ShotSpotter

The Future of the Internet: And How to Stop It
by Jonathan Zittrain
Published 27 May 2009

See, e.g., JEFFREY ROSEN, THE UNWANTED GAZE: THE DESTRUCTION OF PRIVACY IN AMERICA 172—73 (2001) (explaining how, with the help of encryption, “individual Internet users could come close to realizing Louis Brandeis and Samuel Warren’s ideal” of privacy). 43. ShotSpotter is a company that offers some examples of this technology. See ShotSpotter, ShotSpotter Gunshot Location System (GLS) Overview, http://www.shotspotter.com/products/index.html (last visited June 1, 2007) (providing an overview of the company’s products); Ethan Watters, Shot Spotter, WIRED MAGAZINE, Apr. 2007, at 146—52, available athttp://www.shotspotter.com/news/news.html (discussing the use and effectiveness of this technology); see also ShotSpotter, ShotSpotter in the News, http://www.shotspotter.com/news/news.html (last visited June 1, 2007) (providing links to articles discussing the company and its products). 44.

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See September 11 attacks and PATRIOT Act PDAs (personal digital assistants), 58–59 peer production, 206–16 perfect enforcement, 107–10, 112, 122, 134, 161, 166 personal computers (PCs): accessibility via broadband, 4; business adoption of, 15–16; connected by modems, 25; connectivity vs. design of, 166; data sharing on, 160; desktop, 17; development of, 15; as electronic workbooks, 236; as endpoints, 167; flexible architecture of, 16; generative technology of, 2, 3, 5, 19, 34, 72; government investigations of, 186–88; Green and Red, 155; of hobbyists, 13, 14, 15, 18, 19, 34; hourglass architecture of, 69–71; increasing reliance on, 102; independent functioning of, 15; as information (tethered) appliances, 4, 59–61, 102, 185–88; information appliances vs., 18, 29, 57–59; and Internet compatibility, 28–29; lockdown of, 4, 5, 57, 102, 155–56, 164, 165; model of computing, 17; modularization of, 156; PC revolution, 3, 18; potential functionality sold with, 13; regulability of, 106; search across computers, 185; security dilemma of, 241; in sites where users are not owners, 4; and third-party storage, 186–88; “trapped,” 77; unsecured on Internet, 45; users as programmers for, 14, 15; virtual, 156; zombies, 46, 52, 54, 57, 166 personal identity management, 32–33 Pew Internet & American Life Project, 51 phishing, 47, 53, 99 photo recognition, 214–15 physical layer, 67–69 placeholders, 56 plagiarism, 244 plastic, adaptability of, 72 PlayMedia, 104, 108 Pledgebank, 148, 243 pornography, child, 111 Posner, Eric, 213 Post, David, 123 Postel’s Law, 134 post hoc remedies, 122 post hoc scrubs, 116 Postman, Neil, 93 preemption, 108 press conference behavior, 212–13, 229 prime time, being ready for (and the generative Net), 153–54 prior restraints, 115, 122 Privacy Act (1974), 202 privacy: administrative burdens of, 221–22; and captchas, 208; and cheap sensors, 206, 208–9, 210, 216, 221; code-backed norms, 223–28; Constitutional support of, 112, 185–86, 188; and consumer protection law, 177; contextualization, 229–31; data genealogy, 225–28; enforceability of, 112–14; and generation gap, 231–34; and government power, 117–19, 186–88; HEW report (1973) on, 201–5, 222, 233–34; and industry self-regulation, 203; involuntary celebrities, 210–14; “just deal with it,” 111–12; and peer production, 206–16; personal information security, 203–4; Privacy 1.0, 201–5, 208, 215, 216, 222, 232; Privacy 2.0, 205–34; as proxies for other limitations, 112; public vs. private behavior, 212–16; and reputation, 216–21, 228–29; search and seizure, 112; sensitivity identified with, 202; and third-party storage, 185–88; and ubiquitous surveillance, 109–10, 206, 209–16; on Web sites, 203, 226 privacy “tags,” 227 procrastination principle: and Digital Millennium Copyright Act, 119–20; in generative systems, 152, 164, 180, 242, 245; in Internet design, 33, 34; and Morris worm, 39–40; in networks, 31, 33, 99, 164; in operating systems, 69; and Wikipedia, 134, 135; in XO, 237, 240 Prodigy, 7, 23, 24, 81, 157 proprietary rights thickets, 188–92 protocol layer, 39, 67–69 punch card system, 11 QTel, 157 quasi-contracts, 184 Radin, Margaret, 233 radio broadcasts, jamming of, 106 radio frequency identifiers (RFIDs), 203 Radio Shack, 75-in-1 Electronic Project Kit, 14, 73 Rand, Ayn, 143 Raymond, Eric, 137 “Realtime Blackhole List,” 169 reCAPTCHA, 208, 227 Reed, David, 31 Reidenberg, Joel, 104 reputation bankruptcy, 228–29 reputationdefender.com, 230 reputation systems, 216–21; buddy lists, 219–20; correcting or identifying mistakes on, 220; identity systems, 220; search engines, 217, 220–21; user rankings, 146, 217–18, 221; whole-person ratings, 218–19 RFC 1135, “The Helminthiasis of the Internet,” 39 robots, spam messages from, 207–8 robot signaling, 223 robots.txt, 223–25, 227, 243 Rosen, Jeffrey, 216 RSS (really simple syndication), 56 Saltzer, Jerry, 31 Samuelson, Pamela, 225–26 Sanger, Larry, 133, 142–43, 145 Sapphire/Slammer worm, 47 satellite TV, 181, 182 Saudi Arabia, information control in, 113, 180 Scherf, Steve, 145–46 search engines, 220–21, 223, 226, 227; creation of, 224; user rankings, 217 Second Amendment, 117 SEC v. Jerry T. O’Brien, Inc., 185, 188 Seigenthaler, John, Sr., 138, 141, 145 semiotic democracy, 147 Sender ID, 193–94 sensors: cheap, 206, 208–9, 210, 221; ubiquitous, 212–13 September 11 attacks and PATRIOT Act, 186–87 SETI@home, 90 ShotSpotter, 314n43 signal neutrality, 182 Simpson, Jessica, 53 Skype, 56–57, 58, 59, 60, 102, 113, 178, 180, 182 Slashdot, 217 smoking bans, 118 snopes.com, 230 sobig.f virus, 47 social layer, 67 sock puppetry, 136, 228 software: BBS, 25; collaboration, 96; copylefted, 309n75; cross-licensing of, 190; and cyberlaw, 104–7; and data portability, 177; flexible, 15–16; free, 77, 94, 131–32, 189, 191–92; installation of, 14, 16, 18; interoperability of, 176, 184; patents of, 190; poor decisions about, 55; programmers of, 14, 15, 16; of proprietary networks, 82, 189; reconfigurability of, 14; source code of, 189, 192; and statute of limitations, 191; trusted systems, 105; unbundled from hardware, 12, 14; updates of, 176; user-written, 85; written by amateurs, 89; written by third parties, 14, 16–17, 18, 180, 183, 192–93 Solove, Daniel, 210 Sony, Mylo, 58 Spafford, Gene, 37, 240 spam, 99, 130, 137, 166; anonymous, 194; from automated robots, 207–8; blocks of, 111, 194; filters, 46; and link farms, 207; MAPS vs., 168–70; Nigerian “419,” 240; ORBS vs., 169; and viruses, 170–73 specific injunction, 108–9 speech: anonymous, 213; freedom of, 114, 230; “more speech” approach, 230; and prior restraints, 122 speed bumps, 108 spreadsheets, 15, 88 spyware, 53, 130, 172 Stallman, Richard, 77, 131–32, 190 “Star Wars Kid,” 211–12, 213, 234 State Department, U.S., computer virus spread in, 47 statutes of limitations, 191 Sterling, Bruce, 239 StopBadware.org, 52, 159, 170–72 storage: miniaturization of, 155–56; third-party, 185–88 Stored Communications Act, 186 Strahilevitz, Lior, 118, 219, 220 Stuntz, William, 112, 117 subsidiarity, 143 Sunstein, Cass, 213 Supreme Court, U.S.: on gag order, 116; on privacy, 185, 188; on search and seizure, 188 surveillance: and censorship, 113; cheap cameras, 206; and false positives, 116–17; and government power, 117–19, 175, 187; by law enforcement officers, 4–5, 109–10, 113, 117, 118, 209–10, 215–16; “mass dataveillance,” 208; mistakes locked in, 116–17; by mobile phones, 4, 110, 117, 210–14; and PATRIOT Act, 186–87; in tethered appliances, 109–10, 116, 117; and third-party storage, 186–88; at traffic lights, 116–17; ubiquitous, 109–10, 206, 209–16 Sutton, Willie, 55 Swiss Army knife, 72, 73 Symantec Corp., 46, 159 tabulation, punch card system of, 11 TamTam (and XO project), 237 Tattam, Peter, 29, 85 technical protection measures, 105 technology: and automation, 92; cheap networks, 205–6, 210, 214, 216, 221; cheap processors, 205, 210, 216, 221; cheap sensors, 206, 208–9, 210, 216, 221; expansion of, 34, 150; facial recognition, 214–15; functionality of, 105; image recognition, 215–16; international exportation of, 5; Moore’s Law in, 205; participatory, 206; peer production, 206–16; pressure for change in, 175; regulators of, 4, 8, 35, 105, 175; security vs. freedom in, 3–5, 155; social liberalization and progress in, 113–14; user ID, 32, 195; virtualization, 155, 156.

To Save Everything, Click Here: The Folly of Technological Solutionism
by Evgeny Morozov
Published 15 Nov 2013

As the costs of recording devices keep falling, it’s now possible to spot and react to crimes in real time. Consider a city like Oakland in California. Like many other American cities, today it is covered with hundreds of hidden microphones and sensors, part of a system known as ShotSpotter, which not only alerts the police to the sound of gunshots but also triangulates their location. On verifying that the noises are actual gunshots, a human operator then informs the police. These systems are not cheap—ShotSpotter reportedly charges $40,000 to $60,000 a year per square mile—but they are hardly the latest word in crime detection. Why bother with expensive microphones if smartphones can do the job just fine?

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It all boils down to designing an appealing and nonintrusive app and creating the right incentives—perhaps by appealing to the moral conscience of citizens or by turning crime reports into a game—so that citizens can take on some of the tasks of faulty sensors and easily distracted human operators. It’s not hard to imagine other ways to improve a system like ShotSpotter. Gunshot-detection systems are, in principle, reactive; they might help to thwart or quickly respond to crime, but they won’t root it out. The decreasing costs of computing, considerable advances in sensor technology, and the ability to tap into vast online databases allow us to move from identifying crime as it happens—which is what the ShotSpotter does now—to predicting it before it happens. Instead of detecting gunshots, new and smarter systems can focus on detecting the sounds that have preceded gunshots in the past.

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Chapter 6: Less Crime, More Punishment 181 “Imagine what would have happened”: Ursula Franklin, The Real World of Technology (Toronto: House of Anansi, 1999), 18. 181 “What the utopian denounces”: Thomas Molnar, Utopia: The Perennial Heresy (London: Tom Stacey Ltd., 1972), 6. 182 ShotSpotter: Ethan Watters, “Shot Spotter,” Wired, March 2007, http://www.wired.com/wired/archive/15.04/shotspotter.html. 183 PredPol: on PredPol and predictive policing in general, see “Sci-fi Policing: Predicting Crime before It Occurs,” Associated Press, July 1, 2012; Joel Rubin, “Stopping Crime before It Starts,” Los Angeles Times, August 21, 2010, http://articles.latimes.com/2010/aug/21/local/la-me-predictcrime-20100427–1. 183 Consider the New York Police Department’s latest innovation: “NYPD, Microsoft Push Big Data Policing into Spotlight,” Informationweek, August 20, 2012, http://www.informationweek.com/security/privacy/nypd-microsoft-push-big-data-policing-in/240005838 . 183 “understand the unique groups in their customer base”: C.

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

The most interesting interactive screen in the room was devoted to ShotSpotter, a gunshot detection system with acoustic sensors placed in key locations in the city, for which the department paid $800,000 a year. It made a sound like a ray gun in a sci-fi movie each time a shot was detected and displayed a map of Miami that showed where alerts had gone off over the last twenty-four hours. Gooty tapped on a report of twelve rounds being fired in the wee hours of the morning in a majority-Black neighborhood called Overtown. The system let him play the captured audio. It sounded to me like fireworks, but ShotSpotter had labeled it “High capacity” and “Full auto,” suggesting that it was from an assault rifle.

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It sounded to me like fireworks, but ShotSpotter had labeled it “High capacity” and “Full auto,” suggesting that it was from an assault rifle. Gooty said it sounded like fireworks to him as well but that shooters sometimes cover up gunshots with fireworks. Regardless, anytime ShotSpotter detects what it thinks is a gunshot, a police car is sent, sirens on, to check it out. “The system becomes our 911 caller,” Gooty said. Most of the center’s other screens showed grids of surveillance camera footage, most of it from the streets around the music festival’s many stages. The outside venue, and its enormous crowd, was just a half mile away. By Friday evening, there were tens of thousands of people lined up to get into the Ultra festival for the opening set.

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A detective could use it to zoom down to street level—to observe, undetected, what a festivalgoer was doing at an incredible level of detail. “It’s like playing ‘Where’s Waldo?’ ” the detective joked. But that camera was exceptional; the vast majority of Miami’s cameras seemed to be far lower resolution and not as widely distributed as officers would have liked. Time and time again, when ShotSpotter went off, it would be in a blind spot, out of camera view. After the festival, each evening, the festivalgoers flooded out into the street and then seemed to disappear, flowing away from the camera-dense downtown to parts of the city that weren’t as well covered. An armed robbery happened on Saturday.

Bold: How to Go Big, Create Wealth and Impact the World
by Peter H. Diamandis and Steven Kotler
Published 3 Feb 2015

Security-related sensors have also exploded onto the scene. Today’s all-pervasive video surveillance cameras, now coupled to databases stocked with 120 million facial images, give law enforcement unprecedented search capability. But beyond looking for trouble, our sensors can listen as well. Take ShotSpotter,3 a gunfire detection technology that gathers data from a network of acoustic sensors placed throughout a city, filters the data through an algorithm to isolate the sound of gunfire, triangulates the location within about ten feet, then reports it directly to the police. The system is generally more accurate and more reliable than information gleaned from 911 callers.

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Chapter Three: Five to Change the World 1 Adrian Kingsley-Hughes, “Mobile gadgets driving massive growth in touch sensors,” ZDNet, June 18, 2013, http://www.zdnet.com/mobile-gadgets-driving-massive-growth-in-touch-sensors-7000016954/. 2 Peter Kelly-Detwiler, “Machine to Machine Connections—The Internet of Things—And Energy,” Forbes, August 6, 2013, http://www.forbes.com/sites/peterdetwiler/2013/08/06/machine-to-machine-connections-the-internet-of-things-and-energy/. 3 See http://www.shotspotter.com. 4 Clive Thompson, “No Longer Vaporware: The Internet of Things Is Finally Talking,” Wired, December 6, 2012, http://www.wired.com/2012/12/20-12-st_thompson/. 5 Brad Templeton, “Cameras or Lasers?,” Templetons, http://www.templetons.com/brad/robocars/cameras-lasers.html. 6 See http://en.wikipedia.org/wiki/Passenger_vehicles_in_the_United_States. 7 Commercial satellite players include: PlanetLabs (already launched), Skybox (launched and acquired by Google), Urthecast (launched), and two still-confidential companies still under development (about which Peter Diamandis has firsthand knowledge). 8 Stanford University, “Need for a Trillion Sensors Roadmap,” Tsensorsummit.org, 2013, http://www.tsensorssummit.org/Resources/Why%20TSensors%20Roadmap.pdf. 9 Rickie Fleming, “The battle of the G networks,” NCDS.com blog, June 28, 2014, http://www.ncds.com/ncds-business-technology-blog/the-battle-of-the-g-networks. 10 AI with Dan Hesse, 2013–14. 11 Unless otherwise noted, all IoT information and Padma Warrior quotes come from an AI with Padma, 2013. 12 Cisco, “2013 IoE Value Index,” Cisco.com, 2013, http://internetofeverything.cisco.com/learn/2013-ioe-value-index-whitepaper. 13 NAVTEQ, “NAVTEQ Traffic Patterns,” Navmart.com, 2008, http://www.navmart.com/pdf/NAVmart_TrafficPatterns.pdf. 14 Juho Erkheikki, “Nokia to Buy Navteq for $8.1 Billion, Take on TomTom (Update 7),” Bloomberg, October 1, 2007, http://www.bloomberg.com/apps/news?

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R., 27 LIDAR, 43–44, 44 life-extension projects, 66, 81 Li’l Abner (comic strip), 71 Lincoln, Abraham, 109, 194 Lindbergh, Charles, 112, 244, 245, 259–60 linear growth, 7, 9 linear industries, 38, 116 exponential technologies in disrupting of, 17, 18–22 linear organizations, 15, 17, 18, 19, 20, 21, 76, 85, 116 LinkedIn, 77, 213, 231 Lintott, Chris, 220 Linux, 11, 163 Littler Workplace Policy Institute, 60 live-streaming, in crowdsourcing campaigns, 207 Lloyd, Gareth, 4 Local Motors, 33, 217, 223–25, 231, 238, 240, 241 Locke, Edwin, 23, 74, 75, 103 Lockheed, 71–72, 75 Lockheed Martin, 249 Longitude Prize, 245, 247, 267 long-term thinking, 116, 128, 130–31, 132–33, 138 Los Angeles, Calif., 258 loss aversion, 121 Louis Pasteur Université, 104 Lovins, Amory, 222 MacCready, Paul, 263 McDowell, Mike, 291n machine learning, 54–55, 58, 66, 85, 137, 167, 216 see also artificial intelligence (AI) Macintosh computer, 72 McKinsey & Company, 245 McLucas, John, 102 Macondo Prospect, 250 macrotasks, crowdsourcing of, 156, 157–58 Made in Space, 36–37 Made to Stick: Why Some Ideas Survive and Others Die (Heath and Heath), 248 MakerBot printers, 39 Makers (Doctorow), 38 MakieLabs, 39 manufacturing, 33, 41 biological, 63–64 digital, 33 in DIY communities, 223–25 robotics in, 62 subtractive vs. additive, 29–30, 31 3–D printing’s impact on, 30, 31, 34–35 Marines, US, 222 Markoff, John, 56 Mars missions, 99, 118–19, 128 Mars Oasis project, 118 Maryland, University of, 74 Maryniak, Gregg, 244 Mashable, 238 massively transformative purpose (MTP), 215, 221, 230, 231, 233, 240, 242, 274 in incentive competitions, 249, 255, 263, 265, 270 mastery, 79, 80, 85, 87, 92 materials, in crowdfunding campaigns, 195 Maven Research, 145 Maxwell, John, 114n Mead, Margaret, 247 Mechanical Turk, 157 meet-ups, 237 Menlo Ventures, 174 message boards, 164 Mexican entrepreneurs, 257–58 Michigan, University of, 135, 136 microfactories, 224, 225 microlending, 172 microprocessors, 49, 49 Microsoft, 47, 50, 99 Microsoft Windows, 27 Microsoft Word, 11 microtasks, crowdsourcing of, 156–57, 166 Mightybell, 217, 233 Migicovsky, Eric, 175–78, 186, 191, 193, 198, 199, 200, 206, 209 Millington, Richard, 233 Mims, Christopher, 290n MIT, 27, 60, 100, 101, 103, 291n mobile devices, 14, 42, 42, 46, 46, 47, 49, 124, 125, 135, 146, 163, 176 see also smartphones Modernizing Medicine, 57 monetization: in incentive competitions, 263 of online communities, 241–42 Montessori education, 89 moonshot goals, 81–83, 93, 98, 103, 104, 110, 245, 248 Moore, Gordon, 7 Moore’s Law, 6–7, 9, 12, 31, 64 Mophie, 18 moral leadership, 274–76 Morgan Stanley, 122, 132 Mosaic, 27, 32, 33, 57 motivation, science of, 78–80, 85, 87, 92, 103 incentive competitions and, 148, 254, 255, 262–63 Murphy’s Law, 107–8 Museum of Flight (Seattle), 205 music industry, 11, 20, 124, 125, 127, 161 Musk, Elon, xiii, 73, 97, 111, 115, 117–23, 128, 134, 138, 139, 167, 223 thinking-at-scale strategies of, 119–23, 127 Mycoskie, Blake, 80 Mycroft, Frank, 180 MySQL, 163 Napoléon I, Emperor of France, 245 Napster, 11 Narrative Science, 56 narrow framing, 121 NASA, 96, 97, 100, 102, 110, 123, 221, 228, 244 Ames Research Center of, 58 Jet Propulsion Laboratory (JPL) of, 99 Mars missions of, 99, 118 National Collegiate Athletic Association (NCAA), 226 National Institutes of Health, 64, 227 National Press Club, 251 navigation, in online communities, 232 Navteq, 47 Navy Department, US, 72 NEAR Shoemaker mission, 97 Netflix, 254, 255 Netflix Prize, 254–56 Netscape, 117, 143 networks and sensors, x, 14, 21, 24, 41–48, 42, 45, 46, 66, 275 information garnered by, 42–43, 44, 47, 256 in robotics, 60, 61 newcomer rituals, 234 Newman, Tom, 268 New York Times, xii, 56, 108, 133, 145, 150, 155, 220 Nickell, Jake, 143, 144 99designs, 145, 158, 166, 195 Nivi, Babak, 174 Nokia, 47 Nordstrom, 72 Nye, Bill, 180, 200, 207 “Oatmeal, the” (web comic), 178, 179, 193, 196, 200 Oculus Rift, 182 O’Dell, Jolie, 238–39 oil-cleanup projects, 247, 250–53, 262, 263, 264 Olguin, Carlos, 65 1Qbit, 59 operational assets, crowdsourcing of, 158–60 Orteig Prize, 244, 245, 259, 260, 263 Oxford Martin School, 62 Page, Carl, 135 Page, Gloria, 135 Page, Larry, xiii, 53, 74, 81, 84, 99, 100, 115, 126, 128, 134–39, 146 thinking-at-scale strategies of, 136–38 PageRank algorithm, 135 parabolic flights, 110–12, 123 Paramount Pictures, 151 Parliament, British, 245 passion, importance of, 106–7, 113, 116, 119–20, 122, 125, 134, 174, 180, 183, 184, 248, 249 in online communities, 224, 225, 228, 231, 258 PayPal, 97, 117–18, 167, 201 PC Tools, 150 Pebble Watch campaign, 174, 175–78, 179, 182, 186, 187, 191, 200, 206, 208, 209, 210 pitch video in, 177, 198, 199 peer-to-peer (P2P) lending, 172 Pelton, Joseph, 102 personal computers (PCs), 26, 76 Peter’s Laws, 108–14 PHD Comics, 200 philanthropic prizes, 267 photography, 3–6, 10, 15 demonetization of, 12, 15 see also digital cameras; Kodak Corporation Pink, Daniel, 79 Pishevar, Shervin, 174 pitch videos, 177, 180, 192, 193, 195, 198–99, 203, 212 Pivot Power, 19 Pixar, 89, 111 Planetary Resources, Inc., 34, 95, 96, 99, 109, 172, 175, 179, 180, 186, 189–90, 193, 195, 201–3, 221, 228, 230 Planetary Society, 190, 200 Planetary Vanguards, 180, 201–3, 212, 230 PlanetLabs, 286n +Pool, 171 Polaroid, 5 Polymath Project, 145 Potter, Gavin, 255–56 premium memberships, 242 PricewaterhouseCoopers, 146 Prime Movers, The (Locke), 23 Princeton University, 128–29, 222 Prius, 221 probabilistic thinking, 116, 121–22, 129 process optimization, 48 Project Cyborg, 65 psychological tools, of entrepreneurs, 67, 115, 274 goal setting in, 74–75, 78, 79, 80, 82–83, 84, 85, 87, 89–90, 92, 93, 103–4, 112, 137, 185–87 importance of, 73 line of super-credibility and, 96, 98–99, 98, 100, 101–2, 107, 190, 203, 266, 272 passion as important in, 106–7, 113, 116, 119–20, 122, 125, 134, 174, 249, 258 Peter’s Laws in, 108–14 and power of constraints, 248–49 rapid iteration and, 76, 77, 78, 79–80, 83–84, 85, 86, 120, 126, 133–34, 236 risk management and, see risk management science of motivation and, 78–80, 85, 87, 92, 103, 254, 255 in skunk methodology, 71–87, 88; see also skunk methodology staging of bold ideas and, 103–4, 107 for thinking at scale, see scale, thinking at triggering flow and, 85–94, 109 public relations managers, in crowdfunding campaigns, 193–94 purpose, 79, 85, 87, 116, 119–20 in DIY communities, see massively transformative purpose (MTP) Qualcomm Tricorder XPRIZE, 253 Quirky, 18–20, 21, 66, 161 Rackspace, 50, 257 Rally Fighter, 224, 225 rapid iteration, 76, 77, 78, 79–80, 83–84, 85, 86, 236 feedback loops in, 77, 83, 84, 86, 87, 90–91, 92, 120 in thinking at scale, 116, 126, 133–34 rating systems, 226, 232, 236–37, 240 rationally optimistic thinking, 116, 136–37 Ravikant, Naval, 174 Raytheon, 72 re:Invent 2012, 76–77 reCAPTCHA, 154–55, 156, 157 registration, in online communities, 232 Reichental, Avi, 30–32, 35 Rensselaer Polytechnic Institute, 4 reputation economics, 217–19, 230, 232, 236–37 Ressi, Adeo, 118 ReverbNation, 161 reward-based crowdfunding, 173, 174–80, 183, 185, 186–87, 195, 205, 207 case studies in, 174–80 designing right incentives for affiliates in, 200 early donor engagement in, 203–5 fundraising targets in, 186–87, 191 setting of incentives in, 189–91, 189 telling meaningful story in, 196–98 trend surfing in, 208 upselling in, 207, 208–9 see also crowdfunding, crowdfunding campaigns rewards, extrinsic vs. intrinsic, 78–79 Rhodin, Michael, 56 Richards, Bob, 100, 101–2, 103, 104 Ridley, Matt, 137 risk management, 76–77, 82, 83, 84, 86, 103, 109, 116, 121 Branson’s strategies for, 126–27 flow and, 87, 88, 92, 93 incentive competitions and, 247, 248–49, 261, 270 in thinking at scale, 116, 121–22, 126–27, 137 Robinson, Mark, 144 Robot Garden, 62 robotics, x, 22, 24, 35, 41, 59–62, 63, 66, 81, 135, 139 entrepreneurial opportunities in, 60, 61, 62 user interfaces in, 60–61 Robot Launchpad, 62 RocketHub, 173, 175, 184 Rogers, John “Jay,” 33, 38, 222–25, 231, 238, 240 Roomba, 60, 66 Rose, Geordie, 58 Rose, Kevin, 120 Rosedale, Philip, 144 Russian Federal Space Agency, 102 Rutan, Burt, 76, 96, 112, 127, 269 San Antonio Mix Challenge, 257–58 Sandberg, Sheryl, 217, 237 Santo Domingo, Dominican Republic, 3 Sasson, Steven, 4–5, 5, 6, 9 satellite technology, 14, 36–37, 44, 100, 127, 275, 286n scale, thinking at, xiii, 20–21, 116, 119, 125–28, 148, 225, 228, 243, 257 Bezos’s strategies for, 128, 129, 130–33 Branson’s strategies for, 125–27 in building online communities, 232–33 customer-centric approach in, 116, 126, 128, 130, 131–32, 133 first principles in, 116, 120–21, 122, 126, 138 long-term thinking and, 116, 128, 130–31, 132–33, 138 Musk’s strategies for, 119–23, 127 Page’s strategies for, 136–38 passion and purpose in, 116, 119–20, 122, 125, 134 probabilistic thinking and, 116, 121–22, 129 rapid iteration in, 116, 126, 133–34 rationally optimistic thinking and, 116, 136–37 risk management in, 116, 121–22, 126–27, 137 Scaled Composites, 262 Schawinski, Kevin, 219–21 Schmidt, Eric, 99, 128, 251 Schmidt, Wendy, 251, 253 Schmidt Family Foundation, 251 science of motivation, 78–80, 85, 87, 92, 103 incentive competitions and, 148, 254, 255, 262–63 Screw It, Let’s Do It (Branson), 125 Scriptlance, 149 Sealed Air Corporation, 30–31 Second Life, 144 SecondMarket, 174 “secrets of skunk,” see skunk methodology Securities and Exchange Commission (SEC), US, 172 security-related sensors, 43 sensors, see networks and sensors Shapeways.com, 38 Shingles, Marcus, 159, 245, 274–75 Shirky, Clay, 215 ShotSpotter, 43 Simply Music, 258 Singh, Narinder, 228 Singularity University (SU), xi, xii, xiv, 15, 35, 37, 53, 61, 73, 81, 85, 136, 169, 278, 279 Six Ds of Exponentials, 7–15, 8, 17, 20, 25 deception phase in, 8, 9, 10, 24, 25–26, 29, 30, 31, 41, 59, 60 dematerialization in, 8, 10, 11–13, 14, 15, 20–21, 66 democratization in, 8, 10, 13–15, 21, 33, 51–52, 59, 64–65, 276 demonetization in, 8, 10–11, 14, 15, 52, 64–65, 138, 163, 167, 223 digitalization in, 8–9, 10 disruption phase in, 8, 9–10, 20, 24, 25, 29, 32, 33–35, 37, 38, 39, 256; see also disruption, exponential Skonk Works, 71, 72 skunk methodology, 71–87, 88 goal setting in, 74–75, 78, 79, 80, 82–83, 84, 85, 87, 103 Google’s use of, 81–84 isolation in, 72, 76, 78, 79, 81–82, 257 “Kelly’s rules” in, 74, 75–76, 77, 81, 84, 247 rapid iteration approach in, 76, 77, 78, 79–80, 83–84, 85, 86 risk management in, 76–77, 82, 83, 84, 86, 87, 88 science of motivation and, 78–80, 85, 87, 92 triggering flow with, 86, 87 Skunk Works, 72, 75 Skybox, 286n Skype, 11, 13, 167 Sloan Digital Sky Survey, 219–20 Small Business Association, US, 169 smartphones, x, 7, 12, 14, 15, 42, 135, 283n apps for, 13, 13, 15, 16, 28, 47, 176 information gathering with, 47 SmartThings, 48 smartwatches, 176–77, 178, 191, 208 software development, 77, 144, 158, 159, 161, 236 in exponential communities, 225–28 SolarCity, 111, 117, 119, 120, 122 Space Adventures Limited, 96, 291n space exploration, 81, 96, 97–100, 115, 118, 119, 122, 123, 134, 139, 230, 244 asteroid mining in, 95–96, 97–99, 107, 109, 179, 221, 276 classifying of galaxies and, 219–21, 228 commercial tourism projects in, 96–97, 109, 115, 119, 125, 127, 244, 246, 261, 268 crowdfunding campaigns for, see ARKYD Space Telescope campaign incentive competitions in, 76, 96, 109, 112, 115, 127, 134, 139, 246, 248–49, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269 International Space University and, 96, 100–104, 107–8 Mars missions in, 99, 118–19, 128 see also aerospace industry Space Fair, 291n “space selfie,” 180, 189–90, 196, 208 SpaceShipOne, 96, 97, 127, 269 SpaceShipTwo, 96–97 SpaceX, 34, 111, 117, 119, 122, 123 Speed Stick, 152, 154 Spiner, Brent, 180, 200, 207 Spirit of St.

Humans Need Not Apply: A Guide to Wealth and Work in the Age of Artificial Intelligence
by Jerry Kaplan
Published 3 Aug 2015

Quite the contrary, they would be better off with a network of sensors distributed throughout the environment of interest. Your depth perception and ability to locate sounds would be far better if you could separate your ears and eyes by yards instead of inches, not to mention if you could add additional ones at will facing in various directions. Consider, for instance, how much better the automated ShotSpotter system is at locating gunshots than the police are. Similarly, there’s no reason for the means by which robots pursue their goals to be bound together in one package. They can consist of a collection of disconnected and interchangeable actuators, motors, and tools. Finally, the logic that coordinates and drives all of this can be anywhere, like the remote drone pilots in the Nevada desert unleashing Hellfire missiles in Afghanistan.

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See autonomous vehicles self stocking, 40 sensors, 194, 205 applications of, 4, 5 network of, 42–43, 44 recognition by, 39 sex workers and toys, 144–45 Shaw, Dave (King Quant), 51–53, 58, 95, 96, 97, 103 shipping, 39 costs of, 100, 101 delivery and, 141–42, 177 “free,” 101 warehouse stacking and, 144 ShotSpotter system, 43 Silicon Valley startups, x–xi, 64–65, 95–96, 127, 144, 223–24n15 disruption of industries by, 16 personal wealth from, 109 restricted stock vesting by, 184 Simon, Paul, 112 simulated intelligence. See synthetic intellects “siren servers,” 7 Siri (Apple iPhone app), 198 skills, 119–26, 163 obsolescence of, 132, 134, 136–38, 142–43, 152, 153, 158 training to acquire, 13, 14, 132–33, 153–57 Slave Codes, 86 slave self-purchase, 201 smartphones, 105, 115–16 fast-paced innovation and, 26–27, 28, 31, 46, 198 social behavior, 9, 10, 37, 42, 48 fairness and, 74–75 synthetic intellects as threats to, 72–75, 91–92, 199–200 wealth and, 109–10, 114–15.

The Costs of Connection: How Data Is Colonizing Human Life and Appropriating It for Capitalism
by Nick Couldry and Ulises A. Mejias
Published 19 Aug 2019

Continuously caching the social enables corporations and all forms of authority to gain the sense that the social world, or at least selected slices of it, can be continuously streamed just for them—not for their entertainment but to enable that world’s modulation or management in their interests. When the CEO of Shotspotter, makers of algorithmically processed surveillance mechanisms for the law enforcement sector, was asked to disclose his company’s data to the US public, he responded that it would be like “taking someone else’s Netflix subscription.”113 So social caching is more than an academic metaphor: it is the practice that de facto—and, increasingly, de jure—authorizes the privileged viewpoint on human life that corporate power claims for itself in the era of data colonialism.

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See also specific names of countries “reification,” 230n129 Rekognition (Amazon), 10 remote desktop surveillance, 64–65 reputation, platform management of, 130 Requerimiento (Spanish colonial document), 92–94; as analogy to Google EULA and Facebook SRR, 93–94; original purpose of, 92 “reserve army,” unemployed as, 61 Restrepo, Pascual, 238n117 RFID tags, 64 Richards, Neil, 179 Ricoeur, Paul, 253n10, 254n34 Rieder, Bernhard, 137 Rooney, Sally, xv Rose, Nikolas, 122 Rosenblat, Alex, 62 Rossiter, Ned, 39, 47 Rössler, Beate, 154, 165 Rotenberg, Marc, 177 Rouvroy, Annette, 127–28, 249n141 Russia, social quantification sector in, 55 sacrifice zones, 90 Safari (Apple), 48–49 Said, Edward, 77, 239n34 Salesforce, 65 Sammadar, Ranabir, 66 Sandvig, Christian, 132 Santos, Boaventura de Sousa, 201, 263n46 Saudi Aramco, 54 Scandia, 153 Schildt, Hakan, 153 Schneier, Bruce, xv, 23–24, 128, 135 Schüll, Natasha Dow, 171–72 seamfulness, Vertesi on, 198–201 seamlessness, Cohen on, 229n106 second-order control, 182–83 “second slavery,” 73–74 self: double consciousness of, 157; integrity of, 156–61, 197, 204–5; self-determination, 154–55, 252–53n10; Self versus Other, 239n34; space of the self concept, 156–57, 161–65, 167, 172, 178, 199 self-tracking: as autonomy illusion, 168–73; personal data appropriation spectrum of, 173–76; Quantified Self movement, 168, 171, 257n77; “situated objectivity” of, 256n70; as social knowledge, 128–29, 133; in workplace, 65–66, 153–54 Self-Tracking (Neff, Nafus), 257n77 Sen, Amartya, 201–2 sensors and sensing: biosensors, 141; body sensors, 171; GPS tracking, 29; sensing as model for knowledge, 8; for telematics, 65. See also self-tracking Shared Value, 135 sharing economy (gig economy), 13, 59–63, 108 Shilliam, Robbie, 74 Shotspotter, 134 Sidewalk Labs (Google), 150 Simpson, Leanne Betasamosake, xiv–xv, 90, 195–96, 204 Siri (Apple), 133 Skam (Facebook), 109–10 skin-embedded microchips, 172 Skinner, Quentin, 164 slavery, xvii–xviii, 4, 13, 72–76, 83, 106–7, 167, 225n37. See also historical colonialism smart devices, defined, 50 smart scheduling, 64 Smart Technologies (Hildebrandt), 260n142 Smith, Linda Tuhiwai, 209 Smythe, Dallas, 102 Snapchat, 11, 43, 236n58 Snapshot (Progressive), 145 Snowden, Edward, xvi social caching: defined, xiii; for social knowledge, 131–38; in social quantification sector, xv–xvi social factory, Autonomist concept of, 34, 231–32nn138–140 social knowledge, 115–51; as injustice, 150–51, 190–91; overview, 115–18; personalization, 16–17, 61, 132, 175–76; and power/power relations, xii, 41, 43–45, 155, 163–64; social caching for, xiii, xv–xvi, 131–38; social quantification and statistics field, 118–22; social quantification operations, 122–31; social relations and discrimination, 121, 143–49; and social sciences erosion, 138–43 social media: effect on society, xvi, 221n16, 221n18; inception of, and emerging social order of capitalism, 21; for monitoring work interactions, 65.

The Way of the Gun: A Bloody Journey Into the World of Firearms
by Iain Overton
Published 15 Apr 2015

This mass purchase of handguns has been done in the face of evidence that in most shootings involving the police no more than three shots are fired. Of course, many would say the American police are entirely justified in arming themselves to the teeth – look at what they have to contend with. ShotSpotter, a company that specialises in gunfire detection through urban listening monitors, looked at the data from forty-eight American cities over 2013. The company found that fewer than one in five gunfire incidents were reported to the police. In some neighbourhoods less than 10 per cent of gunfire was reported.34 Even with so many illegal shootings, the hyper-militarisation of America’s police force is still of concern.

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The company also found that in the summer months, gunfire increases, and that 42 per cent of all gunfire happened in June, July and August. In the worst place that they looked at, they found on average over eight bullets were shot every single day for an entire year within a single square mile; http://www.shotspotter.com/policy-implications 35. Others would contest this figure as being on the low side. As the Washington Post reported: ‘Officials with the Justice Department keep no comprehensive database or record of police shootings, instead allowing the nation’s more than 17,000 law enforcement agencies to self-report officer-involved shootings as part of the FBI’s annual data on “justifiable homicides” by law enforcement’; http://www.washingtonpost.com/news/post-nation/wp/2014/09/08/how-many-police-shootings-a-year-no-one-knows/; the website http://www.fatalencounters.org has an arguably more accurate figure and these numbers are quoted later in this book. 36. http://www.economist.com/blogs/democracyinamerica/2014/08/armed-police; http://www.smallarmssurvey.org/fileadmin/docs/A-Yearbook/2011/en/Small-Arms-Survey-2011-Chapter-03-EN.pdf 37. https://www.ncjrs.gov/pdffiles1/nij/grants/204431.pdf 38. http://billmoyers.com/2014/08/13/not-just-ferguson-11-eye-opening-facts-about-americas-militarized-police-forces/ 39. http://www.economist.com/news/united-states/21591877-when-pupils-get-trouble-silly-reasons-results-can-be-serious-perils 40. http://www.nytimes.com/2013/01/17/education/report-criticizes-school-discipline-measures-used-in-mississippi.html?

The Rights of the People
by David K. Shipler
Published 18 Apr 2011

For two years, it spit out false positives, mixed up men and women, and failed to lead to a single arrest, so it was finally abandoned. There’s nothing quite like a cop holding a mug shot after all.13 Not only sights but also sounds are being fed into police computers, with more accurate results. ShotSpotter, a system installed in a few American cities, can determine a gunshot’s location within ten to twenty feet by triangulating the noise received by sensors the size of coffee cans, which are concealed atop buildings in high-crime areas. (Gang members get it: They fired at technicians placing microphones in Los Angeles and Oakland.)14 At Washington, D.C.’s Joint Operations Command, a darkened room on the fifth floor of police headquarters, walls covered with huge screens depict jerky scenes from major streets and Metro stations, maps, TV news channels, and lists of recent crimes constantly updated.