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    What Stays in Vegas

    Page 33
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      Government regulation of data, 58–59, 186, 220, 243–246

      GPS tracking (mobile phone location data), 185–188, 239, 265

      Graepel, Thore, 99

      Graf, Steffi, 244–245

      Gramm-Leach-Bliley Act (1999), 65

      Grant, Hugh, 138

      Grant, Susan, 260

      Green, Shane, 225–226, 231–234

      Green Stamps, 23

      Griffin, Beverly and Robert, 127–130

      Griffin Book, 128–130, 136

      Griffin Investigations, 128–130

      Guess Who’s Coming to Dinner movie, 42

      Gupta, Ajay, 85–89

      Gupta, Vinod, 81–83

      Hagerty, Harry, 182, 184

      Hall, Marc, 47

      The Hangover movies, 37, 39, 217

      Harper, Jim, 242

      Harrah’s, 15(fig)

      engages Loveman as COO, 10–14

      financial losses during recession, 91

      WINet loyalty program, 27

      Harrah’s Atlantic City, 14–15, 16, 31

      Harrah’s Kansas City, 176, 179, 193–195, 217

      Hart, Patti, 18–19, 189–190, 216

      Harvard Berkman Center for Internet and Society, 263

      Harvard bomb threat, 263

      Harvard Business School (HBS), 8–12, 98, 187, 206, 220

      The Harvard Crimson, 97–98

      Harvey’s Lake Tahoe, 31–32

      Health care. See Medical data

      Health Insurance Portability and Accountability Act (HIPAA), 108, 244

      Hershiser, Orel, 245

      The Hidden Persuaders (Packard), 237

      High-limit rooms, 95, 198–199, 203

      Hinkley, William, 128

      Hispanics, marketing to, 87, 89

      Hoffman, Dustin, 36

      Holland, Rodney, 179

      Hong Kong, 187

      Hoofnagle, Chris, 242–243

      Hooley, Sean, 105(fig)

      Hooters Casino Hotel, Las Vegas, 128

      Horse racing, 199, 200

      Horseshoe Casino Cincinnati grand opening, 201–203, 204(fig), 205(fig)

      Horseshoe Casinos, 21–22, 174–175

      Howe, Scott, 8, 220–223, 244, 249, 250, 251

      HP (Hewlett Packard), 159, 160

      HTTPS Everywhere, 262

      Hughes, Howard, 42, 43

      Human Rights Campaign, 241

      Hushmail, 264

      Iamcatwalk.com, 164, 169

      IBM, 79, 82, 158, 260

      Identity theft, 245, 267

      Identity.com, 265

      IGT slot machines. See International Game Technology

      Illinois, 51, 144, 145, 148, 152

      Illinois State University, 145

      IMDB, 111

      Imperial Palace, 129

      Inc. Magazine, 169

      Incentives for customers to share personal data, 173, 180, 228, 242

      India, 9–10, 85, 89, 109–110, 227

      Indiana, 7, 246

      Inflection, 61–63, 64(fig), 66–67

      InfoSpace, 59

      InfoUSA, 83

      Inside Edition TV program, 155

      Instagram, 239

      Instant Checkmate, 68–74, 115, 117, 121–122

      Insurance

      auto, 171, 232, 234

      health, 108–109, 244

      life, 105

      Intel, 66

      Intelius, 50, 56–59, 68, 246

      Interactive Advertising Bureau, 169

      Interest groups as aggregated data, 19, 186

      Internal Revenue Service (IRS), 162

      International Game Technology (IGT), 18–19, 189, 216

      Internet

      changes meaning of public, 245

      enables display of mug shots and names, 142

      free services at the price of personal data, 240–243

      as non-transparent, 228

      online anonymity programs, 260

      privacy companies remove damaging reviews, 226, 229

      tools to enhance privacy, 261–263

      Internet advertising

      click fraud pollutes online ad traffic, 163–170

      online behavioral advertising, 157–159

      surfing patterns, tracking, 159–163

      unintended consequences, 248–249

      See also Google ads; Yahoo ads

      Internet erotica, 117–122, 166

      Internet Explorer, 262

      Intolerable Cruelty movie, 36

      Iraq War (2003), 57

      Irvine, California, 63

      Irving, Texas, 79, 151

      Italy, 83

      iView Systems, 131

      Ixquick, 264–265

      Jablon, Joshua, 76

      Jackson, Michael, 138, 245

      Jagger, Mick, 138

      Jain, Naveen, 57, 59

      Java software, 262

      JavaScript, 262

      Jernigan, Carter, 101

      Jobs, Steve, 232

      Johnson, Gerald, II, 87

      Jolie, Angelina, 47

      JPMorgan Chase, 252

      Jumptap, 186

      Kansas City, Missouri, 176, 179, 193, 217

      Kanter, Joshua

      background, 75–76

      on geographic segments, 217

      hired as Caesars’ personal data guru, 93–96

      revamps no outside data policy, 188–189, 210–214(fig), 253–254

      revamps Total Awards, 176–179

      on slot machines, 189

      Sunshine Test, 213–214(fig), 251

      on third-party access to customers’ data, 182–183

      Khuzami, Robert, 83

      Kibak, Kris, 69–73, 122

      Kiev, Ukraine, 58, 66–67

      King, Martin Luther, Jr, 137–138

      Kinsey Institute, 248

      Kivilis, Netta, 238–239

      Kosinski, Michal, 99–100

      Kostel, Daniel, 36–40, 171–172, 175, 176, 196–200

      Koster, John, 178

      Kristen Bright (imaginary Instant Checkmate spokesperson), 72, 115–122

      Kurspahic, Tarik, 231–234

      LA Times, 55

      LaBarba, Janet, 143–144, 150

      Ladies’ Home Journal, 172

      Laine, Frankie, 32

      Lake Tahoe casinos, 23, 31, 185–186

      Lansky, Meyer, 43

      LaRue, Eddie, 22, 32, 43–45

      Las Vegas, 2(fig), 5(fig)

      Boulevard, 4, 36, 209

      Clark County Recorder’s office, 47–49, 62–63, 244–245

      as data collection machine, 4–6

      post-9/11, 1–2

      See also Casinos

      Las Vegas Police, 134–135, 153–154, 245

      Las Vegas Sands Corporation, 216

      Lavabit, 264

      Lawsuits

      against casinos, Griffin, 129–130

      class-actions against data brokers, 59–60

      curtail security, personal data traffic, 130, 151–152

      against mug shot websites, 73, 154–155

      for privacy breaches, 111–112, 246

      Leighton, Robert, 258

      Leonsis, Ted, 232

      Lewis, Harry, 97–98, 118, 136

      Lexis, 48

      LexisNexis, 267

      License plate recognition, 132, 247–248

      Lillian, Donna, 86–87, 88

      LinkedIn profiles, 104, 107, 227, 265

      List Service Direct, 89

      Localytics, 187

      LocatePlus Holdings Corporation, 60

      Lombardi, Rick, 65

      Los Angeles, 36, 48, 49, 117, 169, 175, 226

      Loveman, Gary, 13(fig), 205(fig)

      background, 4–14

      on casino perks and incentives, 172, 197–198

      cell phone ads based on location data, 187

      on changes due to financial crisis, 91–92, 175

      on data analytics’ strengths, limitations, 10–11, 18, 214–216

      on debt issues vs. operations, 203–206

      on direct marketing, 76

      on gathering personal data, targeting, 35,
    77–78, 90, 174, 217–219

      on Total Rewards revamp, 179

      on usability of photo recognition, 132–133

      Lowrey, Thomas, IV, 73

      Loyalty programs

      of airlines, 24–25, 219, 232

      cards used for security and surveillance, 124

      compared to mobile phone customer tracking, 188

      data not shared with others, 250–251

      early slot machine point tickets, 23

      enable collection of personal data, 17–18

      Godiva, 173

      incentives for customers to share personal data, 171–173

      stolen cards scheme revealed by Facebook, 135–136

      See also Total Rewards loyalty program

      LSSiDATA, 65

      Luxor, 209

      Macau operating licenses, 214–216

      Mail-order businesses, 77–78

      Malaysia, 246

      Malware, 166, 262

      Mandalay Bay Hotel, Las Vegas, 84, 209

      Manes, Justin, 168

      Manhattan, 31, 78, 149, 163, 227

      Map Network, 231

      Marcus, Richard, 129

      Marijuana, 106, 107, 144–148

      Marriage and divorce data, 5–6, 47–49, 63, 245

      Marsden, M. K., 244

      Martin, Dean, 21

      MaskMe, 264

      Mason, Matthew, 243

      Massachusetts Group Insurance Commission (GIC), 102

      Massachusetts Institute of Technology (MIT), 7, 16, 101, 102, 128–129

      MasterCard, 266

      Maxvisits.com, 168

      McElroy, James, 94–96

      McKinsey & Company, 94–95

      Media6Degrees, 159

      MediaMorphosis, 89

      Medical data

      collected by data brokers, 244

      imported into consumers’ own managed vaults, 253

      names revealed, 101–108

      of PGP volunteers, 247, 259

      Memphis, Tennessee, 11, 31

      Merchant-funded rewards, 183

      MGM Grand Hotel, 3, 77

      MGM Resorts, 77, 130, 135, 182–188

      Microsoft, 98, 99, 159, 162, 220

      Milgram, Stanley, 98

      Miller, Rob, 50

      Mirage Hotel and Casino, 7–8, 186, 216

      Mirman, Rich, 27–30, 94, 188, 216, 221–222

      Misaldo movie, 231

      Mistree, Behram, 101

      MIT blackjack card counters, 128–129

      Mob figures and mob influence, 43–45, 130, 132

      Mob Museum, 137–138

      Mobile data, 185–186, 265

      Moglen, Eben, 260

      Monahan, Brian, 51, 54–62, 67–68, 265

      Monahan, Matthew, 51–62, 65–68, 74, 244, 265

      Monet, Yvette, 187

      Monte Carlo, 7

      Montgomery Ward, 78

      Moore, James, 131

      Moore, Les, 151

      Moral and ethical considerations of data brokering, 40, 50, 152, 188, 220

      Moscow, 110

      Movie rating system of Netflix, 109–111

      Mug shots

      background, 137–138

      displayed by Busted!/bustedmugshots.com, 140–144, 149–155

      Janet LaBarba case, 143–144, 150

      Paola Roy case, 138–140, 150

      taken of Kyle Prall, 146, 149(fig)

      used in Instant Checkmate ads, 72–74

      Multicultural marketing, 86, 89

      Multi-mailing company, 78

      Munger, Charlie, 52, 53

      Mydex.org, 234

      Myinfosafedirect.com, 234

      MyLife.com, 49–50, 59–60

      MyPersonality, 99, 101

      MyPOQ, 262

      Names as valuable data, 85–89, 170, 173–174

      Narayanan, Arvind, 109–111

      Native Americans, marketing to, 87, 88

      Nebraska, 52, 81–82, 84, 162

      Nebraska Game and Parks Commission, 162

      Nersesian, Bob, 129

      Netflix, 71–72, 109–112

      Nevada Legal News, 43–44

      Nevada State Gaming Control Board, 127

      New Jersey, 31, 75–76, 175

      New Orleans, 11

      New York, 61, 93–94, 149, 157–159, 169

      New York Times, 112, 160, 162, 246, 261

      New York University, 158

      New York-New York casino, Las Vegas, 134, 135, 209

      New Zealand, 246

      Newman, Paul, 47

      Newspaper archives, 42–45

      Nike (nike.com), 164, 231

      9/11 attacks. See September 11, 2001, attacks

      Nokia, 162, 231–232

      Nonprofit organizations, 59, 79, 80–81

      Norlin, Chase, 167–169

      Norton, David, 12–13, 30–32, 91–92, 94

      NoScript, 260, 262–263

      NSA. See US National Security Agency

      Obama, Barack, 3, 86, 88

      Ocean’s Eleven movie, 21, 124

      Ocner, Daniel, 89

      Odds

      better in high-limit rooms, 198

      for blackjack vs. slot machines, 175

      Off Pocket, 265

      Ogilvy and Mather advertising firm, 235

      Ohio, 78, 201

      Omaha, Nebraska, 52–53, 66, 83, 84

      Onion Browser, 263

      Online behavioral advertising, 157, 159–160, 164

      Online surveys, 80, 84, 88, 90, 103–104, 242, 248

      Open records laws, 141, 151

      Opportunity segments, 27, 29(chart)

      Opting out of personal data sharing

      Acxiom’s AboutTheData files, 222–223

      for credit cards, financial institutions, 266

      from data brokers, 252, 267–268

      multiple removals vs. one-stop removals, 246

      from online advertisers, 263

      of PeopleSmart, 67

      search engine results, 155

      of sharing gambling transaction data, 182

      Oracle, 66

      Orbot, 263

      The Outfit, 44–45

      Outside data

      availability to consumers, 252

      Caesars’ policy against use, 40, 74, 90

      Caesars’ policy revamped, 210–214, 253–254

      Ownyourinfo.com, 234

      Packard, Vance, 237

      Palo Alto, California, 56

      Pancer, Andrew, 164

      Papp, Jamie, 201

      Parentingnews.com, 164

      Pasadena, California, 49

      Patient Privacy Rights Foundation, 108

      Peel, Deborah, 108–109

      Pennsylvania, 78, 93, 133

      People search sites, 56–63, 66–67, 239, 267

      Peoplefinders.com, 50

      PeopleSmart

      cell phone numbers not listed, 66–67

      compared to Instant Checkmate, 69, 72

      differentiated by respecting privacy, 50, 61–63

      Perlich, Claudia, 157–166, 169, 222

      Permissions granted/not granted

      to collect personal consumer data, 40, 85, 219–223, 228

      under Fair Credit Reporting Act, 73–74

      for patients’ health records, 108

      to send email messages, 79

      for tapping into social media profiles, 99, 101

      to use persons’ images, 117, 120, 122

      Personal data

      abuse of, 99, 235, 237–238, 252

      allowing individuals to be identified, 101–107

      Caesars’ policy of informing customers, 36, 39, 171, 249

      controlled by consumers (see Control of personal data by consumers; Privacy companies)

      gathered by the Mob, 43–45, 46

      gathering procedures, 33–34

      integrated into future slot machines, 189–190

      limitations, 252–253

      from online surveys, 84

      privacy risks, 241, 259

      used for individualized targeted offers, 39, 77, 217–219

      See also Data brokers; Pu
    blic records as personal data sources

      Personal data vaults, 225–230, 234, 243, 253, 268

      Personal Genome Project (PGP), 103–107, 246, 259

      Personal.com

      background, 225–226, 229–230

      considers credit card without gathering personal data, 266

      encrypts user data, sharing only with permission, 232–233, 268

      Fill It browser plug-in, 234

      Pesci, Joe, 43

      Pfahler, Mike, 133–134

      PGP. See Personal Genome Project

      Pharmacies selling personal data, 108

      Phillips, John, 88–89

      Phillips, Tom, 162–163, 166–167

      Phone book information, 43, 63, 78, 80–82, 262

      Photo recognition technology, 5, 127, 131–134, 253, 260

      Pilant, Darrell, 178

      Pinker, Steven, 105–106

      PlayStation, 242

      Pleitez, Emanuel, 59, 225–226, 239

      Poitier, Sidney, 42

      Poker, 129, 179, 201

      Poland under Communism, 99–100

      Political campaigns using personal data, 88–90, 246, 251

      Political data, 80, 85, 99, 222–223

      Porn sites, 76, 166, 228–229

      Prall, Kyle, 154(fig)

      background and criminal record, 144–149(fig)

      launches, runs, mug shot site, 140–144, 149–155

      views Acxiom file, 222

      Predictive modeling, 158, 161

      Prepaid cashless cards, 184–185

      Presley, Elvis, 42, 43, 47

      Presley, Priscilla Ann Beaulieu, 42

      Price, Melissa, 201

      Prime Access, 89

      Prince Harry, 243

      Privacy

      and mobile phone location tracking, 186, 188, 190

      requires consumer awareness, management, 242

      sacrificed for free services, 240–243

      standards or violations using Internet, 100–101

      See also Control of personal data by consumers

      Privacy companies, 225–235, 245

      Privacy policies of companies

      Google, 263

      long, confusing statements, 103–104, 250

      MyLife.com, 60

      nutrition-label-style notices, 250, 260

      tracking revealed in fine print, 162

      Privacy protection laws in other countries, 246

      Privacy protection methods and strategies, 246, 260–268. See also Government regulation of data

      Privacy rights, 107–113, 249

      Privacy Rights Clearinghouse, 266, 267, 268

      Privacy risks exam of PGP, 103–104

      Privacy tools, 235, 260–261, 268

      Privacychoice.org, 265

      Private investigators, 42–45, 46

      Private WiFi, 262

      Privowny.com, 264

      Productivity Paradox of computers, 10

      Profiles of gamblers

      of big spenders, 32

      of Harrah’s top-tier customers, 193–195

      of repeat customers, 31, 175

      Protecting Your Internet Identity (Claypoole), 248

      Public records as personal data sources

      background, 42–45

      bulk access for data brokers, 244–245

      digitization, 46–49

     


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