lifelogging

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pages: 371 words: 108,317

The Inevitable: Understanding the 12 Technological Forces That Will Shape Our Future by Kevin Kelly

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This passive type of tracking is sometimes called lifelogging. The idea is to simply, mechanically, automatically, mindlessly, completely track everything all the time. Record everything that is recordable without prejudice, and for all your life. You only pay attention to it in the future when you may need it. Lifelogging is a hugely wasteful and inefficient process since most of what you lifelog is never used. But like many inefficient processes (such as evolution), it also contains genius. Lifelogging is possible now only because computation and storage and sensors have become so cheap that we can waste them with little cost. But creative “wasting” of computation has been the recipe for many of the most successful digital products and companies, and the benefits of lifelogging also lie in its extravagant use of computation.

He also recorded many of his conversations, which enabled him to “scroll back” whenever there was disagreement on what had been said. He also scanned all his incoming pieces of paper into digital files and transcribed every phone conversation (with permission). Part of the intent of this experiment was to find out what kind of lifelogging tools Microsoft might want to invent to help workers manage the ocean of data this lifelogging generates—because making sense of all this data is a far bigger challenge than merely recording it. The point of lifelogging is to create total recall. If a lifelog records everything in your life, then it could recover anything you experienced even if your meaty mind may have forgotten it. It would be like being able to google your life, if in fact your life were being indexed and fully saved. Our biological memories are so spotty that any compensation would be a huge win.

A complete passive archive of everything that you have ever produced, wrote, or said. Deep comparative analysis of your activities could assist your productivity and creativity. A way of organizing, shaping, and “reading” your own life. To the degree this lifelog is shared, this archive of information could be leveraged to help others work and to amplify social interactions. In the health realm, shared medical logs could rapidly advance medical discoveries. For many skeptics, there are two challenges that will doom lifelogging to a small minority. First, current social pressure casts self-tracking as the geekiest thing you could possibly do. Owners of Google Glass quickly put them away because they didn’t like how they looked and they felt uncomfortable recording among their friends—or even uncomfortable explaining why they were not recording.


pages: 606 words: 157,120

To Save Everything, Click Here: The Folly of Technological Solutionism by Evgeny Morozov

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Thus, in Your Life, Uploaded, his book-length manifesto on the benefits of lifelogging, Bell assures us that it will yield “enhanced self-insight, the ability to relive one’s own life story in Proustian detail, the freedom to memorize less and think creatively more, and even a measure of earthly immortality by being cyberized.” Armed with a SenseCam, Proust would be a sure viral hit on Instagram. Bell has little use for terms like “self-tracking” and “quantified self”; instead, he describes his hobby as “lifelogging.” Numbers play a minor role in his quest; it’s not so much about generating statistics as about taming the inefficiency and unfaithfulness of human memory. Still, Bell wouldn’t miss a chance to draw an inference or two from all the data he’s accumulated. His rhetoric repeatedly emphasizes various lifesaving opportunities offered by lifelogging—even if they come at the cost of turning us into perpetually anxious individuals with little choice but to track the previously invisible and inconsequential aspects of our existence.

We shouldn’t mistake the easy availability of quick technological fixes for their moral desirability; the latter is anything but assured, and the seemingly uncontroversial moral truths that underpin both lifelogging and file-expiration technologies cannot be taken for granted. The cheap and artificial models of human memory peddled by technologists like Bell ought to be recognized for what they are: cheaper and faster ways of storing data. The Nutritional Aspects of Jerry Springer Where lifeloggers like Gordon Bell try to recruit new converts by invoking our civic duty to remember, another nascent geek movement reminds us that we have a responsibility to consume information conscientiously and think about its nutritional value. This is an outgrowth of the Quantified Self movement, but with an unusual civic streak. The hope here is that self-tracking and lifelogging will make us more aware of what we read on a daily basis and that we will readjust our consumption habits accordingly, with or without active participation from the technology companies that increasingly stand between us and published materials.

NEA Kindle e-reader Kitcher, Philip Knowledge and information reductionism production of Kodakers Kony 2012 campaign Krugman, Paul Kuhn, Thomas Kurzweil, Ray Land records Last Great Thing project Latour, Bruno Law, mass disregard for Laws revision of, and technological enforcement unjust Leaders, and networks Learning, online Lei, Jinna Lerner, Jennifer Lessig, Lawrence and digital preemption and the Internet, permanence of and regulation and transparency Lessing, Theodor Levy, Steven Liberalism, and technology Licensing effect Lifelogging example of See also Quantified Self movement; Self-tracking LinkedIn Lippman, Walter Liquid democracy LiquidFeedback Lohmann, Susanne London, Jack Longo, Justin Lullaby MacKinnon, Rebecca Macroscopism Madison, James Magnet, Shoshana Amielle Maher, Ahmed Malraux, André Manjoo, Farhad Marconi, Guglielmo Margalit, Avishai Maris, Bill Mayer, Marissa Maynaud, Jean McGonigal, Jane McGonigal, Kate McLuhan, Marshall Meal Snap Mechanical objectivity Mechanical Turk (Amazon) Media industry Megaupload Memes and Amazon and filters and algorithms and manipulation vs. authenticity Memory, human vs. computer Mendacity Mendeley Mendelsohn, Daniel Microsoft PhotoDNA Miller, James Minow, Martha Mirror imagery Mitchell, David Molnar, Thomas Monitorial democracy Monopolies Moore, Gordon Moore’s law Morality and authenticity and citizenship revision of, and technological enforcement and situational crime prevention and technology and willpower Motivation and gamification Mubarak, Hosni Music critics Music industry Music Xray MyLifeBits MySpace Narrative imagination Narrative Science National Crime Information Center, FBI National Endowment for Democracy National Endowment for the Arts (NEA) Natural Fuse Nature, and technology Naughton, John NEA.


pages: 397 words: 110,130

Smarter Than You Think: How Technology Is Changing Our Minds for the Better by Clive Thompson

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Google’s famous PageRank system looks at social rankings: If a Web page has been linked to by hundreds of other sites, Google guesses that that page is important in some way. But lifelogs don’t have that sort of social data; unlike blogs or online social networks, they’re a private record used only by you. Without a way to find or make sense of the material, a lifelog’s greatest strength—its byzantine, brain-busting level of detail—becomes, paradoxically, its greatest flaw. Sure, go ahead and archive your every waking moment, but how do you parse it? Review it? Inspect it? Nobody has another life in which to relive their previous one. The lifelogs remind me of Jorge Luis Borges’s story “On Exactitude in Science,” in which a group of cartographers decide to draw a map of their empire with a 1:1 ratio: it is the exact size of the actual empire, with the exact same detail.

The app Evernote has already become popular because of its ability to search for text, even bent or sideways, within photos and documents. • • • Yet the weird truth is that searching a lifelog may not, in the end, be the way we take advantage of our rapidly expanding artificial memory. That’s because, ironically, searching for something leaves our imperfect, gray-matter brain in control. Bell and Gurrin and other lifeloggers have superb records, but they don’t search them unless, while using their own brains, they realize there’s something to look for. And of course, our organic brains are riddled with memory flaws. Bell’s lifelog could well contain the details of a great business idea he had in 1992; but if he’s forgotten he ever had that idea, he’s unlikely to search for it. It remains as remote and unused as if he’d never recorded it at all.

It remains as remote and unused as if he’d never recorded it at all. The real promise of artificial memory isn’t its use as a passive storage device, like a pen-and-paper diary. Instead, future lifelogs are liable to be active—trying to remember things for us. Lifelogs will be far more useful when they harness what computers are uniquely good at: brute-force pattern finding. They can help us make sense of our archives by finding connections and reminding us of what we’ve forgotten. Like the hybrid chess-playing centaurs, the solution is to let the computers do what they do best while letting humans do what they do best. Bradley Rhodes has had a taste of what that feels like. While a student at MIT, he developed the Remembrance Agent, a piece of software that performed one simple task. The agent would observe what he was typing—e-mails, notes, an essay, whatever.


pages: 291 words: 77,596

Total Recall: How the E-Memory Revolution Will Change Everything by C. Gordon Bell, Jim Gemmell

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This isn’t necessarily reticence on their part, because the software tools and hardware accompaniments for easy lifelogging aren’t readily available yet—not quite yet. Through the decade of the 2010s, user-friendly lifelogging applications will proliferate just like any other software niche, and a plethora of cheap devices for sensing, tracking, and compiling all kinds of information from all corners of life will pour steadily into the consumer-electronics market. As this happens, we will see lifelogging start to catch on with the Millennial generation, and older generations too. COLLECTING E-MEMORIES, DISCOVERING WHO YOU ARE It’s impossible to know exactly how long it will take for lifelogging to become common practice, but it’s almost a sure bet that it will do so within a decade. Abstaining from lifelogging will begin to seem more like avoiding the use of e-mail or cell phones, because so many advantages and conveniences will be foregone.

There was enough public outcry over the possible abuses of TIA for it be officially scrapped a few months later. The stink over LifeLog seemed to rest on the fear-driven belief that it amounted to the same thing as TIA. But there was nothing about LifeLog that would have required people to entrust all their personal data to a central server farm in the bowels of the National Security Agency. There was nothing about LifeLog that even implied people would be required to do lifelogging at all. This effort was aimed at helping the individual soldier or officer in a state of information overload. I keep my nose out of partisan politics. I guess that made me naïve enough to imagine someone would just explain the truth of the situation (Safire hadn’t even spoken to anyone at DARPA) and sort things out. Instead, LifeLog was canceled. If I had cared more about politics, I might have been outraged and suspicious that a lot of political decisions were made based on juicy headlines rather than common sense.

Historians ought to jump on the fourth paradigm, and insist on original source material being made readily available. Too many works have relied on secondary sources in the past. And the scope of original sources is about to explode as lifelogging increases. We shall have to see how society evolves to deal with the legacy of e-memories, but I presume that eventually many lifelogs will be opened to a trusted historian to excerpt, if not entirely released to the public. Suppose someone were to release even a quarter of their lifelog posthumously: It would still confront the historians with a corpus vastly larger than they have ever experienced before. As more people lifelog, historians will also have to delve into the e-memories of other related figures as part of their study. Earlier, I pointed out that it was a fallacy to worry about having enough time to watch your whole life.


pages: 598 words: 134,339

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

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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. Already you can install lifelogging apps that record your activities on your smartphone, such as when you talk to friends, play games, watch movies, and so on. But this is just a shadow of what lifelogging will become. In the future, it will include a video record. Google Glass is the first wearable device that has this potential, but others are not far behind. These are examples of the Internet of Things. Environmental sensors will detect pollution levels. Smart inventory and control systems will reduce waste and save money.

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. Google Glass is the first wearable device: Jenna Wortham (8 Mar 2013), “Meet Memoto, the lifelogging camera,” New York Times Blogs, http://bits.blogs.nytimes.com/2013/03/08/meet-memoto-the-lifelogging-camera. Internet of Things: Ken Hess (10 Jan 2014), “The Internet of Things outlook for 2014: Everything connected and communicating,” ZDNet, http://www.zdnet.com/the-internet-of-things-outlook-for-2014-everything-connected-and-communicating-7000024930.

You may be right,” Network World, http://www.networkworld.com/article/2205938/data-center/feel-like-you-rebeing-watched-at-work—you-may-be-right.html. Ann Bednarz (24 Feb 2011), “Pay no attention to that widget recording your every move,” Network World, http://www.networkworld.com/article/2200315/data-breach/pay-no-attention-to-that-widget-recording-your-every-move.html. Josh Bersin (25 Jun 2014), “Quantified self: Meet the quantified employee,” Forbes, http://www.forbes.com/sites/joshbersin/2014/06/25/quantified-self-meet-the-quantified-employee. corporate electronic communications: This is an excellent review of workplace monitoring techniques and their effects on privacy. Corey A. Ciocchetti (2010), “The eavesdropping employer: A twenty-first century framework for employee monitoring,” Daniels College of Business, University of Denver, http://www.futureofprivacy.org/wp-content/uploads/2010/07/The_Eavesdropping_Employer_%20A_Twenty-First_Century_Framework.pdf.


pages: 271 words: 52,814

Blockchain: Blueprint for a New Economy by Melanie Swan

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Broader Perspective blog, September 28, 2014. http://futurememes.blogspot.com/2014/09/blockchain-health-remunerative-health.html. 150 HL7 Standards. “20 Questions for Health IT #5: Bitcoin & Blockchain Technology.” HL7 Standards, September 8, 2014. http://www.hl7standards.com/blog/2014/09/08/20hit-5/. 151 Zimmerman, J. “DNA Block Chain Project Boosts Research, Preserves Patient Anonymity.” CoinDesk, June 27, 2014. http://www.coindesk.com/israels-dna-bits-moves-beyond-currency-with-genes-blockchain/. 152 Swan, M. “Quantified Self Ideology: Personal Data Becomes Big Data.” Slideshare, February 6, 2014. http://www.slideshare.net/lablogga/quantified-self-ideology-personal-data-becomes-big-data. 153 Levine, A.B. “Let’s Talk Bitcoin! #158: Ebola and the Body Blockchain with Kevin J. McKernan.” Let’s Talk Bitcoin podcast, November 1, 2014. http://letstalkbitcoin.com/blog/post/lets-talk-bitcoin-158-ebola-and-the-body-blockchain. 154 McKernan, K. “Niemann-Pick Type C & Ebolavirus: Bitcoin Community Comes Together to Advocate and Fund Open Source Ebolavirus Research.”

Factom is a project developing the idea of batched transaction upload in blocks to the blockchain, using the blockchain attestation/notary hash functionality to batch transactions as a means of avoiding blockchain bloat. Personal Thinking Blockchains More speculatively for the farther future, the notion of blockchain technology as the automated accounting ledger, the quantized-level tracking device, could be extensible to yet another category of record keeping and administration. There could be “personal thinking chains” as a life-logging storage and backup mechanism. The concept is “blockchain technology + in vivo personal connectome” to encode and make useful in a standardized compressed data format all of a person’s thinking. The data could be captured via intracortical recordings, consumer EEGs, brain/computer interfaces, cognitive nanorobots, and other methodologies. Thus, thinking could be instantiated in a blockchain—and really all of an individual’s subjective experience, possibly eventually consciousness, especially if it’s more precisely defined.

Again perhaps speculatively verging on science fiction, ultimately the whole of a society’s history might include not just a public records and document repository, and an Internet archive of all digital activity, but also the mindfiles of individuals. Mindfiles could include the recording of every “transaction” in the sense of capturing every thought and emotion of every entity, human and machine, encoding and archiving this activity into life-logging blockchains. Blockchain Government Another important application developing as part of Blockchain 3.0 is blockchain government; that is, the idea of using blockchain technology to provide services traditionally provided by nation-states in a decentralized, cheaper, more efficient, personalized manner. Many new and different kinds of governance models and services might be possible using blockchain technology.


pages: 527 words: 147,690

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

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At the same time, an incredibly detailed chronicle of your life is created—one that companies with access to this data can sell to commercial partners or mine to sell you products and that you must manage in order to extract any value from it. The quantified-self movement may argue that building up such a cache of data about oneself allows for self-improvement, for changing bad habits, for improving health and quality of life. But an equally important part of the quantified self seems to be sharing that data, turning the act of self-surveillance into a social occasion. Data becomes something to be proud of, something to brag about, not only for what it shows about how one lives his life (look how often I exercise! look at the photos my Memoto took in Tahiti!) but also for the sense that one is being bold by exposing so much of himself for public consumption. Disclosure becomes seen as a good in and of itself, a potentially brave act of radical transparency. One pitfall of lifelogging is how the collection of this data can become normalized, even expected.

—on Facebook are a prominent example, but committed quantified selfers go much further, following the belief of intelligence agencies and Facebook alike, that all data is potentially useful. The collection of data might be its own reward. By lifelogging, as the practice is also called, you can create a vast trove of data on your own life, one that both expands upon and substitutes for your own fallible human memory. In order to satisfy this need, a range of tools has appeared—fitness trackers, wearable cameras, diet apps, automatic check-ins, wearable computers. Some of these devices operate independently of their operators, making the act of self-surveillance autonomous. The Memoto Mini Camera, for instance, clips onto a user’s shirt and automatically takes a photo every thirty seconds. When synced with a computer, the device pulls out what it thinks are the best photos. The strange logic of lifelogging is that devices such as Memoto are somehow empowering, even though they tend to take choices out of the hands of users.

, 149–50 Jezebel blog, 169 Jobs, Steve, 3 Johnson, Benny, 116 journalism and conflicting reports, 108–9 false stories leading to contact with targets, 107–8 feedback loop on social media, 97 immediacy of report vs. facts, 108–10, 113–14 outrage and grievance applied to, 120–21 and tenor of the viral Web, 102–3 See also news organizations journalists overview, ix, 102–3 climate change writer, 333–35, 336–37, 340–41, 343, 346, 347 information overwhelm, 334–36, 340 and social media, 108, 148 and social news, 127 and unconfirmed reports, 110 and virality, 102–3, 105 junk mail with “Daughter Killed in a Car Crash” in address, 279–80 Jurgenson, Nathan, 61 Just Mugshots, 208 Kalanick, Travis, 235 Kardashian, Kim, 67 Karim, Jawed, 15 Karp, David, 27, 29–30 Keller, Jared, 84, 144 Kelly, Kevin, 280–81, 282 Kelly, Ray, 287 Kickstarter Web site, 84 Kirn, Walter, 142–43 Klein, Ezra, 124 Klout, 194–96, 200 Know More Web site (Washington Post:Wonkblog), 123–24 Kunkel, Benjamin, 274 Kurzweil, Ray, 5 labor markets overview, 226, 234–35, 247 Amazon’s Mechanical Turk, 90, 226, 228, 229–30 exploitative nature of, 228–30, 243–44 Gigwalk, 232 social media compared to, 227 TaskRabbit, 222–26, 236–37, 242, 245 workers trapped by, 231–33 See also employment; fractional work Landy, Andy, 187–88 Lanier, Jaron, 138–39, 328 Lasch, Christopher, 23, 45, 319, 342, 343, 345 Law, Rachel, 357–58 Lazewatsky, Miriam, 79–80 Leibovitz, Liel, 348–49 Lenddo, 309 Lenticular printing, 299–300 Leonard, Franklin, 182–83 Lévi-Strauss, Claude, 167–68 libel lawsuit, 113 libertarianism, 1–3, 19. See also cyber-libertarianism life-extension beliefs and research, 5 lifelogging, 136–40 Like, +1, or heart buttons and BuzzFeed listicles, 118–19 as commercial endorsement, 31–33, 34–35 data from, 8, 10, 294, 300 as de facto legal agreement, 26–27 and human nature, 24–26 as limp pat on the back, 52 as people rating system, 190–92 scoreboard function, 48 See also retweets and reblogs like economy, 35 liking studies, 24 linkbait, 104, 125, 125n LinkedIn, 35, 165, 181, 199, 323 Lippmann, Walter, 249 listicles, 114–15, 116–17, 118–19, 123, 261 ListiClock, 118 Lithium Technologies, 196 log-ins, 160, 165–66, 182 London, England, 306 Losse, Katherine, 6, 8, 12, 48, 129, 323, 327 Luddism and Luddites, x, 48 lurkers, 49 Lyft, 235 Lyon, David, 129, 316 MAC (media access control) address, 99 MAC address identifications, 306 Madrigal, Alexis, 25 Maimonides, 179–80 manipulation to obtain free labor, 260–63, 264–65 pricing based on purchaser’s ability to pay, 318 Manjoo, Farhad, 65, 262 Marconi, Guglielmo, 2, 3 market inefficiencies, 234, 235, 240, 243, 245 marketing boosting likes with prizes, 32 celebrity-driven campaigns, 89, 93–94 consumers joining companies in marketing process, 32–33, 34–35, 58–60 Facebook slogan, 12 follower services, 85–87, 88–89 liking studies, 24 marketing as journalism, 27–28 telemarketing, 43 tradition of deception, 92–94 and viral media, 68–69 See also advertising market intelligence, 35–36, 216–17 MarketPsy Capital, 37 Mastering the Internet project, Britain, 314 Master Switch, The (Wu), 67 Matlin, Chadwick, 119 McCoy, Terrence, 68 McDonaldization of Society, The (Ritzer), 270 McGillvary, Caleb “Kai,” 70 Mechanical Turk, 90, 226, 228, 229–30 Medbase2000, 318–19 MediaBrix, 304 media recommendations, 202 Mediated (Zengotita), 120 memes advertisers appropriation of, 60 amplifiers for, 88–89 false stories, 107–8, 109, 111, 113 of Hilton and Kardashian, 67 inflationary rhetoric for, 102–3 and informational appetite, 322 from local newscasts, 69–72 Old Spice guy as, 93 as one greedy industry meeting another, 84–85 poverty and urban crime, 72–73 reworking and corrections, 105, 106–7 unemployed college graduate’s story, 220–26 Memoto Mini Camera, 137–38 messaging apps, 156, 259 Messenger smartphone app, 177 metadata, 131 Metal Rabbit Media, 213 metrics advertising, 97–99 audience, 95–96, 101–2, 103 biometric tools, 305–6 Facebook, 152, 358–59 followers, 53 hits at a Web site, 102 influence scores, 194, 197–98 page views, 98, 102 as reminder of how well others are doing, 152–53 Twitter, 87, 96–97, 348–49 unique visitors, 96, 102 for Upworthy, 102 See also page views micro-fame, 149–50, 152, 196–97, 206 Microsoft, 195, 296, 311–12 micro-targeting listicles, 118–19 micro-work.


pages: 329 words: 93,655

Moonwalking With Einstein by Joshua Foer

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Albert Einstein, Asperger Syndrome, Berlin Wall, conceptual framework, deliberate practice, Fall of the Berlin Wall, Frank Gehry, lifelogging, mental accounting, patient HM, pattern recognition, Rubik’s Cube, speech recognition, Stephen Hawking, zero-sum game

With the SenseCam, he is trying to fix an elemental human problem: that we forget our lives almost as fast as we live them. But why should any memory fade when there are technological solutions that can preserve it? In 1998, with the help of his assistant Vicki Rozyki, Bell began backfilling his lifelog by systematically scanning every document in the dozens of banker boxes he’d amassed since the 1950s. All of his old photos, engineering notebooks, and papers were digitized. Even the logos on his T-shirts couldn’t escape the scanner bed. Bell, who had always been a meticulous preservationist, figures he’s probably scanned and thrown away three quarters of all the stuff he’s ever owned. Today his lifelog takes up 170 gigabytes, and is growing at the rate of about a gigabyte each month. It includes over 100,000 e-mails, 65,000 photos, 100,000 documents, and 2,000 phone calls. It fits comfortably on a hundred-dollar hard drive.

For now, Bell’s internal and external memories don’t mesh seamlessly. In order for him to access one of his stored external memories, he still has to find it on his computer and “re-input” it into his brain through his eyes and ears. His lifelog may be an extension of him, but it’s not yet a part of him. But is it so far-fetched to believe that at some point in the not-too-distant future the chasm between what Bell’s computer knows and what his mind knows may disappear entirely? Eventually, our brains may be connected directly and seamlessly to our lifelogs, so that our external memories will function and feel as if they are entirely internal. And of course, they will also be connected to the greatest external memory repository of all, the Internet. A surrogate memory that recalls everything and can be accessed as naturally as the memories stored in our neurons: It would be the decisive weapon in the war against forgetting.

In fact, what we think of as “me” is almost certainly something far more diffuse and hazier than it’s comfortable to contemplate. At the least, most people assume that their self could not possibly extend beyond the boundaries of their epidermis into books, computers, a lifelog. But why should that be the case? Our memories, the essence of our selfhood, are actually bound up in a whole lot more than the neurons in our brain. At least as far back as Socrates’s diatribe against writing, our memories have always extended beyond our brains and into other storage containers. Bell’s lifelogging project simply brings that truth into focus. EIGHT THE OK PLATEAU If you visited my office in the fall of 2005, you would have seen a Post-it note—one of my external memories—stuck to the wall above my computer monitor. Whenever my eyes strayed from the screen, I saw the words “Don’t Forget to Remember,” a gentle reminder that for the next several months until the U.S.

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

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Bayesian statistics, business intelligence, business process, cellular automata, Celtic Tiger, cloud computing, collateralized debt obligation, conceptual framework, congestion charging, corporate governance, correlation does not imply causation, crowdsourcing, discrete time, George Gilder, Google Earth, Infrastructure as a Service, Internet Archive, Internet of things, invisible hand, knowledge economy, late capitalism, lifelogging, linked data, Masdar, means of production, Nate Silver, natural language processing, openstreetmap, pattern recognition, platform as a service, recommendation engine, RFID, semantic web, sentiment analysis, slashdot, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, smart grid, smart meter, software as a service, statistical model, supply-chain management, the scientific method, The Signal and the Noise by Nate Silver, transaction costs

Such technologies are in an initial phase of development and there are visions for much more comprehensive life-logs that would create a unified, digital record of an individual’s experiences, captured multimodally through digital sensors and stored permanently as a personal multimedia archive (Mann et al. 2003), with a number of research prototypes being developed. Life-logs aim to create a continuous, searchable, analysable record of the past that includes every action, every event, every conversation, every location visited, every material expression of an individual’s life, as well as physiological conditions inside the body and external conditions (e.g., orientation, temperature, levels of pollution) (Dodge and Kitchin 2007b) – ‘the totality of information that flows through a human life’ (Johnson 2003: 85). Clearly the production of such life-logs raise a number of questions concerning privacy, the ownership of the data produced, and how such data are used (Dodge and Kitchin 2007b).

In contrast to surveillance, in which an individual is monitored from an external position by another entity, sousveillance is consciously employed and controlled by an individual for personal fulfilment, providing an interior, first-person perspective on their lives. Over the past decade, a sousveillance movement has developed of people who actively monitor and record their personal data (also known as the quantified self movement). In general, individuals are monitoring aspects of health and fitness, capturing data consumption (e.g., food/calorie intake), physical states (e.g., blood pressure, pulse) emotional states (e.g., mood, arousal) and performance (e.g., miles walked/run/cycled, hours slept and types of sleep), with a number of companies providing associated self-monitoring technologies and services.

Index A/B testing 112 abduction 133, 137, 138–139, 148 accountability 34, 44, 49, 55, 63, 66, 113, 116, 165, 171, 180 address e-mail 42 IP 8, 167, 171 place 8, 32, 42, 45, 52, 93, 171 Web 105 administration 17, 30, 34, 40, 42, 56, 64, 67, 87, 89, 114–115, 116, 124, 174, 180, 182 aggregation 8, 14, 101, 140, 169, 171 algorithm 5, 9, 21, 45, 76, 77, 83, 85, 89, 101, 102, 103, 106, 109, 111, 112, 118, 119, 122, 125, 127, 130, 131, 134, 136, 142, 146, 154, 160, 172, 177, 179, 181, 187 Amazon 72, 96, 131, 134 Anderson, C. 130, 135 Andrejevic, M. 133, 167, 178 animation 106, 107 anonymity 57, 63, 79, 90, 92, 116, 167, 170, 171, 172, 178 apophenia 158, 159 Application Programming Interfaces (APIs) 57, 95, 152, 154 apps 34, 59, 62, 64, 65, 78, 86, 89, 90, 95, 97, 125, 151, 170, 174, 177 archive 21, 22, 24, 25, 29–41, 48, 68, 95, 151, 153, 185 archiving 23, 29–31, 64, 65, 141 artificial intelligence 101, 103 Acxiom 43, 44 astronomy 34, 41, 72, 97 ATM 92, 116 audio 74, 77, 83 automatic meter reading (AMR) 89 automatic number plate recognition (ANPR) 85, 89 automation 32, 51, 83, 85, 87, 89–90, 98, 99, 102, 103, 118, 127, 136, 141, 146, 180 Ayasdi 132, 134 backup 29, 31, 40, 64, 163 barcode 74, 85, 92, Bates, J. 56, 61, 62, 182 Batty, M. 90, 111, 112, 140 Berry, D. 134, 141 bias 13, 14, 19, 28, 45, 101, 134–136, 153, 154, 155, 160 Big Brother 126, 180 big data xv, xvi, xvii, 2, 6, 13, 16, 20, 21, 27–29, 42, 46, 67–183, 186, 187, 188, 190, 191, 192 analysis 100–112 characteristics 27–29, 67–79 enablers 80–87 epistemology 128–148 ethical issues 165–183 etymology 67 organisational issues 160–163 rationale 113–127 sources 87–99 technical issues 149–160 biological sciences 128–129, 137 biometric data 8, 84, 115 DNA 8, 71, 84 face 85, 88, 105 fingerprints 8, 9, 84, 87, 88, 115 gait 85, 88 iris 8, 84, 88 bit-rot 20 blog 6, 95, 170 Bonferroni principle 159 born digital 32, 46, 141 Bowker, G. 2, 19, 20, 22, 24 Borgman, C. 2, 7, 10, 20, 30, 37, 40, 41 boyd, D. 68, 75, 151, 152, 156, 158, 160, 182 Brooks, D. 130, 145 business 1, 16, 42, 45, 56, 61, 62, 67, 79, 110, 113–127, 130, 137, 149, 152, 161, 166, 172, 173, 187 calculative practices 115–116 Campbell’s Law 63, 127 camera 6, 81, 83, 87, 88, 89, 90, 107, 116, 124, 167, 178, 180 capitalism 15, 16, 21, 59, 61, 62, 86, 95, 114, 119–123, 126, 136, 161, 184, 186 capta 2 categorization 6, 8, 12, 19, 20, 102, 106, 176 causation 130, 132, 135, 147 CCTV 87, 88, 180 census 17, 18, 19, 22, 24, 27, 30, 43, 54, 68, 74, 75, 76, 77, 87, 102, 115, 157, 176 Centro De Operações Prefeitura Do Rio 124–125, 182 CERN 72, 82 citizen science 97–99, 155 citizens xvi, 45, 57, 58, 61, 63, 71, 88, 114, 115, 116, 126, 127, 165, 166, 167, 174, 176, 179, 187 citizenship 55, 115, 170, 174 classification 6, 10, 11, 23, 28, 104, 105, 157, 176 clickstream 43, 92, 94, 120, 122, 154, 176 clustering 103, 104, 105, 106, 110, 122 Codd, E. 31 competitiveness xvi, 16, 114, computation 2, 4, 5, 6, 29, 32, 68, 80, 81–82, 83, 84, 86, 98, 100, 101, 102, 110, 129, 136, 139–147, 181 computational social science xiv, 139–147, 152, 186 computing cloud xv, 81, 86 distributed xv, 37, 78, 81, 83, 98 mobile xv, 44, 78, 80, 81, 83, 85, 139 pervasive 81, 83–84, 98, 124 ubiquitous 80, 81, 83–84, 98, 100, 124, 126 confidence level 14, 37, 133, 153, 160 confidentiality 8, 169, 175 control creep 126, 166, 178–179 cookies 92, 119, 171 copyright 16, 30, 40, 49, 51, 54, 96 correlation 105, 110, 130, 131, 132, 135, 145, 147, 157, 159 cost xv, 6, 11, 16, 27, 31, 32, 37, 38, 39, 40, 44, 52, 54, 57, 58, 59, 61, 66, 80, 81, 83, 85, 93, 96, 100, 116, 117, 118, 120, 127, 150 Crawford, K. 68, 75, 135, 151, 152, 155, 156, 158, 160, 182 credit cards 8, 13, 42, 44, 45, 85, 92, 167, 171, 176 risk 42, 63, 75, 120, 176, 177 crime 55, 115, 116, 123, 175, 179 crowdsourcing 37, 73, 93, 96–97, 155, 160 Cukier, K. 68, 71, 72, 91, 114, 128, 153, 154, 161, 174 customer relationship management (CRM) 42, 99, 117–118, 120, 122, 176 cyber-infrastructure 33, 34, 35, 41, 186 dashboard 106, 107, 108 data accuracy 12, 14, 110, 153, 154, 171 administrative 84–85, 89, 115, 116, 125, 150, 178 aggregators see data brokers amplification 8, 76, 99, 102, 167 analogue 1, 3, 32, 83, 88, 140, 141 analytics 42, 43, 63, 73, 80, 100–112, 116, 118, 119, 120, 124, 125, 129, 132, 134, 137, 139, 140, 145, 146, 149, 151, 159, 160, 161, 176, 179, 186, 191 archive see archive assemblage xvi, xvii, 2, 17, 22, 24–26, 66, 80, 83, 99, 117, 135, 139, 183, 184–192 attribute 4, 8–9, 31, 115, 150 auditing 33, 40, 64, 163 authenticity 12, 153 automated see automation bias see bias big see big data binary 1, 4, 32, 69 biometric see biometric data body 177–178, 187 boosterism xvi, 67, 127, 187, 192 brokers 42–45, 46, 57, 74, 75, 167, 183, 186, 187, 188, 191 calibration 13, 20 catalogue 32, 33, 35 clean 12, 40, 64, 86, 100, 101, 102, 152, 153, 154, 156 clearing house 33 commodity xvi, 4, 10, 12, 15, 16, 41, 42–45, 56, 161 commons 16, 42 consolidators see data brokers cooked 20, 21 corruption 19, 30 curation 9, 29, 30, 34, 36, 57, 141 definition 1, 2–4 deluge xv, 28, 73, 79, 100, 112, 130, 147, 149–151, 157, 168, 175 derived 1, 2, 3, 6–7, 8, 31, 32, 37, 42, 43, 44, 45, 62, 86, 178 deserts xvi, 28, 80, 147, 149–151, 161 determinism 45, 135 digital 1, 15, 31, 32, 67, 69, 71, 77, 82, 85, 86, 90, 137 directories 33, 35 dirty 29, 154, 163 dive 64–65, 188 documentation 20, 30, 31, 40, 64, 163 dredging 135, 147, 158, 159 dump 64, 150, 163 dynamic see dynamic data enrichment 102 error 13, 14, 44, 45, 101, 110, 153, 154, 156, 169, 175, 180 etymology 2–3, 67 exhaust 6–7, 29, 80, 90 fidelity 34, 40, 55, 79, 152–156 fishing see data dredging formats xvi, 3, 5, 6, 9, 22, 25, 30, 33, 34, 40, 51, 52, 54, 65, 77, 102, 153, 156, 157, 174 framing 12–26, 133–136, 185–188 gamed 154 holding 33, 35, 64 infrastructure xv, xvi, xvii, 2, 21–24, 25, 27–47, 52, 64, 102, 112, 113, 128, 129, 136, 140, 143, 147, 148, 149, 150, 156, 160, 161, 162, 163, 166, 184, 185, 186, 188, 189, 190, 191, 192 integration 42, 149, 156–157 integrity 12, 30, 33, 34, 37, 40, 51, 154, 157, 171 interaction 43, 72, 75, 85, 92–93, 94, 111, 167 interoperability 9, 23, 24, 34, 40, 52, 64, 66, 156–157, 163, 184 interval 5, 110 licensing see licensing lineage 9, 152–156 linked see linked data lost 5, 30, 31, 39, 56, 150 markets xvi, 8, 15, 25, 42-45, 56, 59, 75, 167, 178 materiality see materiality meta see metadata mining 5, 77, 101, 103, 104–106, 109, 110, 112, 129, 132, 138, 159, 188 minimisation 45, 171, 178, 180 nominal 5, 110 ordinal 5, 110 open see open data ontology 12, 28, 54, 150 operational 3 ownership 16, 40, 96, 156, 166 preparation 40, 41, 54, 101–102 philosophy of 1, 2, 14, 17–21, 22, 25, 128–148, 185–188 policy 14, 23, 30, 33, 34, 37, 40, 48, 64, 160, 163, 170, 172, 173, 178 portals 24, 33, 34, 35 primary 3, 7–8, 9, 50, 90 preservation 30, 31, 34, 36, 39, 40, 64, 163 protection 15, 16, 17, 20, 23, 28, 40, 45, 62, 63, 64, 167, 168–174, 175, 178, 188 protocols 23, 25, 30, 34, 37 provenance 9, 30, 40, 79, 153, 156, 179 qualitative 4–5, 6, 14, 146, 191 quantitative 4–5, 14, 109, 127, 136, 144, 145, 191 quality 12, 13, 14, 34, 37, 40, 45, 52, 55, 57, 58, 64, 79, 102, 149, 151, 152–156, 157, 158 raw 1, 2, 6, 9, 20, 86, 185 ratio 5, 110 real-time 65, 68, 71, 73, 76, 88, 89, 91, 99, 102, 106, 107, 116, 118, 121, 124, 125, 139, 151, 181 reduction 5, 101–102 representative 4, 8, 13, 19, 21, 28 relational 3, 8, 28, 44, 68, 74–76, 79, 84, 85, 87, 88, 99, 100, 119, 140, 156, 166, 167, 184 reliability 12, 13–14, 52, 135, 155 resellers see data brokers resolution 7, 26, 27, 28, 68, 72, 73–74, 79, 84, 85, 89, 92, 133–134, 139, 140, 150, 180 reuse 7, 27, 29, 30, 31, 32, 39, 40, 41, 42, 46, 48, 49–50, 52, 56, 59, 61, 64, 102, 113, 163 scaled xvi, xvii 32, 100, 101, 112, 138, 149, 150, 163, 186 scarcity xv, xvi, 28, 80, 149–151, 161 science xvi, 100–112, 130, 137–139, 148, 151, 158, 160–163, 164, 191 secondary 3, 7–8 security see security selection 101, 176 semi-structured 4, 5–6, 77, 100, 105 sensitive 15, 16, 45, 63, 64, 137, 151, 167, 168, 171, 173, 174 shadow 166–168, 177, 179, 180 sharing 9, 11, 20, 21, 23, 24, 27, 29–41, 48–66, 80, 82, 95, 113, 141, 151, 174, 186 small see small data social construction 19–24 spatial 17, 52, 63, 68, 73, 75, 84–85, 88–89 standards xvi, 9, 14, 19, 22, 23, 24, 25, 31, 33, 34, 38, 40, 52, 53, 64, 102, 153, 156, 157 storage see storage stranded 156 structures 4, 5–6, 12, 21, 23, 30, 31, 40, 51, 68, 77, 86, 103, 106, 156 structured 4, 5–6, 11, 32, 52, 68, 71, 75, 77, 79, 86, 88, 105, 112, 163 tertiary 7–8, 9, 27, 74 time-series 68, 102, 106, 110 transient 6–7, 72, 150 transactional 42, 43, 71, 72, 74, 75, 85, 92, 93–94, 120, 122, 131, 167, 175, 176, 177 uncertainty see uncertainty unstructured 4, 5–6, 32, 52, 68, 71, 75, 77, 86, 100, 105, 112, 140, 153, 157 validity 12, 40, 72, 102, 135, 138, 154, 156, 158 variety 26, 28, 43, 44, 46, 68, 77, 79, 86, 139, 140, 166, 184 velocity 26, 28, 29, 68, 76–77, 78, 79, 86, 88, 102, 106, 112. 117, 140, 150, 153, 156, 184 veracity 13, 79, 102, 135, 152–156, 157, 163 volume 7, 26, 27, 28, 29, 32, 46, 67, 68, 69–72, 74, 76, 77, 78, 79, 86, 102, 106, 110, 125, 130, 135, 140, 141, 150, 156, 166, 184 volunteered 87, 93–98, 99, 155 databank 29, 34, 43 database NoSQL 6, 32, 77, 78, 86–87 relational 5, 6, 8, 32–33, 43, 74–75, 77, 78, 86, 100, 105 data-driven science 133, 137–139, 186 data-ism 130 datafication 181 dataveillance 15, 116, 126, 157, 166–168, 180, 181, 182, 184 decision tree 104, 111, 122, 159, deconstruction 24, 98, 126, 189–190 decontextualisation 22 deduction 132, 133, 134, 137, 138, 139, 148 deidentification 171, 172, 178 democracy 48, 55, 62, 63, 96, 117, 170 description 9, 101, 104, 109, 143, 147, 151, 190 designated community 30–31, 33, 46 digital devices 13, 25, 80, 81, 83, 84, 87, 90–91, 167, 174, 175 humanities xvi, 139–147, 152, 186 object identifier 8, 74 serendipity 134 discourse 15, 20, 55, 113–114, 117, 122, 127, 192 discursive regime 15, 20, 24, 56, 98, 113–114, 116, 123, 126, 127, 190 disruptive innovation xv, 68, 147, 184, 192 distributed computing xv, 37, 78, 81, 83, 98 sensors 124, 139, 160 storage 34, 37, 68, 78, 80, 81, 85–87, 97 division of labour 16 Dodge, M. 2, 21, 68, 73, 74, 76, 83, 84, 85, 89, 90, 92, 93, 96, 113, 115, 116, 124, 154, 155, 167, 177, 178, 179, 180, 189 driver’s licence 45, 87, 171 drone 88, Dublin Core 9 dynamic data xv, xvi, 76–77, 86, 106, 112 pricing 16, 120, 123, 177 eBureau 43, 44 ecological fallacy 14, 102, 135, 149, 158–160 Economist, The 58, 67, 69, 70, 72, 128 efficiency 16, 38, 55, 56, 59, 66, 77, 93, 102, 111, 114, 116, 118, 119, 174, 176 e-mail 71, 72–73, 82, 85, 90, 93, 116, 174, 190 empiricism 129, 130–137, 141, 186 empowerment 61, 62–63, 93, 115, 126, 165 encryption 171, 175 Enlightenment 114 Enterprise Resource Planning (ERP) 99, 117, 120 entity extraction 105 epistemology 3, 12, 19, 73, 79, 112, 128–148, 149, 185, 186 Epsilon 43 ethics 12, 14–15, 16, 19, 26, 30, 31, 40, 41, 64, 73, 99, 128, 144, 151, 163, 165–183, 186 ethnography 78, 189, 190, 191 European Union 31, 38, 45, 49, 58, 59, 70, 157, 168, 173, 178 everyware 83 exhaustive 13, 27, 28, 68, 72–73, 79, 83, 88, 100, 110, 118, 133–134, 140, 150, 153, 166, 184 explanation 101, 109, 132, 133, 134, 137, 151 extensionality 67, 78, 140, 184 experiment 2, 3, 6, 34, 75, 78, 118, 129, 131, 137, 146, 150, 160 Facebook 6, 28, 43, 71, 72, 77, 78, 85, 94, 119, 154, 170 facts 3, 4, 9, 10, 52, 140, 159 Fair Information Practice Principles 170–171, 172 false positive 159 Federal Trade Commission (FTC) 45, 173 flexibility 27, 28, 68, 77–78, 79, 86, 140, 157, 184 Flickr 95, 170 Flightradar 107 Floridi, L. 3, 4, 9, 10, 11, 73, 112, 130, 151 Foucault, M. 16, 113, 114, 189 Fourth paradigm 129–139 Franks, B. 6, 111, 154 freedom of information 48 freemium service 60 funding 15, 28, 29, 31, 34, 37, 38, 40, 41, 46, 48, 52, 54–55, 56, 57–58, 59, 60, 61, 65, 67, 75, 119, 143, 189 geographic information systems 147 genealogy 98, 127, 189–190 Gitelman, L. 2, 19, 20, 21, 22 Global Positioning System (GPS) 58, 59, 73, 85, 88, 90, 121, 154, 169 Google 32, 71, 73, 78, 86, 106, 109, 134, 170 governance 15, 21, 22, 23, 38, 40, 55, 63, 64, 66, 85, 87, 89, 117, 124, 126, 136, 168, 170, 178–182, 186, 187, 189 anticipatory 126, 166, 178–179 technocratic 126, 179–182 governmentality xvi, 15, 23, 25, 40, 87, 115, 127, 168, 185, 191 Gray, J. 129–130 Guardian, The 49 Gurstein, M. 52, 62, 63 hacking 45, 154, 174, 175 hackathon 64–65, 96, 97, 188, 191 Hadoop 87 hardware 32, 34, 40, 63, 78, 83, 84, 124, 143, 160 human resourcing 112, 160–163 hype cycle 67 hypothesis 129, 131, 132, 133, 137, 191 IBM 70, 123, 124, 143, 162, 182 identification 8, 44, 68, 73, 74, 77, 84–85, 87, 90, 92, 115, 169, 171, 172 ideology 4, 14, 25, 61, 113, 126, 128, 130, 134, 140, 144, 185, 190 immutable mobiles 22 independence 3, 19, 20, 24, 100 indexical 4, 8–9, 32, 44, 68, 73–74, 79, 81, 84–85, 88, 91, 98, 115, 150, 156, 167, 184 indicator 13, 62, 76, 102, 127 induction 133, 134, 137, 138, 148 information xvii, 1, 3, 4, 6, 9–12, 13, 23, 26, 31, 33, 42, 44, 45, 48, 53, 67, 70, 74, 75, 77, 92, 93, 94, 95, 96, 100, 101, 104, 105, 109, 110, 119, 125, 130, 138, 140, 151, 154, 158, 161, 168, 169, 171, 174, 175, 184, 192 amplification effect 76 freedom of 48 management 80, 100 overload xvi public sector 48 system 34, 65, 85, 117, 181 visualisation 109 information and communication technologies (ICTs) xvi, 37, 80, 83–84, 92, 93, 123, 124 Innocentive 96, 97 INSPIRE 157 instrumental rationality 181 internet 9, 32, 42, 49, 52, 53, 66, 70, 74, 80, 81, 82, 83, 86, 92, 94, 96, 116, 125, 167 of things xv, xvi, 71, 84, 92, 175 intellectual property rights xvi, 11, 12, 16, 25, 30, 31, 40, 41, 49, 50, 56, 62, 152, 166 Intelius 43, 44 intelligent transportation systems (ITS) 89, 124 interoperability 9, 23, 24, 34, 40, 52, 64, 66, 149, 156–157, 163, 184 interpellation 165, 180, 188 interviews 13, 15, 19, 78, 155, 190 Issenberg, S. 75, 76, 78, 119 jurisdiction 17, 25, 51, 56, 57, 74, 114, 116 Kafka 180 knowledge xvii, 1, 3, 9–12, 19, 20, 22, 25, 48, 53, 55, 58, 63, 67, 93, 96, 110, 111, 118, 128, 130, 134, 136, 138, 142, 159, 160, 161, 162, 187, 192 contextual 48, 64, 132, 136–137, 143, 144, 187 discovery techniques 77, 138 driven science 139 economy 16, 38, 49 production of 16, 20, 21, 24, 26, 37, 41, 112, 117, 134, 137, 144, 184, 185 pyramid 9–10, 12, situated 16, 20, 28, 135, 137, 189 Latour, B. 22, 133 Lauriault, T.P. 15, 16, 17, 23, 24, 30, 31, 33, 37, 38, 40, 153 law of telecosm 82 legal issues xvi, 1, 23, 25, 30, 31, 115, 165–179, 182, 183, 187, 188 levels of measurement 4, 5 libraries 31, 32, 52, 71, 141, 142 licensing 14, 25, 40, 42, 48, 49, 51, 53, 57, 73, 96, 151 LIDAR 88, 89, 139 linked data xvii, 52–54, 66, 156 longitudinal study 13, 76, 140, 149, 150, 160 Lyon, D. 44, 74, 87, 167, 178, 180 machine learning 5, 6, 101, 102–104, 106, 111, 136, 188 readable 6, 52, 54, 81, 84–85, 90, 92, 98 vision 106 management 62, 88, 117–119, 120, 121, 124, 125, 131, 162, 181 Manovich, L. 141, 146, 152, 155 Manyika, J. 6, 16, 70, 71, 72, 104, 116, 118, 119, 120, 121, 122, 161 map 5, 22, 24, 34, 48, 54, 56, 73, 85, 88, 93, 96, 106, 107, 109, 115, 143, 144, 147, 154, 155–156, 157, 190 MapReduce 86, 87 marginal cost 11, 32, 57, 58, 59, 66, 151 marketing 8, 44, 58, 73, 117, 119, 120–123, 131, 176 marketisation 56, 61–62, 182 materiality 4, 19, 21, 24, 25, 66, 183, 185, 186, 189, 190 Mattern, S. 137, 181 Mayer-Schonberger, V. 68, 71, 72, 91, 114, 153, 154, 174 measurement 1, 3, 5, 6, 10, 12, 13, 15, 19, 23, 69, 97, 98, 115, 128, 166 metadata xvi, 1, 3, 4, 6, 8–9, 13, 22, 24, 29, 30, 31, 33, 35, 40, 43, 50, 54, 64, 71, 72, 74, 78, 85, 91, 93, 102, 105, 153, 155, 156 methodology 145, 158, 185 middleware 34 military intelligence 71, 116, 175 Miller, H.J. xvi, 27, 100, 101, 103, 104, 138, 139, 159 Minelli, M. 101, 120, 137, 168, 170, 171, 172, 174, 176 mixed methods 147, 191 mobile apps 78 computing xv, 44, 78, 80, 81, 83, 85, 139 mapping 88 phones 76, 81, 83, 90, 93, 151, 168, 170, 175 storage 85 mode of production 16 model 7, 11, 12, 24, 32, 37, 44, 57, 72, 73, 101, 103, 105, 106, 109, 110–112, 119, 125, 129, 130, 131, 132, 133, 134, 137, 139, 140, 144, 145, 147, 158–159, 166, 181 agent-based model 111, business 30, 54, 57–60, 61, 95, 118, 119, 121 environmental 139, 166 meteorological 72 time-space 73 transportation 7 modernity 3 Moore’s Law 81, moral philosophy 14 Moretti, F. 141–142 museum 31, 32, 137 NASA 7 National Archives and Records Administration (NARA) 67 National Security Agency (NSA) 45, 116 natural language processing 104, 105 near-field communication 89, 91 neoliberalism 56, 61–62, 126, 182 neural networks 104, 105, 111 New Public Management 62, non-governmental organisations xvi, 43, 55, 56, 73, 117 non-excludable 11, 151 non-rivalrous 11, 57, 151 normality 100, 101 normative thinking 12, 15, 19, 66, 99, 127, 144, 182, 183, 187, 192 Obama, B. 53, 75–76, 78, 118–119 objectivity 2, 17, 19, 20, 62, 135, 146, 185 observant participation 191 oligopticon 133, 167, 180 ontology 3, 12, 17–21, 22, 28, 54, 79, 128, 138, 150, 156, 177, 178, 184, 185 open data xv, xvi, xvii, 2, 12, 16, 21, 25, 48–66, 97, 114, 124, 128, 129, 140, 149, 151, 163, 164, 167, 186, 187, 188, 190, 191, 192 critique of 61–66 economics of 57–60 rationale 54–56 Open Definition 50 OpenGovData 50, 51 Open Knowledge Foundation 49, 52, 55, 58, 189, 190 open science 48, 72, 98 source 48, 56, 60, 87, 96 OpenStreetMap 73, 93, 96, 154, 155–156 optimisation 101, 104, 110–112, 120, 121, 122, 123 Ordnance Survey 54, 57 Organization for Economic Cooperation and Development (OECD) 49, 50, 59 overlearning 158, 159 panoptic 133, 167, 180 paradigm 112, 128–129, 130, 138, 147, 148, 186 participant observation 190, 191 participation 48, 49, 55, 66, 82, 94, 95, 96, 97–98, 126, 155, 165, 180 passport 8, 45, 84, 87, 88, 115 patent 13, 16, 41, 51 pattern recognition 101, 104–106, 134, 135 personally identifiable information 171 philanthropy 32, 38, 58 philosophy of science 112, 128–148, 185–188 phishing 174, 175 phone hacking 45 photography 6, 43, 71, 72, 74, 77, 86, 87, 88, 93, 94, 95, 105, 115, 116, 141, 155, 170 policing 80, 88, 116, 124, 125, 179 political economy xvi, 15–16, 25, 42–45, 182, 185, 188, 191 Pollock, R. 49, 54, 56, 57 58, 59 positivism 129, 136–137, 140, 141, 144, 145, 147 post-positivism 140, 144, 147 positionality 135, 190 power/knowledge 16, 22 predictive modelling 4, 7, 12, 34, 44, 45, 76, 101, 103, 104, 110–112, 118, 119, 120, 125, 132, 140, 147, 168, 179 profiling 110–112, 175–178, 179, 180 prescription 101 pre-analytical 2, 3, 19, 20, 185 pre-analytics 101–102, 112 pre-factual 3, 4, 19, 185 PRISM 45, 116 privacy 15, 28, 30, 40, 45, 51, 57, 63, 64, 96, 117, 163, 165, 166, 168–174, 175, 178, 182, 187 privacy by design 45, 173, 174 probability 14, 110, 153, 158 productivity xvi, 16, 39, 55, 66, 92, 114, 118 profiling 12, 42–45, 74, 75, 110–112, 119, 166, 168, 175–178, 179, 180, 187 propriety rights 48, 49, 54, 57, 62 prosumption 93 public good 4, 12, 16, 42, 52, 56, 58, 79, 97 –private partnerships 56, 59 sector information (PSI) 12, 48, 54, 56, 59, 61, 62 quantified self 95 redlining 176, 182 reductionism 73, 136, 140, 142, 143, 145 regression 102, 104, 105, 110, 111, 122 regulation xvi, 15, 16, 23, 25, 40, 44, 46, 83, 85, 87, 89–90, 114, 115, 123, 124, 126, 168, 174, 178, 180, 181–182, 187, 192 research design 7, 13, 14, 77–78, 98, 137–138, 153, 158 Renaissance xvi, 129, 141 repository 29, 33, 34, 41 representativeness 13, 14, 19, 21 Resource Description Framework (RDF) 53, 54 remote sensing 73–74, 105 RFID 74, 85, 90, 91, 169 rhetorical 3, 4, 185 right to be forgotten 45, 172, 187 information (RTI) 48, 62 risk 16, 44, 58, 63, 118, 120, 123, 132, 158, 174, 176–177, 178, 179, 180 Rosenberg, D. 1, 3 Ruppert, E. 22, 112, 157, 163, 187 sampling 13, 14, 27, 28, 46, 68, 72, 73, 77, 78, 88, 100, 101, 102, 120, 126, 133, 138, 139, 146, 149–150, 152, 153, 154, 156, 159 scale of economy 37 scanners 6, 25, 29, 32, 83, 85, 88, 89, 90, 91, 92, 175, 177, 180 science xvi, 1, 2, 3, 19, 20, 29, 31, 34, 37, 46, 65, 67, 71, 72, 73, 78, 79, 97, 98, 100, 101, 103, 111, 112, 128–139, 140, 147, 148, 150, 158, 161, 165, 166, 181, 184, 186 scientific method 129, 130, 133, 134, 136, 137–138, 140, 147, 148, 186 security data 28, 33, 34, 40, 45, 46, 51, 57, 126, 157, 166, 169, 171, 173, 174–175, 182, 187 national 42, 71, 88, 116–117, 172, 176, 178, 179 private 99, 115, 118, 151 social 8, 32, 45, 87, 115, 171 segmentation 104, 105, 110, 119, 120, 121, 122, 176 semantic information 9, 10, 11, 105, 157 Web 49, 52, 53, 66 sensors xv, 6, 7, 19, 20, 24, 25, 28, 34, 71, 76, 83, 84, 91–92, 95, 124, 139, 150, 160 sentiment analysis 105, 106, 121, Siegel, E. 103, 110, 111, 114, 120, 132, 158, 176, 179 signal 9, 151, 159 Silver, N. 136, 151, 158 simulation 4, 32, 37, 101, 104, 110–112, 119, 129, 133, 137, 139, 140 skills 37, 48, 52, 53, 57, 63, 94, 97, 98, 112, 149, 160–163, 164 small data 21, 27–47, 68, 72, 75, 76, 77, 79, 100, 103, 110, 112, 146, 147, 148, 150, 156, 160, 166, 184, 186, 188, 191 smart cards 90 cities 91, 92, 99, 124–125, 181–182 devices 83 metering 89, 123, 174 phones 81, 82, 83, 84, 90, 94, 107, 121, 155, 170, 174 SmartSantander 91 social computing xvi determinism 144 media xv, 13, 42, 43, 76, 78, 90, 93, 94–95, 96, 105, 119, 121, 140, 150, 151, 152, 154, 155, 160, 167, 176, 180 physics 144 security number 8, 32, 45, 87, 115, 171 sorting 126, 166, 168, 175–178, 182 sociotechnical systems 21–24, 47, 66, 183, 185, 188 software 6, 20, 32, 34, 40, 48, 53, 54, 56, 63, 80, 83, 84, 86, 88, 96, 132, 143, 160, 161, 163, 166, 170, 172, 175, 177, 180, 189 Solove, D. 116, 120, 168, 169, 170, 172, 176, 178, 180 solutionism 181 sousveillance 95–96 spatial autocorrelation 146 data infrastructure 34, 35, 38 processes 136, 144 resolution 149 statistics 110 video 88 spatiality 17, 157 Star, S.L. 19, 20, 23, 24 stationarity 100 statistical agencies 8, 30, 34, 35, 115 geography 17, 74, 157 statistics 4, 8, 13, 14, 24, 48, 77, 100, 101, 102, 104, 105, 109–110, 111, 129, 132, 134, 135, 136, 140, 142, 143, 145, 147, 159 descriptive 4, 106, 109, 147 inferential 4, 110, 147 non-parametric 105, 110 parametric 105, 110 probablistic 110 radical 147 spatial 110 storage 31–32, 68, 72, 73, 78, 80, 85–87, 88, 100, 118, 161, 171 analogue 85, 86 digital 85–87 media 20, 86 store loyalty cards 42, 45, 165 Sunlight Foundation 49 supervised learning 103 Supply Chain Management (SCM) 74, 99, 117–118, 119, 120, 121 surveillance 15, 71, 80, 83, 87–90, 95, 115, 116, 117, 123, 124, 151, 165, 167, 168, 169, 180 survey 6, 17, 19, 22, 28, 42, 68, 75, 77, 87, 115, 120 sustainability 16, 33, 34, 57, 58, 59, 61, 64–66, 87, 114, 123–124, 126, 155 synchronicity 14, 95, 102 technological handshake 84, 153 lock-in 166, 179–182 temporality 17, 21, 27, 28, 32, 37, 68, 75, 111, 114, 157, 160, 186 terrorism 116, 165, 179 territory 16, 38, 74, 85, 167 Tesco 71, 120 Thrift, N. 83, 113, 133, 167, 176 TopCoder 96 trading funds 54–55, 56, 57 transparency 19, 38, 44, 45, 48–49, 55, 61, 62, 63, 113, 115, 117, 118, 121, 126, 165, 173, 178, 180 trust 8, 30, 33, 34, 40, 44, 55, 84, 117, 152–156, 163, 175 trusted digital repository 33–34 Twitter 6, 71, 78, 94, 106, 107, 133, 143, 144, 146, 152, 154, 155, 170 uncertainty 10, 13, 14, 100, 102, 110, 156, 158 uneven development 16 Uniform Resource Identifiers (URIs) 53, 54 United Nations Development Programme (UNDP) 49 universalism 20, 23, 133, 140, 144, 154, 190 unsupervised learning 103 utility 1, 28, 53, 54, 55, 61, 63, 64–66, 100, 101, 114, 115, 134, 147, 163, 185 venture capital 25, 59 video 6, 43, 71, 74, 77, 83, 88, 90, 93, 94, 106, 141, 146, 170 visual analytics 106–109 visualisation 5, 10, 34, 77, 101, 102, 104, 106–109, 112, 125, 132, 141, 143 Walmart 28, 71, 99, 120 Web 2.0 81, 94–95 Weinberger, D. 9, 10, 11, 96, 97, 132, 133 White House 48 Wikipedia 93, 96, 106, 107, 143, 154, 155 Wired 69, 130 wisdom 9–12, 114, 161 XML 6, 53 Zikopoulos, P.C. 6, 16, 68, 70, 73, 76, 119, 151


pages: 202 words: 59,883

Age of Context: Mobile, Sensors, Data and the Future of Privacy by Robert Scoble, Shel Israel

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Albert Einstein, Apple II, augmented reality, call centre, Chelsea Manning, cloud computing, connected car, Edward Snowden, Edward Thorp, Elon Musk, factory automation, Filter Bubble, Google Earth, Google Glasses, Internet of things, job automation, John Markoff, Kickstarter, lifelogging, Marc Andreessen, Mars Rover, Menlo Park, Metcalfe’s law, New Urbanism, PageRank, pattern recognition, RFID, ride hailing / ride sharing, Robert Metcalfe, Saturday Night Live, self-driving car, sensor fusion, Silicon Valley, Skype, smart grid, social graph, speech recognition, Steve Jobs, Steve Wozniak, Steven Levy, Tesla Model S, Tim Cook: Apple, urban planning, Zipcar

Nike says its + family of sensor-enabled gear, backed by a strong marketing campaign, had 6 million users in February 2012. The Quantified Self The very high end of these health-related wearable devices is the $199 Basis. Designed for “wellness and fitness,” Basis even tells time but, with five sensors inside, it does a lot more: It measures pulse, perspiration rate, activity, and body temperature as well as sleep quality. Basically, it provides enough data to satisfy an astrophysicist. The Basis site lets users drill deep down into personal data mines of stats, charts and graphs. It is a particular favorite of a growing movement, called the “Quantified Self,” which is composed of people who believe that the more personal data they have, the better they can understand their own bodies and thus become and stay healthier.

Some believe they can ultimately reach a point where they just won’t need a doctor. Loic Le Meur, producer of LeWeb, Europe’s largest tech conference, is an ardent fitness enthusiast and Quantified Self proponent. In August 2010, he suggested in a blog post that as people and mobile devices work together to provide highly personalized data, the human body itself becomes an Application Programming Interface (API), meaning that developers can now offer personalized mobile apps for each individual by letting their computer codes talk with each other. From that perspective, perhaps we are all becoming like The Terminal Man, but today’s picture looks far more positive than the one Crichton painted. As Le Meur demonstrated in his blog, Quantified Self data can build a personal anticipatory system. You can see patterns in your exercise and diet. You can detect correlations between those two factors—plus sleep—and understand why you got sick or experienced an off-pace run.

Glass can only capture what’s directly in the user’s line of vision, and when it does, the prism glows. When you snap a shot, it emits an audible ping. In short, if you use it inappropriately in restrooms or elsewhere, you will likely get caught, and the response may be far worse than what Steve Mann experienced in Paris. It is far easier to take clandestine pictures or video with a smartphone or worse, with an almost undetectable Memoto wearable “lifelogging” camera that automatically and silently snaps a shot every 30 seconds. In our view, a great number of inaccurate reports are dramatically overstating legitimate concerns about illicit data collection and downright spying. Who Watches Whom? The biggest barrier to digital eyewear acceptance is neither competition nor fashion. Rather, concerns about privacy and the potential for surveillance are likely to stop many people for a while—and some people forever—from trying smart glasses.


pages: 350 words: 107,834

Halting State by Charles Stross

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augmented reality, call centre, forensic accounting, game design, Google Earth, hiring and firing, illegal immigration, impulse control, indoor plumbing, Intergovernmental Panel on Climate Change (IPCC), invention of the steam engine, lifelogging, Necker cube, Potemkin village, RFID, Schrödinger's Cat, Vernor Vinge, zero day

with all the force its wheezing, mesothelioma-ridden lungs can muster. Maybe it’s some kind of up-market cottaging club for the tech start-up crowd? You shake your head and climb out of the car, tapping your ear-piece to tell your phone to listen up: “Arriving on SOC, time-stamp now. Start evidence log.” It’s logging anyway—everything you see on duty goes into the black box—but the voice marker is searchable. It saves the event from getting lost in your lifelog. Bob trails along like an eager puppy. Eight weeks out of police college, so help you. At least he’s house-broken. The door to the premises is a retrofitted slab of glossy green plastic that slides open automatically as you approach, revealing a reception room that’s very far from being a public toilet. So much for the cottage scene. The lighting is tasteful, the bleached pine impeccably renewable, and the vacant reception desk supports a screen the size of Texas that’s showing a dizzying motion-picture tour of an online game space, overlaid by the words HAYEK ASSOCIATES PLC.

Rogers—and Jim—hand you a disposable overall, then get the door jacks and battering ram assembled. The latter is about a metre and a half long, and has a transparent face shield and sixteen evidence cameras hanging off it. While they’re doing that, Gavaghan drafts you to help with the duct tape and nylon sheeting, improvising a loose tent to cover the front door and keep particulates from escaping. “Everyone record full lifelog, please,” says Kavanaugh, standing at the back of the cocoonlike white tunnel. Even wearing a blue polythene bag, she manages to look coolly managerial. Jim glances at you as Rogers makes busy with the horizontal ram, jacking the uprights of the door-frame apart to help pop the lock’s tongue out of its groove. “You got your Girl Guides’ badge in battering rams?” he asks. Are you going to get in the way?

Because in the final analysis, that’s a load of dosh, dosh beyond the wildest imagining of the wee neds you get to deal with—like Jimmy Hastie—and you know damn well what they’d get up to for a tinny of Carlsberg, never mind a tax-free twenty-six million. “Are we looking to recover it?” you ask. “That’s for the proceeds of crime unit.” McMullen sniffs dismissively. “I’m sure they’ll find wherever he put it sooner or later. But first, there’s the small matter of the prosecution. Everything happened while CopSpace was compromised, so there’s a slight lack of visuals—and the lifelog transcripts for yourself and the inspector are going to be misplaced. On the other hand, we’ve got the hotel camera footage from the business in the Malmaison, so we’re going to have to run with that. If we can’t nail him for attempted murder and firearms possession in front of a jury on the basis of video evidence and witnesses, one of whom has holes, we’re idiots. The heavy stuff—Chen and Richardson and the blacknet and the penetration at Hayek Associates—we don’t need to bring it up to put him away, and if we keep it out of the picture, there’s no reason why anyone would start digging.


pages: 259 words: 73,193

The End of Absence: Reclaiming What We've Lost in a World of Constant Connection by Michael Harris

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4chan, Albert Einstein, AltaVista, Andrew Keen, augmented reality, Burning Man, Carrington event, cognitive dissonance, crowdsourcing, dematerialisation, en.wikipedia.org, Filter Bubble, Firefox, Google Glasses, informal economy, information retrieval, invention of movable type, invention of the printing press, invisible hand, James Watt: steam engine, Jaron Lanier, jimmy wales, Kevin Kelly, lifelogging, Loebner Prize, Marshall McLuhan, McMansion, moral panic, Nicholas Carr, pattern recognition, pre–internet, Republic of Letters, Silicon Valley, Skype, Snapchat, social web, Steve Jobs, the medium is the message, The Wisdom of Crowds, Turing test

These proved too personal, however. Only 2 to 3 percent of users made use of the text message software, and those who did, says Wegener, often hadn’t thought about whom they were texting one year ago: horrible ex-boyfriends and horrible ex-girlfriends. “People just weren’t comfortable with it,” he told me. “They’d contact us in a hurry and want the feature disconnected.” Wegener himself is deeply committed to lifelogging and feels that “at a deeper level it makes us feel we’re getting more out of life. We’re fighting mortality. If we write everything down, it’ll stay fresh, you know? I mean, we’re being pulled through time against our will toward death. But this can make us feel like we lived.” He also sees his creation as a potential bonding agent for friends and families. “There’s a subtlety to Timehop that a lot of people don’t pick up on,” he told me.

Fourteen percent of users began checking in twice as often; 39 percent more users began adding comments and photos to their check-ins; check-ins overall bumped up 9 percent. The company’s conclusion: “Timehop makes users better.” When users understood that they were creating not just abstract records but fodder for future reminiscences that would be automatically retrieved in a year’s time, they became more involved and invested in the lifelogging process. Wegener had tapped into a major social media truth: We do it because we’re thinking of our own future as a bundle of anticipated memories. When he and I spoke about his own usage of Timehop, Wegener managed to boil things down to a simple core: “It reaffirms me.” Is there a nobler reason to reminisce? When I consider the state of my brain’s dusty mechanisms, by contrast, my supposedly miraculous neurons feel like a broken machine, incapable of “reaffirming me” the way Wegener’s app can.


pages: 361 words: 81,068

The Internet Is Not the Answer by Andrew Keen

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3D printing, A Declaration of the Independence of Cyberspace, Airbnb, AltaVista, Andrew Keen, augmented reality, Bay Area Rapid Transit, Berlin Wall, bitcoin, Black Swan, Bob Geldof, Burning Man, Cass Sunstein, citizen journalism, Clayton Christensen, clean water, cloud computing, collective bargaining, Colonization of Mars, computer age, connected car, creative destruction, cuban missile crisis, David Brooks, disintermediation, Donald Davies, Downton Abbey, Edward Snowden, Elon Musk, Erik Brynjolfsson, Fall of the Berlin Wall, Filter Bubble, Francis Fukuyama: the end of history, Frank Gehry, Frederick Winslow Taylor, frictionless, full employment, future of work, gig economy, global village, Google bus, Google Glasses, Hacker Ethic, happiness index / gross national happiness, income inequality, index card, informal economy, information trail, Innovator's Dilemma, Internet of things, Isaac Newton, Jaron Lanier, Jeff Bezos, job automation, Joseph Schumpeter, Julian Assange, Kevin Kelly, Kickstarter, Kodak vs Instagram, Lean Startup, libertarian paternalism, lifelogging, Lyft, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, Martin Wolf, Metcalfe’s law, move fast and break things, move fast and break things, Nate Silver, Network effects, new economy, Nicholas Carr, nonsequential writing, Norbert Wiener, Norman Mailer, Occupy movement, packet switching, PageRank, Paul Graham, peer-to-peer, peer-to-peer rental, Peter Thiel, Plutocrats, plutocrats, Potemkin village, precariat, pre–internet, RAND corporation, Ray Kurzweil, ride hailing / ride sharing, Robert Metcalfe, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Silicon Valley ideology, Skype, smart cities, Snapchat, social web, South of Market, San Francisco, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, TaskRabbit, Ted Nelson, telemarketer, The Future of Employment, the medium is the message, the new new thing, Thomas L Friedman, Tyler Cowen: Great Stagnation, Uber for X, urban planning, Vannevar Bush, Whole Earth Catalog, WikiLeaks, winner-take-all economy, working poor, Y Combinator

Wearable technology—what the Intel CEO Brian Krzanich in his keynote speech at the show called a “broad ecosystem of wearables”—dominated CES 2014. Sony, Samsung, and many, many startups were all demonstrating products that wouldn’t have been out of place at that old East German Ministry for State Security in Berlin. Two of the most hyped companies producing so-called quantified self products at CES were Fitbit, the maker of a wrist device that tracks physical activity and sleep patterns, and Swedish-based Narrative, the manufacturer of a wearable tiny camera clip designed to be worn on a lapel that automatically takes photos every thirty seconds and is known as a “lifelogging” device for recording everything it sees. “What’s interesting about both companies is they make the invisible part of our lives visible, in an ambient ongoing fashion,” explained one venture capitalist who’d invested in Fitbit and Narrative.21 Thirty years ago, Mielke would have likely bought Narrative devices for the entire East German population.

Our growing concern with the pollution of “data exhaust” is becoming the equivalent of the environmental movement for the digital age. Web 2.0 companies like Facebook, YouTube, and Instagram have reassembled the Bentham brothers’ eighteenth-century Panopticon as data factories. Bentham’s utilitarianism, that bizarre project to quantify every aspect of the human condition, has reappeared in the guise of the quantified-self movement. Even the nineteenth-century debate between Bentham’s utilitarianism and John Stuart Mill’s liberalism over individual rights has reappeared in what Harvard Law School’s Cass Sunstein calls “the politics of libertarian paternalism”—a struggle between “Millville” and “Benthamville” about the role of “nudge” in a world where the government, through partnerships with companies like Acxiom and Palantir, has more and more data on us all25 and Internet companies like Facebook and OkCupid run secretive experiments designed to control our mood.


pages: 416 words: 106,582

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

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23andMe, Albert Einstein, Alfred Russel Wallace, banking crisis, Barry Marshall: ulcers, Benoit Mandelbrot, Berlin Wall, biofilm, Black Swan, butterfly effect, Cass Sunstein, cloud computing, congestion charging, correlation does not imply causation, Daniel Kahneman / Amos Tversky, dark matter, data acquisition, David Brooks, delayed gratification, Emanuel Derman, epigenetics, Exxon Valdez, Flash crash, Flynn Effect, hive mind, impulse control, information retrieval, Intergovernmental Panel on Climate Change (IPCC), Isaac Newton, Jaron Lanier, John von Neumann, Kevin Kelly, lifelogging, mandelbrot fractal, market design, Mars Rover, Marshall McLuhan, microbiome, Murray Gell-Mann, Nicholas Carr, open economy, Pierre-Simon Laplace, place-making, placebo effect, pre–internet, QWERTY keyboard, random walk, randomized controlled trial, rent control, Richard Feynman, Richard Feynman, Richard Feynman: Challenger O-ring, Richard Thaler, Satyajit Das, Schrödinger's Cat, security theater, selection bias, Silicon Valley, stem cell, Steve Jobs, Steven Pinker, Stewart Brand, the scientific method, Thorstein Veblen, Turing complete, Turing machine, Vilfredo Pareto, Walter Mischel, Whole Earth Catalog, zero-sum game

Microsoft saw the potential back in September 2006, when it filed United States Patent application number 20,080,082,393 for a system of “personal data mining.” Having been fed personal data provided by users themselves or gathered by third parties, the technology would then analyze it to “enable identification of opportunities and/or provisioning of recommendations to increase user productivity and/or improve quality of life.” You can decide for yourself whether you trust Redmond with your lifelog, but it’s hard to fault the premise: The personal data mine, the patent states, would be a way “to identify relevant information that otherwise would likely remain undiscovered.” Both I as a citizen and society as a whole would gain if individuals’ personal datastreams could be mined to extract patterns upon which we could act. Such mining would turn my raw data into predictive information that can anticipate my mood and improve my efficiency, make me healthier and more emotionally intuitive, reveal my scholastic weaknesses and my creative strengths.

Such mining would turn my raw data into predictive information that can anticipate my mood and improve my efficiency, make me healthier and more emotionally intuitive, reveal my scholastic weaknesses and my creative strengths. I want to find the hidden meanings, the unexpected correlations that reveal trends and risk factors of which I had been unaware. In an era of oversharing, we need to think more about data-driven self-discovery. A small but fast-growing self-tracking movement is already showing the potential of such thinking, inspired by Kevin Kelly’s quantified self and Gary Wolf’s data-driven life. With its mobile sensors and apps and visualizations, this movement is tracking and measuring exercise, sleep, alertness, productivity, pharmaceutical responses, DNA, heartbeat, diet, financial expenditure—and then sharing and displaying its findings for greater collective understanding. 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.


pages: 588 words: 131,025

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

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

It fits into the employee ID badge and includes infrared sensors, an accelerometer, a microphone sensor, and a wireless communication device. As employees interact with one another, the badges record and transmit to management “who talks to whom, how often, where, and how energetically.”70 Another wearable alternative for tracking employees is smart glasses, such as those made by Vuzix that have a microphone, GPS, accelerometer, and data display. Life-logging apps like Saga incorporate a barometer, camera, microphones, and the smartphone’s location sensors to provide “a more comprehensive, automatic record of your life”72 and know precisely where you are and what you are up to. The barometer helps distinguish exact location, along with deep acoustic and light signals for context. But the most commonly owned wearable sensors are the wireless accelerometers like Fitbit and Jawbone.73–75 These companies are now selling their activity trackers to thousands of employers for corporate wellness programs.75 One large health insurer pointed out that “data collected from those gadgets may eventually impact group insurance pricing.”

infectious diseases, 96–97 mammography, 116–117 patient access to test results, 105–108, 120–121 patient-generated data, 135–136 prostate cancer screening, 118 real-time costs, 150–151 smartphone devices in developing countries, 262–263 Theranos blood testing, 106 See also Imaging; Individualized medicine; Scans; 23and Me LabCorp, 108 Lab-in-the-body (LIB), 111–112 Laennec, Rene, 276 Landman, Zachary, 169 Lansley, Andrew, 172 Leape, Lucian, 28 The Learned Press as an Institution (Morison), 39 Lee, Mike, 229 Leon, Katherine, 211 Lepp, Herman, 25, 25(fig.), 26 Lepp, Miriam, 25, 25(fig.), 26 Leptospira, 96–97 Licensure for physicians, 168–169 Lichter, Allen, 201 Life expectancy, 238, 239(fig.) Life science research, 207–209 Life-logging apps, 228–230 Lifestyle changes, 88, 94 Liquid biopsy of cancerous tumors, 99 Low-cost providers, 156 Lung cancer, 117–118 Luther, Martin, 50 Lynch syndrome, 93 Machine learning, 244, 246–247, 253–256 Madera, James, 22 Madrigal, Alexis, 221 Magnetic resonance imaging (MRI), 113, 116, 118–119. See also Imaging; Scans Magnetic resonance reflexometry, 112 Makary, Marty, 186 Malaria, 258–259, 261–265 Malnutrition, 266, 267(fig.)


pages: 263 words: 75,610

Delete: The Virtue of Forgetting in the Digital Age by Viktor Mayer-Schönberger

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en.wikipedia.org, Erik Brynjolfsson, Firefox, full text search, George Akerlof, information asymmetry, information retrieval, information trail, Internet Archive, invention of movable type, invention of the printing press, John Markoff, lifelogging, moveable type in China, Network effects, packet switching, pattern recognition, RFID, slashdot, Steve Jobs, Steven Levy, The Market for Lemons, The Structural Transformation of the Public Sphere, Vannevar Bush

Of course, Gordon Bell, the software engineer who has captured much of his professional life on digital memory, emphatically insists he is in charge of whether and how he makes his information available to others. Bell himself has decided to not let others peek into his information treasures. His lifeblog project, he explains, is about helping him remember, not giving others access to his files: “A lot of people put their lives on the Web. I’m not an advocate of that. [Lifelogging] was built to be entirely personal, to aid the individual.”40 His view may be admirable but, as he concedes, it is not representative of current Internet users. As I have mentioned, two out of three teenagers in the United States use the Internet to create and share information with others.41 This large and growing portion of the user population has internalized the culture of information bricolage.

The Economic Singularity: Artificial intelligence and the death of capitalism by Calum Chace

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3D printing, additive manufacturing, agricultural Revolution, AI winter, Airbnb, artificial general intelligence, augmented reality, autonomous vehicles, banking crisis, basic income, Baxter: Rethink Robotics, Berlin Wall, Bernie Sanders, bitcoin, blockchain, call centre, Chris Urmson, congestion charging, credit crunch, David Ricardo: comparative advantage, Douglas Engelbart, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Flynn Effect, full employment, future of work, gender pay gap, gig economy, Google Glasses, Google X / Alphabet X, ImageNet competition, income inequality, industrial robot, Internet of things, invention of the telephone, invisible hand, James Watt: steam engine, Jaron Lanier, Jeff Bezos, job automation, John Markoff, John Maynard Keynes: technological unemployment, John von Neumann, Kevin Kelly, knowledge worker, lifelogging, lump of labour, Lyft, Marc Andreessen, Mark Zuckerberg, Martin Wolf, McJob, means of production, Milgram experiment, Narrative Science, natural language processing, new economy, Occupy movement, Oculus Rift, PageRank, pattern recognition, post scarcity, post-industrial society, precariat, prediction markets, QWERTY keyboard, railway mania, RAND corporation, Ray Kurzweil, RFID, Rodney Brooks, Satoshi Nakamoto, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Skype, software is eating the world, speech recognition, Stephen Hawking, Steve Jobs, TaskRabbit, technological singularity, The Future of Employment, Thomas Malthus, transaction costs, Tyler Cowen: Great Stagnation, Uber for X, universal basic income, Vernor Vinge, working-age population, Y Combinator, young professional

Most robots will probably be special-purpose devices, constructed to carry out a very specific task. An example is the Grillbot, a robot the size of a table tennis bat which cleans your barbecue grill, and is otherwise entirely useless.[clvi] Another form of robot which is taking off fast is drones – flying machines that can be controlled remotely or autonomously. They have a wide range of applications, including taking surreptitious photos of celebrities, taking selfies for life-logging Millennials, and delivering parcels for Amazon. They present a serious challenge for regulators concerned about the impact on more established forms of aircraft. These challenges cannot be dismissed or regulated away: internet-connected drones with powerful sensors and computers on board are quickly becoming essential tools for companies in the utilities and engineering industries, as well as government agencies.

The Singularity Is Near: When Humans Transcend Biology by Ray Kurzweil

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additive manufacturing, AI winter, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, anthropic principle, Any sufficiently advanced technology is indistinguishable from magic, artificial general intelligence, Asilomar, augmented reality, autonomous vehicles, Benoit Mandelbrot, Bill Joy: nanobots, bioinformatics, brain emulation, Brewster Kahle, Brownian motion, business intelligence, c2.com, call centre, carbon-based life, cellular automata, Claude Shannon: information theory, complexity theory, conceptual framework, Conway's Game of Life, cosmological constant, cosmological principle, cuban missile crisis, data acquisition, Dava Sobel, David Brooks, Dean Kamen, disintermediation, double helix, Douglas Hofstadter, en.wikipedia.org, epigenetics, factory automation, friendly AI, George Gilder, Gödel, Escher, Bach, informal economy, information retrieval, invention of the telephone, invention of the telescope, invention of writing, Isaac Newton, iterative process, Jaron Lanier, Jeff Bezos, job automation, job satisfaction, John von Neumann, Kevin Kelly, Law of Accelerating Returns, life extension, lifelogging, linked data, Loebner Prize, Louis Pasteur, mandelbrot fractal, Mikhail Gorbachev, mouse model, Murray Gell-Mann, mutually assured destruction, natural language processing, Network effects, new economy, Norbert Wiener, oil shale / tar sands, optical character recognition, pattern recognition, phenotype, premature optimization, randomized controlled trial, Ray Kurzweil, remote working, reversible computing, Richard Feynman, Richard Feynman, Robert Metcalfe, Rodney Brooks, Search for Extraterrestrial Intelligence, selection bias, semantic web, Silicon Valley, Singularitarianism, speech recognition, statistical model, stem cell, Stephen Hawking, Stewart Brand, strong AI, superintelligent machines, technological singularity, Ted Kaczynski, telepresence, The Coming Technological Singularity, Thomas Bayes, transaction costs, Turing machine, Turing test, Vernor Vinge, Y2K, Yogi Berra

Science fiction writer Bruce Sterling refers to our time as 'the Golden Age of dead media, most of them with the working lifespan of a pack of Twinkles," Stewart Brand, "Written on the Wind," Civilization Magazine, November 1998 ("01998" in Long Now terminology), available online at http://www.longnow.org/10klibrary/library.htm. 43. DARPA's Information Processing Technology Office's project in this vein is called LifeLog, http://www.darpa.mil/ipto/Programs/lifelog; see also Noah Shachtman, "A Spy Machine of DARPA's Dreams," Wired News, May 20, 2003, http://www.wired.com/news/business/0,1367,58909,00.html; Gordon Bell's project (for Microsoft) is MyLifeBits, http://research.microsoft.com/research/barc/MediaPresence/MyLifeBits.aspx; for the Long Now Foundation, see http://longnow.org. 44. Bergeron is assistant professor of anesthesiology at Harvard Medical School and the author of such books as Bioinformatics Computing, Biotech Industry: A Global, Economic, and Financing Overview, and The Wireless Web and Healthcare. 45.


pages: 549 words: 116,200

With a Little Help by Cory Doctorow

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autonomous vehicles, big-box store, Burning Man, call centre, carbon footprint, death of newspapers, don't be evil, game design, Google Earth, high net worth, lifelogging, margin call, Mark Shuttleworth, offshore financial centre, packet switching, Ponzi scheme, rolodex, Sand Hill Road, sensible shoes, skunkworks, Skype, traffic fines, traveling salesman, Turing test, urban planning, Y2K

Couldn't even drive a nail when I got here) (Not that there are any nails in there, it's all precision-fitted tongue and groove) (holy moley, lasers totally rock) 244 > But he reserved his worst criticism for the Order itself. You know the litany: we're a cult, we're brainwashed, we're dupes of the Securitat. He was convinced that every instrument in the place was feeding up to the Securitat itself. He'd mutter about this constantly, whenever we got a new stream to work on -- "Is this your lifelog, Brother Antony? Mine? The number of flushes per shitter in the west wing of campus?" 245 > And it was no good trying to reason with him. He just didn't acknowledge the benefit of introspection. "It's no different from them," he'd say, jerking his thumb up at the ceiling, as though there was a Securitat mic and camera hidden there. "You're just flooding yourself with useless information, trying to find the useful parts.


pages: 542 words: 161,731

Alone Together by Sherry Turkle

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Albert Einstein, Columbine, global village, Hacker Ethic, helicopter parent, Howard Rheingold, industrial robot, information retrieval, Jacques de Vaucanson, Jaron Lanier, John Markoff, Kevin Kelly, lifelogging, Loebner Prize, Marshall McLuhan, meta analysis, meta-analysis, Nicholas Carr, Norbert Wiener, Ralph Waldo Emerson, Rodney Brooks, Skype, stem cell, technoutopianism, The Great Good Place, the medium is the message, theory of mind, Turing test, Vannevar Bush, Wall-E, women in the workforce

Children now tell me that parents give them two phones: one to “turn in” on the first day of camp and a second to keep for calling home. 5 In October 2005, ABC News called the term “in vogue.” See “Do ‘Helicopter Moms’ Do More Harm Than Good?” ABCNews.com, October 21, 2005, http://abcnews.go.com/2020/Health/story?id=1237868&page=1 (accessed April 7, 2004). 6 In 2004, the Pentagon canceled its so-called LifeLog project, an ambitious effort to build a database tracking a person’s entire existence: phone calls made, TV shows watched, magazines read, plane tickets bought, e-mails sent and received. It was then partially revived nine months later. See Noah Schachtman, “Pentagon Revives Memory Project,” Wired News, www.wired.com/politics/security/news/2004/09/6491 (accessed August 4, 2010). Backers of the project saw it as a near-perfect digital memory.


pages: 428 words: 136,945

The Happiness Effect: How Social Media Is Driving a Generation to Appear Perfect at Any Cost by Donna Freitas

4chan, fear of failure, lifelogging, Mark Zuckerberg, meta analysis, meta-analysis, moral panic, mutually assured destruction, Skype, Snapchat

For more on incidents in which taking selfies has resulted in injuries or even death, see Reuters, “Selfie Madness: Too Many Dying to Get the Picture,” New York Times, September 3, 2015; Jessica Durando,“Police: Man Killed While Taking Instagram Selfie with Gun,” USA Today, September 2, 2015, ; Jessica Mendoza, “Woman Hurt While Taking Photo with Bison: Why Can’t People Resist Selfies?,” Christian Science Monitor, July 26, 2015; and Kiran Moodley, “Couple Fall to Their Death Whilst Attempting Cliff Face Selfie,” Independent, August 11, 2014. 2.In her book Seeing Ourselves through Technology: How We Use Selfies, Blogs and Wearable Devices to See and Shape Ourselves (New York: Palgrave Macmillan, 2014), Jill Walker Rettberg looks at how selfies, blogs, and other life-logging tools and applications have become important ways through which we understand ourselves. Rettberg’s analysis presents these tools and applications as three intertwined modes of self-representation: visual, written, and quantitative. For more on selfies as a form of identity performance, see Gabriel Fleur, “Sexting, Selfies, and Self-Harm: Young People, Social Media, and the Performance of Self-Development,” Media International Australia, Incorporating Culture & Policy 151 (May 2014): 104–112.

Wireless by Stross, Charles

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anthropic principle, back-to-the-land, Benoit Mandelbrot, Buckminster Fuller, Cepheid variable, cognitive dissonance, colonial exploitation, cosmic microwave background, epigenetics, finite state, Georg Cantor, gravity well, hive mind, jitney, Khyber Pass, lifelogging, Magellanic Cloud, mandelbrot fractal, peak oil, phenotype, Pluto: dwarf planet, security theater, sensible shoes, Turing machine

“Stasis Control thus has access to a theoretical maximum of 5.6 times 1021 slots across the totality of our history—but our legion of humanity comes perilously close, with a total of 2 times 1019 people. Many of the total available slots are reserved for data, relaying the totality of recorded human history to the Library—fully ninety-six percent of humanity lives in eras where ubiquitous surveillance or personal life-logging technologies have made the recording of absolute history possible, and we obviously need to archive their lifelines. Only the ur-historical prelude to Stasis, and periods of complete civilizational collapse and Reseeding, are not being monitored in exhaustive detail. “To make matters worse: in practice there are far fewer slots available for actual traffic, because we are not, as a species, well equipped for reacting in spans of less than a second.


pages: 798 words: 240,182

The Transhumanist Reader by Max More, Natasha Vita-More

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23andMe, Any sufficiently advanced technology is indistinguishable from magic, artificial general intelligence, augmented reality, Bill Joy: nanobots, bioinformatics, brain emulation, Buckminster Fuller, cellular automata, clean water, cloud computing, cognitive bias, cognitive dissonance, combinatorial explosion, conceptual framework, Conway's Game of Life, cosmological principle, data acquisition, discovery of DNA, Douglas Engelbart, Drosophila, en.wikipedia.org, endogenous growth, experimental subject, Extropian, fault tolerance, Flynn Effect, Francis Fukuyama: the end of history, Frank Gehry, friendly AI, game design, germ theory of disease, hypertext link, impulse control, index fund, John von Neumann, joint-stock company, Kevin Kelly, Law of Accelerating Returns, life extension, lifelogging, Louis Pasteur, Menlo Park, meta analysis, meta-analysis, moral hazard, Network effects, Norbert Wiener, P = NP, pattern recognition, phenotype, positional goods, prediction markets, presumed consent, Ray Kurzweil, reversible computing, RFID, Richard Feynman, Ronald Reagan, silicon-based life, Singularitarianism, stem cell, stochastic process, superintelligent machines, supply-chain management, supply-chain management software, technological singularity, Ted Nelson, telepresence, telepresence robot, telerobotics, the built environment, The Coming Technological Singularity, the scientific method, The Wisdom of Crowds, transaction costs, Turing machine, Turing test, Upton Sinclair, Vernor Vinge, Von Neumann architecture, Whole Earth Review, women in the workforce, zero-sum game

Of course, non-destructive scanning would be much better, but experts disagree on its possible timeline, and even feasibility in principle. I prefer to keep an open mind and, since non-destructive, very high resolution brain scanning seems feasible in principle (that is, it is compatible with the laws of physics and so it is just another engineering problem), I tend to think it will be achieved sooner or later. Another possibility is the Bainbridge–Rothblatt “soft” approach: we can create a “lifelogging” database with blogs, pictures, videos, answers to personality tests, etc. (see the CybeRev and LifeNaut projects of Martine Rothblatt [Rothblatt 2009]), hoping that some future AI technology may be able to merge the information in the database with suitable “human firmware” (me-program) and bring it to life. I think this approach is basically feasible in principle, but needs data transfer rates from brain to computer storage much faster than we can achieve today (Vita-More 2010).


pages: 855 words: 178,507

The Information: A History, a Theory, a Flood by James Gleick

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Ada Lovelace, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, AltaVista, bank run, bioinformatics, Brownian motion, butterfly effect, citation needed, Claude Shannon: information theory, clockwork universe, computer age, conceptual framework, crowdsourcing, death of newspapers, discovery of DNA, Donald Knuth, double helix, Douglas Hofstadter, en.wikipedia.org, Eratosthenes, Fellow of the Royal Society, Gödel, Escher, Bach, Henri Poincaré, Honoré de Balzac, index card, informal economy, information retrieval, invention of the printing press, invention of writing, Isaac Newton, Jacquard loom, Jacquard loom, Jaron Lanier, jimmy wales, John von Neumann, Joseph-Marie Jacquard, lifelogging, Louis Daguerre, Marshall McLuhan, Menlo Park, microbiome, Milgram experiment, Network effects, New Journalism, Norbert Wiener, On the Economy of Machinery and Manufactures, PageRank, pattern recognition, phenotype, Pierre-Simon Laplace, pre–internet, Ralph Waldo Emerson, RAND corporation, reversible computing, Richard Feynman, Richard Feynman, Rubik’s Cube, Simon Singh, Socratic dialogue, Stephen Hawking, Steven Pinker, stochastic process, talking drums, the High Line, The Wisdom of Crowds, transcontinental railway, Turing machine, Turing test, women in the workforce

YouTube was streaming more than a billion videos a day. Most of this is haphazard and unorganized, but there are extreme cases. The computer pioneer Gordon Bell, at Microsoft Research in his seventies, began recording every moment of his day, every conversation, message, document, a megabyte per hour or a gigabyte per month, wearing around his neck what he called a “SenseCam” to create what he called a “LifeLog.” Where does it end? Not with the Library of Congress. It is finally natural—even inevitable—to ask how much information is in the universe. It is the consequence of Charles Babbage and Edgar Allan Poe saying, “No thought can perish.” Seth Lloyd does the math. He is a moon-faced, bespectacled quantum engineer at MIT, a theorist and designer of quantum computers. The universe, by existing, registers information, he says.


pages: 268 words: 75,850

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

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3D printing, algorithmic trading, Any sufficiently advanced technology is indistinguishable from magic, augmented reality, big data - Walmart - Pop Tarts, call centre, Cass Sunstein, Clayton Christensen, commoditize, computer age, death of newspapers, deferred acceptance, Edward Lorenz: Chaos theory, Erik Brynjolfsson, Filter Bubble, Flash crash, Florence Nightingale: pie chart, Frank Levy and Richard Murnane: The New Division of Labor, Google Earth, Google Glasses, High speed trading, Internet Archive, Isaac Newton, Jaron Lanier, Jeff Bezos, job automation, John Markoff, Kevin Kelly, Kodak vs Instagram, lifelogging, Marshall McLuhan, means of production, Nate Silver, natural language processing, Netflix Prize, pattern recognition, price discrimination, recommendation engine, Richard Thaler, Rosa Parks, self-driving car, sentiment analysis, Silicon Valley, Silicon Valley startup, Slavoj Žižek, social graph, speech recognition, Steve Jobs, Steven Levy, Steven Pinker, Stewart Brand, the scientific method, The Signal and the Noise by Nate Silver, upwardly mobile, Wall-E, Watson beat the top human players on Jeopardy!, Y Combinator

Not everyone is an expert in supercomputing and not everyone has the ability, nor the resources (his regimen costs between $5,000 and $10,000 each year) to capture huge amounts of personal data, or to make sense of it in the event that they do. But Smarr is not alone. As a data junkie, he is a valued member of the so-called Quantified Self movement: an ever-expanding group of similar individuals who enthusiastically take part in a form of self-tracking, somatic surveillance. Founded by Wired magazine editors Gary Wolf and Kevin Kelly in the mid-2000s, the Quantified Self movement casts its aspirations in bold philosophical terms, promising devotees “self-knowledge through numbers.”4 Taking the Positivist view of verification and empiricism, and combining this with a liberal dose of technological determinism, the Quantified Self movement begs the existential question of what kind of self can possibly exist that is unable to be number-crunched using the right algorithms? If Socrates concluded that the unexamined life was not worth living, then a 21st-century update might suggest the same of the unquantified life.

By quantifying the self, a person can find apparently rigorous answers to questions as broad or specific as how many minutes of sleep are lost each night per unit of alcohol consumed, how consistent their golf swing is, or whether or not they should stay in their current job. Consider, for example, the story of a young female member of the Quantified Self movement, referred to only as “Angela.” Angela was working in what she considered to be her dream job, when she downloaded an app that “pinged” her multiple times each day, asking her to rate her mood each time. As patterns started to emerge in the data, Angela realized that her “mood score” showed that she wasn’t very happy at work, after all. When she discovered this, she handed in her notice and quit. “The one commonality that I see among people in the Quantified Self movement is that they have questions only the data can answer,” says 43-year-old Selfer Vincent Dean Boyce. “These questions may be very simplistic at first, but they very quickly become more complex.

Adams, Douglas 2 Adorno, Theodor 179, 205 Adventures in the Screen Trade (Goldman) 161 Affectiva 193 Against Autonomy (Conly) 138–39 Agrippa (Gibson) 238n Akrich, Madeline 136n algorithms: and Amazon’s “fulfilment associates” 44 and astronaut selection 24 and black-boxing 151–52, 227–28, 235–36 and call centers 21–22, 24–25, 49–50 cars driven by 141–42 in CCTV cameras 145–46 and death 96–98 and differential pricing 50–53 and differentiated search results 47–48 and discriminatory practices 53–54 for divorce 130–31 for drunk-driving detection 131–33 and early computer dating 82 and emotion sniffing 51–52 and equity market 210–11 and exclusive highways 48–49 explained 1–6 for finding love and sex 61–95 passim, 98–105; see also ALikeWise; BeautifulPeople; Bedpost; eHarmony; FindYourFaceMate; FitnessSingles; Internet: dating; Kari; LargeAndLovely; love and sex; “Match”; Match .com; OKCupid; PlentyOfFish; SeaCaptainDate; Serendipity; TrekPassions; UniformDating; VeggieDate Flu Trends 238–39 to forecast crime 119–24; see also Berk, Richard; law and law enforcement and gaming technology 32–34 “genetic” 203–4 growing role of 210 Iamus 206–7 inferences of, and conceptions of self 36–38 and Kari 98–103; see also love and sex and legal documents 129–30 and London Symphony Orchestra 206 and “The Match,” see “Match” measuring students’ progress with 39–41 and medic 211 and money laundering 18–19 and offence 224–27 and police work, public policy and judicial system, see law and law enforcement and recruitment 25–31 and same-sex couples 147 and student grades 208, 212 and terrorism 149–50, 153 as “tricks” 221–23 and “truths” in art 182–83; see also art and entertainment TruthTeller 237 and Twitter 35–36, 38 upward mobility programmed into 46–47 why we trust 149–51 ALikeWise 79 Amabot 214–15 Amazon 85, 188, 198 and disappearing gay-friendly books 232 e-books sold by 179–80 “fulfilment associates” at 44–45 how algorithms work with 1–2 and Solid Gold Bomb 224–25 two departments of 213–15 work practices at 44–46 Ambient Law 131–33, 137, 143–44 Amscreen 20 Anderson, Chris 56, 191n, 223 Angela (Quantified Self devotee) 14 see also Quantified Self movement Aniston, Jennifer 69 Anomo 89–90 Apple 133 Apple v. Samsung 127–28 Apprentice, The (US) 89 Aquinas, Thomas 183 Aron, Arthur 101 art and entertainment 161–207 and dehumanisation 203–4 and films via Internet 179–80 and mass market 175–77 and Salganik–Dodds–Watts study 172–73 and “superstar” markets 173 see also Epagogix; individual participants; individual titles artificial intelligence 126, 217 AT&T 29 Atlantic 11 Avatar 163, 172, 205 Avaya 49 Balloon Brigade 33 Barefoot Into Cyberspace (Hogge) 44 Barrymore, Drew 167 Barthes, Roland 186 Bauman, Zygmunt 81–82 BeautifulPeople 78 beauty map 31–32 Beck, Charlie 106–7 Bedpost 13, 93–95 Bedwood, David 97 Beethoven, Ludwig 202 Bellos, David 215 Benjamin, Walter 178–79 Bense, Max 182n Bentham, Jeremy 55, 118 Berk, Richard 120–24, 236 Bezos, Jeff 190 Bianculli, David 189 Bieber, Justin 202–3 Blackstone Electronic Discovery 127–28 Blink (Gladwell) 211 blogging 30 and owners’ personalities 38–39 and word choice 38–39 body-hacking 13–14 BodyMedia 94 books, see art and entertainment Bowden, B.


pages: 317 words: 87,566

The Happiness Industry: How the Government and Big Business Sold Us Well-Being by William Davies

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1960s counterculture, Airbnb, business intelligence, Cass Sunstein, corporate governance, dematerialisation, experimental subject, Exxon Valdez, Frederick Winslow Taylor, Gini coefficient, income inequality, intangible asset, invisible hand, joint-stock company, lifelogging, market bubble, mental accounting, nudge unit, Philip Mirowski, profit maximization, randomized controlled trial, Richard Thaler, road to serfdom, Ronald Coase, Ronald Reagan, science of happiness, selective serotonin reuptake inhibitor (SSRI), sentiment analysis, sharing economy, Slavoj Žižek, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, Steve Jobs, The Chicago School, The Spirit Level, theory of mind, urban planning, Vilfredo Pareto

When obliged to report on their inner mental states for research purposes, people do so only grudgingly. But when doing so of their own volition, suddenly reporting on behaviour and moods becomes a fulfilling, satisfying activity in its own right. The ‘quantified self’ movement, in which individuals measure and report on various aspects of their private lives – from their diets, to their moods, to their sex lives – began as an experimental group of software developers and artists. But it unearthed a surprising enthusiasm for self-surveillance that market researchers and behavioural scientists have carefully noted. Companies such as Nike are now exploring ways in which health and fitness products can be sold alongside quantified self apps, which will allow individuals to make constant reports of their behaviour (such as jogging), generating new data sets for the company in the process. There is a third development, the political and philosophical implications of which are potentially the most radical of all.

See positive psychology promise of practical utility of, 91 reunion of with economics, 64, 182 social psychology, 125, 189, 266 theory of, as balancing act, 67 The Psychology of Advertising (Scott), 86 psychopharmacology, 162 psychophysical parallelism, 259 psychophysics, 29, 30, 31 psychosomatic interventions/management/programmes/theories, 122, 124, 128, 135 psychotherapy, 124, 127 pulse rate, 25, 26, 27, 37, 79 punishment, 16, 19, 22, 23, 179, 183, 239 PwC, 119 Qualia, 36 quality of life measures, 126 quantitative sociological research, 98 quantified community, 233, 234 quantified self apps, 221 quantified self movement, 221, 228 quants, 237 questionnaires, 165, 175, 176 random acts of managerial generosity, 184 randomized sampling methods, 97 Rapley, Mark, 250 Rayner, Rosalie, 93 Reagan, Ronald, 144, 149, 159 Realeyes, 72 real-time health data, 137 real-time social trends, 224 recessions, 67–8, 252 Recognizing the Depressed Patient (Ayd), 164 reductionism, 27, 264 research ethics, 91–2, 225 resilience training, 35, 273 Resor, Stanley, 93–4, 95, 96 retail culture, 58 Ricard, Matthieu, 2, 4 Robbins, Lionel, 154 Robins, Eli, 169 Rockefeller Foundation, 97, 99, 121 Rogers, Carl, 146 Roosevelt, Franklin, 101, 146 Rowntree, Joseph, 99 RunKeeper, 240 Ryanair, 185 Salter, Tim, 110 sampling methods, 97–8 Santa Monica, California, 4 São Paolo, Brazil, Clean City Law, 275 scales, 146, 165, 175, 176 scanning technology, 75–6 scent logos, 73 Schrader, Harald, 44 scientific advertising, 215 scientific management, 118–19, 120, 136–7, 235 scientific optimism, 242 scientific politics, 77, 88, 145 scientists, as source of authority, 147–8 Scott, Walter Dill, 83, 85 screen time, 207 second brain, 231 secular religions, 260 selective serotonin reuptake inhibitors (SSRIs), 163, 166 self-anchored striving, 147, 166, 175 self-anchoring striving scale, 146 self-forming groups, 200 self-help gurus, 210 self-help literature, 247 self-improvement, 212 self-monitoring, 258 self-optimization, 213 self-reflection, 211 self-surveillance, 221, 230 Seligman, Martin, 165, 277n5 Selye, Hans, 128–31, 133, 264 The Senses and the Intellect (Bain), 48 sentiment analysis/tracking, 6, 221, 223, 261 sexual orientation disturbance, 172 sharing economy, 188 shopping, 58, 74, 93, 188, 239 sick notes, 112 Sing Sing prison, 201 Smail, David, 250 smart cities, 220, 224, 239 smart homes, 239 smart watches, 37 smartphones, 10, 207, 222, 230 smiles/smiling, 36–7, 38 Smith, Adam, 49, 50, 52, 55 social, 1, 36, 184, 186, 187, 188, 190, 191, 203, 204, 205, 207, 208, 211–12 social analytics, 188, 191, 193, 196 social capitalism, 212 social contagion, science of, 257 social economy, 190 social epidemiology, 9, 250, 254 social media, 188, 189, 199, 203, 207, 208–9, 213, 224, 261, 274 social media addiction, 206, 207 social network analysis, 204, 208 social networks, 193, 194, 195, 196, 213, 225 social neuroscience, 193, 195, 213, 214 social obligation, 184 social optimization, 181–214 social prescribing, 194, 212, 246, 271 social psychology, 125, 189, 266 social research, 98, 202, 226 social science, as converging with physiology into new discipline, 195 sociology, 254 sociometric analysis, 199 sociometric maps, 202 Sociometric Solutions, 239 sociometry, 199, 201, 202, 203 Spengler, Oswald, 121 Spitzer, Robert, 171–3, 176, 271 sponsored conversations, 189 sport, as virtue for political leaders, 140 sporting metaphors, 141 SSRIs (selective serotonin reuptake inhibitors), 163, 166 St Louis school of psychiatry, 169, 170, 171, 173, 174, 176, 179 Stanton, Frank, 99 Stigler, George, 150, 152, 153, 156–7, 158, 160 stress, 37, 129, 130, 131, 132, 133, 175, 250, 262, 272, 273 Stuckler, David, 252 subjective affect, science of, 6, 7 subjective feelings, relationship with external circumstances, 254 subjective sensation, 30, 45, 55, 61 Suicide (Durkheim), 227 Sully, James, 59, 84 surveillance, 231, 237, 238, 240, 242.

Neuroscientists identify how happiness and unhappiness are physically inscribed in the brain, as the researchers in Wisconsin did with Matthieu Ricard, and seek out neural explanations for why singing and greenery seem to improve our mental well-being. They claim to have found the precise parts of the brain which generate positive and negative emotions, including an area that provokes ‘bliss’ when stimulated, and a ‘pain dimmer switch’.8 Innovation within the experimental ‘quantified self’ movement sees individuals carrying out personalized ‘mood tracking’, through diaries and smartphone apps.9 As the statistical evidence in this area accumulates, so the field of ‘happiness economics’ grows to take advantage of all this new data, building up a careful picture of which regions, lifestyles, forms of employment or types of consumption generate the greatest mental well-being. Our hopes are being strategically channelled into this quest for happiness, in an objective, measurable, administered sense.


pages: 391 words: 105,382

Utopia Is Creepy: And Other Provocations by Nicholas Carr

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Air France Flight 447, Airbnb, Airbus A320, AltaVista, Amazon Mechanical Turk, augmented reality, autonomous vehicles, Bernie Sanders, book scanning, Brewster Kahle, Buckminster Fuller, Burning Man, Captain Sullenberger Hudson, centralized clearinghouse, cloud computing, cognitive bias, collaborative consumption, computer age, corporate governance, crowdsourcing, Danny Hillis, deskilling, digital map, Donald Trump, Electric Kool-Aid Acid Test, Elon Musk, factory automation, failed state, feminist movement, Frederick Winslow Taylor, friendly fire, game design, global village, Google bus, Google Glasses, Google X / Alphabet X, Googley, hive mind, impulse control, indoor plumbing, interchangeable parts, Internet Archive, invention of movable type, invention of the steam engine, invisible hand, Isaac Newton, Jeff Bezos, jimmy wales, job automation, Kevin Kelly, lifelogging, low skilled workers, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, means of production, Menlo Park, mental accounting, natural language processing, Network effects, new economy, Nicholas Carr, Norman Mailer, off grid, oil shale / tar sands, Peter Thiel, Plutocrats, plutocrats, profit motive, Ralph Waldo Emerson, Ray Kurzweil, recommendation engine, Republic of Letters, robot derives from the Czech word robota Czech, meaning slave, Ronald Reagan, self-driving car, SETI@home, side project, Silicon Valley, Silicon Valley ideology, Singularitarianism, Snapchat, social graph, social web, speech recognition, Startup school, stem cell, Stephen Hawking, Steve Jobs, Steven Levy, technoutopianism, the medium is the message, theory of mind, Turing test, Whole Earth Catalog, Y Combinator

And every company knows that if their people have EI, they’re gonna make a shitload of money.” Namaste. THE QUANTIFIED SELF AT WORK October 25, 2013 THE FAITHFUL GATHERED IN San Francisco earlier this month for the Quantified Self Global Conference, an annual conclave of “self-trackers and tool-makers.” The Quantified Self movement aims to bring the new apparatus of big data to the old pursuit of self-actualization, using sensors, wearables, apps, and the cloud to monitor and optimize bodily functions and engineer a more perfect self. “Instead of interrogating their inner worlds through talking and writing,” longtime QS promoter Gary Wolf explains, self-trackers are seeking “self-knowledge through numbers.” He continues: “Behind the allure of the quantified self is a guess that many of our problems come from simply lacking the instruments to understand who we are.”

., 107 proactive cognitive control, 96 Prochnik, George, 243–46 “Productivity Future Vision (2011),” 108–9 Project Gutenberg, 278 prosperity, technologies of, 118, 119–20 prosumerism, 64 protest movements, 61 Proust and the Squid (Wolf), 234 proximal clues, 303 public-domain books, 277–78 “public library,” debate over use of term, 272–74 punch-card tabulator, 188 punk music, 63–64 Quantified Self Global Conference, 163 Quantified Self (QS) movement, 163–65 Quarter-of-a-Second Rule, 205 racecars, 195, 196 radio: in education, 134 evolution of, 77, 79, 159, 288 as music medium, 45, 121–22, 207 political use of, 315–16, 317, 319 Radosh, Daniel, 71 Rapp, Jen, 341–42 reactive cognitive control, 96 Readers’ Guide to Periodical Literature, 91 reading: brain function in, 247–54, 289–90 and invention of paper, 286–87 monitoring of, 257 video gaming vs., 261–62 see also books reading skills, changes in, 232–34, 240–41 Read Write Web (blog), 30 Reagan, Ronald, 315 real world: digital media intrusion in, 127–30 perceived as boring and ugly, 157–58 as source of knowledge, 313 virtual world vs., xx–xxi, 36, 62, 127–30, 303–4 reconstructive surgery, 239 record albums: copying of, 121–22 jackets for, 122, 224 technology of, 41–46 Redding, Otis, 126 Red Light Center, 39 Reichelt, Franz, 341 Reid, Rob, 122–25 relativists, 20 religion: internet perceived as, 3–4, 238 for McLuhan, 105 technology viewed as, xvi–xvii Republic of Letters, 271 reputations, tarnishing of, 47–48, 190–94 Resident Evil, 260–61 resource sharing, 148–49 resurrection, 69–70, 126 retinal implants, 332 Retromania (Reynolds), 217, 292–95 Reuters, Adam, 26 Reuters’ SL bureau, 26 revivification machine, 69–70 Reynolds, Simon, 217–18, 292–95 Rice, Isaac, 244 Rice, Julia Barnett, 243–44 Richards, Keith, 42 “right to be forgotten” lawsuit, 190–94 Ritalin, 304 robots: control of, 303 creepy quality of, 108 human beings compared to, 242 human beings replaced by, 112, 174, 176, 195, 197, 306–7, 310 limitations of, 323 predictions about, xvii, 177, 331 replaced by humans, 323 threat from, 226, 309 Rogers, Roo, 83–84 Rolling Stones, 42–43 Roosevelt, Franklin, 315 Rosen, Nick, 52 Rubio, Marco, 314 Rumsey, Abby Smith, 325–27 Ryan, Amy, 273 Sandel, Michael J., 340 Sanders, Bernie, 314, 316 Sansom, Ian, 287 Savage, Jon, 63 scatology, 147 Schachter, Joshua, 195 Schivelbusch, Wolfgang, 229 Schmidt, Eric, 13, 16, 238, 239, 257, 284 Schneier, Bruce, 258–59 Schüll, Natasha Dow, 218 science fiction, 106, 115, 116, 150, 309, 335 scientific management, 164–65, 237–38 Scrapbook in American Life, The, 185 scrapbooks, social media compared to, 185–86 “Scrapbooks as Cultural Texts” (Katriel and Farrell), 186 scythes, 302, 304–6 search-engine-optimization (SEO), 47–48 search engines: allusions sought through, 86 blogging, 66–67 in centralization of internet, 66–69 changing use of, 284 customizing by, 264–66 erroneous or outdated stories revived by, 47–48, 190–94 in filtering, 91 placement of results by, 47–48, 68 searching vs., 144–46 targeting information through, 13–14 writing tailored to, 89 see also Google searching, ontological connotations of, 144–46 Seasteading Institute, 172 Second Life, 25–27 second nature, 179 self, technologies of the, 118, 119–20 self-actualization, 120, 340 monitoring and quantification of, 163–65 selfies, 224 self-knowledge, 297–99 self-reconstruction, 339 self-tracking, 163–65 Selinger, Evan, 153 serendipity, internet as engine of, 12–15 SETI@Home, 149 sexbots, 55 Sex Pistols, 63 sex-reassignment procedures, 337–38 sexuality, 10–11 virtual, 39 Shakur, Tupac, 126 sharecropping, as metaphor for social media, 30–31 Shelley, Percy Bysshe, 88 Shirky, Clay, 59–61, 90, 241 Shop Class as Soulcraft (Crawford), 265 Shuster, Brian, 39 sickles, 302 silence, 246 Silicon Valley: American culture transformed by, xv–xxii, 148, 155–59, 171–73, 181, 241, 257, 309 commercial interests of, 162, 172, 214–15 informality eschewed by, 197–98, 215 wealthy lifestyle of, 16–17, 195 Simonite, Tom, 136–37 simulation, see virtual world Singer, Peter, 267 Singularity, Singularitarians, 69, 147 sitcoms, 59 situational overload, 90–92 skimming, 233 “Slaves to the Smartphone,” 308–9 Slee, Tom, 61, 84 SLExchange, 26 slot machines, 218–19 smart bra, 168–69 smartphones, xix, 82, 136, 145, 150, 158, 168, 170, 183–84, 219, 274, 283, 287, 308–9, 315 Smith, Adam, 175, 177 Smith, William, 204 Snapchat, 166, 205, 225, 316 social activism, 61–62 social media, 224 biases reinforced by, 319–20 as deceptively reflective, 138–39 documenting one’s children on, 74–75 economic value of content on, 20–21, 53–54, 132 emotionalism of, 316–17 evolution of, xvi language altered by, 215 loom as metaphor for, 178 maintaining one’s microcelebrity on, 166–67 paradox of, 35–36, 159 personal information collected and monitored through, 257 politics transformed by, 314–20 scrapbooks compared to, 185–86 self-validation through, 36, 73 traditional media slow to adapt to, 316–19 as ubiquitous, 205 see also specific sites social organization, technologies of, 118, 119 Social Physics (Pentland), 213 Society for the Suppression of Unnecessary Noise, 243–44 sociology, technology and, 210–13 Socrates, 240 software: autonomous, 187–89 smart, 112–13 solitude, media intrusion on, 127–30, 253 Songza, 207 Sontag, Susan, xx SoundCloud, 217 sound-management devices, 245 soundscapes, 244–45 space travel, 115, 172 spam, 92 Sparrow, Betsy, 98 Special Operations Command, U.S., 332 speech recognition, 137 spermatic, as term applied to reading, 247, 248, 250, 254 Spinoza, Baruch, 300–301 Spotify, 293, 314 “Sprite Sips” (app), 54 Squarciafico, Hieronimo, 240–41 Srinivasan, Balaji, 172 Stanford Encyclopedia of Philosophy, 68 Starr, Karla, 217–18 Star Trek, 26, 32, 313 Stengel, Rick, 28 Stephenson, Neal, 116 Sterling, Bruce, 113 Stevens, Wallace, 158 Street View, 137, 283 Stroop test, 98–99 Strummer, Joe, 63–64 Studies in Classic American Literature (Lawrence), xxiii Such Stuff as Dreams (Oatley), 248–49 suicide rate, 304 Sullenberger, Sully, 322 Sullivan, Andrew, xvi Sun Microsystems, 257 “surf cams,” 56–57 surfing, internet, 14–15 surveillance, 52, 163–65, 188–89 surveillance-personalization loop, 157 survival, technologies of, 118, 119 Swing, Edward, 95 Talking Heads, 136 talk radio, 319 Tan, Chade-Meng, 162 Tapscott, Don, 84 tattoos, 336–37, 340 Taylor, Frederick Winslow, 164, 237–38 Taylorism, 164, 238 Tebbel, John, 275 Technics and Civilization (Mumford), 138, 235 technology: agricultural, 305–6 American culture transformed by, xv–xxii, 148, 155–59, 174–77, 214–15, 229–30, 296–313, 329–42 apparatus vs. artifact in, 216–19 brain function affected by, 231–42 duality of, 240–41 election campaigns transformed by, 314–20 ethical hazards of, 304–11 evanescence and obsolescence of, 327 human aspiration and, 329–42 human beings eclipsed by, 108–9 language of, 201–2, 214–15 limits of, 341–42 master-slave metaphor for, 307–9 military, 331–32 need for critical thinking about, 311–13 opt-in society run by, 172–73 progress in, 77–78, 188–89, 229–30 risks of, 341–42 sociology and, 210–13 time perception affected by, 203–6 as tool of knowledge and perception, 299–304 as transcendent, 179–80 Technorati, 66 telegrams, 79 telegraph, Twitter compared to, 34 telephones, 103–4, 159, 288 television: age of, 60–62, 79, 93, 233 and attention disorders, 95 in education, 134 Facebook ads on, 155–56 introduction of, 103–4, 159, 288 news coverage on, 318 paying for, 224 political use of, 315–16, 317 technological adaptation of, 237 viewing habits for, 80–81 Teller, Astro, 195 textbooks, 290 texting, 34, 73, 75, 154, 186, 196, 205, 233 Thackeray, William, 318 “theory of mind,” 251–52 Thiel, Peter, 116–17, 172, 310 “Things That Connect Us, The” (ad campaign), 155–58 30 Days of Night (film), 50 Thompson, Clive, 232 thought-sharing, 214–15 “Three Princes of Serendip, The,” 12 Thurston, Baratunde, 153–54 time: memory vs., 226 perception of, 203–6 Time, covers of, 28 Time Machine, The (Wells), 114 tools: blurred line between users and, 333 ethical choice and, 305 gaining knowledge and perception through, 299–304 hand vs. computer, 306 Home and Away blurred by, 159 human agency removed from, 77 innovation in, 118 media vs., 226 slave metaphor for, 307–8 symbiosis with, 101 Tosh, Peter, 126 Toyota Motor Company, 323 Toyota Prius, 16–17 train disasters, 323–24 transhumanism, 330–40 critics of, 339–40 transparency, downside of, 56–57 transsexuals, 337–38 Travels and Adventures of Serendipity, The (Merton and Barber), 12–13 Trends in Biochemistry (Nightingale and Martin), 335 TripAdvisor, 31 trolls, 315 Trump, Donald, 314–18 “Tuft of Flowers, A” (Frost), 305 tugboats, noise restrictions on, 243–44 Tumblr, 166, 185, 186 Turing, Alan, 236 Turing Test, 55, 137 Twain, Mark, 243 tweets, tweeting, 75, 131, 315, 319 language of, 34–36 theses in form of, 223–26 “tweetstorm,” xvii 20/20, 16 Twilight Saga, The (Meyer), 50 Twitter, 34–36, 64, 91, 119, 166, 186, 197, 205, 223, 224, 257, 284 political use of, 315, 317–20 2001: A Space Odyssey (film), 231, 242 Two-Lane Blacktop (film), 203 “Two Tramps in Mud Time” (Frost), 247–48 typewriters, writing skills and, 234–35, 237 Uber, 148 Ubisoft, 261 Understanding Media (McLuhan), 102–3, 106 underwearables, 168–69 unemployment: job displacement in, 164–65, 174, 310 in traditional media, 8 universal online library, 267–78 legal, commercial, and political obstacles to, 268–71, 274–78 universe, as memory, 326 Urban Dictionary, 145 utopia, predictions of, xvii–xviii, xx, 4, 108–9, 172–73 Uzanne, Octave, 286–87, 290 Vaidhyanathan, Siva, 277 vampires, internet giants compared to, 50–51 Vampires (game), 50 Vanguardia, La, 190–91 Van Kekerix, Marvin, 134 vice, virtual, 39–40 video games, 223, 245, 303 as addictive, 260–61 cognitive effects of, 93–97 crafting of, 261–62 violent, 260–62 videos, viewing of, 80–81 virtual child, tips for raising a, 73–75 virtual world, xviii commercial aspects of, 26–27 conflict enacted in, 25–27 language of, 201–2 “playlaborers” of, 113–14 psychological and physical health affected by, 304 real world vs., xx–xxi, 36, 62, 127–30 as restrictive, 303–4 vice in, 39–40 von Furstenberg, Diane, 131 Wales, Jimmy, 192 Wallerstein, Edward, 43–44 Wall Street, automation of, 187–88 Wall Street Journal, 8, 16, 86, 122, 163, 333 Walpole, Horace, 12 Walters, Barbara, 16 Ward, Adrian, 200 Warhol, Andy, 72 Warren, Earl, 255, 257 “Waste Land, The” (Eliot), 86, 87 Watson (IBM computer), 147 Wealth of Networks, The (Benkler), xviii “We Are the Web” (Kelly), xxi, 4, 8–9 Web 1.0, 3, 5, 9 Web 2.0, xvi, xvii, xxi, 33, 58 amorality of, 3–9, 10 culturally transformative power of, 28–29 Twitter and, 34–35 “web log,” 21 Wegner, Daniel, 98, 200 Weinberger, David, 41–45, 277 Weizenbaum, Joseph, 236 Wells, H.

LIVE FAST, DIE YOUNG, AND LEAVE A BEAUTIFUL HOLOGRAM ONLINE, OFFLINE, AND THE LINE BETWEEN GOOGLE GLASS AND CLAUDE GLASS BURNING DOWN THE SCHOOLHOUSE THE ENNUI OF THE INTELLIGENT MACHINE REFLECTIONS WILL GUTENBERG LAUGH LAST? THE SEARCHERS ETERNAL SUNSHINE OF THE SPOTLESS AI MAX LEVCHIN HAS PLANS FOR US EVGENY’S LITTLE PROBLEM THE SHORTEST CONVERSATION BETWEEN TWO POINTS HOME AWAY FROM HOME CHARCOAL, SHALE, COTTON, TANGERINE, SKY SLUMMING WITH BUDDHA THE QUANTIFIED SELF AT WORK MY COMPUTER, MY DOPPELTWEETER UNDERWEARABLES THE BUS THE MYTH OF THE ENDLESS LADDER THE LOOM OF THE SELF TECHNOLOGY BELOW AND BEYOND OUTSOURCING DAD TAKING MEASUREMENT’S MEASURE SMARTPHONES ARE HOT DESPERATE SCRAPBOOKERS OUT OF CONTROL OUR ALGORITHMS, OURSELVES TWILIGHT OF THE IDYLLS THE ILLUSION OF KNOWLEDGE WIND-FUCKING THE SECONDS ARE JUST PACKED MUSIC IS THE UNIVERSAL LUBRICANT TOWARD A UNIFIED THEORY OF LOVE <3S AND MINDS IN THE KINGDOM OF THE BORED, THE ONE-ARMED BANDIT IS KING THESES IN TWEETFORM THE EUNUCH’S CHILDREN: ESSAYS AND REVIEWS FLAME AND FILAMENT IS GOOGLE MAKING US STUPID?


pages: 247 words: 81,135

The Great Fragmentation: And Why the Future of All Business Is Small by Steve Sammartino

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3D printing, additive manufacturing, Airbnb, augmented reality, barriers to entry, Bill Gates: Altair 8800, bitcoin, BRICs, Buckminster Fuller, citizen journalism, collaborative consumption, cryptocurrency, David Heinemeier Hansson, Elon Musk, fiat currency, Frederick Winslow Taylor, game design, Google X / Alphabet X, haute couture, helicopter parent, illegal immigration, index fund, Jeff Bezos, jimmy wales, Kickstarter, knowledge economy, Law of Accelerating Returns, lifelogging, market design, Metcalfe's law, Metcalfe’s law, Minecraft, minimum viable product, Network effects, new economy, peer-to-peer, post scarcity, prediction markets, pre–internet, profit motive, race to the bottom, random walk, Ray Kurzweil, recommendation engine, remote working, RFID, Rubik’s Cube, self-driving car, sharing economy, side project, Silicon Valley, Silicon Valley startup, skunkworks, Skype, social graph, social web, software is eating the world, Steve Jobs, survivorship bias, too big to fail, US Airways Flight 1549, web application, zero-sum game

How can they help them save energy, money and time; provide feedback; give life-hacking suggestions; and cross-reference data with other services? How can they create a mutual benefit for the brand, the end user and the community? That’s the emerging job of marketers. Everything can and will be connected, unless of course the item’s brand proposition is that it’s ‘deliberately not connected’. What’s first? The connected home we spoke about above and the quantified self will provide the seeds of belief and value for everyone to embrace the web of things. The connected home and the quantified self can be defined as technology that tracks our human movements, providing data and feedback on what we do physically. Many popular smartphone apps already play in this space. The benefits we see from using gadgets such as fitness-tracking apps for quantifiable feedback are indisputable. Their popularity will provide a Trojan horse for more personal, and in some ways invasive, tracking into our lives.

They’d say the inability of Foursquare to crack the mainstream was telling. They’d claim that digital games just don’t garner the loyalty required to become a serious commercial outcome. But what they’re missing is the fact that most digital-based gaming hasn’t had the important layer of economic incentives added. This is the missing link. Due to that, gamification in the infiltrated commercial sense is in its infancy. But it has given birth to the quantified-self movement. quantified self: the use of technology to track personal activity and provide feedback to improve ourselves and our lives Games are for nerds, right? Sure, we all enjoy a little mobile app–based game for a bit of fun, but isn’t hardcore, continuous, long-term gaming behaviour the domain of the ultra nerd? Isn’t that something for kids who live in basements and adolescents with headphones and an indoor fluorescent-light suntan?

What smart businesses will do, is connect what they sell and open up or hand over the software-development ecosystem to the crowd to see what they can build. To benefit from a connected world, businesses need to let go of perceived control and hand the brand over to the audience in the same way traditional media should have — but didn’t — when social media arrived. The connected home, the quantified self, two-way loyalty, gamification and real data will usurp demographic profiling and marketing guessing games forever. But getting to that phase requires companies and brands to have trust in the potential or organic commercial ecosystems. They will have to trust that the opportunity can’t be totally strategised or foretold and just needs to be embraced. It will be a bit like walking in the fog: we won’t be able to see the end of the trail, but as we move forward more of the path will become clear.


pages: 410 words: 119,823

Radical Technologies: The Design of Everyday Life by Adam Greenfield

3D printing, Airbnb, augmented reality, autonomous vehicles, bank run, barriers to entry, basic income, bitcoin, blockchain, business intelligence, business process, call centre, cellular automata, centralized clearinghouse, centre right, Chuck Templeton: OpenTable, cloud computing, collective bargaining, combinatorial explosion, Computer Numeric Control, computer vision, Conway's Game of Life, cryptocurrency, David Graeber, dematerialisation, digital map, distributed ledger, drone strike, Elon Musk, ethereum blockchain, facts on the ground, fiat currency, global supply chain, global village, Google Glasses, IBM and the Holocaust, industrial robot, informal economy, information retrieval, Internet of things, James Watt: steam engine, Jane Jacobs, Jeff Bezos, job automation, John Conway, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, joint-stock company, Kevin Kelly, Kickstarter, late capitalism, license plate recognition, lifelogging, M-Pesa, Mark Zuckerberg, means of production, megacity, megastructure, minimum viable product, money: store of value / unit of account / medium of exchange, natural language processing, Network effects, New Urbanism, Occupy movement, Oculus Rift, Pareto efficiency, pattern recognition, Pearl River Delta, performance metric, Peter Eisenman, Peter Thiel, planetary scale, Ponzi scheme, post scarcity, RAND corporation, recommendation engine, RFID, rolodex, Satoshi Nakamoto, self-driving car, sentiment analysis, shareholder value, sharing economy, Silicon Valley, smart cities, smart contracts, sorting algorithm, special economic zone, speech recognition, stakhanovite, statistical model, stem cell, technoutopianism, Tesla Model S, the built environment, The Death and Life of Great American Cities, The Future of Employment, transaction costs, Uber for X, universal basic income, urban planning, urban sprawl, Whole Earth Review, WikiLeaks, women in the workforce

Nobody has embraced this conception of instrumented living more fervently than a loose global network of enthusiasts called the Quantified Self, whose slogan is “self-knowledge through numbers.”2 Founded by Wired editor Gary Wolf and Whole Earth Review veteran Kevin Kelly in 2007, the Quantified Self currently boasts a hundred or so local chapters, and an online forum where members discuss and rate the devices mobilized in their self-measurement efforts. (It can be difficult to disentangle this broader movement from a California company of the same name also founded by Wolf and Kelly, which mounts conferences dedicated to proselytizing for the practice of self-measurement.) In their meetups and on their forum, the stalwarts of the Quantified Self discuss the theory and practice of the measured life, mulling everything from the devices most effective at capturing REM sleep to the legalities involved in sharing data.

If the endeavor retains a certain sprawling and formless quality, we can get a far more concrete sense of what it involves, what it invokes and what it requires by looking at each of the primary scales at which it appears to us: that of the body, that of the room, and that of public space in general. Though they all partake of the same general repertoire of techniques, each of these domains of activity has a specific, distinguishing label associated with it. The quest to instrument the body, monitor its behavior and derive actionable insight from these soundings is known as the “quantified self”; the drive to render interior, domestic spaces visible to the network “the smart home”; and when this effort is extended to municipal scale, it is known as “the smart city.” Each of these scales of activity illuminates a different aspect of the challenge presented to us by the internet of things, and each of them has something distinct to teach us. At the most intimate scale, the internet of things manifests in the form of wearable biometric sensors: devices that collect the various traces of our being in the world, and submit them to the network for inspection and analysis.

Consider the young cognitive neuroscientist who cross-referenced her online purchases, entertainment choices and dating decisions against her menstrual cycle,3 and found among other things that she only ever purchased red clothing when she was at her most fertile. What almost never seems to be addressed in these forums and meetups, though, are questions about what this self-knowledge is being mobilized for, and just where the criteria against which adherents feel they need to optimize their performance come from in the first place. While there are some fascinating questions being explored in the Quantified Self community, a brutal regime of efficiency operates in the background. Against the backdrop of late capitalism, the rise of wearable biometric monitoring can only be understood as a disciplinary power traversing the body itself and all its flows. This is a power that Frederick Taylor never dreamed of, and Foucault would have been laughed out of town for daring to propose. It’s clear that the appeal of this is overwhelmingly to young workers in the technology industry itself, the control they harvest from the act of quantification intended to render them psychophysically suitable for performance in a work environment characterized by implacable release schedules and a high operational tempo.


pages: 292 words: 85,151

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

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23andMe, 3D printing, Airbnb, Amazon Mechanical Turk, Amazon Web Services, augmented reality, autonomous vehicles, Baxter: Rethink Robotics, bioinformatics, bitcoin, Black Swan, blockchain, Burning Man, business intelligence, business process, call centre, chief data officer, Chris Wanstrath, Clayton Christensen, clean water, cloud computing, cognitive bias, collaborative consumption, collaborative economy, commoditize, corporate social responsibility, cross-subsidies, crowdsourcing, cryptocurrency, dark matter, Dean Kamen, dematerialisation, discounted cash flows, distributed ledger, Edward Snowden, Elon Musk, en.wikipedia.org, ethereum blockchain, Galaxy Zoo, game design, Google Glasses, Google Hangouts, Google X / Alphabet X, gravity well, hiring and firing, Hyperloop, industrial robot, Innovator's Dilemma, intangible asset, Internet of things, Iridium satellite, Isaac Newton, Jeff Bezos, Kevin Kelly, Kickstarter, knowledge worker, Kodak vs Instagram, Law of Accelerating Returns, Lean Startup, life extension, lifelogging, loose coupling, loss aversion, Lyft, Marc Andreessen, Mark Zuckerberg, market design, means of production, minimum viable product, natural language processing, Netflix Prize, Network effects, new economy, Oculus Rift, offshore financial centre, p-value, PageRank, pattern recognition, Paul Graham, peer-to-peer, peer-to-peer model, Peter H. Diamandis: Planetary Resources, Peter Thiel, prediction markets, profit motive, publish or perish, Ray Kurzweil, recommendation engine, RFID, ride hailing / ride sharing, risk tolerance, Ronald Coase, Second Machine Age, self-driving car, sharing economy, Silicon Valley, skunkworks, Skype, smart contracts, Snapchat, social software, software is eating the world, speech recognition, stealth mode startup, Stephen Hawking, Steve Jobs, subscription business, supply-chain management, TaskRabbit, telepresence, telepresence robot, Tony Hsieh, transaction costs, Tyler Cowen: Great Stagnation, urban planning, WikiLeaks, winner-take-all economy, X Prize, Y Combinator, zero-sum game

An aircraft engine has as many as three thousand sensors measuring billions of data points per voyage. And as we mentioned in Chapter One, a Google car, with its lidar (light radar) scanning the surrounding environment with sixty-four lasers, collects almost a gigabyte of data per second per car. This revolution is also impacting our human bodies. In 2007, Wired magazine editors Gary Wolf and Kevin Kelly created the Quantified Self (QS) movement, which focuses on self-tracking tools. The first Quantified Self conference was held in May 2011, and today the QS community has more than 32,000 members in thirty-eight countries. Many new devices have been spun out of this movement. One of them is Spire, a QS device that measures respiration. Singularity University alumnus Francesco Mosconi is the chief data officer of Spire. The analytics and software he has written are all about real-time feedback regarding breath and how it relates to stress and focus—not unlike the way sensor feedback in a BMW’s traction control system reduces wheel slip.

In addition to the goal of helping to transform the downtown area into the most community-focused large city in the world, Hsieh aims to create the smartest place on the planet by maximizing the chances of serendipitous learning between Zappos insiders and outsiders. The result is not only a community built around common passions, but also around a common location. Note that in early stages, many companies find it easier to join an existing community that shares its MTP. The Quantified Self movement, for instance, is drawing together startups engaged in measuring all aspects of the human body. Examples of startups offering wearable technology that have banded together to form a community include Scanadu, Withings and Fitbit. As each startup finds its path, of course, it is free to create its own community, particularly once its user base is more significant. Crowd As mentioned earlier, the crowd is made up of concentric rings of people outside the core community.

The goal is not to live forever; the goal is to create something that will.” Step 2: Join or Create Relevant MTP Communities The collaborative power of communities is critical to any ExO. Whatever your passion (let’s say you dream of curing cancer), there are communities out there filled with other passionate, purpose-driven people devoted to the same crusade. The recent rise of the Quantified Self (QS) movement, first introduced in Chapter Five, is a great example of a community with an MTP. Operating in 120 cities and in forty countries, approximately 1,000 companies and 40,000 members currently participate in the QS ecosystem. Anyone interested in setting up a medical device company or addressing a major area such as cancer or heart disease can find and join a rich community of interested fellow participants.


pages: 903 words: 235,753

The Stack: On Software and Sovereignty by Benjamin H. Bratton

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1960s counterculture, 3D printing, 4chan, Ada Lovelace, additive manufacturing, airport security, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, algorithmic trading, Amazon Mechanical Turk, Amazon Web Services, augmented reality, autonomous vehicles, basic income, Benevolent Dictator For Life (BDFL), Berlin Wall, bioinformatics, bitcoin, blockchain, Buckminster Fuller, Burning Man, call centre, carbon footprint, carbon-based life, Cass Sunstein, Celebration, Florida, charter city, clean water, cloud computing, connected car, corporate governance, crowdsourcing, cryptocurrency, dark matter, David Graeber, deglobalization, dematerialisation, disintermediation, distributed generation, don't be evil, Douglas Engelbart, Douglas Engelbart, Edward Snowden, Elon Musk, en.wikipedia.org, Eratosthenes, ethereum blockchain, facts on the ground, Flash crash, Frank Gehry, Frederick Winslow Taylor, future of work, Georg Cantor, gig economy, global supply chain, Google Earth, Google Glasses, Guggenheim Bilbao, High speed trading, Hyperloop, illegal immigration, industrial robot, information retrieval, Intergovernmental Panel on Climate Change (IPCC), intermodal, Internet of things, invisible hand, Jacob Appelbaum, Jaron Lanier, John Markoff, Jony Ive, Julian Assange, Khan Academy, liberal capitalism, lifelogging, linked data, Mark Zuckerberg, market fundamentalism, Marshall McLuhan, Masdar, McMansion, means of production, megacity, megastructure, Menlo Park, Minecraft, Monroe Doctrine, Network effects, new economy, offshore financial centre, oil shale / tar sands, packet switching, PageRank, pattern recognition, peak oil, peer-to-peer, performance metric, personalized medicine, Peter Eisenman, Peter Thiel, phenotype, Philip Mirowski, Pierre-Simon Laplace, place-making, planetary scale, RAND corporation, recommendation engine, reserve currency, RFID, Robert Bork, Sand Hill Road, self-driving car, semantic web, sharing economy, Silicon Valley, Silicon Valley ideology, Slavoj Žižek, smart cities, smart grid, smart meter, social graph, software studies, South China Sea, sovereign wealth fund, special economic zone, spectrum auction, Startup school, statistical arbitrage, Steve Jobs, Steven Levy, Stewart Brand, Stuxnet, Superbowl ad, supply-chain management, supply-chain management software, TaskRabbit, the built environment, The Chicago School, the scientific method, Torches of Freedom, transaction costs, Turing complete, Turing machine, Turing test, universal basic income, urban planning, Vernor Vinge, Washington Consensus, web application, Westphalian system, WikiLeaks, working poor, Y Combinator

The User of this layer is not the universal persona that collapses design research into reductive and manipulative psychologism, a fixed term toward which design must orient its interfaces and artifacts, but as a model that is not given in advance and must be construed by interfaces and constructed for platforms. Its position at the top of The Stack, where driving agency is situated momentarily, is slippery, fragile, and always enmeshed in its own redefinition, an uncertainty that underwrites the formation of subjectivity in general, always a manifest image cobbled in relation to available technologies of self-reflection, from cave walls at Lascaux to Quantified Self Apps.8 The Quantified Self movement enrolls available digital tools into the willful fabrication of autonomic self-interpolation and may be where the current political logic of the User reaches a certain apotheosis. While the empirical tracking and analysis of one's personal biological processes is surely diagnostically important in many ways, especially as such data are aggregated and pluralized beyond private individuals by the surfacing of ecological, economic, and microbial forces, but the currency of personal performance optimization leans toward something rather different.

What Interfaces Are 52. Interfaces at Hand: From Object to Sign to Object 53. The Interface as Layer 54. Interfaces in The Stack 1: The Aesthetics of Logistics 55. Interfaces in The Stack 2: Apps and Programming the Space at Hand 56. Interfaces in the Stack 3: Theo-Interfaciality 57. Geoscapes: Interfaces Drawing Worlds User Layer 58. Origins of the User 59. Finding the Universal User 60. Quantified Self and Its Mirror 61. Trace and Frame 62. Maximum User 63. Death of the User 64. Animal User 65. AI User 66. Machine User 67. From User-Centered Design to the Design of the User III The ProjectsThe Stack to Come 68. Seeing The Stack We Have, Stacks to Come 69. Earth Layer to Come: God Bows to Math; Will Leviathan?9 70. Cloud Layer to Come: Cloud Feudalism and Its Discontents 71. 

This chapter describes how The Stack sees the humans and nonhumans that initiate columns up and down its layers, from Interface to Earth and back again, As a contemporary image of self, the User is asked to speak through utilitarian scripts, and yet its subjectivity is also opened up to unexpected kinds of universality. Human and nonhuman Users are positioned by The Stack (perhaps rudely) as comparable and even interchangeable through a wide-ranging and omnivorous quantification of their behaviors and effects. The preponderance of data generated by Users and the traces of their worldly transactions initially overtrace the outline of a given User (e.g., the hyperindividualism of the quantified self movement), but as new data streams overlap over it and through it, the coherent position of the User dissolves through its overdetermination by external relations and networks. The User's enumeration is first a grotesquely individuated self-image, a profile, but as the same process is oversubscribed by data that trace all the things that affect the User, now included in the profile, the persona that first promises coherency and closure brings an explosion and liquefaction of self.


pages: 304 words: 82,395

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

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

More important, however, it might identify individuals by their weight or the way they stand and walk. It could tell if someone fell and did not get back up, an important feature for the elderly. Retailers could learn the flow of traffic through their stores. When the floor is datafied, there is no ceiling to its possible uses. Datafying as much as possible is not as far out as it sounds. Consider the “quantified self” movement. It refers to a disparate group of fitness aficionados, medical maniacs, and tech junkies who measure every element of their bodies and lives in order to live better—or at least, to learn new things they couldn’t have known in an enumerated way before. The number of “self-trackers” is small for the moment but growing. Because of smartphones and inexpensive computing technology, datafication of the most essential acts of living has never been easier.

Twitter and flu shots—Marcel Salathé and Shashank Khandelwal, “Assessing Vaccination Sentiments with Online Social Media: Implications for Infectious Disease Dynamics and Control,” PLoS Computational Biology, October 2011. [>] IBM’s “smart floor” patent—Lydia Mai Do, Travis M. Grigsby, Pamela Ann Nesbitt, and Lisa Anne Seacat. “Securing premises using surfaced-based computing technology,” U.S. Patent number: 8138882. Issue date: March 20, 2012. The quantified-self movement—“Counting Every Moment,” The Economist, March 3, 2012. Apple earbuds for bio-measurements—Jesse Lee Dorogusker, Anthony Fadell, Donald J. Novotney, and Nicholas R Kalayjian, “Integrated Sensors for Tracking Performance Metrics,” U.S. Patent Application 20090287067. Assignee: Apple. Application Date: 2009-07-23. Publication Date: 2009-11-19. Derawi Biometrics, “Your Walk Is Your PIN-Code,” press release, February 21, 2011 (http://biometrics.derawi.com/?

See also correlation analysis; data analysis big data and, [>]–[>], [>], [>]–[>] Department of Homeland Security uses, [>] vs. free will, [>], [>], [>], [>]–[>] in health care, [>]–[>], [>] in insurance industry, [>]–[>] in Iraq War, [>] in mechanical & structural failure, [>], [>]–[>], [>], [>], [>] parole boards use, [>] police use, [>], [>]–[>], [>] in profiling, [>] punishment based on, [>], [>]–[>], [>], [>]–[>], [>], [>]–[>] in sports, [>]–[>], [>] by Target, [>]–[>] and terrorism, [>], [>]–[>], [>] by UPS, [>] predictive policing, [>] and crime prevention, [>]–[>] price-prediction: for consumer products, [>]–[>], [>] PriceStats, [>] printing press: socioeconomic effects of, [>], [>], [>]–[>] Prismatic: analyzes online media, [>]–[>] privacy: and anonymization, [>]–[>] and big data, [>]–[>], [>], [>], [>] and cell phone data, [>], [>] Google and, [>]–[>] and Internet, [>]–[>] laws protecting, [>], [>] and notice & consent, [>], [>], [>]–[>] Ohm on, [>] and opting out, [>], [>] and personal data, [>]–[>], [>]–[>], [>], [>], [>] profiling: and guilt by association, [>]–[>] predictive analytics in, [>] progress: as concept, [>]–[>] Project Gutenberg, [>] proxies: in correlation analysis, [>]–[>], [>], [>] Ptolemy: Geographia, [>] public health: reporting system limitations, [>]–[>] punch cards: Hollerith and, [>], [>] punishment: based on predictive analytics, [>], [>]–[>], [>], [>]–[>], [>], [>]–[>] quality control: statistical sampling in, [>] Quantcast, [>] quantification. See measurement “quantified self” movement, [>] quantum physics, [>] rabies vaccine: Pasteur and, [>]–[>] randomness: needed in statistical sampling, [>]–[>] real estate: regulation of illegal conversions, [>]–[>] reality mining, [>]–[>] record-keeping: in the ancient world, [>]–[>] Reuters, [>] Rigobon, Roberto, [>] Roadnet Technologies, [>] Rolls-Royce, [>] Roman numerals, [>]–[>] Rudin, Cynthia, [>], [>] Rudin, Ken, [>] sabermetrics, [>] Saddam Hussein: trial of, [>] Salathé, Marcel, [>]–[>] sales data: analysis of, [>], [>], [>], [>] Salesforce.com, [>] sampling, statistical: big data replaces, [>]–[>], [>], [>]–[>], [>]–[>] exactitude necessary in, [>], [>]–[>] Graunt and, [>] limitations inherent in, [>]–[>], [>], [>] Neyman on, [>] in quality control, [>] randomness needed in, [>]–[>] scale in, [>] Silver on, [>] scale: in data, [>]–[>] imprecision and, [>], [>], [>], [>], [>] qualitative functions of, [>], [>]–[>], [>], [>]–[>], [>]–[>] in statistical sampling, [>] scientific method: vs. correlation analysis, [>]–[>] Scott, James: Seeing Like a State, [>] search engines: and mathematical models, [>]–[>] search terms: analysis and reuse of, [>]–[>], [>], [>], [>], [>] Seeing Like a State (Scott), [>] Sense Networks, [>], [>] sentiment analysis, [>], [>]–[>], [>] Silver, Nate: on statistical sampling, [>] Skyhook, [>] Sloan Digital Sky Survey, [>] Smith, Adam, [>] social media: datafication by, [>]–[>] social networking analysis: Huberman and, [>] social sciences: data-gathering in, [>], [>] Society for American Baseball Research, [>] speech-recognition: at Google, [>]–[>] spell-checking systems: and data-reuse, [>]–[>] sports: predictive analytics in, [>]–[>], [>] Stasi, [>], [>], [>] statisticians: demand for, [>], [>] statistics: military use of, [>] stock market investment: datafication in, [>]–[>] subprime mortgage scandal (2009): correlation analysis and, [>] sumo wrestling: corruption in, [>]–[>], [>] Sunlight Foundation, [>] Super Crunchers (Ayres), [>] surveillance: by government, [>]–[>], [>]–[>] SWIFT: data-reuse by, [>] tagging: vs. categorization, [>]–[>] Taleb, Nassim Nicholas, [>] Target: predictive analytics by, [>]–[>] Telefonica Digital Insights, [>] Teradata, [>], [>], [>] terrorism: predictive analytics and, [>], [>]–[>], [>] text: correlation analysis of, [>]–[>] datafication of, [>], [>] The-Numbers.com: predicts Hollywood film profitability, [>]–[>] Thomson Reuters, [>] traffic-pattern analysis: by Inrix, [>]–[>], [>] translation, language, [>] Google and, [>]–[>], [>], [>], [>] IBM and, [>]–[>], [>] Microsoft and, [>] transparency: of algorithms, [>] truth: data as, [>], [>] imprecision and, [>] 23andMe, [>] Twitter, [>], [>], [>]–[>], [>] as big-data company, [>], [>]–[>] data processing by, [>] datafication by, [>]–[>] message analysis by, [>] Udacity, [>] Universal Transverse Mercator (UTM) system, [>] universe: information as basis of, [>]–[>] “Unreasonable Effectiveness of Data, The” (Norvig), [>] UPS: predictive analytics by, [>] uses geospatial location data, [>]–[>] UPS Logistics Technologies, [>] U.S.


pages: 25 words: 5,789

Data for the Public Good by Alex Howard

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23andMe, Atul Gawande, Cass Sunstein, cloud computing, crowdsourcing, Hernando de Soto, Internet of things, lifelogging, Network effects, openstreetmap, Silicon Valley, slashdot, social software, social web, web application

“As some put it, personal data will be the new ‘oil’ — a valuable resource of the 21st century. It will emerge as a new asset class touching all aspects of society.” 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.


pages: 51 words: 8,543

Dear Data by Giorgia Lupi, Stefanie Posavec, Maria Popova

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lifelogging, Menlo Park

Because of this, we are said to be living in the age of “Big Data”, where algorithms and computation are seen as the new keys to universal questions, and where a myriad of applications can detect, aggregate, and visualize our data for us to help us become these efficient super-humans. We prefer to approach data in a slower, more analogue way. We’ve always conceived Dear Data as a “personal documentary” rather than a quantified-self project which is a subtle – but important – distinction. Instead of using data just to become more efficient, we argue we can use data to become more humane and to connect with ourselves and others at a deeper level. We hope this book will inspire you in many ways: to draw (even if you don’t think of yourself as an artist), to slow down and appreciate the small details of your life, and to make connections with other people.


pages: 330 words: 88,445

The Rise of Superman: Decoding the Science of Ultimate Human Performance by Steven Kotler

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Albert Einstein, Any sufficiently advanced technology is indistinguishable from magic, Clayton Christensen, data acquisition, delayed gratification, deliberate practice, fear of failure, Google Earth, haute couture, impulse control, Isaac Newton, Jeff Bezos, jimmy wales, Kevin Kelly, Lao Tzu, life extension, lifelogging, Maui Hawaii, pattern recognition, Ray Kurzweil, risk tolerance, rolodex, selective serotonin reuptake inhibitor (SSRI), Silicon Valley, Steve Jobs, Walter Mischel, X Prize

But this is not the case with action and adventure sports athletes. Quite simply, the zone is the only reason these athletes are surviving the big-mountains, big waves, and big rivers. When you’re pushing the limits of ultimate human performance, the choice is stark: it’s flow or die. Ironically, this is very good news. Scientists have lately made enormous progress on flow. Advancements in brain-imaging technologies like fMRI and consumer “quantified self” devices like the Nike Fuel band allow us to apply serious metrics where once was merely subjective experience. Until now, there’s been no way to tie all this disparate information together, but recent events in action and adventure sports solve this problem. Knowing that survival demands flow gives us a hard data set with which to work. We don’t have to wonder if our research subjects are really in flow: if they live through the impossible, we can be certain.

“People no longer have to come to the lab, get tons of sensors attached, and destroy their normal routines. A football player on the flight home after a game; a businessman about to enter a meeting; a housewife with a half-hour before the kids come home. They just put on the headset and start training.” Concurrently, a revolution in sensors, batteries, and connectivity has led to a flood of “quantified self” devices such as Nike Fuel band, Jawbone’s UP, and the Basis Band. These wearable gadgets monitor an expansive array of biometrics, most of which can be used to hunt flow. And there are iPhone apps that do the same. We can now track cardiac coherence—when brain waves and heart waves synch up—which has been correlated with the state (but needs more research). Other apps let skiers and snowboarders calculate speed, helping them both dial in their challenge/skill ratio and pin down the exact miles per hour that trips their novelty and risk flow triggers.

Page felt otherwise: “We both went to Montessori schools, and I think it was part of that training of not following rules and orders, and being self-motivated, questioning what’s going on in the world, doing things a little bit differently.” they too found a Montessori connection: Jeffrey Dyer, Hal Gregersen, and Clayton Christensen, “The Innovator’s DNA,” Harvard Business Review, December 2009. 179 “Go back to Roger Bannister’s time”: Mike Gervais, AI, April 2013. 180 “The idea was to develop”: Leslie Sherlin, AI, February 2013. “quantified Self” devices: Lila Battis, “Fitness Trackers Compared!” Men’s Health. See: http://www.menshealth.com/techlust/new-fitness-trackers. 181 Hugh Herr, the head of the biomechatronics: Steven Kotler, “Bionic Man,” Playboy, June 2012. “anyone with a bum knee”: Ibid. 182 five times the speed of Moore’s Law: Peter Diamandis and Steven Kotler, Abundance: The Future Is Better Than You Think (Free Press, 2011). 183 meet Alex Honnold: Honnold quotes and details came from a series of interviews conducted by the author between March 2013 and July 2013.


pages: 138 words: 40,787

The Silent Intelligence: The Internet of Things by Daniel Kellmereit, Daniel Obodovski

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3D printing, Airbnb, Amazon Web Services, Any sufficiently advanced technology is indistinguishable from magic, autonomous vehicles, barriers to entry, business intelligence, call centre, Clayton Christensen, cloud computing, commoditize, connected car, crowdsourcing, data acquisition, en.wikipedia.org, Erik Brynjolfsson, first square of the chessboard, first square of the chessboard / second half of the chessboard, Freestyle chess, Google X / Alphabet X, Internet of things, lifelogging, Metcalfe’s law, Network effects, Paul Graham, Ray Kurzweil, RFID, Robert Metcalfe, self-driving car, Silicon Valley, smart cities, smart grid, software as a service, Steve Jobs, web application, Y Combinator, yield management

Imagine storing millions of data sets of patients or athletes who are hooked to devices with a large number of sensors, which are able to track movement, exercise, and sleep behavior. In the near future we will see more and more devices that are able to track not only basic data, but also vital signs. Also, real-time blood analysis will be possible due to super-thin sensors on the skin that transmit data to the cloud, where it will be analyzed. This development, which will be much more powerful than what we see today around the quantified self,33 will create a whole new health ecosystem in the near future. Imagine vending machines for drinks, snacks, or electronic devices in airports and other central locations becoming smart machines that will be able to track what people buy, where, and when. They will even be able to analyze who is standing in front of them and how long the buying decision takes. They will have large digital touchscreens that can run promotions at scheduled times, and they will be able to give exact data to the logistics firm to replenish products at the right time.

But at the end of the day, the best investment opportunities are going to be driven by very well-defined problems that the Internet of Things will help solve: increased visibility, increased productivity, reduced guesswork, better risk management, and better connection to our environment. 29 Paul Graham, “How to Get Startup Ideas,” November 2012. http://www.paulgraham.com/startupideas.html. 30 Iain Morris, “Intelligent Systems to Drive Value in M2M Market: IDC,” Telecom Engine, June 4, 2013. http://www.telecomengine.com/article/intelligent-systems-drive-value-m2m-market-idc. 31 Singularity University, “What Is Singularity University?” http://singularityu.org/overview/. 32 Wikipedia, “Metcalfe’s Law,” http://en.wikipedia.org/wiki/Metcalfe’s_law. 33 Quantified Self, “What We Are Reading,” http://quantifiedself.com/. 34 Department of Health and Human Services, “Food Labeling; Calorie Labeling of Articles of Food in Vending Machines; Proposed Rule,“ Federal Register, April 6, 2011. http://www.gpo.gov/fdsys/pkg/FR-2011-04-06/html/2011-8037.htm. 35 Just prior to publishing, Jawbone acquired BodyMedia for over $100 million. (Source: Lauren Goode, “Jawbone Acquires BodyMedia for More Than $100 Million, as Wearable Tech Gets More Intense,” All Things D. http://allthingsd.com/20130430/jawbone-acquires-bodymedia-for-more-than-100-million-as-wearable-tech-gets-more-intense/.) 36 Fabless manufacturing is the design and sale of hardware devices and semiconductor chips, while outsourcing the fabrication, or “fab” of the devices to a specialized manufacturer called a semiconductor foundry.


pages: 238 words: 68,914

Where Does It Hurt?: An Entrepreneur's Guide to Fixing Health Care by Jonathan Bush, Stephen Baker

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Affordable Care Act / Obamacare, Atul Gawande, barriers to entry, Clayton Christensen, commoditize, informal economy, inventory management, job automation, knowledge economy, lifelogging, obamacare, personalized medicine, ride hailing / ride sharing, Ronald Reagan, Silicon Valley, Steve Jobs, web application, women in the workforce, working poor

And once they know that number, won’t they lower rates for people who share monitoring data? I imagine someone will. And then what about the marathoners or swimmers who accumulate loads of biological data? Many start with a Fitbit or Jawbone wristband to track the miles run and calories burned. But then they see the possibility of measuring sleep, diet, anxiety—in short, participating in what’s called the “Quantified Self” movement. These people are hard at work attempting to optimize their health. Aren’t they likely to flock to doctors, and to insurance companies, that welcome this data and use it to give them better service and care? At the same time, as I mentioned earlier, different blends of data, including patient behavior, genetics, location, and weather, should enable researchers to study the effects of certain drugs and regimes in the wild.

See also wellness Preventive Medicine Research Institute, 119–20 prices, 2–4, 6–8, 64, 66, 149, 166 charged by hospitals, 29–30, 82–83, 90, 94, 96, 101 comparing of, 83, 85 customized, 208 disregard for, 15–16, 166 and fee for service, 71–72 fixed, 201 increase in, 6, 86, 88–89, 92 inflated, 10, 173 and the marketplace, 28–29 of medicines, 76 monopoly in, 136 reduction in, 16, 23, 68, 85, 92–93, 96, 198 transparency of, 94, 109 See also costs primary care, 10, 22, 84, 90–91, 103, 106, 108–9, 112, 117–18, 128 profits, 5, 20, 23, 25, 27, 76, 107, 143 and childbirth, 32–33, 36, 40–41, 55, 105–6, 123, 158 and chronically ill, 84–85, 118 of cooperatives, 125, 127 of doctors, 103, 105, 202–3 of entrepreneurs, 99–102, 105–6, 110, 121, 150, 195, 204–5 of hospitals, 6–8, 84–87, 89–90, 92–96, 106, 108–9, 114, 123, 167 and preventive health care, 119–21 “soft belly,” 36, 85, 106, 123 proton accelerator, 62–65, 77, 149 Purdue, George, 124–25 quality, of health care, 3, 6, 16, 41, 52, 62, 64, 66, 67, 74, 92, 107, 131, 162–63, 198 Quantified Self movement, 189 Radisphere, 161–63 Randazzo, John, 107–9 Reagan, Ronald, 17–18 RegisterPatient.com, 153–54 regulations, 25, 35, 60–62, 66, 68–69, 74–76, 101, 168, 180, 197–98, 204 Renaissance Health, 112, 117 research hospitals, 6–7, 9–10, 23, 83–84, 87, 89–91, 93–96, 99–101, 123, 131, 138, 146, 151 Reuters survey, 190 risk, 173–76, 180, 199–200, 208 risk contracts, 104, 120, 138, 201–3 Roosevelt Hospital, 87 Roth, David Lee, 184 Rugge, John, 122–24, 127–28, 132 Salesforce.com, 150 San Diego, California, 5, 9, 37–41, 44–45, 48–51, 53, 55, 57, 100, 105, 119, 124 Schnucks, 97 Schultz, Howard, 33 Schumer, Charles, 123 Schwartz, Bill, 37–38 Scripps Mercy Hospital, 40 self-insurance, 92, 114 Senior Bridge, 205–6 shopping, for health care, 4, 25, 31, 33, 64–65, 168 and choices, 10–12, 17, 85, 94–95, 186, 212 and doctors, 85, 93, 113, 202 and health care data, 67, 209 and health care quality, 166 and health insurance, 118, 172–73, 187, 199 and hospitals, 68, 83, 85, 94–95, 106, 138 importance of, 11–12, 212 and insurance companies, 51, 198 and procedure prices, 16, 68, 83, 85, 110, 166 Slingerland, Tucker, 125–26 Small Smart Medicine, 178–79 smart phones, 7, 140, 145–46, 152, 155, 176 social networks, 62, 67, 190, 211 software programs, 91, 120–21, 159–60 for appointments, 153–54 for billing, 5, 42–45, 47–50, 53–56, 136, 143, 158 companies of, 57–58, 60, 88, 135–47 for hospitals, 135–47, 156–57 and MUMPS, 141 for patient management, 158, 204 and primitive technology, 206 for scheduling, 171 systems of, 135–36, 150 See also specific companies specialists, 7, 30, 69, 83–84, 86, 90, 97, 106, 111, 118, 131–32, 160–63, 198.


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The End of Traffic and the Future of Transport: Second Edition by David Levinson, Kevin Krizek

2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 3D printing, American Society of Civil Engineers: Report Card, autonomous vehicles, barriers to entry, Bay Area Rapid Transit, big-box store, Chris Urmson, collaborative consumption, commoditize, crowdsourcing, DARPA: Urban Challenge, dematerialisation, Elon Musk, en.wikipedia.org, Google Hangouts, Induced demand, intermodal, invention of the printing press, jitney, John Markoff, labor-force participation, lifelogging, Lyft, means of production, megacity, Menlo Park, Network effects, Occam's razor, oil shock, place-making, Ray Kurzweil, rent-seeking, ride hailing / ride sharing, Robert Gordon, self-driving car, sharing economy, Silicon Valley, Skype, smart cities, technological singularity, Tesla Model S, the built environment, Thomas Kuhn: the structure of scientific revolutions, transaction costs, transportation-network company, Uber and Lyft, Uber for X, urban renewal, women in the workforce, working-age population, Yom Kippur War, zero-sum game, Zipcar

This information will prove useful not only for planning, but even for real-time operations and controls, identifying information that will feed algorithms that decide how to time traffic signal timings or dispatch additional buses. Apps which crowdsource vertical acceleration information and GPS locations from smartphone sensors are already useful for automatically providing agencies about road quality, like where is the latest pothole.209 At the personal level, The "Quantified Self" suggests that the outputs of many new sensors will be fed back to the individual traveler. Yingling Fan of the University of Minnesota suggests that information about travel can lead to behavioral interventions.210 She identifies three stages: awareness: informing the traveler of their environmental impacts, motivation: describing the benefits of change, and action: providing the tools to change behavior (e.g. making it easy to rent a bike or take transit).

Urban laboratories: Experiments in reworking cities. International Journal of Urban and Regional Research 38(2): 379-392. 208 Kitchin, Rob. 2013. The real-time city? Big data and smart urbanism. GeoJournal 79:1-14. 209 gov.uk (2013) Government backs smartphone app to pinpoint potholes https://www.gov.uk/government/news/government-backs-smartphone-app-to-pinpoint-potholes 210 Fan, Yingling (2016) Quantified Self and Quantified Networks (Chapter 5) in Levinson, David; Boies, Adam; Cao, Jason; Fan, Yingling. (2016). The Transportation Futures Project: Planning for Technology Change. Center for Transportation Studies, University of Minnesota. Retrieved from the University of Minnesota Digital Conservancy, http://hdl.handle.net/11299/177640. 211 This idea is also discussed in Enoch, Marcus (2015) How a rapid modal convergence into a universal automated taxi service could be the future for local passenger transport.


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The Digital Doctor: Hope, Hype, and Harm at the Dawn of Medicine’s Computer Age by Robert Wachter

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activist fund / activist shareholder / activist investor, Affordable Care Act / Obamacare, AI winter, Airbnb, Atul Gawande, Captain Sullenberger Hudson, Checklist Manifesto, Chuck Templeton: OpenTable, Clayton Christensen, collapse of Lehman Brothers, computer age, creative destruction, crowdsourcing, deskilling, en.wikipedia.org, Erik Brynjolfsson, everywhere but in the productivity statistics, Firefox, Frank Levy and Richard Murnane: The New Division of Labor, Google Glasses, Ignaz Semmelweis: hand washing, Internet of things, job satisfaction, Joseph Schumpeter, knowledge worker, lifelogging, medical malpractice, medical residency, Menlo Park, minimum viable product, natural language processing, Network effects, Nicholas Carr, obamacare, pattern recognition, peer-to-peer, personalized medicine, pets.com, Productivity paradox, Ralph Nader, RAND corporation, Second Machine Age, self-driving car, Silicon Valley, Silicon Valley startup, six sigma, Skype, Snapchat, software as a service, Steve Jobs, Steven Levy, the payments system, The Wisdom of Crowds, Thomas Bayes, Toyota Production System, Uber for X, US Airways Flight 1549, Watson beat the top human players on Jeopardy!, Yogi Berra

Creating sensors to measure a wide range of biological phenomena, like your stress level or the physiologic effects of certain drugs, was once a daunting engineering problem. But over the past five years, these challenges have been overcome through the development of gizmos ranging from the tiny accelerometers in your Fitbit or Jawbone to nanosensors that can be safely ingested. And, of course, the outputs of all these miraculous devices can now connect to our smartphones and to the Internet. This means that the so-called Quantified Self movement is shifting from a technical problem (how to capture the data) into an analytics question (how to make sense of the data). And this is where the hope butts up against the hype. The consulting firm Gartner defines big data as “high volume, high velocity, and/or high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery, and process optimization.”

For now, I see big data as a crucial area for research and development, one that is likely to bear fruit over time—particularly as EHRs become ubiquitous and somehow linked to patient-generated data from sensors and elsewhere, and as developers figure out how to integrate these tools with the habits and work flows of real people. A wise person once observed that we usually overestimate what can be done in a year and underestimate what can be done in a decade. To me, big data in healthcare meets that descriptor perfectly. If I am right, then, for the foreseeable future, the Quantified Self movement is likely to make its biggest mark among folks who have a bit too much time (and money) on their hands. Mark Smith recalled his experience as a member of the Qualcomm advisory board. Since the company specializes in providing—and profiting from—24/7 connectivity, there were many lively discussions about the value to consumers of minute-to-minute monitoring of things like blood sugar and heart rate.

See PHRs phantom memory, 163 PHRs, 189–193 microchips, 189–191 tethered personal health records, 185 See also EHRs physician unhappiness, 73–76 physician’s notes. See doctor’s notes Picture Archiving and Communication System. See PACS Plummer, Henry, 36 Polevoi, Steve, 77 POMR. See Problem-Oriented Medical Record privacy, 13–14 See also Health Insurance Portability and Accountability Act (HIPAA) Problem-Oriented Medical Record, 46, 79 productivity, 244 productivity paradox, 244–253 Quantified Self movement, 117, 122 radiologists alienation of, 56–58 busyness of, 58–59 economic pressures, 59–60 nighthawks, 60–61 replacement by computers, 61–62 resisting isolation, 62 radiology, 50 impact of PACS on, 53–56 teleradiology, 60–61 transition from film to computerized radiology, 51 RAND Corporation study of healthcare reform’s effects on doctor’s professional satisfaction, 73, 74 study on healthcare costs, 81, 247 rationing, 15 Reason, James, 131 regional health information exchanges (RHIOs), 187 Reider, Jacob, 211–212, 229–230 Reiser, Stanley, 30, 33, 41 relational coordination, 57 relationships, 77–78 demise of, 268 See also doctor-patient relationships Relman, Arnold “Bud”, 23–25 RHIOs.


pages: 479 words: 144,453

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

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

Microsoft has launched the Microsoft Band in November 2014 – a smart armband that monitors among other things your heartbeat, the quality of your sleep and the number of steps you take each day. An application called Deadline goes a step further, telling you how many years of life you have left, given your current habits. Some people use these apps without thinking too deeply about it, but for others this is already an ideology, if not a religion. The Quantified Self movement argues that the self is nothing but mathematical patterns. These patterns are so complex that the human mind has no chance of understanding them. So if you wish to obey the old adage and know thyself, you should not waste your time on philosophy, meditation or psychoanalysis, but rather you should systematically collect biometric data and allow algorithms to analyse them for you and tell you who you are and what you should do.

Martha Mendoza, ‘Google Develops Contact Lens Glucose Monitor’, Yahoo News, 17 January 2014, accessed 12 August 2015, http://news.yahoo.com/google-develops-contact-lens-glucose-monitor-000147894.html; Mark Scott, ‘Novartis Joins with Google to Develop Contact Lens That Monitors Blood Sugar’, New York Times, 15 July 2014, accessed 12 August 2015, http://www.nytimes.com/2014/07/16/business/international/novartis-joins-with-google-to-develop-contact-lens-to-monitor-blood-sugar.html?_r=0; Rachel Barclay, ‘Google Scientists Create Contact Lens to Measure Blood Sugar Level in Tears’, Healthline, 23 January 2014, accessed 12 August 2015, http://www.healthline.com/health-news/diabetes-google-develops-glucose-monitoring-contact-lens-012314. 25. Quantified Self, http://quantifiedself.com/; Dormehl, The Formula, 11–16. 26. Dormehl, The Formula, 91–5; Bedpost, http://bedposted.com. 27. Dormehl, The Formula, 53–9. 28. Angelina Jolie, ‘My Medical Choice’, New York Times, 14 May 2013, accessed 22 December 2014, http://www.nytimes.com/2013/05/14/opinion/my-medical-choice.html. 29. ‘Google Flu Trends’, http://www.google.org/flutrends/about/how.html; Jeremy Ginsberg et al., ‘Detecting Influenza Epidemics Using Search Engine Query Data’, Nature 457:7232 (2008), 1012–14; Declan Butler, ‘When Google Got Flu Wrong’, Nature, 13 February 2013, accessed 22 December 2014, http://www.nature.com/news/when-google-got-flu-wrong-1.12413; Miguel Helft, ‘Google Uses Searches to Track Flu’s Spread’, New York Times, 11 November 2008, accessed 22 December 2014, http://msl1.mit.edu/furdlog/docs/nytimes/2008-11-11_nytimes_google_influenza.pdf; Samantha Cook et al., ‘Assessing Google Flu Trends Performance in the United States during the 2009 Influenza Virus A (H1N1) Pandemic’, PLOS ONE, 19 August 2011, accessed 22 December 2014, http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0023610; Jeffrey Shaman et al., ‘Real-Time Influenza Forecasts during the 2012–2013 Season’, Nature, 23 April 2013, accessed 24 December 2014, http://www.nature.com/ncomms/2013/131203/ncomms3837/full/ncomms3837.html. 30.

(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?’


pages: 348 words: 39,850

Data Scientists at Work by Sebastian Gutierrez

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Albert Einstein, algorithmic trading, Bayesian statistics, bioinformatics, bitcoin, business intelligence, chief data officer, clean water, cloud computing, commoditize, computer vision, continuous integration, correlation does not imply causation, creative destruction, crowdsourcing, data is the new oil, DevOps, domain-specific language, Donald Knuth, follow your passion, full text search, informal economy, information retrieval, Infrastructure as a Service, Intergovernmental Panel on Climate Change (IPCC), inventory management, iterative process, lifelogging, linked data, Mark Zuckerberg, microbiome, Moneyball by Michael Lewis explains big data, move fast and break things, move fast and break things, natural language processing, Network effects, nuclear winter, optical character recognition, pattern recognition, Paul Graham, personalized medicine, Peter Thiel, pre–internet, quantitative hedge fund, quantitative trading / quantitative finance, recommendation engine, Renaissance Technologies, Richard Feynman, Richard Feynman, self-driving car, side project, Silicon Valley, Skype, software as a service, speech recognition, statistical model, Steve Jobs, stochastic process, technology bubble, text mining, the scientific method, web application

So I’m dating a great person now and I don’t think that would have been possible had I not had this epiphany that the data shows that some people do in fact like me. www.it-ebooks.info Data Scientists at Work The dating spreadsheet has become somewhat of a joke now, but it actually really helped. Everyone talks about “quantified self” and everyone wants to track themselves. But no one’s writing down a lot of the interpersonal interactions that actually matter—who cares about how many steps you took last week, who did you kiss? So I think the dating spreadsheet is a good argument for the quantified-self approach in this kind of data. Gutierrez: What does the future of data science or computational neurobiology look like? Jonas: I know that everyone wants to talk about big data. It’s now this phrase that has somehow entered the lexicon in a horrible sort of way.

I see some exciting developments in the present—a growing awareness of the value of data-driven decision making, and recognition of the critical role that data plays in product development. I’m optimistic that this trend will continue, and data will have the primary role it deserves in organizations. What does the future hold? Certainly we’re seeing new sources of data as wearable computing goes mainstream. Only a few years ago, the Quantified Self movement seemed like a futurist fringe. Now, it’s well on its way to being a billion-dollar market. Hopefully, we’ll see the results in a more data-driven approach to healthcare. More broadly, I hope that anyone working on a hard problem will be in a better position to find the data that can help solve it. Gutierrez: How do you think the data science workflow will change? Tunkelang: Today, expertise with big data tools is still fairly specialized.

Watson Research Center, 83 implementers, 100 information retrieval, 92 in-house reporting tools, 97 intellectual omnivore, 94 intuition and experience, 98 knowledge graph, 88 LinkedIn’s professional content, 85 local business search, 91 machine learning, 90–91 metrics, 91 morgue, 98 new approach, 90 non–cutting-edge models, 90 offline analysis, 96 online testing, 96 open-source framework, 87 open source technology, 89 optimistic assumptions, 99 personalization, 89 personal philosophy, 105 portfolio management, 96 presearch processing, 87 probability and statistics, 103 problem solving, 101 www.it-ebooks.info 345 346 Index Tunkelang, Daniel (cont.) product data science team, 83, 85 product sense, 100 professional aspirations, 101 professional network, 95 project’s life cycle, 98 Quantified Self movement, 104 query understanding, 86 real-time feeds, 95 recommendations, 94 recommender systems, 92 relevance, 94 reputation, 94 resources, 95 Reuters news corpus, 93 richer model, 97 search evaluation, 88 search relevance, 86, 89 simple models, 99 skepticism, 100 smallish number of people, 105 software skills, 103 systematic bias and overfitting, 92 technology experience, 101 technology selection, 100 terminology extraction algorithms, 93 theoretical contributions, 105 things-not-strings, 87 transient state, 104 two-sided relevance search approach, 88 wearable devices, 95 web-scale data, 103 web search queries, 91 written production code, 96 TweetDeck, 131 U,V United Nations Global Pulse, 319 Wiggins, Chris academic canon, 15 Associate Professor of Applied Mathematics, 1 background, 2 biggest thing, 12 Breiman, Leo, 17 Chaos: Making a New Science, 14 Compendium of Theoretical Physics, 15 computational social science, 9 Courant Instructor, 1 creativity and caring, 12 data product, 13 data science, 2 Exploratory Data Analysis, 15 founding member, IDSE, 1 hackNY, 1, 6, 10 Hansen, Mark (friend and colleague), 11 Hofman, Jake, 10 interesting project, 8 junior people, 7 Madigan, David (former chair of stats), 11 marketing mechanism, 7 Matt Jones (colleague), 14 model testing, 8 MOOC, 6 NIPS, 5 NYT, 1 orthogonal value system, 12 Riemannian geometry, 6 school life, 4 stochastic gradient, 16 stochastic optimization, 16 subscriber behavior, 11 tools or techniques, 6 Visual Display of Quantitative Information, 15 Wheeler, John Archibald (theoretical physicist), 7 University of Michigan School of Information (UMSI), 148 Wikipedia, 12, 264, 282–283 Unsupervised learning, 61 World Bank, 269, 319, 321 W, X Y, Z Walmart, 192, 194, 311 Yankees, 259–261 www.it-ebooks.info Data Scientists at Work Sebastian Gutierrez www.it-ebooks.info Data Scientists at Work Copyright © 2014 by Sebastian Gutierrez This work is subject to copyright.


pages: 347 words: 97,721

Only Humans Need Apply: Winners and Losers in the Age of Smart Machines by Thomas H. Davenport, Julia Kirby

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AI winter, Andy Kessler, artificial general intelligence, asset allocation, Automated Insights, autonomous vehicles, basic income, Baxter: Rethink Robotics, business intelligence, business process, call centre, carbon-based life, Clayton Christensen, clockwork universe, commoditize, conceptual framework, dark matter, David Brooks, deliberate practice, deskilling, digital map, Douglas Engelbart, Edward Lloyd's coffeehouse, Elon Musk, Erik Brynjolfsson, estate planning, fixed income, follow your passion, Frank Levy and Richard Murnane: The New Division of Labor, Freestyle chess, game design, general-purpose programming language, Google Glasses, Hans Lippershey, haute cuisine, income inequality, index fund, industrial robot, information retrieval, intermodal, Internet of things, inventory management, Isaac Newton, job automation, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Khan Academy, knowledge worker, labor-force participation, lifelogging, loss aversion, Mark Zuckerberg, Narrative Science, natural language processing, Norbert Wiener, nuclear winter, pattern recognition, performance metric, Peter Thiel, precariat, quantitative trading / quantitative finance, Ray Kurzweil, Richard Feynman, Richard Feynman, risk tolerance, Robert Shiller, Robert Shiller, Rodney Brooks, Second Machine Age, self-driving car, Silicon Valley, six sigma, Skype, speech recognition, spinning jenny, statistical model, Stephen Hawking, Steve Jobs, Steve Wozniak, strong AI, superintelligent machines, supply-chain management, transaction costs, Tyler Cowen: Great Stagnation, Watson beat the top human players on Jeopardy!, Works Progress Administration, Zipcar

No doubt most of these attorneys see their greater salvation in the escape from drudgery. A last form of augmentation, also a kind of leverage, is the smart machine that helps you become a better version of yourself. Consider the new class of devices that have recently exploded on the consumer market that allow you to set personal goals and capture the progress you are making toward them. As part of what is known as the “quantified self” movement, they create feedback loops to tell you how you are doing on the (often nonwork) objectives that matter to you—whether you’re training for a marathon, trying to stay mentally sharp, or doing therapy to recover from some setback. In a way, this kind of leverage works not by erecting supports but by countering some of the regrettable tendencies of your human self, such as a lack of willpower or self-discipline.

., 179 Persado, 121 personal shoppers, 111 Pink, Daniel, 169 Plett, Heather, 110–11 Popa, Dan, 123 Port, David, 87 precariat, 241 Predictably Irrational (Ariely), 113 Press, Gil, 191 productivity automation and gains, 1, 3, 167, 227 BYOD and, 13 knowledge workers and, 100 man-machine partnerships and, 234 price reductions and, 14 “silent firing” and, 24 Progressive insurance, 197 “Prose of the Machines, The” (Oremus), 127 ProSystem, 22 “quantified self” movement, 68 Race Against the Machine, 31 RAGE Frameworks, 45, 216–17 Reimsbach-Kounatze, Christian, 236 Rethink Robotics, 50, 182, 193 Rhodin, Mike, 55 Riedl, Mark, 126 Riordan, Staci Jennifer, 160 Rise of the Robots (Ford), 205 Risi, Karin, 210, 220, 223 Ritchie, Graeme, 125 Robinson, Sir Ken, 115 robotic process automation, 48–49, 187, 221, 222–23 robotics, 24, 35, 40, 49–52, 54, 157 anthropomorphizing and, 49 collaborative robots, 49–51, 182, 193 DARPA Robotics Challenge, 51, 56 education for, 232 patience and, 123–24 programming language, 49, 50 self-awareness and, 56 transparency and ease of use, 193 warnings and predictions about, 225–26 Ronanki, Rajeev, 187–89, 220 Roosevelt, Franklin D., 238, 248 Rudin, Cynthia, 193 Rumsfeld, Donald, 214 Russell, Stuart, 227–28 Sachs, Jeffrey, 228 Sadler-Smith, Eugene, 117–18 Safecast, 247 Saffo, Paul, 24 Salovey, Peter, 113, 116 Samasource, 168 Sand, Benjamin, 6 SAP, 133 SAS, 104, 132, 140, 141, 194 Saxena, Manoj, 45 Schneider National, 132, 147–48, 189–90, 196 Short Haul Optimizer, 147, 190, 191 Scientific Music Generator (SMUG), 126 “School of One,” 141 Science: The Endless Frontier (Bush), 248 Scott, David, 67 Scott, Rebecca, 162 Second Machine Age, The (Brynjolfsson and McAfee), 6, 74 self-driving vehicles, 4, 51–52, 213–14, 244, 246 Sharp, Phillip, 209 Shaughnessy, Dan, 117 Shiller, Robert, 7 Simon, Herbert, 163 Singapore, 250 Singularity Is Near, The (Kurzweil), 36 Skype Translator, 56 smartphones, 53, 235, 239 “social license to operate,” 233 Spanish National Research Council, 54–55 Spielberg, Steven, 125 spreadsheets, 69–70 Standing, Guy, 241 Starner, Thad, 65 Stats Inc., 97 Steinberg, Dan, 124–25 Stepping Aside, 77 artisanal jobs, 119–21 augmentation to free people up, 121–24 characteristics of a candidate, 129 for financial planners and brokers, 87 how to build skills for, 129–30 incursion of machines into human attributes, 124–27 in insurance underwriting, 81 jobs with nonprogrammable skills, 109–12 learning “noncognitive” skills, 115–18 multiple intelligences and, 112–14 for teachers, 85 value of human involvement, 127–28 what it means, 108 where a candidate is likely found, 130 Stepping Forward, 77, 176–200 adding new sources of data, 196–97 broadening application of tools, 194–95 broadening the base of methods, 194 characteristics of a candidate, 199–200 consultants, 187–89 creating usability and transparency by business users, 192–94 data scientists, 179–80 embedding automation functions, 196 entrepreneurs, 185–87 examples, successful people, 179–89 for financial planners and brokers, 88 focusing on behavioral finance and economics, 198–99 how to build skills for, 200 in insurance underwriting, 83–84 internal automation leaders, 189–91 jobs, technical and nontechnical, 177–91 marketers, 183–85 number of jobs, 191–92 product managers, 182–83 programmers and IT professionals, 178 reporting and showing results, 195–96 researchers, 181–82 for teachers, 85–86 what it is, 176 where a candidate is likely found, 200 working on the math, 197–98 Stepping In, 77, 131–52 automation technologies and, 134–35 bright future for, 149–51 characteristics of a candidate, 151–52 common attributes of, 145–49 examples, successful people, 132, 134–35, 137–48 for financial planners and brokers, 97 having an aptitude for, 142–45 how to build skills for, 152 in insurance underwriting, 81–82 predecessors of, 132–34 purple people, 131, 133–34, 135, 147, 151 for teachers, 85 value provided by, 138–42 what it is, 131–32 what candidates are and aren’t, 135–38 where a candidate is likely found, 152 working with vendors and, 140–41 Stepping Narrowly, 77, 153–75 achieving mastery and, 162–66 augmentation and, 166–69, 173–74 building on your narrowness, 161–62 characteristics of a candidate, 174 education for, 232 examples, successful people, 153–54, 159–60, 162, 163, 164, 170, 172–73 for financial planners and brokers, 87–88 finding a specialty, 158–61 “hedgehog” thinker and, 171 how to build skills for, 175 individual psychology and, 169–71 in insurance underwriting, 82 “long tail” and, 157, 162 machine-unfriendly economics and, 155–58, 162 in medicine, 157 niche business, 153–54, 171–73 for teachers, 85 where a candidate is likely found, 175 Stepping Up, 76–77, 89–107, 155 automation decisions and, 93–95 big-picture perspective, 98–100 building and ecosystem, 100–102 careful work design for automated business functions, 103–4 characteristics of a candidate, 106 creating a balance between computer-based and human skills, 105–6 examples, successful people, 89–91, 95–98 for financial planners and brokers, 86–87 in financial sector, 92–93 how to build skills for, 106–7 in insurance underwriting, 80 in marketing, 93 staying close, but moving on and, 102–3 for teachers, 84–85 what it is, 91–93 where a candidate is likely found, 107 Stewart, Martha, 111 Summers, Larry, 95, 227 Suncor, 205 Surrogates (film), 125 Sutton, Bob, 170–71 Sweetwood, Adele, 104 taste, augmentation and, 122 TaxCut, 22 tax preparation, 22, 67–68 Tegmark, Max, 243–44, 247 Telefónica’s O2, 49 Teradata, 43 Terminator films, 65 Tesla, 213, 246 Thiel, Peter, 243 Thinking, Fast and Slow (Kahneman), 236 Thinking for a Living (Davenport), 5 This, Herve, 164 Thompson, Derek, 242 Tibco, 194 Time magazine, AI cover and article, 36 TopCoder, 168 Torrence, Travis, 132, 147–48, 189, 190 Tourville, Lisa, 83–84, 137 TurboTax, 22, 67–68 “12 Risks That Threaten Human Civilization” (Armstrong), 249 2001: A Space Odyssey (film), 76, 245 Udacity, 178 UltraTax, 22 UnitedHealthCare, 83 University of California, Berkeley, 51 University of Michigan’s Institute for Social Research, 115 “Unusual and Highly Specialized Practice Areas” (Bohrer), 159 UPS automated driver routing algorithm (ORION), 196 USAA, 87–88 U.S.


pages: 100 words: 28,911

A Short Guide to a Long Life by David B. Agus

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Danny Hillis, Ignaz Semmelweis: hand washing, lifelogging, meta analysis, meta-analysis, Murray Gell-Mann, personalized medicine, placebo effect, risk tolerance, the scientific method

If you really want to take Rule 1 to the maximum, then consider measuring yourself a bit more formally with the help of nifty devices. In 2007, a couple of brainy Wired editors saw this coming: the day when we’d be able to track ourselves digitally as Sanctorius of Padua did manually when he weighed everything that came in and out of his body over a period of thirty years in the sixteenth and seventeenth centuries. The Wired editors coined the term the “quantified self,” and this kind of effort has already become a movement. Even if you don’t subscribe to the idea of wearing a piece of Star Treky equipment, most of us keep mental track of certain things in our lives such as weight, sleep quality, and activity level—if just to make sure we’re within the parameters we’d like to follow. But seriously, you might want to consider adding a tracking app or device of some kind to your life.


pages: 677 words: 206,548

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

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23andMe, 3D printing, active measures, additive manufacturing, Affordable Care Act / Obamacare, Airbnb, airport security, Albert Einstein, algorithmic trading, artificial general intelligence, Asilomar, Asilomar Conference on Recombinant DNA, augmented reality, autonomous vehicles, Baxter: Rethink Robotics, Bill Joy: nanobots, bitcoin, Black Swan, blockchain, borderless world, Brian Krebs, business process, butterfly effect, call centre, Chelsea Manning, cloud computing, cognitive dissonance, computer vision, connected car, corporate governance, crowdsourcing, cryptocurrency, data acquisition, data is the new oil, Dean Kamen, disintermediation, don't be evil, double helix, Downton Abbey, drone strike, Edward Snowden, Elon Musk, Erik Brynjolfsson, Filter Bubble, Firefox, Flash crash, future of work, game design, Google Chrome, Google Earth, Google Glasses, Gordon Gekko, high net worth, High speed trading, hive mind, Howard Rheingold, hypertext link, illegal immigration, impulse control, industrial robot, Intergovernmental Panel on Climate Change (IPCC), Internet of things, Jaron Lanier, Jeff Bezos, job automation, John Harrison: Longitude, John Markoff, Jony Ive, Julian Assange, Kevin Kelly, Khan Academy, Kickstarter, knowledge worker, Kuwabatake Sanjuro: assassination market, Law of Accelerating Returns, Lean Startup, license plate recognition, lifelogging, litecoin, M-Pesa, Mark Zuckerberg, Marshall McLuhan, Menlo Park, Metcalfe’s law, mobile money, more computing power than Apollo, move fast and break things, move fast and break things, Nate Silver, national security letter, natural language processing, obamacare, Occupy movement, Oculus Rift, off grid, offshore financial centre, optical character recognition, Parag Khanna, pattern recognition, peer-to-peer, personalized medicine, Peter H. Diamandis: Planetary Resources, Peter Thiel, pre–internet, RAND corporation, ransomware, Ray Kurzweil, refrigerator car, RFID, ride hailing / ride sharing, Rodney Brooks, Satoshi Nakamoto, Second Machine Age, security theater, self-driving car, shareholder value, Silicon Valley, Silicon Valley startup, Skype, smart cities, smart grid, smart meter, Snapchat, social graph, software as a service, speech recognition, stealth mode startup, Stephen Hawking, Steve Jobs, Steve Wozniak, strong AI, Stuxnet, supply-chain management, technological singularity, telepresence, telepresence robot, Tesla Model S, The Future of Employment, The Wisdom of Crowds, Tim Cook: Apple, trade route, uranium enrichment, Wall-E, Watson beat the top human players on Jeopardy!, Wave and Pay, We are Anonymous. We are Legion, web application, Westphalian system, WikiLeaks, Y Combinator, zero day

Whether it be heavy metal music or threatening voices that the person wearing the device alone could hear, these noises are sure to cause annoyance and consternation on the part of those affected. Hearing aids have now been joined by a panoply of additional choices when it comes to the sensors, trackers, and computers available to be worn on our bodies today. Many of these developments have been driven by the “quantified self” movement, which employs a variety of methodologies for collecting data about an individual’s life using technological tools. Every day, millions of quantified-self adherents record every aspect of their lives, thoughts, and experiences via self-tracking tools in search of a better life through “life logging.” They track and measure their sleep, weight, calories burned, biofeedback, heart rate, brain waves, EKG rhythms, happiness, number of steps in a day, all in an effort to improve mental and physical performance, easily gathered through the introduction of wearable-computing devices known as wearables.

Chapter 14: Hacking You 1 “We Are All Cyborgs Now”: Amber Case, “We Are All Cyborgs Now,” TED Talk, Dec. 2010. 2 Over 90 percent: “Text Message/Mobile Marketing,” WebWorld2000, http://​www.​webworld2000.​com/. 3 Over 100 million: Marcelo Ballve, “Wearable Gadgets Are Still Not Getting the Attention They Deserve—Here’s Why They Will Create a Massive New Market,” Business Insider, Aug. 29, 2013. 4 Most wearable devices: “How Safe Is Your Quantified Self? Tracking, Monitoring, and Wearable Tech,” Symantec Security Response, July 30, 2014. 5 Google has already: “Google Partners with Ray-Ban, Oakley for New Glass Designs,” NBC News, March 24, 2014; Deloitte, Technology, Media, and Telecommunications Predictions, 2014, 10. 6 The fear of filming: Richard Gray, “The Places Where Google Glass Is Banned,” Telegraph, Dec. 4, 2013. 7 In fact, hackers had already: Andy Greenberg, “Google Glass Has Already Been Hacked by Jailbreakers,” Forbes, April 26, 2013. 8 The GPS features: Mark Prigg, “Google Glass HACKED to Transmit Everything You See and Hear: Experts Warn ‘the Only Thing It Doesn’t Know Are Your Thoughts,’ ” Mail Online, May 2, 2013. 9 While your grandma: John Zorabedian, “Spyware App Turns the Privacy Tables on Google Glass Wearers,” Naked Security, March 25, 2014. 10 Given the pace: Katherine Bourzac, “Contact Lens Computer: Like Google Glass, Without the Glasses,” MIT Technology Review, June 7, 2013. 11 The device is in early stages: Leo King, “Google Smart Contact Lens Focuses on Healthcare Billions,” Forbes, July 15, 2014. 12 Not to be outdone: Bourzac, “Contact Lens Computer.” 13 The historic operation: N.


pages: 405 words: 117,219

In Our Own Image: Savior or Destroyer? The History and Future of Artificial Intelligence by George Zarkadakis

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3D printing, Ada Lovelace, agricultural Revolution, Airbnb, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, anthropic principle, Asperger Syndrome, autonomous vehicles, barriers to entry, battle of ideas, Berlin Wall, bioinformatics, British Empire, business process, carbon-based life, cellular automata, Claude Shannon: information theory, combinatorial explosion, complexity theory, continuous integration, Conway's Game of Life, cosmological principle, dark matter, dematerialisation, double helix, Douglas Hofstadter, Edward Snowden, epigenetics, Flash crash, Google Glasses, Gödel, Escher, Bach, income inequality, index card, industrial robot, Internet of things, invention of agriculture, invention of the steam engine, invisible hand, Isaac Newton, Jacquard loom, Jacquard loom, Jacques de Vaucanson, James Watt: steam engine, job automation, John von Neumann, Joseph-Marie Jacquard, liberal capitalism, lifelogging, millennium bug, Moravec's paradox, natural language processing, Norbert Wiener, off grid, On the Economy of Machinery and Manufactures, packet switching, pattern recognition, Paul Erdős, post-industrial society, prediction markets, Ray Kurzweil, Rodney Brooks, Second Machine Age, self-driving car, Silicon Valley, speech recognition, stem cell, Stephen Hawking, Steven Pinker, strong AI, technological singularity, The Coming Technological Singularity, The Future of Employment, the scientific method, theory of mind, Turing complete, Turing machine, Turing test, Tyler Cowen: Great Stagnation, Vernor Vinge, Von Neumann architecture, Watson beat the top human players on Jeopardy!, Y2K

In 2002, British scientist Kevin Warwick, presaging Google Glass somewhat gruesomely, had a hundred electrodes surgically implanted in the median nerve fibres of his left arm. Using the electrodes, he connected his nervous system to the Internet and thereby controlled a host of electrical devices including a robotic arm, a loudspeaker and an amplifier. Meanwhile, a global movement calling itself ‘Quantified Self’ promotes the idea of measuring everything about our body, behaviour and outcomes, and use these measurements as feedback signals for self-improvement. In 2014, Apple unveiled the Watch, which is likely to evolve into a wearable device supporting a quantified lifestyle. Could all such innovations be harbingers of our next evolutionary step? Are we destined to fuse with our computing machines and become absorbed into a collective superorganism of information, like the Borg’s Hive?

A. 61–2, 68 Hofstadter, Douglas 186–8 Hohlenstein Stadel lion-man statuette 3–5, 19–20 holistic approach to knowledge 174–5 holistic scientific methods 41–2 Holocene period 10 Holy Scripture, authority of 113–14 homeostasis 173 Homo erectus 6–7, 8, 10 Homo habilis 6, 12 Homo heidelbergensis 7 Homo sapiens archaic species 7, 8, 10 emergence of modern humans 8 Homo neanderthalensis (Neanderthals) 4, 7–8, 9–10 Homo sapiens sapiens 9–10 human ancestors aesthetic practices 9 archaic Homo sapiens 7, 8, 10 arrival in Europe 3–5 australopithecines 5, 6, 22 changes in the Upper Palaeolithic Age 9–10, 11 common ancestor with chimpanzees 5 emergence of art in Europe 3–5 emergence of modern humans 8 exodus from Africa 3–4, 6–7, 8–9 Homo erectus 6–7, 8, 10 Homo habilis 6, 12 Homo heidelbergensis 7 Homo sapiens 7, 8, 10 Homo sapiens sapiens 9–10 in Africa 5–7 Neanderthals (Homo neanderthalensis) 4, 7–8, 9–10 Human Brain Project (HBP) xiv–xvi, 164–5, 287 see also brain (human) human culture, approaches to understanding 74–9 human replicas, disturbing feelings caused by 66–73 humanity becoming like machines (cyborgs) 79–85 future of 304–17 Hume, David 139–40 humors theory of life 31–4 humour, and theory of mind 54 Humphrey, Nicholas 11 hunter-gatherer view of the natural world 20–2 hydraulic and pneumatic automata 32–6 IBM (International Business Machines) 230, 263, 264 Ice Age Europe 4, 10, 21–2 iconoclasm 67 idealism versus materialism 92–4 identity theory 144–5 imagined world of the spirits 22–3, 25, 27 inanimate objects, projection of theory of mind 15–18 Incompleteness Theorem (Gödel) 180, 186, 206–9, 211–16 inductive logic 196, 197 information disembodiment of 146–52 significance of context 151–2 the mind as 123–5 information age 232–4 information theory 147–52 Ingold, Tim 20 intelligence, definitions of 48–9, 52 intelligent machines as objects of love 48–59 Internet brain metaphor 43 collection and manipulation of users’ data 250–3 origins of 238 potential for sentience 214–15 Internet of things 251–3 intuition 200, 211 Iron Man (film) 82 Ishiguro, Hiroshi 72 Islam 102 Jacquard loom 225 James, William 162 Johnson, Samuel 140 Kasparov, Garry 263 Kauffman, Stuart 295 Kempelen, Wolfgang von 37 Kline, Nathan 79 Koch, Christof 167–8 Krauss, Lawrence 244–5 Krugman, Paul 269 Kubrick, Stanley 56, 257 Kuhn, Thomas 29, 75 Kurzweil, Ray 126, 270–1 Lang, Fritz 50 language and genesis of the modern mind 13–15 and human relationship with objects 15–18 evolution of 13–15 naming of objects 16–17 LeCun, Yann 255 Leibniz, Gottfried Wilhelm 116–17, 218–20 Lettvin, Jerry 293 liberty, end of 313–17 life algorithms of 292–6 origins of 181–3 Life in the Bush of Ghosts (Tutuola) 19 linguistics, descriptions of reality 75 lion-man statuette of Stadel cave 3–5, 19–20 Llull, Ramon (Doctor Illuminatus) 218 Locke, John 139 locked-in syndrome 307 logic x–xi, 195–202 logical substitution method 180, 183, 186 Lokapannatti (early Buddhist story) 34 London forces 107 love conscious artefacts as objects of 48–59 human need for 55–6 human relationships with androids 53–9 Lovelace, Ada 62, 226–7, 228 Luddites 268 Machine Intelligence Research Institute 58–9 machine metaphor for life 36–8 Magdalenian period 21 magnetoencephalography (MEG) 159–60, 161 Maillardet, Henri 218 Marconi, Guglielmo 239 Maria (robot in Metropolis) 50, 51 Marlowe, Christopher 63 Mars colonisation 291 Marx, Groucho 205 materialism versus idealism 92–4 mathematical dematerialisation view 92 mathematical foundations of the universe 103–6 mathematical reflexivity 186–7 mathematics 31 formal logical systems 200–11 views on the nature of 136 Maturana, Humberto 294 McCarthy, John 256, 307 McCorduck, Pamela 45, 67 McCulloch, Warren S. 36, 175, 176–8, 256, 293 Mead, Margaret 175 mechanical metaphor for life 36–8 mechanical Turk 37 medicine, development of 31–2 meditation 157 memristors 286–7 Menabrea, Luigi 226, 227 Mesmer, Franz Anton 40 mesmerism 40 Mesopotamian civilisations 30 metacognition 184 metamathematics 202, 205, 207 metaphors confusing with the actual 44–5 for life and the mind 28–47 in general-purpose language 75 misunderstanding caused by 308–13 Metropolis (1927 film) 50, 51 Middle Palaeolithic 6 Miller, George 154, 155 Milton, John 1 mind altered states 110, 111 as pure information 123–5 aspects of 85–7 debate over the nature of 91–4 disembodiment of 42 empirical approach 143–6 quantum hypothesis 106–9 scientific theory of 152–3 search for a definition 189–91 self-awareness 86–7 separate from the body 110–15 view of Aristotole 137–8 mind-body problem 32, 114–19, 129–31 Minsky, Marvin 178, 256 modern mind big bang of 10, 12–15 birth of 10–15 impacts of the evolution of language 13–15 monads 117, 119 monism versus dualism 92–3 Moore’s Law 244–5, 263, 270–1, 287 moral decision-making 277–8 Moravec paradox 275–6 Morris, Ian 222 Morse, Samuel 42 mud metaphor for life 29–31, 45 My Life in the Bush of Ghosts (music album) 19 Nabokov, Vladimir 167 Nagel, Thomas 120, 121 Nariokotome boy 7 narratives 18–27, 75 see also metaphor Neanderthals (Homo neanderthalensis) 4, 7–8, 9–10 Negroponte, Nicholas 243–4 neopositivism 141 neural machines 282–7 neural networks theory 36 neural synapses, functioning of 117–19 neuristors 286–7 neurodegenerative diseases xiii–xiv, 163–4 Neuromancer (Gibson) 36 neuromorphic computer archtectures 286–7 neurons, McCulloch and Pitts model 177–8 neuroscience 158, 306–8 Newton, Isaac 38, 103 Nike’s Fuel Band 81 noetic machines (Darwins) 284 nootropic drugs 81 Nouvelle AI concept 288 Offray de La Mettrie, Julien 37 Ogawa, Seiji 158–9 Omo industrial complex 6 On the Origin of Species (Darwin) 289–90 ‘ontogeny recapitulates phylogeny’ concept 10 Otlet, Paul 239–40 out-of-body experiences 110–11 Ovid 49, 64 Paley, William 289 panpsychism 92, 117, 252 paradigm shifts 75 in the concept of life 29–47 Pascal, Blaise 219–20 Penrose, Roger 106–9, 117, 211–12, 214 Pert, Candace B. 170 physics, gaps in the Standard Model 105 Piketty, Thomas 267, 269 pineal gland 115–16 Pinker, Steven 13, 275 Pinocchio story 56 Pitts, Walter 36, 177–8, 256, 293 Plato 134, 143, 152, 176, 189, 305 central role of mathematics 103–6 idea of reality 78, 83 influence of 95–106 notion of philosopher-kings 98–9 separation of body and mind 112 The Republic 97–101, 309, 310 theory of forms 99–101, 104, 106 Platonism 101–2, 135–7, 139, 142, 146, 147, 182, 189, 190, 242–3, 296 Pleistocene epoch 7 Poe, Edgar Allan 79 Polidori, John William 60, 62 Popov, Alexander 239 Popper, Karl 98 Porter, Rodney 282 posthuman existence 147 postmodernism 208 post-structuralist philosophers 75–9 precautionary principle 64–5 predicate logic 198–200, 206 Principia Mathematica 205–6, 207 Prometheus 29–30, 63–4 psychoanalysis 50 psychons 118, 119 Pygmalion narrative 49–52 qualia of consciousness 120–3, 157 Quantified Self movement 81–2 quantum hypothesis for consciousness 106–9 quantum tunnelling 118–19 Ramachandran, Vilayanur 70 rationalism 116 Reagan, President Ronald 237 reality, impact of acquisition of language 15–18 reductionism 41–2, 104–5, 121, 184 reflexivity 183–4, 186–9 religions condemnation of human replicas 67 seeds of 22–3, 25–6 Renaissance 34, 103, 139, 218 RepRap machines 290 res cogitans (mental substance) 38, 113–14 res extensa (corporeal substance) 38, 113–14 resurrection beliefs 126–7 RoboCop 80 robot swarm experiments 287–8 robots human attitudes towards 50–1 rebellion against humans 53, 57–9 self-replication 289–92 see also androids Rochester, Nathaniel 256 Romans 31 Rubenstein, Michael 287–8, 291 Russell, Bertrand viii, 92, 198, 204, 205–6, 207, 208, 215 Russell, Stuart 270 Sagan, Carl 133 Saygin, Ayse Pinar 69 science as a cultural product 75–9 influence of Aristotle 134–8 influence of Descartes 113–19 influence of Plato see Plato scientific method 102–5, 121 scientific paradigms 75 scientific reasoning, as unnatural to us 133–4, 137 scientific theory, definition 166, 196 Scott, Ridley 53 Searle, John, Chinese Room experiment 52, 71 Second Commandment (Bible) 67 second machine age, impact of AI 266–9 Second World War 234–6 self-awareness 16, 86–7, 157, 215–16, 273–5 self-driving vehicles 263–4 self-organisation in cybernetic systems 273–4 in living things 292 self-referencing 186–9, 215–16 see also reflexivity self-referencing paradoxes 204–6 self-replicating machines/systems 179–82, 289–92 sensorimotor skills, deficiency in AI 275–6 servers, dependence on 245–9 Shannon, Claude 147–52, 154, 176, 230–1, 256 Shaw, George Bernard Shaw 49–50 Shelley, Mary, Frankenstein 40, 60–5, 165 Shelley, Percy Bysshe 60, 62, 63–4 Shickard, Wilhem 219 Silvester II, Pope 35 Simmons, Dan 160 simulated universe concept 127–9 smart drugs 81 Snow, C.


pages: 239 words: 70,206

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

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23andMe, Affordable Care Act / Obamacare, Albert Einstein, big data - Walmart - Pop Tarts, bioinformatics, business intelligence, call centre, cloud computing, computer age, conceptual framework, Credit Default Swap, crowdsourcing, Daniel Kahneman / Amos Tversky, Danny Hillis, data is the new oil, David Brooks, East Village, Edward Snowden, Emanuel Derman, Erik Brynjolfsson, everywhere but in the productivity statistics, Frederick Winslow Taylor, Google Glasses, impulse control, income inequality, indoor plumbing, industrial robot, informal economy, Internet of things, invention of writing, John Markoff, John von Neumann, lifelogging, Mark Zuckerberg, market bubble, meta analysis, meta-analysis, money market fund, natural language processing, obamacare, pattern recognition, payday loans, personalized medicine, precision agriculture, pre–internet, Productivity paradox, RAND corporation, rising living standards, Robert Gordon, Second Machine Age, self-driving car, Silicon Valley, Silicon Valley startup, six sigma, skunkworks, speech recognition, statistical model, Steve Jobs, Steven Levy, The Design of Experiments, the scientific method, Thomas Kuhn: the structure of scientific revolutions, unbanked and underbanked, underbanked, Von Neumann architecture, Watson beat the top human players on Jeopardy!

There are all sorts of potential uses for IBM’s personality identifying technology, if they can scale it up. Personally, I would like to see it become a consumer service. Let people see themselves more deeply, as revealed by their own tweets and analyzed by some clever software. IBM is not a consumer product company, but it could be the technology engine, partner, or licensor to a hot new start-up. The technology could become a lucrative arm of the quantified-self movement. Why not go beyond health-monitoring wristbands and smartphone applications? Democratize personality measurement. Zhou smiled at the suggestion, and she thinks individuals will someday be using such data-generated personality profiles in areas like career planning. Certain personality traits are correlated with success in different occupations. But IBM’s immediate plans are to apply Zhou’s technology to the corporate marketplace.

Big Data at Work: Dispelling the Myths, Uncovering the Opportunities by Thomas H. Davenport

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Automated Insights, autonomous vehicles, bioinformatics, business intelligence, business process, call centre, chief data officer, cloud computing, commoditize, data acquisition, Edward Snowden, Erik Brynjolfsson, intermodal, Internet of things, Jeff Bezos, knowledge worker, lifelogging, Mark Zuckerberg, move fast and break things, move fast and break things, Narrative Science, natural language processing, Netflix Prize, New Journalism, recommendation engine, RFID, self-driving car, sentiment analysis, Silicon Valley, smart grid, smart meter, social graph, sorting algorithm, statistical model, Tesla Model S, text mining

Image data from CAT scans and MRIs is another huge source; thus far doctors only look at it but don’t analyze it in any systematic fashion. Human genome data—at about 2 terabytes per human—is rapidly becoming inexpensive enough ($1,000 per patient within a few years) to gather on many patients. And if that weren’t enough, there will be massive amounts of data from connected health (telemedicine and remote monitoring) and quantified self (personal monitoring) devices. 3 Imagine that doctors and hospitals could gather data on every patient’s weight, blood pressure, heart rate, physical activity, and even mental state—every day or even every hour or minute! The amount of data boggles the mind. In sum, the ­primary challenge in the health-care industry won’t be how to gather big data, but how to make use of it all. B2B Firms Businesses that sell only to businesses may not have a large number of customers, but they still have a big data future.

Raw Data Is an Oxymoron by Lisa Gitelman

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collateralized debt obligation, computer age, continuous integration, crowdsourcing, Drosophila, Edmond Halley, Filter Bubble, Firefox, fixed income, Google Earth, Howard Rheingold, index card, informal economy, Isaac Newton, Johann Wolfgang von Goethe, knowledge worker, liberal capitalism, lifelogging, Louis Daguerre, Menlo Park, optical character recognition, peer-to-peer, RFID, Richard Thaler, Silicon Valley, social graph, software studies, statistical model, Stephen Hawking, Steven Pinker, text mining, time value of money, trade route, Turing machine, urban renewal, Vannevar Bush

There is of course an ongoing relationship with the real world and the human observer (nature and society), however it is a difficult one to express. Both the natural world and its human observers are being ever more instrumented with intelligent machines. Staggering arrays of sensors and cameras furbish “us” with terabytes of data a day about the natural world and about our social activities. The “quantified self ” movement is an oddly worshipful effort to celebrate this quantification (computers do not deal with “soft” data). The qualified self seems to be slipping out of the picture—the interpretative work is done inside the computer and read out and acted on by humans. A dark vision is that our interaction with the world and each other is being rendered epiphenomenal to these data-program-data cycles.


pages: 669 words: 210,153

Tools of Titans: The Tactics, Routines, and Habits of Billionaires, Icons, and World-Class Performers by Timothy Ferriss

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Airbnb, Alexander Shulgin, artificial general intelligence, asset allocation, Atul Gawande, augmented reality, back-to-the-land, Bernie Madoff, Bertrand Russell: In Praise of Idleness, Black Swan, blue-collar work, Buckminster Fuller, business process, Cal Newport, call centre, Checklist Manifesto, cognitive bias, cognitive dissonance, Colonization of Mars, Columbine, commoditize, correlation does not imply causation, David Brooks, David Graeber, diversification, diversified portfolio, Donald Trump, effective altruism, Elon Musk, fault tolerance, fear of failure, Firefox, follow your passion, future of work, Google X / Alphabet X, Howard Zinn, Hugh Fearnley-Whittingstall, Jeff Bezos, job satisfaction, Johann Wolfgang von Goethe, John Markoff, Kevin Kelly, Kickstarter, Lao Tzu, life extension, lifelogging, Mahatma Gandhi, Marc Andreessen, Mark Zuckerberg, Mason jar, Menlo Park, Mikhail Gorbachev, Nicholas Carr, optical character recognition, PageRank, passive income, pattern recognition, Paul Graham, peer-to-peer, Peter H. Diamandis: Planetary Resources, Peter Singer: altruism, Peter Thiel, phenotype, PIHKAL and TIHKAL, post scarcity, premature optimization, QWERTY keyboard, Ralph Waldo Emerson, Ray Kurzweil, recommendation engine, rent-seeking, Richard Feynman, Richard Feynman, risk tolerance, Ronald Reagan, selection bias, sharing economy, side project, Silicon Valley, skunkworks, Skype, Snapchat, social graph, software as a service, software is eating the world, stem cell, Stephen Hawking, Steve Jobs, Stewart Brand, superintelligent machines, Tesla Model S, The Wisdom of Crowds, Thomas L Friedman, Wall-E, Washington Consensus, Whole Earth Catalog, Y Combinator, zero-sum game

For whatever reasons, many men in this book like precisely these two fiction books. Kelly has daughters and texted me about the latter book, which follows a young female protagonist: “How do you raise girls that are of the system but crush the system while rebuilding a better one?” Boner or No Boner? “Men, if you wake up and you don’t have a boner, there’s a problem. Yes or no? One or zero? Boner, no boner?” TF: “Quantified self” tracking doesn’t need to be complicated. It’s easy to miss the flashing red signal in front of your face while chasing the cutting edge of blood testing, genomics, etc. For men, the “boner or no boner” test is a simple but excellent indicator of sleep quality, hormonal health (GH, FSH, testosterone), circadian rhythm timing, and more. The Campfire Squat Test “If you can’t squat all the way down to the ground with your feet and knees together, then you are missing full hip and ankle range of motion.

In his spare time, he writes best-selling books, co-founded the Rosetta Project, which is building an archive of all documented human languages, and serves on the board of the Long Now Foundation. As part of the last, he’s investigating how to revive and restore endangered or extinct species, including the woolly mammoth. He might be the real-world “most interesting man in the world.” Behind the Scenes I attended the very first Quantified Self meet-up on September 10, 2008, at Kevin’s picturesque wood cabin-style home. From that small, 28-person gathering, “QS” has grown into a pop-culture term and international phenomenon, with organizations in more than 20 countries. Sit, Sit. Walk, Walk. Don’t Wobble. “The Zen mantra is ‘Sit, sit. Walk, walk. Don’t wobble.’ . . . It’s this idea that when I’m with a person, that’s total priority.


pages: 379 words: 109,612

Is the Internet Changing the Way You Think?: The Net's Impact on Our Minds and Future by John Brockman

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A Declaration of the Independence of Cyberspace, Albert Einstein, AltaVista, Amazon Mechanical Turk, Asperger Syndrome, availability heuristic, Benoit Mandelbrot, biofilm, Black Swan, British Empire, conceptual framework, corporate governance, Danny Hillis, Douglas Engelbart, Douglas Engelbart, Emanuel Derman, epigenetics, Flynn Effect, Frank Gehry, Google Earth, hive mind, Howard Rheingold, index card, information retrieval, Internet Archive, invention of writing, Jane Jacobs, Jaron Lanier, John Markoff, Kevin Kelly, lifelogging, lone genius, loss aversion, mandelbrot fractal, Marc Andreessen, Marshall McLuhan, Menlo Park, meta analysis, meta-analysis, New Journalism, Nicholas Carr, out of africa, Paul Samuelson, peer-to-peer, Ponzi scheme, pre–internet, Richard Feynman, Richard Feynman, Rodney Brooks, Ronald Reagan, Schrödinger's Cat, Search for Extraterrestrial Intelligence, SETI@home, Silicon Valley, Skype, slashdot, smart grid, social graph, social software, social web, Stephen Hawking, Steve Wozniak, Steven Pinker, Stewart Brand, Ted Nelson, telepresence, the medium is the message, the scientific method, The Wealth of Nations by Adam Smith, theory of mind, trade route, upwardly mobile, Vernor Vinge, Whole Earth Catalog, X Prize

The seductive online sages, scholars, and muses that joyfully take my curious mind wherever it needs to go, wherever it can imagine going, whenever it wants, are beguiling. All my beloved screens offer infinite, charming, playful, powerful, informative, social windows into global human experience. The Internet, the online virtual universe, is my jungle gym, and I swing from bar to bar, learning about how writing can be either isolating or social, about DIY Drones (unmanned aerial vehicles) at a Maker Faire, about where to find a quantified-self meetup, about how to make sach moan sngo num pachok. I can use an image search to look up “hope” or “success” or “play.” I can find a video on virtually anything: I learned how to safely open a young Thai coconut from this Internet of wonder. As I stare out my window at the unusually beautiful Seattle weather, I realize I haven’t been out to walk yet today—sweet Internet juices still dripping down my chin.


pages: 364 words: 99,897

The Industries of the Future by Alec Ross

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23andMe, 3D printing, Airbnb, algorithmic trading, AltaVista, Anne Wojcicki, autonomous vehicles, banking crisis, barriers to entry, Bernie Madoff, bioinformatics, bitcoin, blockchain, Brian Krebs, British Empire, business intelligence, call centre, carbon footprint, cloud computing, collaborative consumption, connected car, corporate governance, Credit Default Swap, cryptocurrency, David Brooks, disintermediation, Dissolution of the Soviet Union, distributed ledger, Edward Glaeser, Edward Snowden, en.wikipedia.org, Erik Brynjolfsson, fiat currency, future of work, global supply chain, Google X / Alphabet X, industrial robot, Internet of things, invention of the printing press, Jaron Lanier, Jeff Bezos, job automation, John Markoff, knowledge economy, knowledge worker, lifelogging, litecoin, M-Pesa, Marc Andreessen, Mark Zuckerberg, Mikhail Gorbachev, mobile money, money: store of value / unit of account / medium of exchange, new economy, offshore financial centre, open economy, Parag Khanna, peer-to-peer, peer-to-peer lending, personalized medicine, Peter Thiel, precision agriculture, pre–internet, RAND corporation, Ray Kurzweil, recommendation engine, ride hailing / ride sharing, Rubik’s Cube, Satoshi Nakamoto, selective serotonin reuptake inhibitor (SSRI), self-driving car, sharing economy, Silicon Valley, Silicon Valley startup, Skype, smart cities, social graph, software as a service, special economic zone, supply-chain management, supply-chain management software, technoutopianism, The Future of Employment, underbanked, Vernor Vinge, Watson beat the top human players on Jeopardy!, women in the workforce, Y Combinator, young professional

Even with these shifting norms, we’ll need to still try to keep essential information like our genetic makeup from becoming public. As big data erodes privacy, there are some things worth fighting to keep private. OUR QUANTIFIED SELVES Privacy is just the first in a series of concerns that big data will raise as it inserts itself more inseparably into our lives. There are abundant other reasonable objections to the dangers of a newly quantified self and society. Philosophically, there has been a longtime fear with the rise of robotics and automation that machines will become more human—potentially supplanting “us” by taking our jobs or by literally taking over. In the big data world, the new fear is that humans will become more like machines. I think back to the Obama campaign official who said, “We basically found our guts were worthless.”


pages: 502 words: 107,657

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

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Albert Einstein, algorithmic trading, Amazon Mechanical Turk, Apple's 1984 Super Bowl advert, backtesting, Black Swan, book scanning, bounce rate, business intelligence, business process, call centre, commoditize, computer age, conceptual framework, correlation does not imply causation, crowdsourcing, dark matter, data is the new oil, en.wikipedia.org, Erik Brynjolfsson, Everything should be made as simple as possible, experimental subject, Google Glasses, happiness index / gross national happiness, job satisfaction, Johann Wolfgang von Goethe, lifelogging, Machine translation of "The spirit is willing, but the flesh is weak." to Russian and back, mass immigration, Moneyball by Michael Lewis explains big data, Nate Silver, natural language processing, Netflix Prize, Network effects, Norbert Wiener, personalized medicine, placebo effect, prediction markets, Ray Kurzweil, recommendation engine, risk-adjusted returns, Ronald Coase, Search for Extraterrestrial Intelligence, self-driving car, sentiment analysis, software as a service, speech recognition, statistical model, Steven Levy, text mining, the scientific method, The Signal and the Noise by Nate Silver, The Wisdom of Crowds, Thomas Bayes, Turing test, Watson beat the top human players on Jeopardy!, X Prize, Yogi Berra, zero-sum game

Ryan Tate, “How a Geek Cracked the Jeopardy! Code,” Gawker.com, November 16, 2011. http://gawker.com/5860275/how-a-geek-cracked-the-jeopardy-code. Ned Potter, “‘Jeopardy!’ Champ Wins Jackpot with Web App,” ABCNews, Technology Review, November 17, 2011. http://abcnews.go.com/blogs/technology/2011/11/jeopardy-champ-wins-jackpot-with-web-app/. Alexandra Carmichael, “Roger Craig Wins Jeopardy Championship with Knowledge Tracking,” Quantified Self, November 17, 2011. http://quantifiedself.com/2011/11/roger-craig-on-knowledge-tracking/. Ken Jennings used Roger Craig’s study system: Ken Jennings, “Map Tourism,” Ken-Jennings.com blog post, November 17, 2011. http://ken-jennings.com/blog/archives/3385. Ken Jennings quotes: Ken Jennings, “My Puny Human Brain,” Slate.com, February 16, 2011. www.slate.com/articles/arts/culturebox/2011/02/my_puny_human_brain.html.


pages: 354 words: 91,875

The Willpower Instinct: How Self-Control Works, Why It Matters, and What You Can Doto Get More of It by Kelly McGonigal

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banking crisis, bioinformatics, Cass Sunstein, choice architecture, cognitive bias, delayed gratification, game design, impulse control, lifelogging, loss aversion, meta analysis, meta-analysis, phenotype, Richard Thaler, Wall-E, Walter Mischel

It could be calling your mother, meditating for five minutes, or finding one thing in your house that needs to be thrown out or recycled. • Strengthen Self-Monitoring: Formally keep track of something you don’t usually pay close attention to. This could be your spending, what you eat, or how much time you spend online or watching TV. You don’t need fancy technology—pencil and paper will do. But if you need some inspiration, the Quantified Self movement (www.quantifiedself.com) has turned self-tracking into an art and science. For any of these willpower-training exercises, you could choose something related to your main willpower challenge. For example, if your goal is to save money, you might keep track of what you spend. If your goal is to exercise more often, you might decide to do ten sit-ups or push-ups before your morning shower.


pages: 390 words: 115,769

Healthy at 100: The Scientifically Proven Secrets of the World's Healthiest and Longest-Lived Peoples by John Robbins

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clean water, collective bargaining, Community Supported Agriculture, Donald Trump, happiness index / gross national happiness, illegal immigration, indoor plumbing, land reform, life extension, lifelogging, Maui Hawaii, meta analysis, meta-analysis, randomized controlled trial, Silicon Valley, telemarketer

Comparing his results with the frequency of heart disease, he found that the men who used the first-person pronouns the most often had the highest risk of heart trouble. What’s more, by following his subjects for several years thereafter, he found that the more a man habitually talked about himself, the greater the chance he would actually have a heart attack.10 Apparently, counting the times a person said “I” was an ingenious way to quantify self-absorption. It seems that the less you open your heart to others, the more your heart suffers. Dr. Scherwitz counsels: “Listen with regard when others talk. Give your time and energy to others; let others have their way; do things for reasons other than furthering your own needs.” This is sound medical advice, and it speaks also to our spiritual and emotional needs. Many religions have taught that being trapped in the illusion of separateness is the source of much of our suffering.


pages: 742 words: 137,937

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

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

Often, the scale of the data flow demands Big Data techniques (see section 4.6). The Emory University Hospital in Atlanta, for example, has worked with IBM to develop bedside monitors in their Intensive Care Unit that collect and analyse over 100,000 data points for each patient each second.35 The commercial availability of many of these devices and systems has also stirred a cultural movement of ‘self-monitoring’, or ‘self-tracking’. Called ‘Quantified Self’, the many tens of thousands who are involved use devices like Jawbone, Fitbit, and MyFitnessPal to collect large volumes of data about themselves—from pulse rates to digestive behaviour, from sleep patterns to happiness levels—and to analyse it with a sophistication that rivals many clinicians. These devices, designed also with the aesthete in mind, are often called ‘wearables’. Proteus Digital Health is developing a range of ‘ingestibles’—small, pill-shaped monitors, swallowed by the patient, with no battery (powered instead by stomach acid36), that provide internal monitoring.


pages: 836 words: 158,284

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

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23andMe, airport security, Albert Einstein, Black Swan, Buckminster Fuller, carbon footprint, cognitive dissonance, Columbine, correlation does not imply causation, Dean Kamen, game design, Gary Taubes, index card, Kevin Kelly, knowledge economy, life extension, lifelogging, Mahatma Gandhi, microbiome, p-value, Parkinson's law, Paul Buchheit, placebo effect, Productivity paradox, publish or perish, Ralph Waldo Emerson, Ray Kurzweil, Richard Feynman, Richard Feynman, selective serotonin reuptake inhibitor (SSRI), Silicon Valley, Silicon Valley startup, Skype, stem cell, Steve Jobs, survivorship bias, Thorstein Veblen, Vilfredo Pareto, wage slave, William of Occam

Self-experimenters, with total freedom, plenty of time, and easy access to empirical tests, are in a great position to take advantage of it. TOOLS AND TRICKS Seth Roberts, “Self-Experimentation as a Source of New Ideas: Ten Examples Involving Sleep, Mood, Health, and Weight,” Behavioral and Brain Science 27 (2004): 227–88 (www.fourhourbody.com/new-ideas) This 61-page document about self-experimentation provides an overview of some of Seth’s findings, including actionable sleep examples. The Quantified Self (www.quantifiedself.com) Curated by Wired cofounding editor Kevin Kelly and Gary Wolf, a managing editor of Wired, this is the perfect home for all self-experimenters. The resources section alone is worth a trip to this site, which provides the most comprehensive list of data-tracking tools and services on the web (www.fourhourbody.com/quantified). Alexandra Carmichael, “How to Run a Successful Self-Experiment” (www.fourhourbody.com/self-experiment) Most people have never systematically done a self-experiment.