Privacy issues
data leakage, 20–21
employee monitoring, 177
and geo-social apps, 19–22
government collected data, 220–21
health data sharing, pros/cons, 46–48
informational determinism concept, 241
matchmaking sites, 155–56
neighborhood watch network, 215–17
public knowledge, importance of, 212–13, 221–22, 238–42
smartphone data, limiting, 29
Probability. See also Prediction
Bayes theorem, 23–25
Procter & Gamble, radio frequency identification (RDIF) tag use, 115–16
Product sales, drivers of, 106
Project Exile, 187–88
ProMED-mail, 57
PubMatic, 156
Pythagoras, 49–50
Q Sensor, 44
Quantified Self (QS), 32–45. See also Self-tracking
elements of, 32–33
Quantified Self Toronto, 33–34
Quarantine, origin of term, 49–50
Radio frequency identification (RDIF)
components of, 7
customer behavior tracking with, 115–16
data trail, creating with, xv
scope of use of, 6–7
Ramakrishnan, Naren, 196–98
Rebello, Sanjay, 138
Recommendations, Netflix, 87–89, 97–99
Reinstein, John, 204
Relationships
health, measurement device, 174–75
longevity, factors in, 161, 179–81
marital communication, 178–79
matchmaking. See Matchmaking/dating
stress test of, 179–81
Rewards programs
airlines, 110
gambling casinos, 109–13
grocery stores, 117–18
Romney, Mitt, 170–71
Rosin, Hanna, 189
Rudder, Christian, 156, 158
Rudin, Cynthia, 14
Rule-induction algorithms, 190–91
RunKeeper, 32
Saatchi & Saatchi, 103–9, 128
Sadilek, Adam, 25–29, 65–66
Saffron Technology, 236–38
Salathe, Marcel, 59–60
Sam’s Club, 118
Sandia National Laboratories, 148
Satellite Sentinel Project (SSP), 199
Scientific method, 78
Scott, A. O., 96
Search engines, Wolfram Alpha, 39–40
Seismography, earthquake prediction, 2–4
Self-tracking, 32–45
biophysical tracking, 31–33, 38–39, 44–45
devices to compile data, 42–45
historical view, 34–37
of inside-view, 37, 40–42
for lifestyle management, 43
personal conversations, 174–75
for self-improvement, 33–37, 40–41
Semi-Automated Business Research Environment (SABRE), 110
Senior, Carl, 125
Sensors
to detect ammonia/explosives, 8
for eavesdropping, 8
environmental disaster information, 10–14
radio frequency identification (RDIF), 6–7
Sensory data, elements of, xv–xvi
Sentient City Survival Kit, 217
Serendipity, 163–65
Serotonin-based personality, 172–73
Shaker, Steven, 231
Shepard, Mark, 217
Shook, Robert, 111
ShotSpotter, 194
Silver, Nate, 4
Silverman, Lauren, 166
Singer, Natasha, 121
Singles in America survey, 173–74
Slashdot, 160
Smartphones
advertisers, connecting to users, 119–20
geo-social apps, 19–22, 165–66
as Internet of Things driver, 16
location data, limiting on, 29
location predictability based on, 25–30
location-tracking of, 17–20
neighborhood watch network, 213–17
as shopping buddy, 117
Smith, Tracy, 31
Snowden, Edward, 209, 210
Social networks. See also individual social media by name
connection tracking system, 219–20
geo-social apps, 19–22, 165–66
online, and intelligence information, 198
Walmart, use of data, 126–27
weak versus strong ties, 123
Sociometer, honest signals, 167–72, 174
Socrates, 133
Sonar app, 19
Spacey, Kevin, 89
Speech pattern, mood prediction on, 44
Spencer, Roy, 68–70
Stagg, James, 71
Status theory, and matchmaking services, 157–58, 160–61, 167
Stella, Frank, 103
Stereotype threat, 134–36
Strauss, Lewis, 72
Stress
reactions, and health, 41–42
test, of relationships, 179–81
Supramap, 55–57
Takafuji, Takeya, 162–63
Target, big data used by, xiv
Telemetry, xiv–xvi
Amazon reader-behavior analysis, 99–100
meaning of, xiv–xv
Netflix recommendation engine, 87–89
power and scope of, xv–xvi
Television, optimized TV, 89
Terrorism prevention. See Airport security; Government surveillance; Intelligence activities
Terrorist Identities Datamart Environment (TIDE), 220
Testosterone-based personality, 173
Tether, Anthony, 238
Texas Virtual Border Watch, 214
TexTrace, 7
Thampi, Arun, 21
Thiel, Peter, 218
Thrun, Sebastian, 138, 148–49
Tictrac, 42–43, 127
Tinder, 166
Topol, Eric, 58
Total Information Awareness (TIA), 237–38
Total Weather Insurance (TWI), 84–85
Transportation Security Administration (TSA), 202–7, 210
Traumatic events, as relationship stress test, 179–81
Tupes, Ernest, 173
Turow, Joseph, 105–6
Twitter
Ailment Topic Aspect Model (ATAM) study, 61–67
cigarette smoking study, 108–9
geo-social apps, 19–22
Ubiquitous computing
as Internet of Things, 6–17
meaning of, 6, 238
Udacity, 138, 149
Unconscious mind, honest signals, 167–72
U.S. Census, 119
Vedic astrology, matchmaking in, 152–53, 182
Verizon, advertisers, connecting to users, 119–20
Verleysen, Michel, 18
Victimology, 223
Virus sequencing. See Flu detection
Viser, Lisa M., 44
Visualization, 233–34
Von Neumann, John, 72–74
Wagner, Wolfgang, 68–70
Walmart
average customer, profile of, 118
eValues rewards program, 117–18
radio frequency identification (RDIF) tag use, 115–16
social network data used by, 126–27
store of the community individualization program, 115–16
Wang, Becky, 104, 106, 108, 128
Weather and climate prediction, 68–86
Bergen meteorology school, 71
climate insurance, 80–87
computers developed for (1945–50s), 72–75
controversy related to data, 68–70
difficulty of, 75–78
of global warming, 69–70, 74–77
political roadblocks, 70, 77, 79–80
during World War II, 70–72
WeatherBill, 81
Web of trust system, 159
Weinberg, Chuck, 90
Weiser, Mark D., 5–6, 238
Wierenga, Berend, 90
WikiLeaks, 199, 209
Wikipedia, 160
Wilbanks, John, 46–47
Willis, Larry, 204
Wilson, Chris, 134
Wilson, James Q., 184
Winds of Fukushima, 10–11
Wolf, Gary, 33
Wolfram, Stephen, 39–42, 44, 96
Wolfram Alpha, 39–40
Women
dating apps use by, 166
stereotype threat and learning, 134–36
Workplace
accidents, prediction of, 176–77
employee monitoring issue, 177
project failure prediction, 177–78
World of Warcraft, 211–12
World War II, weather prediction during, 70–72
Wraga, Maryjane, 135–36
WrongDiagnosis.com, 63
Yagan, Sam, 166, 174, 181
Yelp, 20
Yogananda, Paramahansa, 152, 182
Zacks, Jeffrey, 232
Zhang, John, 94
Zimmerman, George, 215
Zip code, for customer info, 118–19
Zollman, Dean, 138
Zuckerberg, Mark, 121
Zworykin, Vladimir, 72–73
The Naked Future Page 32