23andMe

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

23andMe, 3D printing, Affordable Care Act / Obamacare, Anne Wojcicki, Atul Gawande, augmented reality, Big Tech, bioinformatics, call centre, Clayton Christensen, clean water, cloud computing, commoditize, computer vision, conceptual framework, connected car, correlation does not imply causation, creative destruction, crowdsourcing, dark matter, data acquisition, data science, deep learning, digital divide, disintermediation, disruptive innovation, don't be evil, driverless car, Edward Snowden, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Firefox, gamification, global village, Google Glasses, Google X / Alphabet X, Ignaz Semmelweis: hand washing, information asymmetry, interchangeable parts, Internet of things, Isaac Newton, it's over 9,000, job automation, Julian Assange, Kevin Kelly, license plate recognition, lifelogging, Lyft, Mark Zuckerberg, Marshall McLuhan, meta-analysis, microbiome, Nate Silver, natural language processing, Network effects, Nicholas Carr, obamacare, pattern recognition, personalized medicine, phenotype, placebo effect, quantum cryptography, RAND corporation, randomized controlled trial, Salesforce, Second Machine Age, self-driving car, Silicon Valley, Skype, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, Snapchat, social graph, speech recognition, stealth mode startup, Steve Jobs, synthetic biology, the scientific method, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, traumatic brain injury, Turing test, Uber for X, uber lyft, Watson beat the top human players on Jeopardy!, WikiLeaks, X Prize

Hill, “The FDA Just Ruined Your Plans to Buy 23andMe’s DNA Test as a Christmas Present,” Forbes, November 25, 2013, http://www.forbes.com/sites/kashmirhill/2013/11/25/fda-23andme/. 58. L. Kish, “The Social Conquest of Medicine: The 23andMe and Conflict,” HL7 Standards, January 7, 2014, http://www.hl7standards.com/blog/2014/01/07/23andme/. 59. J. Kiss, “23andMe Admits FDA Order ‘Significantly Slowed Up’ New Customers,” The Guardian, March 9, 2014, http://www.theguardian.com/technology/2014/mar/09/google-23andme-anne-wojcicki-genetics-healthcare-dna/print. 60. A. Krol, “Show, Don’t Tell: 23andMe Pursues Health Research in the Shadow of the FDA,” Bio-IT World, March 24, 2014, http://www.bio-itworld.com/2014/3/24/show-dont-tell-23andme-pursues-health-research-shadow-fda.html. 61.

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“Multiple Testing an Issue for 23andMe,” Bits of DNA, November 30, 2013, http://liorpachter.wordpress.com/2013/11/30/23andme-genotypes-are-all-wrong/. 55. “23andMe: State of Debate,” Bio-IT World, November 27, 2013, http://www.bio-itworld.com/2013/11/27/23andme-state-of-debate.html. 56. M. Hiltzik, “23andMe’s Genetic Tests Are More Misleading Than Helpful,” Los Angeles Times, December 15, 2013, http://www.latimes.com/business/la-fi-hiltzik-20131215,0,1359952.column. 57. K. Hill, “The FDA Just Ruined Your Plans to Buy 23andMe’s DNA Test as a Christmas Present,” Forbes, November 25, 2013, http://www.forbes.com/sites/kashmirhill/2013/11/25/fda-23andme/. 58.

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Pollack, “Genetic Tester to Stop Providing Data on Health Risks,” New York Times, December 6, 2013, http://www.nytimes.com/2013/12/06/business/genetic-tester-to-stop-providing-data-on-health-risks.html. 37. F. Polli, “Why 23andMe Deserves a Second Chance,” Forbes, January 14, 2014, http://www.forbes.com/sites/fridapolli/2014/01/14/why-23andme-deserves-a-second-chance/. 38. T. Ray, “Facing FDA Warning Letter and Lawsuit, Can 23andMe Stay True to Its DTC Credo in 15 Days?,” GenomeWeb, December 4, 2013, http://www.genomeweb.com/print/1319176?utm_source=SilverpopMai%C9PGxUncertainty. 39. R. Rekhi, “A Government Ban on 23andMe’s Genetic Testing Services Ignores Reality,” The Guardian, December 4, 2013, http://www.theguardian.com/commentisfree/2013/dec/04/23andme-consumer-genomics-fda-ban-regulation/print. 40.

The Industries of the Future by Alec Ross

"World Economic Forum" Davos, 23andMe, 3D printing, Airbnb, Alan Greenspan, algorithmic bias, algorithmic trading, AltaVista, Anne Wojcicki, autonomous vehicles, banking crisis, barriers to entry, Bernie Madoff, bioinformatics, bitcoin, Black Lives Matter, blockchain, Boston Dynamics, Brian Krebs, British Empire, business intelligence, call centre, carbon footprint, clean tech, cloud computing, collaborative consumption, connected car, corporate governance, Credit Default Swap, cryptocurrency, data science, David Brooks, DeepMind, Demis Hassabis, disintermediation, Dissolution of the Soviet Union, distributed ledger, driverless car, Edward Glaeser, Edward Snowden, en.wikipedia.org, Erik Brynjolfsson, Evgeny Morozov, fiat currency, future of work, General Motors Futurama, global supply chain, Google X / Alphabet X, Gregor Mendel, industrial robot, information security, Internet of things, invention of the printing press, Jaron Lanier, Jeff Bezos, job automation, John Markoff, Joi Ito, Kevin Roose, Kickstarter, knowledge economy, knowledge worker, lifelogging, litecoin, low interest rates, M-Pesa, machine translation, Marc Andreessen, Mark Zuckerberg, Max Levchin, Mikhail Gorbachev, military-industrial complex, mobile money, money: store of value / unit of account / medium of exchange, Nelson Mandela, new economy, off-the-grid, offshore financial centre, open economy, Parag Khanna, paypal mafia, peer-to-peer, peer-to-peer lending, personalized medicine, Peter Thiel, precision agriculture, pre–internet, RAND corporation, Ray Kurzweil, recommendation engine, ride hailing / ride sharing, Rubik’s Cube, Satoshi Nakamoto, selective serotonin reuptake inhibitor (SSRI), self-driving car, sharing economy, Silicon Valley, Silicon Valley startup, Skype, smart cities, social graph, software as a service, special economic zone, supply-chain management, supply-chain management software, technoutopianism, TED Talk, The Future of Employment, Travis Kalanick, underbanked, unit 8200, Vernor Vinge, Watson beat the top human players on Jeopardy!, women in the workforce, work culture , Y Combinator, young professional

Founded by Anne Wojcicki: Katie Hafner, “Silicon Valley Wide-Eyed over a Bride,” New York Times, May 29, 2007, http://www.nytimes.com/2007/05/29/technology/29google.html. the company provides ancestry-related: “How It Works,” 23andMe, https://www.23andme.com/howitworks/. It’s not a full sequencing: “About the 23andMe Personal Genome Service,” 23andMe, https://customercare.23andme.com/entries/22591668. Since then, he drinks green tea: Elizabeth Murphy, “Do You Want to Know What Will Kill You?” Salon, October 25, 2013, http://www.salon.com/2013/10/25/inside_23andme_founder_anne_wojcickis_99_dna_revolution_newscred/. all of them have faced: Kira Peikoff, “I Had My DNA Picture Taken, with Varying Results,” New York Times, December 30, 2013, http://www.nytimes.com/2013/12/31/science/i-had-my-dna-picture-taken-with-varying-results.html?

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The FDA’s public letter: “23andMe, Inc. 11/22/13,” FDA: Inspections, Compliance, Enforcement, and Criminal Investigation Warning Letters, November 22, 2013, http://www.fda.gov/iceci/enforcementactions/warningletters/2013/ucm376296.htm; Scott Hensley, “23andMe Bows to FDA’s Demands, Drops Health Claims,” National Public Radio, December 6, 2013, http://www.npr.org/blogs/health/2013/12/06/249231236/23andme-bows-to-fdas-demands-drops-health-claims. Now their tests promise only: Ibid. At this time we do not: “How It Works.” Through a partnership: “Michael J. Fox, Our Big-Time Hero,” 23andMe, April 27, 2012, http://blog.23andme.com/news/inside-23andme/michael-j-fox-our-big-time-hero/; Matthew Herper, “Surprise! With $60 Million Genentech Deal, 23andMe Has a Business Plan,” Forbes, January 6, 2015, http://www.forbes.com/sites/matthewherper/2015/01/06/surprise-with-60-million-genentech-deal-23andme-has-a-business-plan/. Its signature product, Genophen, sequences: “Our Model,” Genophen: How It Works, http://www.genophen.com/consumers/how-it-works/our-model; Davis, “It’s Time to Bet on Genomics.”

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all of them have faced: Kira Peikoff, “I Had My DNA Picture Taken, with Varying Results,” New York Times, December 30, 2013, http://www.nytimes.com/2013/12/31/science/i-had-my-dna-picture-taken-with-varying-results.html?src=recg. In late 2013, it demanded: Chris O’Brien, “23andMe Suspends Health-Related Genetic Tests after FDA Warning,” Los Angeles Times, December 6, 2013, http://articles.latimes.com/2013/dec/06/business/la-fi-tn-23andme-suspends-tests-fda-20131205. The FDA’s public letter: “23andMe, Inc. 11/22/13,” FDA: Inspections, Compliance, Enforcement, and Criminal Investigation Warning Letters, November 22, 2013, http://www.fda.gov/iceci/enforcementactions/warningletters/2013/ucm376296.htm; Scott Hensley, “23andMe Bows to FDA’s Demands, Drops Health Claims,” National Public Radio, December 6, 2013, http://www.npr.org/blogs/health/2013/12/06/249231236/23andme-bows-to-fdas-demands-drops-health-claims.

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

Francis Galton, ‘On the Anthropometric Laboratory at the late international health exhibition’, Journal of the Anthropological Institute of Great Britain and Ireland, vol. 14, 1885, pp. 205–21. 53. ‘Taste’, https://permalinks.23andme.com/pdf/samplereport_traits.pdf. 54. ‘Sneezing on summer solstice?’, 23andMeBlog, 20 June 2012, https://blog.23andme.com/health-traits/sneezing-on-summer-solstice/. 55. ‘Find out what your DNA says about your health, traits and ancestry’, 23andMe, https://www.23andme.com/en-gb/dna-health-ancestry/. 56. Kristen v. Brown, ‘23andMe is selling your data but not how you think’, Gizmodo, 14 April 2017, https://gizmodo.com/23andme-is-selling-your-data-but-not-how-you-think-1794340474. 57. Michael Grothaus, ‘How23andMe is monetizing your DNA’, Fast Company, 15 Jan. 2015, https://www.fastcompany.com/3040356/what-23andme-is-doing-with-all-that-dna. 58.

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Academics, pharmaceutical companies and non-profits around the world are queuing up to partner with 23andMe to hunt for patterns in their data – both with and without the help of algorithms – in the hope of answering big questions that affect all of us: What are the hereditary causes of different diseases? Are there new drugs that could be invented to treat people with particular conditions? Is there a better way to treat Parkinson’s? The dataset is also valuable in a much more literal sense. Although the research being done offers an immense benefit to society, 23andMe isn’t doing this out of the goodness of its heart. If you give it your consent (and 80 per cent of customers do), it will sell on an anonymized version of your genetic data to those aforementioned research partners for a tidy profit.56 The money earned isn’t a happy bonus for the company; it’s actually their business plan.

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Erlich, ‘Identifying personal genomes by surname inference’, Science, vol. 339, no. 6117, Jan. 2013, pp. 321–4, https://www.ncbi.nlm.nih.gov/pubmed/23329047. 61. Currently, genetic tests for Huntington’s disease are not available from any commercial DNA testing kits. 62. Matthew Herper, ‘23andMe rides again: FDA clears genetic tests to predict disease risk’, Forbes, 6 April 2017, https://www.forbes.com/sites/matthewherper/2017/04/06/23andme-rides-again-fda-clears-genetic-tests-to-predict-disease-risk/#302aea624fdc. Cars 1. DARPA, Grand Challenge 2004: Final Report (Arlington, VA: Defence Advanced Research Projects Agency, 30 July 2004), http://www.esd.whs.mil/Portals/54/Documents/FOID/Reading%20Room/DARPA/15-F-0059_GC_2004_FINAL_RPT_7-30-2004.pdf. 2.

Mine!: How the Hidden Rules of Ownership Control Our Lives by Michael A. Heller, James Salzman

23andMe, Airbnb, behavioural economics, Berlin Wall, Big Tech, British Empire, Cass Sunstein, clean water, collaborative consumption, Cornelius Vanderbilt, coronavirus, COVID-19, CRISPR, crowdsourcing, Donald Trump, Downton Abbey, Elon Musk, endowment effect, estate planning, facts on the ground, Fall of the Berlin Wall, Firefox, Garrett Hardin, gig economy, Hernando de Soto, Internet of things, land tenure, Mason jar, Neil Armstrong, new economy, North Sea oil, offshore financial centre, oil rush, planetary scale, race to the bottom, recommendation engine, rent control, Richard Thaler, Ronald Coase, sharing economy, Shoshana Zuboff, Silicon Valley, Silicon Valley startup, social distancing, South China Sea, sovereign wealth fund, stem cell, surveillance capitalism, TaskRabbit, The future is already here, Tim Cook: Apple, Tony Fadell, Tragedy of the Commons, you are the product, Zipcar

Twenty days of data from a fitness tracker is worth two of Barry’s shares, valued at 14 cents; a 23andMe–style test earns you $3.50 in shares; your whole genome nets you $21. People cash in if the start-up shares do well—thus reversing the cash flow from the 23andMe model. But the stock ownership model has downsides, too. It’s meaningfully available only to the handful of sophisticated consumers who search it out, prefer stock to cheap testing, and deliberately opt in to this ownership relationship. Most people keep on mailing in 23andMe and Ancestry.com kits, clicking “I consent,” and getting no direct compensation (though there may be some indirect compensation if it costs companies more to test than consumers pay).

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Control over genetic data raises questions beyond personal privacy and dignity, though those matter, too. As people submit more DNA, the commercial value of gene databases grows exponentially. Medical data licensing has become a multibillion-dollar business. GlaxoSmithKline paid 23andMe $300 million to access data for targeted drug development. 23andMe went one step further, developing an anti-inflammatory drug based on its data. The company already has over 9 million individual profiles; the industry as a whole has over 25 million. There are ever-growing fortunes at stake. Brown decided to retrieve her genetic data.

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With its head start in collecting samples, the database now lets the company detect a wider range of mutations than competitors are able to find—and charge for the information. As databases scale up, they can become exponentially more valuable. The key is to grow the database fast. This is why 23andMe decodes your heritage for just $99: your genetic information is raw material for the real product, its database. To preserve the Wild West regime, the industry has been working to fend off ownership regulation. In a savvy move, companies like 23andMe decided not to fight Brown and others like her. Gene companies have learned the lessons of Napster and music streaming, of HBO and password sharing. Don’t hassle your customers; find less irritating ways to extract value from scarce human resources.

100 Plus: How the Coming Age of Longevity Will Change Everything, From Careers and Relationships to Family And by Sonia Arrison

23andMe, 8-hour work day, Abraham Maslow, Albert Einstein, Anne Wojcicki, artificial general intelligence, attribution theory, Bill Joy: nanobots, bioinformatics, caloric restriction, caloric restriction, Clayton Christensen, dark matter, disruptive innovation, East Village, en.wikipedia.org, epigenetics, Frank Gehry, Googley, income per capita, indoor plumbing, Jeff Bezos, Johann Wolfgang von Goethe, Kickstarter, Larry Ellison, Law of Accelerating Returns, life extension, Nick Bostrom, personalized medicine, Peter Thiel, placebo effect, post scarcity, precautionary principle, radical life extension, Ray Kurzweil, rolodex, Silicon Valley, Silicon Valley billionaire, Simon Kuznets, Singularitarianism, smart grid, speech recognition, stem cell, Stephen Hawking, Steve Jobs, Steve Wozniak, Steven Levy, sugar pill, synthetic biology, Thomas Malthus, upwardly mobile, World Values Survey, X Prize

Kim, “Effects of Aging on Mouse Transcriptional Networks,” NLM Informatics Training Conference 2007, Stanford University, Stanford, California, June 26–27, 2007, www.nlm.nih.gov/ep/trainingconf2007agenda.html#22. 69 Matt C, “23andMe Struts Its Stuff in NYC During Fashion Week,” The Spittoon, September 11, 2008, http://spittoon.23andme.com/2008/09/11/23andme-struts-its-stuff-in-nyc-during-fashion-week/. 70 Andrew Pollack, “Google Co-founder Backs Vast Parkinson’s Study,” New York Times, March 11, 2009, www.nytimes.com/2009/03/12/business/12gene.html?_r=1. 71 Leena Rao, “While 23andMe Raises $11 Million, Mohr Davidow Sells Stake to Invest in Rival,” TechCrunch, May 4, 2009, http://techcrunch.com/2009/05/04/while-23 andme-raises-11-million-mohr-davidow-sells-stake-to -invest-in-rival/. 72 Thomas Goetz, “Sergey Brin’s Search for a Parkinson’s Cure,” Wired, June 22, 2010, www.wired.com/magazine/2010/06/ff_sergeys_search/. 73 Ibid. 74 Interview with Mike Kope, November 11, 2010. 75 Allen Institute, “Paul G.

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Kim, who is a well-known aging expert and one of Larry Ellison’s award recipients.68 Sergey Brin is spreading the meme in a more personal way. 23andMe is a genomics company that was cofounded by Brin’s biologist wife, Anne Wojcicki, and has gone a long way toward popularizing the idea of personalized medicine. “Spit parties” are one of the cute marketing techniques the company uses to get the public interested in thinking about their DNA and how it might be fixed to cure disease. One high-profile party took place during New York City’s Fashion Week. Company staffers recounted the event on their blog, saying, “23andMe managed to lure a few hundred people away from the catwalks Tuesday night to consider the beauty that lies within—DNA.

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While the first Human Genome Project cost roughly $2.7 billion and Craig Venter spent about $70 million to sequence his own genome, by 2009 it was possible to get a genome sequenced for $5,000 and the $1,000 genome (or less) is in sight. Indeed, a partial DNA scan can already be had for only $199 at consumer genomics companies like 23andMe, and that company is using its data sets to attempt to link certain diseases to specific genes, important work on the way toward individually tailored pharmaceuticals and cures.46 Given the speed at which prices for new technology are shooting downward, particularly in biotechnology, the time horizon between longevity technology adoption by the rich and then by the poor within developed countries will probably shrink enough that few will consider taking up arms or unduly involving the state in repairing their bodies.

Denialism: How Irrational Thinking Hinders Scientific Progress, Harms the Planet, and Threatens Our Lives by Michael Specter

23andMe, agricultural Revolution, An Inconvenient Truth, Anne Wojcicki, Any sufficiently advanced technology is indistinguishable from magic, Apollo 13, Asilomar, autism spectrum disorder, carbon footprint, Cass Sunstein, clean water, Drosophila, Edward Jenner, food miles, Gregor Mendel, Helicobacter pylori, invention of gunpowder, John Elkington, Neil Armstrong, out of africa, personalized medicine, placebo effect, precautionary principle, profit motive, randomized controlled trial, Recombinant DNA, Richard Feynman, Richard Feynman: Challenger O-ring, Ronald Reagan, Simon Singh, Skype, stem cell, synthetic biology, technological determinism, Ted Kaczynski, the scientific method, Thomas Malthus, twin studies, Upton Sinclair, X Prize

In 2007, seizing on the cascade of genetic information that had suddenly become acessible, deCODE and two California companies, 23andme and Navigenics, began to sell gene-testing services directly to consumers. The tests analyze up to one million of the most common SNPs—a small fraction of our genome—focusing on the most powerfully documented relationships between those SNPs and common diseases. For each disease or condition, the companies estimate the risk of a healthy person developing that illness. Both deCODE and 23andme sold their first tests for just under $1,000, but prices keep falling. By the end of 2008, a 23andme test cost $400. Navigenics charges $2,500 for its full regimen, which includes the services of genetics counselors; deCODE offers packages at various prices.

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Navigenics charges $2,500 for its full regimen, which includes the services of genetics counselors; deCODE offers packages at various prices. Much of deCODE’s research relies on its own formidable database, while 23andme, whose slogan is “Genetics just got personal,” has emphasized genealogy and intellectual adventure, not just medicine, and encourages customers to share data, participate in research studies, and form social networks on its Web site. In 2008, Time magazine named the 23andme test as its invention of the year, but critics have described the company’s approach as frivolous because it not only provides disease information but also helps customers learn about less useful—but perhaps more amusing—traits like whether they have dry ear wax or can taste bitter foods.

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Well, if the study is correct I still have far less than a 1 percent chance of experiencing myopathy. I’ll take those odds. As 23andme points out in its description of the statin response, “Please note that myopathy is a very rare side effect of statins even among those with genotypes that increase their odds of experiencing it.” The risks of heart disease, however, and, in my family, Alzheimer’s disease, are not rare. CRUISING THROUGH ONE’S genomic data is not for the faint of heart. Thanks to 23andme, I now know that I am left-eyed and can taste bitter food. Cool. But I am also a slow caffeine metabolizer. That’s a shame, because for people like me coffee increases the risk of heart attack, and I already have plenty of those risks.

Masters of Scale: Surprising Truths From the World's Most Successful Entrepreneurs by Reid Hoffman, June Cohen, Deron Triff

"Susan Fowler" uber, 23andMe, 3D printing, Airbnb, Anne Wojcicki, Ben Horowitz, bitcoin, Blitzscaling, Broken windows theory, Burning Man, call centre, chief data officer, clean water, collaborative consumption, COVID-19, crowdsourcing, data science, desegregation, do well by doing good, Elon Musk, financial independence, fulfillment center, gender pay gap, global macro, growth hacking, hockey-stick growth, Internet of things, knowledge economy, late fees, Lean Startup, lone genius, Marc Benioff, Mark Zuckerberg, minimum viable product, move fast and break things, Network effects, Paul Graham, Peter Thiel, polynesian navigation, race to the bottom, remote working, RFID, Ronald Reagan, Rubik’s Cube, Ruby on Rails, Salesforce, Sam Altman, Sheryl Sandberg, Silicon Valley, Silicon Valley startup, social distancing, Steve Jobs, Susan Wojcicki, TaskRabbit, TechCrunch disrupt, TED Talk, the long tail, the scientific method, Tim Cook: Apple, Travis Kalanick, two and twenty, work culture , Y Combinator, zero day, Zipcar

They suddenly had patients coming in saying, “Look what I’ve learned about my health risks from DNA testing—what should I do?” Doctors were used to being the gatekeepers of that type of information. So 23andMe began an ongoing effort to convince physicians that it was a good thing for patients to be proactively asking more questions about their health. But the biggest challenge for 23andMe was dealing with state and federal regulators. One particularly challenging gatekeeper was the U.S. Food and Drug Administration. Anne and her team had been meeting with the FDA since early days, but because 23andMe was a first-of-its-kind company, government regulators didn’t know how to classify it. (Note to readers: Occasionally, being a first-in-field, groundbreaking innovator makes you very annoying to regulators.)

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But you’ve got to know that you’re committed to doing that.’ ” Anne’s response: “I’m not going anywhere. What else do I have to do? I’m committed.” Anne and her 23andMe team decided to slow down the rollout of new products. Usually this is the last thing a founder should do. But in 23andMe’s case, no one else was going to swoop in and grab market share—the FDA was a hard barrier that someone would need to break through. Anne decided it would be her. Although working with the FDA would prove slow and sometimes painful, it would build the trust that allowed 23andMe to grow in the long term. “Our work with the FDA changed our company a lot,” says Anne. “Our engineers, the way we develop, the way we do quality control—it’s a very different process now.

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“Then we saw it trickle down to ten to twenty kits a day. It was sad. In those early days, people would say, ‘Wouldn’t my doctor pay for that? Why am I paying for it? What would I do with the results?’ ” As the 23andMe founders grappled with the problem of reaching consumers, Anne’s marketing team suggested a messaging pivot. Instead of emphasizing a health-information angle, 23andMe began playing up the joys of discovering and sharing your ancestry. Bingo—customers warmed to the idea of getting closer to their roots. And if they could also gain more information about their health, well, that was a nice bonus.

Super Founders: What Data Reveals About Billion-Dollar Startups by Ali Tamaseb

"World Economic Forum" Davos, 23andMe, additive manufacturing, Affordable Care Act / Obamacare, Airbnb, Anne Wojcicki, asset light, barriers to entry, Ben Horowitz, Benchmark Capital, bitcoin, business intelligence, buy and hold, Chris Wanstrath, clean water, cloud computing, coronavirus, corporate governance, correlation does not imply causation, COVID-19, cryptocurrency, data science, discounted cash flows, diversified portfolio, Elon Musk, Fairchild Semiconductor, game design, General Magic , gig economy, high net worth, hiring and firing, index fund, Internet Archive, Jeff Bezos, John Zimmer (Lyft cofounder), Kickstarter, late fees, lockdown, Lyft, Marc Andreessen, Marc Benioff, Mark Zuckerberg, Max Levchin, Mitch Kapor, natural language processing, Network effects, nuclear winter, PageRank, PalmPilot, Parker Conrad, Paul Buchheit, Paul Graham, peer-to-peer lending, Peter Thiel, Planet Labs, power law, QR code, Recombinant DNA, remote working, ride hailing / ride sharing, robotic process automation, rolodex, Ruby on Rails, Salesforce, Sam Altman, Sand Hill Road, self-driving car, shareholder value, sharing economy, side hustle, side project, Silicon Valley, Silicon Valley startup, Skype, Snapchat, SoftBank, software as a service, software is eating the world, sovereign wealth fund, Startup school, Steve Jobs, Steve Wozniak, survivorship bias, TaskRabbit, telepresence, the payments system, TikTok, Tony Fadell, Tony Hsieh, Travis Kalanick, Uber and Lyft, Uber for X, uber lyft, ubercab, web application, WeWork, work culture , Y Combinator

For some billion-dollar startups, creating the market offers clear advantages. Take 23andMe. Before the consumer genetic-testing company was launched, most people would raise their eyebrows at the invitation to mail a tube of their saliva to a startup in Silicon Valley. Genetics testing was, at the time, mostly medical. Few people had used it to calculate their genetic predisposition to certain ailments. In other words, there was no market for consumer genetic testing. The founders of 23andMe—Anne Wojcicki, Linda Avey, and Paul Cusenza—had to create one. The company 23andMe was one of the first to offer autosomal genetics testing for ancestry applications using saliva, and it took years for sales to ramp up beyond the early adopters.

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In the same way that the capability to make cheaper computers opened up personal computing and gave birth to companies like Microsoft, the reduction in costs of DNA sequencing made possible companies like 23andMe. Now, over ten million people have taken the test—and plenty of other consumer genetics companies have sprung up as competitors. Consumer demand and market size are not factors to be taken for granted, however, especially when a new market and a new demand type are being created. While 23andMe had a strong growth rate for years, the company was struggling with direct-to-consumer demand growth at the time of writing this book, as the early adopters of the technology dried up. Time will tell whether 23andMe will be able to use its wealth of clinical data and partnerships with pharmaceutical companies to create a generational company, or whether it will lose its unicorn status.

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The company 23andMe was one of the first to offer autosomal genetics testing for ancestry applications using saliva, and it took years for sales to ramp up beyond the early adopters. Initially, the tests were expensive—23andMe charged $999 for each test back in 2008. Only a very small population of affluent individuals could afford the tests, so the founders of 23andMe threw “spit parties” at high-end gatherings, like the World Economic Forum in Davos, Switzerland, in an attempt to win influential customers. As the volumes went up and Moore’s Law (a historical trend in which the computational power of electronic chips doubles while the cost halves about every two years) became applicable to genetics, the cost for sequencing DNA went down considerably, opening and growing the market.

The Mutant Project: Inside the Global Race to Genetically Modify Humans by Eben Kirksey

23andMe, Abraham Maslow, Affordable Care Act / Obamacare, Albert Einstein, Bernie Sanders, bioinformatics, bitcoin, Black Lives Matter, blockchain, Buckminster Fuller, clean water, coronavirus, COVID-19, CRISPR, cryptocurrency, data acquisition, deep learning, Deng Xiaoping, Donald Trump, double helix, epigenetics, Ethereum, ethereum blockchain, experimental subject, fake news, gentrification, George Floyd, Jeff Bezos, lockdown, Mark Zuckerberg, megacity, microdosing, moral panic, move fast and break things, personalized medicine, phenotype, placebo effect, randomized controlled trial, Recombinant DNA, Shenzhen special economic zone , Shenzhen was a fishing village, Silicon Valley, Silicon Valley billionaire, Skype, special economic zone, statistical model, stem cell, surveillance capitalism, tech billionaire, technological determinism, upwardly mobile, urban planning, young professional

My journalist friend found a way to opt out of BGI’s genome collection program, but only after she carefully searched through the fine print. Though the NIFTY test has not been approved for use in the United States, many other companies, like 23andMe, have long provided genetic tests directly to consumers. In 2013 the FDA ordered 23andMe to stop distributing misleading information about subscribers’ genetic predisposition to hundreds of health problems. A new ruling in 2017 allowed 23andMe to reveal test results for genetic mutations that are strongly associated with a small group of medical conditions like Parkinson’s disease, late-onset Alzheimer’s disease, and celiac disease.

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Lifestyle, diet, exposures to environmental pollution, and family history also strongly influence the likelihood that a person will develop one of these diseases.6 Over 10 million people have already voluntarily contributed genetic samples to 23andMe. These genetic tests are low quality because they are based on small DNA fragments rather than the high-fidelity whole genome sequences being stored in the China National GeneBank. Companies like 23andMe might soon seem quaint and obsolete, as companies like BGI outpace them with more definitive medical applications. At the same time, 23andMe is already exposing some people to ongoing risks of surveillance and discrimination. Forensic investigators in the United States have started to make aggressive use of genetic testing, keeping pace with police counterparts in China who have been targeting Muslim Uyghurs and political dissidents.

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Nonetheless, old ideas about race have been very slow to die. “In our society the social categories of race are a reality that affects our lives,” notes Agustín Fuentes, a primatologist and authority on human evolution. “Race is not biology, but race affects biology, experience, and social context,” Fuentes writes. Companies like 23andMe are turning a profit from DNA testing kits in the United States while fueling misconceptions about race and genetics. Tests that claim to reveal your ancestors’ geographical origins are based on “junk science,” according to Jonathan Marks, a biological anthropologist. Genetic tests can reliably tell you who your parents are—and commercial kits often substantiate rumors about Mom or Dad’s sexual infidelities—but the scientific evidence gets very murky when you try to move past your grandparents’ generation.

Blockchain: Blueprint for a New Economy by Melanie Swan

23andMe, Airbnb, altcoin, Amazon Web Services, asset allocation, banking crisis, basic income, bioinformatics, bitcoin, blockchain, capital controls, cellular automata, central bank independence, clean water, cloud computing, collaborative editing, Conway's Game of Life, crowdsourcing, cryptocurrency, data science, digital divide, disintermediation, Dogecoin, Edward Snowden, en.wikipedia.org, Ethereum, ethereum blockchain, fault tolerance, fiat currency, financial innovation, Firefox, friendly AI, Hernando de Soto, information security, intangible asset, Internet Archive, Internet of things, Khan Academy, Kickstarter, Large Hadron Collider, lifelogging, litecoin, Lyft, M-Pesa, microbiome, Neal Stephenson, Network effects, new economy, operational security, peer-to-peer, peer-to-peer lending, peer-to-peer model, personalized medicine, post scarcity, power law, prediction markets, QR code, ride hailing / ride sharing, Satoshi Nakamoto, Search for Extraterrestrial Intelligence, SETI@home, sharing economy, Skype, smart cities, smart contracts, smart grid, Snow Crash, software as a service, synthetic biology, technological singularity, the long tail, Turing complete, uber lyft, unbanked and underbanked, underbanked, Vitalik Buterin, Wayback Machine, web application, WikiLeaks

wiseGEEK, December 25, 2014. http://www.wisegeek.com/what-is-bittorrent.htm#didyouknowout. 2 Beal, V. “Public-key encryption.” Webopedia. http://www.webopedia.com/TERM/P/public_key_cryptography.html. 3 Hof, R. “Seven Months After FDA Slapdown, 23andMe Returns with New Health Report Submission.” Forbes, June 20, 2014. http://www.forbes.com/sites/roberthof/2014/06/20/seven-months-after-fda-slapdown-23andme-returns-with-new-health-report-submission/. 4 Knight, H. and B. Evangelista. “S.F., L.A. Threaten Uber, Lyft, Sidecar with Legal Action.” SFGATE, September 25, 2041. http://m.sfgate.com/bayarea/article/S-F-L-A-threaten-Uber-Lyft-Sidecar-with-5781328.php. 5 Although it is not strictly impossible for two files to have the same hash, the number of 64-character hashes is vastly greater than the number of files that humanity can foreseeably create.

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New England Journal of Medicine 361 (July 16, 2009):245–54. http://www.nejm.org/doi/full/10.1056/NEJMoa0809578 and discussed in further detail at http://www.genomes2people.org/director/. 141 Regalado, A. “The FDA Ordered 23andMe to Stop Selling Its Health Tests. But for the Intrepid, Genome Knowledge Is Still Available.” MIT Technology Review, October 19, 2014. http://www.technologyreview.com/featuredstory/531461/how-a-wiki-is-keeping-direct-to-consumer-genetics-alive/. 142 DeCODEme. “Sales of Genetic Scans Direct to Consumer Through deCODEme Have Been Discontinued! Existing Customers Can Access Their Results Here Until January 1st 2015.” http://en.wikipedia.org/wiki/DeCODE_genetics. 143 Castillo, M. “23andMe to Only Provide Ancestry, Raw Genetics Data During FDA Review.”

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One example of this is DNA.bits, a startup that encodes patient DNA records to the blockchain, and makes them available to researchers by private key.151 However, it is not just that private health data research commons could be established with the blockchain, but also public health data commons. Blockchain technology could provide a model for establishing a cost-effective public-health data commons. Many individuals would like to contribute personal health data—like personal genomic data from 23andMe, quantified-self tracking device data (FitBit), and health and fitness app data (MapMyRun)—to data research commons, in varying levels of openness/privacy, but there has not been a venue for this. This data could be aggregated in a public-health commons (like Wikipedia for health) that is open to anyone, citizen scientists and institutional researchers alike, to perform data analysis.

Facing Reality: Two Truths About Race in America by Charles Murray

2021 United States Capitol attack, 23andMe, affirmative action, Black Lives Matter, centre right, correlation coefficient, critical race theory, Donald Trump, feminist movement, gentrification, George Floyd, Gunnar Myrdal, income inequality, invention of agriculture, longitudinal study, low skilled workers, medical malpractice, meta-analysis, publication bias, school vouchers, Silicon Valley, The Bell Curve by Richard Herrnstein and Charles Murray, War on Poverty

Geneticists have dealt with this problem by dispensing with both race and ethnicity, and instead using the word population. They have found that they can accurately calibrate people’s mix of ancestral heritages, whether they are popularly understood as races or ethnicities, by examining patterns of genetic variants. That’s why commercial genetic testing companies such as 23andMe and AncestryDNA can, in return for a fee, tell you the breakdown of your own racial heritage. The level of detail that geneticists can achieve depends on the number of genetic variants they include in the analysis. “Who are you?” racially and ethnically has different answers at different levels of specificity, and this is an excellent reason not to think in terms of races.

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Yet the census data tell us that 96.6 percent of us self-identify with a single race. This unrealistically high percentage can be seen as a common-sense compromise between genetic precision and cultural reality. Taken as a group, self-identified Whites have complicated mixes of European ethnicities, but little racial ambiguity. In a large study based on 23andMe data, they had a mean of 98.6 percent European ancestry, 0.2 percent Native American ancestry, and 0.2 percent African ancestry, with the rest being “Other.” Self-identified Blacks in America have a significant White admixture – something that has roots in slavery and has been known anecdotally throughout American history.

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But that mating may have occurred at any time since 1492. People with varying amounts of Spanish and indigenous ancestry have been intermarrying for so long that it is reasonable for them to believe that their racial composition now amounts to a distinct category. The answers to the Census Bureau’s questions are consistent with the 23andMe genetic findings about Latinos. In that sample, the self-identified Latinos showed 65.1 percent European ancestry, 6.2 percent African ancestry, and 18.0 percent Native American ancestry, leaving 10.7 percent for the rest. But these numbers are far from evenly distributed across the self-identified Latinos.

Who We Are and How We Got Here: Ancient DNA and the New Science of the Human Past by David Reich

23andMe, agricultural Revolution, Alfred Russel Wallace, carbon credits, Easter island, European colonialism, Google Earth, Great Leap Forward, invention of agriculture, invention of the wheel, invention of writing, mass immigration, meta-analysis, new economy, out of africa, phenotype, Scientific racism, sparse data, supervolcano, the scientific method, transatlantic slave trade

Between 2011 and 2015, the genetic testing company 23andMe provided customers with an estimate of their proportion of Neanderthal ancestry, allowing them to make a personal connection to the research showing that non-Africans derive around 2 percent of their genomes from Neanderthals.59 The measurement made by the test was highly inaccurate, however, since the true variation in Neanderthal proportion within most populations is only a few tenths of a percent, and the test reports variation of a few percentage points.60 Several people have told me excitedly that their 23andMe Neanderthal testing result put them in the top few percent of people in the world in Neanderthal ancestry, but because of the test’s inaccuracies, the probability that people who got such a high 23andMe Neanderthal reading really do have more than the average proportion of Neanderthal ancestry is only slightly greater than 50/50. I raised this problem to members of the 23andMe team and even highlighted the problems in a 2014 scientific paper.61 Later, 23andMe changed its report to no longer provide these statements. However, the company continues to provide its customers with a ranking of the number of Neanderthal-derived mutations they carry.62 This ranking, too, does not provide strong evidence that customers have inherited more Neanderthal DNA than their population average.

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., “Genome-Wide Ancestry of 17th-Century Enslaved Africans from the Caribbean,” Proceedings of the National Academy of Sciences of the U.S.A. 112 (2015): 3669–73. 59. R. E. Green et al., “A Draft Sequence of the Neanderthal Genome,” Science 328 (2010): 710–22. 60. E. Durand, 23andMe: “White Paper 23-05: Neanderthal Ancestry Estimator” (2011), https://web.stanford.edu/​class/​gene210/​files/​readings/​23andme_Neanderthal_Ancestry.pdf; S. Sankararaman et al., “The Genomic Landscape of Neanderthal Ancestry in Present-Day Humans,” Nature 507 (2014): 354–57. 61. Sankararaman et al., “Genomic Landscape.” 62. https://customercare.23andme.com/​hc/​en-us/​articles/​212873707-Neanderthal-Report-Basics, #13514. 12 The Future of Ancient DNA 1. J. R. Arnold and W.

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Between 2011 and 2015, the genetic testing company 23andMe provided customers with an estimate of their proportion of Neanderthal ancestry, allowing them to make a personal connection to the research showing that non-Africans derive around 2 percent of their genomes from Neanderthals.59 The measurement made by the test was highly inaccurate, however, since the true variation in Neanderthal proportion within most populations is only a few tenths of a percent, and the test reports variation of a few percentage points.60 Several people have told me excitedly that their 23andMe Neanderthal testing result put them in the top few percent of people in the world in Neanderthal ancestry, but because of the test’s inaccuracies, the probability that people who got such a high 23andMe Neanderthal reading really do have more than the average proportion of Neanderthal ancestry is only slightly greater than 50/50.

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

Berkman Center Research Publication, (2010-7), 10-36. 23andMe and Airbnb have partnered: Valle, G. D. (2019, May 22). Airbnb is partnering with 23andMe to send people on “heritage” vacations. Retrieved from https://www.vox.com/2019/5/22/18635829/airbnb-23andme-heritage-vacations-partnership GlaxoSmithKline acquired: Brodwin, E. (2018, July 25). DNA-testing company 23andMe has signed a $300 million deal with a drug giant. Here’s how to delete your data if that freaks you out. Retrieved from https://www.businessinsider.com/dna-testing-delete-your-data-23andme-ancestry-2018-7 Those who share their genetic fingerprints: Resnick, B. (2018, October 15).

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While most parents fret about their children encountering inappropriate content on the internet, perhaps they should be more concerned about what happens when the internet, because of their own actions, is constantly encountering their children? A rash of unintended consequences surrounds DNA data, such as that collected by companies like 23andMe and Ancestry.com — a market that is exploding in popularity as genetic testing technology advances and curious customers want to know more about their lineage or health risks. Like all digital technologies, genetic testing services such as these have higher- and lower-level functions, including selling data they collect on their customers to third parties. For example, 23andMe and Airbnb have partnered to offer customers “heritage vacations” based on their genetic results.64 Large pharmaceutical companies could use genetic data to target users who have specific genetic markers with tailored advertisements for their drugs.

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For example, 23andMe and Airbnb have partnered to offer customers “heritage vacations” based on their genetic results.64 Large pharmaceutical companies could use genetic data to target users who have specific genetic markers with tailored advertisements for their drugs. That’s no doubt why, in 2018, the pharmaceutical giant GlaxoSmithKline acquired a $300 million stake in 23andMe.65 Another obvious potential third-party client is law enforcement agencies, which can use genetic information to locate perpetrators of crimes (however those may be defined). And while specific customers of these services may inform themselves of the risks of handing over their genetic data to these companies, and all third parties to whom they might provide it, none of that due diligence extends to those who share their genetic fingerprints.66 When you hand over your DNA data, you’re not just handing over your own genetic data, you are handing over your entire family’s too — including those of future generations yet to be born.

Exponential: How Accelerating Technology Is Leaving Us Behind and What to Do About It by Azeem Azhar

"Friedman doctrine" OR "shareholder theory", "World Economic Forum" Davos, 23andMe, 3D printing, A Declaration of the Independence of Cyberspace, Ada Lovelace, additive manufacturing, air traffic controllers' union, Airbnb, algorithmic management, algorithmic trading, Amazon Mechanical Turk, autonomous vehicles, basic income, Berlin Wall, Bernie Sanders, Big Tech, Bletchley Park, Blitzscaling, Boeing 737 MAX, book value, Boris Johnson, Bretton Woods, carbon footprint, Chris Urmson, Citizen Lab, Clayton Christensen, cloud computing, collective bargaining, computer age, computer vision, contact tracing, contact tracing app, coronavirus, COVID-19, creative destruction, crowdsourcing, cryptocurrency, cuban missile crisis, Daniel Kahneman / Amos Tversky, data science, David Graeber, David Ricardo: comparative advantage, decarbonisation, deep learning, deglobalization, deindustrialization, dematerialisation, Demis Hassabis, Diane Coyle, digital map, digital rights, disinformation, Dissolution of the Soviet Union, Donald Trump, Double Irish / Dutch Sandwich, drone strike, Elon Musk, emotional labour, energy security, Fairchild Semiconductor, fake news, Fall of the Berlin Wall, Firefox, Frederick Winslow Taylor, fulfillment center, future of work, Garrett Hardin, gender pay gap, general purpose technology, Geoffrey Hinton, gig economy, global macro, global pandemic, global supply chain, global value chain, global village, GPT-3, Hans Moravec, happiness index / gross national happiness, hiring and firing, hockey-stick growth, ImageNet competition, income inequality, independent contractor, industrial robot, intangible asset, Jane Jacobs, Jeff Bezos, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John Perry Barlow, Just-in-time delivery, Kickstarter, Kiva Systems, knowledge worker, Kodak vs Instagram, Law of Accelerating Returns, lockdown, low skilled workers, lump of labour, Lyft, manufacturing employment, Marc Benioff, Mark Zuckerberg, megacity, Mitch Kapor, Mustafa Suleyman, Network effects, new economy, NSO Group, Ocado, offshore financial centre, OpenAI, PalmPilot, Panopticon Jeremy Bentham, Peter Thiel, Planet Labs, price anchoring, RAND corporation, ransomware, Ray Kurzweil, remote working, RFC: Request For Comment, Richard Florida, ride hailing / ride sharing, Robert Bork, Ronald Coase, Ronald Reagan, Salesforce, Sam Altman, scientific management, Second Machine Age, self-driving car, Shoshana Zuboff, Silicon Valley, Social Responsibility of Business Is to Increase Its Profits, software as a service, Steve Ballmer, Steve Jobs, Stuxnet, subscription business, synthetic biology, tacit knowledge, TaskRabbit, tech worker, The Death and Life of Great American Cities, The Future of Employment, The Nature of the Firm, Thomas Malthus, TikTok, Tragedy of the Commons, Turing machine, Uber and Lyft, Uber for X, uber lyft, universal basic income, uranium enrichment, vertical integration, warehouse automation, winner-take-all economy, workplace surveillance , Yom Kippur War

I also learnt about my risk of developing diseases like Alzheimer’s and macular degeneration. Fifteen years on, and 23andMe has a huge set of genomic data. Such a data set is incredibly valuable, and may prove helpful in identifying the genetic drivers of disease. Millions of people have used 23andMe’s services and have shared their genetic information, and more than 80 per cent of them have allowed their genomic data to be used for research. But 23andMe don’t always keep this data to themselves. They can sell it – and they have. In 2018, 23andMe shared the data of consenting customers with pharma giant GlaxoSmithKline for $300 million.

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In 2018, 23andMe shared the data of consenting customers with pharma giant GlaxoSmithKline for $300 million. Once that data was shared, it was no longer under the purview of 23andMe. It could be shared again and again. And the firm might change its policies; people’s genomes might be used in ways they are not comfortable with. In the US, much healthcare data is protected by a 1996 law called HIPAA, which places strenuous requirements on firms handling healthcare data – but genetic testing of the type that 23andMe and others undertake is not covered by HIPAA or similar laws. Rather, it is covered by their own set of guidelines: a nice gesture, but not worth much. Voluntary guidelines have no enforcement mechanism.22 At the most extreme end of the spectrum, our personal data can be used to stigmatise and demographically profile us.

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Credit bureaux often hold inaccurate data, resulting in unfair credit scores. The businesses have also suffered significant data breaches, exposing personal information to the black market.21 These flaws are the other edge of data’s sword: when the information gathered about us works against us. Such risks extend well beyond web surfing and credit data. Take 23andMe. I developed a fascination with the company soon after it was founded in 2006. Named after the 23 pairs of chromosomes in a human cell, it offers low-cost gene sequencing – giving you the chance to view the source code that makes you into you. It tells you things about yourself that you know, and things you don’t.

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

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

But had the hospital known Bates’s condition ahead of time, the incident, which could have easily killed her or resulted in serious brain damage, could have been avoided.21 Thanks to services like 23andMe, many of us will be able to head off such occurrences very soon. For $200, the company takes a saliva sample from you by mail and returns a detailed analysis of your DNA, its algorithm teasing out a variety of fascinating factors, from your ancestry to your health risks and potential reactions to medications. To be sure, some doctors and health experts say that 23andMe’s tests offer no useful information and that consumers should save their money. And some states, including New York, have ordered 23andMe and similar services to get approval from the state’s health department, declaring their tests to be medical and therefore open to regulation.

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David Leonhardt, “Making Health Care Better,” New York Times Magazine, November 3, 2009. 18. Ibid. 19. Ibid. 20. “What Is Heart Failure?” National Heart, Lung, and Blood Institute, http://www.nhlbi.nih.gov/health/health-topics/topics/hf/. 21. “The Power of Knowing,” 23andMe, https://www.23andme.com/stories/6/. 22. Andrew Pollack, “DNA Sequencing Caught in Deluge of Data,” New York Times, November 30, 2011. 23. Ewen Callaway, “Ancient DNA Reveals Secrets of Human History,” Nature, no. 476 (August 9, 2011): 136–37. 24. Anna Wilde Mathews, “WellPoint’s New Hire.

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And some states, including New York, have ordered 23andMe and similar services to get approval from the state’s health department, declaring their tests to be medical and therefore open to regulation. Such regulation is “appallingly paternalistic,” says 23andMe, adding that people have a right to information contained within their own genes. Such genomic scanning is now fast and affordable, thanks in part to Nick Patterson, a Wall Street hacker who after eight years at Renaissance Technologies, the quantitative hedge fund, joined up with the Broad Institute, a joint research center of Harvard and MIT, in 2001. Working at Renaissance, which makes money off of sorting data and spotting patterns that nobody else can, made Patterson the perfect person to help the Broad Institute, which was drowning in DNA data so deep that the researchers there found it to be unnavigable.

The Science and Technology of Growing Young: An Insider's Guide to the Breakthroughs That Will Dramatically Extend Our Lifespan . . . And What You Can Do Right Now by Sergey Young

23andMe, 3D printing, Albert Einstein, artificial general intelligence, augmented reality, basic income, Big Tech, bioinformatics, Biosphere 2, brain emulation, caloric restriction, caloric restriction, Charles Lindbergh, classic study, clean water, cloud computing, cognitive bias, computer vision, coronavirus, COVID-19, CRISPR, deep learning, digital twin, diversified portfolio, Doomsday Clock, double helix, Easter island, Elon Musk, en.wikipedia.org, epigenetics, European colonialism, game design, Gavin Belson, George Floyd, global pandemic, hockey-stick growth, impulse control, Internet of things, late capitalism, Law of Accelerating Returns, life extension, lockdown, Lyft, Mark Zuckerberg, meta-analysis, microbiome, microdosing, moral hazard, mouse model, natural language processing, personalized medicine, plant based meat, precision agriculture, radical life extension, Ralph Waldo Emerson, Ray Kurzweil, Richard Feynman, ride hailing / ride sharing, Ronald Reagan, self-driving car, seminal paper, Silicon Valley, stem cell, Steve Jobs, tech billionaire, TED Talk, uber lyft, ultra-processed food, universal basic income, Virgin Galactic, Vision Fund, X Prize

(New York: Basic Books, 2019), loc. 387, Kindle. 17“World Bank and WHO: Half the world lacks access to essential health services, 100 million still pushed into extreme poverty because of health expenses,” World Health Organization, last modified December 13, 2017, https://www.who.int/news-room/detail/13-12-2017-world-bank-and-who-half-the-world-lacks-access-to-essential-health-services-100-million-still-pushed-into-extreme-poverty-because-of-health-expenses. 18Khosla and Topol, “Vinod Khosla, MS, MBA on AI and the Future of Medicine.” 19“The world’s most valuable resource is no longer oil, but data,” Economist, last modified May 5, 2017, https://www.economist.com/leaders/2017/05/06/the-worlds-most-valuable-resource-is-no-longer-oil-but-data. 20Eva Short, “Here is how much your credit card information is worth on the black market,” Siliconrepublic, last modified September 11, 2019, https://www.siliconrepublic.com/enterprise/black-market-report-armor-credit-card. 21“Hackers are stealing millions of medical records – and selling them on the dark web,” CBS News, last modified February 14, 2019, https://www.cbsnews.com/news/hackers-steal-medical-records-sell-them-on-dark-web/. 22Security Magazine, “75% of Healthcare Organizations Globally Have Experienced Cyberattacks,” BNP Media, last modified March 11, 2020, https://www.securitymagazine.com/articles/91880-of-healthcare-organizations-globally-have-experienced-cyberattacks. 23“Data Protection and Privacy Legislation Worldwide,” United Nations Conference on Trade and Development, accessed May 4, 2020, https://unctad.org/en/Pages/DTL/STI_and_ICTs/ICT4D-Legislation/eCom-Data-Protection-Laws.aspx. 24Avi Selk, “The ingenious and ‘dystopian’ DNA technique police used to hunt the ‘Golden State Killer’ suspect,” Washington Post, last modified April 28, 2018, https://www.washingtonpost.com/news/true-crime/wp/2018/04/27/golden-state-killer-dna-website-gedmatch-was-used-to-identify-joseph-deangelo-as-suspect-police-say/. 25Mary Ann Azevedo, “Apple Said To Have Acquired Another Digital Health Startup,” Crunchbase, last modified May 24, 2019, https://news.crunchbase.com/news/apple-said-to-have-acquired-another-digital-health-startup/. 26Christina Farr, “Facebook sent a doctor on a secret mission to ask hospitals to share patient data,” CNBC, last modified April 6, 2018, https://www.cnbc.com/2018/04/05/facebook-building-8-explored-data-sharing-agreement-with-hospitals.html. 27Jonathan Shieber, “Facebook unveils its first foray into personal digital healthcare tools,” Verizon Media, last modified October 29, 2019, https://techcrunch.com/2019/10/28/facebook-unveils-its-first-foray-into-personal-digital-healthcare-tools/. 28Christina Farr, “Health care is one of Apple’s most lucrative opportunities: Morgan Stanley,” CNBC, last modified April 8, 2019, https://www.cnbc.com/2019/04/08/apple-could-top-300-billion-in-sales-from-health-care-morgan-stanley.html. 29Jessica Hamzelou, “23andMe has sold the rights to develop a drug based on its users’ DNA,” New Scientist, last modified January 10, 2020, https://www.newscientist.com/article/2229828-23andme-has-sold-the-rights-to-develop-a-drug-based-on-its-users-dna/. 30Gregory Barber and Megan Molteni, “Google Is Slurping Up Health Data—and It Looks Totally Legal,” Wired, last modified November 11, 2019, https://www.wired.com/story/google-is-slurping-up-health-dataand-it-looks-totally-legal/. 31Gina Kolata, “Your Data Were ‘Anonymized’?

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It involves nothing more than a simple blood test, can be done from ten weeks into the pregnancy, and is relatively accessible at five hundred to one thousand dollars per test. GENETIC DIAGNOSTICS: A number of affordable genetic testing services on the market can identify your genetic predisposition to disease using nothing more than a swab of your saliva. 23andMe and other consumer products, for instance, offer genotyping (which examines about ~0.02 percent of DNA to find mutations that may contribute to various health risks) that can sometimes offer insight into your genetic predisposition to diseases like breast, ovarian, uterine, and colon cancer; late-onset Alzheimer’s and Parkinson’s diseases; type 2 diabetes; and celiac diseases.

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I also mean your proteome, a complete set of proteins that reflect your current health; your transcriptome, a collection of all the RNA molecules in your body; and your metabolome, containing metabolites, microbiome by-products, and food and drug remnants. Together, these comprise your “personalome”—the incredibly sophisticated and data-rich picture of your health, which is changing how medicine is practiced. Following the $2.5 billion blockbuster market reception of the direct-to-consumer (DTC) genetic testing company 23andMe, diagnostic services that focus on “omes” are exploding. Mind you, this technology still has a long way to go before it can be reliably, widely used. (I refer you to the infamous downfall of Theranos, whose vision for fast, affordable, DTC blood testing was—to put it kindly—ahead of its time.) But it will get there.

She Has Her Mother's Laugh by Carl Zimmer

23andMe, agricultural Revolution, Anthropocene, clean water, clockwatching, cloud computing, CRISPR, dark matter, data science, discovery of DNA, double helix, Drosophila, Easter island, Elon Musk, epigenetics, Fellow of the Royal Society, Flynn Effect, friendly fire, Gary Taubes, germ theory of disease, Gregor Mendel, Helicobacter pylori, Isaac Newton, James Webb Space Telescope, lolcat, longitudinal study, medical bankruptcy, meta-analysis, microbiome, moral panic, mouse model, New Journalism, out of africa, phenotype, Ralph Waldo Emerson, Recombinant DNA, Scientific racism, statistical model, stem cell, twin studies, W. E. B. Du Bois

I could not simply spit into a tube and mail it off to a company like 23andMe. In 2007, 23andMe began providing reports on DNA directly to consumers. For $999, they would identify the variants at half a million sites in a person’s genome, analyze them for clues to their ancestry, and even supply a report about how the variants influenced risks for disorders ranging from diabetes to Alzheimer’s disease. Their service was a profound leap from conventional genetic tests. They had to be approved by the FDA and ordered by doctors. Now 23andMe was delivering information straight to customers. In 2013, the FDA told 23andMe to stop selling unvalidated tests or face the consequences.

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* * * — By 2010, when Pääbo and his colleagues published the first evidence for Neanderthal interbreeding, genetic genealogy was a thriving industry. It was ready to seize such a sensational finding and make the most of it. 23andMe quickly put together a test that they claimed could tell customers just how much of their genome was Neanderthal. When I told people about my reporting about Neanderthals, some of them would eagerly let me know about their percentage. The more Neanderthal DNA they carried, the happier they sounded. Judging from comments that customers have left on 23andMe’s website, Neanderthal pride is a common thing. “I am very proud of my 2.8% Neanderthal DNA,” someone named Gayle wrote in 2011.

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Perspectives in Biology and Medicine 57:132–48. Feyrer, James, Dimitra Politi, and David N. Weil. 2013. “The Cognitive Effects of Micronutrient Deficiency.” National Bureau of Economic Research Working Paper Series, working paper 19233. http://www.nber.org/papers/w19233. “Find Your Inner Neanderthal.” 2011. 23andMe blog, December 15. https://blog.23andme.com/ancestry/find-your-inner-neanderthal/ (accessed July 25, 2017). Finger, Stanley, and Shawn E. Christ. 2004. “Pearl S. Buck and Phenylketonuria (PKU).” Journal of the History of the Neurosciences 13:44–57. Fischbach, Ruth L., and John D. Loike. 2014. “Maternal-Fetal Cell Transfer in Surrogacy: Ties That Bind.”

50 Future Ideas You Really Need to Know by Richard Watson

23andMe, 3D printing, access to a mobile phone, Albert Einstein, Alvin Toffler, artificial general intelligence, augmented reality, autonomous vehicles, BRICs, Buckminster Fuller, call centre, carbon credits, Charles Babbage, clean water, cloud computing, collaborative consumption, computer age, computer vision, crowdsourcing, dark matter, dematerialisation, Dennis Tito, digital Maoism, digital map, digital nomad, driverless car, Elon Musk, energy security, Eyjafjallajökull, failed state, Ford Model T, future of work, Future Shock, gamification, Geoffrey West, Santa Fe Institute, germ theory of disease, global pandemic, happiness index / gross national happiness, Higgs boson, high-speed rail, hive mind, hydrogen economy, Internet of things, Jaron Lanier, life extension, Mark Shuttleworth, Marshall McLuhan, megacity, natural language processing, Neil Armstrong, Network effects, new economy, ocean acidification, oil shale / tar sands, pattern recognition, peak oil, personalized medicine, phenotype, precision agriculture, private spaceflight, profit maximization, RAND corporation, Ray Kurzweil, RFID, Richard Florida, Search for Extraterrestrial Intelligence, self-driving car, semantic web, Skype, smart cities, smart meter, smart transportation, space junk, statistical model, stem cell, Stephen Hawking, Steve Jobs, Steven Pinker, Stewart Brand, strong AI, Stuxnet, supervolcano, synthetic biology, tech billionaire, telepresence, The Wisdom of Crowds, Thomas Malthus, Turing test, urban decay, Vernor Vinge, Virgin Galactic, Watson beat the top human players on Jeopardy!, web application, women in the workforce, working-age population, young professional

Retail genomics Named after the fact that everyone has 23 pairs of chromosomes, 23andMe is a private Californian company that allows ordinary individuals to find out about and understand their personal genomics. The fact that the company is backed financially by Google might seem rather odd to some people, but if Google’s aim is to organize the world’s information, they will clearly need everyone’s DNA. Products available from 23andMe include ancestry testing and healthcare screening, especially with regard to how an individual’s genes might impact on their future health and healthcare costs. The Google-backed biotech company 23andMe was offering individuals gene sequencing for $999 in 2011.

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At the time of writing (June 2012) the cost had fallen to $299. A decade earlier this would have cost close to $10,000, while James Watson, the codiscoverer of DNA and one of the people behind the Human Genome Project, paid around $2 billion to work out how to make sequencing work. Interestingly, 23andMe plugs into the idea of crowd-sourcing data, too, by sending regular questionnaires to thousands of users asking about them about, for example, specific food allergies. When the responses to such surveys are matched against known genetic information they can potentially find the causes of certain traits in a matter of months rather than years and for minimal cost.

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Expect the controversy to develop rapidly alongside our knowledge of the workings of the human brain. the condensed idea Genetic prophesy timeline 1997 Release of the movie Gattaca about genetic enhancement 2008 Knome offers genome sequencing to individuals for $350,000 2009 Knome drops its price to $99,500 2012 23andMe offers gene sequencing for $299 2018 Cost falls to $49 via Walmart 2020 Hospitals and insurers offer free genome profiling 2030 Google dating based upon ideal DNA profiles 2050 DNA database creates human underclass 22 Regenerative medicine Is it possible to prevent or reverse the aging process, perhaps by fiddling with tired tissues and cells, or even growing new organs inside a laboratory?

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

23andMe, Airbnb, airport security, AltaVista, Anne Wojcicki, AOL-Time Warner, augmented reality, behavioural economics, Benjamin Mako Hill, Black Swan, Boris Johnson, Brewster Kahle, Brian Krebs, call centre, Cass Sunstein, Chelsea Manning, citizen journalism, Citizen Lab, cloud computing, congestion charging, data science, digital rights, disintermediation, drone strike, Eben Moglen, Edward Snowden, end-to-end encryption, Evgeny Morozov, experimental subject, failed state, fault tolerance, Ferguson, Missouri, Filter Bubble, Firefox, friendly fire, Google Chrome, Google Glasses, heat death of the universe, hindsight bias, informal economy, information security, Internet Archive, Internet of things, Jacob Appelbaum, James Bridle, Jaron Lanier, John Gilmore, John Markoff, Julian Assange, Kevin Kelly, Laura Poitras, license plate recognition, lifelogging, linked data, Lyft, Mark Zuckerberg, moral panic, Nash equilibrium, Nate Silver, national security letter, Network effects, Occupy movement, operational security, Panopticon Jeremy Bentham, payday loans, pre–internet, price discrimination, profit motive, race to the bottom, RAND corporation, real-name policy, recommendation engine, RFID, Ross Ulbricht, satellite internet, self-driving car, Shoshana Zuboff, Silicon Valley, Skype, smart cities, smart grid, Snapchat, social graph, software as a service, South China Sea, sparse data, stealth mode startup, Steven Levy, Stuxnet, TaskRabbit, technological determinism, telemarketer, Tim Cook: Apple, transaction costs, Uber and Lyft, uber lyft, undersea cable, unit 8200, urban planning, Wayback Machine, WikiLeaks, workplace surveillance , Yochai Benkler, yottabyte, zero day

Watson (10 Oct 2013), “The latest smartphones could turn us all into activity trackers,” Wired, http://www.wired.com/2013/10/the-trojan-horse-of-the-latest-iphone-with-the-m7-coprocessor-we-all-become-qs-activity-trackers. Companies like 23andMe: Thomas Goetz (17 Nov 2007), “23AndMe will decode your DNA for $1,000. Welcome to the age of genomics,” Wired, http://www.wired.com/medtech/genetics/magazine/15-12/ff_genomics. Elizabeth Murphy (14 Oct 2013), “Inside 23andMe founder Anne Wojcicki’s $99 DNA revolution,” Fast Company, http://www.fastcompany.com/3018598/for-99-this-ceo-can-tell-you-what-might-kill-you-inside-23andme-founder-anne-wojcickis-dna-r. personalized marketing: Charles Seife (27 Nov 2013), “23andMe is terrifying, but not for the reasons the FDA thinks,” Scientific American, http://www.scientificamerican.com/article/23andme-is-terrifying-but-not-for-reasons-fda.

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personalized marketing: Charles Seife (27 Nov 2013), “23andMe is terrifying, but not for the reasons the FDA thinks,” Scientific American, http://www.scientificamerican.com/article/23andme-is-terrifying-but-not-for-reasons-fda. insurance companies may someday buy: Rebecca Greenfield (25 Nov 2013), “Why 23andMe terrifies health insurance companies,” Fast Company, http://www.fastcompany.com/3022224/innovation-agents/why-23andme-terrifies-health-insurance-companies. lifelogging apps: Leo Kelion (6 Jan 2014), “CES 2014: Sony shows off life logging app and kit,” BBC News, http://www.bbc.com/news/technology-25633647. it will include a video record: Alec Wilkinson (28 May 2007), “Remember this? A project to record everything we do in life,” New Yorker, http://www.newyorker.com/reporting/2007/05/28/070528fa_fact_wilkinson.

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There are already—or will be soon—devices that continually measure our vital signs, our moods, and our brain activity. It’s not just specialized devices; current smartphones have some pretty sensitive motion sensors. As the price of DNA sequencing continues to drop, more of us are signing up to generate and analyze our own genetic data. Companies like 23andMe hope to use genomic data from their customers to find genes associated with disease, leading to new and highly profitable cures. They’re also talking about personalized marketing, and insurance companies may someday buy their data to make business decisions. Perhaps the extreme in the data-generating-self trend is lifelogging: continuously capturing personal data.

Dirty Genes: A Breakthrough Program to Treat the Root Cause of Illness and Optimize Your Health by Ben Lynch Nd.

23andMe, clean water, double helix, epigenetics, Helicobacter pylori, Indoor air pollution, microbiome, post-work, selective serotonin reuptake inhibitor (SSRI)

As of April 2017, this company tests fifty times more of your DNA than 23andMe. They also give you access to your raw data. Overall, the value is fantastic. However, they don’t test the regulatory regions of your DNA: the genes that control how other genes are turned on or off. Instead, they test your entire exome, which lies within your regulatory regions. This is important to realize going in, because some genes—PEMT, for example—have SNPs you’d want to know about in the regulatory regions. ■23andMe (https://www.23andme.com). This company provides two testing options: with a health report and without.

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This Clean Genes Protocol has helped thousands of people worldwide. I want it to work for you, too. You’ll get the best results if you follow the protocol, no matter what genetic testing you may have had.* * * * Genetic Testing: The Pros and Cons Many of my clients have sent away for a genetic test from such companies as 23andMe and Genos Research. Sometimes the information is helpful, but often the results can be confusing: “Take large quantities of vitamin X to support gene A; avoid vitamin X completely to support gene B; and consume moderate quantities of vitamin X to support gene C.” How do you follow a recommendation like that?

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Now your doctor has said that you have gallstones and need to have your gallbladder taken out. No! There must be a way to save it. What’s Your Genetic Profile? If you want to know your own genetic profile, there are a few ways to go about it. The most expensive route is to get yourself tested by a company like 23andMe or Genos Research. At that point, you’ll know exactly where all your SNPs are—but you won’t necessarily know what those results mean. Another route is to invest four weeks in this book’s Clean Genes Protocol. Most people I know, including health professionals, get genetic testing results back and focus only on the genes.

An Optimist's Tour of the Future by Mark Stevenson

23andMe, Albert Einstein, Alvin Toffler, Andy Kessler, Apollo 11, augmented reality, bank run, Boston Dynamics, carbon credits, carbon footprint, carbon-based life, clean water, computer age, decarbonisation, double helix, Douglas Hofstadter, Dr. Strangelove, Elon Musk, flex fuel, Ford Model T, Future Shock, Great Leap Forward, Gregor Mendel, Gödel, Escher, Bach, Hans Moravec, Hans Rosling, Intergovernmental Panel on Climate Change (IPCC), Internet of things, invention of agriculture, Isaac Newton, Jeff Bezos, Kevin Kelly, Law of Accelerating Returns, Leonard Kleinrock, life extension, Louis Pasteur, low earth orbit, mutually assured destruction, Naomi Klein, Nick Bostrom, off grid, packet switching, peak oil, pre–internet, private spaceflight, radical life extension, Ray Kurzweil, Richard Feynman, Rodney Brooks, Scaled Composites, self-driving car, Silicon Valley, smart cities, social intelligence, SpaceShipOne, stem cell, Stephen Hawking, Steven Pinker, Stewart Brand, strong AI, synthetic biology, TED Talk, the scientific method, Virgin Galactic, Wall-E, X Prize

Because DNA’s component parts love to snap together in predetermined ways, copies of my own genetic code would have latched on to these probes with varying degrees of connectedness, letting the company know which markers I possess and allowing them to suggest what these might mean for my health. Because our understanding of the interplay of our genes and environment is still evolving, 23andMe attaches confidence ratings to each finding (the higher the rating, the more secure they feel in their analysis). Because I have one genetic marker that a 2007 German study suggests is linked to Tourette’s syndrome, 23andMe let me know I might have an elevated chance of the condition, although they give this a confidence rating of one (out of four). In the two-star category there are potential elevated risks of ‘essential tremor,’ ‘Hashimoto’s thyroiditis’ and ‘Sjögren’s syndrome.

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‘Generally the pace of medical research is glacial compared to what I’m used to in the Internet,’ Brin says. ‘We could be looking lots of places and collecting lots of information. And if we see a pattern, that could lead somewhere.’ So he recruited a group of 10,000 Parkinson’s sufferers, had the company 23andMe (which is largely funded by Google) run their DNA, and set out to find links. It’s one of the many examples Kurzweil cites of information technology ‘invading one field after another.’ Sitting in front of Ray Kurzweil, I’m getting just what I came for. I’m becoming disenthralled from my inclination to think linear.

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Just behind me is the spot where in 1795 the British Admiralty erected its optical telegraph station to pass signals down the line between coast and capital. Communications have come a long way since 1795. On my lap is a computer, battered and grubby from long hours on the road. Using my mobile phone as a wireless modem I am surfing the Internet. In particular I am looking at my ‘genetic profile’ having just logged on to the website of 23andMe, the Google-funded personal genomics company that Sergey Brin has been using for his Parkinson’s research. Several weeks ago, the company sent me a plastic tube, which I filled with saliva and returned to its laboratories. From this the company extracted cheek cells, out of which they stripped my DNA to be duplicated many times over.

Money: Vintage Minis by Yuval Noah Harari

23andMe, agricultural Revolution, algorithmic trading, AlphaGo, Anne Wojcicki, autonomous vehicles, British Empire, call centre, credit crunch, DeepMind, European colonialism, Flash crash, Ford Model T, greed is good, job automation, joint-stock company, joint-stock limited liability company, lifelogging, low interest rates, Nick Bostrom, pattern recognition, peak-end rule, Ponzi scheme, self-driving car, Suez canal 1869, telemarketer, The future is already here, The Future of Employment, The Wealth of Nations by Adam Smith, trade route, transatlantic slave trade, Watson beat the top human players on Jeopardy!, zero-sum game

The market for DNA testing is currently growing in leaps and bounds. One of its leaders is 23andMe, a private company founded by Anne Wojcicki, former wife of Google co-founder Sergey Brin. The name ‘23andMe’ refers to the twenty-three pairs of chromosomes that encode the human genome, the message being that my chromosomes have a very special relationship with me. Whoever can understand what the chromosomes are saying can tell you things about yourself that you never even suspected. If you want to know what, pay 23andMe a mere $99, and they will send you a small package with a tube. You spit into the tube, seal it and mail it to Mountain View, California.

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

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

These companies promise a better world through applied genetics. The most famous—familiar to anyone who has encountered its multimillion-dollar advertising campaign—is Google’s 23andMe, which sells mail-order genetic sequencing services to the general public. The marketing ingeniously presents it as not only a potential health benefit, but as the fun indulgence of an innocent curiosity, like some super-sciencey high-tech yuppie version of heredity research websites like Ancestry.com. Medical ethicists have knocked 23andMe for pushing unnecessary screening to people without heritable risk, and for hoarding customer data that could later be sold to insurers or advertisers.

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The company claims its mission is to provide “reproductive autonomy” and argues that its products will help the poor. Counsyl boasts that its low-cost genetic tests can sometimes be covered by health insurance, but it never mentions the likelihood that such tests could become a prerequisite for coverage. Like 23andMe, some ethicists have slammed Counsyl for exploiting the weakly regulated market in genetic data in ways that drove humanity “down the slippery slope toward attempts to control IQ, weight, height and other factors,” as the science journalist and biotech consultant Steve Dickman put it. The way Silicon Valley biotech companies marketed themselves did not inspire confidence.

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Sjöblad’s cyborg evangelism Bryan Menegus, “Company Offers Free, Totally Not Creepy Microchip Implants to Employees,” July 24, 2017, gizmodo.com; James Brooks, “Cyborgs at Work: Employees Getting Implanted with Microchips,” April 23, 2017, apnews.com. “gamete donor selection based on genetic calculations” Anne Wojcicki et al., U.S. Patent 8543339 B2, December 5, 2008; Karen Kaplan, “23andMe’s Designer Baby Patent Is ‘a Serious Mistake,’ Critics Charge,” October 3, 2013, latimes.com. endorsed the Singularity sect Lev Grossman, “2045: The Year Man Becomes Immortal,” February 10, 2011, time.com. an online forum of futurists who called themselves extropians. Max More For more on cryonics and the extropians, see my report, “Everybody Freeze!

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

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

The cost to sequence an individual’s genome approached a thousand dollars in 2012, moving it closer to a mass-market technique that can be performed at scale. As a result, a new industry of individual gene sequencing is cropping up. Since 2007 the Silicon Valley startup 23andMe has been analyzing people’s DNA for only a couple of hundred dollars. Its technique can reveal traits in people’s genetic codes that may make them more susceptible to certain diseases like breast cancer or heart problems. And by aggregating its customers’ DNA and health information, 23andMe hopes to learn new things that couldn’t be spotted otherwise. But there’s a hitch. The company sequences just a small portion of a person’s genetic code: places that are known to be markers indicating particular genetic weaknesses.

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The company sequences just a small portion of a person’s genetic code: places that are known to be markers indicating particular genetic weaknesses. Meanwhile, billions of base pairs of DNA remain unsequenced. Thus 23andMe can only answer questions about the markers it considers. Whenever a new marker is discovered, a person’s DNA (or more precisely, the relevant part of it) has to be sequenced again. Working with a subset, rather than the whole, entails a tradeoff: the company can find what it is looking for faster and more cheaply, but it can’t answer questions that it didn’t consider in advance. Apple’s legendary chief executive Steve Jobs took a totally different approach in his fight against cancer.

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Apple’s legendary chief executive Steve Jobs took a totally different approach in his fight against cancer. He became one of the first people in the world to have his entire DNA sequenced as well as that of his tumor. To do this, he paid a six-figure sum—many hundreds of times more than the price 23andMe charges. In return, he received not a sample, a mere set of markers, but a data file containing the entire genetic codes. In choosing medication for an average cancer patient, doctors have to hope that the patient’s DNA is sufficiently similar to that of patients who participated in the drug’s trials to work. However, Steve Jobs’s team of doctors could select therapies by how well they would work given his specific genetic makeup.

Soonish: Ten Emerging Technologies That'll Improve And/or Ruin Everything by Kelly Weinersmith, Zach Weinersmith

2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 23andMe, 3D printing, Airbnb, Alvin Roth, Apollo 11, augmented reality, autonomous vehicles, connected car, CRISPR, data science, disinformation, double helix, Elon Musk, en.wikipedia.org, Google Glasses, hydraulic fracturing, industrial robot, information asymmetry, ITER tokamak, Kickstarter, low earth orbit, market design, megaproject, megastructure, microbiome, moral hazard, multiplanetary species, orbital mechanics / astrodynamics, personalized medicine, placebo effect, printed gun, Project Plowshare, QR code, Schrödinger's Cat, self-driving car, Skype, space junk, stem cell, synthetic biology, Tunguska event, Virgin Galactic

Moan, Charles E., and Heath, Robert G. “Septal stimulation for the Initiation of Heterosexual Behavior in a Homosexual Male.” Journal of Behavior Therapy and Experimental Psychiatry 3, no. 1 (1972):23–30. Mohan, Pavithra. “App Used 23andMe’s DNA Database to Block People From Sites Based on Race and Gender.” Fast Company, July 23, 2015. fastcompany.com/3048980/fast-feed/app-used-23andmes-dna-database-to-block-people-from-sites-based-on-race-and-gender. Mohiuddin, M. M., Singh, A. K., Corcoran, P. C., Hoyt, R. F., Thomas III, M. L., Ayares, D., and Horvath, K. A. “Genetically Engineered Pigs and Target-Specific Immunomodulation Provide Significant Graft Survival and Hope for Clinical Cardiac Xenotransplantation.”

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For instance, if you have a genetic predisposition for aggression, are there jobs you should not be allowed to have? And do the people around you have a right to know? The U.S. government has not made all kinds of genetic discrimination illegal. As an example, take an app called Genetic Access Control, which was made available on GitHub. The app accessed genomic data on 23andMe (a private company through which you get your genome sequenced) and used those data to restrict users’ access to Web sites. The app’s developer suggests relatively innocuous uses for the app, including creating “safe spaces,” like Web sites that can only be accessed by females. But it’s easy to imagine how an app like this could be used for more sinister purposes.

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Imagine a site that only people with a certain skin color can visit, or a site that only individuals lacking genetic defects could visit. Furthermore, even the more benign uses will create problems, because identity is both genetic and cultural. Some people with a traditionally female body type carry XY chromosomes, and a group that genetically barred nonfemales would have to decide how to handle that. 23andMe quickly blocked this app’s access to their data, but we can probably expect problems like this to pop up again in the future. And it’s not just your personal genetic information. You get half of your genome from your mom and half from your dad.* So if you make your genome public, you’re sharing half of each of your parent’s genomes.

The Messy Middle: Finding Your Way Through the Hardest and Most Crucial Part of Any Bold Venture by Scott Belsky

23andMe, 3D printing, Airbnb, Albert Einstein, Anne Wojcicki, augmented reality, autonomous vehicles, behavioural economics, Ben Horowitz, bitcoin, blockchain, Chuck Templeton: OpenTable:, commoditize, correlation does not imply causation, cryptocurrency, data science, delayed gratification, DevOps, Donald Trump, Elon Musk, endowment effect, fake it until you make it, hiring and firing, Inbox Zero, iterative process, Jeff Bezos, knowledge worker, Lean Startup, Lyft, Mark Zuckerberg, Marshall McLuhan, minimum viable product, move fast and break things, NetJets, Network effects, new economy, old-boy network, Paradox of Choice, pattern recognition, Paul Graham, private spaceflight, reality distortion field, ride hailing / ride sharing, Salesforce, Sheryl Sandberg, Silicon Valley, skeuomorphism, slashdot, Snapchat, Steve Jobs, subscription business, sugar pill, systems thinking, TaskRabbit, TED Talk, the medium is the message, Tony Fadell, Travis Kalanick, Uber for X, uber lyft, WeWork, Y Combinator, young professional

That’s exactly what happened to Anne Wojcicki, CEO and cofounder of genetic testing company 23andMe. Founded in 2006, 23andMe allowed customers to spit in a small tube and, within a few weeks, get access to a wealth of genetic information about their ancestors, predisposition to health issues, and other insights based on their genes. The company thrived in its early years, attracting excited customers and some of Silicon Valley’s greatest investors. But then, in 2013, the U.S. Food and Drug Administration (FDA) abruptly ordered 23andMe to discontinue marketing its personal genome service, based on concerns about the potential consequences of customers receiving inaccurate medical results.

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Food and Drug Administration (FDA) abruptly ordered 23andMe to discontinue marketing its personal genome service, based on concerns about the potential consequences of customers receiving inaccurate medical results. For two years, the company conducted the necessary research and addressed the FDA’s concerns, until October of 2015, when 23andMe announced that it would be offering a revised health component with FDA approval. In retrospect, this major blow to the business and the team’s morale may be nothing more than a blip in the company’s early history. But how do you manage such a setback when it happens? As Anne recalls, the team was so bought into the mission that they were largely undeterred. “The more passionate you are about the cause, the less hard it is,” she explains.

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But after the initial shock of someone leaving us rather than being dismissed, I realized that our team’s immune system was working as it should. As you lose people who aren’t a good match your team becomes stronger. Be great at retaining your A players, and less so with your B players. “You have to constantly be reevaluating the people you have,” says Anne Wojcicki from 23andMe. “Figuring out talent is hard. You never want to set someone up to fail. Doing so only hurts them and the company. One of the hardest parts of leadership is not getting attached to people. Even the people you enjoy the most may face a point where they become too specialized for their role or not specialized enough.

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

In fact, there are already players milling around the starting gate, many of them true heavy hitters from Silicon Valley. The best-known “consumer-facing” genetics company is probably 23andMe, founded by Anne Wojcicki. Anne’s father, Stanley, was the chair of Stanford’s physics department in the late 1990s; he had a couple of students, Sergey Brin and Larry Page, who would go on to start a thing called Google. In fact, they started it in Anne’s sister Susan’s garage. (Anne would later marry and divorce Brin; Susan is now the CEO of YouTube, owned of course by Google.) The company 23andMe is best known for its saliva test that unveils your genetics, though one of its patents envisions using this knowledge to help people, in the words of UC Davis’s Paul Knoepfler, “select a potential mate from a group of possible mates.”

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The party was a kickoff event for the National Academy of Medicine’s Healthy Longevity Grand Challenge, which will award millions of dollars for breakthroughs in the field. There were Hollywood stars in attendance—Goldie Hawn demanded that a Nobel Prize geneticist offer an opinion on glutathione, a powerful antioxidant that features in many health regimens—but the real celebrity was Google cofounder Sergey Brin; you’ll recall that his ex runs 23andMe, the pioneering genetics firm. At this gathering, his current girlfriend, Nicole Shanahan, said Brin had phoned her recently with the sad news that he was going to die—someday. Or maybe not, given that Google was investing huge sums in life-extension technologies. In 2009 it hired Bill Maris to run its venture capital fund, and he quickly began devoting most of its vast resources to life sciences start-ups.

…

Indeed, some of the AI enthusiasts imagine that’s precisely what will happen, arguing that we should be exploring “genetic and/or surgical modifications”7 to allow for space travel or, more likely, simply sending robots. The Russian tech pioneer Yuri Milner (whose parents named him for Yuri Gagarin, first man in space) is a Silicon Valley mainstay—among other things, he’s an investor in the gene-testing company 23andMe (not to mention a partner in Jared Kushner’s real estate ventures). In 2017 he announced plans to spend $100 million to send a robot weighing less than a sheet of paper to Alpha Centauri with a giant space sail and a hundred-billion-watt laser. If it works, it will take only twenty years to get the featherweight probe there.

Singularity Rising: Surviving and Thriving in a Smarter, Richer, and More Dangerous World by James D. Miller

23andMe, affirmative action, Albert Einstein, artificial general intelligence, Asperger Syndrome, barriers to entry, brain emulation, cloud computing, cognitive bias, correlation does not imply causation, crowdsourcing, Daniel Kahneman / Amos Tversky, David Brooks, David Ricardo: comparative advantage, Deng Xiaoping, en.wikipedia.org, feminist movement, Flynn Effect, friendly AI, hive mind, impulse control, indoor plumbing, invention of agriculture, Isaac Newton, John Gilmore, John von Neumann, knowledge worker, Larry Ellison, Long Term Capital Management, low interest rates, low skilled workers, Netflix Prize, neurotypical, Nick Bostrom, Norman Macrae, pattern recognition, Peter Thiel, phenotype, placebo effect, prisoner's dilemma, profit maximization, Ray Kurzweil, recommendation engine, reversible computing, Richard Feynman, Rodney Brooks, Silicon Valley, Singularitarianism, Skype, statistical model, Stephen Hawking, Steve Jobs, sugar pill, supervolcano, tech billionaire, technological singularity, The Coming Technological Singularity, the scientific method, Thomas Malthus, transaction costs, Turing test, twin studies, Vernor Vinge, Von Neumann architecture

Brin uses the testing company 23andMe, named after the 23 pairs of chromosomes in the human genome and cofounded by Brin’s wife, to find the genetic roots of Parkinson’s. 23andMe gives its customers, who include this author, an informative but incomplete genetic profile listing their relative risks of getting different types of disease. I have learned, for example, that, compared to the average adult male of my ethnic group, my genes decrease the odds I will get Alzheimer’s but raise the likelihood of my someday contracting coronary heart disease. Brin subsidizes the purchase of 23andMe services for Parkinson’s patients in the hope of convincing many of them to sign up.313 He also requests that the company’s customers fill out a survey asking if they or any members of their family have Parkinson’s or Parkinson’s symptoms, such as balance problems.

…

Hanson (November 24, 2008). 305. Hanson (May 27, 2011). 306. Lat (2007). 307. Greely (2008b). 308. British Medical Association (2007). 309. Kurzweil (2005). 310. Clark (2007). 311. Boudreaux (2008). 312. Goetz (2010). 313. http://www.parkinson.org/Parkinson-s-Disease/Treatment/Experimental-Therapy---Clinical-Trials/23andMe 314. This estimate doesn’t take into account cryonics. 315. http://www.fightaging.org/archives/2007/08/robert-bradbury-on-longevity-research.php 316. Median expenditures. http://nces.ed.gov/edfin/graph_topic.asp?INDEX=1. Data for 2007-2008. The exact median was $9,786. 317. Coulson (2008). 318.

…

See also nuclear war Thiel, Peter, x, 35, 170, 186, 214 torsion dystonia, 97–98 toxic garbage dumps, 124 trade with extraterrestrials, 122 Transcend: Nine Steps to Living Well Forever (Kurzweil), 179 transistors, 4 trial-and-error methods, 30 Trident submarine, 23 True Names. . . and Other Dangers (Vinge), 36 trust, 70 Turing test, 177 23andMe (testing company), 168–69 2001: A Space Odyssey (movie), 210 U Ulam, Stanislaw, xv ultra-AI. See also artificial intelligence (AI) atoms in our solar system, could completely rearrange the distribution of, 187 code, made up of extremely complex, 30 code, might change its code from friendly to non-friendly, 31 in computer simulation run by a more powerful AI, 45–46 “could never guarantee with “probability one” that the cup would stay on the table,” 28 free energy supply, will obtain, 27 friendly, 14, 33, 46, 208 human destruction because of hyper-optimization, 28 with human-like objectives, 29 humans don’t get a second chance once it is created, 30 indifference towards humanity and would kill us, 27 indifferent to mankind and creation of conditions directly in conflict with our continued existence, 28 intelligence explosion and, 31, 35, 121, 187 is not designed for friendliness and could extinguish humanity, 30, 36 lack patience to postpone what might turn out to be utopia, 46 manipulation through humans to win its freedom, 32 martial prowess, 24 military technologies, will discover, 24 morality, sharing our, 29 as more militarily useful than atomic weapons, 47 power used to stop all AI rivals from coming into existence, 24 pre-Singularity investments, might obliterate the value of, 187 progress toward its goals increased by having additional free energy, 27 rampaging, 23 risks of destroying the world, 49 unfriendly (Devil), 30, 35, 46, 202, 208 unlikely events, will plan against, 28 will command people with hypnosis, love, or subliminal messages, 33 ultra-intelligence, 40, 44, 47 unfriendly.

A Brief History of Everyone Who Ever Lived by Adam Rutherford

23andMe, agricultural Revolution, Albert Einstein, Alfred Russel Wallace, autism spectrum disorder, bioinformatics, British Empire, classic study, colonial rule, dark matter, delayed gratification, demographic transition, double helix, Drosophila, epigenetics, Eyjafjallajökull, Google Earth, Gregor Mendel, Higgs boson, Isaac Newton, Kickstarter, longitudinal study, meta-analysis, out of africa, phenotype, sceptred isle, theory of mind, Thomas Malthus, twin studies

We carry the traces of our ancestors in our cells, and nowadays, for the price of a second-hand copy of Burke’s Peerage, you can pay to have your past supposedly unscrambled. Plenty of companies have emerged who provide this service, and I have had my genome analysed by two of them, BritainsDNA (sic) and 23andMe. The kits are pretty similar: they come in a paperback-sized, high-quality parcel, and inside is a plastic test tube with a lid containing a sealed fluid. You are asked to fast for an hour beforehand, which allows your mouth to be mostly free of the DNA of the food you put in it, and then you are asked to conjure up quite a volume of saliva.

…

The genetic predictions are based on the frequency of these diseases in a whole population, and the very particular genetic sequence that occurs in those patients with those diseases. So, for example, the fact that my sequence came back without a SNP associated with Parkinson’s disease does not mean I will not get Parkinson’s disease. It means that my chance of getting Parkinson’s disease with this particular gene variation is average. Conversely, according to 23andMe, I have a genotype that is of higher risk than most people for developing Alzheimer’s disease. That does not mean that I will get Alzheimer’s disease, it means that the chance I will is slightly higher than most people. Similarly, if you don’t have that genotype, you are not immune to Alzheimer’s.

…

That type of Y chromosome is also present today from Svalbard to Gibraltar to Vladivostok. The Y is a tiny proportion of the total DNA I possess, and in fact less than the amount of DNA that I and most Europeans have inherited from Neanderthals, at least according to the rival DNA testing company 23andMe. To label my ‘ancestral type’ as this Germanic warrior with all his gliding across the frozen Rhine in unfashionable trousers is absurd. By simple percentages in my genome, I am more Neanderthal than this bearded character. Another tiny bit is from my mother’s lineage, the mitochondrial genome, which was not on the database of BritainsDNA at the time of my test, as these types of company generally add data as they add customers. 23 and Me report that it is most common in India – again, not a tremendous surprise given that my mother is Indian.

On the Future: Prospects for Humanity by Martin J. Rees

23andMe, 3D printing, air freight, Alfred Russel Wallace, AlphaGo, Anthropocene, Asilomar, autonomous vehicles, Benoit Mandelbrot, biodiversity loss, blockchain, Boston Dynamics, carbon tax, circular economy, CRISPR, cryptocurrency, cuban missile crisis, dark matter, decarbonisation, DeepMind, Demis Hassabis, demographic transition, Dennis Tito, distributed ledger, double helix, driverless car, effective altruism, Elon Musk, en.wikipedia.org, Geoffrey Hinton, global village, Great Leap Forward, Higgs boson, Hyperloop, Intergovernmental Panel on Climate Change (IPCC), Internet of things, James Webb Space Telescope, Jeff Bezos, job automation, Johannes Kepler, John Conway, Large Hadron Collider, life extension, mandelbrot fractal, mass immigration, megacity, Neil Armstrong, Nick Bostrom, nuclear winter, ocean acidification, off-the-grid, pattern recognition, precautionary principle, quantitative hedge fund, Ray Kurzweil, Recombinant DNA, Rodney Brooks, Search for Extraterrestrial Intelligence, sharing economy, Silicon Valley, smart grid, speech recognition, Stanford marshmallow experiment, Stanislav Petrov, stem cell, Stephen Hawking, Steven Pinker, Stuxnet, supervolcano, technological singularity, the scientific method, Tunguska event, uranium enrichment, Walter Mischel, William MacAskill, Yogi Berra

Ambrosia, a 2016 start-up, offers Silicon Valley executives a transfusion of ‘young blood’. Another recent craze was metformin, a drug intended to treat diabetes, but which is claimed to stave off dementia and cancer; others extol the benefits of placental cells. Craig Venter has a company called Human Longevity, which received $300 million in start-up funds. This goes beyond 23andMe (the firm that analyses our genome well enough to reveal interesting results about our vulnerability to some diseases, and about our ancestry). Venter aims to analyse the genomes of the thousands of species of ‘bugs’ in our gut. It is believed (very plausibly) that this internal ‘ecosystem’ is crucial to our health.

…

See also agriculture fossil fuels: catastrophic warming and, 41–42, 57–58; as cause of rising CO2 levels, 38, 40; cheaper than solar energy, 49; climate sensitivity factor and, 41; direct extraction of CO2 from atmosphere and, 59; origin of, 123; plan B for dealing with, 58 fractals, 168, 174, 193 Fukushima Daiichi disaster, 53, 55–56, 57 future generations, 42–43, 44–45, 226, 227; possibility of human extinction and, 117–18 Gagarin, Yuri, 138 Gaia hypothesis, 216 Galapagos Islands, invasive species on, 74 galaxies: computer simulations of, 190; finite observable volume of, 181; human realisation that there are billions of, 184; Milky Way, 124, 125, 135, 178–79; separating by mysterious force, 179 Game of Life, 167–68, 170, 174 Gandhi, Indira, 22 Gandhi, Mahatma, 26 gas power, 51 Gates, Bill, 48, 224 gene drive, 74 gene editing, 66–68, 73–74, 108 genetically modified (GM) animals, 66 genetically modified (GM) crops, 23, 24–25, 66 genetically modified pathogens, 73, 78, 116 genetic modification of humans: designer babies and, 68–69; unprecedented future kind of, 7; of voyagers from Earth, 151. See also gene editing; germ line alterations genomes: computer analysis of, 192; of gut microbes, 80; plummeting cost of sequencing, 64; sequenced by 23andMe, 80; synthesised, 64–65 geoengineering, 58–59, 60, 225 geothermal power, 50 germ line alterations, 74, 116 Gillon, Michaël, 132 Glenn, John, 138 global warming, 37–42; catastrophic, 40, 42, 57–58; goal of less than 1.5 degrees, 41. See also carbon dioxide in atmosphere; climate change Go, 86–87; Conway’s Game of Life and, 167 God, 194–200 golden rice, 24 Goldilocks planet, 128 Google, 86, 88, 106, 219 googol, 183 googolplex, 183 GPS satellites, 166 gravitational wave detector, 171 Gray, Asa, 195 greenhouse effect, 38, 58; of Venus, 135.

…

See also solar system Sundback, Gideon, 202 superconductors, 190–91 sustainability, Vatican conference on, 34 sustainable development, 26–27, 28 sustainable intensification of agriculture, 23, 24 technology: improvement in most people’s lives due to, 6, 60, 215; need for appropriate deployment of, 4, 26, 60; optimism about, 5, 225–26; as practical application of science, 202; preserving basic methods for the apocalypse, 216–17; for scientific experiments, 206–7; timescales for advance of, 152; unintended destructive consequences of, 215 telescopes: on far side of Moon, 144; optical Earth-based, 134–35, 137; radio telescopes, 134, 144, 157, 207; space telescopes, 137, 142, 143 Teller, Edward, 110 telomeres, 79 terrorism: biological techniques and, 73, 75, 77–78; in interconnected world, 215; new technology and, 100; nuclear weapons and, 20 Thomas, Chris, 74 thorium-based reactor, 54 3D printing: making consumer items cheaper, 31; of replacement organs, 72 tidal energy, 50–51 timescales: of planning for global challenges, 3–4, 59–60, 217. See also short-termism tipping points, 4, 32, 41, 42 Titan, 128, 136 Tito, Dennis, 147 translation by computer, 85, 89, 104 Trump regime, and climate change, 37–38 Tunguska event of 1908, 15 23andMe, 80 universal income, 96 universe: Dyson on numerical bounds for, 179–80; fine-tuned for life, 186, 197–98. See also big bang; multiverse unknown unknowns, 189 urbanisation, 1, 22. See also megacities of developing world vaccines, 65, 72–73 vacuum, 112, 180, 187 Venter, Craig, 64, 80 Venus, 127–28 video surveillance (CCTV), 78 viruses, 64, 72–73, 74, 78, 83 Vital Signs project, 40 vitamin A deficiency, 24 volcanoes, 16, 216 Voyager 1, 120, 121 Wallace, Alfred Russel, 34–35, 126 warfare, and new technology, 100–102 water resources: global warming and, 41; international planning for, 219; used in food production, 24 wave power, 50 weather: extreme events in, 41; predictions of, 171, 190; regional disruptions in, 41 Weinberg, Steven, 175–76, 188 Welby, Justin, 199 Wells, H.

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

‘Instead, they find ways to support their community members and keep them as part of the group.’8 In some cases, however, repression mechanisms yield a reinforcement of the beliefs, or worse, an escalation to even more absurd conspiracy theories that allow them to deny all validity of their test results.9 According to Mr White, genetic tests are purposefully distorted by the so-called ‘ZOG’, ‘the Zionist Occupied Government’, as part of their plot to wipe out the white race. ‘To be honest, with the recent article about 23andMe being manipulated to show more Ashkenazi and Sub-Saharan African in customer reports, it’s difficult to trust anything,’ he writes. There is no reliable evidence to suggest that genetic-test data providers interfere with the test results they provide. But the white supremacist belief that every single aspect of their lives is ruled by Jews, the ‘global elites’ or ‘cultural Marxists’ sits so deep that it is hard to find in their minds anything that is not rigged. The genetic test providers 23andMe and Ancestry are not exempt from their universal distrust.

…

Instead, Jason appears in the recruitment hub of the white nationalist channel. ‘I’m already on a shit ton of watch lists,’ he writes, ‘and I’m only fourteen.’ ‘Ru white tho?;)’ asks Aldritch, who himself is Anglo-Bulgarian with some German, Scottish and Croatian ancestry on the maternal side. Nobody in the group seems to care that Jason is a minor. ‘2% nigger, 23andMe test into the trashbin,’ is Jason’s prompt reply. The boy posts a copy of his genetic test results into the group to prove his whiteness. ‘Just kidding, I’m three-quarters German and a quarter Estonian.’ He gets a grinning emoji in response, as the second administrator, Deus Vult, enters the chat room.

…

Many right-wing extremists have developed an obsession with genetics. Across the dozens of closed chat groups I monitored over the course of 2017–18, at least half of them asked their members to share detailed accounts of their genetic ancestry. Some even wanted to see the test results as part of the application procedure. 23andMe, Ancestry, MyHeritage and other DNA-testing firms recorded an unprecedented surge in their sales of genetic genealogy tests since the summer of 2016. More people had their DNA analysed in 2017 than in all previous years combined.6 But white supremacists’ genetic ancestry test results don’t always match their own purity requirements, which can push them into profound identity crises.

The Driver in the Driverless Car: How Our Technology Choices Will Create the Future by Vivek Wadhwa, Alex Salkever

23andMe, 3D printing, Airbnb, AlphaGo, artificial general intelligence, augmented reality, autonomous vehicles, barriers to entry, benefit corporation, Bernie Sanders, bitcoin, blockchain, clean water, correlation does not imply causation, CRISPR, deep learning, DeepMind, distributed ledger, Donald Trump, double helix, driverless car, Elon Musk, en.wikipedia.org, epigenetics, Erik Brynjolfsson, gigafactory, Google bus, Hyperloop, income inequality, information security, Internet of things, job automation, Kevin Kelly, Khan Academy, Kickstarter, Law of Accelerating Returns, license plate recognition, life extension, longitudinal study, Lyft, M-Pesa, Mary Meeker, Menlo Park, microbiome, military-industrial complex, mobile money, new economy, off-the-grid, One Laptop per Child (OLPC), personalized medicine, phenotype, precision agriculture, radical life extension, RAND corporation, Ray Kurzweil, recommendation engine, Ronald Reagan, Second Machine Age, self-driving car, seminal paper, Silicon Valley, Skype, smart grid, stem cell, Stephen Hawking, Steve Wozniak, Stuxnet, supercomputer in your pocket, synthetic biology, Tesla Model S, The future is already here, The Future of Employment, Thomas Davenport, Travis Kalanick, Turing test, Uber and Lyft, Uber for X, uber lyft, uranium enrichment, Watson beat the top human players on Jeopardy!, zero day

As long as an application and sensor are sold as a patient’s reference tool rather than for a doctor’s use, they don’t need approval. But these applications and attachments increasingly are replacing real medical opinions and tests. Innovators’ path to market isn’t entirely obstacle free. The FDA was able to quickly and easily ban the upstart company 23andMe from selling its home genetics test kits to the public, though it later partly revised its decision.2 Uber has been fighting regulatory battles in Germany and elsewhere, largely at the behest of the taxi industry.3 But the services these two companies provide are nearly inevitable now due to the huge public support they have received as a result of the tremendous benefits they offer in their specific realms.

…

The readouts that consumer devices produce could lead people who don’t have experience in medicine to make poor decisions. And the A.I. doctors won’t have real compassion for at least another decade, maybe two. A larger concern is security and privacy. Genome tests will soon become as common as blood tests, and protecting our genomic data won’t be easy. The company 23andMe ran afoul of regulators because it was telling people what diseases they might be predisposed to. As I mentioned earlier, the issue here was the accuracy of the analysis and what people might do with the information. The bigger question, however, is what businesses may do with genomic data. Genetic-testing companies typically have contractual clauses that let them use and sell their clients’ genetic information to third parties.

…

Started by the government-funded Human Genome Project and later augmented by Celera Genomics and its noted scientist CEO, Craig Venter, the sequencing spanned more than a decade and cost nearly $3 billion. Today, numerous companies are able to completely sequence your DNA for around $1,000, in less than three days. There are even venture-backed companies, such as 23andMe, that sequence parts of human DNA for consumers, without any doctor participation or prescription, for as little as $199. We can expect the price of DNA sequencing to fall to the cost of a regular blood test in the early 2020s and, shortly thereafter, to cost practically nothing. Again, what makes this possible is that the computers that sequence DNA are becoming faster and more powerful in parallel with development of the microprocessors that power them, which double in speed and halve in price every eighteen to twenty-four months.

Sprint: How to Solve Big Problems and Test New Ideas in Just Five Days by Jake Knapp, John Zeratsky, Braden Kowitz

23andMe, 3D printing, Airbnb, Anne Wojcicki, Apollo 13, Blue Bottle Coffee, cognitive load, fake news, Gene Kranz, Google Earth, Google Hangouts, Google X / Alphabet X, self-driving car, side project, Silicon Valley, Wall-E

Over the past few years, our team has had an unparalleled opportunity to experiment and validate our ideas about work process. We’ve run more than one hundred sprints with the startups in the GV portfolio. We’ve worked alongside, and learned from, brilliant entrepreneurs like Anne Wojcicki (founder of 23andMe), Ev Williams (founder of Twitter, Blogger, and Medium), and Chad Hurley and Steve Chen (founders of YouTube). In the beginning, I wanted to make my workdays efficient and meaningful. I wanted to focus on what was truly important and make my time count—for me, for my team, and for our customers.

…

Heidi Qiao volunteered to sit for the customer test photos on pages 203 to 204. All other photos are by either Jake Knapp, Braden Kowitz, or John Zeratsky. Image postproduction by Braden Kowitz. Illustrations by Jake Knapp. JAKE KNAPP created the Google Ventures sprint process and has run more than a hundred sprints with startups such as 23andMe, Slack, Nest, and Foundation Medicine. Previously, Jake worked at Google, leading sprints for everything from Gmail to Google X. He is among the world’s tallest designers. JOHN ZERATSKY has designed mobile apps, medical reports, and a daily newspaper (among other things). Before joining Google Ventures, he was a design lead at YouTube and an early employee of FeedBurner, which Google acquired in 2007.

…

., 229 Sharpies, 75n simplicity, in maps, 66 sketching, 16, 60, 102, 103–18 abstract ideas and, 106–7 in Blue Bottle sprint, 24, 103–4, 108, 113 Crazy 8s exercise in, 109, 111–13 in Move Loot sprint, 113 prototypes and, 104–6 of rough ideas, 109, 111 solution sketches in, see solution sketches taking notes in, 109, 110 as working alone together, 107–9 Slack sprint, 129–31, 143–44, 149–58, 175, 216, 217, 220–21, 222, 223 expansion into new markets as challenge for, 129–30 Smithsonian Institute, 228 snacks, for sprints, 45 solution sketches, 109, 114–18 anonymity of, 114–15 in Blue Bottle sprint, 116–17 deciding on, see deciding as explanatory, 114 importance of words in, 115 maybe-laters in, 142, 155 single-scene, 114, 117 in Slack sprint, 130 sticky notes and, 114 storyboard format in, 114, 116 titles for, 115 winners in, 141–42 speed critique: in deciding process, 131, 135–37 Scribe in, 135–36 sprints: checklists for, 232–49 clearing calendars for, 10, 39, 40–41 concept of, 3 daily schedule in, 39, 40–41, 90–91 deciding process in, see deciding façades in, see façades as five-day process, 5–6, 9, 16, 40–41 frequently asked questions about, 251–57 learning from, see interviews, learning from no-devices rule in, 41, 110 origin of, 2–5 prototypes in, see prototypes, prototyping questions to be answered in, see questions, finding answers to; tests, real-world risk-taking in, 166 Rumbles in, 143–47 setting priorities in, 54–55 storyboards in, see storyboarding time allocation in, 38–41 timers for, 46–48 uncovering dangerous assumptions through, 56–57 universal application of, 229–30 versatility of, 5–6, 229–30 wide application of, 5–6 working alone together in, 107–9 work rooms for, 41–45 Squarespace, 186 SquidCo sprint, 30–31, 32, 139 Starting at the End, 5, 53–58 in Apollo 13 rescue, 53–54 in Blue Bottle sprint, 55–56, 57 in Flatiron Health sprint, 62–63 long-term goals and, 55–57, 61, 62–63, 67 questions to be answered in, 55–58, 62–63, 67 in Savioke sprint, 56 setting priorities in, 54–55 startups, 231 sprints and, 4–5, 15–16, 27 Starwood, 9 sticky notes: poster-size, 43, 44 solution sketches and, 114 see also How Might We notes Stitcher, 187, 189 storyboarding, 125, 148–58 “artist” for, 151, 154–55, 156 assigning prototyping tasks from, 188, 189–90 in Blue Bottle sprint, 153, 157, 188 competitors’ products in, 154 copywriting in, 155–56 Decider in, 156 detail in, 156 in Flatiron Health sprint, 153 maybe-laters in, 155 opening scene in, 152–53 resisting new ideas in, 155 risk-taking in, 156 in Savioke sprint, 153, 157 in Slack sprint, 149–53, 156 solution sketches as, 114, 116 test-time limits and, 157 story-centered design, 5 strategy, 70 straw polls, 87–88 in deciding process, 131, 138–40 successes, flawed, 223–24 supervotes, 143, 144 in deciding process, 131, 140–42, 143 surface, as contact point between product and customer, 28 target, 82, 83–88 in Blue Bottle sprint, 84–85, 101 Decider and, 31, 32, 85–88 in Flatiron Health sprint, 85–87, 88 How Might We notes and, 87 key customers in, 85–86 key event in, 85–86 maps and, 84, 85–86 in Savioke sprint, 84 straw polls and, 87–88 Tcho, 97 team processes, 1 teams, 29–37, 218 in Blue Bottle sprint, 22–24, 33 challenges and, 68 choosing members of, 33, 34–36 Deciders in, see Deciders division of labor in, 101–2 experts and, see Ask the Experts Facilitators in, see Facilitators ideal size of, 33 interviews observed by, see interviews, learning from in Ocean’s Eleven, 29–30 in Savioke sprint, 9–11, 33 in SquidCo sprint, 30–31 troublemakers in, 35 tech/logistic experts, 34 “Tenacious Tour, The” (Slack solution sketch), 144, 175, 217, 220–21, 222 tests, real-world, 5, 16, 231 in Blue Bottle sprint, 25 competitors’ products in, 154 Deciders and, 31, 32 in FitStar sprint, 173–74 in Graco sprint, 27–28 interview in, see interviews recruiting customers for, 119–23, 197 in Savioke sprint, 10, 11–13, 15 time units in, 157 Tharp, Marie, 83–84 3D printing, 27, 185, 186 tight deadlines, 109 time, allocation of, for sprints, 38–41 timers, in deciding process, 136, 138 Time Timers, 46–48 Tolkien, J. R. R., 59 Toy Story (film), 149 trade-offs, in sprint process, 31 troublemakers, in teams, 35 Tse, Alison, 12, 178, 179 Turner, Nat, 60–62 23andMe, 6 Twitter, 6 Vision, 175 WalrusCo sprint, 69 Warren, Charles, 89 Washington Post, 15 Waugh, Chris, 180–81 website usability, 197 Weinberg, Zach, 60–61 whiteboards, 72, 89 in sprint room, 42–44 Wieden+Kennedy, 230 Williams, Ev, 6, 224 Willow Garage, 8 Wojcicki, Anne, 6 words, in solution sketches, 115 working alone together, 107–9 Wright, Orville and Wilbur, 227–28, 231 Writer, 187–88 writing, importance of, 115 Yale University, 107 Yaskawa, Izumi, 11 YouTube, 6 Zeratsky, John, 5, 7, 9, 22, 24, 30, 60, 76, 140, 189 Simon & Schuster 1230 Avenue of the Americas New York, NY 10020 www.SimonandSchuster.com Copyright © 2016 by John Knapp, John Zeratsky, and Braden Kowitz All rights reserved, including the right to reproduce this book or portions thereof in any form whatsoever.

What Would Google Do? by Jeff Jarvis

"World Economic Forum" Davos, 23andMe, Amazon Mechanical Turk, Amazon Web Services, Anne Wojcicki, AOL-Time Warner, barriers to entry, Berlin Wall, bike sharing, business process, call centre, carbon tax, cashless society, citizen journalism, clean water, commoditize, connected car, content marketing, credit crunch, crowdsourcing, death of newspapers, different worldview, disintermediation, diversified portfolio, don't be evil, Dunbar number, fake news, fear of failure, Firefox, future of journalism, G4S, Golden age of television, Google Earth, Googley, Howard Rheingold, informal economy, inventory management, Jeff Bezos, jimmy wales, John Perry Barlow, Kevin Kelly, Marc Benioff, Mark Zuckerberg, moral hazard, Network effects, new economy, Nicholas Carr, old-boy network, PageRank, peer-to-peer lending, post scarcity, prediction markets, pre–internet, Ronald Coase, Salesforce, search inside the book, Sheryl Sandberg, Silicon Valley, Skype, social graph, social software, social web, spectrum auction, speech recognition, Steve Jobs, the long tail, the medium is the message, The Nature of the Firm, the payments system, The Wisdom of Crowds, transaction costs, web of trust, WikiLeaks, Y Combinator, Zipcar

Education and information become insurance against insurance. Godin took this line of thinking to its extreme when he speculated about opportunities not just for smarter people but—genetically speaking—healthier people as determined by 23andMe, a service that analyzes users’ DNA. (Founded by Brin’s wife, Anne Wojcicki, 23andMe discovered his Parkinson’s gene. Google invested in the company.) Godin said: And while some may not like it, what happens when 23andMe gets a lot smarter and the healthiest gene pool starts their own life insurance coop? U.K. business journalist James Ball agreed with me that insurance is “a glorified betting market” where insurance providers “offer odds against certain outcomes—adverse outcomes—and we pay up the stake.

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See search-engine optimization Sequoia Capital, 189 Shardanand, Upendra, 35 Shirky, Clay, 50, 60, 151, 191–92, 197, 235–36, 237 Silverman, Dwight, 13 simplicity, 114–16, 236 SimplyHired.com, 39 Sirius Satellite Radio, 131 Skype, 31, 50 Smart Mobs (Rheingold), 106 Smith, Quincy, 38 Smolan, Rick, 140 social business, 158 social graph, 49 socialization, 211–12 social-media, 172–73 social responsibility, 47 social web, 51 Sorrell, Martin, 42 Sourcetool.com, 100 specialization, 26–27, 154 speed, 103–4, 105–6 Spitzer, Eliot, 96 splogs, 43 Starbucks, 60–62 Stern, Howard, 95, 131–32 Stewart, Jon, 95–96 StudieVZ, 50 Supreme Court, 225 Surowiecki, James, 88 talent, 146, 240 Tapscott, Don, 113, 151, 225 targeting, 151, 179–80 teaching, 193, 214–15 teamwork, 217 TechCrunch, 107, 192 Technorati, 15, 20 TechTV, 132 telecommunications, 165–71 Telegraph Media Group, 123 television, 84 cable, 167 decline of, 65–66 listings, 109–10 networks, 135 Television Without Pity, 135 Tesco, 179 Tesla Motors, 175 testing, 214 Threadbanger, 180 Threadless, 57 TimesSelect, 78 Time Warner, 80–81 Tobaccowala, Rishad, 114, 121–22, 145–48, 151, 177 on Apple, 228 toilet paper, 180–81 TomEvslin.com, 31 Toto, 181 Toyota, 174–75 transparency, 83, 97–98 journalism and, 92 PR and, 223 Tribune Company, 129 Trippi, Joe, 238 trust, 74, 170 control v., 82–83 in customers, 83–84 Tumblr, 192 Turner, Ted, 134 TV Guide, 109–10 20 percent rule, 111, 114 23andMe, 205 Twitter, 20, 126 Dell and, 46 mobs and, 107 real time and, 105–6 Tyndall, Andrew, 220 Union Square Ventures, 30 University of Phoenix, 217 Updike, John, 138 The Vanishing Newspaper (Meyer), 125 Vardi, Yossi, 31–32 Vaynerchuk, Gary, 107, 157–61 VC. See venture capital vendor relationship management (VRM), 201–2 venture capital (VC), 189–95 Vershbow, Ben, 138 Virginia Tech University, 105 Virgin Money, 197 Virtual Law Partners, 223 Vise, David A., 114–15 VRM.

Click Here to Kill Everybody: Security and Survival in a Hyper-Connected World by Bruce Schneier

23andMe, 3D printing, air gap, algorithmic bias, autonomous vehicles, barriers to entry, Big Tech, bitcoin, blockchain, Brian Krebs, business process, Citizen Lab, cloud computing, cognitive bias, computer vision, connected car, corporate governance, crowdsourcing, cryptocurrency, cuban missile crisis, Daniel Kahneman / Amos Tversky, David Heinemeier Hansson, disinformation, Donald Trump, driverless car, drone strike, Edward Snowden, Elon Musk, end-to-end encryption, fault tolerance, Firefox, Flash crash, George Akerlof, incognito mode, industrial robot, information asymmetry, information security, Internet of things, invention of radio, job automation, job satisfaction, John Gilmore, John Markoff, Kevin Kelly, license plate recognition, loose coupling, market design, medical malpractice, Minecraft, MITM: man-in-the-middle, move fast and break things, national security letter, Network effects, Nick Bostrom, NSO Group, pattern recognition, precautionary principle, printed gun, profit maximization, Ralph Nader, RAND corporation, ransomware, real-name policy, Rodney Brooks, Ross Ulbricht, security theater, self-driving car, Seymour Hersh, Shoshana Zuboff, Silicon Valley, smart cities, smart transportation, Snapchat, sparse data, Stanislav Petrov, Stephen Hawking, Stuxnet, supply-chain attack, surveillance capitalism, The Market for Lemons, Timothy McVeigh, too big to fail, Uber for X, Unsafe at Any Speed, uranium enrichment, Valery Gerasimov, Wayback Machine, web application, WikiLeaks, Yochai Benkler, zero day

Scherer (Spring 2016), “Regulating artificial intelligence systems: Risks, challenges, competencies, and strategies,” Harvard Journal of Law & Technology 29, no. 2, http://jolt.law.harvard.edu/articles/pdf/v29/29HarvJLTech353.pdf. 149Israel created its National Cyber Bureau: National Cyber Bureau (2 Jun 2013), “Mission of the bureau,” Prime Minister’s Office, http://www.pmo.gov.il/English/PrimeMinistersOffice/DivisionsAndAuthorities/cyber/Pages/default.aspx. 149The UK created the National Cyber Security Centre: National Cyber Security Centre (9 Jun 2017; accessed 24 Apr 2018), “About the NCSC,” https://www.ncsc.gov.uk/information/about-ncsc. 150One: governments tend to regulate industries: Andrew Odlyzko (1 Mar 2009), “Network neutrality, search neutrality, and the never-ending conflict between efficiency and fairness in markets,” Review of Network Economics 8, no. 1, https://www.degruyter.com/view/j/rne.2009.8.issue-1/rne.2009.8.1.1169/rne.2009.8.1.1169.xml. 151The agency doesn’t conduct the testing itself: Food and Drug Administration (accessed 24 Apr 2018), “The FDA’s role in medical device cybersecurity,” https://www.fda.gov/downloads/MedicalDevices/DigitalHealth/UCM544684.pdf. 151Rules for privacy of patients’ medical data: Charles Ornstein (17 Nov 2015), “Federal privacy law lags far behind personal-health technologies,” Washington Post, https://www.washingtonpost.com/news/to-your-health/wp/2015/11/17/federal-privacy-law-lags-far-behind-personal-health-technologies. 151And sometimes the FDA fights back: Russell Brandom (25 Nov 2013), “Body blow: How 23andMe brought down the FDA’s wrath,” Verge, https://www.theverge.com/2013/11/25/5144928/how-23andme-brought-down-fda-wrath-personal-genetics-wojcicki. Gina Kolata (6 Apr 2017), “F.D.A. will allow 23andMe to sell genetic tests for disease risk to consumers,” New York Times, https://www.nytimes.com/2017/04/06/health/fda-genetic-tests-23andme.html. 151In 2015, the FTC sued Wyndham Hotels: Electronic Privacy Information Center (24 Aug 2015), “FTC v. Wyndham,” https://epic.org/amicus/ftc/wyndham. 152The Federal Court of Appeals sided with: Federal Trade Commission (9 Dec 2015), “Wyndham settles FTC charges it unfairly placed consumers’ payment card information at risk,” https://www.ftc.gov/news-events/press-releases/2015/12/wyndham-settles-ftc-charges-it-unfairly-placed-consumers-payment. 152It took 13 years for Facebook: Josh Constine (27 Jun 2017), “Facebook now has 2 billion monthly users . . . and responsibility,” TechCrunch, https://techcrunch.com/2017/06/27/facebook-2-billion-users. 153The law makes an important distinction: Eric R.

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As you’d expect, medical-data rules are much more stringent. Many developers of new health-related products and services are trying to position their wares as consumer devices, so they don’t require FDA approval. This sometimes works, as with health trackers like Fitbit. And sometimes the FDA fights back, as it did with genetic data collected by 23andMe. For cars, the Department of Transportation has only issued voluntary security standards. Voluntary standards are never as effective as mandatory standards, but they can help. For example, in a lawsuit the court will often assess voluntary compliance with DOT guidance to help determine whether a manufacturer was negligent.

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

GO TO NOTE REFERENCE IN TEXT her book on parenting: Wojcicki, How to Raise Successful People, 138. GO TO NOTE REFERENCE IN TEXT another magazine named her: Elizabeth Murphy, “Inside 23andMe founder Anne Wojcicki’s $99 DNA Revolution,” Fast Company, October 14, 2013, https://www.fastcompany.com/3018598/for-99-this-ceo-can-tell-you-what-might-kill-you-inside-23andme-founder-anne-wojcickis-dna-r. GO TO NOTE REFERENCE IN TEXT a San Jose newspaper: Mike Swift, “Susan Wojcicki: The Most Important Googler You’ve Never Heard Of,” The Mercury News, February 3, 2011, https://www.mercurynews.com/2011/02/03/susan-wojcicki-the-most-important-googler-youve-never-heard-of/.

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GO TO NOTE REFERENCE IN TEXT Ramaswamy grew animated: Amir Efrati, “The Ascension of Google’s Sridhar Ramaswamy,” The Information, April 6, 2015, https://www.theinformation.com/articles/the-ascension-of-google-s-sridhar-ramaswamy. Ramaswamy denied saying this. GO TO NOTE REFERENCE IN TEXT went public with their split: Liz Gannes, “Google Co-Founder Sergey Brin and 23andMe Co-Founder Anne Wojcicki Have Split,” All Things D, August 28, 2013, https://allthingsd.com/20130828/google-co-founder-sergey-brin-and-23andme-co-founder-anne-wojcicki-have-split/. GO TO NOTE REFERENCE IN TEXT Brin went to Burning Man: Vanessa Grigoriadis, “O.K., Glass: Make Google Eyes,” Vanity Fair, March 12, 2014, https://www.vanityfair.com/style/2014/04/sergey-brin-amanda-rosenberg-affair.

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Soon she veered back to the more practical, earning a master’s in economics and another in business, and began a career in technology. She married Dennis Troper, a technologist who would later join her at Google. Her sister Janet became an epidemiologist, and Anne, the youngest, worked on Wall Street before returning home to become Valley royalty. Anne co-created the genetics testing firm 23andMe and married Google’s Sergey Brin in an unorthodox ceremony in the Bahamas. Affable and charming, Anne easily won praise. Vanity Fair called her “Jennifer Aniston in Birkenstocks”; another magazine named her “the most daring CEO in America.” Susan, in contrast, came off as reserved, humble, and conscientious, a “classic older sister,” according to one acquaintance.

Decoding the World: A Roadmap for the Questioner by Po Bronson

23andMe, 3D printing, 4chan, Abraham Maslow, Affordable Care Act / Obamacare, altcoin, Apple's 1984 Super Bowl advert, Asilomar, autonomous vehicles, basic income, Big Tech, bitcoin, blockchain, Burning Man, call centre, carbon credits, carbon tax, cognitive bias, cognitive dissonance, coronavirus, COVID-19, CRISPR, cryptocurrency, decarbonisation, deep learning, deepfake, DeepMind, dematerialisation, Donald Trump, driverless car, dumpster diving, edge city, Ethereum, ethereum blockchain, Eyjafjallajökull, factory automation, fake news, financial independence, Google X / Alphabet X, green new deal, income inequality, industrial robot, Isaac Newton, Jeff Bezos, Kevin Kelly, Kickstarter, Mars Rover, mass immigration, McMansion, means of production, microbiome, microplastics / micro fibres, oil shale / tar sands, opioid epidemic / opioid crisis, Paul Graham, paypal mafia, phenotype, Ponzi scheme, power law, quantum entanglement, Ronald Reagan, Sand Hill Road, sharing economy, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, smart contracts, source of truth, stem cell, Steve Jobs, Steve Jurvetson, sustainable-tourism, synthetic biology, Tesla Model S, too big to fail, trade route, universal basic income, Watson beat the top human players on Jeopardy!, women in the workforce

Which in turn rip an electron off the nucleotide next door, in a long chain reaction that has us, at all times, being ripped apart from within. Another way to say this is, it doesn’t really matter what kind of car you buy—what matters is that you have a good mechanic. Now absolutely zero of what I’ve described is going to show up on a 23andMe report. Most of what’s in a 23andMe report are “associations,” often very soft statistical abstractions between cohorts of people. Too little of what it trawls for has any defined biology. A venture capitalist could never fund a company that relied on an association study. They’re not bankable. Conclusions should rarely be drawn from them.

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Identical twins don’t have the same DNA. If you clone a cat, it doesn’t even look the same. If you have the genes for dark skin, it doesn’t mean you have dark skin. Every cell in your body does not have the same DNA. Gene therapy does not make permanent changes to your genome. Sperm does not carry a “copy” of a father’s genome. 23andMe cannot tell you what nations your ancestors came from. If you knocked out the gene for X, you very likely wouldn’t get rid of X at all. The genes for intelligence do not determine your IQ. I’m going to put this gently. The human body is chock-full of DNA, and only some of it matches your “constitution.”

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Almost every human who lived more than ninety years with their mind still sharp had a very active REST gene. So if I was introducing REST at an awards dinner—maybe a “Genes of the Year Awards”—The Genies—I’d say, “REST is the gene that makes your brain be a brain, and makes your body not try to act like a brain.” REST is a big deal. But you won’t find it on a 23andMe test. Because it’s not like some people have it and others don’t. We all have REST. We all need REST. What matters is how active REST is. Most people with Alzheimer’s disease have suppressed REST genes. REST is active in the brain, too. It makes the brain more efficient. It’s a neuron silencer. Scientists can measure how much energy the brain is using.

The Genetic Lottery: Why DNA Matters for Social Equality by Kathryn Paige Harden

23andMe, Affordable Care Act / Obamacare, assortative mating, autism spectrum disorder, Bayesian statistics, Berlin Wall, Black Lives Matter, classic study, clean water, combinatorial explosion, coronavirus, correlation coefficient, correlation does not imply causation, COVID-19, CRISPR, crowdsourcing, delayed gratification, deliberate practice, desegregation, double helix, epigenetics, game design, George Floyd, Gregor Mendel, impulse control, income inequality, Jeff Bezos, longitudinal study, low skilled workers, Mark Zuckerberg, meritocracy, meta-analysis, Monkeys Reject Unequal Pay, phenotype, randomized controlled trial, replication crisis, Scientific racism, stochastic process, surveillance capitalism, TED Talk, The Bell Curve by Richard Herrnstein and Charles Murray, twin studies, War on Poverty, zero-sum game

Or, we could be matching on a segment from one of our parents but not the other. FIGURE 6.1.  Identity-by-descent sharing of segments of 23 chromosomes between a pair of full siblings. Image from author’s 23andMe® profile. The author and her brother share segments of DNA that have a total length of 3321 centimorgans (cMs), which is 44.6% of the author’s genome. My brother agreed to be genotyped by 23andMe for the sake of this book. (In true little-brother fashion, he immediately demanded that I Venmo him $200 to pay him back.) Helpfully, 23andMe automatically generates an infographic showing which DNA segments we share, and which ones we don’t (figure 6.1). On chromosome 11, for instance, we’re nearly twins; on chromosome 13, we are barely related.

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,” Wall Street Journal, June 13, 2019, https://www.wsj.com/articles/who-deserves-to-go-to-harvard-11560464201. 37. Anne Case and Angus Deaton, Deaths of Despair and the Future of Capitalism (Princeton, NJ: Princeton University Press, 2020), https://press.princeton.edu/books/hardcover/9780691190785/deaths-of-despair-and-the-future-of-capitalism. INDEX 23andMe, 114 Affordable Care Act (ACA), 244–245 Ainsworth, Mary, 97 ancestry and race, 72–73, 93–95; antiracism and responsibility in postgenomic world, 89–93; common ancestors of today’s people and, 73–75; differences between, 77–82; Eurocentric bias of GWAS and, 84–85; genealogical versus genetic ancestors, 76–77; genome-wide association study (GWAS) and, 82–84, 94–95 Anderson, Elizabeth, 18, 213, 227 anti-eugenic policies, 232–233; and luck in meritocracy, 246–251; to stop wasting time, money, talent, and tools, 234–235; structuring society to advantage of those least advantaged, 251–255; using genetic information for equity, not exclusion, 242–246; using genetic information to improve opportunity, not classify people, 235–242; veil of ignorance and, 251–255 anti-eugenic project, 20 antiracism, 89–93, 232 Appelbaum, Paul, 197 attachment, 97 autism spectrum disorders (ASDs), 27–28, 63, 228–229 Awad, Germine, 221 bacteria, 31 Barth, Daniel, 41–43, 44 Bell Curve, The, 16–17, 18, 78, 123 Belsky, Dan, 43, 127, 188 Benjamin, Ruha, 175, 179, 233 Bessey, Sarah, 255 Bezos, Jeff, 7 Binet, Alfred, 216 bioannotation, 136–137 bioethics, 213–215 bioRxiv, 22 Black Lives Matter, 92 Bliss, Catherine, 236 Blueprint, 15 Bourdain, Anthony, 50 Bowlby, John, 97 Box, George, 44 Bradley, Shawn, 38, 42, 63, 222 brain: bioannotation and, 136–137; executive functions and, 138–140 Brigham, Carl, 80 Bronfenbrenner, Urie, 106–107 Buck, Carrie, 14, 15 Buck v.

The Sullivanians: Sex, Psychotherapy, and the Wild Life of an American Commune by Alexander Stille

23andMe, behavioural economics, cognitive dissonance, East Village, experimental subject, fear of failure, medical residency, Milgram experiment, military-industrial complex, Norman Mailer, rent control, Ronald Reagan, Stanford prison experiment, sunk-cost fallacy, white flight

” * * * As the kids of the Fourth Wall came to terms with their past,many of them turned to genetic testing—which became widely available and relatively inexpensive by the 2010s—in order to more clearly establish their paternity. “Me and another friend from the group found out we were siblings through 23andMe,” Pam Newton explained. “That’s what started us on this whole journey.” Pam and another boy from the group, seven years younger, discovered they were half-siblings. “Neither of us knew who our biological fathers were, and we were like, ‘Let’s figure it out,’ so he was the first sibling I gained.” To her surprise, Pam learned that her biological father was Ralph Klein, their downstairs neighbor on the second floor of the Ninety-First Street compound and also—perhaps more important for Pam—the father of Toni Klein, one of her best friends.

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The one significant exception to this was a good friend of hers who gained a whole new family. “She was raised by a single mom and then found out who her dad was, and now she calls him dad and calls his other kids her brothers and sisters. So she really gained a family.” At some point after Pam got her 23andMe results, Karen Bray went to a birthday party for Sean Mack, another Fourth Wall kid, who was turning forty. (The second generation of kids remain very good friends.) Another girl from the group came up to Karen and said something like, “I always tell people that I know a pair of twins who actually have different fathers.”

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Pam also asked Robbie Newton if he would do the test as well. There were kids who were trying to figure out whether they were Saul Newton’s biological children, and since Saul was long dead by this point, Robbie’s DNA might solve that puzzle. Karen awaited her results, and when she got the email from 23andMe, she was thinking, “The options are either yes, Pam and I are siblings, or we’re not.” Instead, her genetic profile revealed that her biological father was her stepfather, Robbie Newton. Karen was completely floored. This was the last thing she expected. The blood test done twenty-five years earlier during the custody battle had ruled out this possibility.

Immortality, Inc. by Chip Walter

23andMe, Airbnb, Albert Einstein, Arthur D. Levinson, bioinformatics, Buckminster Fuller, cloud computing, CRISPR, data science, disintermediation, double helix, Elon Musk, Isaac Newton, Jeff Bezos, Larry Ellison, Law of Accelerating Returns, life extension, Menlo Park, microbiome, mouse model, pattern recognition, Peter Thiel, phenotype, radical life extension, Ray Kurzweil, Recombinant DNA, Rodney Brooks, self-driving car, Silicon Valley, Silicon Valley startup, Snapchat, South China Sea, SpaceShipOne, speech recognition, statistical model, stem cell, Stephen Hawking, Steve Jobs, TED Talk, Thomas Bayes, zero day

Shortly upon arrival, the phlebotomist siphons off 20 or so vials of blood. These are needed to entirely sequence the subject’s genome, all three billion base pairs. Companies like Ancestry.com and 23andMe might say they are analyzing your DNA, but the truth is they only look at snippets of it: the parts science already largely understands, like how much Neanderthal DNA you can claim, or what part of the world various members of your family hailed from, and, more recently, in 23andMe’s case, insights into whether you have the genes associated with heart disease or Parkinson’s or Alzheimer’s. These make up a few drops in the oceans of information contained in any human genome.

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A little more than a year earlier, he had taken over from Eric Schmidt as the company’s CEO, reins he and Brin had voluntarily handed Schmidt in 2001, when the company was still in its infancy. Maris was the head of Google Ventures (also known as GV), a fund that since 2008 had thrown hundreds of millions of dollars at cutting-edge start-ups like Uber, Nest, 23andMe, and a long catalog of others. Together, those businesses had made Maris one of the most successful venture capitalists in Silicon Valley. Maris reached out to Levinson and told him about his idea. Maris knew it might seem a little out of the ordinary—well, maybe way out of the ordinary—but he hoped to get Levinson’s feedback.

Googled: The End of the World as We Know It by Ken Auletta

"World Economic Forum" Davos, 23andMe, AltaVista, An Inconvenient Truth, Andy Rubin, Anne Wojcicki, AOL-Time Warner, Apple's 1984 Super Bowl advert, Ben Horowitz, bioinformatics, Burning Man, carbon footprint, citizen journalism, Clayton Christensen, cloud computing, Colonization of Mars, commoditize, company town, corporate social responsibility, creative destruction, death of newspapers, digital rights, disintermediation, don't be evil, facts on the ground, Firefox, Frank Gehry, Google Earth, hypertext link, Innovator's Dilemma, Internet Archive, invention of the telephone, Jeff Bezos, jimmy wales, John Markoff, Kevin Kelly, knowledge worker, Larry Ellison, Long Term Capital Management, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, Mary Meeker, Menlo Park, Network effects, new economy, Nicholas Carr, PageRank, Paul Buchheit, Peter Thiel, Ralph Waldo Emerson, Richard Feynman, Sand Hill Road, Saturday Night Live, semantic web, sharing economy, Sheryl Sandberg, Silicon Valley, Skype, slashdot, social graph, spectrum auction, stealth mode startup, Stephen Hawking, Steve Ballmer, Steve Jobs, strikebreaker, Susan Wojcicki, systems thinking, telemarketer, the Cathedral and the Bazaar, the long tail, the scientific method, The Wisdom of Crowds, Tipper Gore, Upton Sinclair, vertical integration, X Prize, yield management, zero-sum game

But even though he was raised as a Jew and attended Hebrew school for a few years, he was nonpracticing, did not have a bar mitzvah, and was put off by traditional Jewish celebrations, which he once told an Israeli reporter he “associated with getting lots of gifts and money, and I was never comfortable with that.” When he was married on an island in the Bahamas in May of 2007 to Anne Wojcicki, cofounder of 23andMe, a genetics research company, the couple stood in bathing suits under a chuppah, the traditional Jewish wedding canopy, but no rabbi officiated. Then, as now, he was uncomfortable with introspection. Asked by the same Israeli reporter if it was a coincidence that his wife was Jewish, he said, “I believe there are lots of nice non-Jewish girls out there.

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A longtime Google employee describes Page this way: “Larry is like a wall. He analyzes everything. He asks, ‘Is this the most efficient way to do this?’ You’re always on trial with Larry. He always pushes you.” While Brin is more approachable than Page, he, too, can be awkward around strangers. His wife Anne Wojcicki’s company, 23andMe, was feted at a fashionable cocktail party in September 2008 that was cohosted by Diane von Furstenberg and her husband, Barry Diller, Wendi and Rupert Murdoch, and Georgina Chapman and her husband, Harvey Weinstein. The event was held at Diller’s Frank Gehry-designed IAC headquarters in Manhattan.

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The three men chatted on stage for a few minutes when Page interrupted to say that Brin wanted ten minutes to share something. Brin stepped to a microphone and riveted the audience for about ten minutes with a precise, impersonal account of his mother’s recent diagnosis of Parkinson’s disease. He explained that his wife, Anne Wojcicki, had cofounded 23andMe to study genetics, including the genetics of Parkinson’s. He said the evidence of a genetic link to Parkinson’s was at first slight, but studies had recently unearthed one gene, LRRK2, in particular a mutation known as G2019S, that in some ethnic groups creates a familial link through which the disease travels.

Data for the Public Good by Alex Howard

"World Economic Forum" Davos, 23andMe, Atul Gawande, Cass Sunstein, cloud computing, crowdsourcing, data science, Hernando de Soto, Internet of things, Kickstarter, lifelogging, machine readable, Network effects, openstreetmap, Silicon Valley, slashdot, social intelligence, social software, social web, web application

The idea of data as a currency is still in its infancy, as Strata Conference chair Edd Dumbill has emphasized. The Locker Project, which provides people with the ability to move their own data around, is one of many approaches. The growth of the Quantified Self movement and online communities like PatientsLikeMe and 23andMe validates the strength of the movement. In the U.S. federal government, the Blue Button initiative, which enables veterans to download personal health data, has now spread to all federal employees and earned adoption at Aetna and Kaiser Permanente. In early 2012, a Green Button was launched to unleash energy data in the same way.

Uncharted: How to Map the Future by Margaret Heffernan

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

The different experiences and environments of the two individuals, even with exactly the same DNA, are different enough to produce life-defining differences. What happens along the way is life. Since DNA testing has become easily available to the general public, over 26 million consumers have chosen to see how much of their future might be detectable. Rupert Baines tried the genetic testing kit 23andMe out of sheer curiosity; as a lifelong technologist, he was open-minded about what he learned. ‘I think what’s interesting is what it doesn’t tell you,’ Baines laughed. ‘There were a lot of caveats – likelihoods rather than absolutes. Likely doesn’t have red hair. Likely dark hair, that kind of thing.’

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Mark McCarthy, a geneticist at Oxford University, worries that ‘there aren’t enough genetic counsellors on the planet’ to manage the subtle interpretations of polygenic scores. But, as always in the world of forecasting, there’s money to be made from commercialising prophecy and imbuing it with moral urgency. Both Plomin and Anne Wojcicki of 23andMe believe it is a parent’s duty to ‘arm themselves with their child’s blueprint’.32 Duty to whom? Plomin’s big idea and Wojcicki’s big business trivialise the danger of emphasising what’s certain – the score – over and above what’s uncertain – the other half that represents life. Stereotyping, rationing, discrimination, passivity, surrender: these are the very real risks produced when overstating the foresight afforded by DNA.

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., 94 ‘Rosina’ anecdote, 173 RTÉ, 145 Rubbia, Carlo, 207, 216 rules-bound games, 107–8 Rumi, 296 Russell, Bertrand, 97 Russia Today (RT), 111 Sagrada Família, 224–8, 232 St Margaret’s Hospice, 289–94, 321 St Patrick’s Cathedral, 260 Samaritans, 119 same-sex marriage, 140 Sanford Underground Research Facility, 204 Sanger Centre, 219–21, 224, 231, 232 Santayana, George, 51 Saquinavir, 266 Sargent, Singer, 15 SARS, 298 Saunders, Cicely, 289 scenario planning, 155–75 Schatz, Albert, 15 schizophrenia, 92, 93, 96 Schoenberg, Arnold, 197 Schrödinger, Erwin, 206 Schubert, Franz, 277 scientific management, 120, 199 Scotland, independence sort by, 39 Seagram Building, 226 Sears, 117 Second World War, 54, 73, 80, 99, 147, 152, 162, 164, 273–4, 279 seedbanks, 306, 316 segregation, 33, 97, 129 self-discipline, 19, 230 self-interest, 23, 29, 36, 174 Sencer, David, 58–9 sensitive humility, 192 Shafak, Elif, 191 Shakespeare, William, 31, 108–9, 184, 195, 198, 275–6 shamanism, 2 Sharper Image, 247 Sheffield Health Geeks, 118 Shell Oil Corporation, 154–66 passim short-termism, 78, 308 sickle-cell anaemia, 89 Siilasmaa, Risto, 248–50 ‘Silence = Death’ campaign, 265 Silicon Valley, 33, 129, 246, 285 Skidelsky, Robert, 25 Sky, 111 ‘sleeping beauties’, 82 sleight of hand, 3 Sloane Kettering Cancer Center, 296 social connection, 103 social efficiency, 101 ‘social rubbish’, 97 social turmoil, 4 soft data, 156, 159, 168 ‘something for everyone’, 76 soothsaying, 2 Sophocles, 177 Spence, Basil, 226 Spiritual Association of the Devotees of Saint Joseph, 224 SSC, 209 stability, 17–18, 22, 56, 113, 154, 158, 282 Standard Life (SL), 251 Stanford, 273 statistics, 16, 20, 23, 40, 74, 82, 92, 136, 139, 178 stereotyping, 79–80, 93, 95, 151 sterilisation, 97 Stonyfield, 113–14, 115 Strauss, Levi, 274 Stravinsky, Igor, 15 streptomycin, 15 Suez Crisis, 53 Sugrañes, Domènec, 225 Suharto, Tommy, 254 Sulston, John, 219 Sumpter, Donald, 195 super-collider projects, 185, 204–32 super-forecasting, 37, 38, 41, 63 SUperSYmmetry (SUSY), 216 surrender, 7, 36, 96, 102, 103, 202, 242, 319 Sustainable Development Goals (SDGs), 309 SUSY, 216 Svalbard, 306–7, 316 swine flu, 57, 58 Symbian, 247 Syngenta, 160 Szabłowski, Witold, 121 Tambo, Oliver, 258 Tate, 186 taxation, 28 taxi drivers/driving, 42–6, 63, 181, 314 TB, 14–15, 19, 41 Terrence Higgins Trust (THT), 257–8, 268 terrorism, 15, 36, 85–6, 173, 305 test-tube baby, first-ever, 222 Tetlock, Philip, 5, 27–8, 36–7, 40 Texas University, 129, 163 Thamotheram, Raj, 279, 294 Thatcher, Margaret, 209 Thiel, Peter, 286 Third Law of Motion, 19 THT, 257–8, 268 Thunberg, Greta, 269, 317 Tóibín, Colm, 179 Toys “R” Us, 248 track record, 5, 28, 41 trade wars, 4 Transcend, 283 transformation programmes, 116, 166, 199 transhumanism, 280, 283–7 Trump, Donald, 4, 28, 39, 40, 170, 176 trust, 2, 9, 17, 19, 28, 41, 54, 70, 103, 108, 112, 140, 151, 163–5, 172, 182–7, 201, 211, 221–2, 234, 244, 249, 252, 255, 266, 270, 302, 304–7, 316, 318 tuberculosis, see TB 21/7, 85 23andMe, 95 Twitter, 4 tyranny, 7, 63, 121–2 Umbert, Esteve, 229–30 Unified Planning Machine, 154 United Arab Emirates (UAE), 312 United Nations (UN), 309, 313 unknowns, density of, 17 urban crowding, 14 US Congress, 1, 24, 58, 264 utopia, 6, 103, 312, 313 vaccines, 14, 57–8, 297–304, 298–304 Venter, Craig, 219 Vera Drake, 185, 192 Vidal, Francesc de Paula Quintana i, 227 Vietnam War, 53–4 Vision for Slovenia, 162–5 volatility, 3, 4, 17–18, 147, 155, 157, 224, 237 W boson, 207, 216 Wack, Pierre, 154, 155–6, 159, 168 Waksman, Selman, 15 Wall Street, 20 Walmart, 151 war on cancer, 82 Warnock Commission, 222, 223, 234 Warnock, Mary, 222–3, 316 Washington Mutual, 248 wasteful exuberance, 20 Webb, Beatrice and Sidney, 97 wellbeing, 118, 156, 164, 309, 312 Wellbeing of Future Generations Act (2015) (Wales), 309, 310, 311, 313 Wellcome Sanger Institute, 219, 224, 231 Wellcome Trust, 85 Wells, H.

Homo Deus: A Brief History of Tomorrow by Yuval Noah Harari

23andMe, Aaron Swartz, agricultural Revolution, algorithmic trading, Anne Wojcicki, Anthropocene, anti-communist, Anton Chekhov, autonomous vehicles, behavioural economics, Berlin Wall, call centre, Chekhov's gun, Chris Urmson, cognitive dissonance, Columbian Exchange, computer age, DeepMind, Demis Hassabis, Deng Xiaoping, don't be evil, driverless car, drone strike, European colonialism, experimental subject, falling living standards, Flash crash, Frank Levy and Richard Murnane: The New Division of Labor, glass ceiling, global village, Great Leap Forward, Intergovernmental Panel on Climate Change (IPCC), invention of writing, invisible hand, Isaac Newton, job automation, John Markoff, Kevin Kelly, lifelogging, low interest rates, means of production, Mikhail Gorbachev, Minecraft, Moneyball by Michael Lewis explains big data, Monkeys Reject Unequal Pay, mutually assured destruction, new economy, Nick Bostrom, pattern recognition, peak-end rule, Peter Thiel, placebo effect, Ray Kurzweil, self-driving car, Silicon Valley, Silicon Valley ideology, stem cell, Steven Pinker, telemarketer, The future is already here, The Future of Employment, too big to fail, trade route, Turing machine, Turing test, ultimatum game, Watson beat the top human players on Jeopardy!, zero-sum game

The market for DNA testing is currently growing in leaps and bounds. One of its leaders is 23andMe, a private company founded by Anne Wojcicki, former wife of Google co-founder Sergey Brin. The name ‘23andMe’ refers to the twenty-three pairs of chromosomes that contain our genome, the message being that my chromosomes have a very special relationship with me. Anyone who can understand what the chromosomes are saying can tell you things about yourself that you never even suspected. If you want to know what, pay 23andMe a mere $99, and they will send you a small package with a tube. You spit into the tube, seal it and mail it to Mountain View, California.

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(game show) 315–16, 315 Jesus Christ 91, 155, 183, 187, 271, 274, 297 Jews/Judaism: ancient/biblical 60, 90–1, 94, 172–3, 174, 181, 193, 194–5, 268, 390; animal welfare and 94; expulsions from early modern Europe 197, 198; Great Jewish Revolt (AD 70) 194; homosexuality and 225–6; Second World War and 164–5, 165, 182 Jolie, Angelina 332–3, 335, 347 Jones, Lieutenant Henry 254 Journal of Personality and Social Psychology 354–5 Joyce, James: Ulysses 240 JSTOR digital library 383 Jung, Carl 223–4 Kahneman, Daniel 294, 295–6, 338–9 Kasparov, Garry 320–1, 320 Khmer Rouge 264 Khrushchev, Nikita 263, 273–4 Kurzweil, Ray 24, 25, 27; The Singularity is Near 381 Kyoto protocol, 1997 215–16 Lake Fayum engineering project, Egypt 161–2, 175, 178 Larson, Professor Steve 324–5 Law of the Jungle 14–21 lawns 58–64, 62, 63 lawyers, replacement by artificial intelligence of 314 Lea, Tom: That 2,000 Yard Stare (1944) 244, 245, 246 Lenin Academy for Agricultural Sciences 371–2 Lenin, Vladimir 181, 207, 251, 271, 272, 273, 375 Levy, Professor Frank 322 liberal humanism/liberalism 98, 181, 247; contemporary alternatives to 267–77; free will and 281–90, 304; humanism and see humanism; humanist wars of religion, 1914– 1991 and 261–7; individualism, belief in 290–304, 305; meaning of life and 304, 305; schism within humanism and 246–57; science undermines foundations of 281–306; technological challenge to 305–6, 307–50; value of experience and 257–9, 260, 387–8; victory of 265–7 life expectancy 5, 25–7, 32–4, 50 ‘logic bombs’ (malicious software codes) 17 Louis XIV, King 4, 64, 227 lucid dreaming 361–2 Luther, Martin 185–7, 275, 276 Luther King, Martin 263–4, 275 Lysenko, Trofim 371–2 MAD (mutual assured destruction) 265 malaria 12, 19, 315 malnutrition 3, 5, 6, 10, 27, 55 Mao Zedong 27, 165, 167, 251, 259, 263, 375 Maris, Bill 24 marriage: artificial intelligence and 337–8, 343; gay 275, 276; humanism and 223–5, 275, 276, 291, 303–4, 338, 364; life expectancy and 26 Marx, Karl/Marxism 56–7, 60, 183, 207, 247–8, 271–4; Communist Manifesto 217; Das Kapital 57, 274 Mattersight Corporation 317–18 Mazzini, Giuseppe 249–50 meaning of life 184, 222, 223, 299–306, 338, 386 Memphis, Egypt 158–9 Mendes, Aristides de Sousa 164–5, 164 Merkel, Angela 248–9 Mesopotamia 93 Mexico 8–9, 11, 263 Michelangelo 27, 253; David 260 Microsoft 15, 157, 330–1; Band 330–1; Cortana 342–3 Mill, John Stuart 35 ‘mind-reading’ helmet 44–5 Mindojo 314 MIT 322, 383 modern covenant 199–219, 220 Modi, Narendra 206, 207 money: credit and 201–5; Dataism and 352, 365, 379; intersubjective nature of 144, 145, 171, 177; invention of 157, 158, 352, 379; investment in growth 209–11 mother–infant bond 88–90 Mubarak, Hosni 137 Muhammad 188, 226, 270, 391 Murnane, Professor Richard 322 Museum of Islamic Art, Qatar 64 Muslims: Charlie Hebdo attack and 226; Crusades and 146, 147, 148, 149; economic growth, belief in 206; evaluating success of 174; evolution and 103; expulsions of from early modern Europe 197, 198; free will and 285; lawns and 64; LGBT community and 225 see also Islam Mussolini, Benito 302 Myanmar 144, 206 Nagel, Thomas 357 nanotechnology 23, 25, 51, 98, 212, 269, 344, 353 National Health Service, UK 334–5 National Salvation Front, Romania 136 NATO 264–5 Naveh, Danny 76, 96 Nayaka people 75–6, 96 Nazism 98, 164–5, 181, 182, 247, 255–7, 262–3, 375, 376, 396 Ne Win, General 144 Neanderthals 49, 156, 261, 273, 356, 378 Nebuchadnezzar, King of Babylonia 172–3, 310 Nelson, Shawn 255 New York Times 309, 332–4, 347, 370 New Zealand: Animal Welfare Amendment Act, 2015 122 Newton, Isaac 27, 97–8, 143, 197 Nietzsche, Friedrich 234, 254, 268 non-organic beings 43, 45 Norenzayan, Ara 354–5 Novartis 330 nuclear weapons 15, 16, 17, 17, 131, 149, 163, 216, 265, 372 Nyerere, Julius 166 Oakland Athletics 321 Obama, President Barack 313, 375 obesity 5–6, 18, 54 OncoFinder 323 Ottoman Empire 197, 207 ‘Our Boys Didn’t Die in Vain’ syndrome 300–3, 301 Page, Larry 28 paradox of knowledge 55–8 Paris Agreement, 2015 216 Pathway Pharmaceuticals 323 Petsuchos 161–2 Pfungst, Oskar 129 pharmacists 317 pigs, domesticated 79–83, 82, 87–8, 90, 98, 99, 100, 101, 231 Pinker, Steven 305 Pius IX, Pope 270–1 Pixie Scientific 330 plague/infectious disease 1–2, 6–14 politics: automation of 338–41; biochemical pursuit of happiness and 41; liberalism and 226–7, 229, 232, 232, 234, 247–50, 247n, 252; life expectancy and 26–7, 29; revolution and 132–7; speed of change in 58 pollution 20, 176, 213–14, 215–16, 341–2 poverty 3–6, 19, 33, 55, 205–6, 250, 251, 262, 349 Presley, Elvis 159–60, 159 Problem of Other Minds 119–20, 126–7 Protestant Reformation 185–7, 198, 242–4, 242, 243 psychology: evolutionary 82–3; focus of research 353–6, 360–2; Freudian 117; humanism and 223–4, 251–2; positive 360–2 Putin, Vladimir 26, 375 pygmy chimpanzees (bonobos) 138–9 Quantified Self movement 331 quantum physics 103, 170, 182, 234 Qur’an 170, 174, 269, 270 rats, laboratory 38, 39, 101, 122–4, 123, 127–8, 286–7 Redelmeier, Donald 296 relativity, theory of 102, 103, 170 religion: animals and 75–8, 90–8, 173; animist 75–8, 91, 92, 96–7, 173; challenge to liberalism 268; Dataism 367–97 see also Dataism; defining 180–7; ethical judgments 195–7; evolution and see evolution; formula for knowledge 235–7; God, death of 67, 234, 261, 268; humanist ethic and 234–5; monotheist 101–2, 173; science, relationship with 187–95, 197–8; scriptures, belief in 172–4; spirituality and 184–7; theist religions 90–6, 98, 274 revolutions 57, 60, 132–7, 155, 263–4, 308, 310–11 Ritalin 39, 364 robo-rat 286–7 Roman Empire 98, 191, 192, 194, 240, 373 Romanian Revolution, 1989 133–7, 138 Romeo and Juliet (Shakespeare) 365–6 Rousseau, Jean-Jacques 223, 282, 305 Russian Revolution, 1917 132–3, 136 Rwanda 15 Saarinen, Sharon 53 Saladin 146, 147, 148, 150–1 Santino (chimpanzee) 125–7 Saraswati, Dayananda 270, 271, 273 Scientific Revolution 96–9, 197–8, 212, 236–7, 379 Scotland 4, 303–4, 303 Second World War, 1939–45 21, 34, 55, 115, 164, 253, 262–3, 292 self: animal self-consciousness 124–7; Dataism and 386–7, 392–3; evolutionary theory and 103–4; experiencing and narrating self 294–305, 337, 338–9, 343; free will and 222–3, 230, 247, 281–90, 304, 305, 306, 338; life sciences undermine liberal idea of 281–306, 328–9; monotheism and 173, 174; single authentic self, humanist idea of 226–7, 235–6, 251, 281–306, 328–41, 363–6, 390–1; socialism and self-reflection 251–2; soul and 285; techno-humanism and 363–6; technological challenge to liberal idea of 327–46, 363–6; transcranial stimulator and 289 Seligman, Martin 360 Senusret III 161, 162 September 11 attacks, New York, 2011 18, 374 Shavan, Shlomi 331 Shedet, Egypt 161–2 Silico Medicine 323 Silicon Valley 15, 24, 25, 268, 274, 351, 381 Sima Qian 173, 174 Singapore 32, 207 smallpox 8–9, 10, 11 Snayers, Pieter: Battle of White Mountain 242–4, 243, 246 Sobek 161–2, 163, 171, 178–9 socialist humanism/socialism 247–8, 250–2, 256, 259–60, 261–2, 263, 264, 265, 266–7, 271–4, 325, 351, 376 soul 29, 92, 101–6, 115–16, 128, 130, 132, 138, 146, 147, 148, 150, 160, 184–5, 186, 189, 195, 229, 272, 282, 283, 285, 291, 324, 325, 381 South Korea 33, 151, 264, 266, 294, 349 Soviet Union: communism and 206, 208, 370, 371–2; data processing and 370, 370, 371–2; disappearance/collapse of 132–3, 135, 136, 145, 145, 266; economy and 206, 208, 370, 370, 371–2; Second World War and 263 Spanish Flu 9–10, 11 Sperry, Professor Roger Wolcott 292 St Augustine 275, 276 Stalin, Joseph 26–7, 256, 391 stock exchange 105–10, 203, 210, 294, 313, 369–70, 371 Stone Age 33–4, 60, 74, 80, 131, 155, 156, 157, 163, 176, 261 subjective experience 34, 80, 82–3, 105–17, 143–4, 155, 179, 229, 237, 312, 388, 393 Sudan 270, 271, 273 suicide rates 2, 15, 33 Sumerians 156–8, 159, 162–3, 323 Survivor (TV reality show) 240 Swartz, Aaron 382–3; Guerilla Open Access Manifesto 383 Sylvester I, Pope 190–1 Syria 3, 19, 149, 171, 220, 275, 313 Taiping Rebellion, 1850–64 271 Talwar, Professor Sanjiv 286–7 techno-humanism: definition of 352–3; focus of psychological research and 353–9; human will and 363–6; upgrading of mind 359–66 technology: Dataism and see Dataism; inequality and future 346–50; liberal idea of individual challenged by 327–46; renders humans economically and militarily useless 307–27; techno-humanism and see techno-humanism Tekmira 203 terrorism 14, 18–19, 226, 288, 290, 311 Tesla 114, 322 Thatcher, Margaret 57, 372 Thiel, Peter 24–5 Third Man, The (movie) 253–4 Thirty Years War, 1618–48 242–3 Three Gorges Dam, 163, 188, 196 Thucydides 173, 174 Toyota 230, 294, 323 transcranial stimulators 44–5, 287–90, 362–3, 364 Tree of Knowledge, biblical 76–7, 77, 97, 98 tuberculosis 9, 19, 23, 24 Turing, Alan 120, 367 Turing Machine 367 Turing Test 120 23andMe 336 Twitter 47, 137, 313, 387 US Army 287–90, 362–3, 364 Uganda 192–3, 195 United States: Dataism and 374; energy usage and happiness levels in 34; evolution, suspicion of within 102; Kyoto protocol, 1997 and 215–16; liberalism, view of within 247n; nuclear weapons and 163; pursuit of happiness and 31; value of life in compared to Afghan life 100; Vietnam War and 264, 265; well-being levels 34 Universal Declaration of Human Rights 21, 24, 31 Urban II, Pope 227–8 Uruk 156–7 Valla, Lorenzo 192 Valle Giulia, Battle of, 1968 263 vampire bats 204–5 Vedas 170, 181, 270 Vietnam War, 1954–75 57, 244, 264, 265 virtual-reality worlds 326–7 VITAL 322–3 Voyager golden record 258–9 Waal, Frans de 140–1 Walter, Jean-Jacques: Gustav Adolph of Sweden at the Battle of Breitenfeld (1631) 242, 243, 244–5 war 1–3, 14–19; humanism and narratives of 241–6, 242, 245, 253–6 Warsaw Pact 264–5 Watson (artificial intelligence system) 315–17, 315, 330 Watson, John 88–9, 90 Waze 341–2 web of meaning 143–9 WEIRD (Western, educated, industrialised, rich and democratic) countries, psychology research focus on 354–5, 359, 360 West Africa: Ebola and 11, 13, 203 ‘What Is It Like to Be a Bat?’

Brotopia: Breaking Up the Boys' Club of Silicon Valley by Emily Chang

"Margaret Hamilton" Apollo, "Susan Fowler" uber, "World Economic Forum" Davos, 23andMe, 4chan, Ada Lovelace, affirmative action, Airbnb, Alan Greenspan, Andy Rubin, Apollo 11, Apple II, augmented reality, autism spectrum disorder, autonomous vehicles, barriers to entry, Benchmark Capital, Bernie Sanders, Big Tech, Burning Man, California gold rush, Chuck Templeton: OpenTable:, clean tech, company town, data science, David Brooks, deal flow, Donald Trump, Dr. Strangelove, driverless car, Elon Musk, emotional labour, equal pay for equal work, fail fast, Fairchild Semiconductor, fake news, Ferguson, Missouri, game design, gender pay gap, Google Glasses, Google X / Alphabet X, Grace Hopper, Hacker News, high net worth, Hyperloop, imposter syndrome, Jeff Bezos, job satisfaction, Khan Academy, Lyft, Marc Andreessen, Mark Zuckerberg, Mary Meeker, Maui Hawaii, Max Levchin, Menlo Park, meritocracy, meta-analysis, microservices, Parker Conrad, paypal mafia, Peter Thiel, post-work, pull request, reality distortion field, Richard Hendricks, ride hailing / ride sharing, rolodex, Salesforce, Saturday Night Live, shareholder value, Sheryl Sandberg, side project, Silicon Valley, Silicon Valley startup, Skype, Snapchat, Steve Jobs, Steve Jurvetson, Steve Wozniak, Steven Levy, subscription business, Susan Wojcicki, tech billionaire, tech bro, tech worker, TED Talk, Tim Cook: Apple, Travis Kalanick, uber lyft, women in the workforce, Zenefits

Schmidt’s New York apartment: Sam Biddle, “Google Boss Enjoys $15 Mil Manhattan Sex Penthouse,” Valleywag, July 25, 2013, http://valleywag.gawker.com/google-boss-enjoys-15-mil-manhattan-sex-penthouse-909299764. “the most daring CEO”: Ryan Chittum, “Fast Company’s Daring 23andMe Cover,” Columbia Journalism Review, Nov. 23, 2013, http://archives.cjr.org/the_audit/fast_companys_daring_23andme_c.php. Longtime chief legal counsel: Albergotti, “Google Reckoning with History of Interoffice Romance by Top Execs.” Executives, she tweeted: Shawn Paul Wood, “Google Engineer Accused of Sexual Harassment Allegedly Does Nothing,” Adweek, March 9, 2015, http://www.adweek.com/digital/google-engineer-accused-of-sexual-harassment-allegedly-does-nothing.

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To make matters more complicated, Rosenberg’s then-boyfriend, Hugo Barra, was a lead executive heading up Google’s Android division, who left at about the same time as the scandal broke in the press to run global operations at the Chinese smartphone maker Xiaomi. And to make it even more complicated, Brin was married to Susan Wojcicki’s sister Anne, a Silicon Valley force in her own right, heading up the genetic-testing company 23andMe. Fast Company once called her “the most daring CEO in America.” Other sexcapades involving lesser-known but still powerful men at Google became part of company lore but took years to end up in the media. Longtime chief legal counsel David Drummond had an extramarital affair with a paralegal in his departent, Jennifer Blakely, and the pair had a child together.

The 4-Hour Body: An Uncommon Guide to Rapid Fat-Loss, Incredible Sex, and Becoming Superhuman by Timothy Ferriss

23andMe, airport security, Albert Einstein, Black Swan, Buckminster Fuller, caloric restriction, caloric restriction, carbon footprint, cognitive dissonance, Columbine, confounding variable, correlation does not imply causation, Dean Kamen, game design, Gary Taubes, Gregor Mendel, index card, Kevin Kelly, knowledge economy, language acquisition, life extension, lifelogging, Mahatma Gandhi, messenger bag, microbiome, microdosing, p-value, Paradox of Choice, Parkinson's law, Paul Buchheit, placebo effect, Productivity paradox, publish or perish, radical life extension, Ralph Waldo Emerson, Ray Kurzweil, Recombinant DNA, Richard Feynman, selective serotonin reuptake inhibitor (SSRI), Silicon Valley, Silicon Valley startup, Skype, stem cell, Steve Jobs, sugar pill, survivorship bias, TED Talk, The future is already here, The Theory of the Leisure Class by Thorstein Veblen, Thorstein Veblen, Vilfredo Pareto, wage slave, William of Occam

—without realizing that food allergy testing is notoriously error-prone. If you get an alarming result, repeat the test. If you have the budget, consider using a different lab or, better still, sending two identical samples to the same lab under different names. I did the latter with several tests, including 23andMe, to ensure the results were consistent. 23andMe passed, but many others did not. Get a second opinion before doing anything drastic. I owe special thanks to Dr. Justin Mager for helping me navigate the world of testing. THE MENU Insurance will often cover the first one or two comprehensive tests you have performed, and I encourage you to speak with your doctor about this option.

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Arthur Jones Collection (www.fourhourbody.com/jones) This site, compiled by Brian Johnston, is a collection of the writing and photographs of the legendary Arthur Jones, including the original Nautilus Bulletins, “The Future of Exercise,” and unpublished works. End of Chapter Notes 8. I’ve since confirmed this finding with three separate genetic profiles through 23andMe (two tests with different names to ensure consistent results) and Navigenics. 9. I’ve since learned to worry less about cholesterol if HDL is high enough and triglycerides are low enough. 10. Compiled with a combination of the lowest and highest measurements from both locations. 11. To give my adrenal glands and adrenergic receptors a rest, I didn’t consume NO-Xplode on Sundays. 12.

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***ZRT at-home Vitamin D test kits (www.zrtlab.com/vitamindcouncil): $65–220 Determine your vitamin D levels before supplementing. The ZRT tests are saliva-based and reasonably accurate. Note that vitamin D is often included in the comprehensive bloodwork (in our example, “Chem 6”), and it is always included in the SpectraCell testing I recommend. Genetic insights (www.23andme.com and www.navigenics.com): $99–1,000 per test If you’d like to determine your genetic indicators for fast-twitch muscle fiber, caffeine metabolism, or ethnic make-up, these tests will offer answers. Berkeley Heart Labs or Advanced Cardio Lipid Panel: $120–260 If you adhere to the Lipid Hypothesis of cardiovascular disease (in essence, that cholesterol and fats cause it) these laboratories offer comprehensive lipid analyses, including tests that measure LDL and HDL particle size as a distribution of seven and five subclasses, respectively.

Eat People: And Other Unapologetic Rules for Game-Changing Entrepreneurs by Andy Kessler

23andMe, Abraham Maslow, Alan Greenspan, Andy Kessler, bank run, barriers to entry, Bear Stearns, behavioural economics, Berlin Wall, Bob Noyce, bread and circuses, British Empire, business cycle, business process, California gold rush, carbon credits, carbon footprint, Cass Sunstein, cloud computing, collateralized debt obligation, collective bargaining, commoditize, computer age, Cornelius Vanderbilt, creative destruction, disintermediation, Douglas Engelbart, Dutch auction, Eugene Fama: efficient market hypothesis, fiat currency, Firefox, Fractional reserve banking, George Gilder, Gordon Gekko, greed is good, income inequality, invisible hand, James Watt: steam engine, Jeff Bezos, job automation, Joseph Schumpeter, junk bonds, Kickstarter, knowledge economy, knowledge worker, Larry Ellison, libertarian paternalism, low skilled workers, Mark Zuckerberg, McMansion, Michael Milken, Money creation, Netflix Prize, packet switching, personalized medicine, pets.com, prediction markets, pre–internet, profit motive, race to the bottom, Richard Thaler, risk tolerance, risk-adjusted returns, Silicon Valley, six sigma, Skype, social graph, Steve Jobs, The Wealth of Nations by Adam Smith, transcontinental railway, transfer pricing, vertical integration, wealth creators, Yogi Berra

The biggest nearterm gain will probably be seen by networking researchers. Sage Bionetworks allows researchers around the world to contribute to and draw from an open database of clinical and molecular data so they can “build innovative new dynamic disease models.” But it’s not just for scientists; 23andMe analyzes your DNA and then compares it with others’ to identify your potential predisposition to various diseases. Lots of issues need to be worked out, not the least of which is, what does “your DNA suggests a 27 percent probability of contracting liver cancer” even mean? The Personal Genome Project, meanwhile, lets individuals upload their DNA sequencing for researchers to probe, privacy be damned.

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Stroud number StubHub Sustainability, and efficiency Sun Microsystems Sunstein, Cass Super Sloppers Supply and demand Taranto, James Taxation Teachers, public school, as Thieves Technology adapting to humans next big move, recognizing personalized recommendations to customers Telecosm (Gilder) Television content, over virtual pipe Telmex Thaler, Richard Thieves TiVo Town, Phil Toyota Prius Trade secrets, versus patents Trophy Generation Turner, Ted 23andMe Twitter Union workers, as Sponges United Auto Workers United States as horizontal enterprise Jetsons to Flintstones analogy Universities, and exceptionalism U.S. Steel Vanderbilt, Cornelius market entrepreneurship of Vardi, Yossi Veach, Eric VentureBeat Vertical integration Apple as example examples of media companies negative aspects of signs of situations for Soviet Union example Video games companies virtual pipe of next wave, recognizing through online gaming, virtual pipe of Virtual pipe of Apple control, profitability of creating, examples of economic model for relationship to media of social networking Vital Few Voice mail Voice recognition Wagner, Todd Walker brothers Wall Street commissions, lowering Slimers on Wal-Mart Walton, Sam Waste benefits of versus efficiency Watt, James Wealth and abundance versus scarcity comes from productivity.

The Ethical Algorithm: The Science of Socially Aware Algorithm Design by Michael Kearns, Aaron Roth

23andMe, affirmative action, algorithmic bias, algorithmic trading, Alignment Problem, Alvin Roth, backpropagation, Bayesian statistics, bitcoin, cloud computing, computer vision, crowdsourcing, data science, deep learning, DeepMind, Dr. Strangelove, Edward Snowden, Elon Musk, fake news, Filter Bubble, general-purpose programming language, Geoffrey Hinton, Google Chrome, ImageNet competition, Lyft, medical residency, Nash equilibrium, Netflix Prize, p-value, Pareto efficiency, performance metric, personalized medicine, pre–internet, profit motive, quantitative trading / quantitative finance, RAND corporation, recommendation engine, replication crisis, ride hailing / ride sharing, Robert Bork, Ronald Coase, self-driving car, short selling, sorting algorithm, sparse data, speech recognition, statistical model, Stephen Hawking, superintelligent machines, TED Talk, telemarketer, Turing machine, two-sided market, Vilfredo Pareto

Starting in the mid-2000s, people began to voluntarily upload their own DNA to public databases on the Internet, to learn more about their family histories. For example, in 2011, two volunteers started a website called GEDmatch, which hobbyists could use to upload DNA profiles that they had generated using commercial sites such as 23andMe. Users could search for partial matches, ostensibly to find their own distant relatives and link their family trees, which GEDmatch made available. But anyone else could also conduct such a search—and police still investigating the Golden State Killer uploaded a sample of his DNA, taken from a crime scene, in hopes of finding a match.

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See also gender data and bias sexual orientation data, 25–26, 51–52, 86–89 Shapley, Lloyd, 129–30 The Shining (King), 118, 120 Shmatikov, Vitaly, 25 Simmons, Joe, 157–58 simple algorithms, 174 simulated game play, 134–35 single nucleotide polymorphisms (SNPs), 30–31 singularity, 180 Smith, Adam, 36 smoking, 27–28, 34–36, 39, 51–54 Snowden, Edward, 47–48 social awareness, 16–17, 131 social welfare, 97, 113, 115 societal norms and values, 12, 15–18, 20–21, 86, 134, 169–70 socioeconomic groups, 57 software engineers, 48–49 sorting algorithms, 4–5 spurious correlations, 150, 159 stable equilibriums, 99–100, 128 stable matchings, 128–30 standoffs, 98 statistics and adaptive data analysis, 159 and aggregate data, 22–23, 30–31 and algorithmic violations of fairness and privacy, 96 Bayesian, 38–39, 173 and the Bonferroni correction, 149 criminal sentencing, 14–15 and differential privacy, 40, 44–45, 47–52, 167 and fairness issues, 193–94 flawed statistical reasoning, 140–41 and interpretability of model outputs, 171–72 and investing scams, 138–41 and medical research, 34 and online shopping algorithms, 117 and p-hacking, 144–45, 153–55, 157–59, 161, 164, 169–70 statistical modeling, 90 statistical parity, 69–74, 84 and US Census data, 195 and “word embedding” models, 57–58, 63–64 stock investing, 81, 137–41 strategy, 97–102 Strava, 50–51 subgroup protections, 88–89 subjectivity, 86, 172 subpoenas, 41, 45–46, 48 “superfood” research, 143–44 superintelligent AI, 179–81, 185, 187 supervised machine learning, 63–64, 69–70, 183 supply and demand, 94–97 Supreme Court nomination hearings, 24 survey responses, 40–45 Sweeney, Latanya, 23 synthetic images, 132–35 target populations, 172–73 TD-Gammon program, 132 technological advances, 100–101, 103 TED Talks, 141–42 telemarketing calls, 38 temporal difference, 132 Tesauro, Gerry, 132 test preparation courses, 74–75 theoretical computer science, 11–13, 36 threshold rule, 75 Title VII, 15 tobacco research, 34–36 torturing data, 156–59 traffic and navigation problems, 19–20, 101–11, 113–15, 179 training data, 61–62 transparency, 125–26, 170–71 trust, 45–47, 170–71, 194–95 “truthfulness” in game theory, 114 “tunable” parameters, 37–39, 125–26, 171 Turing, Alan, 11–12, 180 Turing Award, 133 Turing machine, 11 23andMe, 54–55 2020 Census, 49, 195 Twitter Predictor Game, 52–53 two-route navigation problem, 107 two-sided markets, 127 2001: A Space Odyssey (film), 184 typing, 118 underspecified problems, 183 unintended consequences, 6–8, 16–17, 184–85, 188 unique data points, 26–27 unsupervised learning, 63–64 upstream effects, 194 US Census Bureau, 49 US Constitution, 49 US Equal Employment Opportunity Commission, 86–87 user identifiers, 24 user modeling, 121 user ratings, 118–21 US military deployments, 50–51 US State Department, 15 validation sets, 162–63 value alignment problems, 184 values.

The AI-First Company by Ash Fontana

23andMe, Amazon Mechanical Turk, Amazon Web Services, autonomous vehicles, barriers to entry, blockchain, business intelligence, business process, business process outsourcing, call centre, Charles Babbage, chief data officer, Clayton Christensen, cloud computing, combinatorial explosion, computer vision, crowdsourcing, data acquisition, data science, deep learning, DevOps, en.wikipedia.org, Geoffrey Hinton, independent contractor, industrial robot, inventory management, John Conway, knowledge economy, Kubernetes, Lean Startup, machine readable, minimum viable product, natural language processing, Network effects, optical character recognition, Pareto efficiency, performance metric, price discrimination, recommendation engine, Ronald Coase, Salesforce, single source of truth, software as a service, source of truth, speech recognition, the scientific method, transaction costs, vertical integration, yield management

The e-commerce behemoth collects data about what customers want based on what they buy and how they browse, then uses this data to make better recommendations. Amazon has been doing this for so long that the company can make better recommendations than other shopping websites. Harvesting data from consumers for one reason then selling it to corporations for a different reason is common and can be the basis of a big business. 23andMe did this with genomics, BillGuard with purchasing data, Credit Karma with credit scoring, Onavo with app performance, and Dark Sky with location data. However, building a durable business this way can be difficult. First, the “trick” that gets users to submit their data may not last; another company could utilize the same trick or come up with a different trick to get the same data while charging less.

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., 6 teams in proof of concept phase, 60 see also AI-First teams telecommunications industry, 250–51 telephones mobile, 113 iPhone, 253 networks, 23–25 templates, 171 temporal leverage, 3 threshold logic unit (TLU), 5 ticker data, 120–21 token-based incentives, 109–10 tools, 2–3, 93–97 training data, 199 transactional pricing, 237, 280 transaction costs, 243 transfer learning, 147–48 true and false, 204–6 Turing, Alan, 5 23andMe, 112 Twilio, 87 uncertainty sampling, 96 unit analysis, 213–14 United Nations, 250 unsupervised machine learning, 53, 147–48, 281 Upwork, 99 usability, 255–56 usage-based pricing, 237–38, 281 usage metrics, 209 user interface (UI), 89, 159, 281 utility of network effects, 42 of products, 35–36 validation data, 199 value chain, 18–19, 281 value proposition, 59 values, missing, 178 variable importance plots, 53, 281 variance reduction, 96 Veeva Systems, 212 vendors, 73, 161 data, prices charged by, 73 independent software, 161, 248, 276 lock-in and, 247–48 venture capital, 230 veracity of data, 75 versioning, 169–70, 281 vertical integration, 226–37, 239, 244, 252, 281 vertical products, 210–12, 282 VMWare, 248 waterfall charts, 282 Web crawlers, 115–16, 282 weights, 150, 281 workflow applications, 84–86, 253, 259, 282 workflow-first versus integrations-first companies, 88–89 yield management systems, 42 Zapier, 87 Zendesk, 233 zettabyte, 8, 282 Zetta Venture Partners, 8–9 A B C D E F G H I J K L M N O P Q R S T U V W X Y Z ABOUT THE AUTHOR Ash Fontana became one of the most recognized startup investors in the world after launching online investing at AngelList.

Terms of Service: Social Media and the Price of Constant Connection by Jacob Silverman

"World Economic Forum" Davos, 23andMe, 4chan, A Declaration of the Independence of Cyberspace, Aaron Swartz, Airbnb, airport security, Amazon Mechanical Turk, augmented reality, basic income, Big Tech, Brian Krebs, California gold rush, Californian Ideology, call centre, cloud computing, cognitive dissonance, commoditize, company town, context collapse, correlation does not imply causation, Credit Default Swap, crowdsourcing, data science, deep learning, digital capitalism, disinformation, don't be evil, driverless car, drone strike, Edward Snowden, Evgeny Morozov, fake it until you make it, feminist movement, Filter Bubble, Firefox, Flash crash, game design, global village, Google Chrome, Google Glasses, Higgs boson, hive mind, Ian Bogost, income inequality, independent contractor, informal economy, information retrieval, Internet of things, Jacob Silverman, Jaron Lanier, jimmy wales, John Perry Barlow, Kevin Kelly, Kevin Roose, Kickstarter, knowledge economy, knowledge worker, Larry Ellison, late capitalism, Laura Poitras, license plate recognition, life extension, lifelogging, lock screen, Lyft, machine readable, Mark Zuckerberg, Mars Rover, Marshall McLuhan, mass incarceration, meta-analysis, Minecraft, move fast and break things, national security letter, Network effects, new economy, Nicholas Carr, Occupy movement, off-the-grid, optical character recognition, payday loans, Peter Thiel, planned obsolescence, postindustrial economy, prediction markets, pre–internet, price discrimination, price stability, profit motive, quantitative hedge fund, race to the bottom, Ray Kurzweil, real-name policy, recommendation engine, rent control, rent stabilization, RFID, ride hailing / ride sharing, Salesforce, self-driving car, sentiment analysis, shareholder value, sharing economy, Sheryl Sandberg, Silicon Valley, Silicon Valley ideology, Snapchat, social bookmarking, social graph, social intelligence, social web, sorting algorithm, Steve Ballmer, Steve Jobs, Steven Levy, systems thinking, TaskRabbit, technological determinism, technological solutionism, technoutopianism, TED Talk, telemarketer, transportation-network company, Travis Kalanick, Turing test, Uber and Lyft, Uber for X, uber lyft, universal basic income, unpaid internship, women in the workforce, Y Combinator, yottabyte, you are the product, Zipcar

They also know far more about us than their predecessors ever did, while making us complicit in the process by encouraging checkins, structuring data, location services, and other data production/sharing that is, we are told, designed to improve a service. A growing crop of biometric tools—sleep measurement apps, fitness monitors, the thumbprint reader introduced on Apple’s iPhone 5S, the gene-sequencing service 23andme.com—means that corporations are set to know us at the physical, even genomic level. (“Your DNA will be your data,” says one particularly creepy HSBC ad spotted at JFK airport.) They may even anticipate health problems before we realize we have them. Read your fitness tracker’s terms of service agreement.

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Perhaps we’d join Miinome, “the first member-controlled, portable human genomics marketplace,” where you can sell your genomic information and receive deals from retailers based on that same information. (Again, I think back to HSBC’s “Your DNA will be your data” ad, this time recognizing it not as an attempt at imparting a vaguely inspirational, futuristic message, but as news of a world already here.) That beats working with 23andMe, right? That company already sells your genetic profile to third parties—and that’s just in the course of the (controversial, non-FDA-compliant) testing they provide, for which they also charge you. Tellingly, a version of this proposal for a data marketplace appears in the World Economic Forum (WEF) paper that announced data as the new oil.

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See also targeting individuals traffic models, 140 transparency, 310 Transportation Security Administration, 215 trending overview, 82–84 and analytics team for Bleacher Report, 127 business incentives behind, 84–85 buying Twitter followers, 85–87, 88–89 fallacy of, 111 fractional workers sorting through queries on Twitter, 229–30 identifying trends, 88–91 and journalists, 97, 101 newsworthiness vs., 124–25 value of supposed trend, 84 tribalism, 63 trolls, 252 trust economy, 282 trust, management of, 234 Tseng, Erick, 324, 324n Tumblr social media site, 27–30, 59, 170–72, 257 Turkle, Sherry, 156 Turow, Joseph, 293, 308, 309, 326–27 23andMe, 328 twentysomethings and photographs, 58 Twitch app for Androids, 260 Twitter AP account hack, 39 bot posts, 38 Connect tab, 351 fractional workers contracted by, 228, 244 investments and sentiment analysis, 37 metrics, 87, 96–97, 147 newscasters reading from tweets, 110 reasons for success, 16 response statistics, 52 secondary orality, 63 sponsored tweets, 174, 200n as triumph of humanity, 6 “Tweets of Privilege,” 170–72 Weird Twitter, 352–53 YesYoureRacist account, 172–73 See also followers; trending Twitter users any user messaging any other user, 360 Bieber, 147–48 celebrity death hoaxes, 348–49 deleting tweets with insufficient responses, 53 devaluing your data, 351–53 Glitchr, 353 and influence rating, 196 lurkers, 49 New York Comic Con tweets posted by convention promoters, 34 reciprocity for retweets, 54–55 recognizing when you’re done, 258 surfacing examples of abuse and injustice, 170 thinking in tweets, 341 user rights, 311 Twopcharts, 87 typeface, OCR-proof, 358 Uber customer rating system, 187–88 driver rating system, 187, 191 drivers for, 241–42, 243, 331 long-term plan, 242 money trail, 236 and New York City, 237 and smartphones, 235 surge pricing, 241 unemployment, 220–26, 331–32.

Capitalism Without Capital: The Rise of the Intangible Economy by Jonathan Haskel, Stian Westlake

23andMe, activist fund / activist shareholder / activist investor, Airbnb, Alan Greenspan, Albert Einstein, Alvin Toffler, Andrei Shleifer, bank run, banking crisis, Bernie Sanders, Big Tech, book value, Brexit referendum, business climate, business process, buy and hold, Capital in the Twenty-First Century by Thomas Piketty, carbon credits, cloud computing, cognitive bias, computer age, congestion pricing, corporate governance, corporate raider, correlation does not imply causation, creative destruction, dark matter, Diane Coyle, Donald Trump, Douglas Engelbart, Douglas Engelbart, driverless car, Edward Glaeser, Elon Musk, endogenous growth, Erik Brynjolfsson, everywhere but in the productivity statistics, Fellow of the Royal Society, financial engineering, financial innovation, full employment, fundamental attribution error, future of work, gentrification, gigafactory, Gini coefficient, Hernando de Soto, hiring and firing, income inequality, index card, indoor plumbing, intangible asset, Internet of things, Jane Jacobs, Jaron Lanier, Jeremy Corbyn, job automation, Kanban, Kenneth Arrow, Kickstarter, knowledge economy, knowledge worker, laissez-faire capitalism, liquidity trap, low interest rates, low skilled workers, Marc Andreessen, Mother of all demos, Network effects, new economy, Ocado, open economy, patent troll, paypal mafia, Peter Thiel, pets.com, place-making, post-industrial society, private spaceflight, Productivity paradox, quantitative hedge fund, rent-seeking, revision control, Richard Florida, ride hailing / ride sharing, Robert Gordon, Robert Solow, Ronald Coase, Sand Hill Road, Second Machine Age, secular stagnation, self-driving car, shareholder value, sharing economy, Silicon Valley, six sigma, Skype, software patent, sovereign wealth fund, spinning jenny, Steve Jobs, sunk-cost fallacy, survivorship bias, tacit knowledge, tech billionaire, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, Tim Cook: Apple, total factor productivity, TSMC, Tyler Cowen, Tyler Cowen: Great Stagnation, urban planning, Vanguard fund, walkable city, X Prize, zero-sum game

As is often the case with new technologies, the future may already be here among us. Software developers have been using online tools like Slack and GitHub to collaborate for years now. There are any number of firms experimenting with new ways of Internet-enabled collaboration, in fields from healthcare research (such as Patientslikeme or 23andMe) to brokering intellectual property among companies (such as Nathan Myhrvold’s Intellectual Ventures) to data analytics (such as Kaggle, recently acquired by Google). It is easy to laugh when technology advocates make predictions that don’t come to pass. Where is the paperless office? Where is the Internet of Things?

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., 131 rules and norms, 211–14 Sadun, Rafaella, 53, 82 Salter, Ammon, 197 Sampson, Rachelle, 168 Samsung, 73, 112 Sanders, Bernie, 223 Santa Fe Institute, 80 scalability, 9–10, 58, 60, 87, 101–2; definition of, 246n2; importance of, 67–68; income inequality and, 133–34; and increased investment, 110; and intangibles, 65–67; secular stagnation and, 103–5 Schreyer, Paul, 40 Schwarzenegger, Arnold, 16 Science: The Endless Frontier (Bush), 232 Second Machine Age, 30 secular stagnation, 91, 116; explanation for, 101–16; and intangibles investment, 102–3; profits and productivity differences and, 103–7; relationship of scalability and spillovers to, 109–16; symptoms of, 92–96 Shankar, Ravi, 61 Shi, Yuan, 168 Shih, Willy, 85 Shinoda, Yukio, 42 short-termism, 161, 168–69 Sichel, Dan, 4, 5, 39, 42, 43, 45 Siemens, 60–61, 204 single-factor productivity, 98–101 Six Sigma, 51 Skype, 217 Slack, 152, 217 smartphones, 72–73, 81 Smil, Vaclav, 146 Smith, Adam, 36, 188 social capital, 156, 236 soft infrastructure, 156 solar energy, 85 Solow, Robert, 39, 125 Song, Jae, 129, 131, 135 South Wales Institution of Engineers, 83 speculation, 249n1 spending, 46–47, 54; on assets, 20; rent-seeking, 113 Spenser, Percy, 80 spillovers, 9, 58, 61, 87, 102; contestedness and, 87; importance of, 77–79; and intangibles, 72–77, 109–16; Jacobs, 138; Marshall-Arrow-Romer, 62, 138; physical infrastructure and, 147–51; secular stagnation and, 103–4; slowing TFP growth and, 107–9; venture capital and, 178 Spotify, 18 Stack Overflow, 29 Stansted Airport, 1–2, 3–4 Starbucks, 34, 52, 65, 140, 183, 195, 197; scalability of, 67 start-up ecosystems, 222 Statute of Anne (1709), 76 stock markets, 167–68, 205–6; IPOs and, 171–72 stock of intangible assets, 56–57 Summers, Larry, 93 sunkenness, 8–9, 58, 60, 87, 246n5; as characteristic of intangibles, 68–70; importance of, 70–72; venture capital and, 175–76 sustained advantage, 250n2 Sutton, John, 67 symbolic analysis, 132–34 synergies, 10, 58, 61, 87–88, 213; and intangible assets, 80–83, 83–86; among investments, 110; maximizing the benefits of, 214–18; physical infrastructure and, 147–51; venture capital and, 176 System of National Accounts, 20, 43, 51 systems innovation, 198 tacit knowledge, 65 tangible investments, differences between intangible and, 7–10, 58 taxes, 139–40, 235; and financing, 166, 219 technology: and cost of intangible investment, 28; inequality as result of improvements in, 123–24, 126–27; and productivity of intangibles, 28–30; and spillovers, 151–52 Tesla Motors, 24, 111, 209 Thatcher, Margaret, 127 Theory of Moral Sentiments, The (Smith), 188 Thiel, Peter, 78, 175, 184–85, 187, 223 3M, 194 Toffler, Alvin, 4 Tonogi, Konomi, 42 total factor productivity (TFP), 96, 98, 102; poor performance of, 109–9, 114 Toyota, 29, 51 trade and inequality, 124 trademarks, 76 training and education, 51–52, 170, 228–30 Trajtenberg, Manuel, 106 Trump, Donald, 122, 141–42, 143 trust, 156 23andMe, 152 Twitter, 185, 187 Uber, 24, 28, 51; building of driver network by, 112–13; contestedness and, 115; legal travails of, 187; scalability of, 67, 101–2, 105; and synergies, 82; venture capital and, 174, 175 uncertainty, 87 Ure, Andrew, 126 Ur-Nammu, 75 US Federal Reserve, 4, 40, 41, 42, 165 US Food and Drug Administration, 154 Van Reenen, John, 82, 136, 173, 195 venture capital (VC) funding, 154–55, 161, 166, 174–75; problems with, 177–79; and intangibles, 175–77 Vlachos, Jonas, 131 Volcker, Paul, 165 von Mises, Ludwig, 38 von Wachter, Till, 129 Wallis, Gavin, 42, 223–24 Walmart, 81, 187 Warsh, David, 62 Wasmer, Etienne, 128 Watt, James, 78 wealth, 119–20, 121; housing and, 122, 128–29, 136–39; inequality of, 139–40; intangibles’ effects on, 129–40 Wealth of Nations, The (Smith), 36 Weightless World, The (Coyle), 4 Weitzman, Martin L., 195 Welch, Jack, 184 Whalley, Alexander, 224 “What Is the U.S.

The Future of the Brain: Essays by the World's Leading Neuroscientists by Gary Marcus, Jeremy Freeman

23andMe, Albert Einstein, backpropagation, bioinformatics, bitcoin, brain emulation, cloud computing, complexity theory, computer age, computer vision, conceptual framework, correlation does not imply causation, crowdsourcing, dark matter, data acquisition, data science, deep learning, Drosophila, epigenetics, Geoffrey Hinton, global pandemic, Google Glasses, ITER tokamak, iterative process, language acquisition, linked data, mouse model, optical character recognition, pattern recognition, personalized medicine, phenotype, race to the bottom, Richard Feynman, Ronald Reagan, semantic web, speech recognition, stem cell, Steven Pinker, supply-chain management, synthetic biology, tacit knowledge, traumatic brain injury, Turing machine, twin studies, web application

Consider a company formed with the promise of offering customers interesting information about their thoughts and/or predictive information about brain diseases they might be at risk of acquiring. Many such companies, some more legitimate than others, are operating now in the sphere of genomics. Some are huge and have proven profitable, like deCODE and 23andMe. Others are small and often make claims that are on the fringes of genomic science. Building on preliminary and incomplete information coming out of the brain mapping projects and related research, we can predict with certainty that new “brain diagnostic,” “truth assessment,” and “brain detective companies” will begin to proliferate on the web and elsewhere.

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., 5 transcranial magnetic stimulation (TMS), 228 transcriptome, 48 transducer, 246, 250 transistor, 82, 84, 85f, 86–88, 135, 177, 181, 183, 210, 221, 245, 250 traumatic brain injury, 194, 266 trilevel hypothesis: brain, 84–85 Tsuchiya, Nao, 168, 169 tuberculosis, 171 tuberous sclerosis, 241 tumors, 266 Turing machine, 26 23andMe, 198 Twitter, 103 two-photon imaging: mouse cortex, 107 two-photon microscopy, 32 two-photon tomography, 34 ulcerative colitis, 234 ultrasonic frequencies, 246 ultrasonic waves, 249 ultrasound, 250 Universidad Politécnica de Madrid, 116 University College London, 122, 177 University of California–San Diego, 177 University of Edinburgh, 115 University of Oslo, 115, 116 US BRAIN Initiative, 113, 124 US Human Connectome Project, 113 Vallortigara, Giorgio, 207 Vandenbroucke, Annelinde, 166 Van Essen, David, 12 variable binding: brain, 213–14; language, 212 Venter, Craig, 256 Vesalius, Andreas, 3, 4f vestibular system, 22 virtual brains: building, 97–99 virtual reality: whole brain neuroimaging and, 17–24 vision: restoration, 227, 230 Vision (Marr), 181 visual processing: stimuli, 163 visual responses: brute-force data collection, 105 visual-spatial extinction, 163–64 visual system: primates, 104–5 visual thalamus, 264 Vogt, Karl, 91 Vogt, Marthe, 4 von Economo, Constantin, 4 von Neumann, John, 208, 212–13 V2 neurons: hypothesis, 105–6 Waddington, Conrad, 189 Watson, James, 7, 46 Waxholm Space, 115 Werbos, Paul, 41 White, John, 12 whole-brain neuroimaging, 20–21, 17–24 whole-brain neuroscience: behavior as brain output, 121–22; building the brain, 118–19; ethics, 123; global collaboration, 123–24; global effort to understand brain, 124; modeling brain disorders and diseases, 122; unifying brain models, 120–21; validity of model, 119–20 whole-brain simulation: creating to understand, 111–13; neuroinformatics for computing, 113–15; next generation brain atlases, 115–17; ongoing debate, 267–68; predictive neuroscience, 117–18.

The Human Age: The World Shaped by Us by Diane Ackerman

23andMe, 3D printing, additive manufacturing, airport security, Albert Einstein, Anthropocene, augmented reality, back-to-the-land, carbon footprint, clean water, climate change refugee, dark matter, dematerialisation, digital divide, double helix, Drosophila, epigenetics, Google Earth, Google Glasses, haute cuisine, Higgs boson, hindcast, Internet of things, Lewis Mumford, Loebner Prize, Louis Pasteur, Masdar, mass immigration, Medieval Warm Period, megacity, microbiome, mirror neurons, Neil Armstrong, Nick Bostrom, nuclear winter, ocean acidification, personalized medicine, phenotype, Ray Kurzweil, refrigerator car, rewilding, Search for Extraterrestrial Intelligence, SETI@home, skunkworks, Skype, space junk, stem cell, Stewart Brand, synthetic biology, TED Talk, the High Line, theory of mind, urban planning, urban renewal, We are as Gods, Whole Earth Catalog

As a daily jogger, she’d be inhaling a lot more pollution than most people, and she figures her genes have already been restyled just by growing up among the master trailblazers of the Human Age. But she is tempted to read the book of her genes, and discover more about her lineage and genetic biases. For a truly personal profile, all our redhead would need is a vial of her blood and between $100 and $1,000. Such companies as Navigenics or 23andMe will gladly provide a glimpse of her future, a tale still being written but legible enough for genetic fortune-telling. She may have a slightly higher than normal risk of macular degeneration, a tendency to go bald, a gene variant that’s a well-known cause of blood cancer, maybe a different variant associated with Alzheimer’s, the family bane.

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., 87 Stanley Park, 78 starlings, 153, 165–66 Star Trek, 232, 253, 260 Statue of Liberty, 59 steam engine, 34 Steel Pier, 47 stem cells, 13, 150 Stockholm, 96–97 Stoermer, Eugene, 313 stomata, 91 Stony Creek harbor, 56–57, 66–67 storks, 124 Strauss, Richard, 269 suburban sprawl, 116 succulents, 83 sugar, 239 Suharto, 313 sulfur, 99 Summit, Scott, 236–37 sustainability, popularity of, 108 Sustainability Revolution, The (Edwards), 88 Svalbard Global Seed Vault, 154–55 Svensson, Tore, 101 Sweden, 96–97, 98–101, 106, 132 Swiss chard, 89, 90 Switzerland, 78, 132 swordfish, 65 sycamores, 111, 113 SyNAPSE, 256, 318 Taft, William Howard, 58 Tahiti, 159 Taiwan, 83 Taliban, 146 Tasmanian devils, 151, 164 taste, 211–12 Taylor, Robert, 89 technical nutrients, 87 technology, 10, 13–14 nature and, 188–200 Technology University, 104 Teitiota, Ioane, 49 Tel Aviv University, 293 telekenesis, 203 telephones, 171 telescopes, 171 televisions, 87, 191 temperate zones, 80 Tennessee, 46 termites, 92–93 Texas, 41 texting, 190 by plants, 205–7 Thailand, 79, 180 Thames Barrier, 50–51 theory of mind, 216–17, 218–19 Thimble Islands, 58 Thimble Island Salts, 62 “Thousand Dreams of Stellavista, The” (Ballard), 231 3D printing, 232–39, 244 Three Gorges Dam, 101 Thumb, Tom, 58 Thus Spake Zarathustra, 269–70 thyme, 90 Tiananmen Square, 271 tiger mosquitos, 132 time-rock, 32–33 titanium dioxide, 181 toads, 125 Tohoku, 46 Tokyo, 78 tomatoes, 89 Tom Jones (film), 294 Tonga, 158 tools, 171 human use of, 7, 9 orangutan use of, 5 tornadoes, 41 Toronto, Canada, 78 touch, 178 “Town Mouse and the Country Mouse, The” (Aesop), 115 Toxoplasma gondii, 296–99 trains, 102 transparent aluminum, 34 tree lizards, 80 trees, 83 trilobites, 29–30 trumpeter swans, 135 tube worms, 37–38 TU Delft, 104, 105 tuna, 65 Tushi, 272 Tuvalu, 48–49 23andMe, 271 twins, 282 Twitter, 317 2001: A Space Odyssey (film), 269–70 Tybee Island Ocean Rescue, 65 typewriter, 191 typhoons, 46 Uganda, 72 United Kingdom, 83, 298 cities in, 72 United Nations Conference on the Human Environment, 99 United Nations Panel on Climate Change, 41–42 United States, 83 urban beekeeping, 88 urban eyes, 192 urbanization, 154 U.S.

Big Data and the Welfare State: How the Information Revolution Threatens Social Solidarity by Torben Iversen, Philipp Rehm

23andMe, Affordable Care Act / Obamacare, algorithmic bias, barriers to entry, Big Tech, business cycle, centre right, collective bargaining, COVID-19, crony capitalism, data science, DeepMind, deindustrialization, full employment, George Akerlof, income inequality, information asymmetry, invisible hand, knowledge economy, land reform, lockdown, loss aversion, low interest rates, low skilled workers, microbiome, moral hazard, mortgage debt, Network effects, new economy, obamacare, personalized medicine, Ponzi scheme, price discrimination, principal–agent problem, profit maximization, Robert Gordon, speech recognition, subprime mortgage crisis, tail risk, The Market for Lemons, The Rise and Fall of American Growth, union organizing, vertical integration, working-age population

The prototype version developed in 2001 cost about US$300 million, but since then the price of sequencing has dropped to about US$1,000 in 2014, to less than US$200 in 2018, and it continues to fall. In fact, according to the National Human Genome Research Institute, the cost of sequencing the human genome has been falling much faster than implied by Moore’s Law.5 If a complete sequencing of the gene is not required, a company such as 23andMe can provide a pretty comprehensive genotyping of individuals for less than US$200,6 though the accuracy of consumer genomics products still leaves much to be desired. Gene-based diagnostics and treatment are in their infancy but progressing fast. The number of available personalized gene-based diagnostics and treatments approved by the Food and Drug Administration (FDA) in the USA rose from 13 in 2006 to 113 in 2014 (Personalized Medicine Coalition 2016), and it continued to climb sharply, reaching 184 in 2019.

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This is because accurate and timely diagnosis is a necessary condition for effective treatment and therefore for a lower PYLL.20 For example, hereditary amyloidosis is a condition that is caused by an inherited genetic mutation, which can be identified through DNA testing – even with an affordable home testing kit like 23andme – long before symptoms arise. Once symptoms appear, there are blood and tissue tests that can pinpoint the exact form of the disease, which in turn decides the treatment. Most who are diagnosed with hereditary amyloidosis eventually die from heart or kidney failure, but early detection and treatment – ranging from a strict diet to drugs and even liver transplants – create a wide PYLL range.

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“Mortgage Credit: Denmark’s Financial Capacity Building Regime.” New Political Economy 24(6): 833–50. Young, Professor H. P. 1985. “Monotonic Solutions of Cooperative Games.” International Journal of Game Theory 14(2): 65–72. https://doi.org/10.1017/9781009151405.008 Published online by Cambridge University Press Index 23andMe, 62 401(k) plans, 33, 64 actuarial science: fair premiums and, 2, 17, 68, 72, 89, 99–100, 190–191; historical perspective on, 45, 48–49, 65, 68; labor markets and, 160, 163n2, 177, 179, 184; prices and, 2; private markets and, 72, 81, 83, 89, 99–100; sound principles of, 10; tables for, 45, 49, 65; trackers and, 3 adverse selection: Akerlof on, 6; credit markets and, 112; gatekeeping and, 193; historical perspective on, 13, 45–50, 54, 65, 67; life expectancy and, 45; opting out and, 30, 54, 199; partisanship and, 37; pooled equilibrium and, 40–42; private information and, 40–42; private markets and, 72, 82n17, 83, 88; regulation and, 37–38; risk and, 1–2, 4, 6, 13, 30, 34, 45– 46, 49–50, 54, 65, 67, 72, 82, 112, 199, 202; theoretical model and, 30; time inconsistency and, 30, 34 Affordable Care Act (ACA), 11, 50n2, 60– 61, 63, 91, 94, 97 Ahlquist, John S., 109 AIA Australia, 79–80 AIDS, 86 Akerlof, George A., 6, 12, 19, 23–25, 27, 29, 190, 196 algorithms, 10, 12, 81, 93, 116n7, 119, 202 “Alliance for Sweden” campaign, 184 Alphabet, 5, 62 Amazon, 5, 62 American National Election Survey (ANES), 97–99 Ansell, Ben W., 109 Apple, 5, 62, 79 Arndt, Christoph, 182–183 artificial intelligence (AI), 5, 27, 62, 81–82, 202 Australia, 80, 90, 102, 107 Austria, 80, 90, 102, 107, 147 autocorrelation, 87 automobiles, 3 bad state, 20–21, 25n9, 40, 41, 112n5, 114, 142n27, 143–145, 190 bankruptcy, 31, 33, 46, 74, 96 banks: default and, 116, 132, 197; Fannie Mae and, 65, 109, 116–117, 121; financial crises and, 14, 61, 65, 116n7; Freddie Mac and, 65, 109, 116–117, 119–130, 140n25, 197; governmentsponsored enterprises (GSEs) and, 116– 121; loans and, 65, 105, 116, 131–132, 202; mortgages and, 131 (see also mortgages); small-town, 105 Barr, Nicholas, 12, 19, 24–25 Bayesianism, 15n1, 26, 56, 113, 143, 160, 164 Besley, Timothy, 93 Beveridge model, 53 Big Data: consequences of, 5; differential risk pools and, 63; financialization and, 138; informed patients and, 22; poor people and, 138; private markets and, 13, 219 https://doi.org/10.1017/9781009151405.009 Published online by Cambridge University Press 220 Index 63, 191; uncertainty reduction by, 13; utility and, 119; variety of available data, 108 Big Tech, 81, 201 Bildt government, 11, 177 Bismarckian system, 52–53, 58, 67, 191, 199–201 Blue Cross Blue Shield, 1, 49–50, 60 Boadway, Robin, 19 Bradley, David, 188 budget constraints, 20, 36n20, 42–43 burial insurance, 47–48 Busemeyer, Marius R., 39–40 Bush, George W., 17 Calico, 62 Canada, 90, 102, 107 CAT scans, 1 Clareto, 77–78 Clinton, Bill, 116 Code on Genetics, 93 coercion, 15, 25 collective bargaining, 64, 159, 195 commercial banks, 116–117, 131n14 commercial insurance: customer exclusions and, 193; digitalization and, 76; mutual aid societies (MASs) and, 45–50, 54–55, 67; unemployment insurance funds (UIFs) and, 66 Comparative Political Data Set, 102 Comparative Study of Electoral Systems (CSES), 176 COVID-19 pandemic, 61, 74, 77, 86n20, 100, 189 credible information, 28, 38, 39 credit guarantee schemes (CGSs), 115 credit markets: access to, 105–106; adverse selection and, 112; banks and, 105 (see also banks); collective bargaining and, 64, 159, 193; default and, 108–120, 128, 131–136, 141–146, 196–197; democracy and, 105, 117; discretionary income and, 100, 105, 108–115, 118, 138, 140, 142, 196; education and, 7, 33, 110, 115, 138, 141; empirical applications and, 196– 198; employment and, 108, 133–135; FICO scores and, 121–130, 149, 151– 158; flat-rate benefits and, 37, 114–115, 132, 144–146; Germany and, 107, 131, 135n23, 147; Gini coefficient and, 121– 127, 129, 138; government-sponsored enterprises (GSEs) and, 116–121; historical perspective on, 64–65; homeownership and, 108, 116, 131–140; inequality and, 106–115, 118–131, 138, 140, 144, 196–198; information and, 64– 65, 112–113; interest rates and, 105, 108, 111–132, 138–144, 152, 156; liquidity and, 109; loans and, 118–119 (see also loans); middle class and, 106; model for, 110–117, 141–144; mortgages and, 131 (see also mortgages); partisanship and, 118; pensions and, 64–65, 114, 131n14, 135n20, 141; Placebo outcomes and, 126–127, 146, 156–157; poor people and, 115, 133–140, 196; poverty and, 115; redistribution and, 109, 115, 124, 128, 144; reform and, 116–117, 120, 131– 137, 140; regression analysis and, 125– 126, 127, 130, 146, 147–158; regulation and, 14, 109–111, 115–131, 138, 140; rich people and, 133–137, 140, 196; risk and, 105, 108–120, 128–146; savings and loans (S&Ls), 116–117; segmentation and, 40, 159, 192; Single Family LoanLevel Dataset and, 121; subsidies and, 109, 116, 118, 131n14, 138, 139, 144; taxes and, 114–115, 139, 144; transfers and, 109, 114–115, 144; unemployment and, 108–109, 131–138; United States and, 106–107, 109, 117, 121, 124, 131, 139–140; wealth and, 108, 110, 111n2, 133, 140; welfare and, 105, 108–115, 131–138, 140 credit reports, 76 crime, 21n4 CT scans, 27, 83 deductibles, 17, 50, 195 DeepMind, 62 default: credit markets and, 108–120, 128, 131–136, 141–146, 196–197; flat-rate benefits and, 144–146; historical perspective on, 63; income relationship and, 146; information and, 7; private markets and, 80; theoretical model and, 17 democracy: asymmetric information and, 22–25; credit markets and, 105, 117; future issues, 199; historical perspective on, 51–52, 56, 63–64, 67–68; inequality and, 12, 70, 188; intergenerational https://doi.org/10.1017/9781009151405.009 Published online by Cambridge University Press Index transfers and, 190; labor markets and, 163, 183; market failure and, 19–30; mutual aid societies (MASs) and, 16; private markets and, 13, 70, 73, 89, 100; rich people and, 2, 73, 183; social protection and, 2, 56; symmetric information and, 25–29; theoretical model and, 16, 19–20, 30, 32nn15–16, 33; transfers and, 16, 30, 67, 190; uncertainty and, 8; welfare and, 8 Denmark, 8–9, 90, 92, 102, 107, 109, 117, 147, 183, 193, 197–198 Department of Motor Vehicles, 75 destitution, 45, 67 diagnostics, 10, 27, 49, 62, 81, 83–88, 94, 100, 193 digitalization, 76–79 disability, 34, 38, 44, 63, 75, 139, 197 Discovery Limited, 79 discretionary income: credit markets and, 100, 105, 108–115, 118, 138, 140, 142, 196; risk and, 100, 105, 108–115, 138; welfare and, 110–111 discrimination, 2, 5, 35, 38–39, 63, 81, 88, 93–94, 100, 116, 199, 202 “double payment” problem, 9, 13, 37, 39, 68, 89, 92, 94–95, 100, 198–199 education: additional schooling, 107; advantages of, 200; credit markets and, 7, 33, 110, 115, 138, 141; double-payment problem and, 9; employment and, 11, 33, 60, 66, 69, 159, 161–162, 165, 174, 179, 183–184, 192, 197–198; health and, 9, 60, 66, 84, 93, 95–96, 159, 192–193, 197; income and, 9, 11, 17, 33, 60, 64, 69, 92–96, 110, 115, 138, 141, 161, 174, 192, 197; labor markets and, 159, 161– 162, 165, 167, 174, 179, 183–184, 198; mutual aid societies (MASs) and, 192; private markets and, 84, 92–95, 96n24; rich people and, 9, 40, 60, 92, 95; risk and, 7, 11, 17, 33, 40, 60, 66, 69, 84, 93, 115, 138, 141, 159, 161–162, 165, 174, 179, 183–184, 192, 197n3, 198; social media and, 196; unemployment and, 11, 60, 66, 159, 161–162, 165, 174, 179, 183–184, 192, 197n3, 198 elasticity, 111 elderly: health and, 2, 7, 18, 29, 34, 96–97, 99; higher expenses of, 195; insecurity 221 and, 8, 18; labor markets and, 159, 171, 173, 185–186; market feasibility and, 16– 18, 30–35; Medicare and, 2, 7, 9, 17, 59– 60, 96–99, 133; mutual aid societies (MASs) and, 44, 47–49, 55; old-age insurance and, 4–5, 13, 31, 159; pensions and, 56 (see also pensions); poverty and, 46–47; private markets and, 18, 96–97; public spending on, 29n13; time inconsistency and, 7, 16–18, 30–35, 47, 56, 89, 96, 193; welfare and, 4, 7–8, 13– 14, 18, 33, 53–54, 58, 105, 188, 193, 199 electronic health records (EHRs), 76–79 empirical implications of theoretical models (EITM) approach, 201 Employee Retirement Income Security Act, 50n2, 60–61 employment: credit markets and, 108, 133– 135; education and, 11, 33, 60, 66, 69, 159, 161–162, 165, 174, 179, 183–184, 192, 197–198; health insurance and, 2, 4– 5, 10, 13, 18, 20, 34–35, 44, 50–51, 55, 58, 60, 66, 159–160, 191–192, 197; historical perspective on, 50, 58, 66, 69n9; homeownership and, 134–137; insiders vs. outsiders and, 66; Job Pact and, 182; labor market risks and, 159, 162, 165, 167, 174n9, 179–181, 184; Law on Employment Protection, 180; mobility and, 49, 66, 68, 189, 191–192, 200; mutual aid societies (MASs) and, 48– 49 (see also mutual aid societies (MASs); retirement and, 33 (see also retirement); sickness pay and, 44, 48; unemployment insurance funds (UIFs) and, 11, 14, 66, 177–184, 192, 198–199 employment protection, 159, 162, 180 Equitable Life Assurance Society, 49 error correction model (ECM), 87, 103 Esping-Andersen, Gosta, 52, 199 European Observatory on Health Systems and Policies (EOHSP), 93 European Social Survey (ESS), 174, 176, 186–187 Fair Housing Act, 12, 116n7 Fannie Mae, 65, 109, 116–117, 121 Federal Housing Administration (FHA), 117 FICO score: Gini coefficient and, 121–127, 129, 138; interest rates and, 121–130; loans and, 121–130, 149, 151–158 https://doi.org/10.1017/9781009151405.009 Published online by Cambridge University Press 222 Index financial crises, 14, 61, 65, 116n7 financialization, 7, 14, 16, 33, 65, 106–110, 115, 138–139 Finland, 90, 102, 107, 147 Fitbit, 79 flat-rate benefits, 37, 114–115, 132, 144–146 Food and Drug Administration, 62 Foote, Christopher, 120–121, 131 Fordism, 47, 106, 162 fragmentation: information revolution and, 58–67; labor markets and, 50n2; political polarization and, 2; risk pools and, 2, 12, 188; solidarity and, 58–67; unemployment insurance and, 11–12 France, 80, 90, 102, 107, 147 fraternal sciences, 47, 52 Freddie Mac, 65, 109, 116–130, 140n25, 197 Friedman, Rachel, 15n1, 19, 191 funded systems: adverse selection and, 45; information and, 18; intergenerational transfers and, 7; pension systems, 7, 17, 33, 53, 55, 58, 64, 193, 201; retirement and, 16, 33, 45, 64, 96; transfers and, 7, 16, 47, 64, 96 GDP, 64, 70, 83, 86n21, 87–91, 104, 139 Generali, 80 genetics, 18, 38, 62–63, 81–88, 93–94, 191, 193 German General Social Survey (ALLBUS), 171–172, 173, 185–186 German Socio-Economic Panel (GSOEP), 134–137, 165–172 Germany, 195; credit markets and, 107, 131, 135n23, 147; Hartz reforms and, 14, 65, 131–137, 140, 198; health insurance and, 17; health savings plans and, 7, 33; labor markets and, 165–172, 173, 185– 186, 198; private markets and, 80, 89n23, 90, 91, 96n25, 102; unemployment and, 14, 65, 165, 168– 173, 185–186, 198 Ghent system, 177, 179–180, 182, 184, 198 Gingrich, Jane R., 59 Gini coefficient, 121–127, 129, 138 Goering, John, 116n7 good state, 20–21, 25n9, 40, 41, 112n5, 114, 142n27, 143–144 Google, 62, 73 Gordon, Robert, 49 Gottlieb, Daniel, 48, 50n3 government-sponsored enterprises (GSEs), 116–121 GPS, 3 Great Depression, 30, 46, 117, 189 Grogan, Colleen M., 99 group plans, 49–50 Hacker, Jacob, 60 Hall, John, 93 Hariri, Jacob Gerner, 109 Harsanyi, John, 15–16 Hartz IV reforms, 14, 65, 131–137, 140, 198 health: data devices and, 62–63; diagnostics and, 10, 27, 49, 62, 81, 83–88, 94, 100, 193; disease, 10, 44, 62, 67, 79, 84, 86– 87, 100–102; education and, 9, 60, 66, 84, 93, 95–96, 159, 192–193, 197; elderly and, 2, 7, 18, 29, 34, 96–97, 99; genetics and, 18, 38, 62–63, 81–88, 93– 94, 191, 193; rich people and, 2, 4, 8–9, 58, 60, 91, 95, 193; younger generation and, 4, 6–7, 13, 17–18, 30–31, 48, 56, 67, 86, 92, 96, 101, 193–195 Healthcare NExt, 81 Health Information Technology and Economic and Clinical Health Act, 76 health insurance: Affordable Care Act (ACA), 11, 50n2, 60–61, 63, 91, 94, 97; artificial intelligence (AI) and, 81–82; choice between public/private, 94–99; electronic health records (EHRs), 76–79; empirical applications and, 193–196; employment and, 2, 4–5, 10, 13, 18, 20, 34–35, 44, 50–51, 55, 58, 60, 66, 159– 160, 191–192, 197; guaranty associations and, 33; historical perspective on, 44, 49– 51, 55, 58, 60–64; illness and, 8, 13–14, 20, 25, 48, 62–63, 75, 96, 108, 110, 171, 173, 185–186, 188; information and, 4– 8, 11, 13, 60–64, 192–196; laboratories and, 81, 83, 87; labor markets and, 159; medical data and, 75; Medical Information Bureau (MIB) and, 72n4, 75, 78–79; prescription databases and, 75, 77; private markets and, 70–102, 104, 201; Republican Party and, 94; as second largest insurance, 70; segmentation and, 70; supplementary private, 88–94; https://doi.org/10.1017/9781009151405.009 Published online by Cambridge University Press Index theoretical model and, 17–19, 33–37; trackers and, 76, 79–81, 100; underwriting and, 17, 92–94, 100; voluntary private, 63, 89–93 Health Insurance Portability and Accountability Act (HIPAA), 63n8, 78 health savings plans, 7, 17, 33, 96, 195 HealthVault, 62 Hicks, Timothy, 59, 197n3 high information, 8, 10, 25–27, 38, 56–58, 64, 82n17, 200 Home Mortgage Disclosure Act (HMDA), 120n10 homeownership: credit markets and, 108, 116, 131–140; employment and, 134– 137; GSEOP and, 134–137; Hartz IV reforms and, 14; mortgages and, 106 (see also mortgages); private markets and, 93; Sample Survey of Income and Expenditure (EVS) and, 134–135, 137; stratified rates of, 198; subsidies and, 131, 138–139, 197; VPHI and, 93; welfare and, 131–138 homophily, 164 housing, 11–12, 115–117, 121, 132–133, 138–141, 192 Human API portal, 77–78 human genome, 62, 81, 83 IBM, 62 Ignacio Conde-Ruiz, J., 53 illness, 8, 13–14, 20, 25, 48, 62–63, 75, 96, 108, 110, 171, 173, 185–186, 188 immigrants, 46, 167 individual retirement accounts (IRAs), 47, 64, 193 industrialization, 17, 96n25; deindustrialization and, 12, 30, 179, 188– 189; health insurance and, 195; historical perspective on, 44, 49, 51, 56; knowledge economy and, 192; middle class and, 6, 15, 51, 53–54; mutual aid societies (MASs) and, 44, 190; uncertainty and, 189; urbanization and, 189 inequality: credit markets and, 106–115, 118–131, 138, 140, 144, 196–198; democracy and, 12, 70, 188; future issues and, 201; Hartz IV reforms and, 14; historical perspective on, 59–61, 64–65; increased, 2, 7, 14, 16, 19, 33, 59, 61, 64– 65, 70–71, 100, 106, 108–113, 118, 128, 223 130, 138, 140, 188–189, 197–198, 201; information and, 2, 5, 7, 12, 14; labor markets and, 198; mortgages and, 119– 131; private markets and, 70–71, 82, 92, 100; reduction of, 92, 112, 118, 138, 188–189, 198; regulation and, 119–131; risk and, 2, 7, 12, 14, 19, 33, 59–61, 65, 82, 92, 100, 108, 111–114, 130, 138, 144, 188–189, 196–198, 201; segmentation and, 59, 61, 188–189, 196; taxes and, 19, 60, 100, 188–189; theoretical model and, 16, 19, 33 information: actuarial science and, 49 (see also actuarial science); asymmetric, 2–4, 8, 15, 20–27, 38, 39, 55, 56, 63, 74, 82n17, 160, 190, 199, 202; Big Data, 5, 13, 22, 63, 108, 119, 138, 191; credible, 28, 38, 39; credit markets and, 64–65, 112–113; Department of Motor Vehicles and, 75; diagnostics and, 10, 27, 49, 62, 81–88, 94, 100, 193; division of insurance pools and, 5–10; electronic health records (EHRs) and, 76–79; funded systems and, 18; health insurance and, 4–8, 11, 13, 60–64, 192–196; high, 8, 10, 25–27, 38, 56–58, 64, 82n17, 200; human genome, 62, 81, 83; incomplete, 2, 12, 18, 29, 55, 66; inequality and, 2, 5, 7, 12, 14, 119–131; laboratories and, 81, 83, 87; labor markets and, 160–165; life insurance and, 4–7, 10, 13, 72–73, 82– 88, 101–103, 104, 193–193; loans and, 112–113, 118–119; low, 8, 10, 14, 18, 25–26, 28, 38, 39, 56, 57, 67, 199; market failure and, 6, 9, 19–30, 190; market feasibility and, 16–19, 30–37, 46, 58, 160, 199; Medical Information Bureau (MIB) and, 72n4, 75, 78–79; Moore’s Law and, 61–62, 83n18; mortgages and, 119–131; mutual aid societies (MASs) and, 6, 8, 10–13, 199; ownership of, 202; pensions and, 64–65; preferences and, 18–19, 35–37; prescription databases and, 75, 77; privacy and, 10, 26–29, 40–42, 63, 78, 94, 202; regulation and, 2, 14, 18, 38, 63– 65, 70, 73, 81, 87–89, 93–94, 100, 110, 117–131, 140, 199, 202; revolution in, 2, 4, 13, 35, 39, 55, 58–73, 82, 88, 94, 100, 108, 188, 201; risk and, 1–15, 18–30, 35– 37, 160–165; segmentation and, 2, 5–6, https://doi.org/10.1017/9781009151405.009 Published online by Cambridge University Press 224 Index 8, 11–14, 16, 18, 58–59, 66–67, 70, 89, 94, 159, 162, 165, 177, 180, 188–189, 192, 196; social insurance and, 2–13, 189–190, 193, 198; social solidarity and, 53–60; symmetric, 20, 25–29, 39, 55, 82n17; trackers and, 3–4, 29, 79–80, 191; uncertainty and, 16 (see also uncertainty); underwriting and, 74–75; unemployment insurance and, 65–67, 183; welfare and, 2–14 information and communication technology (ICT), 4, 8, 119, 131, 189 integration, 2, 5 interest rates: changing, 17; credit markets and, 105, 108, 111–132, 138–144, 152, 156; Denmark and, 198; equalization of, 65; FICO scores and, 121–130; Gini coefficient and, 121–127, 129, 138; mortgages, 14, 65, 116–124, 128, 138– 140, 197; segmentation and, 52, 58, 70 International Monetary Fund (IMF), 106, 107 Ireland, 90, 102, 107, 147 ISCO, 174 Italy, 90, 102, 107, 147, 203 Japan, 58, 66, 90, 91, 102, 107 Jawbone, 79 Job Pact, 182 John Hancock Life Insurance, 4, 29, 77–78, 80 Kaiser Family Foundation Poll, 99 Keen, Michael, 19 Korpi, Walter, 53, 193 laboratories, 81, 83, 87 labor markets: actuarial approach and, 160, 163n2, 177, 179, 184; collective bargaining and, 64, 159, 193; democracy and, 163, 183; disability and, 34, 38, 44, 63, 75, 139, 197; education and, 159, 161–162, 165, 167, 174, 179, 183–184, 198; elderly and, 159, 171, 173, 185– 186; empirical applications and, 198– 199; employment protection, 159, 162, 180; fragmentation and, 50n2; Germany and, 165–172, 173, 185–186, 198; Ghent system and, 177, 179–180, 182, 184, 198; health insurance and, 159; inequality and, 198; information and, 160–165; Law on Employment Protection, 180; market failure and, 184; partisanship and, 177, 183; poor people and, 160, 176; preferences and, 14, 66, 160, 163, 165– 177; public system and, 165, 177, 182– 183; redistribution and, 172, 174–176, 183, 186–187; reform and, 165, 177– 182, 198; regression analysis and, 166, 172, 173, 185–186; regulation and, 159; segmentation and, 14, 50, 67, 159, 162, 165, 177, 180, 182, 188, 192, 198; social insurance and, 159–160, 163, 177; subsidies and, 182, 185; Swedish unemployment insurance and, 177–183; taxes and, 159, 177, 180, 181; uncertainty and, 160, 163n2; unemployment protection, 46, 159, 164, 197n3; unions and, 159, 161, 164, 174, 177–184, 200; United States and, 66; voters and, 163–164, 184; wage protection, 159 Latin America, 66 Law on Employment Protection, 180 layoffs, 110 legal issues: clerical marriage, 44; discrimination, 116; intergenerational contracts and, 31; social media, 81; symmetric information and, 26 Lexis Nexis Risk Classifier, 76 life expectancy: adverse selection and, 45; historical perspective on, 45, 48–51; increased data on, 10, 45; predicting, 18, 193; premiums and, 17; private markets and, 72, 83–87; risk and, 34 life insurance: artificial intelligence (AI) and, 81–82; commercialization of, 45–50, 54– 55, 67; credit reports and, 76; Department of Motor Vehicles and, 75; diagnostics and, 10, 27, 49, 62, 81, 83– 88, 94, 100, 193; division of insurance pools and, 5, 7; electronic health records (EHRs) and, 76–79; empirical applications and, 193–196; funded plans and, 7, 16–18, 33, 45, 48, 53, 58, 96, 193–195; guaranty associations and, 33; historical perspective on, 44–49, 55, 58, 63; information and, 4–7, 10, 13, 72–73, 82–88, 101–103, 104, 193–193; laboratories and, 81, 83, 87; Lexis Nexis Risk Classifier and, 76; market penetration of, 82–88, 101–103, 104; https://doi.org/10.1017/9781009151405.009 Published online by Cambridge University Press Index Medical Information Bureau (MIB) and, 72n4, 75, 78–79; micro-targeted products and, 73; permanent, 72; prescription databases and, 75, 77; private markets and, 70–94, 100–102, 103–104; purpose of, 71–72; theoretical model and, 16–17, 29, 33–38; trackers and, 76, 79–81, 100; underwriting and, 71, 73–82, 87–88, 100–101 liquidity, 109 loans: access to, 65, 105–106, 110; bank, 65, 105, 116, 131–132, 202; credit markets and, 118–119; default and, 108 (see also default); discretionary income and, 100, 105, 108–115, 118, 138, 140, 142, 196; FICO scores and, 121–130, 149, 151–158; flat-rate benefits and, 37, 114–115, 132, 144–146; Gini coefficient and, 121–127, 129, 138; Hartz reform and, 65, 132; inequality and, 119–131; information and, 112–113, 118–119; interest rates and, 110 (see also interest rates); liquidity and, 109; model for, 110– 117, 141–144; mortgages, 110 (see also mortgages); private markets and, 83; regulation and, 115–131; risk and, 65, 100, 105, 108–109, 111–117, 130, 132, 138, 141–142, 196, 202; Single Family Loan-Level Dataset and, 121; welfare and, 110–111, 113–115, 131–138 loan-to-value ratio, 124, 131, 156 Loewenstein, Lara, 120–121, 131 low information, 8, 10, 14, 18, 25–26, 28, 38, 39, 56, 57, 67, 199 lump sum payments, 33, 35–36, 114 McFadden pseudo R-squared measure, 166–172, 173, 185–186 Maclaurin, Colin, 45 market failure: asymmetric information and, 22–25; classic framework for, 19– 30; democracy and, 19–30; historical perspective on, 53, 57, 67; information and, 6, 9, 190; labor markets and, 184; mutual aid societies (MASs) and, 6, 67; private markets and, 94; redistribution and, 6, 12, 67, 191, 200; symmetric information and, 25–29; theoretical model and, 12, 15, 18–20, 29 market feasibility, 160, 199; historical perspective on, 46, 58; information and, 225 16–18, 30–35; preferences and, 18–19, 35–37; time inconsistency and, 16–18, 30–35 market-mediated funded systems, 201 Medicaid, 8, 10, 60, 68, 96–99, 193 Medical Information Bureau (MIB), 72n4, 75, 78–79 Medical Literature Analysis and Retrieval System Online, 84 Medical Subject Headings (MeSH), 84 Medicare, 2, 7, 9, 17, 59–60, 96–99, 193 Meltzer-Richard model, 114 Microsoft, 5, 62, 81 micro-tracking, 3 middle class: credit markets and, 106; education and, 199; industry and, 6, 15, 51, 53–54; mortgages and, 65, 106; preferences of, 59, 196, 200; private markets and, 69, 71, 92, 97, 200; theoretical model and, 5; universal public system and, 30; voters, 32, 51, 61, 193; welfare and, 6, 8, 13, 15, 54, 68–69, 193– 195, 199 Misfit, 79 MLC On Track, 80 mobility, 49, 66, 68, 189, 191–192, 200 Moore’s Law, 61–62, 83n18 moral hazard, 10, 45, 48, 184, 198 mortality: artificial intelligence (AI) and, 81–82; Lexis Nexis Risk Classifier and, 76; life expectancy and, 10, 17, 34, 45, 48–51, 72, 83–87, 193; private markets and, 72, 75–76, 79, 81, 84, 86, 101–102 mortgages: credit markets and, 106, 109– 140, 146, 147; FICO scores and, 121– 130, 149, 151–158; Gini coefficient and, 121–127, 129, 138; Home Mortgage Disclosure Act (HMDA) and, 120n10; inequality and, 119–131; information and, 119–131; interest rates and, 14, 65, 116–124, 128, 138–140, 197; middle class and, 65, 106; private markets and, 198; redlining and, 11, 116, 202; regulation and, 14, 65, 109, 115, 117– 131, 138, 140, 197; risk and, 14, 65, 109, 115–117, 120, 128, 132, 134–138, 197, 202; Single Family Loan-Level Dataset and, 121; underwriting, 120, 207–208 Motor Vehicle Reports, 75 MRI scans, 1, 27, 83 Murray, Charles, 51–52 https://doi.org/10.1017/9781009151405.009 Published online by Cambridge University Press 226 Index mutual aid societies (MASs): asymmetric information and, 23, 25, 199; burial insurance, 47–48; commercialization of, 45–50, 54–55, 67; democracy and, 16; destitution and, 45, 67; double bind of, 48, 50, 54, 67, 190; dues to, 46; education and, 192; elderly and, 44, 47–49, 55; Equitable Life Assurance Society, 49; failure of, 12; heyday of, 51; historical perspective on, 10–11, 13, 44–57, 65, 67, 192; immigrants and, 46; increase of, 44; industrialization and, 44; information and, 6, 8, 10–13, 199; limitations of, 6; market failure and, 6, 67; New England Mutual Life Insurance Company, 49; New York Life Insurance Company, 49; as partial solution, 190; protections by, 44; role of, 11; Scottish Presbyterian Widows Fund, 44–46, 49, 83, 193; sickness pay and, 44, 48; solidarity and, 46, 53–58; taxes and, 47; theoretical model and, 15–16, 23, 25, 32; timeinconsistency and, 6–7, 16, 32, 45, 47– 48, 54, 56, 199; transfers and, 6, 48, 57– 58; unions and, 192; United States and, 44, 46, 49, 55; welfare and, 6, 8, 10, 12– 13, 15–16, 25, 48, 51–52, 54, 56; widespread use of, 44 National Human Genome Research Institute, 62 National Laboratory of Medicine, 84 Netherlands, 90, 91, 102, 107, 147 New England Mutual Life Insurance Company, 49 New York Life Insurance Company, 49 New York State Department of Financial Services, 80–81 New Zealand, 90, 102, 107 Norway, 90, 92, 102, 107, 147 Obama, Barack, 76, 81, 90 occupational unemployment rates (OURs), 174n0 OECD Health Statistics, 89, 101 opting out: adverse selection and, 30, 54, 199; Akerlof and, 24; Bismarckian system and, 53; cost of, 19, 29; deterrents against, 9; private markets and, 25; privileged, 15; public system and, 8–9, 15, 19, 24–25, 30, 37, 54, 57, 59, 64, 71, 89n23, 94–96; segmentation and, 8; selfinsurance and, 11–12, 20–22, 50n2, 51, 57, 60, 67, 73, 93, 190; theoretical model and, 15, 19, 24–25, 29–30, 37, 41 Oscar Health Insurance, 80 Palme, Joakim, 53, 193 Park, Sunggeun (Ethan), 99 participation, 9, 67, 95, 102, 184 partisanship: adverse selection and, 37; coercion and, 6; Comparative Political Data Set and, 102; credit markets and, 118; historical perspective on, 59; labor markets and, 177, 183; preferences and, 12, 19, 59, 200; private markets and, 71, 92, 94, 97, 101–102, 103–104, 195; regulation and, 37–38; theoretical model and, 37–38; welfare and, 12 pay-as-you-go (PAYG) systems: credible government commitment to, 7; historical perspective on, 46–48, 53–58, 64, 67; market-mediated funded systems and, 201; private markets and, 96; redistribution and, 16, 18, 32, 53, 64, 67; subsidies and, 18, 67; time-inconsistency and, 16, 31–35, 47, 56, 96, 191, 193; transfers and, 16, 47, 55, 191; voters and, 193; welfare and, 16, 18, 33, 48, 53, 193; younger generation and, 16, 18, 31, 33, 47–48, 56, 64, 67, 96, 193 pay-how-you-drive (PHYD), 3 pensions: credit-based insurance and, 64– 65; credit markets and, 64–65, 114, 131n14, 135n20, 141; funded systems and, 7, 17, 33, 53, 55, 58, 64, 193, 201; historical perspective on, 51, 53–60, 64– 65; information and, 64–65; marketmediated funded systems and, 201; PAYG and, 31 (see also pay-as-you-go (PAYG) systems); private markets and, 18, 36, 70, 82; taxes and, 19, 31 “piggy bank”, 12, 24 Placebo outcomes, 126–127, 148, 156–157 “Politics of Medicaid, The: Most Americans Are Connected to the Program, Support Its Expansion, and Do Not View It as Stigmatizing” (Grogan and Park), 99 Ponzi schemes, 48 poor people: attitudinal gap and, 176; becoming, 7; cost of insurance and, 30; credit markets and, 115, 133–140, 196; https://doi.org/10.1017/9781009151405.009 Published online by Cambridge University Press Index labor markets and, 160, 176; Medicaid and, 8, 10, 60, 68, 96–99, 193; Medicare and, 2, 7, 9, 17, 59–60, 96–99, 193; private markets and, 96, 98, 100; support of by rich people, 4; transfers and, 7–8, 55, 115, 200; welfare and, 68 (see also welfare) Portugal, 90, 102, 147 Potential Years of Life Lost (PYLL), 86–87, 101–102, 104 poverty: credit markets and, 115; destitution, 45, 67; elderly and, 46–47; fear of, 7–8; historical perspective on, 46– 47, 55, 67–68; insurance against, 7–9, 193; private markets and, 71, 96, 99; transfers and, 13 Precision Medicine Initiative, 81 preferences: bifurcation of, 30, 163; constrained, 9, 59, 199; divergence in, 192; first-best, 9, 95; formation of, 35– 37; increased information and, 18–19, 35–37; labor markets and, 14, 66, 160, 163, 165–177; market feasibility and, 18– 19, 35–37; mass, 18; middle class, 59, 196, 200; partisan, 12, 19, 59, 200; polarization of, 2, 9, 12, 14, 16, 20, 37, 39, 66–67, 163, 169, 172, 176, 184; policy, 11–12, 14, 19, 26, 37, 67, 172, 184; political, 160, 163–177, 184, 186; private markets and, 95, 96n24, 99; public spending and, 18, 37, 59, 95, 192; redistribution, 12, 16, 18, 21n4, 35, 172, 174, 200, 203; risk and, 2, 12, 14, 16, 18, 21, 26, 30, 35, 37, 39, 57, 59, 66–67, 160, 163–176, 184, 192, 199–200, 203; shaping, 19, 59, 66, 160, 200; uncertainty and, 16, 26, 66, 199; welfare and, 2, 9, 12, 18, 21, 30, 37, 39, 68, 203 prescription databases, 75, 77 Preston, Ian, 93 price discrimination, 38 price nondiscrimination, 39 privacy, 10, 26–29, 40–42, 63, 78, 94, 202 private markets: actuarial approach and, 72, 81, 83, 89, 99–100; adverse selection and, 72, 82n17, 83, 88; Big Data and, 13, 63, 191; democracy and, 13, 70, 73, 89, 100; education and, 84, 92–95, 96n24; elderly and, 18, 96–97; Germany and, 80, 89n23, 90, 91, 96n25, 102; health insurance and, 70–102, 104, 201; homeownership and, 227 93; inequality and, 70–71, 82, 92, 100; life expectancy and, 72, 83–87; life insurance and, 70–94, 100–102, 103– 104; market failure and, 94; middle class and, 69, 71, 92, 97, 200; mortality and, 72, 75–76, 79, 81, 84, 86, 101–102; mortgages and, 198; opting out and, 25; partisanship and, 71, 92, 94, 97, 101– 102, 103–104, 195; pay-as-you-go (PAYG) systems and, 96; pensions and, 18, 36, 70, 82; poor people and, 96, 98, 100; poverty and, 71, 96, 99; preferences and, 95, 96n24, 99; public system and, 71, 82, 91–97, 100; reform and, 89–92; regression analysis and, 83; regulation and, 19, 37–38, 70, 73, 80–81, 87–94, 97, 100, 102; risk and, 70–100; segmentation and, 2, 5, 8, 11, 13–14, 18, 40, 53, 58–59, 63, 67, 70, 89, 94, 165, 180, 196; social insurance and, 70, 96; subsidies and, 94; taxes and, 89, 92, 100; time-inconsistency and, 71, 89, 96–99; top-up plans and, 9, 89, 179–182, 195; transfers and, 80n15, 81, 96; uncertainty and, 101; unemployment and, 4; United States and, 8, 18, 44, 51, 70, 74, 77–84, 89n23, 90, 91–99, 102–103, 195; voters and, 101; wealth and, 70, 97, 100; welfare and, 19, 37–38, 70; younger generation and, 84–86, 92, 96–97, 101 professional associations, 49, 66, 159, 161, 164, 179 Profeta, Paola, 53 Prudential, 80 Prussia, 44 Przeworski, Adam, 19 public spending, 29n13, 37, 68, 139, 145, 192, 199 public system: historical perspective on, 54, 57, 59, 63–64; information and, 8–9; labor markets and, 165, 177, 182–183; left’s support for, 19, 37–38; opting out and, 8–9, 15, 19, 24–25, 30, 37, 54, 57, 59, 64, 71, 89n23, 94–96; private markets and, 71, 82, 91–97, 100; taxes and, 9, 15, 19, 25, 31, 37, 39, 54, 60, 195, 200; theoretical model and, 15–20, 24– 25, 28–30, 35, 37–40; top-up plans and, 9, 36, 89, 179–182, 195; uncertainty and, 8, 15–16, 30, 61, 67 Putnam, Robert, 203 https://doi.org/10.1017/9781009151405.009 Published online by Cambridge University Press 228 Index Qualcomm, 80 Rawls, John, 8, 15n1, 54, 67 recessions, 46, 189 reciprocity, 46, 203 Recovery Act, 76 redistribution: credit markets and, 109, 115, 124, 128, 144; division of insurance pools and, 5; historical perspective on, 46, 53, 58, 60, 64, 67; intergenerational, 32, 67; labor markets and, 172, 174–176, 183, 186–187; literature on, 21n4, 189; lumpsum benefits and, 36; market failure and, 6, 12, 67, 191, 200; pay-as-you-go (PAYG) systems, 16, 18, 32, 53, 64, 67; preferences and, 12, 16, 18, 21n4, 35, 172, 174, 200, 203; risk, 5, 17, 30, 38, 53, 58, 60, 172, 174–176, 183, 186–187, 197, 200; time-inconsistency and, 30; transfers and, 16, 30, 64, 109, 144, 188– 189, 200; welfare and, 6, 12, 16, 18, 21, 36, 38, 53, 56, 58, 68, 115, 188, 191, 197, 203; younger generation and, 16, 30, 64 redlining, 11, 116, 202 reform, 201; credit markets and, 116–117, 120, 131–137, 140; Hartz IV, 14, 65, 131–137, 140, 198; historical perspective on, 65, 67; labor markets and, 165, 177– 182, 198; private markets and, 89–92; regulation and, 14, 18, 65, 89, 117; Scottish Reformation, 44; unemployment, 14, 29, 65, 67, 131–137, 165, 177–182, 198; voters and, 18, 29 regression analysis: credit markets and, 125–126, 127, 130, 146, 147–158; discontinuity results and, 148; labor markets and, 166, 172, 173, 185–186; private markets and, 83 regulation: adverse selection and, 37–38; constraints from, 2, 63, 68, 94, 111; credit markets and, 14, 109–111, 115–131, 138, 140; historical perspective on, 50, 60–65, 68; inequality and, 119–131; of information, 2, 14, 18, 38, 63–65, 70, 73, 81, 87–89, 93–94, 100, 110, 117– 131, 140, 199, 202; labor markets and, 159; loans and, 115–131; mortgage markets and, 14, 65, 109, 115, 117–131, 138, 140, 197; partisanship and, 37–38; private markets and, 19, 37–38, 70, 73, 80–81, 87–94, 97, 100, 102; redistribution and, 172, 174–176, 183, 186–187; reform and, 14, 18, 65, 89, 117; risk and, 2, 14, 18–19, 33, 42, 50, 60–61, 64–65, 70, 73, 81, 89, 94, 109, 115–120, 130–131, 138, 140, 159, 195, 197, 199, 202; role of, 37–38, 115–118; segmentation and, 2, 6, 11–14, 16, 18, 40, 50, 52–53, 58–67, 70, 89, 94, 159, 162, 165, 177, 180, 188–189, 192–193, 196, 198; tax, 19, 50, 63, 115, 195, 199; trackers and, 80–81; welfare and, 37–38 Reinfeldt, Fredrick, 92, 177 Republican Party, 94 retirement: adverse selection and, 45; Employee Retirement Income Security Act and, 50n2, 60–61; funded systems and, 16, 33, 45, 64, 96; individual retirement accounts (IRAs), 47, 64, 193; pensions and, 64–65 (see also pensions); Social Security, 47, 67 rich people: attitudinal gap and, 176; credit markets and, 133–137, 140, 196; democracy and, 2, 73, 183; education and, 9, 40, 60, 92, 95; health and, 2, 4, 8– 9, 58, 60, 91, 95, 193; self-insurance and, 11–12, 20–22, 50n2, 51, 57, 60, 67, 73, 93, 190; selfinsuring by, 12, 22; support of poor by, 4 risk: adverse selection and, 1–2, 4, 6, 13, 30, 34, 45–46, 49–50, 54, 65, 67, 72, 82, 112, 199, 202; Akerlof model and, 6, 12, 19, 23–25, 27, 29, 190, 196; argument synopsis on, 189–192; average, 16, 22– 23, 24n7, 25n8, 28, 38, 54–55, 57, 59, 163n2; aversion to, 20, 22n6, 29n14, 36– 37, 41–42, 54, 56; credit markets and, 105, 108–120, 128–146; default, 144–146 (see also default); discretionary income and, 100, 105, 108–115, 138, 196; distribution of, 5, 16–17, 29–30, 38, 53–60, 108, 112, 128n13, 132, 140, 183, 189, 191, 197–200; education and, 7, 11, 17, 33, 40, 60, 66, 69, 84, 93, 115, 138, 141, 159, 161–162, 165, 174, 179, 183– 184, 192, 197n3, 198; flat-rate benefits and, 144–146; historical perspective on, 44–69; inequality and, 2, 7, 12, 14, 19, 33, 59–61, 65, 82, 92, 100, 108, 111–114, https://doi.org/10.1017/9781009151405.009 Published online by Cambridge University Press Index 130, 138, 144, 188–189, 196–198, 201; information and, 1–15, 18–30, 35– 37, 160–165; labor markets and, 159– 185; Lexis Nexis Risk Classifier and, 76; life expectancy and, 34; loans and, 65, 105, 108–109, 111–112, 115–117, 130, 132, 141–142, 202; market failure and, 184 (see also market failure); medical data and, 75; moral hazard and, 10, 45, 48, 184, 198; mortgages and, 14, 65, 109, 115–117, 120, 128, 132, 134–138, 197, 202; pooling of, 1–16, 19, 22–29, 38–42, 50–51, 54–55, 58–68, 72, 128, 159–160, 171, 177, 179–180, 184–185, 188, 191, 200–203; preferences and, 2, 12, 14, 16, 18, 21, 26, 30, 35, 37, 39, 57, 59, 66–67, 160, 163–176, 184, 192, 199–200, 203; private markets and, 70–100; redistribution and, 5, 17, 30, 38, 53, 58, 60, 197, 200; regulation and, 2, 14, 18–19, 33, 42, 50, 60–61, 64–65, 70, 73, 81, 89, 94, 109, 115–120, 130–131, 138, 140, 159, 195, 197, 199, 202; segmentation and, 189; subsidies and, 1, 4, 11, 17–18, 23, 25, 28, 30, 54, 61, 67, 109, 116, 118, 185, 192, 197, 199; theoretical model and, 15–43; timeinconsistency and, 7, 30–35, 45, 47, 54, 56, 89, 96, 191, 199; traditional classification of, 3; uncertainty and, 8, 13, 16, 26, 30, 36, 56, 61, 66–67, 160, 163, 191, 196, 199; unemployment and, 5, 8– 14, 18, 20, 26, 29, 35, 44, 46, 51, 60, 65– 67, 108–109, 131–132, 136–138, 159– 166, 169, 171–174, 177–180, 183–184, 188, 191–192, 197–198; voters and, 18, 25, 29, 61, 64, 163, 184, 188–191, 197n3, 199; welfare and, 2, 6–30, 33, 36– 39, 48, 51–58, 68–69, 105, 108–109, 115, 138, 140, 188, 191, 193, 197, 201, 203 Rogers, Will, 108 Rothschild, Michael, 19, 25, 41 Rothstein, Bo, 52 Rueda, David, 162 Sample Survey of Income and Expenditure (EVS), 134–135, 137 SAP government, 182–183 savings: credit markets and, 114, 116–117, 133, 157; health savings plans and, 7, 17, 229 33, 96; private markets and, 96–97; wealth and, 1, 7–8, 17, 20–21, 29, 33–34, 36, 46–47, 51, 66, 96–97, 114, 116–117, 133, 136, 141, 160, 180, 190, 193 savings and loans (S&Ls), 116–117 Scottish Mutual, 55 Scottish Presbyterian Widows Fund, 44–46, 49, 83, 193 Scottish Reformation, 44 segmentation: choice and, 8; concept of, 6; credit markets and, 40, 159, 192; health insurance and, 70; historical perspective on, 50, 52–53, 58–59, 61, 63, 66–67; inequality and, 59, 61, 188–189, 196; information and, 2, 5–8, 11–18, 58–59, 66–67, 70, 89, 94, 159, 162, 165, 177, 180, 188–189, 192, 196; information levels and, 2, 5; integration and, 2, 5; interest rates and, 52, 58, 70; labor markets and, 14, 50, 67, 159, 162, 165, 177, 180, 182, 188, 192, 198; opting out and, 8; private markets and, 2, 5, 8, 11, 13–14, 18, 40, 53, 58–59, 63, 67, 70, 89, 94, 165, 180, 196; regulation and, 2, 70, 89, 94; risk and, 2, 6, 11, 13–14, 16, 18, 40, 50, 52–53, 58–59, 61, 63, 66–67, 70, 89, 94, 159, 162, 165, 177, 180, 188– 189, 192–193, 196, 198; state programs and, 11, 18, 50, 52–53, 159, 188; theoretical model and, 16, 18, 40; unemployment insurance and, 177–183; welfare and, 8, 18, 52–53, 188 self-insurance, 11–12, 20–22, 50n2, 51, 57, 60, 67, 73, 93, 190 self-interest, 19, 29, 52, 191 Shapley decomposition, 169, 170, 170 sickness pay, 44, 48 Single Family Loan Level Dataset, 121 social capital, 51–52, 203 social insurance: future politics of, 199–201; historical perspective on, 44, 51–52, 54, 56–60, 65, 67; information and, 2–13, 189–190, 193, 198; labor markets and, 159–160, 163, 177; private markets and, 70, 96; theoretical model and, 15, 19, 21n4, 30, 35, 37, 39 social media, 80–81 social networks, 11–12, 14, 18, 25, 66–67, 164, 183–184, 196 Social Security, 47, 67 https://doi.org/10.1017/9781009151405.009 Published online by Cambridge University Press 230 Index solidarity: COVID-19 pandemic and, 61; cross-class, 8, 14, 18, 203; emergence of, 53–58; fragmentation of, 58–67; information revolution and, 58–67, 71, 201; mutual aid societies (MASs) and, 46, 53–58; reciprocity and, 203; uncertainty and, 66, 160, 196; unemployment insurance and, 183, 192; welfare and, 8, 18, 40n21, 201, 203 Spain, 90, 102, 147 Stiglitz, Joseph, 19, 25 Stolle, Dietlind, 52 Study Watch, 62 subsidies: credit markets and, 109, 116, 118, 131n14, 138, 139, 144; historical perspective on, 54, 61, 67; homeownership, 131, 138–139, 197; labor markets and, 182, 185; pay-as-yougo (PAYG) systems and, 18, 67; private markets and, 94, 192; risk and, 1, 4, 11, 17–18, 23, 25, 28, 30, 54, 61, 67, 109, 116, 118, 185, 192, 197, 199; tax, 4, 37, 54, 199 supplementary health insurance, 88–94 Swaan, Abram de, 50–51 Sweden, 11, 38, 66, 90, 102; “Alliance for Sweden” campaign, 184; Bildt and, 11, 177; credit markets and, 107, 147; Democrats, 182–183; Ghent system and, 177, 179–180, 182, 184, 198; Job Pact and, 182; Law on Employment Protection and, 180; Left Party, 182; politics of private markets and, 180; Reinfeldt and, 92, 177; SAP government and, 182–183; unemployment insurance funds (UIFs) and, 180–184; unions and, 182 Swedish Confederation of Professional Associations (SACO), 179–180, 182 Swedish Confederation of Professional Employees (TCO), 180, 182 symmetric information, 20, 25–29, 39, 55, 82n17 taxes: coercive, 12; credit markets and, 114– 115, 139, 144; credits, 9, 195, 199; deductions, 50, 92, 115, 199; flat-rate, 37, 114–115, 132, 144–146; historical perspective on, 47, 50, 54–56, 60, 63, 66; inequality and, 19, 60, 100, 188–189; labor markets and, 159, 177, 180, 181; mutual aid societies (MASs) and, 47; paying for social protection by, 4, 8, 15, 19, 25, 31, 198–200; pensions and, 19, 31; power to, 54, 191; preference formation and, 35–37; price nondiscrimination and, 39; private markets and, 89, 92, 100; public system and, 9, 15, 19, 25, 31, 37, 39, 54, 60, 195, 200; regulation and, 19, 50, 63, 115, 195, 199; subsidies and, 4, 37, 54, 199; transfers and, 8, 114–115, 144, 188–191, 200; voters and, 25, 31, 188–191 time-inconsistency: adverse selection and, 30, 34; asymmetric information and, 56, 190, 199; elderly and, 7, 16–18, 30–35, 47, 56, 89, 96, 193; historical perspective on, 45, 47–48, 54, 56; intergenerational bargains and, 47, 191, 193; market feasibility and, 16–18, 30–35; mutual aid societies (MASs) and, 6–7, 16, 45, 47–48, 54, 56, 199; overlapping generations models and, 32; pay-as-you-go (PAYG) systems and, 16, 31–35, 47, 56, 96, 191, 193; persistence of, 7; private markets and, 71, 89, 96–99; redistribution and, 30; risk and, 7, 30–35, 45, 47, 54, 56, 89, 96, 191, 199; theoretical model and, 30– 35; voters and, 32, 191, 193, 199; younger generation and, 6–7, 16–18, 30–35, 47–48, 56, 96, 190, 194 top-up plans, 9, 36, 89, 179–182, 195 trackers, 3–4, 29, 76, 79–81, 100, 191 transfers: credit markets and, 109, 114–115, 144; democracy and, 16, 30, 67, 190; funded systems and, 7, 16, 47, 64, 96; intergenerational, 6–7, 13, 55, 56, 190; mutual aid societies (MASs), 6, 48, 57– 58; pay-as-you-go (PAYG) systems, 16, 47, 55, 191; poor people and, 7–8, 55, 115, 200; poverty and, 13; private markets and, 80n15, 81, 96; redistribution and, 16, 30, 64, 109, 144, 188–189, 200; taxes and, 8, 114–115, 144, 188–191, 200; theoretical model and, 16, 20, 30, 47–48, 55, 56–57, 64–65, 67; younger generation and, 6–7, 13, 16, 30, 47–48, 56, 67, 96, 190 uncertainty: democracy and, 8; incomplete information and, 8, 66–67; industrialization and, 189; labor markets and, 160, 163n2; preferences and, 16, 26, https://doi.org/10.1017/9781009151405.009 Published online by Cambridge University Press Index 66, 199; private markets and, 101; public system and, 8, 15–16, 30, 61, 67; risk and, 8, 13, 16, 26, 30, 36, 56, 61, 66–67, 160, 163, 191, 196, 199; solidarity and, 66, 160, 196; voters and, 31, 61, 101, 163, 199; welfare and, 8, 13, 36, 56, 189, 191 underwriting: actuarial science and, 49; artificial intelligence (AI) and, 81–82; COVID-19 pandemic and, 74, 77; current practices of, 73–76; Department of Motor Vehicles and, 75; diagnostics and, 10, 27, 49, 62, 81, 83–88, 94, 100, 193; digitalization and, 76–79; electronic health records (EHRs) and, 76–79; health insurance and, 17, 92– 94, 100; innovations in, 76–82; laboratories and, 81, 83, 87; Lexis Nexis Risk Classifier and, 76; life insurance and, 71, 73–82, 87–88, 100–101; Medical Information Bureau (MIB) and, 72n4, 75, 78–79; mortgages, 120–121, 207–208; prescription databases and, 75, 77; trackers and, 3–4, 29, 76, 79–81, 100, 191; unemployment insurance funds (UIFs) and, 180 unemployment: benefits during, 14, 65, 109, 131–133, 136n24, 137–138, 169–172, 173, 182–184, 185, 198, 200; credit markets and, 108–109, 131–138; disability and, 44, 139, 197; education and, 11, 60, 66, 159, 161–162, 165, 174, 179, 183–184, 192, 197n3, 198; Germany and, 14, 65, 165, 168–173, 185–186, 198; high levels of, 180, 182, 184; historical perspective on, 44, 46, 51, 55, 60, 65–67; homeownership and, 134– 137; information and, 8–14; insurance for, 4, 11, 14, 34, 35, 46, 55, 65–67, 159– 160, 163, 165, 177–184, 192, 198; lost income and, 109, 188; occupational unemployment rates (OURs), 174n0; private markets and, 4; reform and, 14, 29, 65, 67, 131–137, 165, 177–182, 198; risk and, 5, 8–11, 13–14, 18, 20, 26, 29, 35, 44, 46, 51, 60, 65–67, 108–109, 131– 132, 136–138, 159–166, 169, 171–174, 177–180, 183–184, 188, 191–192, 197– 198; theoretical model and, 16, 18, 20, 25, 26n10, 29–30, 35; United States and, 198 231 unemployment insurance funds (UIFs), 11, 14, 66, 177–184, 192, 198–199 unemployment protection, 46, 159, 164, 197n3 unions: fall of, 12, 188; historical perspective on, 58, 66; Job Pact and, 182; labor markets and, 159, 161, 164, 174, 177–184, 200; rise of, 12; Sweden and, 182; unemployment insurance funds (UIFs) and, 11, 14, 66, 177–184, 192, 198–199 UnitedHealth, 80 United Kingdom, 80, 90, 93, 147 United States: 401(k) plans, 33, 64; Bush and, 17; Clinton and, 116; credit markets and, 106–107, 109, 117, 121, 124, 131, 139–140; employer-based coverage, 58; Fair Housing Act and, 12; Fannie Mae, 65, 109, 116–117, 121; financial crisis of, 14; fraternal societies and, 47, 52; Freddie Mac, 65, 109, 116–117, 119–130, 140n25, 197; Great Depression, 30, 46, 117, 189; guaranty associations and, 33; healthcare costs in, 29n13, 62; health savings accounts (HSAs), 17, 195; individual retirement accounts (IRAs), 193; information revolution and, 58–60; labor markets and, 66; Medicaid, 8, 10, 60, 68, 96–99, 133; Medicare, 2, 7, 9, 17, 59–60, 96–99, 193; mutual aid societies (MASs) and, 44, 46, 49, 55; Obama and, 76, 81, 90; private markets and, 8, 18, 44, 51, 70, 74, 77–84, 89n23, 90, 91–99, 102–103, 195; Republican Party and, 94; self-insurance and, 11; Social Security, 47, 67; as stingy welfare state, 197; unemployment and, 198 universal public system, 18, 30, 91 University of Edinburgh, 45 urbanization, 6, 30, 51, 189 US Genetic Information Nondiscrimination Act (GINA), 38, 63, 93, 94 Verily Life Sciences, 62, 81 Vitality Health, 79–80 voluntary private health insurance (VPHI), 63, 89–93 voters: Comparative Study of Electoral Systems (CSES), 176; labor markets and, 163–164, 184; median, 25, 32, 64; https://doi.org/10.1017/9781009151405.009 Published online by Cambridge University Press 232 Index middle-class, 1; pay-as-you-go (PAYG) systems and, 193; private markets and, 101; reform and, 18, 29; risk and, 18, 25, 29, 61, 64, 163, 184, 188–191, 197n3, 199; self-interested, 29; taxes and, 25, 31, 188–191; time inconsistency and, 32, 191, 193, 199; uncertainty and, 31, 61, 101, 163, 199 wage protection, 159 Wallace, Robert, 45 wealth: credit markets and, 108, 110, 111n2, 133, 140; discretionary income and, 100, 105, 108–115, 118, 138, 140, 142, 196; historical perspective on, 56; mobility and, 49, 66, 68, 189, 191–192, 200; private markets and, 70, 97, 100; public system and, 15; savings and, 1, 7–8, 17, 20–21, 29, 33–36, 46–47, 51, 66, 96– 97, 114–117, 133, 136, 141, 160, 180, 190, 193; self-insurance and, 11–12, 20–22, 50n2, 51, 57, 60, 67, 73, 93, 190, 192 Webster, Alexander, 45 welfare: Bismarckian, 52–53, 58, 67, 191, 199–201; credit markets and, 105, 108– 115, 131–138, 140; democracy and, 8; destitution and, 45, 67; discretionary income and, 110–111; elderly and, 4, 7–8, 13–14, 18, 33, 53–54, 58, 105, 188, 193, 199; Golden Age of, 54; historical perspective on, 44–58, 68–69; homeownership and, 131–138; information and, 2–14; loans and, 110–111, 113–115, 131–138; middle class and, 6, 8, 13, 15, 54, 68–69, 193– 195, 199; mutual aid societies (MASs) and, 6, 8, 10, 12–13, 15–16, 25, 48, 51– 52, 54, 56; partisanship and, 12; pay-asyou-go (PAYG) systems and, 16, 18, 33, 48, 53, 193; preferences and, 2, 9, 12, 18, 21, 30, 37, 39, 68, 203; private markets and, 19, 37–38, 70; public system and, 19; redistribution and, 6, 12, 16, 18, 21, 36, 38, 53, 56, 58, 68, 115, 188, 191, 197, 203; regulation and, 37–38; risk and, 2, 6–30, 33, 36–39, 48, 51–58, 68–69, 105, 108–109, 115, 138, 140, 188, 191, 193, 197, 201, 203; role of, 188; segmentation and, 8, 18, 52–53, 188; solidarity and, 8, 18, 40n21, 201, 203; theoretical model and, 15–25, 30–33, 36–40; uncertainty and, 8, 13, 36, 56, 189, 191 Westcott, Edward Noyes, 108 Wiedemann, Andreas, 109 Wienk, Ron, 116n7 Willen, Paul, 120–121 World Health Organization (WHO), 86, 93 World War II era, 4, 30, 36, 51, 189 younger generation: deductibles and, 17; health and, 4, 6–7, 13, 17–18, 30–31, 48, 56, 67, 86, 92, 96, 101, 193–195; health savings plans and, 7, 17, 33, 96; market feasibility and, 16–18, 30–35; pay-asyou-go (PAYG) systems and, 16, 18, 31, 33, 47–48, 56, 64, 67, 96, 193; private markets and, 84–86, 92, 96–97, 101; redistribution and, 16, 30, 64; support of elderly by, 4; time-inconsistency and, 6–7, 16–18, 30–35, 47–48, 56, 96, 190, 193; transfers and, 6–7, 13, 16, 30, 47–48, 56, 67, 96, 190 https://doi.org/10.1017/9781009151405.009 Published online by Cambridge University Press CAMBRIDGE STUDIES IN COMPARATIVE POLITICS Other Books in the Series (continued from page ii) Laia Balcells, Rivalry and Revenge: The Politics of Violence during Civil War Lisa Baldez, Why Women Protest?

The Coming Wave: Technology, Power, and the Twenty-First Century's Greatest Dilemma by Mustafa Suleyman

"World Economic Forum" Davos, 23andMe, 3D printing, active measures, Ada Lovelace, additive manufacturing, agricultural Revolution, AI winter, air gap, Airbnb, Alan Greenspan, algorithmic bias, Alignment Problem, AlphaGo, Alvin Toffler, Amazon Web Services, Anthropocene, artificial general intelligence, Asilomar, Asilomar Conference on Recombinant DNA, ASML, autonomous vehicles, backpropagation, barriers to entry, basic income, benefit corporation, Big Tech, biodiversity loss, bioinformatics, Bletchley Park, Blitzscaling, Boston Dynamics, business process, business process outsourcing, call centre, Capital in the Twenty-First Century by Thomas Piketty, ChatGPT, choice architecture, circular economy, classic study, clean tech, cloud computing, commoditize, computer vision, coronavirus, corporate governance, correlation does not imply causation, COVID-19, creative destruction, CRISPR, critical race theory, crowdsourcing, cryptocurrency, cuban missile crisis, data science, decarbonisation, deep learning, deepfake, DeepMind, deindustrialization, dematerialisation, Demis Hassabis, disinformation, drone strike, drop ship, dual-use technology, Easter island, Edward Snowden, effective altruism, energy transition, epigenetics, Erik Brynjolfsson, Ernest Rutherford, Extinction Rebellion, facts on the ground, failed state, Fairchild Semiconductor, fear of failure, flying shuttle, Ford Model T, future of work, general purpose technology, Geoffrey Hinton, global pandemic, GPT-3, GPT-4, hallucination problem, hive mind, hype cycle, Intergovernmental Panel on Climate Change (IPCC), Internet Archive, Internet of things, invention of the wheel, job automation, John Maynard Keynes: technological unemployment, John von Neumann, Joi Ito, Joseph Schumpeter, Kickstarter, lab leak, large language model, Law of Accelerating Returns, Lewis Mumford, license plate recognition, lockdown, machine readable, Marc Andreessen, meta-analysis, microcredit, move 37, Mustafa Suleyman, mutually assured destruction, new economy, Nick Bostrom, Nikolai Kondratiev, off grid, OpenAI, paperclip maximiser, personalized medicine, Peter Thiel, planetary scale, plutocrats, precautionary principle, profit motive, prompt engineering, QAnon, quantum entanglement, ransomware, Ray Kurzweil, Recombinant DNA, Richard Feynman, Robert Gordon, Ronald Reagan, Sam Altman, Sand Hill Road, satellite internet, Silicon Valley, smart cities, South China Sea, space junk, SpaceX Starlink, stealth mode startup, stem cell, Stephen Fry, Steven Levy, strong AI, synthetic biology, tacit knowledge, tail risk, techlash, techno-determinism, technoutopianism, Ted Kaczynski, the long tail, The Rise and Fall of American Growth, Thomas Malthus, TikTok, TSMC, Turing test, Tyler Cowen, Tyler Cowen: Great Stagnation, universal basic income, uranium enrichment, warehouse robotics, William MacAskill, working-age population, world market for maybe five computers, zero day

That is, the price dropped a millionfold in under twenty years, a thousand times faster than Moore’s law. A stunning development hiding in plain sight. Genome sequencing is now a booming business. In time it seems likely that the majority of people, plants, animals, and everything in between will have their genomes sequenced. Services like 23andMe already offer DNA profiling of individuals for a few hundred dollars. But the power of biotech goes far beyond our ability to simply read the code; it now enables us to edit it, and write it, too. CRISPR gene editing (the acronym stands for clustered regularly interspaced short palindromic repeats) is perhaps the best-known example of how we can directly intervene in genetics.

…

See authoritarianism; surveillance traffic optimization, 98 transcriptors, 88 transformers, 64, 90–91 transistor, 32–33, 67 Treaty on the Non-proliferation of Nuclear Weapons (1968), 43, 263 Tsar Bomba, 42 Tsinghua University, 121 TSMC, 251 Turing, Alan, 35, 75 23andMe, 81 2001: A Space Odyssey, 110 U Uighur ethnic cleansing, 195 Ukraine, 44, 103–4, 161–62 Unabomber, 213 United States export controls, 249–50 international cooperation and, 265–66 surveillance, 195 universal basic income (UBI), 262 University of Oxford, 101 Urban II (pope), 39 urbanization, technology waves and, 27–28 U.S.

The Great Experiment: Why Diverse Democracies Fall Apart and How They Can Endure by Yascha Mounk

23andMe, affirmative action, basic income, centre right, coronavirus, COVID-19, critical race theory, Donald Trump, failed state, global pandemic, illegal immigration, income inequality, language acquisition, Mahatma Gandhi, meta-analysis, Milgram experiment, Peter Singer: altruism, phenotype, Republic of Letters, Ronald Reagan, Steven Pinker, theory of mind, transatlantic slave trade, universal basic income, unpaid internship, World Values Survey

In many cases, members of today’s ethnic groups also share a common lineage. To the best of our knowledge, for example, Jews and Zoroastrians really are descended from the small bands of people who first took on these identities thousands of years ago. And if you send a small vial with your spit as well as a payment of $99 to the friendly folks at 23andMe, they will be able to create a pretty chart that informs you that you are, say, 75 percent West African, 10 percent South Asian, 10 percent Oceanian, and 5 percent southern European. (It will also tell you whether you are 100 percent Homo sapiens or have a little Neanderthal blood coursing through your veins.)

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See also authoritarianism Tower Hamlets, 159 town councils, 157 traditionalism, 106, 123 traditional societies, 114 transfers of wealth, 260 trends, cultural, 197–98 tribalism, 26, 33–35, 46, 49, 55, 57, 226, 302n44, 303n46, 304n57 Trieste, Italy, 13 Trump, Donald election loss to Biden, 244, 273 racist and anti-immigrant rhetoric, 172–74, 217–18, 220, 274, 283, 298n14 and rise of authoritarianism, 21 and rise of far-right politics, 14, 128, 201 and US demographic dynamics, 242–45 Tumbukas, 42–45, 302n44 Turkey, 110–11, 115 23andMe, 36–37 tyranny of the majority, 119. See also majority rule/dominance U Uganda, 45, 134 unemployment insurance, 260 Unione Party (Italy), 269 United Arab Emirates, 306n68 United Kingdom.

The Power Law: Venture Capital and the Making of the New Future by Sebastian Mallaby

"Susan Fowler" uber, 23andMe, 90 percent rule, Adam Neumann (WeWork), adjacent possible, Airbnb, Apple II, barriers to entry, Ben Horowitz, Benchmark Capital, Big Tech, bike sharing, Black Lives Matter, Blitzscaling, Bob Noyce, book value, business process, charter city, Chuck Templeton: OpenTable:, Clayton Christensen, clean tech, cloud computing, cognitive bias, collapse of Lehman Brothers, Colonization of Mars, computer vision, coronavirus, corporate governance, COVID-19, cryptocurrency, deal flow, Didi Chuxing, digital map, discounted cash flows, disruptive innovation, Donald Trump, Douglas Engelbart, driverless car, Dutch auction, Dynabook, Elon Musk, Fairchild Semiconductor, fake news, family office, financial engineering, future of work, game design, George Gilder, Greyball, guns versus butter model, Hacker Ethic, Henry Singleton, hiring and firing, Hyperloop, income inequality, industrial cluster, intangible asset, iterative process, Jeff Bezos, John Markoff, junk bonds, Kickstarter, knowledge economy, lateral thinking, liberal capitalism, Louis Pasteur, low interest rates, Lyft, Marc Andreessen, Mark Zuckerberg, market bubble, Marshall McLuhan, Mary Meeker, Masayoshi Son, Max Levchin, Metcalfe’s law, Michael Milken, microdosing, military-industrial complex, Mitch Kapor, mortgage debt, move fast and break things, Network effects, oil shock, PalmPilot, pattern recognition, Paul Graham, paypal mafia, Peter Thiel, plant based meat, plutocrats, power law, pre–internet, price mechanism, price stability, proprietary trading, prudent man rule, quantitative easing, radical decentralization, Recombinant DNA, remote working, ride hailing / ride sharing, risk tolerance, risk/return, Robert Metcalfe, ROLM, rolodex, Ronald Coase, Salesforce, Sam Altman, Sand Hill Road, self-driving car, shareholder value, side project, Silicon Valley, Silicon Valley startup, Skype, smart grid, SoftBank, software is eating the world, sovereign wealth fund, Startup school, Steve Jobs, Steve Wozniak, Steven Levy, super pumped, superconnector, survivorship bias, tech worker, Teledyne, the long tail, the new new thing, the strength of weak ties, TikTok, Travis Kalanick, two and twenty, Uber and Lyft, Uber for X, uber lyft, urban decay, UUNET, vertical integration, Vilfredo Pareto, Vision Fund, wealth creators, WeWork, William Shockley: the traitorous eight, Y Combinator, Zenefits

Most of the modern Sequoia’s venture triumphs can be traced to this sort of systematic work, put in place in the first years of the new century. By recruiting the young Roelof Botha and deliberately building his credentials, Sequoia laid the groundwork for billions of dollars of profits. After his wins in YouTube and Xoom, Botha followed up with a string of grand slams: the fintech company Square, the genetics testing outfits Natera and 23andMe, the social-media hit Instagram, and the database innovator MongoDB. When Forbes published its Midas List in April 2020, Botha ranked third. Five months later, he celebrated the stock market debut of the 3-D software platform Unity and a gain for Sequoia of more than $6 billion. A skeptic might object that this story sounds too simple.

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It could be inventing a new kind of burger (Impossible Foods), a new way of selling eyeglasses (Warby Parker), a fashion concept (Stitch Fix, Rent the Runway), a virtual-reality headset (Oculus), a fitness tracker (Fitbit), an affordable smartphone (Xiaomi), a scooter- and bike-rental service (Lime), a genetics-testing service (23andMe), medical robots (Auris Health), a mental wellness service (Lyra Health), a payments service for merchants (Stripe, Square), or a consumer bank (Revolut, Monzo). Inevitably, there will always be critics who object that venture capitalists could allocate society’s resources in some better way. But these critics’ subjective priorities could be interrogated, too, and it is not as though all non-venture-backed businesses are virtuous.

…

See Facebook Theranos, 339–42 Thiel, Peter, 198–215 Facebook and, 198, 199, 207, 208–9 Founders Fund, 208–15, 291, 296, 358, 403, 444n, 445n Musk and, 205–6, 211, 214–15 opposition to VC mentoring, 209–11, 290 PayPal, 198, 201–4, 206–9, 211, 214, 444n power law and, 8, 9, 209, 210–11, 221, 277 Stripe investment, 378, 455n 3Com, 100–107, 114, 138, 390 Tickle, 252 Tiger Global, 278–88, 337 Baidu, 452n Ctrip, 285–86, 448n DST, 276–77, 287, 452n Facebook, 273–78, 288, 452n hedge fund/venture hybrid model, 283–86, 299–300, 326, 378 Private Investment Partners fund, 284–86 SenseTime, 393 Sina, Sohu, and NetEase, 279–82 Tiger Management, 278, 281, 337 TikTok, 248, 388 Tilbury, Charlotte, 332 Time (magazine), 12, 20, 150, 339 Tokopedia, 324 Torvalds, Linus, 20 Toshiba, 94 Toys “R” Us, 64 TPG Capital, 358, 360 Traitorous Eight, 17–18, 21, 25, 28, 31–39, 53, 67, 423n Treybig, Jimmy, 69–72, 86, 102 T. Rowe Price, 289, 346, 349 Trump, Donald, 402, 403 Tsai, Joe, 226–27, 228–29, 232–33 Tsinghua University, 238, 242 Tung, Hans, 225 23andMe, 313, 383 Twilio, 333 Twitter, 12, 211, 298, 307, 385, 452n TX-0 (computer), 19, 28 Tyson, Mike, 347 U Uber, 349–71 Andreessen Horowitz’s investment, 353–55, 378 Benchmark Capital’s investment, 172, 349–56, 358–71, 372, 380, 440n, 458n, 459n blitzscaling, 357–59, 362, 364, 385, 387 in China, 362–63, 364 Didi Kuaidi, 362, 363, 364, 459n Founders Fund and, 211, 444n Greyball, 365–66, 369, 459n Gurley’s attack and resignation of Kalanick, 366–69 Gurley’s critique of, 361–63, 373 IPO, 372–73 Menlo Ventures investment, 354, 355–57, 368 Son’s investment, 370–71 toxic culture of, 360, 365–66 UberX, 357–58 Ungermann, Ralph, 107–8 Ungermann-Bass, 107–8, 113, 129, 203, 432n unicorns, 13–14, 289, 296, 303, 304, 372, 414 Gurley’s critique of, 361–63, 373, 458–59n WeWork, 342, 343, 346–47 Union Street Railway, 24 Unity, 309, 313 university endowments, 62, 416n Sequoia’s Heritage funds, 321, 333–36 University of California, San Francisco (UCSF), 73, 75 University of Chicago, 49 University of Illinois, 20, 144–45, 200, 237 University of Virginia, 216 Urban Decay, 117 Usenet, 436n UUNET, 132–44, 148, 175, 179, 286, 436n V Vacuum Foods, 25 Valentine, Donald, 60–66, 79–80, 97 Apple investment, 83–87, 90–91, 96, 160–61, 428n, 430n Atari investment, 62–63, 64–66, 80, 96, 379, 426n background of, 60–61 Botha and, 306 Capital Group, 425n, 426n Cisco investment, 113–19, 131, 158, 379, 435n Facebook investment, 194–95 founding of Sequoia, 60–62 fundraising, 61–62, 92, 394 Horowitz compared with, 296 retirement of, 160, 304 stage-by-stage financing, 60, 66, 80 Yahoo investment, 160 Vassallo, Trae, 269–70, 271 Veit, Stan, 82–83, 87 Venrock, 51, 71, 86–87, 88, 90–91, 229 venture boom, 93, 96–97, 111 venture-capital mindset, 14 “venture capital,” use of term, 418n venture hubs, 15, 18, 95–96, 391–92 Viaweb, 191–92, 217, 218–19 viral marketing, 443n Vivendi, 159 VKontakte, 274–475, 287 volatility selling, 415n W Waite, Charles P., 31 Walker’s Wagon Wheel, 54, 96, 106, 432n Wall Street Crash of 1929, 24 Wall Street Journal, 226, 296, 339 Walmart, 12 Wang, Jeff, 332–33 Wang Laboratories, 423–24n Wang Xing, 242–48 Warner Communications, 66, 80 Washington Post, 182, 402 Washington Post Company, 188, 258–60 weak ties, 95 WEB, 203 Webvan, 178, 184 Weinreich, Andrew, 20 Welch, Jack, 364 Wellfleet Communications, 112, 118 West, Donda, 235 West, Kanye, 235 WestBridge Capital, 321 Western Association of Venture Capitalists, 27, 51, 419n WeWork, 342–49, 371–73, 457n Benchmark Capital’s investment, 172, 342–49, 353, 371–72, 457n governance and corruption issues, 343, 344–45, 359 IPO process, 372–73 JPMorgan Chase’s investment, 343–44 Son’s investment, 346–49, 370–73 super-voting rights, 344, 346, 359, 371–72, 373 Wharton School, 161, 244, 287, 290 WhatsApp, 304, 307–8, 314, 388 white-hot risks, 70, 75, 76, 80, 88, 128, 266, 383 Whitman, Meg, 167–69 Whitney, John Hay, 25–26, 29, 418n Wikipedia, 317 wild-man risk, 59 Wilson Sonsini Goodrich & Rosati, 329 Wirehog, 195, 196, 207, 219, 254, 260 Wolfe, Josh, 382–83 Wolfe, Tom, 52–53, 56, 57 Wolff, Stephen S., 436n World War II, 18, 25, 28 World Wide Web, 19–20 Wozniak, Steve, 82–85, 86, 90, 100 Wu, John, 232–33 X X.com, 201–7 Xerox’s Palo Alto Research Center (PARC), 82, 96, 99, 100 Xiaomi, 224, 383 Xi Jinping, 302–3, 395 Xoom, 306, 313 Xu, Kathy, 235–37, 239, 245–46, 279 Y Yahoo, 149–61 Draper and, 150, 152, 341 Google and, 181 IPO, 156, 157, 438n, 439n sales and marketing, 153–54, 438n Sequoia Capital’s investment, 150–54, 155–56, 160–61, 170, 173, 206, 440n Son’s investment, 155–60, 175, 277, 347, 348, 439n Viaweb acquisition, 191 Yahoo Japan, 159 Yale Law School, 226 Yale University, 150, 225, 226, 334 Yandex, 287 Yang, Jerry, 150–60.

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

23andMe, 3D printing, Abraham Maslow, additive manufacturing, AI winter, Albert Einstein, Amazon Mechanical Turk, Amazon Robotics, Amazon Web Services, Andrew Keen, Atul Gawande, Automated Insights, autonomous vehicles, Big bang: deregulation of the City of London, big data - Walmart - Pop Tarts, Bill Joy: nanobots, Blue Ocean Strategy, business process, business process outsourcing, Cass Sunstein, Checklist Manifesto, Clapham omnibus, Clayton Christensen, clean water, cloud computing, commoditize, computer age, Computer Numeric Control, computer vision, Computing Machinery and Intelligence, conceptual framework, corporate governance, creative destruction, crowdsourcing, Daniel Kahneman / Amos Tversky, data science, death of newspapers, disintermediation, Douglas Hofstadter, driverless car, en.wikipedia.org, Erik Brynjolfsson, Evgeny Morozov, Filter Bubble, full employment, future of work, Garrett Hardin, Google Glasses, Google X / Alphabet X, Hacker Ethic, industrial robot, informal economy, information retrieval, interchangeable parts, Internet of things, Isaac Newton, James Hargreaves, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joseph Schumpeter, Khan Academy, knowledge economy, Large Hadron Collider, lifelogging, lump of labour, machine translation, Marshall McLuhan, Metcalfe’s law, Narrative Science, natural language processing, Network effects, Nick Bostrom, optical character recognition, Paul Samuelson, personalized medicine, planned obsolescence, pre–internet, Ray Kurzweil, Richard Feynman, Second Machine Age, self-driving car, semantic web, Shoshana Zuboff, Skype, social web, speech recognition, spinning jenny, strong AI, supply-chain management, Susan Wojcicki, tacit knowledge, TED Talk, telepresence, The Future of Employment, the market place, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Tragedy of the Commons, transaction costs, Turing test, Two Sigma, warehouse robotics, Watson beat the top human players on Jeopardy!, WikiLeaks, world market for maybe five computers, Yochai Benkler, young professional

Researchers are creeping towards printing entire organs.46 This matters—on average, twenty-one people a day die in the United States, and just under three in the United Kingdom, waiting for spare organs.47 Increasing computational power has meant that certain fields, previously conceivable in theory but impossible in practice, are now thriving. Genomics, the science of scanning a patient’s DNA to personalize medical treatment and anticipate future disease, is one example. In 2007 it would have cost around $10 million to read a human genome. Now it costs a few thousand dollars.48 Companies like 23andMe, Navigenics, and deCODE offer commercial testing services from $99.49 In the field of ‘genome editing’, scientists search for problematic genes and actively intervene to change or remove them. Nanomedicine, the use of nanotechnology in a medical setting, is another field. Nobel Laureate Richard Feynman’s seventy-year-old prediction that we might one day ‘swallow the surgeon’50 has come true—there are already small nanobots that are able to swim through our bodies, relaying images, delivering targeted drugs, and attacking particular cells with a precision that makes even the finest of surgeons’ blades look blunt.

…

., ‘Hydrogel bioprinted microchannel networks for vascularization of tissue engineering constructs’, Lab on a Chip, 14: 13 (2014), 2202–11. 47 <http://www.organdonor.gov> and ‘Fact Sheets: Transplants save lives’, NHS website, Aug. 2014 <http://www.organdonation.nhs.uk/newsroom/fact_sheets/transplants_save_lives.asp> (accessed 9 March 2015). 48 Erika Check Hayden, ‘Technology: The $1,000 Genome’, Nature, 19 Mar. 2014. 49 Francis S. Collins, The Language of Life: DNA and the Revolution in Personalized Medicine (2010), p. xviii discusses the services, but their costs are now far lower. See e.g. the $99 service at <https://www.23andme.com> (accessed 27 March 2015). 50 Richard P. Feynman, ‘Plenty of Room at the Bottom’, talk to the American Physical Society at Caltech, Dec. 1959, p. 5 <http://www.pa.msu.edu/~yang/RFeynman_plentySpace.pdf> (accessed 27 March 2015). 51 Miguel Helft, ‘Google’s Larry Page: The Most Ambitious CEO in the Universe’, Fortune Magazine, 13 Nov. 2014 <http://fortune.com> (accessed 27 March 2015). 52 David L.

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

In Los Angeles, Smith: Jordan Valinsky, “Vice’s Shane Smith: ‘Expect a Bloodbath’ in Media within the Next Year,” Digiday, May 20, 2016, https://digiday.com/media/shane-smith-vice-media-interview/. On Election Night he hosted: Shane Smith, interviewed by Jill Abramson, Manhattan, August 4, 2017. She did one story: Elspeth Reeve, “Alt-Right Trolls Are Getting 23andMe Genetic Tests to ‘Prove’ Their Whiteness,” Vice News, October 9, 2016, https://news.vice.com/en_us/article/vbygqm/alt-right-trolls-are-getting-23andme-genetic-tests-to-prove-their-whiteness. After the election, the sideshow: Vice News, “Control Alt Elite: Inside America’s Racist ‘Alt-Right,’ ” Vice, December 7, 2016, https://www.vice.com/en_id/article/mgv9nn/control-alt-elite-inside-americas-racist-alt-right.

…

Though their reporters mostly hadn’t used conventional political reporting methods, they had developed contacts in areas sometimes overlooked by their conventional, old-media competitors. Reeve had smartly used her tech-culture beat to cultivate sources on the alt-right, monitoring them on 4chan and other dark corners of the web. She did one story on how some members of the alt-right used the genetic research firm 23andMe to prove the ethnic purity of their whiteness, and interviewed the white nationalist Richard Spencer, whose supporters were known to shout “Sieg Heil” with a Nazi salute. After the election, the sideshow of radical right-wingers moved to center stage, and Vice was well-positioned to cover their story.

100 Things We've Lost to the Internet by Pamela Paul

2021 United States Capitol attack, 23andMe, Big Tech, coronavirus, COVID-19, emotional labour, financial independence, Google Earth, Jaron Lanier, John Perry Barlow, Kickstarter, lock screen, Lyft, Mark Zuckerberg, Minecraft, off-the-grid, pre–internet, QR code, QWERTY keyboard, rolodex, Rubik’s Cube, Silicon Valley, Snapchat, TaskRabbit, telemarketer, TikTok, trickle-down economics, Uber and Lyft, uber lyft, Wall-E

Too many people you know will want to keep the dead alive, posting condolences and, later, memories, and still later, death anniversaries, an eternal scroll of grief. Everyone sits Shiva indefinitely and the wake goes on, and on. Perhaps it’s not possible to close the book entirely on another human being. Lost cousins reach out courtesy of Ancestry and 23andMe, and a distant relative you cut ties with decisively decades ago DMs you on Twitter. During a late-night deep dive, you may discover your father had another family before he had yours. The face of the guy who date-raped you in college can pop up as Someone You Might Know. The racist boss from your first job will be promoted yet again on LinkedIn.

Editing Humanity: The CRISPR Revolution and the New Era of Genome Editing by Kevin Davies

23andMe, Airbnb, Anne Wojcicki, Apple's 1984 Super Bowl advert, Asilomar, bioinformatics, California gold rush, clean water, coronavirus, COVID-19, CRISPR, crowdsourcing, discovery of DNA, disinformation, Doomsday Clock, double helix, Downton Abbey, Drosophila, Edward Jenner, Elon Musk, epigenetics, fake news, Gregor Mendel, Hacker News, high-speed rail, hype cycle, imposter syndrome, Isaac Newton, John von Neumann, Kickstarter, life extension, Mark Zuckerberg, microbiome, Mikhail Gorbachev, mouse model, Neil Armstrong, New Journalism, ocean acidification, off-the-grid, personalized medicine, Peter Thiel, phenotype, QWERTY keyboard, radical life extension, RAND corporation, Recombinant DNA, rolodex, scientific mainstream, Scientific racism, seminal paper, Shenzhen was a fishing village, side project, Silicon Valley, Silicon Valley billionaire, Skype, social distancing, stem cell, Stephen Hawking, Steve Jobs, Steven Pinker, Stewart Brand, synthetic biology, TED Talk, the long tail, Thomas Kuhn: the structure of scientific revolutions, Thomas Malthus, traumatic brain injury, warehouse automation

The two women have shared the “Nobel Prizes” of Japan, Spain, Israel, and Canada (with Zhang), to name a few. The most lucrative award was the Breakthrough Prize, created by Silicon Valley billionaires including Priscilla Chan and Mark Zuckerberg (Facebook), Sergey Brin (Google) and his ex-wife Anne Wojcicki (23andMe), and Dick Costolo (Twitter). At a black-tie awards ceremony in November 2014, Doudna and Charpentier received their awards from Hollywood actress Cameron Diaz. Charpentier flashed her Gallic humor on stage. “It’s kind of surreal to receive the prize from Cameron,” she said, then turned to Costolo: “Three powerful women… I was just wondering if you’re Charlie?”

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See also RNA Transthyretin amyloidosis (TTR), 174 Trebeck, Alex, 179 Treff, Nathan, 350 Trinity College, 29 Triplet Therapeutics, 175 Tropic Biosciences, 312 Tsinghua University, 79 Tsui, Lap-Chee, 231–232 Tudge, Colin, 48 Tufts University, 51 Turnbull, Douglas, 213–215 Twain, Mark, 108 23andMe, 95 Twort, Frederick, 162 U UCSF Benioff Children’s Hospital, 120 UK Biobank, 249, 351 Umeå University, 61 “Unite to Cure,” 12 University College London, 252, 360 University of Alicante, 31 University of Bristol, 249 University of California, 127, 179–190, 293, 317, 346, 359 University of Chicago, 347 University of Edinburgh, 27, 257 University of Georgia, 56 University of Hawaii, 47 University of Hong Kong, 231, 267 University of Illinois, 190 University of Leicester, xi University of Massachusetts, 50, 164, 180, 247 University of Minnesota, 302 University of Missouri, 318 University of New South Wales, 153 University of Newcastle, 213 University of Oslo, 8 University of Pennsylvania, 119, 135, 140, 147, 166, 195 University of Pittsburgh, 163, 196 University of Science and Technology of China, 206–207, 209 University of Strasbourg, 39 University of Sydney, 232 University of Texas, 175, 345 University of Tokyo, 26 University of Utah, 107, 113 University of Vienna, 60–61, 180–190, 184 University of Wisconsin, 107 Uppsala University, 27 Urnov, Fyodor, xvi, xvii, xviii, 16, 19–20, 67, 105–116, 197, 261, 265, 335, 338–339, 365 U.S.

Data-Ism: The Revolution Transforming Decision Making, Consumer Behavior, and Almost Everything Else by Steve Lohr

"World Economic Forum" Davos, 23andMe, Abraham Maslow, Affordable Care Act / Obamacare, Albert Einstein, Alvin Toffler, Bear Stearns, behavioural economics, big data - Walmart - Pop Tarts, bioinformatics, business cycle, business intelligence, call centre, Carl Icahn, classic study, cloud computing, computer age, conceptual framework, Credit Default Swap, crowdsourcing, Daniel Kahneman / Amos Tversky, Danny Hillis, data is the new oil, data science, David Brooks, driverless car, East Village, Edward Snowden, Emanuel Derman, Erik Brynjolfsson, everywhere but in the productivity statistics, financial engineering, Frederick Winslow Taylor, Future Shock, Google Glasses, Ida Tarbell, impulse control, income inequality, indoor plumbing, industrial robot, informal economy, Internet of things, invention of writing, Johannes Kepler, John Markoff, John von Neumann, lifelogging, machine translation, Mark Zuckerberg, market bubble, meta-analysis, money market fund, natural language processing, obamacare, pattern recognition, payday loans, personalized medicine, planned obsolescence, precision agriculture, pre–internet, Productivity paradox, RAND corporation, rising living standards, Robert Gordon, Robert Solow, Salesforce, scientific management, Second Machine Age, self-driving car, Silicon Valley, Silicon Valley startup, SimCity, six sigma, skunkworks, speech recognition, statistical model, Steve Jobs, Steven Levy, The Design of Experiments, the scientific method, Thomas Kuhn: the structure of scientific revolutions, Tony Fadell, unbanked and underbanked, underbanked, Von Neumann architecture, Watson beat the top human players on Jeopardy!, yottabyte

At Mount Sinai, they are sequencing entire genomes—looking at all three billion nucleotides, the basic structural unit of DNA. Within that deluge of nucleotides, scientists have identified about ten million DNA segments called SNPs (pronounced snips), for single nucleotide polymorphisms, that have been linked to diseases in research studies. Consumer gene-testing services, like 23andMe, look at fewer than a million SNPs. At Mount Sinai, the ambitions are larger. They want to see the whole picture, the entire genome sequenced. To really advance research and treatments at Mount Sinai, it will have to do a lot of it, very quickly. The goal, Kovatch says, is to compress the time it takes from days down to an hour.

In the Plex: How Google Thinks, Works, and Shapes Our Lives by Steven Levy

"World Economic Forum" Davos, 23andMe, AltaVista, Andy Rubin, Anne Wojcicki, Apple's 1984 Super Bowl advert, autonomous vehicles, Bill Atkinson, book scanning, Brewster Kahle, Burning Man, business process, clean water, cloud computing, crowdsourcing, Dean Kamen, discounted cash flows, don't be evil, Donald Knuth, Douglas Engelbart, Douglas Engelbart, Dutch auction, El Camino Real, Evgeny Morozov, fault tolerance, Firefox, General Magic , Gerard Salton, Gerard Salton, Google bus, Google Chrome, Google Earth, Googley, high-speed rail, HyperCard, hypertext link, IBM and the Holocaust, informal economy, information retrieval, Internet Archive, Jeff Bezos, John Markoff, Ken Thompson, Kevin Kelly, Kickstarter, large language model, machine translation, Mark Zuckerberg, Menlo Park, one-China policy, optical character recognition, PageRank, PalmPilot, Paul Buchheit, Potemkin village, prediction markets, Project Xanadu, recommendation engine, risk tolerance, Rubik’s Cube, Sand Hill Road, Saturday Night Live, search inside the book, second-price auction, selection bias, Sheryl Sandberg, Silicon Valley, SimCity, skunkworks, Skype, slashdot, social graph, social software, social web, spectrum auction, speech recognition, statistical model, Steve Ballmer, Steve Jobs, Steven Levy, subscription business, Susan Wojcicki, Ted Nelson, telemarketer, The future is already here, the long tail, trade route, traveling salesman, turn-by-turn navigation, undersea cable, Vannevar Bush, web application, WikiLeaks, Y Combinator

Many cheeky activities that had once seemed so refreshing began to assume an aura of calculation when they became routine. How many scavenger hunts can you attend before it becomes a chore? Page and Brin themselves had grown in the decade since they founded Google. Both were now married and within a year of each other fathered sons. Brin’s wife, Anne Wojcicki, was a cofounder of 23andMe, a company involved in personal DNA analysis. Brin defied corporate propriety when he shifted his personal investment in the firm to a company one. Google’s lawyers made sure the transaction passed formal muster. The normally gregarious Brin could turn icy when an unfamiliar person referred to his private life—for example, when a reporter offered congratulations at a Q and A at the Googleplex soon after his wedding, he changed the subject without acknowledging the remark.

…

Brin put aside talk of commerce to explain that he had examined his own genome with the help of his wife’s DNA-testing enterprise. Since his mother, Eugenia, had previously been diagnosed with Parkinson’s disease, he had looked specifically for an anomaly on the genetic location known as LRRK2—and discovered a mutation known as G2019S, associated with Parkinson’s. His mother, also a 23andMe customer, had the same mutation. (“She’s okay,” he assured everyone. “She skis.”) Brin immediately began researching the implications of this signal; “I found it fairly empowering,” he said. He also became involved with charities trying to find a cure for Parkinson’s, such as the Michael J. Fox Foundation.

Tribe of Mentors: Short Life Advice From the Best in the World by Timothy Ferriss

"World Economic Forum" Davos, 23andMe, A Pattern Language, agricultural Revolution, Airbnb, Albert Einstein, Alvin Toffler, Bayesian statistics, bitcoin, Black Lives Matter, Black Swan, blockchain, Brownian motion, Buckminster Fuller, Clayton Christensen, cloud computing, cognitive dissonance, Colonization of Mars, corporate social responsibility, cryptocurrency, David Heinemeier Hansson, decentralized internet, dematerialisation, do well by doing good, do what you love, don't be evil, double helix, driverless car, effective altruism, Elon Musk, Ethereum, ethereum blockchain, family office, fear of failure, Gary Taubes, Geoffrey West, Santa Fe Institute, global macro, Google Hangouts, Gödel, Escher, Bach, haute couture, helicopter parent, high net worth, In Cold Blood by Truman Capote, income inequality, index fund, information security, Jeff Bezos, job satisfaction, Johann Wolfgang von Goethe, Kevin Kelly, Lao Tzu, Larry Ellison, Law of Accelerating Returns, Lyft, Mahatma Gandhi, Marc Andreessen, Marc Benioff, Marshall McLuhan, Max Levchin, Mikhail Gorbachev, minimum viable product, move fast and break things, Mr. Money Mustache, Naomi Klein, Neal Stephenson, Nick Bostrom, non-fiction novel, Peter Thiel, power law, profit motive, public intellectual, Ralph Waldo Emerson, Ray Kurzweil, Salesforce, Saturday Night Live, Sheryl Sandberg, side project, Silicon Valley, Skype, smart cities, smart contracts, Snapchat, Snow Crash, Steve Jobs, Steve Jurvetson, Steven Pinker, Stewart Brand, sunk-cost fallacy, TaskRabbit, tech billionaire, TED Talk, Tesla Model S, too big to fail, Turing machine, uber lyft, Vitalik Buterin, W. E. B. Du Bois, web application, Whole Earth Catalog, Y Combinator

Esther Dyson TW: @edyson wellville.net ESTHER DYSON is the founder of HICCup and chairman of EDventure Holdings. Esther is an active angel investor, best-selling author, board member, and advisor concentrating on emerging markets and technologies, new space, and health. She sits on the boards of 23andMe and Voxiva (txt4baby), and is an investor in Crohnology, Eligible API, Keas, Omada Health, Sleepio, StartUp Health, and Valkee, among others. From October 2008 to March 2009, Esther lived in Star City outside Moscow, Russia, training as a backup cosmonaut. * * * What is the book (or books) you’ve given most as a gift, and why?

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., 289 Taleb, Nassim, 60 Talk therapy, 550 Task and distractions list, 542–43 TaskRabbit, 200 Tata Harper Fierce lip balm, 233 Taubes, Gary, 480 Technology, 213 disruptive, 222–23, 346 Moore’s Law for, 294–95 TED Conference, 407–8 Tesla, 42, 293 Therapy, 26–27, 81, 550 Theroux, Paul, 210 Thich Nhat Hanh, 235, 450 Thiel, Peter, 153 Thoreau, Henry David, 39, 140, 205, 463 Þórisdóttir, Anníe Mist, 305–7, 421 Thrive Global, 211 Thrive Global phone bed, 213–15 Thucydides, 6–7 Thumbtack, 31 Tile Mate key finder, 97 Tippett, Krista, 308 Tivoli Systems, 64 Tolstoy, Leo, 335 Tony Hawk Foundation, 298 Tony Hawk Signature Series, 298 Topic.com, 141 Top Ramen, 391 Torres, Dara, 390–91 Total Immersion, 440, 442, 443 Tradedoubler, 286 Transcendental Meditation, 80, 241, 242, 322, 380, 381, 489 Trickstutorials.com, 385 Truman, Harry, 206 Tumblr, 215 23andMe, 243 Twitch.tv, 64 Twitter, 31, 64, 215, 250, 401 Tyler, Aisha, 431–35 U Uber, 31, 37, 211, 215, 250, 347–48, 459, 461 Ulmer, Kristen, 546–53 Under Armour, 447 Union Square Hospitality Group (USHG), 371 Union Square Ventures, 492 Urban, Tim, 40–49, 495 USCF Memory and Aging Center, 296–97 V Valkee, 243 Van de Snepscheut, Jan L.

Raw Data Is an Oxymoron by Lisa Gitelman

23andMe, collateralized debt obligation, computer age, continuous integration, crowdsourcing, disruptive innovation, Drosophila, Edmond Halley, Filter Bubble, Firefox, fixed income, folksonomy, Google Earth, Howard Rheingold, index card, informal economy, information security, Isaac Newton, Johann Wolfgang von Goethe, knowledge worker, Large Hadron Collider, liberal capitalism, lifelogging, longitudinal study, Louis Daguerre, Menlo Park, off-the-grid, optical character recognition, Panopticon Jeremy Bentham, peer-to-peer, RFID, Richard Thaler, Silicon Valley, social graph, software studies, statistical model, Stephen Hawking, Steven Pinker, text mining, time value of money, trade route, Turing machine, urban renewal, Vannevar Bush, WikiLeaks

A dark vision is that our interaction with the world and each other is being rendered epiphenomenal to these data-program-data cycles. If it’s not in principle measurable, or is not being measured, it doesn’t exist. Thus in the natural world, we have largely as a species elected to take the quantifiable genome (https://www.23andme.com) as the measure of all life: when we save species (in seedbanks for example), we are saving irreducible genetic information—not communities (despite the fact that every individual comes with its own internal flora and fauna central to its survival; and that each individual can be understood equally as the product of a network of relationships).

Final Jeopardy: Man vs. Machine and the Quest to Know Everything by Stephen Baker

23andMe, AI winter, Albert Einstein, artificial general intelligence, behavioural economics, business process, call centre, clean water, commoditize, computer age, Demis Hassabis, Frank Gehry, information retrieval, Iridium satellite, Isaac Newton, job automation, machine translation, pattern recognition, Ray Kurzweil, Silicon Valley, Silicon Valley startup, statistical model, The Soul of a New Machine, theory of mind, thinkpad, Turing test, Vernor Vinge, vertical integration, Wall-E, Watson beat the top human players on Jeopardy!

Such analyses could save lives, Jasinski said. ”We kill a hundred thousand people a year from preventable medical errors.” In fact, the potential for next-generation computers in medicine stretches much further. Within a decade, it should cost less than $100 to have an individual’s entire genome sequenced. Some people will volunteer to have this done. (Already, companies like 23andMe, a Silicon Valley startup, charge people $429 for a basic decoding.) Others, perhaps, will find themselves pressed, or even compelled, by governments or insurers, to submit their saliva samples. In either case, computers will be studying, correlating, and answering questions about growing collections of this biological information.

The Pattern Seekers: How Autism Drives Human Invention by Simon Baron-Cohen

23andMe, agricultural Revolution, airport security, Albert Einstein, Apollo 11, Asperger Syndrome, assortative mating, autism spectrum disorder, bioinformatics, coronavirus, corporate social responsibility, correlation does not imply causation, COVID-19, David Attenborough, discovery of penicillin, Elon Musk, en.wikipedia.org, Fellow of the Royal Society, Greta Thunberg, intentional community, invention of agriculture, Isaac Newton, James Watt: steam engine, Jim Simons, lateral thinking, longitudinal study, Menlo Park, meta-analysis, neurotypical, out of africa, pattern recognition, phenotype, Rubik’s Cube, Silicon Valley, six sigma, Skype, social intelligence, Stephen Hawking, Steven Levy, Steven Pinker, systems thinking, theory of mind, twin studies, zero-sum game

But to claim that empathy and systemizing evolved, these psychological abilities must have had at least a partly genetic basis. To discover if genes play any part in empathy and systemizing we launched the ambitious Genetics of Empathizing and Systemizing Study. Working with the personal genomics company 23andMe, we asked their customers—who consent to their genetic data being shared anonymously with researchers—to take two empathy tests so we could look for genetic associations with individual differences in scores on the empathy tests. Eighty-eight thousand people who had provided their DNA took one of our empathy tests, the “Reading the Mind in the Eyes” test, or the “Eyes” test for short.23 Of these, 46,000 also took the other empathy test, the Empathy Quotient (EQ), and 50,000 took the Systemizing Quotient (SQ).

Big Business: A Love Letter to an American Anti-Hero by Tyler Cowen

"Friedman doctrine" OR "shareholder theory", 23andMe, Affordable Care Act / Obamacare, augmented reality, barriers to entry, Bernie Sanders, Big Tech, bitcoin, blockchain, Bretton Woods, cloud computing, cognitive dissonance, company town, compensation consultant, corporate governance, corporate social responsibility, correlation coefficient, creative destruction, crony capitalism, cryptocurrency, dark matter, David Brooks, David Graeber, don't be evil, Donald Trump, driverless car, Elon Musk, employer provided health coverage, experimental economics, Fairchild Semiconductor, fake news, Filter Bubble, financial innovation, financial intermediation, gentrification, Glass-Steagall Act, global reserve currency, global supply chain, Google Glasses, income inequality, Internet of things, invisible hand, Jeff Bezos, junk bonds, late fees, Mark Zuckerberg, mobile money, money market fund, mortgage debt, Network effects, new economy, Nicholas Carr, obamacare, offshore financial centre, passive investing, payday loans, peer-to-peer lending, Peter Thiel, pre–internet, price discrimination, profit maximization, profit motive, RAND corporation, rent-seeking, reserve currency, ride hailing / ride sharing, risk tolerance, Ronald Coase, shareholder value, Silicon Valley, Silicon Valley startup, Skype, Snapchat, Social Responsibility of Business Is to Increase Its Profits, Steve Jobs, The Nature of the Firm, Tim Cook: Apple, too big to fail, transaction costs, Tyler Cowen, Tyler Cowen: Great Stagnation, ultimatum game, WikiLeaks, women in the workforce, World Values Survey, Y Combinator

Still, every new technology does enable new kinds of crimes, and that is a growing worry, even if the innovating companies are not themselves morally at fault. Another potential problem could spring from genetic testing and the information embodied in those results. Right now, you can swab your cheek to get a DNA sample and send it in to a number of companies, most prominently 23andMe. They will send you back some information about yourself, including an assessment of your susceptibility to particular diseases (some legal restrictions have been placed on this), information about your ethnic background, and information about other people you are probably related to. That may involve some privacy issues, but so far it seems manageable; furthermore, the information held by the company has not (yet?)

Technical Blogging: Turn Your Expertise Into a Remarkable Online Presence by Antonio Cangiano

23andMe, Albert Einstein, anti-pattern, bitcoin, bounce rate, cloud computing, content marketing, en.wikipedia.org, Hacker News, John Gruber, Kickstarter, Lean Startup, lolcat, Network effects, Paradox of Choice, revision control, Ruby on Rails, search engine result page, slashdot, software as a service, web application

If you are creating this blog for a company, you don’t have to mimic the look of your main site and integrate your blog with the company site 100 percent. If you wish, you can make the blog a visually separate entity with a slightly different look and a greater degree of editorial freedom. An example of this approach can be seen at http://spittoon.23andme.com. Tip 10 Prominently link to your company site from your blog. Given that company budgets (even startup ones) are usually larger than what your typical solo bloggers have at their disposal, you may even consider having a designer create a custom theme and logo for your company blog. Another appealing option for those on a tighter budget is to heavily personalize one of the premium themes.

Exponential Organizations: Why New Organizations Are Ten Times Better, Faster, and Cheaper Than Yours (And What to Do About It) by Salim Ismail, Yuri van Geest

23andMe, 3D printing, Airbnb, Amazon Mechanical Turk, Amazon Web Services, anti-fragile, augmented reality, autonomous vehicles, Baxter: Rethink Robotics, behavioural economics, Ben Horowitz, bike sharing, bioinformatics, bitcoin, Black Swan, blockchain, Blue Ocean Strategy, book value, Burning Man, business intelligence, business process, call centre, chief data officer, Chris Wanstrath, circular economy, Clayton Christensen, clean water, cloud computing, cognitive bias, collaborative consumption, collaborative economy, commoditize, corporate social responsibility, cross-subsidies, crowdsourcing, cryptocurrency, dark matter, data science, Dean Kamen, deep learning, DeepMind, dematerialisation, discounted cash flows, disruptive innovation, distributed ledger, driverless car, Edward Snowden, Elon Musk, en.wikipedia.org, Ethereum, ethereum blockchain, fail fast, game design, gamification, Google Glasses, Google Hangouts, Google X / Alphabet X, gravity well, hiring and firing, holacracy, Hyperloop, industrial robot, Innovator's Dilemma, intangible asset, Internet of things, Iridium satellite, Isaac Newton, Jeff Bezos, Joi Ito, Kevin Kelly, Kickstarter, knowledge worker, Kodak vs Instagram, Law of Accelerating Returns, Lean Startup, life extension, lifelogging, loose coupling, loss aversion, low earth orbit, Lyft, Marc Andreessen, Mark Zuckerberg, market design, Max Levchin, means of production, Michael Milken, minimum viable product, natural language processing, Netflix Prize, NetJets, Network effects, new economy, Oculus Rift, offshore financial centre, PageRank, pattern recognition, Paul Graham, paypal mafia, peer-to-peer, peer-to-peer model, Peter H. Diamandis: Planetary Resources, Peter Thiel, Planet Labs, prediction markets, profit motive, publish or perish, radical decentralization, Ray Kurzweil, recommendation engine, RFID, ride hailing / ride sharing, risk tolerance, Ronald Coase, Rutger Bregman, Salesforce, Second Machine Age, self-driving car, sharing economy, Silicon Valley, skunkworks, Skype, smart contracts, Snapchat, social software, software is eating the world, SpaceShipOne, speech recognition, stealth mode startup, Stephen Hawking, Steve Jobs, Steve Jurvetson, subscription business, supply-chain management, synthetic biology, TaskRabbit, TED Talk, telepresence, telepresence robot, the long tail, Tony Hsieh, transaction costs, Travis Kalanick, Tyler Cowen, Tyler Cowen: Great Stagnation, uber lyft, urban planning, Virgin Galactic, WikiLeaks, winner-take-all economy, X Prize, Y Combinator, zero-sum game

While tech companies have long backed startups, their venture arms have a history of terribly subpar returns, mainly because there was no real independence from the parent company. Google Ventures has invested in more than 225 portfolio companies encompassing all stages and industry sectors, including such rising stars as Uber, Nest, 23andMe, Cloudera, Optimizely, TuneIn, Homejoy and High Fidelity. As a result of its many successes, Google Ventures opened a London office in 2014, with $100 million to invest in European startups. Although Google provides the funds for Google Ventures, invested companies don’t have to benefit Google. That means portfolio companies stay independent and can be acquired by competitors.

How to Fix the Future: Staying Human in the Digital Age by Andrew Keen

"World Economic Forum" Davos, 23andMe, Ada Lovelace, Affordable Care Act / Obamacare, Airbnb, Albert Einstein, AlphaGo, Andrew Keen, Apple's 1984 Super Bowl advert, augmented reality, autonomous vehicles, basic income, Bernie Sanders, Big Tech, bitcoin, Black Swan, blockchain, Brewster Kahle, British Empire, carbon tax, Charles Babbage, computer age, Cornelius Vanderbilt, creative destruction, crowdsourcing, data is the new oil, death from overwork, DeepMind, Demis Hassabis, Didi Chuxing, digital capitalism, digital map, digital rights, disinformation, don't be evil, Donald Trump, driverless car, Edward Snowden, Elon Musk, Erik Brynjolfsson, European colonialism, fake news, Filter Bubble, Firefox, fulfillment center, full employment, future of work, gig economy, global village, income inequality, independent contractor, informal economy, Internet Archive, Internet of things, invisible hand, Isaac Newton, James Watt: steam engine, Jane Jacobs, Jaron Lanier, Jeff Bezos, jimmy wales, job automation, Joi Ito, Kevin Kelly, knowledge economy, Lyft, Marc Andreessen, Marc Benioff, Mark Zuckerberg, Marshall McLuhan, Menlo Park, Mitch Kapor, move fast and break things, Network effects, new economy, Nicholas Carr, Norbert Wiener, OpenAI, Parag Khanna, peer-to-peer, Peter Thiel, plutocrats, post-truth, postindustrial economy, precariat, Ralph Nader, Ray Kurzweil, Recombinant DNA, rent-seeking, ride hailing / ride sharing, Rutger Bregman, Salesforce, Sam Altman, Sand Hill Road, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Silicon Valley billionaire, Silicon Valley ideology, Silicon Valley startup, Skype, smart cities, Snapchat, social graph, software is eating the world, Stephen Hawking, Steve Jobs, Steve Wozniak, subscription business, surveillance capitalism, Susan Wojcicki, tech baron, tech billionaire, tech worker, technological determinism, technoutopianism, The Future of Employment, the High Line, the new new thing, Thomas L Friedman, Tim Cook: Apple, Travis Kalanick, Triangle Shirtwaist Factory, Uber and Lyft, Uber for X, uber lyft, universal basic income, Unsafe at Any Speed, Upton Sinclair, urban planning, WikiLeaks, winner-take-all economy, Y Combinator, Yogi Berra, Zipcar

In 1998, when Larry Page and Sergei Brin founded Google as Stanford graduate students, Susan rented them space in her garage. Today Susan Wojcicki is the CEO of YouTube and among the most powerful entertainment moguls in the world. Her sister Janet is a professor of epidemiology at UC San Francisco. Anne, the youngest Wojcicki, is the cofounder and CEO of the gene mapping start-up 23andMe and was married to Google cofounder Sergei Brin. So Brin is Esther Wojcicki’s former son-in-law, and they remain, she tells me, on very friendly terms. We happen to meet on what one of Wojcicki’s students referred to as “moonshot day”—the day of the week when the Media Arts Center provides students with its facilities and resources to do their own special projects.

Overdiagnosed: Making People Sick in the Pursuit of Health by H. Gilbert Welch, Lisa M. Schwartz, Steven Woloshin

23andMe, classic study, do well by doing good, double helix, Google Earth, Gregor Mendel, invisible hand, it's over 9,000, life extension, longitudinal study, mandelbrot fractal, medical residency, meta-analysis, phenotype, placebo effect, randomized controlled trial, Ronald Reagan, sugar pill, The Wealth of Nations by Adam Smith

And gene therapy—treatment for a specific disease that involves altering DNA itself—could, in certain settings, prove to be a genuine medical cure. But genetic testing could just as easily be a road map to widespread ill health. Already, numerous commercial enterprises exist that will take your DNA (and your money) and tell you about your future. One such company, 23andMe, promises to “unlock the secrets of your own DNA,” while Navigenics wants you to be tested and “do everything you can to stay healthy.” And deCODEme hopes that genetic testing will “prompt people to do the right thing.” This commercialization of genetic testing appears to be selling health, but from my standpoint at least, it’s selling overdiagnosis.

Everything's Trash, but It's Okay by Phoebe Robinson

23andMe, Airbnb, Bernie Madoff, Bernie Sanders, Black Lives Matter, crack epidemic, Donald Trump, double helix, Downton Abbey, Elon Musk, feminist movement, Firefox, Lyft, Mahatma Gandhi, Mark Zuckerberg, microaggression, retail therapy, Rosa Parks, Silicon Valley, Silicon Valley startup, Tim Cook: Apple, uber lyft

Before I continue, I should probably explain what exactly the difference is between the two. White and “h-white” both concern white people, but the former category is run-of-the-mill stuff that is silly and sometimes annoying but usually harmless, while the latter category is screwed-up trash that makes you wanna do a drive-by at 23andMe.com to make sure you’re not related to the white nonsense you’re witnessing. Some examples include: White is Gwyneth Paltrow, in one of her Goop newsletters, intentionally referring to Billy Joel as William Joel for no gahtdamn reason; “h-white” is an AP reporter calling black child actress Quvenzhané Wallis by the name Annie because it’s “easier.”

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

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

Stanford itself earned 1.8 million shares in exchange for Google’s access to Page’s patents held by the university. (Stanford had cashed in those shares for $336 million by 2005). Google moved out of Stanford in 1999 into the Menlo Park garage of Susan Wojcicki, an Intel manager soon to be CEO of YouTube and a sister of Anne, the founder of the genomic startup 23andMe. Brin’s marriage to Anne in 2007 symbolized the procreative embrace of Silicon Valley, Sand Hill Road, and Palo Alto. (They divorced in 2015.) By 2017, Google’s own computer scientists had authored more of the world’s most-cited papers in the subject than had Stanford’s own faculty.1 Google’s founders always conceived of their projects in prophetic terms.

The Nocturnal Brain: Nightmares, Neuroscience, and the Secret World of Sleep by Dr. Guy Leschziner

23andMe, Berlin Wall, British Empire, impulse control, meta-analysis, mirror neurons, pattern recognition, phenotype, stem cell, twin studies

., Shah, S. H., Gieger, C., Peters, A., Rouleau, G. A., Berger, K., Oexle, K., Di Angelantonio, E., Hinds, D. A., Müller-Myhsok, B., Winkelmann, J., ‘Identification of novel risk loci for restless legs syndrome in genome-wide association studies in individuals of European ancestry: a meta-analysis’, 23andMe Research Team, DESIR study group, Lancet Neurol, November 2017, 16(11): 898—907. doi: 10.1016/S1474-4422(17)30327-7. Review. Winkelmann, J., Allen, R. P., Högl, B., Inoue, Y., Oertel, W., Salminen, A. V., Winkelman, J. W., Trenkwalder, C., Sampaio, C., ‘Treatment of restless legs syndrome: Evidence-based review and implications for clinical practice (Revised 2017)’, Mov Disord, 14 May 2018. doi: 10.1002/ mds.27260.

100 Years of Identity Crisis: Culture War Over Socialisation by Frank Furedi

1960s counterculture, 23andMe, Abraham Maslow, behavioural economics, Brexit referendum, Cass Sunstein, classic study, coronavirus, COVID-19, Donald Trump, epigenetics, Greta Thunberg, Gunnar Myrdal, Herbert Marcuse, Johann Wolfgang von Goethe, knowledge worker, libertarian paternalism, lockdown, New Urbanism, nocebo, nudge theory, nudge unit, scientific management, the scientific method, Thorstein Veblen, work culture

Cooper (2000) Beyond “identity”’, Theory & Society, 29(1), 1 – 47, at 5. 701 W.B. Michaels (1992) ‘Race into culture: a critical genealogy of cultural identity’, Critical Inquiry, 18(4), 655 – 685, at 684. 702 See www.theguardian.com/world/2003/feb/14/race.science?INTCMP=SRCH. 703 See www.nytimes.com/2021/02/16/opinion/23andme-ancestry-race.html#click=https://t.co/8gbXdZ9Xjb (accessed 6 March 2021). 704 See www.tandfonline.com/doi/abs/10.1080/01419870.2015.1058496 (accessed 18 March 2021) and https://journals.sagepub.com/doi/abs/10.1068/d150223?journalCode=epda (accessed 19 March 2021). 705 F. Fukuyama (2018) ‘The new tribalism and the crisis of democracy’, Foreign Affairs, Sept.

Augmented: Life in the Smart Lane by Brett King

23andMe, 3D printing, additive manufacturing, Affordable Care Act / Obamacare, agricultural Revolution, Airbnb, Albert Einstein, Amazon Web Services, Any sufficiently advanced technology is indistinguishable from magic, Apollo 11, Apollo Guidance Computer, Apple II, artificial general intelligence, asset allocation, augmented reality, autonomous vehicles, barriers to entry, bitcoin, Bletchley Park, blockchain, Boston Dynamics, business intelligence, business process, call centre, chief data officer, Chris Urmson, Clayton Christensen, clean water, Computing Machinery and Intelligence, congestion charging, CRISPR, crowdsourcing, cryptocurrency, data science, deep learning, DeepMind, deskilling, different worldview, disruptive innovation, distributed generation, distributed ledger, double helix, drone strike, electricity market, Elon Musk, Erik Brynjolfsson, Fellow of the Royal Society, fiat currency, financial exclusion, Flash crash, Flynn Effect, Ford Model T, future of work, gamification, Geoffrey Hinton, gig economy, gigafactory, Google Glasses, Google X / Alphabet X, Hans Lippershey, high-speed rail, Hyperloop, income inequality, industrial robot, information asymmetry, Internet of things, invention of movable type, invention of the printing press, invention of the telephone, invention of the wheel, James Dyson, Jeff Bezos, job automation, job-hopping, John Markoff, John von Neumann, Kevin Kelly, Kickstarter, Kim Stanley Robinson, Kiva Systems, Kodak vs Instagram, Leonard Kleinrock, lifelogging, low earth orbit, low skilled workers, Lyft, M-Pesa, Mark Zuckerberg, Marshall McLuhan, megacity, Metcalfe’s law, Minecraft, mobile money, money market fund, more computing power than Apollo, Neal Stephenson, Neil Armstrong, Network effects, new economy, Nick Bostrom, obamacare, Occupy movement, Oculus Rift, off grid, off-the-grid, packet switching, pattern recognition, peer-to-peer, Ray Kurzweil, retail therapy, RFID, ride hailing / ride sharing, Robert Metcalfe, Salesforce, Satoshi Nakamoto, Second Machine Age, selective serotonin reuptake inhibitor (SSRI), self-driving car, sharing economy, Shoshana Zuboff, Silicon Valley, Silicon Valley startup, Skype, smart cities, smart grid, smart transportation, Snapchat, Snow Crash, social graph, software as a service, speech recognition, statistical model, stem cell, Stephen Hawking, Steve Jobs, Steve Wozniak, strong AI, synthetic biology, systems thinking, TaskRabbit, technological singularity, TED Talk, telemarketer, telepresence, telepresence robot, Tesla Model S, The future is already here, The Future of Employment, Tim Cook: Apple, trade route, Travis Kalanick, TSMC, Turing complete, Turing test, Twitter Arab Spring, uber lyft, undersea cable, urban sprawl, V2 rocket, warehouse automation, warehouse robotics, Watson beat the top human players on Jeopardy!, white picket fence, WikiLeaks, yottabyte

In 1984, the first Human Genome Project (HGP) was proposed and funded by the US government, but the project really only got underway with international cooperation in 1990. It then took 13 years and collectively almost US$3 billion of public and private investment to complete the first human genome sequence of the approximately 20,500 genes and 150,000 base pairs present in the donor DNA samples.2 Today, companies like 23andMe can do a genotyping sequencing (comparing your DNA with other human baselines) for just US$100 in a few weeks. If you want a full, original genome sequence, it still costs around US$10,000, but that is expected to fall to under US$1,000 over the next few years thanks to Moore’s Law. Falling from US$3 billion to US$1,000 in just 25 years means that by 2025 it will likely cost less than US$10 to do an original sequencing of your DNA, and computer processing power will enable it within seconds.

This Will Make You Smarter: 150 New Scientific Concepts to Improve Your Thinking by John Brockman

23andMe, adjacent possible, Albert Einstein, Alfred Russel Wallace, Anthropocene, banking crisis, Barry Marshall: ulcers, behavioural economics, Benoit Mandelbrot, Berlin Wall, biofilm, Black Swan, Bletchley Park, butterfly effect, Cass Sunstein, cloud computing, cognitive load, congestion charging, correlation does not imply causation, Daniel Kahneman / Amos Tversky, dark matter, data acquisition, David Brooks, delayed gratification, Emanuel Derman, epigenetics, Evgeny Morozov, Exxon Valdez, Flash crash, Flynn Effect, Garrett Hardin, Higgs boson, hive mind, impulse control, information retrieval, information security, Intergovernmental Panel on Climate Change (IPCC), Isaac Newton, Jaron Lanier, Johannes Kepler, John von Neumann, Kevin Kelly, Large Hadron Collider, lifelogging, machine translation, mandelbrot fractal, market design, Mars Rover, Marshall McLuhan, microbiome, Murray Gell-Mann, Nicholas Carr, Nick Bostrom, ocean acidification, open economy, Pierre-Simon Laplace, place-making, placebo effect, power law, pre–internet, QWERTY keyboard, random walk, randomized controlled trial, rent control, Richard Feynman, Richard Feynman: Challenger O-ring, Richard Thaler, Satyajit Das, Schrödinger's Cat, scientific management, security theater, selection bias, Silicon Valley, Stanford marshmallow experiment, stem cell, Steve Jobs, Steven Pinker, Stewart Brand, Stuart Kauffman, sugar pill, synthetic biology, the scientific method, Thorstein Veblen, Turing complete, Turing machine, twin studies, Vilfredo Pareto, Walter Mischel, Whole Earth Catalog, WikiLeaks, zero-sum game

It is using its tools for clustering, classifying, and discovering rules in raw data, but mostly it is simply quantifying that data to extract signals—information—from the noise. The cumulative rewards of such thinking will be altruistic rather than narcissistic, whether in pooling personal data for greater scientific understanding (23andMe) or in propagating user-submitted data to motivate behavior change in others (traineo). Indeed, as the work of Daniel Kahneman, Daniel Gilbert, and Christakis and Fowler demonstrate so powerfully, accurate individual-level data tracking is key to understanding how human happiness can be quantified, how our social networks affect our behavior, how diseases spread through groups.

Gene Eating: The Science of Obesity and the Truth About Dieting by Giles Yeo

23andMe, agricultural Revolution, Albert Einstein, caloric restriction, caloric restriction, Cass Sunstein, choice architecture, correlation does not imply causation, CRISPR, delayed gratification, Drosophila, Easter island, Gregor Mendel, longitudinal study, Louis Pasteur, Mark Zuckerberg, meta-analysis, microbiome, nudge theory, post-truth, publish or perish, randomized controlled trial, Richard Thaler, Steve Jobs, TED Talk, twin studies, Wall-E, zoonotic diseases

THE GENETIC CRYSTAL BALL Would you pay £249 to find out whether you are genetically predisposed to gaining weight? Or if you’re likely to develop high blood pressure if you eat too much salt? Or to become a supertaster? Or if you are better suited to a high-protein diet? That’s certainly the hope behind the ‘personalised’ gene tests now available from companies such as 23andMe, Nutrigenomix and DNAFit. They not only claim their tests can identify genes related to diseases including dementia and obesity, but also predict how you might respond to specific diets, such as low salt, low caffeine or high fat. By using this information, you can then exercise more effectively, lose weight and stay healthy; that is their pitch.1 The idea of peering into a genetic crystal ball to predict your future self, or how you might respond to specific treatments and diets should, in principle, be possible.

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

The rest will take the drug without any clinical benefit besides a better cholesterol lab test result. For decades, we’ve known the clinical factors that pose a risk for heart disease, like smoking and diabetes, and now we can factor in genetic data with a risk score from an inexpensive gene array (data that can be obtained for $50 to $100 via 23andMe, AncestryDNA, and other companies). That score, independent of as well as in addition to traditional clinical risk factors, predicts the likelihood of heart disease and whether use of a statin will benefit that individual. Similar genetic risk scores are now validated for a variety of conditions including breast cancer, prostate cancer, atrial fibrillation, diabetes, and Alzheimer’s disease.

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

Hardware, software, and platform companies analyze their own data, of course, but analytics firms provide more specialized services such as psychometrics (large-scale analysis of users’ personalities and preferences) and telematics (coordinating production and distribution processes using data collected at multiple points). US examples of marketing-oriented analytic firms include Paxata, Trifacta, IBM, and Google. But there is a wide spectrum of companies that collect and analyze data across many domains of life, including health (Mede Analytics), genetics (23andMe), education (Junyo), crime (Wynyard), and so on. In China, data analytics are concentrated in big corporations such as Alibaba, Baidu, and WeChat. Some of these firms focus on data that can be used for sales and marketing purposes, but they increasingly integrate information about users’ social lives into their models and products.

Life on the Rocks: Building a Future for Coral Reefs by Juli Berwald

23andMe, 3D printing, Alfred Russel Wallace, Anthropocene, Black Lives Matter, carbon footprint, Charles Lindbergh, circular economy, clean water, coronavirus, COVID-19, en.wikipedia.org, Fellow of the Royal Society, financial innovation, Garrett Hardin, George Floyd, Google Earth, Gregor Mendel, Greta Thunberg, Intergovernmental Panel on Climate Change (IPCC), lateral thinking, Maui Hawaii, microbiome, mouse model, ocean acidification, Panamax, Paris climate accords, Skype, social distancing, sovereign wealth fund, stem cell, TED Talk, the scientific method, too big to fail, Tragedy of the Commons

“A good place to start would be getting an inventory of what you have, with scientific names,” I said. Noah nodded. “What we need is a way for the hobbyists to identify the coral, like a DNA test,” he said. “And then I can use that as a model to get other hobbyists to add their information to build a database.” “Like a 23andMe for coral,” Richard brainstormed, referring to the DNA-sequencing company named for our twenty-three pairs of chromosomes. “It’s a great idea,” I said, “if it only existed. Also, I wonder how many chromosomes corals have.” Later, I learned it would be more like 28andMe. We talked about the continued gap between the scientific world and the world of hobbyists, and the ways in which each could benefit from the other’s expertise.

The Equality Machine: Harnessing Digital Technology for a Brighter, More Inclusive Future by Orly Lobel

2021 United States Capitol attack, 23andMe, Ada Lovelace, affirmative action, Airbnb, airport security, Albert Einstein, algorithmic bias, Amazon Mechanical Turk, augmented reality, barriers to entry, basic income, Big Tech, bioinformatics, Black Lives Matter, Boston Dynamics, Charles Babbage, choice architecture, computer vision, Computing Machinery and Intelligence, contact tracing, coronavirus, corporate social responsibility, correlation does not imply causation, COVID-19, crowdsourcing, data science, David Attenborough, David Heinemeier Hansson, deep learning, deepfake, digital divide, digital map, Elon Musk, emotional labour, equal pay for equal work, feminist movement, Filter Bubble, game design, gender pay gap, George Floyd, gig economy, glass ceiling, global pandemic, Google Chrome, Grace Hopper, income inequality, index fund, information asymmetry, Internet of things, invisible hand, it's over 9,000, iterative process, job automation, Lao Tzu, large language model, lockdown, machine readable, machine translation, Mark Zuckerberg, market bubble, microaggression, Moneyball by Michael Lewis explains big data, natural language processing, Netflix Prize, Network effects, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, occupational segregation, old-boy network, OpenAI, openstreetmap, paperclip maximiser, pattern recognition, performance metric, personalized medicine, price discrimination, publish or perish, QR code, randomized controlled trial, remote working, risk tolerance, robot derives from the Czech word robota Czech, meaning slave, Ronald Coase, Salesforce, self-driving car, sharing economy, Sheryl Sandberg, Silicon Valley, social distancing, social intelligence, speech recognition, statistical model, stem cell, Stephen Hawking, Steve Jobs, Steve Wozniak, surveillance capitalism, tech worker, TechCrunch disrupt, The Future of Employment, TikTok, Turing test, universal basic income, Wall-E, warehouse automation, women in the workforce, work culture , you are the product

There are no patents on Mirai because, as Barzilay noted, “this should be for everyone to build on.”41 The rapid advancement of AI and automated data collection is further underscoring the risks of our laws protecting the interests of corporations at the expense of distributive justice in the information ecosystem. Erin Murphy, a New York University law professor, warns that if your sibling or child provided their genetic information by spitting into a DNA kit and mailing it back to a company like 23andMe, “they are compromising your family for generations.” The balance between preserving privacy and health, private property and distributive justice, free speech and equality, and many other democratic values will continue to be at the heart of any new technological capability. But as we’ve seen, AI can move the needle on some of the ongoing challenges by leveraging technology itself to decrease the tension between these different values.

The Immortal Life of Henrietta Lacks by Rebecca Skloot

23andMe, Adam Curtis, air freight, company town, desegregation, index card, indoor plumbing, life extension, medical malpractice, RAND corporation, Ronald Reagan, stem cell, white picket fence

A few years ago the National Cancer Institute started gathering what it expects will be millions of tissue samples for mapping cancer genes; the Genographic Project began doing the same to map human migration patterns, as did the NIH to track disease genes. And for several years the public has been sending samples by the millions to personalized DNA testing companies like 23andMe, which only provide customers with their personal medical or genealogical information if they first sign a form granting permission for their samples to be stored for future research. Scientists use these samples to develop everything from flu vaccines to penis-enlargement products. They put cells in culture dishes and expose them to radiation, drugs, cosmetics, viruses, household chemicals, and biological weapons, and then study their responses.

Fix Your Gut: The Definitive Guide to Digestive Disorders by John Brisson

23andMe, big-box store, biofilm, butterfly effect, clean water, Helicobacter pylori, life extension, meta-analysis, microbiome, pattern recognition, publication bias, selective serotonin reuptake inhibitor (SSRI), Silicon Valley, Zimmermann PGP

If enough alcohol is consumed the symptoms intensify from a severe hangover to coma and eventually death from untreated aldehyde poisoning. Some people have gene mutations sadly that cause the body to produce less of these enzymes or none at all. ALDH2 is one of these genes and is tested if you get a 23andMe test. Mold and yeast also produce many aldehydes that require these enzymes to help us detoxify them. Does Flagyl Increase Mold Sensitivity? Flagyl like the medication disulfiram may reduce the body’s ability to produce aldehyde detoxification enzymes. The inhibition of these enzymes is the reason why alcohol is strongly discouraged in people who are taking Flagyl for infections.

Surveillance Valley: The Rise of the Military-Digital Complex by Yasha Levine

23andMe, activist fund / activist shareholder / activist investor, Adam Curtis, Airbnb, AltaVista, Amazon Web Services, Anne Wojcicki, anti-communist, AOL-Time Warner, Apple's 1984 Super Bowl advert, bitcoin, Black Lives Matter, borderless world, Boston Dynamics, British Empire, Californian Ideology, call centre, Charles Babbage, Chelsea Manning, cloud computing, collaborative editing, colonial rule, company town, computer age, computerized markets, corporate governance, crowdsourcing, cryptocurrency, data science, digital map, disinformation, don't be evil, Donald Trump, Douglas Engelbart, Douglas Engelbart, Dr. Strangelove, drone strike, dual-use technology, Edward Snowden, El Camino Real, Electric Kool-Aid Acid Test, Elon Musk, end-to-end encryption, fake news, fault tolerance, gentrification, George Gilder, ghettoisation, global village, Google Chrome, Google Earth, Google Hangouts, Greyball, Hacker Conference 1984, Howard Zinn, hypertext link, IBM and the Holocaust, index card, Jacob Appelbaum, Jeff Bezos, jimmy wales, John Gilmore, John Markoff, John Perry Barlow, John von Neumann, Julian Assange, Kevin Kelly, Kickstarter, Laura Poitras, life extension, Lyft, machine readable, Mark Zuckerberg, market bubble, Menlo Park, military-industrial complex, Mitch Kapor, natural language processing, Neal Stephenson, Network effects, new economy, Norbert Wiener, off-the-grid, One Laptop per Child (OLPC), packet switching, PageRank, Paul Buchheit, peer-to-peer, Peter Thiel, Philip Mirowski, plutocrats, private military company, RAND corporation, Ronald Reagan, Ross Ulbricht, Satoshi Nakamoto, self-driving car, sentiment analysis, shareholder value, Sheryl Sandberg, side project, Silicon Valley, Silicon Valley startup, Skype, slashdot, Snapchat, Snow Crash, SoftBank, speech recognition, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, Susan Wojcicki, Telecommunications Act of 1996, telepresence, telepresence robot, The Bell Curve by Richard Herrnstein and Charles Murray, The Hackers Conference, Tony Fadell, uber lyft, vertical integration, Whole Earth Catalog, Whole Earth Review, WikiLeaks

It blasted beyond pure Internet services and delved into fiber-optic telecommunication systems, tablets, laptops, home security cameras, self-driving cars, shopping delivery, robots, electric power plants, life extension technology, cyber security, and biotech. The company even launched a powerful in-house investment bank that now rivals Wall Street companies, investing money in everything from Uber to obscure agricultural crop monitoring start-ups, ambitious human DNA sequencing companies like 23andME, and a secretive life extension research center called Calico.88 No matter what service it deployed or what market it entered, surveillance and prediction were cooked into the business. The data flowing through Google’s system are staggering. By the end of 2016, Google’s Android was installed on 82 percent of all new smartphones sold around the world, with over 1.5 billion Android users globally.89 At the same time, Google handled billions of searches and YouTube plays daily and had a billion active Gmail users, which meant it had access to most of the world’s emails.90 Some analysts estimate that 25 percent of all Internet traffic in North America goes through Google servers.91 The company isn’t just connected to the Internet, it is the Internet.

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

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

Problems of problematic and even contrived identity: Melissa Korn and Jennifer Levitz, “Students Were Advised to Claim to Be Minorities in College-Admissions Scandal,” Wall Street Journal, May 19, 2019, www.wsj.com/articles/students-were-advised-to-claim-to-be-minorities-in-college-admissions-scandal-11558171800; Vijay Chokal-Ingam, “Why I Faked Being Black for Med School,” New York Post, April 12, 2015, nypost.com/2015/04/12/mindy-kalings-brother-explains-why-he-pretended-to-be-black; Chris Bodenner, “Check Your Privilege, Kids, but Don’t Check a Race Box,” The Atlantic, December 17, 2015, www.theatlantic.com/notes/2015/12/check-your-privilege-kids-but-dont-check-a-race-box/421107. 28. DNA tests: C. Farr, “Consumer DNA Testing Has Hit a Lull—Here’s How It Could Capture the Next Wave of Users,” CNBC, August 25, 2019, www.cnbc.com/2019/08/25/dna-tests-from-companies-like-23andme-ancestry-see-sales-slowdown.html. Race and admissions: Douglas Belkin, “The Most Agonizing Question on a College Application: What’s Your Race?,” Wall Street Journal, December 23, 2019, www.wsj.com/articles/the-most-agonizing-question-on-a-college-application-11577100370. 29. In fact, applicants are using DNA tests to find elements of nonwhite ancestry and thereby, in a nonsystematic fashion, to obtain some sort of advantage in hiring or admission—given that no federal guidelines establish the precise racial percentage that allows one to claim minority status: Sarah Zhang, “A Man Says His DNA Test Proves He’s Black, and He’s Suing,” The Atlantic, September 19, 2018, www.theatlantic.com/science/archive/2018/09/dna-test-race-lawsuit/570250; Ashifa Kassam, “Users of Home DNA Tests ‘Cherry Pick’ Results Based on Race Biases, Study Says,” The Guardian, July 1, 2018, www.theguardian.com/science/2018/jul/01/home-dna-test-kits-race-ethnicity-dna-ancestry. 30.

Beautiful Data: The Stories Behind Elegant Data Solutions by Toby Segaran, Jeff Hammerbacher

23andMe, airport security, Amazon Mechanical Turk, bioinformatics, Black Swan, business intelligence, card file, cloud computing, computer vision, correlation coefficient, correlation does not imply causation, crowdsourcing, Daniel Kahneman / Amos Tversky, DARPA: Urban Challenge, data acquisition, data science, database schema, double helix, en.wikipedia.org, epigenetics, fault tolerance, Firefox, Gregor Mendel, Hans Rosling, housing crisis, information retrieval, lake wobegon effect, Large Hadron Collider, longitudinal study, machine readable, machine translation, Mars Rover, natural language processing, openstreetmap, Paradox of Choice, power law, prediction markets, profit motive, semantic web, sentiment analysis, Simon Singh, social bookmarking, social graph, SPARQL, sparse data, speech recognition, statistical model, supply-chain management, systematic bias, TED Talk, text mining, the long tail, Vernor Vinge, web application

How to Become a Genetic Hacker More than other data-intensive areas, genomics has a great history of providing open, online data repositories, from a variety of genome browsing and annotation tools (such as Enesembl and UCSC), to details of diseases linked to genes (HapMap, SNPedia) and personalized genomics services such as 23andMe and Navigenics. So much so that anyone can become a genetic hacker these days. Next Next-Gen At present, such companies provide only a high-level overview of certain points of interest along the genome. But innovation continues unabated with the development of the next generation of sequencing instrumentation and genome analyzers.

The Rational Optimist: How Prosperity Evolves by Matt Ridley

"World Economic Forum" Davos, 23andMe, Abraham Maslow, agricultural Revolution, air freight, back-to-the-land, banking crisis, barriers to entry, Bernie Madoff, British Empire, call centre, carbon credits, carbon footprint, carbon tax, Cesare Marchetti: Marchetti’s constant, charter city, clean water, cloud computing, cognitive dissonance, collateralized debt obligation, colonial exploitation, colonial rule, Corn Laws, Cornelius Vanderbilt, cotton gin, creative destruction, credit crunch, David Ricardo: comparative advantage, decarbonisation, dematerialisation, demographic dividend, demographic transition, double entry bookkeeping, Easter island, Edward Glaeser, Edward Jenner, electricity market, en.wikipedia.org, everywhere but in the productivity statistics, falling living standards, feminist movement, financial innovation, flying shuttle, Flynn Effect, food miles, Ford Model T, Garrett Hardin, Gordon Gekko, greed is good, Hans Rosling, happiness index / gross national happiness, haute cuisine, hedonic treadmill, Herbert Marcuse, Hernando de Soto, income inequality, income per capita, Indoor air pollution, informal economy, Intergovernmental Panel on Climate Change (IPCC), invention of agriculture, invisible hand, James Hargreaves, James Watt: steam engine, Jane Jacobs, Jevons paradox, John Nash: game theory, joint-stock limited liability company, Joseph Schumpeter, Kevin Kelly, Kickstarter, knowledge worker, Kula ring, Large Hadron Collider, Mark Zuckerberg, Medieval Warm Period, meta-analysis, mutually assured destruction, Naomi Klein, Northern Rock, nuclear winter, ocean acidification, oil shale / tar sands, out of africa, packet switching, patent troll, Pax Mongolica, Peter Thiel, phenotype, plutocrats, Ponzi scheme, precautionary principle, Productivity paradox, profit motive, purchasing power parity, race to the bottom, Ray Kurzweil, rent-seeking, rising living standards, Robert Solow, Silicon Valley, spice trade, spinning jenny, stem cell, Steve Jobs, Steven Pinker, Stewart Brand, supervolcano, technological singularity, Thales and the olive presses, Thales of Miletus, the long tail, The Wealth of Nations by Adam Smith, Thorstein Veblen, trade route, Tragedy of the Commons, transaction costs, ultimatum game, upwardly mobile, urban sprawl, Vernor Vinge, Vilfredo Pareto, wage slave, working poor, working-age population, world market for maybe five computers, Y2K, Yogi Berra, zero-sum game

Instead of money, ‘peer producers who create the stuff gain credit, status, reputation, enjoyment, satisfaction and experience’. People are willing to share their photographs on Flickr, their thoughts on Twitter, their friends on Facebook, their knowledge on Wikipedia, their software patches on Linux, their donations on GlobalGiving, their community news on Craigslist, their pedigrees on Ancestry.com, their genomes on 23andMe, even their medical records on PatientsLikeMe. Thanks to the internet, each is giving according to his ability to each according to his needs, to a degree that never happened in Marxism. This catallaxy will not go smoothly, or without resistance. Natural and unnatural disasters will still happen.

The Code Breaker: Jennifer Doudna, Gene Editing, and the Future of the Human Race by Walter Isaacson

"World Economic Forum" Davos, 23andMe, Albert Einstein, Alfred Russel Wallace, Anne Wojcicki, Apollo 13, Apple II, Asilomar, Asilomar Conference on Recombinant DNA, Bernie Sanders, Colonization of Mars, contact tracing, coronavirus, COVID-19, CRISPR, crowdsourcing, Dean Kamen, discovery of DNA, discovery of penicillin, double helix, Edward Jenner, Gregor Mendel, Hacker News, Henri Poincaré, iterative process, Joan Didion, linear model of innovation, Louis Pasteur, Mark Zuckerberg, microbiome, mouse model, Nick Bostrom, public intellectual, Recombinant DNA, seminal paper, Silicon Valley, Skype, stealth mode startup, stem cell, Steve Jobs, Steve Wozniak, Steven Levy, Steven Pinker, synthetic biology, the scientific method, Thomas Malthus, wikimedia commons