (September 18, 2019). 31“Increased Shale Oil Production and Political Conflict Contribute to Increase in Global Gas Flaring” The World Bank online (June 12, 2019). 32Christopher Bendiksen & Samuel Gibbons, “The Bitcoin Mining Network – Trends, Composition, Average Creation Cost, Electricity Consumption & Sources” coinshares.com (December 3, 2019). 33https://digiconomist.net/bitcoin-energy-consumption Chapter 12: Outlook 34Mark Wilson, “50% of people cheat at Monopoly, so Hasbro redesigned it for them” Fast Company (May 22, 2018). 35Kirsten Acuna, “The top 10 ways fans say they cheat at Monopoly” Insider.com (January 16, 2018).

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

Facebook, which supplied the lifeblood to new digital media sites, was all about deriving ad revenue from the fast-paced social sharing of their 2.2 billion global users. Eschewing its responsibilities as mankind’s biggest publisher, Facebook would be badly tarnished after the 2016 election for sharing users’ data with a Trump-tied outfit, Cambridge Analytica, and for failing to police its platform, enabling fake-news creators in Russia to disrupt the election. All in all, it felt like a singular moment. The fate of the republic seemed to depend more than ever on access to honest, reliable information, and people were consuming more news than ever, but every news company was turning itself upside down to produce and pay for it in the digital age.

…

How carefully—or not—Facebook safeguarded the intelligence it kept on its users would become an explosive issue following the political calamities of the Brexit vote in Britain and the U.S. election in 2016. In 2018 Facebook finally admitted it had allowed more than 80 million users’ data to be collected by Cambridge Analytica, a political consulting firm powered by the Mercers, an ultraconservative U.S. family. Both the firm and the family also worked for the Trump campaign. Until then, the science behind which content was served and to whom remained opaque. But for years Facebook had been quietly giving the corporate world, especially advertisers, the news media, and now politicians, a switchboard for sentiment manipulation.

…

Trump’s digital director had used Facebook’s Custom Audiences tool to round up the Facebook profiles of everyone on the campaign’s mailing lists, then used another program, called Lookalike Audiences, to come up with a list of users with similar outlooks and interests. The Mercer-backed company Cambridge Analytica enabled them to take this pool of potential voters and sort them into psychographic silos. They used the data to craft messages tailored exactly to what each person, each outlook, needed to hear to be convinced. They honed those messages even further by using Facebook’s A/B testing tool, called Brand Lift.

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

Plenty of lines can be drawn between 2008 and the political upheavals of 2016.7 The financial crisis also played a decisive role in politicising a younger generation on the left, who made an important contribution to Jeremy Corbyn’s unexpected electoral surge in 2017.8 The effect of tech platforms on liberal democracies has been feverishly discussed. Following Britain’s 2016 referendum and Trump’s election victory, liberals fixated on the malign power of Facebook, Cambridge Analytica, Russian ‘troll farms’ and Vladimir Putin to sway election outcomes by planting ‘fake news’ in front of the eyeballs of easily persuaded swing voters. The lack of any editorial bottlenecks or regulation meant that a kind of information anarchy had broken out, heralding a ‘post-truth’ world in which nobody could tell truth from lies any longer.

…

With the authority of statistics waning, and nothing stepping into the public sphere to replace it, people can live in whatever ‘imagined community’ they feel most aligned to and willing to believe in, which may or may not be a national one. Where statistics can be used to correct faulty claims about the economy, society or the population, data analytics does little to prevent people from giving way to their instinctive perspectives or emotional prejudices. On the contrary, companies such as Cambridge Analytica treat those feelings as things to be tracked. But even if there were an ‘Office for Data Analytics’, acting on behalf of the public and the government as the ONS does, it’s not clear that it would offer the kind of scientific perspective that liberals today are struggling to defend. The new apparatus of number-crunching is well suited to detecting trends, sensing the mood and spotting things as they bubble up.

…

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. Questions were raised about the relationships between polling companies and hedge funds on the day of the referendum, with fears that pollsters were passing on sensitive information to private clients, to give them first-mover advantage.

Because Internet: Understanding the New Rules of Language by Gretchen McCulloch

4chan, Black Lives Matter, book scanning, British Empire, Cambridge Analytica, citation needed, context collapse, Day of the Dead, DeepMind, digital divide, disinformation, Donald Trump, emotional labour, en.wikipedia.org, eternal september, Firefox, Flynn Effect, Google Hangouts, Ian Bogost, Internet Archive, invention of the printing press, invention of the telephone, lolcat, machine translation, moral panic, multicultural london english, natural language processing, Neal Stephenson, off-the-grid, pre–internet, QWERTY keyboard, Ray Oldenburg, Silicon Valley, Skype, Snapchat, Snow Crash, social bookmarking, social web, SoftBank, Steven Pinker, tech worker, TED Talk, telemarketer, The Great Good Place, the strength of weak ties, Twitter Arab Spring, upwardly mobile, Watson beat the top human players on Jeopardy!, Wayback Machine

Not much came of it, in the end: the Library of Congress changed course in 2017, restricting their Twitter archive to tweets that met stricter criteria of newsworthiness. A less benign social media data controversy happened in 2018, when British political consulting firm Cambridge Analytica was discovered to have obtained personal data from millions of Facebook users in 2015 by convincing people to link a personality quiz with their Facebook account. The personal data derived from the quiz was then used to target voters and potentially sway elections. The Library of Congress and Cambridge Analytica represent two extremes, but less publicized researchers have continued mining for data on social media, restricted only by terms of service and their own senses of fair play.

…

., 187 authorship, shared, 261–62 avatars, 156 “b4” (before), 72 “bae” (babe; before anyone else), 22, 51, 135–36 Baron, Naomi, 204 Bashwiner, Meg, 64 Bazin, Hervé, 133 BeerAdvocate, 31 Behold the Field meme needlework of author, 252–54, 259 Bell, Alexander Graham, 201 birthday emoji, 166–68, 173 blackface, 165 Blinkenlights, 255–56 blogs, 34–35, 73, 224–25 book metaphor for language, 265–69, 273–74 boyd, danah, 81–82, 102, 103, 232 “brb” (be right back), 72 Brennan, Amanda, 260 Brennan, Susan, 121–22 British English spellings, 46–47 Brown, Kara, 172 “btw” (by the way), 72, 74 Bulletin Board Systems (BBSes), 68 Cambridge Analytica, 22–23 Canadian spellings and pronunciations, 40–41, 48 Carpenter, Nicole, 79 Carroll, Lewis, 175 case in formal language, 152 initial caps, 145 Ironic Capitals, 134, 138, 147 and minimalist typography, 139–50 for social/internet acronyms, 11, 48 cat videos/pictures, 190, 241–44, 246 Cedergren, Henrietta, 28–29 chain emails, 77, 255 Chambers, J.

…

., 152 Curzan, Anne, 45–46 Darics, Erika, 125–26 dashes as separation characters, 96–98, 111–12 Davis, Claire, 58 Dawkins, Richard, 238–39 debate memes, 247 Denham, Henry, 133 Denis, Derek, 59–60 dialect mapping, 18–26 dictionaries, 265–67, 268 Dictionary of American Regional English, 19, 20 Dictionary of the English Language, A (Johnson), 266 digital immigrants, 88 digital natives, 76–77, 84 digital residency, 100 diglossia, 52 disappearing content, 104, 222–23 doge meme, 248–49, 250 dot dot dot (ellipsis points), 96–98, 107–8, 111–13, 114, 150 Dresner, Eli, 185–87 Drouin, Michelle, 58 Dutch language, 56 early adopters, 73, 81 Eckert, Penelope, 27 Edison, Thomas, 201 Edmont, Edmond, 18–19, 61 eggplant emoji, 162, 164, 167, 172–73 Eisenstein, Jacob, 23–24, 55, 185 ellipsis points (ellipses), 96–98, 107–8, 111–13, 114, 150 emails chain emails, 77, 255 editing of, 215 greetings in, 204–7 as second place, 228 third places mediated through, 223–24 usage trends of cohorts, 89–90, 92–93, 94 Wired Style’s discussion of, 87 emblems, 159, 161–65 embodiment, digital, 156–57, 185, 188, 191–93 emoji, 155–95 advantages of, 184 compared to a language, 157–58 in court cases, 193–94 as cues about intention, 186–87, 192, 194–95 details conveyed by, 192 and digital embodiment, 156–57, 185, 188, 191–93 and dynamic communication, 157 emblem gestures, 161–65, 167, 172–73 facial expressions, 185 history of, 167, 173–84 illustrative gestures, 166–68, 173 as indication of active listening, 189–90 most commonly used, 14 new additions to, 182–83 popularity of, 157, 182, 191 and Pre Internet People cohort, 95, 98 repetitions in, 170–72 and Semi Internet People cohort, 90 standardization of, 163, 181, 183 success of, 191–92 with taboo meanings, 162–63, 167 term, 180 used in combination, 168–70, 172, 173 variation among platforms, 163, 167, 181 and virtually hanging out, 189–90 Emojination, 183 Emojipedia blog, 163 emoticons as cues about intention, 186–87 emoji used in lieu of, 185 emoji’s advantages over, 184 and Full Internet People cohort, 83 gender-based use of, 35 in handwritten postcards, 97 in Jargon File, 72 origins of, 176–78 and Pre Internet People cohort, 95 and Semi Internet People cohort, 90 and Snapchat, 164 emotion in informal writing, conveying, 74–75, 107–8 English language(s) and Arabizi, 51–55 book metaphor for, 265–69 and British spellings, 46–47 and Canadian spellings/pronunciations, 40–41, 48 displacement of other languages, 270–71 fast rate of change in, 36–39 Epstein, Brandon, 251 Esperanto, 191 ethics of internet-based research, 22 exclamation!compounds, 131–32 exclamation marks, 123–25 exclamation marks, inverted, 133 Facebook American adults using, 85–86 and Cambridge Analytica controversy, 22–23 founding population of, 79–80 and Full Internet People cohort, 79 name treatment for, 48 in non-English languages, 270 and Old Internet People cohort, 74 and platform switching, 103 and Post Internet People cohort, 93, 100 and Pre Internet People cohort, 93 real names used on, 80 status updates on, 222, 227, 229–34 and strong/weak ties in, 39 third-place functions of, 228 time spent on, 222 usage differences among cohorts, 81 vaguebooking on, 232–33 Facebook Messenger, 213 FaceTime, 94 Fagyal, Zsuzsanna, 38 Fahlman, Scott, 177, 178 familects, 26–27, 38 fanfiction, 262 faxlore, 255, 256 FidoNews, 75 First Wave of internet people, 65–75 Fixing English (Curzan), 45–46 Flickr, 129 flirting, 105–6 flower-in-hair kaomoji, 179 formal language/writing disembodied nature of, 13 and effects of informal language use, 58 in essays, 195 expectations for, 14–15 gesturing in, 12–13 and informal/formal language mix of youth, 59–60 punctuation of, 152 and time to revise, 110 forums, 68 founder effect, 65 Freeman, Nina, 79, 80 friendliness, conveying, 124 friendships on the internet, 63, 74–75 Friendster, 103 Full Internet People cohort, 78–84 and context collapse issue, 103 and email, 90, 92–93 and memes, 246, 252 social function of internet for, 77, 78, 82, 100, 103 typing skills of, 122–23 “fyi” (for your information), 72 Gawne, Lauren, 159, 160 Gchat, 86, 100, 213, 217 gender, 33–35 GeoCities, 78, 79 geographic coordinate tags on Twitter, 23 gesturing co-speech function of, 165–66 emblem gestures, 161–65, 167, 172–73 in formal/informal speech, 12–13 illustrative gestures, 166–68, 173 movement conveyed by, 192 repetitions in (beats), 171–72 gifs customization of, 14 emblems displayed with, 164 emoji’s advantages over, 184 as emotional currency, 190 as indication of active listening, 189 Gilliéron, Jules, 18 Gmail, 182 Godwin, Mike, 239, 251 Godwin’s Law, 239, 251 Goldman, Eric, 193 Google Docs, 49 Google Groups, 69 Google Hangouts, 213 Gosling, Ryan, meme based on, 245, 247 grammar checkers in word processors, 45–46 Grant, Harley, 144–45 “gr8” (great), 149 Great Good Place, The (Oldenburg), 220 greetings, 200–207, 235 Grieve, Jack, 24 Grumpy Cat meme, 245, 247 gun emoji, 194 Hacker’s Dictionary, The, 71 Hale, Constance, 87 hallways as third places, 221 Hancock, Jeffrey, 149 Harrison, George, 96–97 Harry Potter and the Cursed Child (Rowling), 192–93 Hartzog, Woodrow, 230–31 Harvard Dialect Survey, 20 hashtags, 38, 55–56, 128–30, 145 hate speech, 234 Heath, Maria, 115 “hella,” 23 “hello” (greeting), 200–202 Herring, Susan, 34–35, 102, 185–87 “hey girl” meme, 245, 247 High Expectations Asian Father meme, 257 high school cliques, linguistic distinctions in, 27–28 Hitler/Nazi comparisons on the internet, 239, 251 homepages, personal, 78, 79 Houseparty, 235 HTML, 69 humor, characters marking, 176–77 Hwang, Tim, 247 hyphens as separation characters, 113 IBM, 151 Icelandic, 36–38, 270–71 “ICQ” (I seek you), 78, 213, 226 ICT (information and communications technologies), 84 identity, online, 74, 80–81 “ikr” (I know, right?)

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

There would, after the 2016 election, be a whole new genre of articles and books explaining how Donald Trump won. Some of them suggested that he, or the Russians, or a shady consulting firm his campaign employed called Cambridge Analytica, had found a way to manipulate Facebook and manipulate us through it. But the Russians had spent a trivial amount of money, just $100,000 all told. An exhaustive British government report found little evidence that Cambridge Analytica could actually deliver on its promises to customers. Trump’s own campaign had spent about seven hundred times as much as the Russians on Facebook ads. And Trump’s campaign strategy—of riling up his supporters, rather than trying to convert moderates—had indeed meant that he got far more clicks on his advertisements than Clinton.

…

Nick let go of a bit of his image management in Zurich, too, stopped giving interviews of any kind to reporters, with one exception: a curious Swiss journalist named Hannes Grassegger, who had himself played a role in the unraveling Facebook scandals, as the first to report on the wild claims being made by the chief of Cambridge Analytica. The pioneering web designer Oliver Reichenstein, who was working with Nick on the new project, had introduced him to the reporter, and Grassegger was fascinated by the sparks being thrown off America’s internet media. He was delighted to learn that Nick—in his view the most prominent exile in Zurich and perhaps the first political refugee of the Trump era—would grant him an interview.

…

., 32, 41, 44, 102, 284 Business Insider, 61, 149, 269 BusinessWeek, 66 BuzzFeed and AOL’s purchase of Huffington Post, 149 “Buzz Detection” tool, 74 BuzzFeed News feature, 238, 247, 299 and competition with old media, 145 and devaluation of traffic, 264–70 Disney purchase negotiations, 195–202 and Facebook’s political content, 238–40, 244–45 and Gawker’s competition, 139 and Gionet, 297 and growth of Twitter, 115 launch of BuzzFeed Politics, 165 layoffs and labor tensions, 279–85 and meetings with New York Times board, 219–20, 223 news and social content, 157–64, 165–69, 172–73 origins of, 72–76 and product marketing, 287–89 and Ratter’s launch, 217 relationship with Huffington Post, 78–79, 107 reliance on Google searches, 151–54, 154–56 and revival of legacy media, 228–30 and right-wing media, 185–88, 190–94, 290–94 rivalry with Gawker, 170–71, 174 and social engagement on Facebook, 271–77 SPAC deal, 300–303, 324n302 and splintering of internet media, 299 and the Steele Dossier, 247, 249, 250–52, 254, 256–57, 260 and tech financing boom, 147 and “the Dress” viral post, 209–12 traffic growth, 122–27, 129–30, 203–12 and Upworthy, 179–83 Zuckerberg’s purchase offer for, 160–62, 165 “BuzzFeed Meme Machine” (memo), 123 C cable networks, 127–28, 269 Calacanis, Jason, 216 Cambridge Analytica, 242, 261 Camp, Garrett, 150–51 Campbell, Pamela, 231 Camp Bowery, 19, 54, 138 Canada, 226 Canvas Networks, 127 Carlson, Nicholas, 84–85, 120 Carson, Ben, 240 Case, Steve, 25 censorship, 211, 296–97 Cerami, Kassie, 112, 114 Charles, Michael, 188 Charlottesville rally, 294 Chartbeat, 204 Chateau Marmont, 199 Chatroulette, 151 Cheney, Dick, 71 Chinese Communist Party, 211 Chomsky, Noam, 4 Christie, Chris, 239 Claremont Middle School, 5 clickbait, 182–83 “click meter” tool, 105 Clinton, Bill, 27, 32, 94, 110, 119 Clinton, Hillary Rodham and Facebook’s political content, 239–42, 244–45 and Gionet, 293 presidential primary campaign, 102–3, 106 and the Steele Dossier, 248, 250, 253–54 support from women’s media, 94 and Weiner scandal, 144 WikiLeaks email controversy, 254, 259 Clooney, George, 56 CNET News, 41 CNN, 127–28, 167, 243, 249–51, 253 Coen, Jessica and author’s background, 246 and Denton’s parties, 53–56 and Denton’s wedding, 174 and Durst sex tape scandal, 63–64 and Gawker’s sexual content, 140 and Huffington Post’s traffic, 68–69 influence at Gawker, 53–56 and Jezebel’s style and content, 87, 95 Cohen, Michael, 250 Colbert, Stephen, 152 Coleman, Greg, 266 College Preparatory School, 5 Columbia Journalism School, 53 Comcast, 269 Comey, James, 249 Complex, 300 Comscore, 150, 179, 287 Condé Nast, 54, 88, 94, 156, 218 Conspiracy (Holiday), 234, 262 conspiracy theories and websites, 184, 258 Contagious Media, 27–28, 47–51, 71–72, 103 content management systems, 82 Conway, Ron, 285–86 Coppins, McKay, 166 Cormier, Anthony, 254, 257 Couric, Katie, 3–4, 8 COVID-19 pandemic, 299 Cox, Ana Marie, 29–31 Cox, Chris, 162–63, 206, 211 CPM (cost per thousand views) measure, 22–23, 45, 83, 169 Craigslist, 281 Cronkite, Walter, 28 CrowdTangle, 275 Cruz, Ted, 239, 240 Crying while Eating meme, 49, 50 cryptocurrency, 283, 299 Cuban, Mark, 216 Cube, the, 2, 11, 47 culture jamming, 9, 27 curiosity gap, 181, 205.

Breaking News: The Remaking of Journalism and Why It Matters Now by Alan Rusbridger

"World Economic Forum" Davos, accounting loophole / creative accounting, Airbnb, Andy Carvin, banking crisis, Bellingcat, Bernie Sanders, Bletchley Park, Boris Johnson, Brexit referendum, Cambridge Analytica, centre right, Chelsea Manning, citizen journalism, country house hotel, cross-subsidies, crowdsourcing, data science, David Attenborough, David Brooks, death of newspapers, Donald Trump, Doomsday Book, Double Irish / Dutch Sandwich, Downton Abbey, Edward Snowden, Etonian, Evgeny Morozov, fake news, Filter Bubble, folksonomy, forensic accounting, Frank Gehry, future of journalism, G4S, high net worth, information security, invention of movable type, invention of the printing press, Jeff Bezos, jimmy wales, Julian Assange, Large Hadron Collider, Laura Poitras, Mark Zuckerberg, Mary Meeker, Menlo Park, natural language processing, New Journalism, offshore financial centre, oil shale / tar sands, open borders, packet switching, Panopticon Jeremy Bentham, post-truth, pre–internet, ransomware, recommendation engine, Ruby on Rails, sexual politics, Silicon Valley, Skype, Snapchat, social web, Socratic dialogue, sovereign wealth fund, speech recognition, Steve Bannon, Steve Jobs, the long tail, The Wisdom of Crowds, Tim Cook: Apple, traveling salesman, upwardly mobile, WikiLeaks, Yochai Benkler

His mother, Kay,13 had battled President Nixon over Watergate. Where were these apolitical regulators going to materialise from? It was a question of free speech.14 The Cambridge Analytica crisis was real enough. But it coincided with two popular movements in which social media had acted as a global bushfire. The hashtags #MeToo and #TimesUp had been used by millions of women to amplify the full implications of the outing (by the NYT in October 2017) of Harvey Weinstein’s abuse of women. And – almost simultaneous with the Cambridge Analytica affair – millions of Americans came together under the banner of #NeverAgain to demand gun control in the wake of the massacre of 17 people at a Florida high school.

…

Google, meanwhile, was also making mindblowing amounts of money from advertising – $67 billion in revenues in 2015, growing to $79.4 million the following year. It was, perhaps, only a matter of time before the privacy implications of this digital gold rush based on the mining of our lives would become fully apparent. They did – with an ear-splitting crash – in the aftermath of the Cambridge Analytica exposé in the Observer in early 2018. But, for now, the money was – for the West Coast giants – simply washing in. The annual Reuters Institute for the Study of Journalism ‘Digital News Report’ for 2016 did not make cheerful reading about the crisis gripping newspapers the world over: ‘Across our 26 countries, we see a common picture of job losses, cost-cutting, and missed targets as falling print revenues combine with the brutal economics of digital in a perfect storm.’20 Much of this was due to revenues being sucked out of minnows, who were left gasping for air as the West Coast giants began to hoover up the advertising dollars in earnest.

…

Some academics began to develop normative standards (e.g. dealing with hate speech, falsehood, free speech, privacy and so on) to which Facebook could sign up, and which could then be monitored – assuming the company was prepared to be more transparent. A big assumption. And then, in the spring of 2018, the legacy media finally drew blood. A long and lonely investigation by one Observer reporter, Carole Cadwalladr,9 had picked away at the part played by a shadowy political consulting firm, Cambridge Analytica (CA), in using vast troves of personal data harvested by Facebook to target voters in American and UK plebiscites. Two things changed the impact of Cadwalladr’s campaign. In association with the NYT and C4 in London, the Observer produced a whistleblower who was prepared to speak on the record.

The System: Who Owns the Internet, and How It Owns Us by James Ball

"World Economic Forum" Davos, behavioural economics, Big Tech, Bill Duvall, bitcoin, blockchain, Cambridge Analytica, Chelsea Manning, cryptocurrency, digital divide, don't be evil, Donald Trump, Douglas Engelbart, Edward Snowden, en.wikipedia.org, fake news, financial engineering, Firefox, Frank Gehry, Internet of things, invention of movable type, Jeff Bezos, jimmy wales, John Gilmore, John Perry Barlow, Julian Assange, Kickstarter, Laura Poitras, Leonard Kleinrock, lock screen, Marc Andreessen, Mark Zuckerberg, Menlo Park, military-industrial complex, Minecraft, Mother of all demos, move fast and break things, Network effects, Oculus Rift, packet switching, patent troll, Peter Thiel, pre–internet, ransomware, RFC: Request For Comment, risk tolerance, Ronald Reagan, Rubik’s Cube, self-driving car, Shoshana Zuboff, Silicon Valley, Silicon Valley startup, Skype, Snapchat, Steve Crocker, Stuxnet, surveillance capitalism, systems thinking, The Chicago School, the long tail, undersea cable, uranium enrichment, WikiLeaks, yield management, zero day

This is what O’Kelley means when he talks about an iceberg – but it’s not clear we’re even seeing the tip of it. The Cambridge Analytica scandal – where the political consultancy was found to have bought up data on 87 million people via an online personality quiz – brought down the company and brought huge public fury. The story was important and the company was rightly criticised, but the scale of its data was trivial compared with the scale of the really big players. In fact, Cambridge Analytica’s data was almost useless to them, given the sheer scale and power of the advertising and targeting tools Facebook itself (and its rivals) holds.

…

That digital divide will only widen. 7https://www.theguardian.com/technology/2017/jul/27/facebook-free-basics-developing-markets Index Aadhaar, here Abramson, Jill, here Ackerman, Spencer, here Acquisti, Alessandro, here ad blockers, here, here advertising, online, here, here, here, here, here, here complexity of, here, here and consumer benefits, here CPM (cost per mille), here programmatic advertising, here, here, here see also surveillance airspace spectrum, here Al Shabab, here Alexander, General Keith, here, here, here Alibaba, here al-Qaeda, here Amazon, here, here, here, here, here, here, here, here and advertising, here and centralisation of power, here and regulation, here Andreessen, Marc, here, here Android, here, here angel investors, here, here, here, here, here antitrust laws, here AOL, here, here, here Apple, here, here, here, here, here, here AppNexus, here, here, here ARPANET, here, here, here, here, here, here, here, here, here, here separation of military elements, here, here see also DARPA Ars Technica, here artificial intelligence (AI), here, here, here Associated Press, here AT&T, here, here, here, here Atlantic, here Baidu, here Barlow, John Perry, here, here, here batch processing, here Bell, Emily, here, here Berners-Lee, Tim, here, here, here betaworks, here, here Bezos, Jeff, here bit.ly, here Bitcoin, here, here, here blackholing, here blockchains, here Bomis, here book publishers, here Border Gateway Protocol (BGP), here Borthwick, John, here, here, here, here, here, here botnets, here Brandeis, Louis, here broadband customers, here, here BT, here, here BuzzFeed, here cable companies, here lobbying, here peering agreements, here profits, here, here reputation and trust, here tier one providers, here, here traffic blocking, here transit fees, here cable TV, here, here, here Cambridge Analytica, here Carnegie, Andrew, here celebrities, here Cerf, Vint, here, here, here, here Certbot, here Chicago School of Economics, here China, here, here, here, here, here, here, here, here Chrome, here CIA, here Cisco, here Clinton, Hillary, here ‘cloud, the’, here CNN, here Cohn, Cindy, here, here Cold War, here, here Comcast, here, here, here, here, here CompuServe, here computers, early, here content farms, here, here cookies, here, here, here, here, here Cox, Ben, here credit cards, here Crimea, here Crocker, Steve, here, here, here, here, here, here, here cryptocurrencies, here, here, here, here Daily Caller, here, here Daly, Tom, here, here, here DARPA, here, here, here, here, here data brokers, here, here, here Defense Communications Agency, here del.icio.us, here Deliveroo, here ‘digital colonialism’, here DirecTV, here distributed denial of service (DDoS) attacks, here, here, here Dolby, here Domain Name System (DNS), here, here, here, here, here, here Dots and Two Dots, here DoubleClick, here duolingo, here Duvall, Bill, here Dyn attack, here eBay, here, here Eisenstein, Elizabeth, here elections, interference in, here Electronic Frontier Foundation (EFF), here, here Eliason, Frank, here, here, here, here, here Encarta, here encryption, here, here Engelbart, Doug, here Etsy, here European Union (EU), here, here, here, here, here, here see also General Data Protection Regulation (GDPR) Facebook, here, here, here, here, here, here, here, here, here, here, here, here, here, here acquisition of WhatsApp, here, here, here, here and advertising, here, here, here, here, here, here and centralisation of power, here and ‘digital colonialism’, here and government entities, here influence on elections, here Menlo Park campus, here privacy scandals, here and regulation, here, here, here, here Facetime, here facial recognition, here FakeMailGenerator, com, here Fastclick, here Fastly, here FBI, here, here Federal Communications Commission (FCC), here, here, here financial crash, here, here FireEye, here First World War, here, here Five Eyes, here, here, here Flickr, here Flint, Michigan, here Foreign Policy, here, here Fotolog, here, here, here Foursquare, here Franz Ferdinand, Archduke, here Free Basics, here free speech, here, here, here, here, here Freedom of Information Act, here GCHQ, here, here, here, here, here and encryption, here General Data Protection Regulation (GDPR), here, here, here George V, King, here Ghonim, Wael, here Gibson, Janine, here, here, here Gilded Age, here, here, here Gilmore, John, here Gimlet media, here Giphy, here Gizmodo blog, here Gmail, here Goodwin, Sir Fred, here Google, here, here, here, here, here, here, here, here, here, here, here, here, here, here, here and advertising, here, here, here, here, here, here, here and centralisation of power, here London headquarters, here and regulation, here, here, here Grateful Dead, here Greene, Jeff, here, here, here Greenwald, Glenn, here Grindr, here Guardian, here, here, here, here and Snowden leaks, here, here Guo Ping, here Gutenberg press, here Heatherwick, Thomas, here Herzfeld, Charles, here Hoffman, Reid, here Hong Kong, here HOSTS.TXT, here Hotmail, here HTML, here HTTP, here, here HTTPS Everywhere, here Huawei, here, here Hutchins, Marcus, here IBM, here identity, here India, here, here Industrial Revolution, here Instagram, here intellectual property, here, here internet, origins of, here, here commercialisation and globalisation, here gradual expansion, here logging and security, here the name, here origins of networking, here separation of military elements, here, here see also ARPANET Internet Corporation for Assigned Names and Numbers (ICANN), here, here, here, here Internet Hall of Fame, here, here Internet of Things, here internet service providers (ISPs), here, here, here, here, here, here, here, here and Pakistan/YouTube incident, here intranets, here IP (Internet Protocol), here IP addresses, here, here, here, here, here, here, here, here, here and blackholing attacks, here iPhones, here, here Iran, here, here, here, here Stuxnet worm attack, here, here ISIS, here Jackson, Steve, here Jarvis, Jeff, here journalism, here see also newspapers Kaspersky, here key cards, here Kickstarter, here, here, here Kidane v.

Money Men: A Hot Startup, a Billion Dollar Fraud, a Fight for the Truth by Dan McCrum

air gap, Amazon Web Services, Bernie Madoff, Big Tech, bitcoin, Brexit referendum, Buckminster Fuller, call centre, Cambridge Analytica, centre right, Citizen Lab, corporate governance, corporate raider, COVID-19, Donald Trump, Elon Musk, fake news, forensic accounting, Internet Archive, Kinder Surprise, lockdown, Market Wizards by Jack D. Schwager, multilevel marketing, new economy, off-the-grid, offshore financial centre, pirate software, Ponzi scheme, Potemkin village, price stability, profit motive, reality distortion field, rolodex, Salesforce, short selling, Silicon Valley, Skype, SoftBank, sovereign wealth fund, special economic zone, Steve Jobs, Vision Fund, WeWork

(He claimed to mostly fly commercial, although in the weeks that followed he offered Murphy help with a story about lax security at a UK airfield which attracted Russian private jets – Marsalek said he could put an FT reporter on a Gulfstream in Moscow, if he wanted. Murphy declined, as that level of co-operation was a little too close for comfort.) Marsalek also talked about some of his private investments. He was looking at backing a reformed Cambridge Analytica, the scandal-hit political consultancy which had been caught harvesting Facebook data on a massive scale. Marsalek had also put $7m into a fundraising by Telegram, the group behind the encrypted messaging app, and encouraged Murphy to write about the project. (The US authorities later forced Telegram to return the $1.2bn it raised in total from investors.)

…

Murphy’s interview took longer to reach the same destination. In the end, our best guess was that Wirecard got lucky. Gold did have a sense of how we worked because Murphy had been developing him as a source that year. To begin with he’d tried to get Gold to broker an interview with Alexander Nix, the Cambridge Analytica whistleblower whom Gold claimed to know. Then Gold had been a source about lax money laundering controls at Flutter, owner of the Betfair exchange which allowed gamblers to lay bets with each other. In theory, it would be a neat way to move money from A to B by taking either side of obscure wagers.

…

To find a specific word or phrase from the index, please use the search feature of your ebook reader. 1A Mauritius fund 79–89, 115, 134, 250 advisors’ fees 88 Ernst & Young investigation 135 7995 transaction codes 16, 19, 42, 101 Absolute Poker 30 acai berry sellers 61 Acai Berry King see Willms, Jesse Achleitner, Paul 224, 231–2 Adyen 175 AIM market 91 Akhavan, Hamid ‘Ray’ ix, 118 and Animo Associates 278–9 and Marsalek 227, 278, 285 arrested USA 285 sentenced 304 Al Alam Solutions 245, 246, 249, 258, 272, 276–7, 301 and Allied Wallet 210 and Third-Party Acquiring 200–202, 221 rebrands as Symtric 277 unsecured loans/no income 286–7 Wirtschaftswoche on 261 Al Alawi, Kumail 69–70 Ali, Marsalek’s bribery contact 184 Alken Asset Management 119, 140 Allied Wallet 210–11, 304 Allscore Beijing, Wirecard and 250 Alphaville blog (FT) 52–3, 54, 91, 258 Camp Alphaville 52–3, 55–6, 96, 112–13 House of Wirecard series 91 and Ingenico/Wirecard 108 ‘Rabble’ 54, 96 Schillings on 119 Anderson, Pamela 223 Angermayer, Christian 198–9, 239 Animo Associates, Wickford 278–9, 283–4 APG Protection 255, 257n Arafat, Yasser 266 Ardiss, Katherine, and 1A/Hermes deal 83–4 Ashazi Services, Bahrain 67–71, 72–7 Asian Internet Gaming conference 57–8 Assion, Rüdiger, KPMG report meeting 290 Austrian coalition government collapse 2019 263 Austrian Interior Ministry, and refugees/stabilization 265–9 Austrian People’s Party 196 Aykroyd, Dan 21 Badel, Antoine 119, 140 BaFin and Earl 208–10, 294 and Palos 116 ban Wirecard shorting 180, 182, 186, 226, 240–41 blamed by MPs 302 criminal complaint against McCrum and Palma 195 on market manipulation 139, 172 reforms 305 Baker Tilly 85 Banc de Binary 211 Banco de Oro (BDO) 274 declares Wirecard documents spurious 294 Bandits xii ‘Bank of Oman’ 181 Bank of the Philippine Islands (BPI) 274 declares Wirecard documents spurious 293–4 Barber, Lionel xii, 54, 107, 141, 143–4, 169, 175, 176, 177, 205, 206, 224, 225, 247, 257, 259, 270, 299 and FTI 261–2 on FT bribery accusation 207 on Nick Gold tapes 220–23 on Novichok story 244–5 on Wirecard story 1–6 reviews McCrum and Zatarra 132 Barclay Brothers, Sunday Business 53–4 Barth, Hubert 167, 305 Batson, Chris 173 Bauer, Christopher ix, 45, 62, 249 and Third-Party Acquiring 200 denies running PayEasy 193–4 in Manila 58 meets KPMG 275–6 on Ashazi Services 70–71 Palma seeking 191–4, 207 reported dead 303 Bauer-Schlichtegroll, Paul ix, 14 and Electronic Billing Systems (EBS) 12–14, 17 and Flynt Publications 11–12 and InfoGenie reverse takeover 17 and Wagner 10 buys Wirecard for porn billing 12–13 moves to supervisory board 27 divests from Wirecard 31, 46 Bäumler-Hösl, Hildegard 183–6, 209–10 Bavarian police, 2015 Wirecard raid 101–3 Bayerische Wirtschaft 31 Bellenhaus, Oliver x, 10, 44, 261 and EBS 18–19 and prepaid credit cards 18 CardSystems Middle East 200–202 Al Alam meeting 276–7 and Allied Wallet 210 and Wirecard special audit 252 driving 39–40 personal habits 199–200 surrendered/co-operated 303 BellTrox 298–9 Bergermann, Melanie, on Al Alam 261 Roland Berger 233 Bergman, James, PayEasy 62 Berntsen, Gary 178 Bharara, Preet, hedge funds prosecution 35–6 Bijlipay card reader 80–81 Bill (purported Wirecard source) 244, 282 Bitcoin, Braun on 250 Blank Rome, and Wirecard self-review 102–3 Block, Carson xi, 93, 99 Doing Business in China for Dummies 37 Marsalek tries to bribe 118 on Casino supermarkets 112–13 on NMC Health 261 on Sino Forest 36–7 Bloomberg, Ali on bribing 184–5 Blue Ridge hedge fund 121 Bluetool 97 Bosler, Tobias 107 and the Turkish boxers 33–4 on Wirecard accounts 32–4 Bournewood (BVI entity) 97 Boyd, Roddy, ‘Great Indian Shareholder Robbery’ 146–7 Branston & Gothard 53–4 Braun, Dr Markus, Wirecard CEO ix, 25–34, 46–7, 60, 103, 110, 111, 145, 154, 172, 176, 229, 231, 234 on Ashazi 76–7 and Deutsche Bank 232 loan 147 and FT imaginary clients story 248–52 offers interview 259–60 orders Marsalek to get FT onside 230 intimidates short sellers 31–4 in French Riviera 197 and visit by heavies 197 Ingenico, revives purported bid 117–18 and IT systems 41–4 and KPMG report blames KPMG for delay 289 cash loan January 2020 288 Gill on 301–2 KPMG meeting 290 on publication 291 rejects supervisory board advice 289 suspicions of 287 not fired 294–5 resigns 296 arrested 303 management style 64 and McKinsey report 234–5 on Project Tiger 174, 175 SoftBank, and Wirecard 197–200, 203, 205, 237, 238 Vienna weekends 196–7 on Wirecard and Bitcoin 249–50 on Wirecard Asian non-offices 93 on Wirecard Brazil/Turkey MCAs 236 and Wirecard DAX Index membership 156, 159–60 on Wirecard total integrity 74–7 Zatarra Report 107 Kroll to investigate 117–19 Earl on 124 Wirecard London presentation 111 Braun, Sylvia 64 Bribery Act 207 Brinken Merchant Incorporations 44 British Virgin Islands and shell companies 44 Wirecard and 31 Bub Gauweiler 183 Buckminster Fuller question 75 Budde, Andreas 203 Buffett, Warren 65, 95 Bundestag, Wirecard inquiry 302 critical report on EY 305 MPs apologize to FT 302 Burtnick, Nelson, Marsalek on 62–3 Cambridge Analytica story 150, 241 Camp Alphaville 52–3, 55–6, 96, 112–13 CardSystems Middle East 200–202 Casino supermarkets 112–13 CellarDoor 53 CenturionBet 102n Cerberus 231 chargebacks nutraceuticals scam 47–9 Visa 2009 crackdown 49 China, Wirecard buying Allscore Beijing 250 Chinese frauds exposure 36–7 Chuprygin, Andrey xi and GRU 268 Citadelle Corporate Services, uncooperative 271, 272 Citigroup AsiaPacific deal with Wirecard 145–6, 152–3 Project Tiger summary papers sent to 167–8 Click2Pay (Wirecard online wallet) 13–19 Clifford Chance, and Manila trustee meeting 272–5 Cloudflare 109 CMS lawyers 17, 243 CNBC, Braun interview on FT and accounts 203–4 Coathanger King 244, 257, 282 Cobb, Oliver, on Wirecard 144–5, 236–7, 298 Cohodes, Marc 226 ‘Colin’ (Marsalek’s friend) x, 86–7, 88–9, 277, 278, 301 at P61 116 in Singapore 133–4 on Dr Rami 278 barbecue 279–80 Commerzbank 157, 292 accuses FT of market manipulation 172 retracts 174 losses 304 Committee to Protect Journalists 187 ConePay, purported creditor, non-existent 187–90 Connaught outsourcing company 94 Control Risks, and R&T information flow 202–3 Covid, travel issues 276 credit cards high-risk processing 43–4, 47 payments, post–2008 scrutiny 47 prepaid/unbranded, for Click2Pay e-wallets 17–19 Credit Suisse 23 and Wirecard/SoftBank bond 238 Crypto currency, Braun on 250 Dahmen, Martin (EY) 292 and Singapore audit 202–3 Al Alam meeting 277 and Manila trustee meeting 272–5 on Third-Party arrangements 251–2 ‘Dale’, whistleblower, on Wirecard UK & Ireland 245 Dallas investigation 227, 282 Daniel Stewart stockbroker 134n Dave the IT guy 109, 113, 123 Davies, Paul 238 DAX 30 28, 236, 287, 288 Dennis, Jonathan 213, 215, 216, 217, 241 Der Spiegel 195, 263 Deutsche Bank 3, 183, 196, 224, 305 and Braun loan 288 Samt and Marsalek decide to buy 231 Wirecard and 27 Dialectic Capital hedge fund 105 Dolan, Shane 261 Döpfner, Mathias 177 Dowson, Simon x, 44, 97, 278–9 Reuters investigation 122 Dun & Bradstreet 233 Duterte, Rodrigo 187, 221, 251, 273 Dyer, Geoff 194 Earl, Matthew xi, 94–5, 109–12, 185–6 and BaFin on Zatarra 109 case dropped 141–3 explains Wirecard to 208–10 avoiding Perring 123–4 Kroll on 119, 130 on Markus Braun 124 on Wirecard/Hermes 95, 97–100 reports to FBI on Wirecard critics hacking 208 reports to Mastercard on Wirecard 208 talks on Sky News 298 Toronto University on hacking gang 208, 298–9 under siege 127–31 faked photo of 257 outed on Twitter 127 phished/attacked online 131–2 shadowed 127–9 VisMas Files 124 EasyJet 233 Eaze 285 Edelman, KPMG report meeting 290 Eichelmann, Thomas 233, 235, 249, 294, 296 backs Braun and special audit 271–2, 283, 288–9 El Obeidi, Rami xi, 218–19, 301 Elder, Bryce 108, 117–18 Electronic Billing Systems (EBS) 12–14, 17, 18–19 Elvins, Hayley xi, 255, 256–7, 257n Emery, Bruce 144–5, 236 Enderle, Franz 183, 242 Ennismore hedge fund 91 Epsilon Investments 134 Ernst & Young 76, 77, 237, 248, 249 and CardSystems 201 litigation against 305 and NMC Health 261 and Wirecard Singapore 154, 167–8, 201–3 Wirecard/1A/Hermes investigation 135–8, 144 Wirecard special audit 249–50, 251–2 alerts BaFin 294 and Al Alam Solutions 201, 277 and Manila trustee meeting 272–5 completing audit 292–4 on Third-Party arrangements 251–2 Ernst & Young Canada 37 European Securities and Markets Authority 180 Exxon, on BellTrox 299 Federal Trade Commission, and Allied Wallet 210 Fieldfisher, and Singapore audit 203 financial crisis 2008 23–4 financial markets betting schemes 61 Financial Conduct Authority 99, 109, 255 Financial Times Alphaville see Alphaville Festival of Finance 112–13 Lex column 21–2 North American edition, Lex column 22–4 office, London 1–2 people xii moves back to Bracken House 205, 206–7 newsroom 169 surveillance discovered 173–4 office New York 20–24, 35–8 scepticism culture 37–8 Wirecard investigations/stories 1–7 and short-sellers set-up 212–19, 220–25, 228 blamed for Wirecard short attack 107 Braun orders Marsalek to get FT onside 230 declines Braun interview offer 259–60 FT’s QC blocks Project Tiger story 4–6, 168 puts questions to Wirecard 218 Singapore investigation story published 170–71, 174 accused of market manipulation 172 blames Zatarra 107 Wirecard suing for misuse of business secrets 194–5 Singapore/Philippines stories 236 Wirecard imaginary clients story 248–52 Wirecard action vs. 242–3 internal investigation 240–42 see also specific FT people Fleep messaging service 82 Flutter group 213, 241–2 Flynt, Larry, and Bauer-Schlichtegroll 11–12 Foster Mitchell, Victoria 261 Foulis, Patrick 21 Frankfurt stock exchange (Deutsche Börse) 25 Frankfurter Allgemeine Zeitung 180, 305 Freedom Party Austria 178, 263 Freis, James 294–6 Friend Finder 43 Fritsche, Klaus-Dieter 250 Froehlich Tours 191 FTI Consulting 111, 261–2 Full Tilt 30, 62–3 G2Pay payment processor 29–31, 102 G2Pay Dublin 39, 42–4 G2Pay Toronto 30, 42 begins to shrink 45–6, 59–60 ICC-Cal issues 49–51 Mastercard fines 42 miscoded 7995 transactions 42 upfront payment to Wirecard 30–31 Gattringer, Wolfgang, and Libya refugee project 266–9 General Electric 153 German civil legal system 242–3 German institutions, investor confidence in 93 German press supports Wirecard 110 Geschonneck, Alexander 251, 290 Getnow 278 GI Retail 105 GI Technology 86 Gibraltar, Wirecard and 31 Gill, Evelyn (Pav’s mother) 160, 162, 166–7, 168, 171, 306 Gill, Pav, Wirecard AsiaPacific legal counsel x, 152–60 and Ng investigate finance team 155–8 and whistleblower 154–5, 156, 158 Ng & Steinhoff, Telegram chats 157–8, 163 on Braun/Marsalek 301–2 on Wirecard Singapore 161–5, 171 ousted 158–60 Project Tiger copies 158–60 thriving 305–6, 307 Gold, Nick xii, 212–13, 229, 254–5 El Obeidi on 219 IVA agreed 306 Kroll to investigate 117–19 on FT about to expose Wirecard 213–17 recorded/quoted 221–2, 241–2 Goldman Sachs 249 Goomo travel firm 87, 88, 133, 135, 137 P61 HQ 116 Görres, Andrea, and Wirecard x self-review 102–3 special audit 252 Graham and Dodd, Security Analysis 95 Grant Thornton 30 Greenvale Capital 144–5, 236–7 GRU (Russia Military Intelligence) 263–70 Guardian 53 Gupta, Varun 89 Gustenau, Brigadier, on refugee project 267 Guttenberg, Karl-Theodore zu 250 Hallbergmoos, Wirecard office 9–11 Hamilton, Ben (re Kroll), fishing visit to Earl 129–30 Handelsblatt 177, 186, 219, 222, 229 Hanson, Nigel xii, 3–6, 106, 125, 170, 171, 175, 194, 205, 243 on McCrum’s correspondence hacked 121–2 on FT/short-sellers set-up 220–22 reviews McCrum and Zatarra 132 Harper Gray 174 Harris, Daniel, and Wirecard shorting rumour 182–3 Harris, James 115 Helms, Matthias (Wirecard due diligence) 135–7 Hempton, John xi, 55–6, 74, 188–9 Henseler, Alfons 234 Herbert Smith Freehills (law firm) 175, 220, 221, 223, 224 Hermes i-Tickets 78–89 Earl on 95–7 Ernst & Young investigation 135–8 Ramasamy on 111 Hodgson, Camila 149 ‘Hollins, Ian’ 96, 112, 123–4, 127, 226, 305 Honourable Artillery Company 52 House of Wirecard Alphaville series 91 HSBC 185 Hufeld, Felix 294, 305 Hume, Neil 54 Hustler, Flynt Publications, Bauer-Schlichtegroll and 11–12 ICC-Cal 27, 48 miscoded 7995 transactions 42 Merchant IDs crackdown 50–51 Wirecard cash stolen 50–51 IIFL Wealth 82 Inatec 46, 61, 63, 97, 116 InBev and Budweiser story 54 Indo-German Chamber of Commerce 250 InfoGenie reverse takeover 17 Ingenico purported bid for Wirecard 108, 117–18 Investors Chronicle 21 Israeli security Wirecard executives and 50–51 Iwersen, Sönke 219, 222 J-Capital Research 92–4, 98, 113, 121 ‘Jack’, whistleblower 166, 188 Jakab, Spencer 23 Jenkins, Patrick 141 Jilson (photographer) 187 Jon, on short sellers surveillance 254–7 Jones Day 130 Jones, Sam xii, 126 on FT office surveillance 173 on Marsalek, Libya, GRU and Wagner 263–70 Kalixa, Senjo buys 138 Kaminska, Izabella 223–4 Kepler Cheuvreux 292 Khalaf, Roula 173, 259–60, 270, 302 Khan, Imran 1 Khawaja, Ahmad ‘Andy’ 210, 304 Kilbey, Gary xii, 115, 306 and Marsalek 147–51 on Wirecard shorting rumour 181 on Wirecard story news leak 170–71 Kilbey, Tom xii, 147, 148–51 and Marsalek 182 Kirch, Leo 183 Kirch Media 109–10, 142 Kirk, Stuart (US Lex team) 35 Kleinschmidt, Kilian on Marsalek 264–5 reaction to Marsalek and Libya 269–70 testifies 302 Klestil, Stefan 232–3, 234 Knöchelmann, Dietmar x, 29–31, 45 KPMG 26 on 1A/Hermes 85, 88 Wirecard special audit 249, 250–51 Al Alam meeting 277 complains of obstructions/delays 287 Manila trustee meeting 272–5 on PayEasy client non-existence 276 PayEasy meeting 275–6 seeking Wirecard Singapore cash 271–6 draft report to supervisory board 286–90 enforces deadline 290 final report, no evidence for Third-Party Acquiring 291 Braun’s spins on 285, 287, 291–2 Kramp-Karrenbauer, Annegret 231 Krisper, Stephanie, on Marsalek contact 264–5 Kroeber, Susannah, on Wirecard Asian offices 92–4 Kroll investigations 58 accusatory letter to Earl 129–30 seeking Zatarra, 117, 119 Kukies, Jörg 231, 249–50 Kurniawan, Edo x and Ernst & Young 135–8, 154 on cash definition issues 259 FT and 6–7, 174 head of Wirecard Asia Pacific finance team 138, 153–8, 161, 170, 172, 210, 246, 301 and Hong Kong unit accounts 154 on ‘round tripping’ funds 155–8 paperwork 258 Wirecard supports 170 and Project Tiger 158, 165–6 vanished 176, 303 Kurz, Sebastian 196, 266 Lauterbach, Anastassia 233–4, 235, 249, 287 Lehman Brothers 22–3, 47 Leitz, Sven-Olaf 251 Ley, Wirecard CFO ix, 28, 31, 46, 50–51, 60, 64, 78, 79, 136, 142, 153, 236, 291 on Deutsche Bank 239 and Hermes 84, 85 and Kirch Media 109–10 on Wirecard Asian non-offices 93 Wirecard cash flow statement 90–91 and Wirecard self-review 102–3, 104 confronts Greenvale 144–5 KPMG report meeting 290 arrested 303, 304 Liao, Bob 139 Libya Marsalek and 116 cement plants 116, 135, 151, 247, 267, 268 creating strong border force 269 refugees as guest workers 266–9 Kleinschmidt’s reaction to 269–70 GRU and 268–9 Rami El Obeidi 255–6 Lincolnshire police 125–6 Linklaters 88 Lipscomb, Dashiell 200 Lordship Trading blog 95 Louis XIII project 231, 239 M’Cwabeni, Vuyiswa 233, 234 Macquarie, on Wirecard 139 Madoff, Bernie, Ponzi scam 23–4 Mail on Sunday 261 Majali, Yousef 105, 121 Manager Magazin allegations 261 Eichelmann interview 271–2 on forensic audit 249 on FT bribery 207 on Wirecard board 234–5 Maria, Tolentino’s paralegal 273 Marques, Eduardo xi, 299 on Senjo and 1A 146 on Wirecard and SoftBank 210 shorts Wirecard stock 59 Marsalek, Jan (Wirecard chief operating officer) ix, 39, 40, 46–51, 64, 153, 154, 172, 226 and 1A fund 115 Al Alam meeting 276–7 on Ali, FT and Bloomberg bribery scam 183–6 and Akhavan 278 whistleblower on 285 and Animo Associates 278–9 on Burtnick hiring 62–3 on Cambridge Analytica 150 and CardSystems Third-Party Acquiring 200–203 and Chuprygin; Gustenau; Gattringer 268–9 and Click2Pay 11, 13–16 ATM cards for e-wallets 17–19 on Deutsche Bank 239 and Dr Rami 278 on Elon Musk/Tesla 151 and Nick Gold tapes 217–19 Kilbeys, pays off 151 suspected of story news leak 170 G2Pay pressured 46 and Gold 213–14 and Goomo travel firm 87, 88–9 and Hermes i-Tickets/1A 78–89 and fake clients special audit 251–2 at Colin’s barbecue 279–80 crying drunk 279–80 and FT fake clients story 248–52 Third-Party Acquiring cover story 258–9 defends Third-Party business 234, 235–6 on Inatec 61 on Ingenico purported bid 108 and IT systems 41–4 on Israeli politics 178–9 on KPMG report publication 291 KPMG report meeting 290 post-audit, offers raw data 287–8 stalls 294–5 suspended not fired 294–5 fired, police charge 296 disappears to Minsk 300 and Kurniawan 136–8 on Libya 151 and refugees as guest workers 266–9 cement plants 116, 135, 151, 247, 267, 268 on creating strong Libya border force 269 Manila trustee meeting 273–5 management/lifestyle 64 extreme Covid precautions 277–8 extravagance, employee on 177–8 new information on 263–70 office 115–16 office, Samt on 252–3 P61 villa 115–16, 269, 277, 278, 280 questions about 247 Sabines (two assistants) 115, 116, 269, 279, 300 on McCrum 149 McKinsey report on 234, 235 and Novichok documents 303 recipe 179–80 story 244 and nutraceuticals chargebacks scam 47–9 PayEasy meeting 275–6 police take inbox archives 101–3, 104 Rami El Obeidi link 256 ‘Ray’, correspondence from 178 and Samt 229–30 decide to buy Deutsche Bank 231 on Senjo 138 in Singapore 134–5 and Singapore audit 201–3 in Project Tiger papers 166 on Singapore cash new Manila trustee 272 Turkey money replaces Singapore 278 and Smaul 65–6 nutraceutical processing deal 59–63 on Syria visit with Russian military 266 on Telegram 150 on Wirecard misunderstood 149 and Zatarra Report 114–19 suspects UK leak 116–17 targets McCrum and Palos 116–19 tries to bribe Carson Block 118 Marsalek, Viola 252, 253 Martiradonna, Francesco 102n Mastercard 43 fines G2Pay 42 Project Tiger summary papers sent to 167–8 compliance person 118–19 on Wirecard 208 Mateschitz, Dietrich 15 Mattias, Wulf 232–3, 249, 271 MCA Mathematik (Greenvale alias) 236–7 on forensic audit 249 McCrum, Charlotte (author’s wife) 22, 55, 126–7, 165, 174, 205, 256, 285, 297 targeted by Wirecard 175 McCrum, Dan early career 20–24, 35 New York FT office 20–24, 35–8 joins Alphaville 55–6 moved to FT Lex 141, 143–4 FT internal investigation 240–41 personal life 22–3, 105, 120, 140–41, 165, 205, 225, 227–8, 285, 297–8, 299 improves home security 126–7, 131–2 surveillance fears 257–8 and Nick Gold tapes 220–25, 228 Wirecard investigations/stories Animo Associates 283–4 and Ashazi Services, Bahrain 67–71, 72–7 blog post on Wirecard short attack 106 Exocet on fake clients 247–8, 272, 300 and Macquarie Wirecard meeting 139–40 following-up Wirecard Third-Party Acquiring 221 Marsalek said to intend bribe 147–50 and Palma, accused of bribery and threats 207 criminal case dropped 302 and Pav Gill 161–5 Singapore story publication 1–7 telephone interview with Braun 74–7 testifies to Bundestag inquiry 302 and Zatarra accusations against 127, 132 correspondence hacked 121–2, 125–6 decides to move on 132 Kroll to investigate 117–19 Marsalek’s security to investigate 116–19 meets with Earl and Perring 100 Schillings on 119 on whistleblowers protection 302–3 see also specific people or stories McKinsey 35, 233 Wirecard compliance review 252 on Wirecard Third-Party business 234, 235 and Wirecard/Deutsche Bank 239 Merchant Category Codes 16 Merchant ID (MID) 16 Visa/Mastercard and 43 Merkel, Angela 250 Metropolitan Police 208 Mishcon de Reya 127, 142, 143 Moody’s 237 Mubadala, takes over SoftBank loan to Wirecard 238 multilevel marketing pyramid schemes 61 Munich public prosecutor 183 Munich Security Conference 231 Murphy, Gary 226–7 Murphy, Paul xii, 52–5, 106, 115, 143–4, 170, 171, 172, 177, 194, 211, 225, 228, 237, 245, 246–7, 263, 278, 297, 298, 299, 302, 306 and Ashazi Services story 67, 68, 69, 73 has Alphaville IT secured 125 at Alphaville’s vaudeville 223–4 and Coathanger King/Bill 282–3 on FT/short-sellers set-up 220–22 denies shorting rumour 181 frightens Animo Associates director 279 FT internal investigation 241–2 Marsalek said to intend bribe 147–51 on SoftBank and Wirecard 205–6 spy story published 260 and surveillance informers 254–8 and Wirecard source 243–4 on Wirecard story 1–6, 100 Naheta, Akshay 198, 210, 237, 238 Narayanan, Veerappan 88 Nasdaq exchange 24 Neteller 16, 29 Neuer Markt Frankfurt 17 Neukeferloh, Grasbrunn, Wirecard move to 14 Newcastle Building Society prepaid card unit 66 Newton, Helmut 14 Ng, Royston 153, 154, 209 and Gill investigate finance team 155–8 Marsalek implicates in Bloomberg scam 185–6 Nikkei 144, 194, 205, 206, 222 Nix, Alexander 241 NMC Health 261 Novichok documents leaked 303 GRU and 268 Marsalek story 244 recipe, Marsalek and 179–80 Novum stockbroker 134n nutraceuticals charges scam 47–9 Marsalek deal with Smaul 59–63 O’Connor, Sarah 149 O’Murchu, Cynthia xii, 149, 261, 282 O’Sullivan, Henry x, 117, 249, 250, 271, 278 arrested 304 and Hermes i-Tickets 78–89 and Senjo loan 138 in Singapore 133–4 and Third-Party Acquiring 200 WalPay 102 Odey, Crispin 257 Öner, Ahmet 33–4 online casinos/gambling and banks 16 and Click2Pay 14–16 and Wirecard 14–17 countries outlawing 45–6 USA bans 2006 29 online poker legal grey area 29 US indictment 2011 62–3 7995 transactions 42–3 online porn billing, Bauer-Schlichtegroll and Wirecard 12–13, 43 online wallets 13, 16–17, 29 Orbit travel agency 87, 88 Organization for the Prohibition of Chemical Weapons 179 Ortiz, Carlos, and Wirecard self-review 102–3 Osterloh, Martin 47–9, 57–8, 199, 301 P61 (Marsalek’s villa) 115–16, 269, 277, 278, 280 Pacha club 15 Pacquiao, Manny 304 Pago (Deutsche Bank) 27 Pal, Alasdair 298 accusations against 127 on Dowson paperwork factory 122 Palldium phase 2 surveillance dossier 257 Palma, Stefania (FT) xii, 176, 243, 276, 299, 300 accused of bribery and threats 207 criminal case dropped 302 finds whistleblower Jack 166 in Singapore and Kuala Lumpur 165 meetings with Gill and Evelyn 163–4 hostile-environment training 193 seeking Christopher Bauer 191–4 seeking ConePay 187–90 Palos, Brett 116–19, 257 Paolucci, Paul 208 Pauls, Heike, analyst xii, 292, 304 accuses FT of market manipulation 172 retracts 174 on ‘buying opportunity’ 175 Paulson, John, and Sino Forest 36–7 PayEasy Solutions 58, 62, 70–71, 258, 272, 301 and Third-Party Acquiring 200 KPMG and 249, 275–6 no information 191–4 unsecured loans/no income 286–7 PayPal 2 Perring, Fraser xii, 95, 96–7, 109–13, 179, 226, 257 faces prosecution for Zatarra 141 further activities 305 on ‘Ian Hollins’ 96, 112, 123–4, 127, 226, 305 Kroll on 119 on Wirecard/Hermes 95, 97–100 outed on Twitter 127 reports demand to name Zatarra people 124–5 wants expenses 123–4 Perry, Leo xii, 210, 299 on Wirecard 67, 73, 90–92, 139–40 Philippines Wirecard new trustee meeting 272–5 Wirecard purported partners 187–94 Palma’s story published 195 Poker Stars 30, 42n Pollard, Brett 261 Ponzi scam (Madoff) 24 Portsea Asset Management 226 Prima Vista Solusi 66 Project Panther 239 ‘Project Tiger’ 155–8 Gill saves copies 158–60 information flow 202–3 summary papers sent to banks/auditor 167–8 taken over by Marsalek 157–9 ProtonMail 178, 227 Puck, Wolfgang 134, 148 Putin, Vladimir, foreign policy speculative 269 matryoshka doll 252 Quadir, Fahmi 225–7 on Akhavan and Marsalek 285 attacked 281–2 and Marsalek whistleblower 226–7 Safkhet Capital, FBI source 281–2 on Wirecard Pennsylvania 226 Quintana-Plaza, Susana 233, 289 Quirk, Mark 278–9, 284 Rajah & Tann, Project Tiger 155 Gill seen with McCrum 162 interim report 167 information flow 202–3 Report 177, 243 Braun on 287 Ramasamy, Ramu and Palani ‘The Boys’ x, 79–80, 81–9 at London presentation 111 blamed for Hermes accounts 137 Wirecard falling-out 155 Rami El Obeidi, Dr and Marsalek 278 and short sellers surveillance 255–6 sends FT flowers 260–61 Randall, Jeff 53 Raynor, Greg xi, 255, 257n Mancunian facilitator 213–17 refugees/stabilization, Austrian Interior Ministry, and 265–9 Reichert, Jochen, on Zatarra weaknesses 109–10 Reserve Bank of India 83 Reuters, on Dowson paperwork factory 122 Reynolds Porter Chamberlain (RPC, law firm) 107, 222, 224–5, 228, 240–2 on Zatarra Report 107 FT internal investigation 240–2 Robert Smith 261 Roddy 95–7, 112–13, 123 at Wirecard London presentation 111–12 on Wirecard/Hermes 95, 97–100 seeks advice 99, 100 sees vehicles shadowing Earl 129 Roland Berger 233 RP Richter (auditor) 30 Rubie, Saif 213, 216, 217 Russian diplomat, at Colin’s barbecue 279–80 Russian military in Syria 266 Novichok 179–80, 244, 268, 303 Wagner Group soldiers 268–9 Russian Military Intelligence (GRU) 263–70 Sabines (Marsalek’s two assistants) 115, 116, 269, 279, 300 Safkhet Capital 281–2 Samt, Mr (Marsalek’s PR) x, 217–19, 229–30, 231, 252–3 Santego Capital 81 SAP 233 Schäfer, Daniel 177 Schillings law firm 91 blames FT for Wirecard short attack 107 letters to FT on Zatarra 132 on McCrum/Alphaville 119 on Wirecard story 4–6, 170–71 replaced 175 Schneider, Dagmar 279 and KPMG special audit 251, 252 KPMG report meeting 290 Manila trustee meeting 273–5 Schneider, Klaus (SdK), on Wirecard accounts 34 Schütt, Michael 59, 97 Schütz, Alexander 196–7, 198 on FT 196–7 apologizes 304–5 Schwager, Market Wizards 95 SdK (Schutzgemeinschaft Der Kleinaktionäre) on Wirecard 31–4 Sender, Henny 24 Senjo 134, 138, 258, 272, 301 and Third-Party Acquiring 200, 202 buys Kalixa 138 KPMG to consider 249 unsecured loans/no income 286–7 Sewing, Christian 231, 232 ShadowFall Research 185, 209 Shah, Amit 82–8 Shanmugaratnam, R.

The Digital Party: Political Organisation and Online Democracy by Paolo Gerbaudo

Airbnb, barriers to entry, basic income, Bernie Sanders, bitcoin, Californian Ideology, call centre, Cambridge Analytica, centre right, creative destruction, crowdsourcing, data science, digital capitalism, digital divide, digital rights, disintermediation, disruptive innovation, Donald Trump, Dunbar number, Edward Snowden, end-to-end encryption, Evgeny Morozov, feminist movement, gig economy, industrial robot, Jaron Lanier, Jeff Bezos, Jeremy Corbyn, jimmy wales, Joseph Schumpeter, Mark Zuckerberg, Network effects, Occupy movement, offshore financial centre, oil shock, post-industrial society, precariat, Ralph Waldo Emerson, Richard Florida, Richard Stallman, Ruby on Rails, self-driving car, Silicon Valley, Skype, Slavoj Žižek, smart cities, Snapchat, social web, software studies, Stewart Brand, technological solutionism, technoutopianism, the long tail, Thomas L Friedman, universal basic income, vertical integration, Vilfredo Pareto, WikiLeaks

The consequences of Big Data on civil liberties and individual privacy have become widely debated after a number of famous events, from the revelations made in 2013 by U.S. information analyst Edward Snowden about the way digital companies were collaborating with the National Security Agency to conduct mass surveillance on internet users, to the 2018 controversy surrounding Cambridge Analytica and its data misuse. A concern about privacy was also central to Pirate Parties’ campaigning in defence of peer-to-peer file-sharing, as it was felt that preventing people from downloading copyrighted material would have involved large-scale surveillance. This conflict opposes the connected outsiders to all those authorities interested in maintaining forms of surveillance and control over individuals.

…

In fact, since Pirate Parties’ early days, one of the arguments in defence of peer-to-peer file exchange was precisely that in order to block it, governments would have had to conduct very intrusive controls on people’s online activities. The urgency of this issue has become all the more apparent in the aftermath of the 2013 Edward Snowden revelations about the doings of the National Security Agency mass surveillance operations, and after the Cambridge Analytica scandal which highlighted the scale of Facebook’s mishandling of user data. Activists have proposed various solutions, including the use of encrypted communication and the development of the Tor (the onion router) tunnelling service, which shields internet users from control over their internet activity.

…

Index Affordances: 5, 66, 68–9, 101 Agora voting: 119–20, 124–5 Alcibiades: 185 Alliance for Workers’ Liberty: 103 Alliance of Liberals and Democrats for Europe (ALDE): 65 Anticapitalism: 64 Appendino, Chiara: 10 Arab Spring: 168 Avaaz: 74, 169 Bauman, Zygmunt: 92 Benevolent dictator: 19, 159–60, 185 Berlusconi, Silvio: 33, 35, 150, 154 Bezos, Jeff: 19, 66 Big Data: 4, 46, 50 Big organising: 76 Blair, Tony: 35, 166 Bonaparte, Charles-Louis Napoléon: 110 Bonapartism: 110 Bond, Becky: 14, 157, 172 Bratton, Benjamin: 71–3 Breznev, Leonid: 148 Bureaucracy: 17–8, 31, 35, 40, 148, 179–80, 183, 191 As a problem in political parties: 40–1 Consultants: 18 Conflict between bureaucracy charismatic leadership: 148–9, 151 Elimination of: 75–6, 89, 96–7, 105, 183 Microbureaucracy: 97 Party in central office: 94, 95 Caesarism: 150–2 Callaghan, James: 148 Cambridge Analytica: 50, 56 Carmena, Manuela: 11 Casaleggio Associati: 9, 102, 116, 125, 141–2, 160 Casaleggio, Davide: 15, 61, 81, 89, 167 Casaleggio, Gianroberto: 9, 60–1, 94, 97, 116, 154, 160–1 Casas Moradas: 104 Castells Manuel: 23, 146 Clinton, Hillary: 54, 158 Colau, Ada (mayor of Barcelona): 11 Collaborative policy development: 17, 107, 130–3, 141, 180 Comisión de Garantias (guarantee committee, Podemos): 136 Complutense University of Madrid: 11, 155 Computer Chaos Club (Germany): 124 Connected outsiders: 20, 43–4, 50–1, 55, 177 Income: 53–4 Young vote: 52 Education: 53 Representatives’ sociodemographics: 54 Conservative Party (UK): 31 Considerant, Victor: 126 Consul (decision-making software): 108, 115, 120–2 Corbyn, Jeremy: 12, 151 Dalton, Richard: 35 Decidim: 108, 124 Deliveroo: 13, 49, 50 De Tocqueville, Alexis: 27 Dean, Howard: 13 Dean, Jodi: 26 Decision-making platforms: 105–15 Della Volpe, Galvano: 28 Democracy Deliberative democracy: 38, 60, 91, 108, 109–11, 114, 123–4, 127 Direct democracy: 61, 142, 180 Democracy quality: 40, 128, 186 Demands for “real democracy”: 59 Democratic centralism: 41 Conditions for: 129 Criticism of existing: 58–9 Criticism of: 110 Intraparty: 13 OMOV (one man, one vote system): 102 Participatory budgeting: 60 Participatory democracy: 3, 17 DemocracyOS: 108 Democrazia Proletaria (Proletarian Democracy): 26 Di Battista, Alessandro: 83, 100, 135, 157 Di Maio, Luigi: 1–3, 135, 157, 181 Digital democracy: External validation: 125 Discussion of direct legislation: 110 Management of online decision-making: 127–30, 191 Online democracy: 60 Need for guarantee rules: 143 Participatory legislation: 17 Reactive democracy: 18, 127, 163, 185–6 Thresholds: 121, 124 Digital capitalism: 46–7, 93 Digital disruption: 18 Economic rise: 47, 49 Gig economy: 50 Digital parties (also platform parties): 3–5, 14, 18–9 As cloud parties: 79 As forum parties: 79 As start-up parties: 80 Conflicts between national leadership and local groups: 102 Data gathering: 69, 73–4 Platform as policy platform: 77, 189 Free labour: 18, 69, 75, 178, 191 Free membership: 17, 69 Free registration: 74 History: 7–10 Low marginal costs of communication: 5, 48 Low staff numbers: 49 Similarities with platform companies: 5 Similarities with television party: 78 Digital platforms: 69 Architecture: 115–6 Definitions: 69 Hierarchies: 73 Reintermediation: 71 Standardisation: 71 Supposed neutrality: 72 Digital revolution: 44–6, 48 And Fordism: 31 As a cleavage: 45–7 Comparison with industrial revolution: 26, 28, 30–1, 33, 44–7, 49, 51, 54 Digital rights: 55–7 Privacy: 55 Digital surveillance: 55 Reform of copyright: 56 Digital Bill of rights (UK): 58 Marco Civil da Internet (Brazil): 58 Direct Connect (file-sharing hub): 8 Direttorio (M5S Directorate): 135 Discorsi all’umanità: 150, 154 Disintermediation: 66, 70, 71, 75–6, 109 Distributed centralisation: 17, 72, 76, 145, 183 Distributed organising: 14, 75, 182 Dryzek, John S.: 109 Dunbar number: 98 Duverger, Maurice: 31, 39–4, 75, 165 Distinction between direct and indirect party: 41 Theory of party structure: 40 Dyer-Whiteford, Nick: 49 Echenique, Pablo: 136 Economic crisis: 20, 27, 43, 51–3, 145–6 Eggers, David: 94 Emerson, Ralph Waldo: 24 Encadrement: 163, 165, 174 Engström, Christian (Pirate Party MEP): 55 Environmental movements: 25, 32, 146 Erdogan, Tayyip: 110 Errejón, Iñigo: 11, 138, 149, 160–1 Europe of Freedom and Direct Democracy (EFDD): 65, 135 Exley, Zack: 14, 157, 172 FAANGs (Facebook, Amazon, Apple, Netflix, Google): 49–50, Facebook: 2–4, 12–3, 43, 47, 49, 56, 66, 68–74, 84, 144, 156, 163, 169 Facebook live: 3 Newsfeed algorithm: 106 Falkvinge, Rick: 8, 56, 156, 159, 173, 181 Feminist movements: 25, 145 Fico, Roberto (president of the Italian lower chamber): 3, 95, 100, 135 Forza Italia (Italy): 33, 35, 52 Foti, Alex: 50 France Insoumise: 4, 12, 74, 81, 83, 86, 87, 91, 93, 96–9, 108, 121–2, 132–3, 139, 144, 158–9, 166–70, Avenir en Commun electoral programme: 122, 132 Groupes d’appui (support groups): 97–9 Friedman, Milton: 64 Friedman, Thomas L.: 23 Galapagar case: 138–9 Game of Thrones: 156 Ghibellines: 28 Gillespie, Tarleton: 69 Gramsci, Antonio: 7, 27, 37–8, 41, 43–4, 75, 77, 105, 143, 164 Theory of party structure: 38–9, 164 On the passivity of the mass: 147 On leadership: 151–2, Great Recession: 4, 27, 46, 168, Green Party: 10, 16, 26, 27 Basisdemokratie (grassroots democracy): 16 Grillo, Beppe: 2–3, 9, 43, 59–60, 74–5, 80, 83, 89, 95, 100–1, 135, 141, 153, 154–5, 158–60, 181 theatre shows: 154 Guelphs: 28 Guevara, Che: 25, 26, 148 House of Cards: 25 Hyperleader: 17, 144–62 And reactive democracy: 185 As benevolent dictator: 186 Characteristics: 153–5 Relationship with advisors: 159–60 Reputation: 154 Iglesias Turrion, Pablo: 11, 86, 94, 136, 138–9, 145, 149–50, 151, 153, 155–6, 158–60, 181 Italia a 5 Stelle (Five star movement annual gathering): 1–3 Izquierda Unida (IU): 136 Julius Caesar: 19, 28, 150, 152, 159, 161 Kant, Immanuel: 184 Karpf, David: 13, 169 Katz, Richard: 7, 30, 32, 59, 99 Kautsky, Karl: 110 Kennedy, John Fitzgerald: 33 Kirchheimer, Otto: 7, 32 Klug, Adam: 12, 171 La Tuerka: 150, 156 Labour Party: 12, 14, 29, 31, 35, 41, 52, 54, 107–8, 111, 148, 151, 156, 165, 168, 177 Lansman, Jon: 12, 103, Lavapies (neighbourhood in Madrid): 94 Leadership: 146–8 Charismatic leadership: 148–9 Leaderlessness: 77, 146, 181, 183, 187 Legal-rational: 147 Routinisation of charisma: 188 Liberalism: 28 Linux: 19, 82, 86, 159 Liquid Feedback: 4, 16, 61, 112–4, 121, 124 Loomio: 108, 112, 114–5 Machiavelli, Niccolò: 151, 186 Macron, Emmanuel: 13, 108, 140 Madison, James: 24 Mair, Peter: 7, 30, 32, 59, 99 Marx, Karl: 68, 93 May’s law: 124, 170 Mélenchon, Jean-Luc: 12, 52, 53, 86–8, 93, 107, 122, 132, 144–5, 156–9 Michels, Robert: 7, 16, 27, 30–1, 36–9, 41, 103, 110, 140, 142, 147, 152–3, 175, 179 Iron law of oligarchy: 36–7 Theory of party structure: 39 Microbureaucracy: 97 Mill, John Stuart: 24 Momentum: 26, 73, 80, 83, 87, 96, 102–3, 107, 166, 171–2 Monedero, Juan Carlos: 11 Montero, Irene: 138–9, 158 Morgan, Gareth: 67 MoVimento 5 Stelle (Five Star Movement): 1–5, 7, 9–19, 26, 43, 52–4, 57, 60–4, 66, 73–4, 77, 80–1, 83, 86–90, 93, 95–7, 99, 100–2, 105, 107–8, 112, 115–7, 119–20, 124, Meetup groups: 97, 99–102 Referendums for the expulsion of members: 135 Salary restitution programme: 57 Movimento Sociale Italiano (rightwing party in Italy): 2 NationBuilder (political campaigning app): 12, 107, 121, 124 Nazism: 24 Nielsen, Jakob: 91 Law of participation: 91 Nixon, Richard: 33 Nvotes: 108, 119 Obama, Barack: 11, 13 Olivetti, Adriano: 88–9, 154 Optimates: 28 Organisation: 67 Delegation: 17 Elimination of middlemen: 15, 183 Integration of technology: 13 Iron law of oligarchy: 36–7, 185 Lean management: 15 Organisational fragility: 187 Netroots organisations: 13 Ostrogorski, Moisei: 24, 27, 31, 104, Paine, Thomas: 111 Panebianco, Angelo: 7, 27, 32, 34–5 Parlamentarie (M5S online primaries): 10 Parliament et Citoyens (French parliament digital democracy project): 107 Parsons, Talcott: 45 Participa (Podemos participatory portal): 12, 73, 132 Participation And anti-party suspicion: 85–8 As an idea in contemporary culture: 84 And distrust towards bureaucracy: 150 And lack of party office: 96 Aristocratic tendencies: 164, 173 Difference between militant and sympathiser: 174 Habitueés of meetings: 103 Individualisation of participation: 102–3, 188 In parties’ discourse: 82–4 Lurking supporters: 174 Participationism: 81–9, 191 Participation aristocracy: 91 Participation divide: 91 Participatory representation: 123 Passive membership: 175 Superbase: 17, 152, 162–72 Partido de la Red (Party of the Net, Argentina): 8 Partido Popular (Popular Party): 11 Partido Socialista Obrero Español (PSOE): 11, 14, 108, 166, 190 Partido X (X Party, also known as the Party of the Future, Spain): 8 Partito Comunista Italiano (Italian Communist Party): 31, 35, 42, 92, 93, 95 Partito Democratico (Democratic Party, Italy): 10, 35, 52–3, 111 Partito Socialista Italiano (Italian Socialist Party, PSI): 153 Pericles: 185 Pirate Bay (file sharing server): 8, 56, 58, 166 Pirate Parties: 4, 7–9, 12–3, 16, 26, 48, 50, 52, 54–8, 61–2, 64, 66, 73, 77, 82, 86, 88, 93, 99, 105, 107, 112, 115, 159, 166, 172, 174, 177, 178, 180–1 Piratar (Iceland): 8 Pirate Party International (PPI): 8 Piratenpartei (Germany): 8, 114 Piratpartiet (Sweden): 8, 55, 166, 167 Česká pirátská strana (Czech Pirate Party): 8 Place Fear of, terror loci: 93, 95 Organisational principle of: 42 Platformisation: 14, 67, 69, 73, 76–7, 179, 183–4, 187, Podemos: 4, 7, 9, 11–4, 16, 19, 26, 52–5, 57, 61–3, 65–6, 69, 73, 81, 86–8, 93–8, 104–5, 107–8, 112, 115, 119–21, 123–5, 131–2, 136–43, 149–51, 153, 155–60, 166–70, 173–4, 177, 180–1, 193 Circles (Podemos’ local groups): 97–8, 115, 132 Citizens’ Council (Podemos’ central committee): 11, 96, 131, 136 Iniciativas Ciudadanas and Popular Podemos (Podemos Citizens’ and Popular initiatives): 121, 131 Plaza Podemos: 16, 86, 120, 131 Political Parties: Astroturf parties: 26 Definitions of: 27–9 Cadres: 18, 161, 179, 183 Catchall: 33 Integration: 182 Electoral/professional parties: 33 Party systems: 26 Political careers: 99 Mass parties: 30–2 Movement parties: 25 New Left: 27 Party sections, cells: 97–8 Passivity of the mass: 186 Patronage parties: 28 Return of: 25–8 Suspicion towards: 22–4 Television parties: 33–6 Populares (Party in ancient Rome): 28 Populism: 1, 4, 9, 10, 12, 15, 27, 39, 44 Poulantzas, Nicos: 27 Power struggles: 161, Precariat: 50 Proceduralism: 188, 189, Protest movements: 1968: 26 2011: 36 Environmentalist: 25, 146 Feminist: 25, 146 Raggi, Virginia: 10 Rajoy, Mariano: 138 Reduction of membership of traditional parties: 165 Rees, Emma: 12, 103 Renewable energy: 62–3 Republican Party: 28 Republique En Marche (REM, Macron’s movement): 108 Revelli, Marco: 31–2 Rittinghausen, Moritz Robespierre Rokkan, Stein: 45 Role as diffusors of messages: 176 Rousseau (5 Star Movement decision-making system): 2, 10–11, 116–7 Lex functions: 117, 131 Lex Iscritti: 117 Hacker attacks: 119 Villaggio Rousseau: 2 Rousseau, Jean-Jacques: 37 Salvini, Matteo: 1, 13 Sanchez, Pedro: 11 Sanders, Bernard (US senator and presidential primary candidate in 2016): 13 Scarrow, Susan: 28, 128–9 Schneider, James: 12 Schumpeter, Joseph: 38 Scudo della Rete (Shield of the Net): 57 Security Silicon Valley: 15 Signup process: 168–9 Skocpol, Theda: 42 Snowden, Edward: 50 Sozialdemokratische Partei Deutschlands (SPD): 14 Srnicek, Nick: 71 Stalinism: 24 Stallman, Richard (open source activist): 116, 124 Super-volunteer: 171–3 Teatro Smeraldo, Milan: 9 Telegram: 4 The Apprentice: 156 TOR (The onion router): 56 Tormey, Simon: 60 Torvalds, Linus: 159 Transparency: 57 Trump, Donald: 6, 35 Tufekci, Zeynep: 187 Twitter: 4, 124 UK Independence Party (UKIP): 65 Universal basic income: 63, 131 Universal basic services: 64 V for Vendetta (film): 3 Vaffanculo Day (literally ‘Fuck Off Day’, M5S protest in 2007): 9 Veltroni, Walter: 93 Von Hayek, Friedrich: 25 Von Treitsche, Heinrich: 24 Wales, Jimmy: 159 Washington, George Weber, Max: 7, 27–9., 31, 37–8, 40, 147, 151, 185 Weil, Simone (Christian anarchist); WhatsApp: 4 Whigs (Liberal party, UK): 22 Wikipartido (Wikiparty, Mexico): 8 Wikipedia: 19, 82, 86, 91, 159 World Social Forum: 25 Yang, Guobin: 44 Your Priorities: 108 Zeming, Jang: 148 Zuckerberg, Mark: 63, 66, 158

Going Dark: The Secret Social Lives of Extremists by Julia Ebner

23andMe, 4chan, Airbnb, anti-communist, anti-globalists, augmented reality, Ayatollah Khomeini, Bellingcat, Big Tech, bitcoin, blockchain, Boris Johnson, Cambridge Analytica, citizen journalism, cognitive dissonance, Comet Ping Pong, crisis actor, crowdsourcing, cryptocurrency, deepfake, disinformation, Donald Trump, Dunning–Kruger effect, Elon Musk, fake news, false flag, feminist movement, game design, gamification, glass ceiling, Google Earth, Greta Thunberg, information security, job satisfaction, Mark Zuckerberg, mass immigration, Menlo Park, Mikhail Gorbachev, Network effects, off grid, OpenAI, Overton Window, pattern recognition, pre–internet, QAnon, RAND corporation, ransomware, rising living standards, self-driving car, Silicon Valley, Skype, Snapchat, social intelligence, Social Justice Warrior, SQL injection, Steve Bannon, Steve Jobs, Transnistria, WikiLeaks, zero day

‘It certainly doesn’t feel like that,’ Facebook CEO Mark Zuckerberg told Senator Lindsey Graham during his 2018 US Senate hearing.8 His response raised much laughter, although it wasn’t entirely wrong: there is indeed a growing niche audience that is exploring alternative solutions. As the big tech firms come increasingly under fire – whether in the US Senate, the EU, the British Home Office or the German Ministry for Justice – non-state actors ranging from radical libertarians to extremist users spot a unique chance to woo away unhappy clients. The Cambridge Analytica scandal sent Facebook’s shares tumbling9 and caused thousands of users to participate in a #Deletefacebook campaign, which was strongly encouraged on competing platforms that welcomed dissatisfied users with open arms. Even the most extreme users found ways of keeping their online presence.

…

But, increasingly, tech giants like Facebook have begun to realise that their platforms have been systematically used to hack people’s minds. Facebook failed to protect its users from personal data breaches and targeted manipulation, Twitter ignored the disinformation campaigns launched by fake profiles and bot nets on its platform and YouTube was reluctant to combat extremist and violence-inciting content. The Cambridge Analytica scandal and social-media-inspired terrorist attacks were among the many virtual earthquakes that have shaken the democratic pillars of the real world. Cyber innovations have given rise to global networks of extremists who increasingly cooperate across borders to radicalise new generations of digital natives.

…

M. here, here b4bo here bin Laden, Osama here, here, here birthrates here, here Bissonnette, Alexandre here, here BitChute here bitcoin here, here, here Blissett, Luther here Bloc Identitaire here blockchain technology here bloggers here Blood & Honour here Bloom, Mia here Bloomberg, Michael here Böhmermann, Jan here Bowers, Robert here Breed Them Out here Breitbart here, here, here Breivik, Anders Behring here, here ‘Brentonettes’ here Brewer, Emmett here Brexit here, here Britain First here British National Party (BNP) here, here, here Broken Heart operation here Brown, Dan here Bubba Media here Bumble here, here Bundestag hack here, here BuzzFeed here C Star here, here ‘Call of Duty’ here, here Cambridge Analytica here, here Camus, Renaud here Carroll, Lewis here CBS here Channel programme here Charleston church shooting here Charlie Hebdo here Charlottesville rally here, here, here, here, here, here, here, here, here Chemnitz protests here, here Choudary, Anjem here Christchurch terror attacks here, here, here, here Christian identity here Chua, Amy here CIA here, here, here Clinton, Bill and Hillary here, here, here, here, here, here, here Cohn, Norman here Collett, Mark here Cologne rape crisis here Combat here, here Comey, James here Comvo here concentration camps here Conrad, Klaus here Conservative Political Action Conference here Constitution for the Ethno-State here Corem, Yochai here counter-extremism legislation here counter-trolling here Covington, Harold here Crash Override Network here Crusius, Patrick here cryptocurrencies here, here, here, here Cuevas, Joshua here Cyberbit here Cyborgology blog here ‘Daily Shoah’ podcast here Daily Stormer here, here, here, here, here, here, here, here, here Weev and here Damore, James here Dark Net here Data and Society Research Institute here Davey, Jacob here Dawkins, Richard here, here De La Rosa, Veronique here de Turris, Gianfranco here Dearden, Lizzie here deep fakes here, here DefCon here, here Der Spiegel here Deutsche Bahn here Diana, Princess of Wales here, here Die Linke here Die Rechte here ‘digital dualism’ here digital education here disinformation here, here, here Disney here Domestic Discipline here, here Donovan, Joan here Doomsday preppers here doubling here Dox Squad here, here doxxing here, here, here, here, here Doyle, Laura here, here Draugiem here DTube here Dugin, Alexander here Dunning–Kruger Effect here Dutch Leaks here Dylan, Bob here Earnest, John here 8chan here, here, here, here, here, here, here, here EKRE (Estonian fascist party) here El Paso shooting here Element AI here Emanuel, Rahm here encryption and steganography here Encyclopedia Dramatica here English Defence League here, here, here, here Enoch, Mike here environmentalism here, here ethno-pluralism here, here ‘Eurabia’ here, here ‘European Israel’ here European National here European Parliament elections here European Spring here Evola, Julius here executions here Facebook friends here fashions and lifestyles here, here Fawcett, Farah here Faye, Guillaume here FBI here, here, here, here, here Fearless Democracy here, here FedEx here Feldman, Matthew here Ferdinand II, King of Aragon here Fiamengo, Janice here Fields, James Alex here Fight Club here Finkelstein, Robert here Finsbury Mosque attack here, here, here Fisher, Robert here Foley, James here Follin, Marcus here football hooligans here, here Football Lads Alliance (FLA) here For Britain party here Fortnite here 4chan here, here, here, here, here, here, here, here, here FPÖ (Austrian Freedom Party) here, here, here, here, here Frankfurt School here Fransen, Jayda here Fraternal Order of Alt-Knights here Freedom Fighters, The here freedom of speech here, here, here, here F-Secure here FSN TV here Gab here, here, here, here, here, here Gamergate controversy here GamerGate Veterans here gamification here, here, here, here, here, here, here, here Ganser, Daniele here Gates of Vienna here Gateway Pundit here Gawker here GCHQ here GE here GellerReport here Generation Identity (GI) here, here, here, here, here, here, here, here Generation Islam here genetic testing here, here German elections here, here German Institute on Radicalization and De-Radicalization Studies here German National Cyber Defence Centre here Gervais, Ricky here Ghost Security here Giesea, Jeff here Gigih Rahmat Dewa here Gionet, Tim here gladiators here Global Cabal of the New World Order here global financial crisis here, here global warming here GNAA here Goatse Security here GOBBLES here Goebbels, Joseph here GoFundMe here Goldy, Faith here Goodhart, David here ‘Google’s Ideological Echo Chamber’ here Gorbachev, Mikhail here Graham, Senator Lindsey here Gratipay here Great Awakening here, here Great Replacement theory here, here, here, here, here ‘Grievance Studies’ here grooming gangs here, here Guardian here, here H., Daniel here Habeck, Robert here HackerOne here hackers and hacking here ‘capture the flag’ operations here, here denial of service operations here ethical hacking here memory-corruption operations here political hacking here ‘qwning’ here SQL injections here techniques here Halle shooting here Hamas here, here Hanks, Tom here Happn here Harris, DeAndre here ‘hashtag stuffing’ here Hate Library here HateAid here, here Hatreon here, here, here Heidegger, Martin here Heise, Thorsten here, here Hensel, Gerald here, here Herzliya International Institute for Counter-Terrorism here Heyer, Heather here, here, here Himmler, Heinrich here Hintsteiner, Edwin here Histiaeus here Hitler, Adolf here, here, here, here, here Mein Kampf here, here Hitler salutes here, here, here, here Hitler Youth here HIV here Hizb ut-Tahrir here, here, here Höcker, Karl-Friedrich here Hofstadter, Richard here Hollywood here Holocaust here Holocaust denial here, here, here, here, here Holy War Hackers Team here Home Office here homophobia here, here, here Hooton Plan here Hoover Dam here Hope Not Hate here, here, here Horgan, John here Horowitz Foundation here Hot or Not here House of Saud here Huda, Noor here human trafficking here, here Hussein, Saddam here, here Hutchins, Marcus here Hyppönen, Mikko here Identity Evropa here, here iFrames here Illuminati here Incels (Involuntary Celibacy) here, here Independent here Inkster, Nigel here Institute for Strategic Dialogue (ISD) here, here, here, here, here, here, here, here Intelius here International Business Times here International Centre for the Study of Radicalisation (ICSR) here International Federation of Journalists here International Holocaust Memorial Day here International Institute for Strategic Studies here Internet Research Agency (IRA) here iPads here iPhones here iProphet here Iranian revolution here Isabella I, Queen of Castile here ISIS here, here, here, here, here, here, here, here, here, here, here, here hackers and here, here, here, here, here Islamophobia here, here, here, here, here, here, here Tommy Robinson and here, here see also Finsbury Mosque attack Israel here, here, here, here, here Israel Defense Forces here, here Jackson, Michael here jahiliyya here Jakarta attacks here Jamaah Ansharud Daulah (JAD) here Japanese anime here Jemaah Islamiyah here Jesus Christ here Jewish numerology here Jews here, here, here, here, here, here, here, here, here see also anti-Semitism; ZOG JFG World here jihadi brides here, here JihadWatch here Jobs, Steve here Johnson, Boris here Jones, Alex here Jones, Ron here Junge Freiheit here Jurgenson, Nathan here JustPasteIt here Kafka, Franz here Kampf der Niebelungen here, here Kapustin, Denis ‘Nikitin’ here Kassam, Raheem here Kellogg’s here Kennedy, John F. here, here Kennedy family here Kessler, Jason here, here Khomeini, Ayataollah here Kim Jong-un here Kohl, Helmut here Köhler, Daniel here Kronen Zeitung here Kronos banking Trojan here Ku Klux Klan here, here Küssel, Gottfried here Lane, David here Le Loop here Le Pen, Marine here LeBretton, Matthew here Lebron, Michael here Lee, Robert E. here Li, Sean here Li family here Libyan Fighting Group here LifeOfWat here Lifton, Robert here Littman, Gisele here live action role play (LARP) here, here, here, here, here, here lobbying here Lokteff, Lana here loneliness here, here, here, here, here, here, here Lorraine, DeAnna here Lügenpresse here McDonald’s here McInnes, Gavin here McMahon, Ed here Macron, Emmanuel here, here, here, here MAGA (Make America Great Again) here ‘mainstream media’ here, here, here ‘Millennium Dawn’ here Manosphere here, here, here March for Life here Maria Theresa statue here, here Marighella, Carlos here Marina Bay Sands Hotel (Singapore) here Marx, Karl here Das Kapital here Masculine Development here Mason, James here MAtR (Men Among the Ruins) here, here Matrix, The here, here, here, here May, Theresa here, here, here Meechan, Mark here Meme Warfare here memes here, here, here, here and terrorist attacks here Men’s Rights Activists (MRA) here Menlo Park here Mercer Family Foundation here Merkel, Angela here, here, here, here MGTOW (Men Going Their Own Way) here, here, here MI6, 158, 164 migration here, here, here, here, here, here, here, here, here see also refugees millenarianism here Millennial Woes here millennials here Minassian, Alek here Mindanao here Minds here, here misogyny here, here, here, here, here see also Incels mixed martial arts (MMA) here, here, here, here Morgan, Nicky here Mounk, Yascha here Movement, The here Mueller, Robert here, here Muhammad, Prophet here, here, here mujahidat here Mulhall, Joe here MuslimCrypt here MuslimTec here, here Mussolini, Benito here Naim, Bahrun here, here Nance, Malcolm here Nasher App here National Action here National Bolshevism here National Democratic Party (NPD) here, here, here, here National Health Service (NHS) here National Policy Institute here, here National Socialism group here National Socialist Movement here National Socialist Underground here NATO DFR Lab here Naturalnews here Nawaz, Maajid here Nazi symbols here, here, here, here, here, here, here see also Hitler salutes; swastikas Nazi women here N-count here Neiwert, David here Nero, Emperor here Netflix here Network Contagion Research Institute here NetzDG legislation here, here Neumann, Peter here New Balance shoes here New York Times here News Corp here Newsnight here Nietzsche, Friedrich here, here Nikolai Alexander, Supreme Commander here, here, here, here, here, here 9/11 attacks here, here ‘nipsters’ here, here No Agenda here Northwest Front (NWF) here, here Nouvelle Droite here, here NPC meme here NSDAP here, here, here Obama, Barack and Michelle here, here, here, here, here Omas gegen Rechts here online harassment, gender and here OpenAI here open-source intelligence (OSINT) here, here Operation Name and Shame here Orbán, Viktor here, here organised crime here Orwell, George here, here Osborne, Darren here, here Oxford Internet Institute here Page, Larry here Panofsky, Aaron here Panorama here Parkland high-school shooting here Patreon here, here, here, here Patriot Peer here, here PayPal here PeopleLookup here Periscope here Peterson, Jordan here Pettibone, Brittany here, here, here Pew Research Center here, here PewDiePie here PewTube here Phillips, Whitney here Photofeeler here Phrack High Council here Pink Floyd here Pipl here Pittsburgh synagogue shooting here Pizzagate here Podesta, John here, here political propaganda here Popper, Karl here populist politicians here pornography here, here Poway synagogue shooting here, here Pozner, Lenny here Presley, Elvis here Prideaux, Sue here Prince Albert Police here Pro Chemnitz here ‘pseudo-conservatives’ here Putin, Vladimir here Q Britannia here QAnon here, here, here, here Quebec mosque shooting here Quilliam Foundation here, here, here Quinn, Zoë here Quran here racist slurs (n-word) here Radio 3Fourteen here Radix Journal here Rafiq, Haras here Ramakrishna, Kumar here RAND Corporation here Rasmussen, Tore here, here, here, here Raymond, Jolynn here Rebel Media here, here, here Reconquista Germanica here, here, here, here, here, here, here Reconquista Internet here Red Pill Women here, here, here, here, here Reddit here, here, here, here, here, here, here, here, here, here redpilling here, here, here, here refugees here, here, here, here, here Relotius, Claas here ‘Remove Kebab’ here Renault here Revolution Chemnitz here Rigby, Lee here Right Wing Terror Center here Right Wing United (RWU) here RMV (Relationship Market Value) here Robertson, Caolan here Robinson, Tommy here, here, here, here, here, here, here, here Rockefeller family here Rodger, Elliot here Roof, Dylann here, here Rosenberg, Alfred here Rothschilds here, here Rowley, Mark here Roy, Donald F. here Royal Family here Russia Today here, here S., Johannes here St Kilda Beach meeting here Salafi Media here Saltman, Erin here Salvini, Matteo here Sampson, Chris here, here Sandy Hook school shooting here Sargon of Akkad, see Benjamin, Carl Schild & Schwert rock festival (Ostritz) here, here, here Schilling, Curt here Schlessinger, Laura C. here Scholz & Friends here SchoolDesk here Schröder, Patrick here Sellner, Martin here, here, here, here, here, here, here, here, here, here Serrano, Francisco here ‘sexual economics’ here SGT Report here Shodan here, here Siege-posting here Sleeping Giants here SMV (Sexual Market Value) here, here, here Social Justice Warriors (SJW) here, here Solahütte here Soros, George here, here Sotloff, Steven here Southern, Lauren here Southfront here Spencer, Richard here, here, here, here, here, here Spiegel TV here spoofing technology here Sputnik here, here SS here, here Stadtwerke Borken here Star Wars here Steinmeier, Frank-Walter here Stewart, Ayla here STFU (Shut the Fuck Up) here Stormfront here, here, here Strache, H.

The Science of Hate: How Prejudice Becomes Hate and What We Can Do to Stop It by Matthew Williams

3D printing, 4chan, affirmative action, agricultural Revolution, algorithmic bias, Black Lives Matter, Brexit referendum, Cambridge Analytica, citizen journalism, cognitive dissonance, coronavirus, COVID-19, dark matter, data science, deep learning, deindustrialization, desegregation, disinformation, Donald Trump, European colonialism, fake news, Ferguson, Missouri, Filter Bubble, gamification, George Floyd, global pandemic, illegal immigration, immigration reform, impulse control, income inequality, longitudinal study, low skilled workers, Mark Zuckerberg, meta-analysis, microaggression, Milgram experiment, Oklahoma City bombing, OpenAI, Overton Window, power law, selection bias, Snapchat, statistical model, The Turner Diaries, theory of mind, TikTok, twin studies, white flight

This trend is fuelled by the internet revolution and its corruption by masked individuals, the far right and state actors. Societal divisions are being prised wide open with the use of the internet in an attempt to garner support for populist leaders and ideologies. Donald Trump’s 2016 presidential campaign hired Cambridge Analytica and the Leave.EU Brexit campaign hired Aggregate IQ to use artificial intelligence to ‘micro-target’ those who would be most vulnerable to messages designed to stir up fears of the ‘other’.3 During the COVID-19 pandemic, social media was flooded with far-right conspiracy theories and hate targeting Jewish, Muslim, Chinese and LGBTQ+ people for supposedly creating and/or spreading the disease (more on this in Chapter 10).4 Beyond organised campaigns, the everyday internet user also took to social media to post hateful messages, triggered by disinformation and careless phrases, like ‘Chinese virus’ and ‘kung flu’, coming out of the White House.5 What is most worrying about this trend is that the research shows divisive messages from public figures are directly linked to tipping some people into hateful violence on the streets.

…

The Search Engine Manipulation Effect (SEME) exerted the greatest influence on moderate Republicans and could shift the voting preferences of undecided voters by 20 per cent or more in the US.13 What is more insidious is that once links are clicked and pages are visited, the administrators of unscrupulous websites are known to use ‘trackers’ to follow a visitor’s future moves around the internet, allowing them to develop psychological profiles through clicks and likes. This can facilitate Cambridge Analytica-style political micro-targeting.14 The effectiveness of online advertisements tailored to psychological profiles has been tested by Columbia University’s Professor Sandra Matz. Expanding established laboratory studies to the internet, Matz conducted three field experiments involving 3.5 million internet users.

…

Abdallah, Abdalraouf, 1 Abedi, Salman, 1, 2, 3, 4 abortion, 1, 2 Abu Sayyaf Group, 1 abuse, 1, 2, 3, 4, 5 accelerants to hate, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 accelerationists, 1 addiction, 1, 2, 3, 4 Admiral Duncan bar, 1 adolescence, 1, 2, 3, 4, 5, 6, 7 advertising, 1, 2, 3, 4, 5 African Americans, 1, 2, 3, 4, 5, 6, 7 afterlife, 1, 2 age, 1, 2 aggression: brain and hate, 1, 2, 3, 4, 5; false alarms, 1; group threat, 1, 2, 3, 4, 5, 6; identity fusion, 1; mortality, 1; pyramid of hate, 1; trauma and containment, 1, 2 AI, see artificial intelligence Albright, Jonathan, 1 alcohol, 1, 2, 3, 4, 5, 6, 7, 8 algorithms: far-right hate, 1, 2, 3, 4; filter bubbles and bias, 1, 2; Google, 1, 2, 3; online hate speech, 1, 2, 3, 4, 5, 6; Tay, 1, 2; tipping point, 1, 2; YouTube, 1 Algotransparency.org, 1 Allport, Gordon, 1, 2, 3, 4 Al Noor Mosque, Christchurch, 1 al-Qaeda, 1, 2 Alternative für Deutschland (AfD), 1 alt-right: algorithms, 1, 2; brain and hate, 1; Charlottesville rally, 1, 2; counter-hate speech, 1; definition, 1n; Discord, 1; Facebook, 1, 2, 3; fake accounts, 1; filter bubbles, 1, 2; red-pilling, 1, 2; social media, 1, 2; Trump, 1, 2; YouTube, 1 Alzheimer’s disease, 1 American Crowbar Case, 1 American culture, 1 American Nazi Party, 1, 2 Amodio, David, 1n amygdala: brain and signs of prejudice, 1, 2; brain tumours, 1; disengaging the amygdala autopilot, 1; hate and feeling pain, 1, 2; and insula, 1; neuroscience of hate, 1n, 2, 3, 4; parts that edge us towards hate, 1; parts that process prejudice, 1; prepared versus learned amygdala responses, 1, 2; processing of ‘gut-deep’ hate, 1; recognising facial expressions, 1n, 2; stopping hate, 1, 2; trauma and containment, 1, 2; unlearning prejudiced threat detection, 1 anger, 1, 2, 3, 4, 5, 6, 7, 8 anonymity, 1, 2 anterior insula, 1n Antifa, 1, 2n, 3 anti-gay prejudice, 1, 2, 3, 4, 5, 6, 7, 8 anti-hate initiatives, 1, 2 antilocution, 1 anti-Muslim hate, 1, 2, 3, 4, 5, 6 anti-Semitism, 1, 2, 3, 4, 5, 6 anti-white hate crime, 1 Antonissen, Kirsten, 1, 2 anxiety: brain and hate, 1, 2, 3, 4; harm of hate speech, 1; intergroup contact, 1, 2; subcultures of hate, 1, 2; trauma and containment, 1; trigger events, 1, 2 Arab people, 1, 2, 3, 4, 5, 6 Arbery, Ahmaud, 1 Arkansas, 1, 2 artificial intelligence (AI), 1, 2, 3, 4 Asian Americans, 1, 2 Asian people, 1, 2, 3, 4 assault, 1, 2, 3 asylum seekers, 1, 2, 3, 4 Athens, 1 Atlanta attack, 1 Atran, Scott, 1, 2 attachment, 1 attention, 1, 2, 3 attitudes, 1, 2, 3, 4, 5, 6 Aung San Suu Kyi, 1 austerity, 1 Australia, 1 autism, 1 averages, 1, 2 avoidance, 1, 2, 3 Bali attack, 1 Bangladeshi people, 1 BBC (British Broadcasting Corporation), 1, 2, 3 behavioural sciences, 1, 2 behaviour change, 1, 2, 3 beliefs, 1, 2, 3 Bell, Sean, 1, 2 Berger, Luciana, 1 Berlin attacks, 1 bias: algorithms, 1; brain and hate, 1, 2, 3, 4, 5, 6, 7; filter bubbles, 1; Google Translate, 1; group threat, 1, 2, 3, 4; police racial bias, 1; predicting hate crime, 1; stopping hate, 1, 2, 3; unconscious bias, 1, 2, 3, 4 Bible, 1 Biden, Joe, 1 ‘Big Five’ personality traits, 1 biology, 1, 2, 3, 4, 5, 6, 7 Birstall, 1 bisexual people, 1 Black, Derek, 1, 2 Black, Don, 1, 2, 3 blackface, 1 Black Lives Matter, 1 Black Mirror, 1n black people: author’s brain and hate, 1, 2, 3, 4, 5; brain and signs of prejudice, 1, 2; brain parts that edge us towards hate, 1; brain parts that process prejudice, 1; Charlottesville rally, 1, 2; disengaging the amygdala autopilot, 1; Duggan shooting, 1; feeling pain, 1; Google searches, 1, 2; group threat, 1, 2, 3, 4; online hate speech, 1, 2, 3, 4; police relations, 1, 2; predicting hate crime, 1, 2; prepared versus learned amygdala responses, 1; pyramid of hate, 1, 2, 3n; recognising facial expressions, 1, 2; South Africa, 1; steps to stop hate, 1, 2, 3, 4; trauma and Franklin, 1, 2, 3, 4; trigger events, 1, 2, 3; unconscious bias, 1; unlearning prejudiced threat detection, 1, 2; white flight, 1 BNP, see British National Party Bolsonaro, Jair, 1 Bosnia and Herzegovina, 1, 2 bots, 1, 2, 3, 4, 5 Bowers, Robert Gregory, 1 boys, 1, 2 Bradford, 1 brain: ancient brains in modern world, 1; author’s brain and hate, 1; beyond the brain, 1; the brain and hate, 1; brain and signs of prejudice, 1; brain damage and tumours, 1, 2, 3, 4; brains and unconscious bias against ‘them’, 1; brain’s processing of ‘gut-deep’ hate, 1; defence mechanisms, 1; disengaging the amygdala autopilot, 1; figures, 1; finding a neuroscientist and brain scanner, 1; group threat detection, 1, 2; hacking the brain to hate, 1; hate and feeling pain, 1; locating hate in the brain, 1; neuroscience and big questions about hate, 1; overview, 1; parts that edge us towards hate, 1; parts that process prejudice, 1; prepared versus learned amygdala responses, 1; recognising facial expressions, 1; rest of the brain, 1; signs of prejudice, 1; steps to stop hate, 1, 2; tipping point to hate, 1, 2, 3, 4, 5; trauma and containment, 1, 2; unlearning prejudiced threat detection, 1; where neuroscience of hate falls down, 1 brain imaging: author’s brain and hate, 1; beyond the brain, 1; the brain and hate, 1; brain and signs of prejudice, 1, 2; brain injury, 1, 2; Diffusion MRI, 1; disengaging the amygdala autopilot, 1; finding a neuroscientist and brain scanner, 1; fusiform face area, 1; locating hate in the brain, 1; MEG, 1; neuroscience of hate, 1, 2, 3; parts that process prejudice, 1; prepared versus learned amygdala responses, 1; processing of ‘gut-deep’ hate, 1; subcultures of hate, 1, 2; unconscious bias, 1 brainwashing, 1, 2 Bray, Mark, 1n Brazil, 1, 2, 3 Breivik, Anders, 1, 2 Brexit, 1, 2, 3, 4n, 5, 6, 7, 8, 9 Brexit Party, 1, 2 Brick Lane, London, 1 Britain First, 1, 2 British identity, 1, 2 British National Party (BNP), 1, 2n, 3, 4, 5 Brixton, 1 Broadmoor Hospital, 1, 2 Brooker, Charlie, 1n Brooks, Rayshard, 1 Brown, Katie, 1, 2 Brown, Michael, 1, 2 Brussels attack, 1 Budapest Pride, 1 bullying, 1, 2 Bundy, Ted, 1 burka, 1, 2, 3 Burmese, 1 Bush, George W., 1 Byrd, James, Jr, 1 California, 1, 2n, 3 Caliskan, Aylin, 1 Cambridge Analytica, 1, 2 cancer, 1, 2 Cardiff University Brain Research Imaging Centre (CUBRIC), 1, 2, 3, 4 caregiving motivational system, 1 care homes, 1, 2 Casablanca, 1 cascade effect, 1, 2 categorisation, 1, 2, 3, 4 Catholics, 1 Caucasian Crew, 1 causality, 1, 2 celebrities, 1, 2, 3, 4 censorship, 1, 2 Centennial Olympic Park, Atlanta, 1 Centers for Disease Control (CDC), 1 change blindness, 1 charity, 1, 2, 3 Charlottesville rally, 1, 2, 3n, 4 chatbots, 1, 2, 3 Chauvin, Derek, 1 Chelmsford, 1 Chicago, 1 childhood: attachment issues, 1; child abuse, 1, 2, 3; child grooming, 1; child play, 1; failures of containment, 1, 2, 3, 4; group threat, 1, 2; intergroup contact, 1, 2; learned stereotypes, 1; online hate speech, 1, 2; predicting hate crime, 1; trauma and containment, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10; trigger events, 1, 2; understanding the ‘average’ hate criminal, 1; understanding the ‘exceptional’ hate offender, 1, 2, 3 China, 1, 2, 3, 4 Chinese people, 1, 2, 3 ‘Chinese virus,’ 1, 2 Cho, John, 1 Christchurch mosque attack, 1 Christianity, 1, 2, 3 cinema, 1 citizen journalism, 1 civilising process, 1 civil rights, 1, 2, 3, 4 class, 1, 2 cleaning, 1 climate change, 1, 2 Clinton, Hillary, 1, 2 cognitive behavioural therapy, 1 cognitive dissonance, 1 Cohen, Florette, 1, 2 Cold War, 1 collective humiliation, 1 collective quests for significance, 1, 2 collective trauma, 1, 2 colonialism, 1n, 2 Combat 1, 2 comedies, 1, 2, 3 Communications Acts, 1, 2 compassion, 1, 2, 3 competition, 1, 2, 3, 4, 5, 6, 7, 8 confirmation bias, 1 conflict, 1, 2, 3, 4 conflict resolution, 1, 2, 3, 4, 5 Connectome, 1 Conroy, Jeffrey, 1 Conservative Party, 1, 2, 3 conspiracy theories, 1, 2, 3 contact with others, 1, 2 containment: failures of, 1; hate as container of unresolved trauma, 1; understanding the ‘exceptional’ hate offender, 1, 2, 3 content moderation, 1, 2, 3 context, 1, 2, 3 Convention of Cybercrime, 1 cooperation, 1, 2, 3, 4, 5, 6 Copeland, David, 1, 2, 3, 4, 5, 6, 7 coping mechanisms, 1, 2, 3, 4, 5, 6, 7 Cordoba House (‘Ground Zero mosque’), 1 correction for multiple comparisons, 1, 2n ‘corrective rape’, 1, 2 cortisol, 1 Council of Conservative Citizens, 1n counter-hate speech, 1, 2, 3, 4 courts, 1, 2, 3, 4, 5, 6 COVID-19 pandemic, 1, 2, 3 Cox, Jo, 1, 2, 3 Criado Perez, Caroline, 1 crime, 1, 2, 3, 4, 5, 6, 7 Crime and Disorder Act 1998, 1n crime recording, 1, 2, 3, 4 crime reporting, 1, 2, 3, 4, 5, 6, 7 Crime Survey for England and Wales (CSEW), 1 criminal justice, 1, 2, 3 Criminal Justice Act, 1, 2n criminal prosecution, 1, 2 criminology, 1, 2, 3, 4, 5, 6 cross-categorisation, 1 cross-race or same-race effect, 1 Crusius, Patrick, 1, 2 CUBRIC (Cardiff University Brain Research Imaging Centre), 1, 2, 3, 4 cultural ‘feeding’, 1, 2, 3, 4, 5 cultural worldviews, 1, 2, 3, 4, 5, 6, 7 culture: definitions, 1; group threat, 1, 2, 3; steps to stop hate, 1, 2, 3; tipping point, 1, 2, 3, 4, 5; unlearning prejudiced threat detection, 1 culture machine, 1, 2, 3, 4, 5 culture wars, 1 Curry and Chips, 1 cybercrime, 1 dACC, see dorsal anterior cingulate cortex Daily Mail, 1, 2 Dailymotion, 1 Daily Stormer, 1, 2n Daley, Tom, 1, 2 Darfur, 1 dark matter, 1 death: events that remind us of our mortality, 1; newspapers, 1; predicting hate crime, 1; religion and hate, 1, 2; subcultures of hate, 1, 2; trigger events, 1, 2 death penalty, 1, 2 death threats, 1 decategorisation, 1 De Dreu, Carsten, 1, 2, 3, 4 deep learning, 1, 2 defence mechanisms, 1 defensive haters, 1, 2 dehumanisation, 1, 2, 3, 4, 5, 6 deindividuation, 1, 2 deindustrialisation, 1, 2, 3, 4 Democrats, 1, 2, 3 Denny, Reginald, 1 DeSalvo, Albert (the Boston Strangler), 1 desegregation, 1, 2, 3 Desmond, Matthew, 1 Dewsbury, 1, 2, 3 Diffusion Magnetic Resonance Imaging (Diffusion MRI), 1, 2 diminished responsibility, 1, 2 Director of Public Prosecutions (DPP), 1 disability: brain and hate, 1, 2; group threat, 1, 2, 3, 4, 5, 6; intergroup contact, 1; Japan care home, 1, 2; online hate speech, 1; profiling the hater, 1; suppressing prejudice, 1; victim perception, 1n Discord, 1, 2, 3, 4 discrimination: brain and hate, 1, 2; comedy programmes, 1; Google searches, 1; Japan laws, 1; preference for ingroup, 1; pyramid of hate, 1, 2, 3; questioning prejudgements, 1; trigger events, 1, 2, 3 disgust: brain and hate, 1, 2, 3, 4, 5, 6; group threat detection, 1, 2, 3; ‘gut-deep’ hate, 1, 2; Japan care home, 1; what it means to hate, 1, 2 disinformation, 1, 2, 3 displacement, 1, 2 diversity, 1, 2, 3 dlPFC, see dorsolateral prefrontal cortex domestic violence, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 Doran, John, 1, 2, 3 dorsal anterior cingulate cortex (dACC), 1, 2, 3n, 4, 5, 6, 7, 8, 9 dorsolateral prefrontal cortex (dlPFC), 1n, 2, 3 Douglas, Mary, Purity and Danger, 1 drag queens, 1 drugs, 1, 2, 3, 4, 5, 6, 7, 8, 9 Duggan, Mark, 1 Duke, David, 1 Dumit, Joe, Picturing Personhood, 1 Durkheim, Emile, 1 Dykes, Andrea, 1 Earnest, John T., 1 Eastern Europeans, 1, 2, 3 Ebrahimi, Bijan, 1, 2, 3, 4, 5, 6 echo chambers, 1, 2n economy, 1, 2, 3, 4, 5, 6 EDL, see English Defence League education, 1, 2, 3, 4 Edwards, G., 1 8chan, 1, 2 elections, 1, 2, 3, 4, 5, 6 electroencephalography, 1n elites, 1 ELIZA (computer program), 1 The Ellen Show, 1 El Paso shooting, 1 Elrod, Terry, 1 Emancipation Park, Charlottesville, 1 Emanuel African Methodist Church, Charleston, 1 emotions: brain and hate, 1, 2, 3, 4n, 5, 6, 7, 8, 9; group threat, 1; subcultures of hate, 1; trigger events and mortality, 1; what it means to hate, 1, 2, 3, 4 empathy: brain and hate, 1, 2, 3, 4, 5, 6; feeling hate together, 1; group threat, 1, 2; steps to stop hate, 1, 2, 3; subcultures of hate, 1; trauma and containment, 1 employment, 1, 2, 3, 4, 5, 6, 7 English Defence League (EDL), 1, 2n, 3 epilepsy, 1, 2, 3, 4, 5 Epstein, Robert, 1 equality, 1, 2 Essex, 1 ethnicity, 1, 2n, 3, 4 ethnic minorities, 1, 2, 3, 4, 5, 6 ethnocentrism, 1 EU, see European Union European Commission, 1, 2 European Digital Services Act, 1 European Parliament, 1, 2 European Social Survey, 1 European Union (EU): Brexit referendum, 1, 2, 3, 4n, 5; Facebook misinformation, 1; group threat, 1, 2; online hate speech, 1, 2, 3; trigger events, 1 Eurovision, 1 evidence-based hate crime, 1 evolution, 1, 2, 3, 4, 5, 6, 7, 8 executive control area: brain and hate, 1, 2, 3, 4, 5, 6, 7, 8; disengaging the amygdala autopilot, 1, 2; extremism, 1; recognising false alarms, 1; trauma and containment, 1; trigger events, 1 exogenous shocks, 1 expert opinion, 1 extreme right, 1, 2, 3, 4, 5 extremism: Charlottesville and redpilling, 1, 2; feeling hate together, 1; online hate speech, 1; perceiving versus proving hate, 1; quest for significance, 1, 2, 3; subcultures of hate, 1, 2, 3, 4, 5, 6, 7; trauma and containment, 1; trigger events, 1, 2, 3 Facebook: algorithms, 1, 2; Charlottesville rally, 1, 2; Christchurch mosque attack, 1; far-right hate, 1, 2, 3, 4, 5; filter bubbles, 1, 2; how much online hate speech, 1, 2; Myanmar genocide, 1; online hate and offline harm, 1, 2, 3; redpilling, 1; stopping online hate speech, 1, 2, 3, 4 facial expression, 1, 2, 3, 4 faith, 1, 2 fake accounts, 1, 2; see also bots fake news, 1, 2, 3, 4 false alarms, 1, 2, 3 Farage, Nigel, 1, 2 far left, 1n, 2, 3, 4 Farook, Syed Rizwan, 1 far right: algorithms, 1, 2, 3, 4; brain injury, 1; Charlottesville rally, 1, 2, 3n, 4; COVID-19 pandemic, 1, 2; Facebook, 1, 2, 3, 4, 5; filter bubbles, 1, 2; gateway sites, 1; group threat, 1, 2; red-pilling, 1; rise of, 1; stopping online hate speech, 1; subcultures of hate, 1, 2, 3, 4, 5; terror attacks, 1, 2, 3; tipping point, 1, 2; trauma and containment, 1, 2, 3, 4n; trigger events, 1, 2; YouTube, 1 fathers, 1, 2, 3 FBI, see Federal Bureau of Investigation fear: brain and hate, 1, 2, 3, 4, 5, 6, 7; feeling hate together, 1; group threat, 1, 2, 3, 4, 5; mortality, 1; online hate speech, 1, 2, 3; steps to stop hate, 1, 2; trauma and containment, 1, 2; trigger events, 1, 2, 3 Federal Bureau of Investigation (FBI), 1, 2, 3, 4, 5, 6, 7 Federation of American Immigration Reform, 1 Ferguson, Missouri, 1 Festinger, Leon, 1 fiction, 1 Fields, Ted, 1 50 Cent Army, 1 ‘fight or flight’ response, 1, 2, 3 films, 1, 2 filter bubbles, 1, 2, 3, 4 Finland, 1, 2, 3, 4, 5, 6 Finsbury Park mosque attack, 1, 2, 3 first responders, 1 Fiske, Susan, 1 Five Star Movement, 1 flashbacks, 1 Florida, 1, 2 Floyd, George, 1, 2, 3 Flynt, Larry, 1 fMRI (functional Magnetic Resonance Imaging), 1, 2, 3, 4, 5, 6, 7 football, 1, 2, 3, 4, 5 football hooligans, 1, 2 Forever Welcome, 1 4chan, 1, 2 Fox News, 1, 2 Franklin, Benjamin, 1 Franklin, Joseph Paul, 1, 2, 3, 4, 5, 6, 7, 8 Fransen, Jayda, 1 freedom fighters, 1, 2 freedom of speech, 1, 2, 3, 4, 5, 6 frustration, 1, 2, 3, 4 functional Magnetic Resonance Imaging (fMRI), 1, 2, 3, 4, 5, 6, 7 fundamentalism, 1, 2 fusiform face area, 1 fusion, see identity fusion Gab, 1 Gadd, David, 1, 2n, 3, 4 Gaddafi, Muammar, 1, 2 Gage, Phineas, 1, 2 galvanic skin responses, 1 Gamergate, 1 gateway sites, 1 gay people: author’s experience, 1, 2, 3; brain and hate, 1, 2; Copeland attacks, 1, 2; COVID-19 pandemic, 1; filter bubbles, 1; gay laws, 1; gay marriage, 1, 2, 3; group associations, 1; group threat, 1, 2, 3, 4, 5; hate counts, 1, 2, 3, 4; physical attacks, 1, 2; profiling the hater, 1; Russia, 1, 2, 3, 4, 5; Section 1, 2, 3, 4; steps to stop hate, 1, 2, 3; trigger events, 1, 2; why online hate speech hurts, 1; see also LGBTQ+ people gay rights, 1, 2, 3, 4 gender, 1, 2, 3, 4, 5, 6, 7 Generation Identity, 1 Generation Z, 1, 2 genetics, 1n, 2, 3 genocide, 1, 2, 3, 4, 5, 6 Georgia (country), 1 Georgia, US, 1, 2, 3, 4 Germany, 1, 2, 3, 4, 5, 6, 7 Gilead, Michael, 1 ginger people, 1 girls, and online hate speech, 1 Gladwell, Malcolm, 1 Global Project Against Hate and Extremism, 1 glucocorticoids, 1, 2 God, 1, 2 God’s Will, 1, 2 Goebbels, Joseph, 1 Google, 1, 2, 3, 4, 5, 6, 7, 8 Google+, 1 Google Translate, 1 goth identity, 1, 2, 3, 4 governments, 1, 2, 3, 4, 5, 6 Grant, Oscar, 1 gravitational waves, 1 Great Recession (2007–9), 1 Great Replacement conspiracy theory, 1 Greece, 1, 2 Greenberg, Jeff, 1, 2, 3 Greene, Robert, 1 grey matter, 1 Grillot, Ian, 1, 2 Grodzins, Morton, 1 grooming, 1, 2, 3 ‘Ground Zero mosque’ (Cordoba House), 1 GroupMe, 1 groups: ancient brains in modern world, 1; brain and hate, 1, 2, 3, 4; childhood, 1; feeling hate together, 1; foundations of prejudice, 1; group threat and hate, 1; identity fusion, 1, 2, 3; intergroup hate, 1; pyramid of hate, 1; reasons for hate offending, 1; steps to stop hate, 1, 2; tipping point, 1, 2, 3, 4; warrior psychology, 1, 2, 3; what it means to hate, 1, 2 group threat, 1; beyond threat, 1; Bijan as the threatening racial other, 1; context and threat, 1; cultural machine, group threat and stereotypes, 1; evolution of group threat detection, 1; human biology and threat, 1; neutralising the perception of threat, 1; overview, 1; society, competition and threat, 1; threat in their own words, 1 guilt, 1, 2, 3, 4 guns, 1, 2 ‘gut-deep’ hate, 1, 2, 3, 4 Haines, Matt, 1 Haka, 1 Halle Berry neuron, 1, 2 harassment, 1, 2, 3, 4, 5 harm of hate, 1, 2, 3, 4, 5, 6, 7 Harris, Brendan, 1 Harris, Lasana, 1 Harris, Lovell, 1, 2, 3, 4 hate: author’s brain and hate, 1; the brain and hate, 1; definitions, 1, 2; feeling hate together, 1; foundations of prejudice and hate, 1, 2, 3; group threat and hate, 1; ‘gut-deep’ hate, 1, 2; hate counts, 1; hate in word and deed, 1; profiling the hater, 1; pyramid of hate, 1; rise of the bots and trolls, 1; seven steps to stop hate, 1; subcultures of hate, 1; tipping point from prejudice to hate, 1; trauma, containment and hate, 1; trigger events and ebb and flow of hate, 1; what it means to hate, 1 hate counts, 1; criminalising hate, 1; how they count, 1; overview, 1; perceiving versus proving hate, 1; police and hate, 1; rising hate count, 1; ‘signal’ hate acts and criminalisation, 1; Sophie Lancaster, 1; warped world of hate, 1 hate crime: author’s experience, 1, 2, 3; brain and hate, 1, 2, 3, 4, 5; definitions, 1; events and hate online, 1; events and hate on the streets, 1, 2; the ‘exceptional’ hate criminal, 1; far-right hate, 1, 2, 3; foundations of prejudice and hate, 1, 2, 3, 4; group threat, 1, 2, 3, 4, 5, 6, 7, 8; hate counts, 1, 2, 3, 4, 5; laws, 1n, 2, 3, 4, 5; number of crimes, 1, 2; online hate speech, 1, 2, 3, 4; predicting hate crime, 1; profiling the hater, 1; steps to stop hate, 1, 2, 3; trauma and containment, 1, 2, 3, 4; trigger events, 1, 2, 3, 4, 5, 6; understanding the ‘average’ hate criminal, 1; understanding the ‘exceptional’ hate offender, 1; what it means to hate, 1, 2, 3 hate groups, 1, 2, 3, 4, 5 hate in word and deed, 1; algorithmic far right, 1; Charlottesville rally, 1, 2, 3n, 4; extreme filter bubbles, 1; game changer for the far right, 1; gateway sites, 1; overview, 1; ‘real life effort post’ and Christchurch, 1; red-pilling, 1 HateLab, 1, 2, 3, 4, 5 hate speech: far-right hate, 1, 2, 3; filter bubbles and bias, 1; harm of, 1; how much online hate speech, 1; Japan laws, 1; pyramid of hate, 1; stopping online hate speech, 1; Tay chatbot, 1; trigger events, 1, 2, 3; why online hate speech hurts, 1 hate studies, 1, 2 ‘hazing’ practices, 1 health, 1, 2, 3, 4 Henderson, Russell, 1 Herbert, Ryan, 1 Hewstone, Miles, 1 Heyer, Heather, 1 Hinduism, 1, 2 hippocampus, 1, 2, 3, 4 history of offender, 1 Hitler, Adolf, 1, 2, 3, 4, 5, 6, 7 HIV/AIDS, 1, 2, 3, 4, 5, 6, 7 hollow mask illusion, 1, 2 Hollywood, 1, 2 Holocaust, 1, 2, 3, 4 Homicide Act, 1n homophobia: author’s experience, 1, 2, 3, 4; brain and hate, 1, 2, 3; evidence-based hate crime, 1; federal law, 1; jokes, 1; online hate speech, 1, 2; Russia, 1, 2; Shepard murder, 1; South Africa, 1; trauma and containment, 1; victim perception of motivation, 1n Homo sapiens, 1 homosexuality: author’s experience, 1; online hate speech, 1; policing, 1; questioning prejudgements, 1; Russia, 1, 2; trauma and containment, 1, 2; see also gay people hooligans, 1, 2 Horace, 1 hormones, 1, 2, 3 hot emotions, 1 hot-sauce study, 1, 2 housing, 1, 2, 3, 4, 5, 6 Huddersfield child grooming, 1 human rights, 1, 2, 3 humiliation, 1, 2, 3, 4, 5, 6 humour, 1, 2 Hungary, 1 hunter-gatherers, 1n, 2 Hustler, 1 IAT, see Implicit Association Test identity: author’s experience of attack, 1; British identity, 1, 2; Charlottesville rally, 1, 2; children’s ingroups, 1; group threat, 1, 2; online hate speech, 1, 2, 3, 4; steps to stop hate, 1, 2 identity fusion: fusion and hateful murder, 1; fusion and hateful violence, 1; fusion and self-sacrifice in the name of hate, 1; generosity towards the group, 1; tipping point, 1, 2; warrior psychology, 1, 2, 3 ideology, 1, 2, 3, 4 illegal hate speech, 1, 2, 3, 4 illocutionary speech, 1 imaging, see brain imaging immigration: Forever Welcome, 1; group threat, 1, 2, 3, 4, 5, 6, 7; hate counts, 1n, 2; HateLab Brexit study, 1; identity fusion, 1; intergroup contact, 1; negative stereotypes, 1; online hate speech, 1; Purinton, 1, 2; trauma and containment, 1, 2, 3; trigger events, 1, 2n, 3, 4, 5, 6, 7; YouTube algorithms, 1 immortality, 1, 2 Implicit Association Test (IAT), 1, 2, 3, 4, 5, 6, 7, 8, 9 implicit prejudice: author’s brain and hate, 1, 2, 3, 4; brain and hate, 1, 2, 3, 4, 5, 6; online hate speech, 1, 2 India, 1 Indonesia, 1 Infowars, 1, 2 Ingersoll, Karma, 1 ingroup: brain and hate, 1, 2, 3, 4; child play, 1; group threat, 1, 2, 3, 4, 5, 6, 7; HateLab Brexit study, 1; identity fusion, 1, 2; pyramid of hate, 1; reasons for hate offending, 1; trigger events, 1, 2, 3; what it means to hate, 1, 2, 3, 4, 5 Instagram, 1, 2, 3 Institute for Strategic Dialogue, 1 institutional racism, 1 instrumental crimes, 1 insula: brain and signs of prejudice, 1, 2, 3; facial expressions, 1, 2; fusiform face area, 1; hacking the brain to hate, 1; hate and feeling pain, 1; neuroscience of hate, 1n, 2, 3, 4, 5; parts that edge us towards hate, 1; parts that process prejudice, 1; processing of ‘gut-deep’ hate, 1, 2 Integrated Threat Theory (ITT), 1, 2, 3 integration, 1, 2, 3, 4 intergroup contact, 1, 2, 3 Intergroup Contact Theory, 1, 2, 3 intergroup hate, 1, 2, 3, 4 internet: algorithms, 1, 2; chatbots, 1; counterhate speech, 1; COVID-19 pandemic, 1; far-right hate, 1, 2, 3, 4, 5, 6, 7; filter bubbles, 1, 2, 3; Google searches, 1; hate speech harm, 1; how much online hate speech, 1; online news, 1; reasons for hate offending, 1; rise of the bots and trolls, 1; stopping online hate speech, 1; tipping point, 1, 2, 3; training the machine to count hate, 1; why online hate speech hurts, 1 interracial relations, 1, 2, 3, 4 intolerance, 1, 2 Iranian bots, 1 Iraq, 1 Irish Republican Army (IRA), 1 ISIS, 1, 2, 3, 4, 5, 6, 7, 8, 9 Islam: group threat, 1; online hate speech, 1, 2, 3, 4, 5; steps to stop hate, 1, 2, 3; subcultures of hate, 1, 2, 3, 4; trigger events, 1, 2, 3 Islamism: group threat, 1; online hate speech, 1, 2, 3, 4; profiling the hater, 1; subcultures of hate, 1, 2, 3; trigger events, 1, 2, 3 Islamophobia, 1, 2, 3, 4 Israel, 1, 2, 3 Italy, 1, 2 ITT, see Integrated Threat Theory James, Lee, 1, 2, 3, 4, 5, 6 Japan, 1, 2, 3 Jasko, Katarzyna, 1 Jefferson, Thomas, 1 Jenny Lives with Eric and Martin, 1 Jewish people: COVID-19 pandemic, 1, 2; far-right hate, 1, 2, 3, 4, 5; filter bubbles, 1; Google searches, 1, 2; group threat, 1; Nazism, 1, 2; negative stereotypes, 1 2 online hate speech, 1; pyramid of hate, 1; questioning prejudgements, 1; ritual washing, 1; subcultures of hate, 1, 2; trauma and Franklin, 1, 2, 3 jihad, 1, 2, 3, 4, 5 jokes, 1, 2, 3, 4, 5, 6, 7 Jones, Alex, 1 Jones, Terry, 1 Josephson junction, 1 Judaism, 1; see also Jewish people Jude, Frank, Jr, 1, 2, 3, 4, 5 Kansas, 1 Kerry, John, 1 Kik, 1 King, Gary, 1 King, Martin Luther, Jr, 1, 2 King, Rodney, 1, 2, 3 King, Ryan, 1 Kirklees, 1, 2 KKK, see Ku Klux Klan Kuchibhotla, Srinivas, 1, 2, 3, 4 Kuchibhotla, Sunayana, 1, 2 Ku Klux Klan (KKK), 1, 2, 3n, 4, 5, 6, 7 Labour Party, 1, 2, 3 Lancaster, Sophie, 1, 2 language, 1, 2, 3, 4, 5, 6, 7 LAPD (Los Angeles Police Department), 1 Lapshyn, Pavlo, 1 Lashkar-e-Taiba, 1 Las Vegas shooting, 1, 2 Latinx people, 1, 2, 3, 4, 5, 6, 7 law: brain and hate, 1, 2, 3; criminalising hate, 1; hate counts, 1, 2, 3; Kansas shooting, 1; limited laws, 1; online hate speech, 1; pyramid of hate, 1 Law Commission, 1 Lawrence, Stephen, 1 learned fears, 1, 2, 3 Leave.EU campaign, 1, 2 Leave voters, 1, 2, 3n Lee, Robert E., 1, 2, 3 left orbitofrontal cortex, 1n, 2n Legewie, Joscha, 1, 2, 3, 4 lesbians, 1, 2 Levin, Jack, 1 LGBTQ+ people, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17; see also gay people LIB, see Linguistic Intergroup Bias test Liberman, Nira, 1 Liberty Park, Salt Lake City, 1, 2 Libya, 1, 2, 3, 4 Light, John, 1 Linguistic Intergroup Bias (LIB) test, 1 Liverpool, 1, 2 Livingstone, Ken, 1, 2 Loja, Angel, 1 London: author’s experience of attack, 1; Copeland nail bombing, 1, 2; Duggan shooting, 1; far-right hate, 1; group threat, 1, 2, 3; online hate speech, 1, 2; Rigby attack, 1; terror attacks, 1, 2, 3, 4, 5, 6 London Bridge attack, 1, 2, 3 London School of Economics, 1 ‘lone wolf’ terrorists, 1, 2, 3, 4 long-term memory, 1, 2, 3, 4 Loomer, Laura, 1 Los Angeles, 1 loss: group threat, 1; subcultures of hate, 1, 2, 3, 4; tipping point, 1; trauma and containment, 1, 2, 3, 4, 5 love, 1, 2 Love Thy Neighbour, 1 Lucero, Marcelo, 1, 2 Luqman, Shehzad, 1 ‘Macbeth effect’, 1 machine learning, 1 Madasani, Alok, 1, 2, 3 Madrid attack, 1, 2 Magnetic Resonance Imaging (MRI): Diffusion MRI, 1, 2; functional MRI, 1, 2, 3, 4, 5, 6, 7 magnetoencephalography (MEG), 1, 2, 3 Maldon, 1 Malik, Tashfeen, 1 Maltby, Robert, 1, 2 Manchester, 1, 2 Manchester Arena attack, 1, 2, 3, 4, 5, 6 marginalisation, 1, 2 Martin, David, 1 Martin, Trayvon, 1, 2 MartinLutherKing.org, 1, 2 martyrdom, 1, 2, 3, 4n masculinity, 1, 2, 3, 4, 5 The Matrix, 1 Matthew Shepard and James Byrd Jr Hate Crimes Prevention Act, 1n, 2n Matz, Sandra, 1 Mauritius, 1 McCain, John, 1 McDade, Tony, 1 McDevitt, Jack, Levin McKinney, Aaron, 1 McMichael, Gregory, 1 McMichael, Travis, 1 media: far-right hate, 1, 2; group threat, 1, 2, 3; steps to stop hate, 1, 2, 3, 4, 5, 6; stereotypes in, 1, 2; subcultures of hate, 1; trigger events, 1 Meechan, Mark, 1 MEG (magnetoencephalography), 1, 2, 3 memory, 1, 2, 3, 4, 5, 6, 7 men, and online hate speech, 1 men’s rights, 1 mental illness, 1, 2, 3, 4, 5, 6 mentalising, 1, 2, 3 meta-analysis, 1 Metropolitan Police, 1 Mexican people, 1, 2, 3, 4 micro-aggressions, 1, 2n, 3, 4, 5, 6 micro-events, 1 Microsemi, 1n Microsoft, 1, 2, 3, 4, 5, 6 micro-targeting, 1, 2 Middle East, 1, 2 migration, 1, 2, 3, 4, 5, 6, 7; see also immigration Milgram, Stanley, 1 military, 1 millennials, 1 Milligan, Spike, 1 Milwaukee, 1, 2, 3 minimal groups, 1 Minneapolis, 1, 2, 3 minority groups: far-right hate, 1, 2; group threat, 1, 2, 3, 4, 5; police reporting, 1; questioning prejudgements, 1; trauma and containment, 1; trigger events, 1, 2 misinformation, 1, 2, 3, 4, 5, 6 mission haters, 1, 2, 3 mobile phones, 1, 2, 3 moderation of content, 1, 2, 3 Moore, Nik, 1 Moore, Thomas, 1 Moores, Manizhah, 1 Moore’s Ford lynching, 1 Moradi, Dr Zargol, 1, 2, 3, 4, 5, 6 Moral Choice Dilemma tasks, 1, 2, 3 moral cleansing, 1, 2, 3 moral dimension, 1, 2, 3, 4 moral outrage, 1, 2, 3, 4, 5 Moroccan people, 1, 2 mortality, 1, 2, 3 mortality salience, 1, 2, 3, 4, 5 Moscow, 1 mosques, 1, 2, 3, 4, 5, 6, 7 Moss Side Blood, 1 mothers, 1, 2, 3, 4, 5, 6 motivation, 1n, 2, 3, 4, 5, 6 Mphiti, Thato, 1 MRI, see Magnetic Resonance Imaging Muamba, Fabrice, 1 multiculturalism, 1, 2, 3, 4 murder: brain injury, 1, 2; group threat, 1, 2, 3; hate counts, 1; identity fusion and hateful murder, 1; police and hate, 1, 2; profiling the hater, 1; trauma and containment, 1, 2, 3, 4, 5 Murdered for Being Different, 1 music, 1, 2, 3 Muslims: COVID-19 pandemic, 1; far-right hate, 1, 2, 3, 4; Google searches, 1; group threat, 1, 2, 3, 4, 5, 6; negative stereotypes, 1; online hate speech, 1, 2; profiling the hater, 1, 2; Salah effect, 1; subcultures of hate, 1, 2, 3; trigger events, 1, 2, 3, 4, 5; and Trump, 1, 2, 3, 4n, 5, 6n Mvubu, Themba, 1 Myanmar, 1, 2 Myatt, David, 1 Nandi, Dr Alita, 1 National Action, 1 National Consortium for the Study of Terrorism and Responses to Terrorism, 1 national crime victimisation surveys, 1, 2 National Front, 1, 2, 3 nationalism, 1, 2 National Socialist Movement, 1, 2, 3, 4 natural experiments, 1, 2 Nature: Neuroscience, 1 nature vs nurture debate, 1 Nazism, 1, 2, 3, 4, 5, 6, 7, 8 NCVS (National Crime Victimisation Survey), 1, 2 negative stereotypes: brain and hate, 1, 2; feeling hate together, 1, 2; group threat, 1, 2, 3, 4, 5, 6; steps to stop hate, 1, 2, 3, 4, 5; tipping point, 1 Nehlen, Paul, 1 neo-Nazis, 1n, 2, 3, 4, 5, 6 Netherlands, 1, 2 Netzwerkdurchsetzungsgesetz (NetzDG) law, 1 neuroimaging, see brain imaging neurons, 1, 2, 3, 4, 5, 6, 7 neuroscience, 1, 2, 3, 4, 5, 6, 7, 8, 9 Newark, 1, 2 news, 1, 2, 3, 4, 5, 6, 7 newspapers, 1, 2, 3, 4 New York City, 1, 2, 3, 4, 5, 6 New York Police Department (NYPD), 1 New York Times, 1, 2 New Zealand, 1 n-grams, 1 Nimmo, John, 1 9/11 attacks, 1, 2, 3, 4, 5, 6, 7 911 emergency calls, 1 Nogwaza, Noxolo, 1 non-independence error, 1, 2n Al Noor Mosque, Christchurch, 1 Northern Ireland, 1 NWA, 1 NYPD (New York Police Department), 1 Obama, Barack, 1n, 2, 3, 4, 5, 6 Occupy Paedophilia, 1 ODIHR, see Office for Democratic Institutions and Human Rights Ofcom, 1 offence, 1, 2, 3, 4 Office for Democratic Institutions and Human Rights (ODIHR), 1, 2 Office for Security and Counter Terrorism, 1 office workers, 1 offline harm, 1, 2 Oklahoma City, 1 O’Mahoney, Bernard, 1 online hate speech: author’s experience, 1; COVID-19 pandemic, 1; far-right hate, 1, 2, 3, 4, 5; hate speech harm, 1; how much online hate speech, 1; individual’s role, 1; law’s role, 1; social media companies’ role, 1; steps to stop hate, 1; tipping point, 1, 2; training the machine to count hate, 1; trigger events, 1 Ono, Kazuya, 1 optical illusions, 1 Organization for Human Brain Mapping conference, 1 Orlando attack, 1 Orwell, George, Nineteen Eighty-Four, 1 Osborne, Darren, 1 ‘other’, 1, 2, 3, 4, 5, 6 Ottoman Empire, 1 outgroup: author’s brain and hate, 1, 2, 3; brain and hate, 1, 2, 3, 4, 5, 6, 7; child interaction and play, 1, 2; evolution of group threat detection, 1; feeling hate together, 1; group threat, 1, 2, 3, 4, 5, 6; ‘gut-deep’ hate, 1; HateLab Brexit study, 1; human biology and threat, 1; identity fusion, 1; prejudice formation, 1; profiling the hater, 1; push/pull factor, 1; pyramid of hate, 1; society, competition and threat, 1; steps to stop hate, 1, 2; tipping point, 1; trauma and containment, 1, 2, 3, 4, 5; trigger events, 1, 2, 3, 4, 5, 6, 7, 8 outliers, 1 Overton window, 1, 2, 3, 4 oxytocin, 1, 2, 3, 4 Paddock, Stephen, 1 Paddy’s Pub, Bali, 1 paedophilia, 1, 2, 3, 4, 5 page rank, 1 pain, 1, 2, 3, 4, 5, 6, 7 Pakistani people, 1, 2, 3, 4, 5 Palestine, 1 pandemics, 1, 2, 3, 4 Papua New Guinea, 1, 2, 3 paranoid schizophrenia, 1, 2 parents: caregiving, 1; subcultures of hate, 1; trauma and containment, 1, 2, 3, 4, 5; trigger events, 1, 2, 3 Paris attack, 1 Parsons Green attack, 1, 2 past experience: the ‘average’ hate criminal, 1; the ‘exceptional’ hate criminal, 1; trauma and containment, 1 perception-based hate crime, 1, 2 perception of threat, 1, 2, 3, 4, 5 perpetrators, 1, 2 personal contact, 1, 2 personality, 1, 2, 3 personality disorder, 1, 2 personal safety, 1, 2 personal significance, 1 perspective taking, 1, 2 PFC, see prefrontal cortex Philadelphia Police Department, 1 Philippines, 1 physical attacks, 1, 2, 3, 4, 5, 6, 7, 8 play, 1 Poland, 1, 2, 3 polarisation, 1, 2, 3, 4, 5 police: brain and hate, 1, 2; Duggan shooting, 1; group threat, 1, 2, 3; and hate, 1; NYPD racial bias, 1; online hate speech, 1, 2, 3, 4; perceiving versus proving hate, 1; police brutality, 1, 2, 3, 4; predicting hate crime, 1; recording crime, 1, 2, 3, 4; reporting crime, 1, 2, 3; rising hate count, 1, 2, 3; ‘signal’ hate acts and criminalisation, 1; steps to stop hate, 1, 2, 3; use of force, 1 Polish migrants, 1 politics: early adulthood, 1; far-right hate, 1, 2; filter bubbles and bias, 1; group threat, 1, 2, 3; online hate speech, 1, 2; seven steps to stop hate, 1, 2, 3, 4; trauma and containment, 1; trigger events, 1, 2, 3, 4, 5; Trump election, 1, 2 populism, 1, 2, 3, 4, 5 pornography, 1 Portugal, 1, 2 positive stereotypes, 1, 2 post-traumatic stress disorder (PTSD), 1, 2, 3, 4, 5 poverty, 1, 2, 3 Poway synagogue shooting, 1 power, 1, 2, 3, 4, 5 power law, 1 predicting the next hate crime, 1 prefrontal cortex (PFC): brain and signs of prejudice, 1; brain injury, 1; disengaging the amygdala autopilot, 1; feeling pain, 1; ‘gut-deep’ hate, 1; prejudice network, 1; psychological brainwashing, 1; recognising false alarms, 1; salience network, 1; trauma and containment, 1; trigger events, 1; unlearning prejudiced threat detection, 1, 2 prehistoric brain, 1, 2 prehistory, 1, 2 prejudgements, 1 prejudice: algorithms, 1; author’s brain and hate, 1, 2, 3, 4, 5, 6, 7; brain and hate, 1, 2, 3, 4, 5, 6, 7; brain and signs of prejudice, 1; cultural machine, 1; far-right hate, 1, 2; filter bubbles and bias, 1; foundations of, 1; Google, 2; group threat, 1, 2, 3, 4, 5, 6, 7, 8, 9; human biology and threat, 1; neuroscience of hate, 1, 2; online hate speech, 1, 2, 3; parts that process prejudice, 1; prejudice network, 1, 2, 3, 4; prepared versus learned amygdala responses, 1; pyramid of hate, 1; releasers, 1, 2; steps to stop hate, 1, 2, 3, 4; tipping point from prejudice to hate, 1; trauma and containment, 1, 2, 3, 4, 5; trigger events, 1, 2, 3, 4, 5, 6, 7, 8; Trump, 1, 2; unconscious bias, 1; unlearning prejudiced threat detection, 1; what it means to hate, 1, 2, 3, 4, 5 prepared fears, 1, 2 Prisoner’s Dilemma, 1 profiling the hater, 1 Proposition 1, 2 ProPublica, 1n, 2 prosecution, 1, 2, 3 Protestants, 1 protons, 1 psychoanalysis, 1 psychological development, 1, 2, 3, 4 psychological profiles, 1 psychological training, 1 psychology, 1, 2, 3, 4 psychosocial criminology, 1, 2 psy-ops (psychological operations), 1 PTSD, see post-traumatic stress disorder Public Order Act, 1 pull factor, 1, 2, 3, 4, 5 Pullin, Rhys, 1n Purinton, Adam, 1, 2, 3, 4, 5, 6, 7 push/pull factor, 1, 2, 3, 4, 5, 6 pyramid of hate, 1, 2 Q …, 1 al-Qaeda, 1, 2 quality of life, 1 queer people, 1, 2 quest for significance, 1, 2, 3 Quran burning, 1 race: author’s brain and hate, 1, 2, 3, 4; brain and hate, 1, 2, 3, 4, 5, 6, 7; brain and signs of prejudice, 1; far-right hate, 1, 2, 3; Google searches, 1; group threat, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10; hate counts, 1, 2, 3; online hate speech, 1; predicting hate crime, 1; pyramid of hate, 1; race relations, 1, 2, 3; race riots, 1, 2; race war, 1, 2, 3, 4, 5; steps to stop hate, 1, 2, 3; trauma and containment, 1, 2, 3, 4n, 5, 6; trigger events, 1, 2; unconscious bias, 1; unlearning prejudiced threat detection, 1 racism: author’s experience, 1; brain and hate, 1, 2, 3, 4, 5, 6; far-right hate, 1, 2; group threat, 1, 2, 3, 4, 5, 6, 7, 8; Kansas shooting, 1; NYPD racial bias, 1; online hate speech, 1, 2, 3, 4; steps to stop hate, 1n, 2, 3; Tay chatbot, 1; trauma and containment, 1, 2, 3, 4, 5, 6, 7; Trump election, 1; victim perception of motivation, 1n; white flight, 1 radicalisation: far-right hate, 1, 2, 3; group threat, 1; subcultures of hate, 1, 2, 3, 4, 5; trigger events, 1 rallies, 1, 2, 3; see also Charlottesville rally Ramadan, 1, 2 rape, 1, 2, 3, 4, 5 rap music, 1 realistic threats, 1, 2, 3, 4, 5 Rebel Media, 1 rebels, 1 recategorisation, 1 recession, 1, 2, 3, 4, 5 recommendation algorithms, 1, 2 recording crime, 1, 2, 3, 4 red alert, 1 Reddit, 1, 2, 3, 4 red-pilling, 1, 2, 3, 4 refugees, 1, 2, 3, 4, 5 rejection, 1, 2, 3, 4, 5, 6 releasers of prejudice, 1, 2 religion: group threat, 1, 2, 3; homosexuality, 1; online hate speech, 1, 2, 3; predicting hate crime, 1; pyramid of hate, 1; religion versus hate, 1; steps to stop hate, 1, 2; subcultures of hate, 1, 2; trauma and containment, 1n, 2; trigger events, 1, 2, 3, 4, 5; victim perception of motivation, 1n reporting crimes, 1, 2, 3, 4, 5, 6, 7 repression, 1 Republicans, 1, 2, 3, 4, 5 research studies, 1 responsibility, 1, 2, 3 restorative justice, 1 retaliatory haters, 1, 2, 3 Reuters, 1 Rieder, Bernhard, 1 Rigby, Lee, 1 rights: civil rights, 1, 2, 3, 4; gay rights, 1, 2, 3, 4; human rights, 1, 2, 3; men’s rights, 1; tipping point, 1; women’s rights, 1, 2 right wing, 1, 2, 3, 4, 5, 6; see also far right Right-Wing Authoritarianism (RWA) scale, 1 riots, 1, 2, 3, 4 risk, 1, 2, 3 rites of passage, 1, 2 rituals, 1, 2, 3 Robb, Thomas, 1 Robbers Cave Experiment, 1, 2, 3, 4, 5, 6 Robinson, Tommy (Stephen Yaxley-Lennon), 1, 2, 3, 4 Rohingya Muslims, 1, 2 Roof, Dylann, 1, 2 Roussos, Saffi, 1 Rudolph, Eric, 1 Rushin, S,, 1n Russia, 1, 2, 3, 4, 5, 6, 7, 8 Russian Internet Research Agency, 1 RWA (Right-Wing Authoritarianism) scale, 1 Rwanda, 1 sacred value protection, 1, 2, 3, 4, 5, 6, 7, 8 Saddam Hussein, 1 safety, 1, 2 Sagamihara care home, Japan, 1, 2 Salah, Mohamed, 1, 2, 3 salience network, 1, 2 salmon, brain imaging of, 1 Salt Lake City, 1 same-sex marriage, 1, 2 same-sex relations, 1, 2, 3 San Bernardino attack, 1n, 2, 3 Scanlon, Patsy, 1 scans, see brain imaging Scavino, Dan, 1n schizophrenia, 1, 2, 3, 4 school shootings, 1, 2 science, 1, 2, 3 scripture, 1, 2 SDO, see Social Dominance Orientation (SDO) scale Search Engine Manipulation Effect (SEME), 1 search queries, 1, 2, 3, 4 Second World War, 1, 2, 3 Section 1, Local Government Act, 1, 2, 3 seed thoughts, 1 segregation, 1, 2, 3 seizures, 1, 2, 3 selection bias problem, 1n self-defence, 1, 2 self-esteem, 1, 2, 3, 4 self-sacrifice, 1, 2, 3 Senior, Eve, 1 serial killers, 1, 2, 3 7/7 attack, London, 1 seven steps to stop hate, 1; becoming hate incident first responders, 1; bursting our filter bubbles, 1; contact with others, 1; not allowing divisive events to get the better of us, 1; overview, 1; putting ourselves in the shoes of ‘others’, 1; questioning prejudgements, 1; recognising false alarms, 1 sexism, 1, 2 sexual orientation, 1, 2, 3, 4, 5, 6, 7 sexual violence, 1, 2, 3, 4, 5 sex workers, 1, 2, 3, 4 Shakespeare, William, Macbeth, 1 shame, 1, 2, 3, 4, 5, 6, 7, 8, 9 shared trauma, 1, 2, 3 sharia, 1, 2 Shepard, Matthew, 1, 2 Sherif, Muzafer, 1, 2, 3, 4, 5, 6, 7 shitposting, 1, 2, 3n shootings, 1, 2, 3, 4, 5, 6, 7, 8 ‘signal’ hate acts, 1 significance, 1, 2, 3 Simelane, Eudy, 1 skin colour, 1, 2, 3n, 4, 5, 6, 7 Skitka, Linda, 1, 2 slavery, 1 Slipknot, 1 slurs, 1, 2, 3, 4, 5, 6 Snapchat, 1 social class, 1, 2 social desirability bias, 1, 2 Social Dominance Orientation (SDO) scale, 1 social engineering, 1 socialisation, 1, 2, 3, 4, 5 socialism, 1, 2 social media: chatbots, 1; COVID-19 pandemic, 1; far-right hate, 1, 2, 3, 4; filter bubbles and bias, 1; HateLab Brexit study, 1; online hate speech, 1, 2, 3, 4, 5; online news, 1; pyramid of hate, 1; steps to stop hate, 1, 2, 3; subcultures of hate, 1; trigger events, 1, 2; see also Facebook; Twitter; YouTube Social Perception and Evaluation Lab, 1 Soho, 1 soldiers, 1n, 2, 3 Sorley, Isabella, 1 South Africa, 1 South Carolina, 1 Southern Poverty Law Center, 1n, 2 South Ossetians, 1 Soviet Union, 1, 2 Spain, 1, 2, 3 Spencer, Richard B., 1 Spengler, Andrew, 1, 2, 3, 4 SQUIDs, see superconducting quantum interference devices Stacey, Liam, 1, 2 Stanford University, 1 Star Trek, 1, 2, 3 statistics, 1, 2, 3, 4, 5, 6, 7, 8 statues, 1 Stephan, Cookie, 1, 2 Stephan, Walter, 1, 2 Stephens-Davidowitz, Seth, Everybody Lies, 1 Stereotype Content Model, 1 stereotypes: brain and hate, 1, 2, 3, 4, 5, 6, 7; cultural machine, group threat and stereotypes, 1; definitions, 1; feeling hate together, 1, 2; group threat, 1, 2, 3, 4; homosexuality, 1; NYPD racial bias, 1; steps to stop hate, 1, 2, 3, 4, 5; study of prejudice, 1; tipping point, 1; trigger events, 1 Stoke-on-Trent, 1, 2 Stormfront website, 1, 2, 3 storytelling, 1 stress, 1, 2, 3, 4, 5, 6, 7, 8 striatum, 1, 2, 3n, 4 subcultures, 1, 2, 3, 4, 5 subcultures of hate, 1; collective quests for significance and extreme hate, 1; extremist ideology and compassion, 1; fusion and generosity towards the group, 1; fusion and hateful murder, 1; fusion and hateful violence, 1; fusion and self-sacrifice in the name of hate, 1; quest for significance and extreme hatred, 1; religion/belief, 1; warrior psychology, 1 subhuman, 1, 2 Sue, D.

Like, Comment, Subscribe: Inside YouTube's Chaotic Rise to World Domination by Mark Bergen

23andMe, 4chan, An Inconvenient Truth, Andy Rubin, Anne Wojcicki, Big Tech, Black Lives Matter, book scanning, Burning Man, business logic, call centre, Cambridge Analytica, citizen journalism, cloud computing, Columbine, company town, computer vision, coronavirus, COVID-19, crisis actor, crowdsourcing, cryptocurrency, data science, David Graeber, DeepMind, digital map, disinformation, don't be evil, Donald Trump, Edward Snowden, Elon Musk, fake news, false flag, game design, gender pay gap, George Floyd, gig economy, global pandemic, Golden age of television, Google Glasses, Google X / Alphabet X, Googley, growth hacking, Haight Ashbury, immigration reform, James Bridle, John Perry Barlow, Justin.tv, Kevin Roose, Khan Academy, Kinder Surprise, Marc Andreessen, Marc Benioff, Mark Zuckerberg, mass immigration, Max Levchin, Menlo Park, Minecraft, mirror neurons, moral panic, move fast and break things, non-fungible token, PalmPilot, paypal mafia, Peter Thiel, Ponzi scheme, QAnon, race to the bottom, recommendation engine, Rubik’s Cube, Salesforce, Saturday Night Live, self-driving car, Sheryl Sandberg, side hustle, side project, Silicon Valley, slashdot, Snapchat, social distancing, Social Justice Warrior, speech recognition, Stanford marshmallow experiment, Steve Bannon, Steve Jobs, Steven Levy, surveillance capitalism, Susan Wojcicki, systems thinking, tech bro, the long tail, The Wisdom of Crowds, TikTok, Walter Mischel, WikiLeaks, work culture

Senator Mark Warner, a Virginia Democrat, called YouTube RT’s “go-to platform” and a “target-rich environment for any disinformation campaign.” YouTube, feeling the heat, removed RT from its premium slate and added labels for all state-backed media outlets. Yet just as pressure on YouTube mounted, Facebook tripped again. Four days after Wojcicki was grilled in Texas over conspiracies, the Cambridge Analytica scandal broke. A consulting firm had scraped Facebook data to make psychological profiles for Trump’s campaign. Outrage and attention turned back on the social network. Google found it best to lie low. Perhaps this reflected the temperament of its leader. Pichai, Google’s soft-spoken, ruminative CEO, vastly preferred consensus over confrontation.

…

See also problematic/troubling content Botha, Roelof, 29–30, 36, 50, 53 Boutin, Paul, 47 boycotts, advertisers, 283–90, 295, 300, 308, 329 brand and aesthetic of YouTube and “Our Brand Mission” video, 4–5 and premium content ambition, 73–75, 126–27, 210, 391 skateboarding bulldog as representative of, 77, 126, 139 Brandcast, 210 brand pages, 68 Breitbart News, 263, 273 Brexit, 264 Bridle, James, 312–13 Brin, Sergey and advertising, 108 on collective memory function of YouTube, 384 and Friday staff meetings, 81–82 and Google’s acquisition of YouTube, 53, 54, 59 and Google’s origins, 45 marriage and divorce of, 197, 200–201 at post-election staff meeting, 272, 273 retirement of, 401 and searchable TV database project, 96–97 and shooting at San Bruno offices, 337 and Snowden, 230 and Viacom lawsuit, 99 and Wojcicki, 199 Brodack, Brooke “Brookers,” 26–27, 40, 49, 98 Brolsma, Gary, 27 Brown, Dan, 120 Buckley, Michael, 115 bullying problem at YouTube, 262–63 Burnett, Mark, 124–25 Bush, George W., 82, 83 business unit of YouTube, 68–69 BuzzFeed, 190, 218 Byrne, Jamie, 181, 282–83, 287, 288, 290 C Cain, Caleb, 193, 222, 225 Cambridge Analytica scandal, 341 Campaign for a Commercial-Free Childhood, 243 Campbell, Bill, 202 Carl, Shay, 112, 278 Carle, John, 322 Carl’s Jr. promotions, 110, 111, 112 Carrico, Jennifer, 32 car videos, 58, 67, 99–100 CBS television network, 76 censorship, 84, 144, 215–16, 268, 340, 342.

…

See also Zappin, Danny Dickson, Marion, 10 Digg, 95 Digital Millennium Copyright Act (DMCA, 1998), 35, 36, 37, 61, 99 Disney content on YouTube, 242–43 and Frozen (film), 241–42 Maker Studios acquired by, 219, 242 and PewDiePie/Kjellberg, 219, 278 and success of YouTube model, 210 YouTube’s attempt to partner with, 130 and Zappin, 107 DisneyCollectorBR, 171–73, 174, 239, 242 DistBelief, 232 diversity, 301, 302, 344 do-it-yourself crafting, 57 dollar-sign indicators for creators, 268 domain for YouTube.com, 16 Donahue, Kevin, 28–29, 66–67, 168–69 Donaldson, Jimmy, 353 Donovan Data Systems, 74 Donovan, Lisa, 106–7, 186 Dorsey, Jack, 397 DoubleClick Incorporated, 70–71, 75, 197, 198, 257, 284 Douek, Evelyn, 398 Downs, Juniper, 281 doxing problem at YouTube, 262–63 DreamWorks, 210 Drudge Report, 270 Drummond, David, 215, 216 Ducard, Malik, 378 Dynamic Ad Loads (Dallas), 191–92, 194 E eBaum’s World, 21 eBay, 52 echo chambers of YouTube, 265–66, 299 edgelords, 275–76, 383 EduTubers, 170, 245, 246 egalitarianism prioritized at YouTube, 164, 180, 194 Egypt, 137–38, 141–42, 143 Electronic Frontier Foundation (EFF), 37, 215 Elizabeth II, Queen of Great Britain, 92, 126 Elsa, people dressed as, 305–7, 309, 312 Elsagate, 314, 321 employees of YouTube contract employees, 317–20, 327, 349 diversity hiring in, 301 as parents, 174 and perks at YouTube offices, 148 poached from Yahoo, 52 and Wojcicki, 211–13 engagement of users emphasis placed on, 154, 158–59 (see also watch time of audience) and machine learning applied to advertising, 191 payments based on (Moneyball proposal), 337–38, 341 strain related to goals for, 203 See also comments and comment section; likes Equals Three (=3) production company, 120 Europe, 340, 365, 371 European Parliament, 215–16 EvanTubeHD, 237–38 Ezarik, Justine (iJustine), 40, 78, 95, 110, 119, 392 F Facebook advertising on, 252, 284 and Arab Spring, 142 boycotts of, 382 Cambridge Analytica scandal, 341 Chen’s employment with, 24 competition of YouTube with, 264–65 and COVID-19 misinformation, 397, 398 criticisms of, 366 engagement of users, 154 as global public square, 142 growth/popularity of, 93, 138, 146, 284 “Like” button, 138 as media company, 285–86 “move fast and break things” motto of, 309 and New Zealand terrorist attack, 10, 358, 359 political quagmires of, 340, 391, 397 recruitment of creators, 390 and Russian agents, 326–27, 340 Russia’s blocking of, 397 and Sandberg, 195 screeners at, 319 and Stapleton, 81 Steyer’s distrust in, 402 struggles for relevancy, 6 and Trump, 370 users leaving platform, 394 and video, 210, 251, 264–65 YouTube clips shared on, 251 faceless channels, 171–72 “fake news,” 399 fakes on YouTube, 144–45 “false flags,” 326 fashion industry, 189 Fast Company, 299–300 Federal Communications Commission (FCC), 168, 224 Federal Trade Commission (FTC), 168, 243, 368, 394 “Feet for Hands” (Smosh), 67 feminism, 223, 224, 225 fetish, borderline, 309, 310 Figglehorn, Fred (Cruikshank), 65–66, 69, 77–78, 131, 169 financials of YouTube crossing $1 billion in revenue, 126 and expectation of profitability, 93–94 and first profit of YouTube, 50 funding from Sequoia Capital, 29–30, 50 and Google’s priorities for YouTube, 68 impact of changed algorithm on, 159 and monetization of YouTube, 66–67, 93–94, 96 money lost by YouTube, 93 and PewDiePie, 8–9 revenue goals of Wojcicki, 252, 382 and videos eligible for advertising, 110 “Finger Family” videos, 239–40, 312 Finland, mass shooting in (2007), 64 flagged content, 165 Flannery, Michele, 94, 95, 101 Flash, 21, 24 flat-earth videos, 299, 328 Flickr, 17, 18 Flinders, Mesh, 41–42 Floyd, George, 378, 384 Foley, James, decapitation of, 213, 215 Forbes, 29 founders of YouTube, 26.

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. But if someone is on welfare[,] he has negative value.

…

None of these fights is easy; as I finish this manuscript, the Trump administration has just announced a new attack on the Endangered Species Act, on the grounds that it “impedes people’s livelihood.”2 But in a world where algorithms are starting to take over, where Facebook and Amazon know us much too well, these self-imposed limits help keep us human. Our great literary conscience, the Kentucky farmer-writer Wendell Berry, said it best, long before anyone had heard of Cambridge Analytica: Love the quick profit, the annual raise, vacation with pay. Want more of everything ready-made. Be afraid to know your neighbors and to die. And you will have a window in your head. Not even your future will be a mystery any more. Your mind will be punched in a card and shut away in a little drawer.

…

Black Star Energy bluefin tuna Blue Origin Blue Planet II (TV series) Boeing Bolshevik Revolution Bonds, Barry Borkowski, Sara and Mark Borsook, Paulina Boston Bostrom, Nick Box, Jason BP Branden, Nathaniel Brannen, Peter Branson, Richard Brazil Breakout Labs Breashears, David Brevard County Historical Commission Brexit Breyer, Christian Brin, Sergey Britain British Columbia Broad Institute Brodie, Jon bubonic plague Buchanan, James McGill Buddha Bunyan, Paul Burgess, Seth Burns, Jennifer Bush, George H. W. Bush, George W. BusinessWeek Cairo Calcutta Calico California floods and wildfires and Cambrian explosion Cambridge Analytica campaign finance Canada cancer Cape Canaveral Cape Cod Cape of Good Hope Cape Town capitalism carbon cap-and-trade carbon dioxide emissions Bush, G.W., and cognitive ability and drought and extinctions and heat trapping and increase in natural gas vs. coal and nutrients in crops and oceans and oil industry research and permafrost and rainfall and reducing U.S. footprint and sea level and “Carbon Dioxide: They Call It Pollution” (TV ad) carbon taxes Cargill Carnegie, Andrew Carson, Rachel Carter, Clint Cas9 enzyme cattle ranching cedars of Lebanon Center for Genetics and Society Center for Libertarian Studies Center for the Study of Public Choice Centers for Disease Control cereals CertainTeed Corporation Charpentier, Emmanuelle Chattanooga, Tennessee Chaucer, Geoffrey chemotherapy Cheney, Dick Chevron Oil China chlorination chlorofluorocarbons choice Christianity Church, George Churchill, Canada Churchill, Winston CIMON (Crew Interactive Mobile CompaniON) Citizens United civil disobedience civil rights movement Clean Air Act Clean Water Act Cleveland Clinic climate change.

Messing With the Enemy: Surviving in a Social Media World of Hackers, Terrorists, Russians, and Fake News by Clint Watts

4chan, active measures, Affordable Care Act / Obamacare, barriers to entry, behavioural economics, Bellingcat, Berlin Wall, Bernie Sanders, Black Lives Matter, Cambridge Analytica, Chelsea Manning, Climatic Research Unit, crowdsourcing, Daniel Kahneman / Amos Tversky, disinformation, Donald Trump, drone strike, Edward Snowden, en.wikipedia.org, Erik Brynjolfsson, failed state, fake news, Fall of the Berlin Wall, false flag, Filter Bubble, global pandemic, Google Earth, Hacker News, illegal immigration, information security, Internet of things, Jacob Silverman, Julian Assange, loss aversion, Mark Zuckerberg, Mikhail Gorbachev, mobile money, mutually assured destruction, obamacare, Occupy movement, offshore financial centre, operational security, pre–internet, Russian election interference, Sheryl Sandberg, side project, Silicon Valley, Snapchat, Steve Bannon, the long tail, The Wisdom of Crowds, Turing test, University of East Anglia, Valery Gerasimov, WikiLeaks, Yochai Benkler, zero day

If social media users believe that the core’s agenda is their own preference, they’ll wholeheartedly support an idea, a politician, or an organization. Social media nations and their members will cast doubt on experts who oppose the hidden core, insulate themselves from challengers through clickbait populism, and unwittingly support policies detrimental to their own well-being. In some ways this has already happened, with companies like Cambridge Analytica and the propaganda machine of Steve Bannon coming together during the election of 2016 to convince poor, working-class southern and midwestern whites to vote for a New York City real estate developer and reality TV star named Donald Trump. The “hidden core” conducting social inception will win over key influencers by mapping their every purchase, chat, post, and picture, creating a targeting profile to nudge unwitting “useful idiots”—those enticed by money and ego—to advance scripted narratives.

…

The video had been sped up and the reporter’s comments had been removed.38 The rapid proliferation of social media disinformation was expected, but rapid proliferation of social media disinformation from the White House was not. If America can’t count on the commander in chief to do the right thing, we most certainly can’t expect everyone else to do much better. The best disinformation peddlers in the future will have three distinct technological advantages over those that came before them. Cambridge Analytica demonstrated how the aggregation of user data provided deep insights for nimbly targeting and influencing selected audience members. Future firms and campaigns able to employ machine learning to mine and connect user data across nearly all aspects of a person’s daily life. Knowing individualized, intimate details will enable the best tech-enabled manipulators to subtly nudge social media users in undetectable ways.

…

Republicans already openly push for their own apps to bring supporters to an online world of their own design. The National Rifle Association, the pro-Trump political action committee America First, and Senator Ted Cruz’s Cruz Crew seek a conservative social media world similar to their Fox News television universe.43 Curiously, Cambridge Analytica cofounder and former Trump adviser Steve Bannon not only echoes these sentiments but called for nationalizing Facebook.44 For me, this seems like an odd position for a voracious capitalist who seeks the end of the administrative state. Taking down the tech giants opens enormous space for the strongest manipulators to take hold of unwitting minds; Bannon would be one of those best positioned to gain from their demise.

Artificial Whiteness by Yarden Katz

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

Glenn Greenwald, No Place to Hide: Edward Snowden, the NSA, and the US Surveillance State (New York: Macmillan, 2014).     7.   Shoshana Zuboff, “Big Other: Surveillance Capitalism and the Prospects of an Information Civilization,” Journal of Information Technology 30, no. 1 (2015): 75–89.     8.   See the controversy surrounding Cambridge Analytica as reported, for instance, in “Cambridge Analytica Files,” Guardian, https://www.theguardian.com/news/series/cambridge-analytica-files.     9.   Nick Bilton, “Google Buys A.I. Company for Search, Not Robots,” New York Times, January 28, 2014.   10.   David Ignatius, “A Tech Bridge from the Pentagon to Silicon Valley,” Washington Post, January 25, 2019.   11.   

Rentier Capitalism: Who Owns the Economy, and Who Pays for It? by Brett Christophers

"World Economic Forum" Davos, accounting loophole / creative accounting, Airbnb, Amazon Web Services, barriers to entry, Big bang: deregulation of the City of London, Big Tech, book value, Boris Johnson, Bretton Woods, Brexit referendum, British Empire, business process, business process outsourcing, Buy land – they’re not making it any more, call centre, Cambridge Analytica, Capital in the Twenty-First Century by Thomas Piketty, Cass Sunstein, cloud computing, collective bargaining, congestion charging, corporate governance, data is not the new oil, David Graeber, DeepMind, deindustrialization, Diane Coyle, digital capitalism, disintermediation, diversification, diversified portfolio, Donald Trump, Downton Abbey, electricity market, Etonian, European colonialism, financial deregulation, financial innovation, financial intermediation, G4S, gig economy, Gini coefficient, Goldman Sachs: Vampire Squid, greed is good, green new deal, haute couture, high net worth, housing crisis, income inequality, independent contractor, intangible asset, Internet of things, Jeff Bezos, Jeremy Corbyn, Joseph Schumpeter, Kickstarter, land bank, land reform, land value tax, light touch regulation, low interest rates, Lyft, manufacturing employment, market clearing, Martin Wolf, means of production, moral hazard, mortgage debt, Network effects, new economy, North Sea oil, offshore financial centre, oil shale / tar sands, oil shock, patent troll, pattern recognition, peak oil, Piper Alpha, post-Fordism, post-war consensus, precariat, price discrimination, price mechanism, profit maximization, proprietary trading, quantitative easing, race to the bottom, remunicipalization, rent control, rent gap, rent-seeking, ride hailing / ride sharing, Right to Buy, risk free rate, Ronald Coase, Rutger Bregman, sharing economy, short selling, Silicon Valley, software patent, subscription business, surveillance capitalism, TaskRabbit, tech bro, The Nature of the Firm, transaction costs, Uber for X, uber lyft, vertical integration, very high income, wage slave, We are all Keynesians now, wealth creators, winner-take-all economy, working-age population, yield curve, you are the product

But data are not often sold, even by Facebook: as the New York Times pointed out to its readers in the wake of the Cambridge Analytica scandal – in which the political data firm hired by Donald Trump’s 2016 election campaign controversially gained access to private information on more than 50 million Facebook users – Facebook does not allow user data ‘to be sold or transferred “to any ad network, data broker or other advertising or monetization-related service” ’.20 This, Facebook argued, was exactly what Dr Aleksandr Kogan, an academic at Cambridge University, had done in providing the information to Cambridge Analytica. And as the Economist also noted, the reasons why platform operators, for all their expertise in making markets, have generally not been making markets in data, are readily explicable: This absence of markets is the result of the same factors that have given rise to firms.

…

Zuboff, The Age of Surveillance Capitalism (London: Profile, 2019). 18. ‘Datafication’ is the term used by Jathan Sadowski in his ‘When Data Is Capital: Datafication, Accumulation, and Extraction’, Big Data & Society, doi: 10.1177/2053951718820549. 19. Economist, ‘Data Is Giving Rise to a New Economy’, 6 May 2017. 20. K. Granville, ‘Facebook and Cambridge Analytica: What You Need to Know as Fallout Widens’, New York Times, 19 March 2018. 21. Economist, ‘Data Is Giving Rise to a New Economy’. See also T. Hale, ‘Data Is Not the New Oil’, 8 May 2019, at ftalphaville.ft.com. 22. We Are Social, ‘Digital in 2018’, January 2018, pp. 126, 128 – pdf available at digitalreport.wearesocial.com. 23.

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See BT Group Britoil, 282, 450n5 Broadberry, Stephen, 19 Brotherstone, Terry, 129, 131 Broughton, Andrea, 319 Brown, Bonnie, 214–215 Brown, Gordon, 55–56 Brown, Wendy, 127 BT Group, 7; as multidimensional rentier, 8; contract rents and, 256–257; increasing competition to, in mobile telephony, 295; infrastructure monopoly of, 295–300, 303–304; infrastructure rents and, 288, 324; intellectual property of, 146, 148, 162; Openreach division, 298–300, 303–304, 324, 415–416; price controls and, 314; privatization of, 282, 284, 293, 295 Build to Rent, 338 Bunn, Philip, 79 Bunzl, 9 Burkhauser, Richard, 43 Business, Innovation and Skills Select Committee, 153, 285 buy to let mortgage, 342 Cabinet Office, 246 Cable & Wireless, 282, 450n5 Cadent Gas, 288, 293–294 Cadogan, Charles Gerald John, 363, 364 Cadogan Estates, 363 Cahill, Kevin, 328 Cambridge Analytica, 195, 196 Cameron, David, 35, 49, 153 Canada Pension Plan Investment Board, xv, 294 Canary Wharf Group, 356, 357–358 Cant, Callum, 443n78 Capgemini, 249, 259 Capita, 233, 239, 248–250, 264, 268–269, 271 Capital (Marx), 29, 30–31, 51, 331 Capital and Ideology (Piketty), xxviii capital expenditure, 244–246 capital gains tax (CGT), 26–27, 60–61, 350, 427n74, 458n66 Capital in the Twenty-First Century (Piketty), xix, xxvii, 45, 391 capital platforms, 184–187 Capitalism, Socialism and Democracy (Schumpeter), 31–32 capitalization (finance), 56 capitalized land rents, 329–330, 332, 360 carbon democracy, 127 Carillion, 247, 258, 263, 264, 449n100 Carlyle private equity group, 219–220 Catalano, Alejandrina, 81, 358, 366 Cave, Tamasin, 113–114 Celador, 162 Central Arbitration Committee, 272 Central Electricity Generating Board, 282 Centre for Health and the Public Interest (CHPI), 261–262, 267, 269 Centrica, 9, 416 Chakrabortty, Aditya, 219–220, 264, 273, 404, 406 Chamberlin, Edward, 139–141, 150 Chartered Institute of Personnel and Development, 41 Chicago School of law and economics, 25–26, 387 Christensen, John, 61–62 Churchill, Winston, 351 Cisco, 227 Citigroup, 227 citizen petitions, 175 Citizens’ Wealth Fund, 404 City of London, 22–23, 50, 55–56, 61, 63 Civil Aviation Authority (CAA), 313–314 civilization, 64, 384–385 CK Hutchison, 294–297 CK Infrastructure Holdings, 294 The Cleaners (documentary), 215 Clegg, Nick, 202 climate change, 131–136 Clinical Commissioning Group, 243, 267 Cogan, Douglas, 133 Cohen, Nick, 383 Colbourn, John, 159 collateral rehypothecation, 58–59 Collier, Ruth, 217 Collinson, Patrick, 333 Comcast, 11 commercial property, 338–339, 350, 357, 364 commissions.

21 Lessons for the 21st Century by Yuval Noah Harari

"World Economic Forum" Davos, 1960s counterculture, accounting loophole / creative accounting, affirmative action, Affordable Care Act / Obamacare, agricultural Revolution, algorithmic trading, augmented reality, autonomous vehicles, Ayatollah Khomeini, basic income, behavioural economics, Bernie Sanders, bitcoin, blockchain, Boris Johnson, Brexit referendum, call centre, Cambridge Analytica, Capital in the Twenty-First Century by Thomas Piketty, carbon tax, carbon-based life, Charlie Hebdo massacre, cognitive dissonance, computer age, computer vision, cryptocurrency, cuban missile crisis, decarbonisation, DeepMind, deglobalization, disinformation, Donald Trump, Dr. Strangelove, failed state, fake news, Filter Bubble, Francis Fukuyama: the end of history, Freestyle chess, gig economy, glass ceiling, Google Glasses, illegal immigration, Intergovernmental Panel on Climate Change (IPCC), Internet of things, invisible hand, job automation, knowledge economy, liberation theology, Louis Pasteur, low skilled workers, Mahatma Gandhi, Mark Zuckerberg, mass immigration, means of production, Menlo Park, meta-analysis, Mohammed Bouazizi, mutually assured destruction, Naomi Klein, obamacare, pattern recognition, post-truth, post-work, purchasing power parity, race to the bottom, RAND corporation, restrictive zoning, Ronald Reagan, Rosa Parks, Scramble for Africa, self-driving car, Silicon Valley, Silicon Valley startup, TED Talk, transatlantic slave trade, trolley problem, Tyler Cowen, Tyler Cowen: Great Stagnation, universal basic income, uranium enrichment, Watson beat the top human players on Jeopardy!, zero-sum game

Once politicians can press our emotional buttons directly, generating anxiety, hatred, joy and boredom at will, politics will become a mere emotional circus. As much as we should fear the power of big corporations, history suggests that we are not necessarily better off in the hands of over-mighty governments. As of March 2018, I would prefer to give my data to Mark Zuckerberg than to Vladimir Putin (though the Cambridge Analytica scandal revealed that perhaps there isn’t much of a choice here, as any data entrusted to Zuckerberg may well find its way to Putin). Private ownership of one’s own data may sound more attractive than either of these options, but it is unclear what it actually means. We have had thousands of years of experience in regulating the ownership of land.

…

His ultimate goal is ‘to help 1 billion people join meaningful communities … If we can do this, it will not only turn around the whole decline in community membership we’ve seen for decades, it will start to strengthen our social fabric and bring the world closer together.’ This is such an important goal that Zuckerberg vowed ‘to change Facebook’s whole mission to take this on’.3 Zuckerberg is certainly correct in lamenting the breakdown of human communities. Yet several months after Zuckerberg made his vow, and just as this book was going to print, the Cambridge Analytica scandal revealed that data entrusted to Facebook was harvested by third parties and used to manipulate elections around the world. This made a mockery of Zuckerberg’s lofty promises, and shattered public trust in Facebook. One can only hope that before undertaking the building of new human communities, Facebook first commits itself to protecting the privacy and security of existing communities.

…

Abbasid caliphs 94 Abraham, prophet 182–3, 186, 187, 274 advertising 36, 50, 53, 54, 77–8, 87, 97, 113, 114, 267 Afghanistan 101, 112, 153, 159, 172, 210 Africa 8, 13, 20, 58, 76, 79, 100, 103–4, 107, 139, 147, 150–1, 152, 168, 182, 184, 223, 226, 229, 239 see also under individual nation name African Americans 67, 150, 152, 227 agriculture 171, 185; animals and 71, 118–19, 224; automation of jobs in 19–20, 29; climate change and modern industrial 116, 117; hierarchical societies and birth of 73–4, 185, 266–7; religion and 128–30 Aisne, third Battle of the (1918) 160 Akhenaten, Pharaoh 191 Al-Aqsa mosque, Jerusalem 15 al-Baghdadi, Abu Bakr 98 Algeria 144, 145 algorithms see artificial intelligence (AI) Ali, Husayn ibn 288 Alibaba (online retailer) 50 Allah 104, 128, 130, 204, 271–2, 289 AlphaZero 31, 123 al-Qaeda 162, 168 Amazon (online retailer) 39, 40, 50, 52, 91, 267–8 Amazon rainforest 116 Amos, prophet 188 Amritsar massacre (1919) 10 Andéol, Emilie 102 animals xi, 73, 86, 98–9, 182, 190, 218, 245; distinct social behaviours 94–5; ecological collapse and 71, 116, 118–19, 224; farm animals, subjugation of 71, 118–19, 224; morality and 187–8, 200; religious sacrifice of 190 anti-Semitism 142, 143, 194, 195, 235–6 see also Jews Apple (technology company) 91, 178 Arab Spring xi, 91 Arjuna (hero of Bhagavadgita) 269–70, 271, 299 art, AI and 25–8, 55–6, 182 artificial intelligence (AI) xiii, xiv; art and 25–8, 55–6, 182; authority shift from humans to 43, 44–72, 78, 268; biochemical algorithms and 20, 21, 25–8, 47–8, 56, 59, 251, 299; cars and see cars; centaurs (human-AI teams) 29, 30–1; communism and 35, 38; consciousness and 68–72, 122, 245–6; creativity and 25–8, 32; data ownership and 77–81; dating and 263; decision-making and 36–7, 50–61; democracy and see democracy; digital dictatorships and xii, 43, 61–8, 71, 79–80, 121; discrimination and 59–60, 67–8, 75–6; education and 32, 34, 35, 38 39, 40–1, 259–68; emotional detection/manipulation 25–8, 51–2, 53, 70, 79–80, 265, 267; equality and xi, 8, 9, 13, 41, 71–2, 73–81, 246; ethics and 56–61; free will and 46–9; games and 29, 31–2, 123; globalisation and threat of 38–40; government and xii, 6, 7–9, 34–5, 37–43, 48, 53, 61–8, 71, 77–81, 87, 90, 121, 267, 268; healthcare and 22–3, 24–5, 28, 48–9, 50; intuition and 20–1, 47; liberty and 44–72; manipulation of human beings 7, 25–8, 46, 48, 50–6, 68–72, 78, 79–80, 86, 96, 245–55, 265, 267, 268; nationalism and 120–6; regulation of 6, 22, 34–5, 61, 77–81, 123; science fiction and 245–55, 268; surveillance systems and 63–5; unique non-human abilities of 21–2; war and 61–8, 123–4 see also war; weapons and see weapons; work and 8, 18, 19–43 see also work Ashoka, Emperor of India 191–2, 286 Ashura 288, 289 Asia 16, 39, 100, 103, 275 see also under individual nation name Assyrian Empire 171 Athenian democracy, ancient 95–6 attention, technology and human 71, 77–8, 87, 88–91 Australia 13, 54, 116, 145, 150, 183, 187, 232–3 Aztecs 182, 289 Babri Mosque, Ayodhya 291 Babylonian Empire 188, 189 Baidu (technology company) 23, 40, 48, 77, 267–8 Bangladesh 38–9, 273 bank loans, AI and 67 behavioural economics 20, 147, 217 Belgium 103, 165, 172 Bellaigue, Christopher de 94 Berko, Anat 233 bestiality, secular ethics and 205–6 bewilderment, age of xiii, 17, 215, 257 Bhagavadgita 269–70, 271, 299 Bhardwaj, Maharishi 181 Bible 127, 131–2, 133, 186–90, 198, 199, 200, 206, 233, 234–5, 240, 241, 272, 298 Big Data xii, 18, 25, 47, 48, 49, 53, 63, 64, 68, 71–2, 268 biometric sensors 23, 49, 50, 52, 64, 79, 92 biotechnology xii, xiv, 1, 6, 7, 8, 16, 17, 18, 21, 33–4, 41, 48, 66, 75, 80, 83, 88, 109, 121, 122, 176, 211, 251–2, 267 see also under individual area of biotechnology bioterrorism 167, 169 Bismarck, Otto von 98–9 bitcoin 6 Black Death 164 Blair, Tony 168 blockchain 6, 8 blood libel 235–6 body, human: bioengineered 41, 259, 265; body farms 34; technology and distraction from 88–92 Bolshevik Revolution (1917) 15, 248 Bonaparte, Napoleon 96, 178, 231, 284 Book of Mormon 198, 235, 240 Book of the Dead, Egyptian 235 Bouazizi, Mohamed xi brain: biochemical algorithms of 20, 21, 47, 48; brain-computer interfaces 92, 260; brainwashing 242–4, 255, 267, 295; decision-making and 50, 52; equality and 75, 79; flexibility and age of 264–5; free will and 250–2, 255; hominid 122; marketing and 267; meditation and 311, 313–14, 316, 317 Brazil 4, 7, 12, 76, 101, 103, 118, 130 Brexit referendum (2016) 5, 9, 11, 15, 45–6, 93, 99, 115 Brihadaranyaka Upanishad 283–4, 302–3 Britain 5, 9, 10, 11, 13, 15, 44–5, 94, 99, 108, 115, 139, 143, 150, 165, 172, 178, 182, 232–3, 243 Brussels bombings (March, 2016) 160 Buddha/Buddhism 58, 102, 136, 183, 184, 186, 190, 196, 278, 291, 302–6, 315 Bulgaria 169, 195, 227 Burma 304–5 Bush, George W. 4, 168, 176, 178 Caesar, Julius 96, 179 California, U.S. 8, 39, 85, 88, 148, 172, 177, 178, 200, 266 Cambridge Analytica 80, 86 Cambridge University 12, 45, 194 Cameron, David 45, 46 Canaan 189, 190, 289, 291 Canada 13, 38, 74, 107 capitalism xii, 11, 16, 35, 38, 55, 68, 76, 77, 96, 105–6, 108, 113, 130, 131, 132, 134, 135, 148, 210, 217, 245, 273, 292, 309 carbon dioxide 117 care industry 24–5 Caro, Rabbi Joseph 195 cars 133, 135; accidents and 23–4, 54, 56–7, 114, 159, 160; choosing 78; GPS/navigation and 54; self-driving 22, 23–4, 33, 41, 56–7, 58–9, 60–1, 63, 168 Catalan Independence 124, 125 Catholics 108, 132, 133, 137, 213, 292, 299 centaurs (human-AI teams) 29, 30 Chad 103, 119 Chaucer, Geoffrey: Canterbury Tales 235–6 Chemosh 191 chess 29, 31–2, 123, 180 Chigaku, Tanaka 305 child labour 33, 224 chimpanzees 94–5, 98, 122, 187–8, 200, 242 China xi, 4, 5, 8, 9, 10, 12, 13, 15, 64, 76, 100, 104, 105, 106, 107, 109, 113, 114, 115, 118, 119, 120, 121, 135, 145, 150, 151, 159, 168, 169, 171, 172–3, 175, 176, 177–8, 180, 181, 182, 183, 184, 185, 186, 193, 201, 227–8, 232, 251, 259–60, 262, 274, 284–5 Chinese Communist Party 5 Christianity 13, 55, 58, 96, 98, 126, 128–30, 131, 132, 133, 134–5, 137, 142, 143, 148, 183, 184–6, 187, 188, 189–90, 191, 192, 193, 194, 196, 199, 200, 203, 204, 208, 212–13, 233, 234–5, 236, 253, 282, 283, 288, 289, 291, 294, 296, 308; Orthodox 13, 15, 137, 138, 183, 237, 282, 308 Churchill, Winston 53, 108, 243 civilisation, single world xi, 5, 92, 95–109, 110, 138; ‘clash of civilisations’ thesis and 93–8; economics and 105–6; European civilisation and 95–6, 108–9; human tribes and 98–100; science and 107–8 ‘clash of civilisations’ 93–4 climate change x, xi, 15, 75–6, 78, 108, 109, 116–20, 121, 122–3, 124, 127, 128, 130, 133, 138, 168, 195, 219, 223, 228, 244, 265 Clinton, Bill 4, 168, 176 Clinton, Hillary 8, 97, 236 Cnut the Great, King of the Danes 105 Coca-Cola 50, 238, 267 Coldia (fictional nation) 148–50, 152–4 Cold War (1947–91) 99, 100, 113, 114, 131, 176, 180 communism xii, 3, 5, 10, 11, 14, 33, 35, 38, 74, 87, 95, 131, 132, 134, 176–7, 209–10, 251, 262, 273, 277, 279 Communities Summit (2017) 85 community 11, 37, 42, 43, 85–92, 109, 110, 135, 143–4, 201, 230, 241; breakdown of 85–7; Facebook and building of global xiii, 81, 85–91 compassion 62, 63, 71, 186; Buddhism and 305–6; religion and 186, 200, 201–2, 204, 208–9, 234, 305–6; secular commitment to 200, 201–2, 204–6, 208–9, 210 Confucius 15, 136, 181, 190, 260, 284–5 consciousness ix; AI and 36, 68–72, 122; intelligence and 68–70, 245–6; meditation and 315, 316; religion and 197 Conservative Party 45 conservatives: conservation and 219–20; embrace liberal world view 44–5 conspiracy theories 222, 229 Constantine the Great, Roman Emperor 192 Constantius II, Roman Emperor 192 cooperation 12, 29, 134; fictions and mass 134, 137, 233–42, 245; human-AI 29, 31; morality and 47, 187; nationalism and 134, 137, 236–8; religion and 134, 137, 233–6 corruption 12, 13, 15, 188–9 Council of Religion and the Homosexual (CRH) 200 creativity 25–8, 31, 32, 75, 182, 234, 262, 299 Crimea 174–5, 177, 179, 231, 238 Croats 282 Crusades 96, 165, 184, 199, 212, 213, 296 cryptocurrency 6 Cuba 9–10, 11, 114, 176 Cuban Missile Crisis (1962) 114 cultures, differences between 147–55 culturism 150–4 cyberwarfare 127, 176, 178, 179 cyborgs 8, 76–7, 212, 278 Czech Republic 200 Daisy advertisement: US presidential election (1964) and 113, 114 Darwin, Charles 194; On the Origin of Species 98–9 Darwinism 213 data: Big Data xii, 18, 25, 47, 48, 49, 53, 63, 64, 68, 71–2, 268; liberty and 44–72; ownership regulation 77–81, 86 see also artificial intelligence (AI) Davos World Economic Forum 222 Dawkins, Richard 45 Deep Blue (IBM’s chess program) 29, 31 democracies: ‘clash of civilisations’ thesis and 93–8; data processing and 65; equality and 74; individual, trust in and 217, 220; liberal democracy see liberal democracy; liberty and 44–6, 53, 55, 64, 65, 66, 67; media manipulation and 12–13; secular ethics and 204, 210 Denmark 4, 94, 105, 144, 153, 200, 210 dharma 270, 271, 286, 299, 309 Di Tzeitung 97 dictatorships 3, 5, 33, 74, 210, 305; digital xii, 43, 61–8, 71, 79–80, 121 discrimination: AI and 59–60, 67–8, 75–6; brain and structural bias 226–8; religion and 135, 191, 200, 208; racism/culturism, immigration and 147–55 disease 16, 22, 28, 49, 88, 107, 218, 289 disorientation, sense of 5, 6 DNA 49, 66, 67, 79, 98, 150, 182 doctors 22–3, 24, 28, 48–9, 106–7, 128–9, 280 dogmas, faith in 229–30 dollar, American 106 Donbas 238 Donetsk People’s Republic 232 drones 29, 30, 35, 64, 76 East Africa 239 ecological crisis, xi, xiv, 7, 109, 195, 219, 244, 265; climate change x, xi, 15, 75–6, 78, 108, 109, 116–20, 121, 122–3, 124, 127, 128, 130, 133, 138, 168, 195, 219, 223, 228, 244, 265; equality and 75–6; global solution to 115–26, 138, 155; ignorance and 219–20; justice and 223, 228, 244, 265; liberalism and 16; nationalism and 15, 115–26; religion and 127, 128, 130, 133, 138; technological breakthroughs and 118–19, 121, 122–4 economics xii, 3, 4, 7, 9, 11, 16, 68, 99, 222, 224, 225, 240, 262, 309; AI and 6, 7, 8, 9, 19–43; capitalist see capitalism; communism and see communism; data processing and 65–6; economic models 37, 105–6; equality and 9, 71, 73–7 see also equality; liberalism and 3–5, 16, 44–5; nationalism and 115, 117, 118, 120, 121, 124; religion and 130–3; war and 171–5, 177–8, 179–80; work and 19–43 education 11, 16, 66, 74, 75, 111, 112, 113, 184, 194, 259–68; AI and 32, 34, 35, 38 39, 40–1, 259–68; basic level of 40–1; future of 259–68; liberal 217, 219, 261; secular 207, 209 Egypt 63, 74, 128–9, 172, 181, 188–9, 235, 284, 291, 296 Einstein, Albert 45, 181, 193, 194, 195 El Salvador 4, 150 ‘End of History’ 11 Engels, Friedrich: The Communist Manifesto 262, 273 England 105, 139, 235–6 equality xi, 13, 41, 71–2, 73–81, 92, 95, 144, 204, 223; AI and 75–81; history of 73– 4; secularism and 206–7, 208–9 ethics: AI and 56–61, 63, 121; complex nature of modern world and 223–30; nationalism and 121–2; religion and 186–93, 199–202; secular 199–202, 203–14 Europe xi, xii, 5, 10, 11, 16, 40, 47, 79, 93–100, 103–4, 105, 106, 107, 108–9, 113, 114, 115, 124–5, 128, 135, 136, 138, 139, 140, 143–4, 145, 147, 150, 153, 154–5, 159, 160, 164, 169, 171–2, 175, 176, 186, 187, 193, 201, 207, 228, 236, 252, 294, 307 see also under individual nation name European Union xii, 47, 93, 94, 95, 99, 108, 115, 124, 169; Constitution 95, 124; crisis in 138; immigration and 138, 139, 143–4, 154–5; Russia and 177; size and wealth of 176; terrorism and 159 Evangelical Christians 133 evolution 47, 98–9, 110–11, 127, 187, 194, 205, 206, 217, 218, 223, 274, 276, 277 Ex Machina (film) 246 Facebook xiii, 27, 77, 178, 230, 301, 302, 306; community-building and xiii, 85–91, 93; equality and 77, 80; liberty and 55, 64, 65, 67, 80, 86; ownership of personal data 80, 86; post-truth and 233, 235, 238; US presidential election (2016) and 80, 86 failed states 101, 112, 210 fair game rules 187 fake news xi, 231–42 famine 16, 33, 208, 212, 238, 251, 271 farming, modern industrial 29, 116, 118, 127, 128, 129, 224, 260, 262 see also agriculture fascism xii, 3, 9, 10, 11, 33, 142, 148, 154, 237, 251, 292–5, 297, 305 feminism 87, 143, 208, 217, 246, 280 Ferdinand, Archduke Franz 9, 11, 171 Fernbach, Philip 218 financial crisis, global (2008) 4, 171 financial system, computers and complexity of 6 Finland 38, 74 First World War (1914–18) 9, 10, 11, 30, 33, 99–100, 112, 123, 124, 160, 170, 171, 172, 265 Flag Code of India 285–6 flags, national 103, 285–6 fMRI scanner 21, 240 football, power of fictions and 241 France 10, 13, 51, 63, 66, 76, 94, 96, 99, 102, 103, 104, 115, 122, 139, 144, 145, 164, 165, 172, 182, 184, 194, 204, 285, 295–6 Francis, Pope 133 Freddy (chimpanzee) 188 free-market capitalism xii, 3, 4, 11, 16, 44, 55, 217, 245 free will 20, 44, 45–6, 47–8, 250–1, 299–301 French Revolution (1789) 63, 184, 207 Freud, Sigmund 135, 185, 193, 194–5, 286 Friedman, Milton 130 Front National 13 Galilei, Galileo 193, 207 gay marriage 44, 198, 205–6 Gaza 173 genetically modified (GM) crops 219 Georgia 176, 177 Germany 13, 66, 68, 95, 96, 98–9, 108, 118, 139, 147, 148, 155, 169, 171–2, 173, 179, 182, 194, 195, 239, 251, 277; Nazi 10, 66, 96, 134, 136, 212, 213, 226, 237, 251, 279, 294, 295 Gandhi, Mahatma 132 globalisation 8, 9, 113, 139; AI/automation and 38–9; history of 99; inequality and 73, 74, 76; nationalism and 109; reversing process of xiii, 5; spread of 4, 99 global stories, disappearance of 5, 14 global warming see climate change God xi, xiii, 46, 106, 197–202; 245, 252, 254, 269, 281, 285, 287, 303, 304; Bible and see Bible; ethics and 199–202, 205, 206, 208, 209; existence of 197–9; Jewish and Christian ideas of 184–5, 189, 190; justice and 225; mass cooperation and 245; monotheism and 190–3; post-truth and 234–6, 239; sacrifice and 287, 289; state identity and 138 gods xii, 277, 281, 291; agriculture and 128, 129; humans becoming ix, 79, 86; justice and 188, 189; sacrifice and 287–9; state identity and 136, 137 Goebbels, Joseph 237 Goenka, S.

Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again by Eric Topol

"World Economic Forum" Davos, 23andMe, Affordable Care Act / Obamacare, AI winter, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, algorithmic bias, AlphaGo, Apollo 11, artificial general intelligence, augmented reality, autism spectrum disorder, autonomous vehicles, backpropagation, Big Tech, bioinformatics, blockchain, Cambridge Analytica, cloud computing, cognitive bias, Colonization of Mars, computer age, computer vision, Computing Machinery and Intelligence, conceptual framework, creative destruction, CRISPR, crowdsourcing, Daniel Kahneman / Amos Tversky, dark matter, data science, David Brooks, deep learning, DeepMind, Demis Hassabis, digital twin, driverless car, Elon Musk, en.wikipedia.org, epigenetics, Erik Brynjolfsson, fake news, fault tolerance, gamification, general purpose technology, Geoffrey Hinton, George Santayana, Google Glasses, ImageNet competition, Jeff Bezos, job automation, job satisfaction, Joi Ito, machine translation, Mark Zuckerberg, medical residency, meta-analysis, microbiome, move 37, natural language processing, new economy, Nicholas Carr, Nick Bostrom, nudge unit, OpenAI, opioid epidemic / opioid crisis, pattern recognition, performance metric, personalized medicine, phenotype, placebo effect, post-truth, randomized controlled trial, recommendation engine, Rubik’s Cube, Sam Altman, self-driving car, Silicon Valley, Skinner box, speech recognition, Stephen Hawking, techlash, TED Talk, text mining, the scientific method, Tim Cook: Apple, traumatic brain injury, trolley problem, War on Poverty, Watson beat the top human players on Jeopardy!, working-age population

Of equal, and perhaps even greater, importance will be an exploration of AI’s liabilities, such as human bias, the potential for worsening inequities, its black-box nature, and concerns for breaches of privacy and security. The transfer of tens of millions of people’s personal data from Facebook to Cambridge Analytica, who then used AI to target individuals, illustrates one critical aspect of what could go wrong in the healthcare context. Then we’re ready to move on to the new medicine that will integrate the tools of AI. We’ll assess how machine pattern recognition will affect the practice of radiologists, pathologists, and dermatologists—the doctors with patterns.

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Even though it resulted in an important product that helped clinicians and patients, there were valuable lessons learned.53 One other example of deep learning’s potential to invade privacy is an effort described in a paper in the Proceedings of the National Academy of Sciences.54 By combining 50 million Google Street View images of 22 million cars, in two hundred cities, with publicly available data, researchers at Stanford University’s AI lab and their collaborators were able to accurately estimate public voting patterns, race, education, and income by zip code or precinct. While the use of deep learning algorithms did not provide estimates at the individual or household level, you can be certain that many tech companies have such data and, with similar neural net analytics, can come up with this information. The most notable case is Cambridge Analytica’s expansive individual profiles of the majority of American adults, developed via extracting Facebook’s data, ultimately with claims of shifting the 2016 election outcome, alongside algorithmically targeted fake news distribution.55 The worry about potential hacking has been reinforced by automated cyberattacks and the legitimate concern that products of AI, like driverless cars, could be run off the road.

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.), 180–181 PTSD and, 174–175 black box problem, 97 accountability and, 96 AI Now Institute on, 95 Deep Dream and, 96 Deep Patient and, 95 Domingos on, 95 medical imaging and, 96 blockchain, medical data and, 275 Blue Cross Blue Shield Association, 200–201 Bonnefon, Jean-Francois, 104–105 Bostrom, Nick, 110 brain cancer, 117 genomics and, 214 molecular diagnostics and, 128–129 brain-wave monitoring, depression and, 174 breast cancer, misdiagnosis and, 126–127 breathing tubes, machine vision and, 196 Brooks, David, 307 Bryan, Nick, 121 Brynjolfsson, Erik, 107 Budner, Pascal, 180 Buoy Health, 51 burnout, 18, 30, 285, 288–289 Butterfly Network, 154 C. diff. See Clostridia difficile Camacho Collados, Jose, 93–94 Cambridge Analytica, 103 Camelyon Challenge, 127 Canada, AI healthcare initiatives in, 203 cancer diagnosis, 133–134 SOPHiA GENETICS and, 159 Tempus Labs and, 158–159 Watson supercomputer and, 155–157 Cancer Genome Atlas, 209 cancer research, 264 genomics and, 213–214 cancer risk, nutritional science and, 237, 239 (fig.), 246 Capper, David, 213 capsule networks, Hinton on, 93 car safety, 85 Cardiogram, 154 care.coach, 265 CareSkore, 188 Carr, Nicholas, 261 Casarett, David, 27 Castle, Matthew, 289 CBT.

Siege: Trump Under Fire by Michael Wolff

"RICO laws" OR "Racketeer Influenced and Corrupt Organizations", Bernie Madoff, Boris Johnson, Cambridge Analytica, conceptual framework, cuban missile crisis, currency manipulation / currency intervention, Deng Xiaoping, disinformation, Donald Trump, fake news, forensic accounting, gig economy, Great Leap Forward, high net worth, hiring and firing, illegal immigration, immigration reform, impulse control, Jeffrey Epstein, Julian Assange, junk bonds, Michael Milken, oil shale / tar sands, opioid epidemic / opioid crisis, Potemkin village, Quicken Loans, Saturday Night Live, sovereign wealth fund, Steve Bannon, Steve Jobs, WikiLeaks

With hooded eyes and an overcoat in need of replacement, the seventy-four-year-old Halper was yet another spy vs. spy player in Cambridge, where, in Bannon’s cryptic summation, “all worlds lead.” (Bannon knew Cambridge well: he and Halper walked the same streets as members of the back-office staff of Cambridge Analytica, the shady tech company with which Bannon was associated that had more or less unscrupulously acquired vast amounts of election metadata.) Indeed, Stefan Halper was a spy, a heavy hitter in the U.S.-UK spy world, who had been married to the daughter of a legendary CIA figure, Ray Cline, who was on the case during the Cuban Missile Crisis.

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(AMI) Anbang Insurance Group Anderson, Kristin “Anonymous” op-ed anti-Semitism Anton, Michael AP Apollo Global Management Apprentice, The (TV show) Arafat, Yasser Aramco Arpaio, Joe Arthur Andersen (firm) Ashcroft, John Assange, Julian Auchincloss, Louis Avenatti, Michael Axios Ayers, Nick Azerbaijan Bannon, Maureen Bannon, Steve allies of ambitions of banished from White House Brussels NATO summit and budget bill and Burck and Cambridge Analytica and caravan and China and Cobb and Cohen and Comey and Conway and Congress and Corsi and Democrats and Daniels and deep state and deplorables and donors and elections of 2016 and elections of 2020 and on endgame establishment and Europe and exogenous events and family separations and film Trump @War and finances of Fox News and Giuliani and government shutdown and Haley and Hannity and Helsinki summit and Hillary Clinton’s emails and impeachment threat and inauguration and Ivanka and Jackson and Jared and Kavanaugh and Khashoggi murder and liberal globalism and liberal media and Manafort and Mattis and Mexico and midterms and Mueller and Mueller report and Murdoch and national emergency and North Korea and Pelosi and Pence and plan of, to save Trump populism and Porter and Priebus and right wing and Rosenstein firing urged by Russia and Ryan and Sessions and State of the Union and Steele dossier and Summers and trip to London and Trump and Trump’s marriage to Melania and Trump’s personality and Trump’s sex scandals and UK and unified field theory of U.S. politics and Wall and White House staff and Woodward and Barr, William P.

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See also Wall Bossie, David Bowers, Robert Gregory Bracamontes, Luis Brand, Rachel Breitbart, Andrew Breitbart News Brennan, John Brexit bribery Britain (United Kingdom) Brookfield Asset Management budget bills Burck, Bill Burdick v. United States Burnett, Mark Bush, George H. W. Bush, George W. Bush, Jeb Bush family Bush v. Gore Calamari, Matt Calley, Brian Cambridge Analytica Cameron, Ron campaign finance laws Camp of the Saints, The (Raspail) Canada Car & Driver caravan Carlson, Tucker Carter, Sara Catholics CBS Central Intelligence Agency (CIA) Chao, Elaine Charles, Prince of Wales China North Korea and tariffs and China Club Christie, Chris Churchill, Winston Cipollone, Pat Citibank Citizens United Clapper, James Clifford, Clark Cline, Ray Clinton, Bill impeachment and Rich pardon and Clinton, Hillary Clinton Cash (Schweizer) Clinton Foundation CNBC CNN Coats, Dan Cobb, Ty Cohen, Michael Daniels and FBI raid and guilty plea and McDougal and Trump Tower Moscow and Cohen, Samantha Cohn, Gary Cohn, Roy Colbert, Stephen Comey, James Ashcroft and Clinton’s emails and deep state and elections of 2016 and Flynn and Giuliani and publishes Higher Loyalty Comstock, Barbara Congressional Leadership Fund (CLF) Conway, George Conway, Kellyanne Corsi, Jerome Costa, Robert Coulter, Ann Council for the American Worker Crimea criminal justice reform Cruz, Ted Cuban Missile Crisis Cummings, Elijah Cuomo, Andrew Daily Beast Daily Caller Daily Mail Daniels, Stormy Davidson, Keith M.

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

Edward Snowden’s revelations taught us of the enormous amount of data that the government is already collecting on us, and made it fairly clear that whatever data the private firms have, the NSA could easily get hold of.23 And revelations about how Facebook has been using some of its data and allowing others (for example, Cambridge Analytica) to use its data, and the security measures it has taken to protect the data shouldn’t make us any too comfortable either. George Orwell’s dystopian novel 1984 and a more recent one, The Circle, by Dave Eggers, illustrate our fears of a Big Brother government having control over us—and Big Data provides it with the ability to control that which was well beyond Orwell’s imagination.24 In short, we should be concerned about our loss of privacy.

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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. Some put greater onus on the platforms.

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Valeo, 332n31 budget deficits, 268n42 and infrastructure, 183 2017 tax bill and, xviii, 258n7 and trade imbalance, 90 Buffett, Warren, 5–6, 47–48 bullying, 136 bundling, 58 bureaucracy checks and balances on, 232–33 Trump’s undermining of competency/integrity of, 164 Burtless, Gary, 41 Bush, George H. W., xv, 165, 238 Bush, George W., and administration antitrust cases, 62 Social Security privatization, 214 Supreme Court’s loss of status as fair arbiter, 165–66 tax cuts, 25 Bush, Jeb, 178 Bush v. Gore, 165–66 Cambridge Analytica, 127–28, 132 campaign spending, 171–73; See also Citizens United Canada, 17 capital-income ratio, 54 capitalism American-style, See American-style capitalism end of communism as alleged triumph of, 3 capitalized value of rents, 282n17 capital stock, 53 capture, 149, 223, 333n32 carbon tax, 194, 206–7 carried-interest loophole, 258n6 Carter, Jimmy, and administration, 78 Case, Anne, 41–42 CEA (Council of Economic Advisers), xii Centers for Disease Control, 41 central banks, 142 CEO salaries, 39, 198, 298n89 Chao, Elaine L., 335n6 Charter Communications, 147 charter schools, 342n43 checks and balances, 163–67, 232–34 Chicago School, 68–69 childcare, 197 China economic ideology, 28–29 GDP, 272n12 and globalization, 81, 94–98 and global risk-free return on capital, 53 growth rate, 37 lack of privacy protections, 135 and risk-free return on capital, 53 trade wars, 93–94 and US unemployment, 83 churn, 314n21 cigarette companies, 18, 20 Circle, The (Eggers), 128 Citigroup, 107 Citizens United v.

Rule Britannia: Brexit and the End of Empire by Danny Dorling, Sally Tomlinson

3D printing, Ada Lovelace, Alfred Russel Wallace, anti-communist, anti-globalists, Big bang: deregulation of the City of London, Boris Johnson, Brexit referendum, British Empire, Bullingdon Club, Cambridge Analytica, centre right, colonial rule, Corn Laws, correlation does not imply causation, David Ricardo: comparative advantage, deindustrialization, disinformation, Dominic Cummings, Donald Trump, Edward Snowden, electricity market, en.wikipedia.org, epigenetics, Etonian, falling living standards, Flynn Effect, gentrification, housing crisis, illegal immigration, imperial preference, income inequality, inflation targeting, invisible hand, Jeremy Corbyn, knowledge economy, market fundamentalism, mass immigration, megacity, New Urbanism, Nick Leeson, North Sea oil, offshore financial centre, out of africa, Right to Buy, Ronald Reagan, Silicon Valley, South China Sea, sovereign wealth fund, spinning jenny, Steven Pinker, Suez canal 1869, Suez crisis 1956, The Wealth of Nations by Adam Smith, Thomas Malthus, University of East Anglia, Wayback Machine, We are the 99%, wealth creators

You are unlikely to believe that everyone came to their own decision without being influenced by any funded lobbying group or media campaign. (In fact, long before the Cambridge Analytica scandal broke, it was revealed in May 2017 how the Leave campaign devoted most of its resources: ‘Vote Leave sent, Dominic Cummings wrote, “nearly a billion targeted digital adverts” and spent approximately 98% of their money on digital campaigning.’31) But the good news is that it really was not the Russians who arranged all this, or some wonks working in an outfit called Cambridge Analytica. Brexit was a home-grown enterprise. Mostly it was paid for in Britain, although the money was often routed through tax havens.

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However, when you compare prices around major train stations in these cities, and account for the square metres that are inside dwellings, central London is often found to be the most expensive, at least for now – its prices are falling. 57 Macpherson, W. (1999) The Stephen Lawrence Inquiry, Cmnd 4262, London: The Stationery Office. 58 Adams, T. (2013) ‘Doreen Lawrence: “I could have shut myself away, but that is not me”’, The Guardian, 20 April, https://www.theguardian.com/uk/2013/apr/20/doreen-lawrence-stephen-lawrence INDEX Abramovich, Roman 1 abstentions in EU referendum 1, 2, 3 Acheson, Dean 1 Act of Union (1707) 1, 2, 3 Adonis, Andrew 1 age as factor in referendum 1, 2, 3 and views on immigration 1 and support for political parties 1 Al Nahyan, Mansour bin Zayed 1 Aliens Act (1905) 1, 2 Allen, Graham 1 Andrew, Prince 1 Anglo-Saxon myth 1 arms trade 1, 2, 3 Arne, Thomas 1 Arsenal 1 Ashcroft, Lord 1, 2, 3 Attlee, Clement 1, 2 BAE 1 Baker, Herbert 1 Bamford, Lord 1 Bank of England 1, 2 Banks, Arron 1, 2, 3 Barclay, Stephen 1 Barnier, Michel 1 Bartley, Jonathan 1 bell curve 1, 2 Benn, Tony 1 Besant, Annie 1 Bevan, Aneurin 1 Bildt, Carl 1 Blair, Tony 1, 2, 3 Blake, William 1 Bloomberg, Michael 1 Blunkett, David 1 Blunt, Anthony 1 BMG 1 Boer War 1, 2 Bolton, Henry 1 Bonaparte, Napoleon 1 Bone, Peter 1 Booth, Robert 1 Borja, Mario Cortina 1, 2 Bowers, Simon 1 Boyle, Frankie 1 Bradlaugh, Charles 1 Bradley, Karen 1 Bragg, Billy 1 Branson, Richard 1 Bravo, Antonio 1 Bravo, Manuel 1 Brexit Cookbook, The 1 Brexit negotiations Theresa May’s position on 1 free trade deals 1, 2, 3, 4, 5, 6, 7, 8 life after Brexit 1, 2, 3 impact on EU 1 and financial services 1 and impact reports 1 and Brexit War Cabinet 1 and ‘no deal’ Brexit 1, 2 and Greenland example 1 ‘soft’ and ‘hard’ Brexits 1 Labour Party position on 1 costs of Brexit 1 Britain definition of 1, 2 misconception of identity 1 role in modern world 1 post-Empire 1, 2, 3 mythology of 1, 2, 3, 4 creation of 1 ‘Great’ in 1 identity of 1, 2, 3 and natural selection 1 international comparisons 1 rise in inequality in 1 pride in 1 industrial revolution in 1 pollution in 1 arms trade in 1, 2, 3 financial services in 1, 2, 3, 4 arms trade in 1 manufacturing industry in 1, 2, 3, 4, 5, 6, 7 statistics on trade 1 values of 1 wage levels in 1 life expectancy in 1 possible break-up of 1 Britannia 1 British Brothers’ League 1 British Chamber of Commerce 1 British Empire loss of 1, 2 pride in 1, 2 and immigration 1 creation of 1 and British identity 1 education about 1, 2, 3, 4, 5 and dependencies 1 as market captive 1, 2, 3, 4 remnants of 1, 2, 3 and public schools 1 racism in 1 fantasy of 1 and Darwinism 1 delusions of grandeur 1 spoils of 1 legacy of 1, 2 Opium Wars 1 and need for food 1 British Empire Union 1 British Medical Journal 1, 2 BRIT(ish): On Race Identity and Belonging (Hirsch) 1 British Union of Fascists 1 Brokenshire, James 1 Brown, Gordon 1, 2, 3 Bullingdon Club 1 Burgess, Guy 1 Buxton, Ronald 1 Cairncross, John 1 Cairns, Alun 1 Cambridge Analytica 1 Cambridge University 1, 2, 3, 4 Cameron, David promises referendum 1, 2 negotiations with EU 1 on ‘Jerusalem’ 1 on trade with the EU 1 at Oxford University 1, 2 family involvement in slavery 1 toughness on immigration 1 at Eton 1 resignation of 1 millionaires in Cabinet 1 wealth of 1 negotiations with EU 1 unauthorised biography of 1 Campbell, Alastair 1 Capital Group 1 Carney, Mark 1 Catholic Herald 1 Cavell, Edith 1 Centre for Social Justice 1 Chagos Islanders 1 Chandler, Christopher 1 Channel Islands 1 Charles, Prince 1, 2, 3, 4 Chelsea football club 1 Child Poverty Action Group 1 Churchill, Winston 1, 2, 3 Clark, Greg 1 Clarke, Kenneth 1, 2 class as factor in referendum 1, 2, 3, 4, 5 and the British Empire 1 Clegg, Nick 1 Clinton, Bill 1 Cockburn, Patrick 1 Collingham, Lizzie 1, 2 Commonwealth 1, 2, 3, 4, 5 Commonwealth Immigration Act (1968) Conan Doyle, Arthur 1, 2 Confederation of British Industry (BFI) 1 Confession of Faith (Rhodes) 1 Conservative Party donations to 1, 2 issue of EU in 1, 2, 3 wins 2015 general election 1 in European Parliament 1 age of supporters 1 Contemporary Review Journal 1 Corbyn, Jeremy 1 personality of 1, 2 election as Labour Party leader 1 and Windrush scandal 1 and 2017 general election 1 honesty of 1 comparisons with Attlee 1, 2 opposition to austerity 1 and second referendum 1 Corera, Gordon 1 corporal punishment 1 Cox, Geoffrey 1 Cox, Jo 1, 2, 3 Crabb, Stephen 1 Cromwell, Oliver 1 Culloden, Battle of 1 Cumberbatch, Benedict 1 Cummings, Dominic and political repercussions of referendum 1 to be played by Benedict Cumberbatch 1 early life and career 1, 2 belief in natural selection 1, 2, 3 in Vote Leave campaign 1, 2, 3 Cyprus 1 Daily Express 1 Daily Mail 1, 2 Daily Mirror 1 Daily Telegraph 1, 2, 3, 4, 5 Dalla Valle, Luciana 1, 2 Dalrymple, William 1 Daly, Paul 1 Darling, Alistair 1 Darwin, Charles 1, 2, 3, 4 Darwinism 1 Davis, David and customs union ‘backstop’ 1 and impact reports 1 made Secretary for Exiting the EU 1 Frankie Boyle on 1 bets on referendum result 1 Demetriades, Panicos 1 Democratic Unionist Party (DUP) 1, 2, 3 Der Spiegel 1 Deripaska, Oleg 1 Duncan Smith, Iain 1 East India Company 1, 2, 3 Economists for Free Trade 1 Edmiston, Lord 1 education as factor in referendum 1 universities 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 selective 1 and inequality 1, 2, 3 history of in Britain 1 competition in 1 rise in levels of 1 in OECD countries 1 reforms to 1 Education and Race from Empire to Brexit (Tomlinson) 1 Edward, Prince 1 Edward I, King 1 Edwards, David 1 El-Enany, Nadine 1, 2, 3, 4 Elgot, Jessica 1 Elliott, Larry 1 Elliott, Matthew 1 Empire Marketing Board 1, 2 Empire Windrush 1, 2 England, pride in 1, 2 environmental legislation 1 Eton 1 eugenics 1, 2, 3 European Parliament 1 European Research Group (ERG) 1, 2 Evans, Natalie 1 Evans-Gordon, Major 1 Eyres, Harry 1 Falkland Islands 1 Fallon, Michael 1, 2 Farage, Nigel 1 contemplates Northern Ireland seat 1, 2 foiled leadership ambitions 1 and fantasy of British Empire 1 and immigration 1, 2 and Grassroots Out 1 farming industry 1 Festival of Britain 1 Field, Frank 1 financial services 1, 2, 3, 4 Financial Times 1, 2 Fingleton, Eamonn 1 Finnish Lessons (Sahlberg) 1 Fletcher, C.

Competition Overdose: How Free Market Mythology Transformed Us From Citizen Kings to Market Servants by Maurice E. Stucke, Ariel Ezrachi

"Friedman doctrine" OR "shareholder theory", affirmative action, Airbnb, Alan Greenspan, Albert Einstein, Andrei Shleifer, behavioural economics, Bernie Sanders, Boeing 737 MAX, Cambridge Analytica, Cass Sunstein, choice architecture, cloud computing, commoditize, corporate governance, Corrections Corporation of America, Credit Default Swap, crony capitalism, delayed gratification, disinformation, Donald Trump, en.wikipedia.org, fake news, Garrett Hardin, George Akerlof, gig economy, Glass-Steagall Act, Goldman Sachs: Vampire Squid, Google Chrome, greed is good, hedonic treadmill, incognito mode, income inequality, income per capita, independent contractor, information asymmetry, invisible hand, job satisfaction, labor-force participation, late fees, loss aversion, low skilled workers, Lyft, mandatory minimum, Mark Zuckerberg, market fundamentalism, mass incarceration, Menlo Park, meta-analysis, Milgram experiment, military-industrial complex, mortgage debt, Network effects, out of africa, Paradox of Choice, payday loans, Ponzi scheme, precariat, price anchoring, price discrimination, profit maximization, profit motive, race to the bottom, Richard Thaler, ride hailing / ride sharing, Robert Bork, Robert Shiller, Ronald Reagan, search costs, shareholder value, Sheryl Sandberg, Shoshana Zuboff, Silicon Valley, Snapchat, Social Responsibility of Business Is to Increase Its Profits, Stanford prison experiment, Stephen Hawking, sunk-cost fallacy, surveillance capitalism, techlash, The Chicago School, The Market for Lemons, The Myth of the Rational Market, The Theory of the Leisure Class by Thorstein Veblen, The Wealth of Nations by Adam Smith, Thomas Davenport, Thorstein Veblen, Tim Cook: Apple, too big to fail, Tragedy of the Commons, transaction costs, Uber and Lyft, uber lyft, ultimatum game, Vanguard fund, vertical integration, winner-take-all economy, Yochai Benkler

First, are we, the users, really in control? By one count, Mark Zuckerberg, Facebook’s CEO, said, “You are in control of your data” forty-five times during the two congressional hearings, where he was called to testify after the fallout from the Cambridge Analytica/Facebook scandal.112 The scandal, contrary to this illusion—or delusion—of control, exposed how Cambridge Analytica accessed the Facebook data of up to eighty-seven million people, entirely unbeknownst to them, in order to develop techniques designed to help Donald Trump win the 2016 presidential election.113 We typically view the Gamemaker as the servant that keeps providing us with services at no cost, rather than as the master that it really is.

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The significance of the referral traffic from Google and Facebook to Australian news media businesses has provided these digital platforms with a substantial degree of market power in the market for news media referral services”). 106.Elisa Shearer and Jeffrey Gottfried, “News Use Across Social Media Platforms 2017,” Pew Research Center, September 7, 2017, http://pewrsr.ch/2xdh8vt; Elisa Shearer and Katerina Eva Matser, “News Use Across Social Media Platforms 2018,” Pew Research Center, September 10, 2018, https://pewrsr.ch/2x1umJR. 107.ACCC Preliminary Report, 3. 108.Natasha Tracy, “Types of Addiction: List of Addictions,” Healthy Place, April 22, 2019, https://www.healthyplace.com/addictions/addictions-information/types-of-addiction-list-of-addictions. 109.Melissa Kirsch, “Change Your Screen to Grayscale to Combat Phone Addiction,” Life Hacker, June 5, 2017, https://lifehacker.com/change-your-screen-to-grayscale-to-combat-phone-addicti-1795821843. 110.Google Safety Center, “Privacy Controls,” accessed May 2, 2019, https://safety.google/privacy/privacy-controls/. 111.Facebook, Privacy Basics, accessed May 2, 2019, https://www.facebook.com/about/basics. 112.Wheeler, The Root of the Matter, 8. 113.For an early report of the scandal, see Matthew Rosenberg, Nicholas Confessore, and Carole Cadwalladr, “How Trump Consultants Exploited the Facebook Data of Millions,” New York Times, March 17, 2018, https://nyti.ms/2GB9dK4; Cyrus Farivar and Sean Gallagher, “Facebook: It Wasn’t 50M Hit by Cambridge Analytica Breach, but Rather 87M,” Ars Technica, April 4, 2018, https://arstechnica.com/?post_type=post&p=1288245. 114.ACCC Preliminary Report, 6. 115.Ryan Nakashima, “Google Tracks Your Movements, Like It or Not,” Associated Press, https://apnews.com/828aefab64d4411bac257a07c1af0ecb. 116.Kashmir Hill, “‘Do Not Track,’ the Privacy Tool Used by Millions of People, Doesn’t Do Anything,” Gizmodo, October 15, 2018, https://gizmodo.com/do-not-track-the-privacy-tool-used-by-millions-of-peop-1828868324; Bundeskartellamt, “Bundeskartellamt Prohibits Facebook.” 117.Hill, “‘Do Not Track.’” 118.Privacy International, “How Apps on Android Share Data with Facebook—Report,” December 2018, https://privacyinternational.org/report/2647/how-apps-android-share-data-facebook-report. 119.Sam Schechner and Mark Secada, “You Give Apps Sensitive Personal Information.

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

It sees the stories I read and share, but it’s an algorithm targeting a cohort, not a feed-based platform designed specifically for me. Facebook’s algorithm can be used to microtarget distinct populations in specific geographic areas. An advertiser can say, “Give me all the millennial women around Portland looking to buy a car.” Using data mined from the social media accounts of millions of Americans, Cambridge Analytica, a data firm that worked on Brexit and on the Trump campaign, created a “psychographic profile” of voters ahead of the 2016 election. The company used behavioral microtargeting to deliver specific pro-Trump messages that resonated with specific voters for highly personal reasons.18 With knowledge of 150 likes, their model could predict someone’s personality better than their spouse.

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FBI, 63–64, 65–66 and Wozniak, 69, 88, 180 and Xerox’s GUI, 161, 166 See also iPhone; Jobs, Steve artificial intelligence (AI), 196–200 artisans and artisanship, 76–77, 78–79 AT&T, 228–29 backfire effect, 123 behavioral targeting, 107, 196–99 Bezos, Jeff on adherence to process, 112 and Alexa, 57 business plan formulation, 13 and competition, 181 on future of Amazon, 182 and Lore, 45–47 risk taking of, 35–37 and robotics, 29–30, 52–54 storytelling of, 55 vision of, 23, 25 and Washington Post, 146 wealth of, 4 Bloomberg, Michael, 141–42, 164 body, biology, and business, 169–82 and Amazon, 176–77 and Apple, 178–79 and brain’s rational choices, 169–71, 175–77 and competition, 179–82 and Facebook, 177 and genitalia-based choices, 173–75, 178–79 and Google, 175–76 and heart-based choices, 171–73, 173, 177 Brand, Stewart, 163, 164 brands and Amazon, 172–73 era of, 50, 50–52, 172–73, 184 Facebook investments of, 165, 166 Google’s effect on, 5, 8–9, 172–73 and heart-based choices, 172 See also luxury brands business school education, 11–12 Cambridge Analytica, 107 capitalization and T Algorithm, 188–89 career strategies, 230–62 accepting and giving help, 252 active career management, 247–48 for Boomers, 243–44 and core functions driving companies, 249–50 dealing with unfair treatment, 248–49 demonstrating physical/mental strength, 251–52 and emotional maturity, 233–35 entrepreneurship, 260–64 and exceptional vs. good employees, 230–32 and leadership stages in life cycles of firms, 253–57 and long/short tails, 257–59 loyalty to people, 247 and myth of balance, 259 and personal success factors, 233–36 and regression to the mean, 249 self-promotion, 242–43 serial monogamy, 245–46 and sexy jobs vs.

Nothing But Net by Mark Mahaney

Airbnb, AltaVista, Amazon Web Services, AOL-Time Warner, augmented reality, autonomous vehicles, Big Tech, Black Swan, Burning Man, buy and hold, Cambridge Analytica, Chuck Templeton: OpenTable:, cloud computing, COVID-19, cryptocurrency, discounted cash flows, disintermediation, diversification, don't be evil, Donald Trump, Elon Musk, financial engineering, gamification, gig economy, global pandemic, Google Glasses, Jeff Bezos, John Zimmer (Lyft cofounder), knowledge economy, lockdown, low interest rates, Lyft, Marc Andreessen, Mark Zuckerberg, Mary Meeker, medical malpractice, meme stock, Network effects, PageRank, pets.com, ride hailing / ride sharing, Salesforce, Saturday Night Live, shareholder value, short squeeze, Silicon Valley, Skype, Snapchat, social graph, Steve Jobs, stocks for the long run, subscription business, super pumped, the rule of 72, TikTok, Travis Kalanick, Uber and Lyft, uber lyft

The implied criticism holds for Zuckerberg, too. There have also been legitimate issues around Facebook’s lack of sufficient focus on protecting its users’ privacy. In April 2020, a federal court approved a $5 billion settlement between the Federal Trade Commission and Facebook arising from the FTC’s assertion that the Cambridge Analytica scandal, in which data on 87 million Facebook users was used by a political consultancy that worked on President Trump’s 2016 election campaign, violated an earlier 2012 agreement between Facebook and the FTC to protect user privacy. All of which leads to the June 2018 quarter, one of the greatest self-inflicted share price wounds in tech history that I have witnessed, and the lesson of how even the best stocks can suck at times.

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S&P, 279t, 282t as platform company, 241–242 playing quarters at, 57–58, 57t and pricing power flywheel, 192–194, 193f, 196–197 revenue, 82, 106–108, 153, 153t rise of, 5 sell-offs of, 48–52 share price, 51f underestimations of, 2 Amazon Kindle, 50, 115–116 Amazon Prime, 115, 174, 180–183, 192, 205 Amazon Subscribe & Save, 115 Amazon Web Services (AWS): launch of, 50 product innovation, 114–119, 179 revenue, 117f “Amazon.Bomb,” 10, 177–178 “Amazon’s Antitrust Paradox,” 308 American Technology Research, 156, 181 Android, ubiquity of, 63 Antitrust regulations, 308–310 AOL, 5, 7–8, 82 Apple: growth of, 305 management teams of, 203–204, 204t, 220t market cap of, 7 product innovation at, 114 revenue, 108, 153, 153t share price, 48–49 and Snap, 63 APRN (Blue Apron), 18–23, 19f, 33 Athar, Sohaib, 134 Auletta, Ken, 149 AWS (see Amazon Web Services [AWS]) Ayers, Charlie, 145 BABA (see Alibaba [BABA]) Bad stocks, 15–33, 293 Blue Apron, 18–23 and fundamentals of stock-picking, 15–18 Groupon, 27–32 Zulily, 23–27 Bain Capital, 24 Barron’s magazine, 9–10, 90, 91, 177–178 Barton, Rich, 188, 191, 209 Bezos, Jeff: acknowledgments of mistakes by, 219, 221 and Amazon Prime, 181, 193 and Amazon Web Services, 115, 116 and Burning Man, 220t as company founder, 204t competition for, 8 innovation by, 10, 205–206 shareholder letters by, 214–216, 216t–217t “Big baggers,” 1–2 “The Big Long,” 5–7 The Big Short (Lewis), 5 Black swan events, 18 Blockbuster, 10 Blue Apron (APRN), 18–23, 19f, 33 Blue Nile (NILE), 23–24 Booking.com (BKNG): acquisition of, 80 as big bagger, 1 during Covid-19 pandemic, 303 fundamentals at, 261t market cap of, 7 net income of, 5, 6t as tech stock, 3 Bow Street, 24 Boyd, Jeff, 91, 210 Brin, Sergey, 145, 146, 204t, 209, 219, 220t Broadcast.com, 87 Brown, Josh, 226 Buffett, Warren, 214 Burning Man, 219, 220t “Burning Up,” 177 Buyer, Lise, 145–146 Calico, 208 Cambridge Analytica, 37 Candor, of management teams, 221 Carpenter, Matt, 311 Case, Steve, 7 Cavens, Darrell, 23–24 Chernobyl (miniseries), 131 Chewy (CHWY): as competitor, 310 and Covid-19 pandemic, 3, 4, 17 during Covid-19 pandemic, 303 fundamentals at, 261t as long-term investment, 66–70 market cap of, 247t share price, 70f as tech stock, 3 CIA, AWS used by, 118 Cisco Systems, 6 Cloud computing, 117–118 Cloudflare, 17 CNBC, 68 Cohen, Ryan, 68, 302 Cohort performance, 250 Companies: judging high-quality, 292 live-from-home and work-from-home, 303 with minimal earnings, 235–242 with no earnings, 242–254, 243t with robust earnings, 232–235 user-generated content, 248–249 Competitive moats, 169–170 Comps, 105–107 Consumerism, as research, 140 ConsumerVoice.org, 21 Content moderation, on Facebook, 37 “A Conventional Look at an Unconventional IPO,” 156 Cooper, Bradley, 135 Covid-19 pandemic, 302–305 Amazon during, 3 Chewy during, 69 DoorDash during, 161–162 eBay during, 85 effect of, on markets, 17–18, 226, 246 and forecasting, 255 Google during, 46 and Internet sector, 3–4 Netflix during, 45 and revenue, 105–107 Stitch Fix during, 124–125, 127 stock dislocations due to, 276 Covid-19 pandemic tech stocks during, 131 Uber during, 159, 161 Cramer, Jim, 157 Criteo (CRTO), 288–289, 289f Cruz, Ted, 37 Customer focus: of Amazon, 180 of DoorDash, 185–186 long-term investments in companies with, 187 of management teams, 214–216, 216t–217t and pricing power flywheel, 194 of product innovation, 295–296 Customer value propositions, 173–199, 297 Amazon vs. eBay, 174–183 DoorDash vs.

Talk to Me: How Voice Computing Will Transform the Way We Live, Work, and Think by James Vlahos

Albert Einstein, AltaVista, Amazon Mechanical Turk, Amazon Web Services, augmented reality, Automated Insights, autonomous vehicles, backpropagation, Big Tech, Cambridge Analytica, Chuck Templeton: OpenTable:, cloud computing, Colossal Cave Adventure, computer age, deep learning, DeepMind, Donald Trump, Elon Musk, fake news, Geoffrey Hinton, information retrieval, Internet of things, Jacques de Vaucanson, Jeff Bezos, lateral thinking, Loebner Prize, machine readable, machine translation, Machine translation of "The spirit is willing, but the flesh is weak." to Russian and back, Mark Zuckerberg, Menlo Park, natural language processing, Neal Stephenson, Neil Armstrong, OpenAI, PageRank, pattern recognition, Ponzi scheme, randomized controlled trial, Ray Kurzweil, Ronald Reagan, Rubik’s Cube, self-driving car, sentiment analysis, Silicon Valley, Skype, Snapchat, speech recognition, statistical model, Steve Jobs, Steve Wozniak, Steven Levy, TechCrunch disrupt, Turing test, Watson beat the top human players on Jeopardy!

X2AI is compliant with the privacy mandates of HIPAA, the Health Insurance Portability and Accountability Act, which strictly forbids unauthorized sharing of patient information. But when users chat with Woebot over Messenger, Facebook has the ability to see the content of the therapy sessions. (Woebot’s dedicated iOS and Android apps, though, do not allow data sharing with external companies.) After the Cambridge Analytica scandal broke in 2018, the world learned that Facebook couldn’t always be trusted to keep personal data private—and conversations with a therapist, even a synthetic one, are among the most private that any person could have. Also, as detailed earlier, conversations with AIs, like anything traveling over the internet, are susceptible to being hacked.

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See also Hello Barbie Bartneck, Christoph, 193 Bates, James, 222–24 beam forming, 43 Bell, Alexander Graham, 69 Bell, Alexander Melville, 68–69 Bell Laboratories, 70, 91–92, 110 Belsky, Jared, 209 Bengio, Yoshua, 89, 91–94, 100, 143, 148 Benini, JP, 235 Bennett, Susan, 110–12 Bergen, Hilary, 131 Bessi, Alessandro, 216 Bezos, Jeff, 39–40, 42, 43, 44, 54, 214 Bhat, Ash, 216 Bicentennial Man (film), xi Bing search engine, 49, 212, 213, 281 Black Mirror (TV show), 250 Blake’s 7 (TV show), 199 Blanchett, Cate, 271 Blue Origin, 39 Bonaparte, Napoleon, 66 Bonelli, Sherry, 208 Boole, George, 89 brazen heads, 9, 64–65 Breazeal, Cynthia, 191–92 Brigham, Chris, 55 Brown, Dan, 199 Buber, Martin, 188 Burkey, John, 48, 50 Butler, Samuel, 68 C Call of Duty (video game), 172–73, 253 CALO (Cognitive Assistant that Learns and Organizes), 22–23, 24, 25 Cambridge Analytica, 248 Canadian Institute for Advanced Research “Canadian Mafia,” 10, 89, 92 Capital One, 132 Carolan, Shawn, 27–28 Cassell, Justine, 132 Cecchi, Guillermo, 248 celebrity bots, 58 Celebrity Net Worth, 210–11 Cerf, Vint, 75 CES (Consumer Electronics Show), xiii–xvi, 7, 43 chatbots (conversational bots).

News and How to Use It: What to Believe in a Fake News World by Alan Rusbridger

airport security, basic income, Bellingcat, Big Tech, Black Lives Matter, Bletchley Park, Boris Johnson, Brexit referendum, call centre, Cambridge Analytica, Chelsea Manning, citizen journalism, Climategate, cognitive dissonance, coronavirus, correlation does not imply causation, COVID-19, Credit Default Swap, crisis actor, cross-subsidies, crowdsourcing, disinformation, Dominic Cummings, Donald Trump, Edward Snowden, end-to-end encryption, fake news, Filter Bubble, future of journalism, George Floyd, ghettoisation, global pandemic, Google Earth, green new deal, hive mind, housing crisis, Howard Rheingold, illegal immigration, Intergovernmental Panel on Climate Change (IPCC), Jeff Bezos, Jeffrey Epstein, Jeremy Corbyn, Johann Wolfgang von Goethe, Julian Assange, Kickstarter, lockdown, Mark Zuckerberg, Murray Gell-Mann, Narrative Science, Neil Kinnock, Nelson Mandela, New Journalism, Nicholas Carr, ocean acidification, offshore financial centre, post-truth, profit motive, public intellectual, publication bias, Seymour Hersh, Snapchat, social distancing, Social Justice Warrior, Steve Bannon, tech baron, the scientific method, TikTok, universal basic income, WikiLeaks, yellow journalism