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What Stays in Vegas

Page 32

by Adam Tanner


  Nagle, James. “Trading Stamps: A Long History,” New York Times, December 26, 1971.

  Nobel, Carmen. Why We Blab Our Intimate Secrets on Facebook. Harvard Business School Working Knowledge, December 10, 2012.

  Ohm, Paul. “Broken Promises of Privacy: Responding to the Surprising Failure of Anonymization.” In UCLA Law Review 57 (2010), 1701.

  PricewaterhouseCoopers LLP. Transforming Healthcare Through Secondary Use of Health Data, 2009.

  Reidenberg, Joel R. “Resolving Conflicting International Data Privacy Rules in Cyberspace.” In “Symposium: Cyberspace and Privacy: A New Legal Paradigm?” Stanford Law Review 52, no. 5 (May 2000), 1315–1371.

  Schwartz, David. Seeking Value or Entertainment? The Evolution of Nevada Slot Hold, 1992–2009, and the Slot Players’ Experience. Occasional Paper Series 1. Las Vegas: Center for Gaming Research, University Libraries, University of Nevada Las Vegas, 2010.

  Schwartz, Paul M. “Property, Privacy, and Personal Data.” In Harvard Law Review 117, no. 7 (May 2004), 2056–2128.

  Shaw, Jonathan. “Exposed: The Erosion of Privacy in the Internet Era.” In Harvard Magazine, October 2009.

  Solove, Daniel J., “Access and Aggregation: Public Records, Privacy and the Constitution.” In Minnesota Law Review 86, no. 6 (2002).

  Solove, Daniel J., and Chris Jay Hoofnagle. “A Model Regime of Privacy Protection.” GWU Law School Public Law Research Paper No. 132; GWU Legal Studies Research Paper No. 132, April 5, 2005.

  Stein, Joel. “Data Mining: How Companies Now Know Everything About You.” In Time Magazine, March 10, 2011.

  Sweeney, Latanya. Patient Identifiability in Pharmaceutical Marketing Data, Data Privacy Lab Working Paper 1015. Cambridge, 2011.

  ———. Discrimination in Online Ad Delivery, at http://dataprivacylab.org/projects/onlineads/1071-1.pdf, January 28, 2013.

  Turdean, Cristina. Computerizing Chance: The Digitization of the Slot Machine (1960–1984). Occasional Paper Series 15. Las Vegas: Center for Gaming Research, University Libraries, University of Nevada Las Vegas, 2012.

  Wall Street Journal. “What They Know” series and other reporting.

  INDEX

  Abine

  form-filling plug-in, 268

  MaskMe, 264

  opt out service, 245–246, 267–268

  technologies of privacy tools, 261

  Aboutmyinfo.org, 104

  AboutTheData.com, 221–223, 267

  Abstractors, 47–48

  AccuData, 63

  Accurint, 267

  Acquisti, Alessandro, 260–261

  Acres, John, 25–26, 190–191(fig), 222

  Acxiom

  AboutTheData, 221–223, 267

  considers paying users for data, 235

  consumers see files, 219–223, 252

  as data broker, data appender, 9, 63, 173, 186

  favors regulation, 244

  sells information to casinos, 90

  Adam & Eve adult stores, 228–229

  Adblock Plus, 260, 262

  Adelson, Sheldon, 216

  Adler, Jim, 50, 100

  Adobe Flash, 262

  Advantage players, 127, 129–130

  Advertising on mobile devices, 163, 186–187

  African Americans, 76, 88

  Agassi, Andre, 245

  Ahn, Tony, 135–136

  Airline frequent flyer/loyalty programs, 17, 24–25, 38, 213, 232

  Alba, Diana, 244–245

  Alcohol, 76, 99, 100, 124

  Alliance Data, 79

  Alliant, 251

  AlphaBird, 167–169

  Amazon, 35, 71–72, 100, 212, 248

  Amazon MYHABIT, 238

  American Airlines, 9–10, 17, 24, 162

  American Business Information, 82

  American Express, 266

  American Heart Association, 87

  American Name Society, 87, 88

  American Student Marketing, 76, 241

  America’s Most Wanted TV show, 153

  Ancestry.com, 62

  Anonymizer.com, 261–263

  Anonymous (hacker group), 264

  AOL search history data release, 112

  Apollo Global Management, 91

  Archives.com, 62, 66

  ARIA Resort and Casino, 77, 123–124, 125(fig), 133, 135–136

  Aristotle, 88

  Arizona, 195

  Arrest booking photos. See Mug shots

  ASL Marketing, 76

  Asterisk, 260

  AT&T, 81

  Atlantic City casinos, 14–16, 31, 175, 185–186, 195, 205, 217

  ATMs, 83, 93, 181–182

  Auerbach, Dan, 226

  Aunt Jemima, 72

  Austin, Texas, 108, 140–142, 149, 153–155

  Authentic8 Silo, 262

  Bacchanal restaurant, 36

  Background check websites, 46, 48, 69–74

  Bagnall, Andy, 89, 90

  Bally’s, 174

  Bank of America, 183

  Bankruptcy, 6, 117, 129–130, 206

  Banks

  card-issuing, 183

  purchasing personal data, 47, 80

  share data from users’ accounts, 234, 266

  Beat the Players (Nersesian), 129

  Behrman, Clay, 183

  Bell, Gordon, 268

  Bell, Tom, 246

  Bellagio, 17, 37, 77, 133, 197, 200, 209

  Bellevue, Washington, 57

  Benefits to customers from personal data gathering, 31, 38–39, 171, 176, 249, 253

  Bentley University, 102, 239

  Berkshire Hathaway, 52

  Berlin Wall, 158, 222, 231

  The Better Angels of Our Nature (Pinker), 105

  Betty Crocker, 72

  Big data

  generated from cell phones, 231–232

  helps Caesars, 112, 171–173

  potential human rights backlash internationally, 100

  power and potential, 214, 238

  for segmenting customers, 85–86, 89

  Bing, 66

  Binion, Benny, 21–22, 32, 33, 195

  Black list of excluded gamblers, 127

  Blackjack

  compared to slot machines, 175

  played by Kostel, 36, 37, 172, 197–200

  Blackjack card counters from MIT in 1990s, 128–129

  Blackphone, 265

  Bond, James, 7, 162

  Bonds, Barry, 138

  Booz Allen Hamilton, 27

  Bosnian war, 230–231

  Botnet traffic, 168, 169–170

  Boushy, John, 11–12

  Bravo, Adam, 77

  Brierley, Hal, 24–25, 79, 80

  Brilliantriches.com, 167

  Britain, 7, 99, 174, 243

  Brownstein, Peter, 87–88

  Browser fingerprinting, 251–252, 261

  Buffett, Warren, 52–53, 66

  Busted! 140–144, 149–155

  Busted! Grid (bustedgrid.com), 153, 154

  Busted! In Austin newspaper, 141–142

  Bustedmugshots.com, 142, 143–144, 150–151, 222

  Cable operators, 65, 83, 113, 175

  Caesars Entertainment

  purchased by Harrah’s, restructured, 4, 40

  cell phone apps, 185–186

  debt load, 6, 67, 74, 91, 203–206

  direct mail targeting clients, 76–77

  policy of no outside data, 40, 210–214

  during recession, 94–95, 175

  tracks loyalty members’ spending, 174–175, 181

  use of personal data, 16–17, 130, 249

  See also Total Rewards loyalty program

  Caesars Palace

  background, 4–5, 36–37

  cash handling costs, 183–184

  Colosseum, 216

  comps top-tier gamblers, 193, 200

  customers choose to share personal data, 36, 39, 171–173, 249

  Forum Shops, 198–199

  high-limit room, 198–199

  California State Univers
ity, Monterey Bay, 70

  Caller ID, 54, 56–57, 58

  Cambridge, Massachusetts, 102

  Cameras for public and casino surveillance, 123, 125–127, 132–134, 136, 184, 202

  Canada, 99, 131, 173

  Cancer, 76, 84, 158, 244

  Card counting, 127, 128–130, 134

  Card readers for slot machines, 25–26, 190

  Carnegie Mellon University, 260

  CAS Inc., 84

  Case, Steve, 112, 232

  Cash, 181–184

  Casino movie, 43, 44

  Casino Share Intelligence (CSI), 182

  Casino staff

  explain Total Rewards changes, 179

  at opening of Horseshoe Cincinnati, 201–203

  surveillance of, 133–134, 183–184

  Casinos

  cashiers cage, 126, 133, 183–184, 198

  change from locally autonomous to centralized, 94–96, 195–196

  comps and perks, 193, 197–198, 200

  count rooms, 133, 183–184, 202

  high-limit rooms, 95, 198–199, 203

  surveillance rooms, 123–126, 133, 201

  Catalina Marketing, 187

  Cato Institute, 242

  Celebrity names, 41, 47–48, 67, 245

  Cell phones

  apps and advertising, 163, 185–188, 265

  generate big data, 231–232

  numbers, unpublished, 54, 61, 65

  Charlotte, North Carolina, 248

  Chase, Chevy, 41–42, 46–47

  Chase.com, 164

  Cheaters. See Thieves casinos want to exclude

  Cheez Whiz, 63

  Chicago, 44, 45, 47, 174

  China/Chinese language, 18, 86, 89, 215

  ChinaFlix.com, 164

  Church, George, 103–104, 246–247

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

  Claypoole, Ted, 248, 250

  Click fraud, 163–170

  Clinton, Bill, 82–83

  Clinton, Hillary, 3, 82–83

  Clooney, George, 36

  Cloud-based servers for customer data, 210–211

  Cocaine, 107, 145

  Cocoon, 262

  Cold Stone Creamery, 185

  Cole-Schwartz, Michael, 241

  Collegeshortcuts.com, 51

  Columbia Law School, 260

  Commodore Corporation, 81–82

  Consumer Federation of America, 260

  Consumer protection laws, 242–243, 246. See also Privacy protection methods and strategies

  The Control Group (thecontrolgroup.com), 70–71

  Control of personal data by consumers, 220–223, 231–235, 240, 253, 259–260

  Cook, Tom, 193–196, 217

  Cookies (digital), 160–161, 162, 229, 251–252, 261

  CoreLogic, 63, 65

  Cortés, Hernán, 56

  Cosmopolitan Hotel, 197, 200

  Costa Rica, 153

  CounterMail, 264

  Credit cards and credit card companies

  advances for gamblers reaching limits, 181

  vs. cash, 182–185

  companies as Acxiom’s clients, 80, 220

  opting out from targeting, 266

  payments for mug shot sites, 155

  transactions as personal data, 39, 266

  Credit header data, 65, 80

  Crime Stoppers conference, 154

  Criminal records sold to public, 3, 68, 72

  Cruise, Tom, 36

  Cruise ship voyages, 193, 196–197

  Cullen, Todd, 235

  Cullotta, Frank, 44–45

  Culnan, Mary, 239–240

  Customer loyalty, 11, 14–16, 217.

  See also Loyalty programs

  Danforth, Holly, 34

  Daniels, Calvin, 207

  Dark Mail Alliance, 264

  Data analytics

  mastered by Caesars, 10–11, 18

  opting out from, 266

  strengths and limitations, 203–206, 214–216, 252

  Data appenders, 173–174

  Data brokers

  introduced, 19–20

  block consumers from seeing own information, 219–220

  buy, rent, from data wholesalers, 62–63, 65

  and Caesars’ policy of no outside data, 40, 74

  with direct marketing name lists, 76, 83

  investigated by FTC, Congress, 72–73, 244

  opting out processes, 267

  selling medical data, 108, 244

  sued for legal violations, 58–60

  Data dossiers

  of casino customers, 193–200

  detailing personal information, 19, 68, 106, 267

  information withheld from consumers, 219–223, 252

  for marketing and risk mitigation, 80–81

  removal processes, 246, 267

  Data scientists, 111, 158–159, 163–167

  Data Square, 173

  Data vaults. See Personal data vaults; Privacy companies

  Data wholesalers, 62–65, 222

  DataBanker.com, 268

  Database mining

  origins and described, 77–113

  by Caesars, 6, 200

  predictive, 158

  DatabaseUSA, 83

  Datacoup.com, 234

  Dating websites, 69–70, 120, 238

  Davis, Chad, 228

  Davis, Phil, 174

  Davis, Sammy, Jr., 21

  Dawson-Brown, Claire, 151–152

  De Niro, Robert, 43

  Dead Souls (Gogol), 84

  Dean, Gabriel, 104

  Democratic Party, 3, 80

  Demographic information

  from Acxiom, 80

  changed to thwart privacy invasion, 106

  used by data appenders, 173–174

  of video game and Internet generations, 189

  without financial details, 211

  Department stores, 78, 113, 132

  Desert Inn, 42

  Detectives. See Private investigators

  Digital Advertising Alliance, 263

  Digital Marketing Works, 186

  Dion, Celine, 197, 216–217

  Direct Marketing Association (DMA), 61, 84–85, 89–90, 173, 251

  Direct marketing/direct mail marketing

  compared to online ad targeting, 163

  opting out, 266

  as term, 237–238

  uses sophisticated segmenting, 75–77, 84–90

  Disconnect.me, 160–161(fig), 262

  Discover credit cards, 184

  Discrimination based on personal identity, 107–108

  Disney World, 219

  DNA information shared, 103, 104, 110, 247, 259

  Do Not Call Registry, 246, 266

  DocuSearch, 69–74

  DoNotTrackMe, 262

  007.com, 162

  DoubleClick, 160

  Douglas, Kirk, 47

  Downey, Sarah, 245–246, 267

  Dowty, Scott, 181–182

  Dropbox, 268

  Dstillery, 159–167, 170, 248

  DuckDuckGo, 264–265

  Dunn, JoAnne Monfradi, 251

  Dyson, Esther, 226

  East Germany, 157–158, 219, 231

  eBay, 160, 162

  The Electric Horseman movie, 36

  Electric Reliability Council of Texas, 140

  Electronic Arts, 66

  Electronic Frontier Foundation, 226

  Electronic Privacy Information Center, 268

  Ellis, Brandi, 178

  Email, 79, 263–264

  Emerge Digital, 169

  Epsilon Data Management, 24, 63, 79, 80, 244, 252

  Equifax, 63, 266

  Eskin, Barbara, 172–173

  Ethnic and racial group targeting, 76, 85–90, 102

  Ethnic Technologies, 87–89

  European Union, 246

  Excluded Person List, 127

  Experian, 63, 173, 219, 252, 266

  Facebook

  created, 97�
��98

  as ad firm, 160, 162

  allows users to download personal data, 254

  Instant Checkmate arrest records ad, 72

  “likes” suggest personal information, 99–100, 248

  privacy levels, 265

  reveals personal data clues, 98–99, 134–136, 212–213

  Facial identification. See Photo recognition technology

  Fair Credit Reporting Act, 59, 73–74

  Family Circle, 172

  FBI fingerprint and criminal history records, 70, 150

  Federal Trade Commission (FTC)

  complaints against Instant Checkmate, 72–74

  fines Spokeo, 59, 239

  scrutinizes data brokers, 85, 244, 246

  Fertik, Michael, 226–229, 234, 248

  Feuer, Jack, 186

  Field, Don, 141

  Fifth Street Gaming, 133

  FileThis, 234

  Fill It browser plug-in, 234, 268

  Financial crisis of 2008

  changes forecasting models, 175

  impact on Caesars, 6, 67, 74, 91–93

  impact on Las Vegas, 20

  Fine, Randy, 32, 206

  Firefox, 262

  Flickr, 150

  Florida, 17, 47, 63, 73, 83, 138–140, 228

  Flynn, Tom, 131

  Flynt, Larry, 153

  Fonda, Jane, 47

  Ford, Gerald, 41–42

  Foursquare, 239

  Foxwoods Resort Casino, Connecticut, 93

  FoxyProxy, 262

  France, 7

  Fraud, 60, 80. See also Click fraud

  FTC. See Federal Trade Commission

  Fulloffashion.com, 167

  Fulltraffic.net, 168, 169

  Fundwiser.com, 167

  Future of Privacy Forum, 239

  Gamble, Fred, 107

  Gambling addiction, 35

  Gandolfini, James, 36

  Gantt, Leon, 219

  Gates, Bill, 98

  Gaydar, 100

  Geico insurance, 234

  GenealogyArchives.com, 61–62

  Gerber, Larry, 241

  Gibson, Mel, 137–138

  Global Cash Access (GCA), 181–183

  Gmail, 254, 263–264

  Godiva, 173

  Gogol, Nikolai, 84

  Golden Nugget Casino, 43

  Good Housekeeping, 172

  Goodman, Oscar, 1–2, 32, 36, 43, 240, 241(fig)

  Google

  changes user rules, 240

  privacy policy, 263

  rankings of negative postings, mug shots, 155, 227

  as search engine, 70, 264–265

  Google ads

  settings, 263

  AdWords, 54–55

  allows users to copy Gmail and calendar data, 254

  Instant Checkmate arrest records ads, 72–74

  of PeopleSmart, 66

  Google Voice, 260

  Government agencies selling to data wholesalers, 62–63, 65, 67

 

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