Book Read Free

Everyday Chaos

Page 28

by David Weinberger

National Archives of the United Kingdom, 42

  Netflix, 5

  net neutrality, 95

  “New Kind of Science,” 34–35

  Newton, Isaac

  gravity and, 26, 28, 206n16

  interoperability compared to Newton’s laws, 109, 112–113

  prediction and rules of universe, 25–30, 32

  Principia, 27–28

  strategy and, 128

  three-body problem and, 28

  tides and, 48–49

  traditional strategy and, 139

  weather forecasting and laws of, 24

  nonlinear systems, 12–13

  the Normal, accidents and, 36–38

  nuclear war strategy, 128

  Nudge (Thaler & Sunstein), 174, 175

  Obama presidential campaign, A/B testing and, 4–5

  obscurity, strategic, 142–144

  Occupy movement, 176–177

  on-demand manufacturing, 14

  On War (Clausewitz), 126

  open APIs, 117

  open platforms, 14–15, 85–93

  adding value to products, 89–90

  benefits of, 87–93

  increasing presence via, 87–88

  integrating into workflows, 90–91

  moving unanticipation upstream, 91–93

  part of major business shift underway from push to pull, 94–96

  resilience and, 88–89

  open-source content management system, 133

  open standards, 15, 104, 156

  Open Text search engine, 97

  operationalizing of morality, 184–189

  optimization, over explanation, 68–73

  Order of Things, The (Foucault), 119–120

  O’Reilly, Tim, 91, 93

  Packard, Vance, 174

  Pahlka, Jennifer, 91

  Palfry, John, 103, 110

  Paracelsus, 119–120

  Parker, Theodore, 148

  Pascal, Blaise, 30

  Pearl, Judea, 104, 114, 115, 121

  Pebble, 90

  Perrault, Charles, 150

  Peters, Tom, 82

  Phillips, Alban William Housego, 50–51

  Phillips, Macon, 84

  Philosophical Essay on Probabilities, A (Laplace), 27

  Pigliucci, Massimo, 173

  Plato, 31, 32, 149, 199n4, 210n11

  Porter, Michael, 129

  possibility, 123–144

  Drupal and, 132–135, 137–138

  interoperability and increasing, 138–142

  invention of strategy, 125–127

  narrowing, 123–125

  strategic obscurity and, 142–144

  strategy revealing, 127–132

  Tesla and Google, 135–138

  unanticipation creating, 96, 100

  Power of Pull, The (Hagel, Brown & Davison), 94–95

  “Predictability” (Lorenz), 12

  prediction

  complexity beyond, 14–15

  deep learning and, 53–55, 57–58

  defined, 21

  forecasts vs., 197n4

  Game of Life and, 33–35

  improvements in some domains, 35–36

  Newton’s laws and first level of, 25–27

  Newton’s laws and second level of, 27–30, 32

  probability theory and, 30–32

  between surprise and certainty, 20–25

  third level of, 35–36

  weather, 12–13, 19–20, 44–45

  preparing for the future, anticipate-and-prepare strategy, 77–79

  presentism, 178

  Present Shock (Rushkoff), 178

  Principia (Newton), 27–28

  principle-based morality, 182, 183–184, 189

  probability theory, 30–32

  probablistic truth, machine learning and, 121

  programming, 32–33

  progress

  generative, 160–163

  generativity and, 154–160

  invention of, 148–150

  moral, 148

  shape of, 147–148, 155

  technological, 148, 151–154, 162

  traditional, 157–159

  proportion, interoperability and, 112–113

  Raleigh, Walter, 149

  RAND Corporation, 128, 130

  Reed, David, 95

  Re-engineering Humanity (Frischmann & Selinger), 69

  regularity, assumption of in models, 53

  Ren Zhengfei, 142

  resilience, open platforms and, 88–89

  Richardson, Lewis Fry, 44

  Ries, Eric, 80

  Robinson, Frank, 81

  rules

  explanations and, 64

  interoperability and adjustable, 111–112

  Rushkoff, Douglas, 178

  Russell, Chris, 57

  Saltzer, J., 95

  Samsung, 8, 123

  Sandberg, Sheryl, 85, 87

  Sandhaus, Evan, 106

  Santucci, Antonio, 47

  Sarewitz, Daniel, 11–12, 158

  Saussure, Ferdinand de, 190

  scenario planning, 128–129, 131

  Schema.org, 104–107, 117

  Schoolhouse Rock!, 176

  Schwartz, Peter, 128–129

  search engines, 97–100, 104–107

  searching, browsing vs., 97–98

  Sedol, Lee, 59–60

  Selinger, Evan, 69

  Semantic Web, 117

  SGML (Standard Generalized Markup Language), 107

  Signal and the Noise, The (Silver), 44

  signs, machine learning and, 120–121

  Silent Spring (Carson), 13

  Silver, Nate, 44, 45

  simplification

  deep learning and, 60

  models and, 52, 53

  Slack, 81–82, 90–91

  Smiles, Samuel, 152–153

  Smith, Adam, 28

  Smith, Arfon, 92–93

  social graph, 86, 190

  social influencers, 177

  social role of explanations, 171–172

  Socrates, 126, 199n4

  software development

  agile, 14, 83–85, 103, 140

  waterfall process of, 84–85

  spontaneity, preparing for, 93–94

  spreadsheets, 45–47

  standards

  open, 15, 104, 156

  useful unpredictability of, 104–108

  statistical forecasting, 44–45

  statistics, 31–32

  steam engine, progress and, 152–154

  Stiegler, Bernard, 179

  Stone, Edward, 9

  Stone, Zak, 136

  storytelling, 178–181

  strategic communications, 142–144

  strategic obscurity, 142–144

  strategy

  Drupal example, 132–135, 137–138

  invention of, 125–127

  possibility revealed by, 127–132

  Tesla and Google examples, 135–137, 138

  traditional business, 123–125

  Strategy: A History (Freedman), 126

  Structure of Scientific Revolutions, The (Kuhn), 61

  Sunstein, Cass, 174, 175

  Swift, Jonathan, 150

  systems, interoperability working across, 109–111

  tactics, 126

  Technics and Civilization (Mumford), 211n24

  technodeterminism, 163–165, 166–167

  Technohuman Condition, The (Allenby & Sarewitz), 11–12, 158

  technological progress, 148, 151–154, 162

  technology, effects of, 165–166

  Tech Surge, 84

  telephone

  dialing a, 145–147, 209n2, 209n3

  history of, 147

  Temple, William, 150

  TensorFlow, 136–137, 154

  Tesla Motors, open-sourced patents at, 135–137, 138

  Thaler, Richard, 174, 175

  three-body problem, 28, 29–30

  tick marks, traditional progress and, 147, 155, 157, 158, 159


  tides, 48–50

  Tides (White), 48–49

  Too Big to Know (Weinberger), 17

  tools

  computers as, 153–154

  explanations as, 172

  future and new, 192–193

  significance of, 151–154

  thinking out in the world with, 165–167

  Torralba, Antonio, 160–161

  total conversions, 15

  Total Quality Management (TQM), 82

  trade-offs, machine learning and, 70–71

  traditional progress, characteristics of, 157–159

  transient advantage, 129, 131

  Transkribus, 42

  Trojan War strategy, 125–126

  Trolley Problem, 183

  truth

  ground, 42

  probabilistic, 121

  Turgot, Anne Robert Jacques, 151

  Turkle, Sherry, 164

  Twitter, 84, 106, 111–112, 113

  Twitter hashtags, 113, 117–118, 177

  Uber, 69–70

  unanticipation, 79–93

  agile development, 83–85

  creating possibilities, 96, 100

  internet and, 75, 95–96

  minimum viable product and, 80–83

  open platforms and, 85–93

  universe

  armillary model of, 47–48

  clock metaphor for workings of, 25–27, 116

  as vast computer, 34–35

  unpredictability, internet and, 101

  The Upshot platform, 92

  Usual Suspects, The (film), 179

  Utilitarianism, 182–183, 188

  Value of All Chances in Games of Fortune, The (Huygens), 30–31

  Van Doren, Charles, 148

  video games, 15

  See also individual games; Modding/mods

  virtual reality systems, 162

  virtue ethics, 188, 214n29

  Wachter, Sandra, 57

  Wack, Pierre, 128–129

  war, model explaining causes of, 65–66

  See also Military strategy

  waterfall process of software development, 84–85

  weather prediction and modeling, 12–13, 19–20, 44–45

  web

  interoperability and, 116

  Semantic, 117

  webs of meaning, 190–191

  Welchman, Lisa, 134–135

  Wenger 16999 Swiss Army Knife, 78, 153

  White, Jonathan, 48–49

  White, Lynn, Jr., 164

  willow bark, discovering reasons for effectiveness of, 9–10

  Winge, Sara, 93–94

  Wittgenstein, Ludwig, 64

  Wolfram, Stephen, 34–35

  workflows, open platforms and integrating into, 90–91

  working models, 41–43

  armillary, 47–48

  machine learning and, 53–62

  Mississippi River basin model, 50–53

  spreadsheets, 45–47

  tides, 48–50

  World War II military strategy, 127–128, 130

  Yahoo!, 97–98, 104

  Yandex, 104

  Yext, 106

  Zittrain, Jonathan, 156

  Zuckerberg, Mark, 86, 87

  ACKNOWLEDGMENTS

  As I have gotten older, I have become more and more grateful for the privilege—in both its senses—of living in communities where I’m surrounded by people who are simultaneously intelligent, curious, patient, and kind. The thoughts in this book have been formed by the endless tanglings of these networks.

  First among these is, of course, my family, newly sweet with grandchildren, but not untouched by sorrow. Our children have sharp eyes for where the rails lead and when I would happily veer off of them. I owe an endless thanks to my wife, Ann Geller, who has seen me through the many years it has taken to write this book, always bringing her clear and sympathetic mind to my prose, and joy to my life. Everyone who knows us agrees that I am the luckiest person in the world.

  I have benefited incalculably from being allowed to be part of Harvard’s Berkman Klein Center for Internet & Society for the past fifteen years. It is a model of a community of scholars and researchers who care passionately about their work, the world, and one another—remarkable not only in its level of scholarship but also in its compassion.

  Within that community, the members of the “Book Club”—people working on books—have been especially supportive.

  Because I’m an old-school internet user, I also rely on mailing lists, some of which go back decades. Since they’re private lists—there’s that privilege again!—I’ll designate them in ways their members will recognize: Thank you, IRR, BH, and Gordon!

  In the final couple of months of this project, when I was cleaning up drafts and the like, I began a six-month tenure as a part-time writer-in-residence—an outsider embedded on the inside—at Google PAIR (People + AI Research). While the book was fully drafted at that point, working literally next to machine learning developers and having the opportunity to pester them with endless and endlessly foolish questions has helped deepen my understanding and appreciation of the world we’ve entered.

  Thanks to the Harvard Library Innovation Lab, from which I learned so much about the delicate and intricate connections among computer representations of ideas. Also thanks to the Lab for developing—under Jonathan Zittrain’s direction—the Perma.cc service this book uses to provide stable referents for web links.

  David Miller and Lisa Adams have been my literary agents and dear friends for almost twenty years. With extraordinary patience and clearheadedness, they helped me locate ideas worth talking about and shape them into the form of a book.

  Then I had the incredible good fortune to work with Ania Wieckowski, an executive editor at Harvard Business Review Press. Ania worked through my drafts with an unparalleled commitment to challenging and clarifying the ideas and my expression of them. Her fierce patience, perfect pitch, and intellect were crucial, as were her enthusiasm and kindness. I could not have dreamed of a better editor.

  Many other people and many conversations helped me, not least those who let me interview them for the book. Of course, I cannot capture all the other conversations that provided insights, steered me away from errors, and opened up entirely new lines of thought. So here are just a few of the people to whom I owe warm thanks—although more than a few of them will disagree with the broad themes or details of this book: Hal Abelson, Yannick Assogba, Dan Brickley, Greg Cavanagh, Judith Donath, Finale Doshi-Velez, Elena Esposito, John Frank, Brett Frischmann, Urs Gasser, Elyse Graham, Mary L. Gray, Jenn Halen, Timo Hannay, Eszter Hargittai, Tim Hwang, David Isenberg, Joi Ito, Reena Jana, Ansgar Koene, Jeannie Logozzo, Hilary Mason, Elliot Noss, Angelica Quicksey, Emily Reif, Angela Ridgely, Daniel Russell, Bruce Schneier, Evan Selinger, Zak Stone, Tim Sullivan, John Sundman, Peter Sweeney, Fernanda Viegas, Martin Wattenberg, Joel Weinberger, James Wexler, and Ethan Zuckerman.

  I miss both of my wife’s parents who passed away during the course of writing this book. Virginia and Marvin Geller were constant sources of support for me as an individual but more importantly as a member of a large, lively, and loving family.

  I also miss my teacher Professor Joseph P. Fell who opened worlds when he taught, and was a model of scholarship, thoughtfulness, teaching, decency, and friendship.

  This book’s errors, mistakes, omissions, redundancies, misunderstandings, exaggerations, misrepresentations, inaccuracies, mispellings, biases, lacunae, typos, blind spots, missteps, lapses, redundancies, fallacies, misjudgments, flaws, slights, and redundancies are all that I can claim as fully mine.

  ABOUT THE AUTHOR

  From the earliest days of the web, DAVID WEINBERGER has been a pioneering thought leader about the internet’s effect on our lives, on our businesses, and most of all, on our ideas. He has contributed in a range of fields, from marketing to libraries to politics to journalism and more. And he has contributed in a remarkably wide range of ways: as the author of books tha
t explore the meaning of our new technology; a writer for publications from Wired and Scientific American to Harvard Business Review and even TV Guide; an acclaimed keynote speaker around the world; a strategic marketing vice president and consultant; a teacher; an internet adviser to presidential campaigns; an early social-networking entrepreneur; the codirector of Harvard’s groundbreaking Library Innovation Lab; a writer-in-residence at Google; a senior researcher at Harvard’s Berkman Klein Center for Internet & Society; a fellow at Harvard’s Shorenstein Center on Media, Politics and Public Policy; a Franklin Fellow at the US State Department; and always a passionate advocate for an open internet. Dr. Weinberger received his doctorate in philosophy from the University of Toronto.

 

 

 


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