23andMe

The Patient Will See You Now: The Future of Medicine Is in Your Hands
by Eric Topol
Published 6 Jan 2015

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
Published 2 Feb 2016

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
Published 17 Sep 2018

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 and James Salzman
Published 2 Mar 2021

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
Published 22 Aug 2011

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
Published 14 Apr 2009

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 and Deron Triff
Published 14 Oct 2021

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
Published 14 Sep 2021

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
Published 10 Nov 2020

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
Published 22 Jan 2014

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
Published 14 Jun 2021

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
Published 22 Mar 2018

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
Published 14 Aug 2020

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
Published 6 Sep 2021

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
Published 29 Aug 2012

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
Published 23 Aug 2021

(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
Published 29 May 2018

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
Published 5 Nov 2013

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
Published 2 Mar 2015

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.

An Optimist's Tour of the Future
by Mark Stevenson
Published 4 Dec 2010

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.

Dirty Genes: A Breakthrough Program to Treat the Root Cause of Illness and Optimize Your Health
by Ben Lynch Nd.
Published 30 Jan 2018

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.

Money: Vintage Minis
by Yuval Noah Harari
Published 5 Apr 2018

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.

Big Data: A Revolution That Will Transform How We Live, Work, and Think
by Viktor Mayer-Schonberger and Kenneth Cukier
Published 5 Mar 2013

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.

Live Work Work Work Die: A Journey Into the Savage Heart of Silicon Valley
by Corey Pein
Published 23 Apr 2018

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!

Soonish: Ten Emerging Technologies That'll Improve And/or Ruin Everything
by Kelly Weinersmith and Zach Weinersmith
Published 16 Oct 2017

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
Published 1 Oct 2018

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.

Singularity Rising: Surviving and Thriving in a Smarter, Richer, and More Dangerous World
by James D. Miller
Published 14 Jun 2012

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.

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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.

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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.

Falter: Has the Human Game Begun to Play Itself Out?
by Bill McKibben
Published 15 Apr 2019

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.

A Brief History of Everyone Who Ever Lived
by Adam Rutherford
Published 7 Sep 2016

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.

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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.

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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
Published 14 Oct 2018

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.

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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.

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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
Published 20 Feb 2020

‘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.

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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 and Alex Salkever
Published 2 Apr 2017

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.

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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.

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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 and Braden Kowitz
Published 8 Mar 2016

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.

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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.

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., 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
Published 15 Feb 2009

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
Published 3 Sep 2018

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
Published 5 Sep 2022

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.

…

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.

The Genetic Lottery: Why DNA Matters for Social Equality
by Kathryn Paige Harden
Published 20 Sep 2021

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.

…

,” 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.

Decoding the World: A Roadmap for the Questioner
by Po Bronson
Published 14 Jul 2020

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.

…

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.”

…

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 Sullivanians: Sex, Psychotherapy, and the Wild Life of an American Commune
by Alexander Stille
Published 19 Jun 2023

” * * * 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.

…

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.”

…

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
Published 7 Jan 2020

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.

…

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
Published 1 Jan 2009

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.

…

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.

…

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
Published 21 Feb 2012

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
Published 20 Feb 2020

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.’

…

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.

…

., 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
Published 1 Mar 2015

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.

…

(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
Published 6 Feb 2018

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.

…

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
Published 1 Dec 2010

—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.

…

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
Published 1 Feb 2011

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 and Aaron Roth
Published 3 Oct 2019

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
Published 4 May 2021

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
Published 17 Mar 2015

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 and Stian Westlake
Published 7 Nov 2017

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 and Jeremy Freeman
Published 1 Nov 2014

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
Published 9 Sep 2014

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 and Philipp Rehm
Published 18 May 2022

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.

…

“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 Great Experiment: Why Diverse Democracies Fall Apart and How They Can Endure
by Yascha Mounk
Published 19 Apr 2022

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.)

…

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 Coming Wave: Technology, Power, and the Twenty-First Century's Greatest Dilemma
by Mustafa Suleyman
Published 4 Sep 2023

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 Power Law: Venture Capital and the Making of the New Future
by Sebastian Mallaby
Published 1 Feb 2022

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.

…

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.

Your Face Belongs to Us: A Secretive Startup's Quest to End Privacy as We Know It
by Kashmir Hill
Published 19 Sep 2023

According to Johnson, Ton-That also called his ex-wife, asking to buy the shares she and their daughter held, but she refused. After this news sunk in, Johnson acted blasé about it. He had moved from Texas to Virginia, had a new girlfriend, and had his hands full, he said, with a new startup called Traitwell, which would invite people to upload their DNA results from companies such as 23andMe and Ancestry, in order to “learn new and dangerous things about yourself.” One of its offerings was a “Covid forecaster” to predict the severity of one’s symptoms if infected. Johnson’s true goal, though, was to build a genetic database that police could use to help solve crimes; this would ideally include everyone’s DNA or at least that of someone related to them, which would be enough to make them findable in a genetic search.

…

See also eugenics stingrays, 155 stock photo sites, 192 “stop the steal,” 228 Strategic Computing Initiative, 42 “Success Stories” marketing document, 137 Super Bowl (2001), 60–62, 63, 65 Super Sad True Love Story (Shteyngart), 34 supercomputers, 75–76 SuperVision, 146–147 Supreme Court Abrams and, 207 Citizens United and, 306n206 on First Amendment, 306n206 involuntary sterilizations and, 26 location privacy and, 203 NAACP and, 39 Pentagon Papers and, 207 Sutskever, Ilya, 295n146 Swedish Authority for Privacy Protection, 292n137 Swedish Police Authority, 136 Swisher, Kara, 102 symbolic AI, 37 Syndrome, 119 T Taigman, Yaniv, 146–148 TechCrunch, 101 technical sweetness, 48, 148 Telegram, 222 Temple of Heaven, 224 TensorFlow, 208 Tesla, 73 Texas Capture or Use of Biometric Identifier Act, 83 Therrien, Daniel, 193 Thiel, Peter attempts to contact, 160 background of, xi Clearview AI and, 111 at DeploraBall, 55 Gawker and, 14–15 Kirenaga Partners and, xiv lawsuits against PayPal and, 210–211 at Republican Convention, 15–16, 29 Scalzo and, 119–120 Smartcheckr and, 79–81, 89 Ton-That and, 13, 14 Trump administration and, 53 This Person Does Not Exist, 163, 195 Thorn, 115 TikTok, 224 Tinder, xvii, 34 toilet paper dispensers, 224 Tomas, Alexander, 309n222 Tompkins Square Park, 30 Tong, William, 139 Ton-That, Hoan Abrams and, 209–211 AR glasses and, 249–250 attempts to contact, 160 attorneys general and, 138–139 avoidance of past by, 247 background of, 3–4 Besson and, 128, 129 Bezos and, 116 bias and, 239 on blocking author’s face, 163 Borthwick and, 113 Capitol insurrection and, 229 databases used by, 242 dlib and, 195 Dumanski and, 160–161 early plans of, 31–35 Facebook apps by, 5–6 FindFace and, 220 Gawker and, 15 growth of database and, 246–247 hit rate and, 133 international backlash and, 193, 194 investors and, 116 Johnson and, 12–13, 27, 33, 94–96, 247–249 Kutcher and, 115 lawsuits and, 209–211, 213 Leone and, 113–114 Liu and, 75–76, 77 Lynch and, 91, 92, 93 meeting with, 161–164 Montana and, 114 in New York, 9 NIST testing and, 240 NYPD and, 128, 129, 130, 131–132 opposition and, 138 Orbán and, 56 photos of, 8–9 politics of, 9–10 pseudonym use by, 134 at Republican Convention, 3, 10–11, 12, 13–14, 15–16 in San Francisco, 4–5 Scalzo and, 111, 112, 113, 118, 188–189 Schwartz and, 29–30 scraping and, 78–79, 81 self-assessment of, 250–251 Smartcheckr and, 52, 53, 58, 72–73, 74–75, 77–81, 89, 94 Thiel and, 79–80 Trump and, 50, 51–52 ViddyHo and, 7–8 Ton-That, Quynh-Du, 4 TopShot, 9 Toronto Police, 136 Touchfelt, 4 Traitwell, 248 Transportation Security Agency (TSA), 28 “Tremolo” (Ton-That), 8 True Depth camera, 109 true faces, 17 Trump, Donald Cambridge Analytica scandal and, 92 as candidate, 3, 8, 16, 29 Capitol insurrection and, 228, 229 casinos owned by, 62 Congressional hearings and, 155–156 DeploraBall and, 53–54 election night and, 50–52 Johnson and, 95 Luckey and, 57 Lynch and, 88 Mackey and, 93–94 Orbán and, 56 Thiel and, xi Ton-That’s support of, 3, 10, 13, 16, 116 Trump, Melania, 14 Trump Hair, 9 TruthFinder, 58 TSA (Transportation Security Agency), 28 Tsvetkov, Egor, 221 Turk, Matthew Autonomous Land Vehicle (“Alvin”) and, 42 Facebook and, 152 at MIT Media Lab, 43–44, 45–47, 48–49, 60 timing of work of, 66 Turow, Joseph, 280n78 Tuskegee Institute, 279n74 23andMe, 248 Twitter Cernovich and, 12 Clearview AI and, xvii, 165 FTC and, 123 Johnson and, 11, 95 machine learning and, 72 Mackey and, 93–94 Smartcheckr and, 53 Ton-That and, 5, 9 ViddyHo and, 7 Yiannopoulos and, 14 2chan, 221–222 U Uber, 5, 189, 210 Ukraine, Russia’s invasion of, 237 Ultra Music Festival, 231, 232, 233–234 undercover officers, dangers to, xvii Urban, Scott, 241 U.S.

The Future of the Professions: How Technology Will Transform the Work of Human Experts
by Richard Susskind and Daniel Susskind
Published 24 Aug 2015

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
Published 5 Feb 2019

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
Published 14 Oct 2021

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.

A Short History of Humanity: How Migration Made Us Who We Are
by Johannes Krause and Thomas Trappe
Published 8 Apr 2021

As vast sums of money are being poured into genetic research, humanity faces a difficult task in answering this and other highly complex ethical questions, though we are on the verge of being presented with a fait accompli. In 2012, the China National GeneBank was established with the express purpose of decoding not merely the human blueprint but that of the entire biosphere. Meanwhile, a major shareholder in 23andMe, one of the world’s largest private genetic-testing firms, is the data company Google. THE LURE OF THE DESIGNER HUMAN * * * THE DEVELOPMENT OF GENETIC RESEARCH IS LIKE THE development of supersonic flight—we’re fascinated by its extraordinary promise yet have only the vaguest sense of the risks that might be lurking behind the technology.

Editing Humanity: The CRISPR Revolution and the New Era of Genome Editing
by Kevin Davies
Published 5 Oct 2020

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
Published 10 Mar 2015

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
Published 12 Apr 2011

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
Published 14 Jun 2017

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.

Final Jeopardy: Man vs. Machine and the Quest to Know Everything
by Stephen Baker
Published 17 Feb 2011

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.

Raw Data Is an Oxymoron
by Lisa Gitelman
Published 25 Jan 2013

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).

The Pattern Seekers: How Autism Drives Human Invention
by Simon Baron-Cohen
Published 14 Aug 2020

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).

Technical Blogging: Turn Your Expertise Into a Remarkable Online Presence
by Antonio Cangiano
Published 15 Mar 2012

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 and Yuri van Geest
Published 17 Oct 2014

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.

Big Business: A Love Letter to an American Anti-Hero
by Tyler Cowen
Published 8 Apr 2019

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?)

How to Fix the Future: Staying Human in the Digital Age
by Andrew Keen
Published 1 Mar 2018

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 and Steven Woloshin
Published 18 Jan 2011

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
Published 15 Oct 2018

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
Published 16 Jul 2018

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.

100 Years of Identity Crisis: Culture War Over Socialisation
by Frank Furedi
Published 6 Sep 2021

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.

The Nocturnal Brain: Nightmares, Neuroscience, and the Secret World of Sleep
by Dr. Guy Leschziner
Published 22 Jul 2019

., 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.

Augmented: Life in the Smart Lane
by Brett King
Published 5 May 2016

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
Published 14 Feb 2012

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
Published 3 Jun 2019

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
Published 1 Jan 2019

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 and Ulises A. Mejias
Published 19 Aug 2019

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
Published 4 Apr 2022

“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
Published 17 Oct 2022

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
Published 2 Feb 2010

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
Published 12 Apr 2014

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.

The Dying Citizen: How Progressive Elites, Tribalism, and Globalization Are Destroying the Idea of America
by Victor Davis Hanson
Published 15 Nov 2021

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.

Surveillance Valley: The Rise of the Military-Digital Complex
by Yasha Levine
Published 6 Feb 2018

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.

Beautiful Data: The Stories Behind Elegant Data Solutions
by Toby Segaran and Jeff Hammerbacher
Published 1 Jul 2009

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
Published 17 May 2010

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
Published 9 Mar 2021

The citation heralded them “for harnessing an ancient mechanism of bacterial immunity into a powerful and general technology for editing genomes.” The prize, which carries a $3 million award for each recipient, had been established a year earlier by the Russian billionaire and early Facebook funder Yuri Milner, along with Sergey Brin of Google, Anne Wojcicki of 23andMe, and Mark Zuckerberg of Facebook. Milner, an ebullient fanboy of scientists, staged a glittering televised award ceremony that infused the glory of science with some of the glamor of Hollywood. The 2014 black-tie event, cohosted by Vanity Fair, was held in a spacecraft hangar at NASA’s Ames Research Center in Mountain View, California, in the heart of Silicon Valley.

Future Crimes: Everything Is Connected, Everyone Is Vulnerable and What We Can Do About It
by Marc Goodman
Published 24 Feb 2015

Then, in 2008, something astounding happened: the creation of so-called next-generation sequencers caused the price of decoding human genomes to plummet. As a result, improvements in genetic sequencing outpaced advances in computing by five times. By 2014, we had reached the age of the $1,000 whole-genome mapping. Companies such as 23andMe were offering home DNA test kits to the general public for $99 or less, allowing them to merely spit into a plastic tube, ship it off via a prepaid envelope, and a week or two later receive health, ancestry, and genealogy results online. Looking forward, the trend in DNA sequencing suggests that in a few years the price of DNA sequencing will drop to the point that some company will pay to sequence new customers, reducing the out-of-pocket costs to free—a widely used business model in computer technology.

Human Diversity: The Biology of Gender, Race, and Class
by Charles Murray
Published 28 Jan 2020

Take, for example, the 1979 and 1997 cohorts of the National Longitudinal Survey of Youth, two of the most widely used American databases. Almost all of the members of those samples are still alive and most of their whereabouts are known. Ask them for cheek swabs in return for the kind of genomic information for which 23andMe charges a few hundred dollars. We may be genotyping people at age 60, but in doing so we get virtually the same baseline information that we would have gotten had we genotyped them at birth.39 If we want to explore intergenerational effects, we can genotype the parents and the offspring of the members of these samples.

The Transhumanist Reader
by Max More and Natasha Vita-More
Published 4 Mar 2013

Advances in human whole genome testing will likely become available by 2014 so that every person’s entire complement of genes can be scanned and known at his or her physician’s office for as little as $1,000 (National Cancer Institute 2009). Once whole genome testing is perfected we will all learn what even our randomly conferred genes may predispose us to do and from what future ills we are likely suffer. Already, my relatively inexpensive genotype scan from 23andMe tells me that I have alleles that give me a somewhat greater risk of developing celiac disease, a lower risk of rheumatoid arthritis, and a gene variant that some studies suggest can increase my risk of substance abuse (of both alcohol and “street” drugs) fourfold. With ­accumulation of genetic understanding, human freedom will then properly be seen as acting to overcome these predispositions, much like a former alcoholic can overcome his thirst for booze.