by Adam Tanner
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