NO. 13-1339
`
`
`In the Supreme Court of the United StatesIn the Supreme Court of the United States
`In the Supreme Court of the United States
`
`In the Supreme Court of the United StatesIn the Supreme Court of the United States
`
`SPOKEO, INC.,
`
`v.
`
`Petitioner,
`
`THOMAS ROBINS, INDIVIDUALLY AND ON
`BEHALF OF ALL OTHERS SIMILARLY SITUATED,
` Respondent.
`
`On Writ of Certiorari to the United States
`Court of Appeals for the Ninth Circuit
`
`BRIEF OF AMICI CURIAE STATES OF MASSACHUSETTS,
`CONNECTICUT, DELAWARE, THE DISTRICT OF COLUMBIA,
`HAWAII, ILLINOIS, MAINE, MARYLAND, MINNESOTA,
`MISSISSIPPI, NEW MEXICO, NEW YORK, OREGON, AND
`WASHINGTON IN SUPPORT OF RESPONDENT
`
`MAURA HEALEY
` Attorney General of Massachusetts
`SARA CABLE*
`FRANCESCA L. MICELI
` Assistant Attorneys General
`Office of the Attorney General
`One Ashburton Place
`Boston, MA 02108
`(617) 727-2200
`sara.cable@state.ma.us
`*Counsel of Record for Amici Curiae
`
`(Additional Counsel on Inside Cover)
`
`Becker Gallagher · Cincinnati, OH · Washington, D.C. · 800.890.5001
`
`
`
`
`In the Supreme Court of the United StatesIn the Supreme Court of the United States
`In the Supreme Court of the United States
`
`In the Supreme Court of the United StatesIn the Supreme Court of the United States
`
`SPOKEO, INC.,
`
`v.
`
`Petitioner,
`
`THOMAS ROBINS, INDIVIDUALLY AND ON
`BEHALF OF ALL OTHERS SIMILARLY SITUATED,
` Respondent.
`
`On Writ of Certiorari to the United States
`Court of Appeals for the Ninth Circuit
`
`BRIEF OF AMICI CURIAE STATES OF MASSACHUSETTS,
`CONNECTICUT, DELAWARE, THE DISTRICT OF COLUMBIA,
`HAWAII, ILLINOIS, MAINE, MARYLAND, MINNESOTA,
`MISSISSIPPI, NEW MEXICO, NEW YORK, OREGON, AND
`WASHINGTON IN SUPPORT OF RESPONDENT
`
`MAURA HEALEY
` Attorney General of Massachusetts
`SARA CABLE*
`FRANCESCA L. MICELI
` Assistant Attorneys General
`Office of the Attorney General
`One Ashburton Place
`Boston, MA 02108
`(617) 727-2200
`sara.cable@state.ma.us
`*Counsel of Record for Amici Curiae
`
`(Additional Counsel on Inside Cover)
`
`Becker Gallagher · Cincinnati, OH · Washington, D.C. · 800.890.5001
`
`
`
`LORI SWANSON
`Attorney General
`of Minnesota
`102 State Capitol
`75 Rev. Dr. Martin Luther
`King Jr. Blvd.
`St. Paul, MN 55155
`
`JIM HOOD
`Attorney General
`of Mississippi
`P. O. Box 220
`Jackson, MS 30205
`
`HECTOR H. BALDERAS
`Attorney General
`of New Mexico
`P. O. Drawer 1508
`Santa Fe, NM 87504
`
`ERIC T. SCHNEIDERMAN
`Attorney General
`of New York
`120 Broadway
`25th Floor
`New York, NY 10271
`
`ELLEN F. ROSENBLUM
`Attorney General
`of Oregon
`1162 Court St. N.E.
`Salem, OR 97301
`
`ROBERT W. FERGUSON
`Attorney General
`of Washington
`1125 Washington St. SE
`P.O. Box 40100
`Olympia, WA 98504
`
`GEORGE JEPSEN
`Attorney General
`of Connecticut
`55 Elm St.
`Hartford, CT 06106
`
`MATTHEW P. DENN
`Attorney General
`of Delaware
`820 N French St., 6th Fl.
`Wilmington, DE 19801
`
`KARL A. RACINE
`Attorney General
`for the District of Columbia
`441 4th St., NW
`Washington, DC 20001
`
`DOUGLAS S. CHIN
`Attorney General
`of Hawaii
`425 Queen St.
`Honolulu, HI 96813
`
`LISA MADIGAN
`Attorney General
`of Illinois
`100 W. Randolph St.
`12th Floor
`Chicago, IL 60601
`
`JANET T. MILLS
`Attorney General
`of Maine
`109 Sewall St.
`Cross Office Building
`6th Floor
`Augusta, ME 04330
`
`BRIAN E. FROSH
`Attorney General
`of Maryland
`200 Saint Paul Pl.
`Baltimore, MD 21202
`
`
`
` i
`
`TABLE OF CONTENTS
`
`TABLE OF AUTHORITIES . . . . . . . . . . . . . . . . . .
`
`iii
`
`INTERESTS OF AMICI CURIAE . . . . . . . . . . . . . . 1
`
`SUMMARY OF ARGUMENT . . . . . . . . . . . . . . . . . . 2
`
`ARGUMENT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
`
`I. CONSUMERS ARE ROUTINELY HARMED BY
`THE DISSEMINATION AND USE OF
`INACCURATE DATA PROFILES . . . . . . . . . . . 4
`
`A. Vast Amounts of Detailed, Personal
`Consumer Data Are Collected, Processed,
`and Sold By the Data Broker Industry . . . . . 5
`
`B. Businesses Frequently Rely on Data Profiles
`to Make Decisions With
`Important
`Consequences for Consumers . . . . . . . . . . . 11
`
`C. Error-Prone Consumer Data Profiles Lead to
`Negative Consequences that Consumers Are
`Unable to Identify . . . . . . . . . . . . . . . . . . . . . 16
`
`II. THE FCRA IS A CRITICAL TOOL TO
`PROTECT CONSUMERS FROM THE
`DISSEMINATION OF INACCURATE DATA
`PROFILES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
`
`A. The FCRA Is Intended to Protect Consumers
`Against the Dissemination of Inaccurate
`Data Profiles by Data Brokers . . . . . . . . . . . 21
`
`B. Harm to Reputation or Property Rights,
`Even Without Proof of Additional Injury, Has
`Been Long Understood to Create a Judicable
`Case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
`
`
`
` ii
`
`C. The Dissemination of Inaccurate Personal
`Data Causes a Substantial Risk of Injury
`Sufficient for Standing . . . . . . . . . . . . . . . . . 26
`
`D. Statutory Damages Cases and Private Class
`Actions Are Needed to Complement the Role
`of Attorneys General
`in Protecting
`Consumers . . . . . . . . . . . . . . . . . . . . . . . . . . 33
`
`CONCLUSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
`
`
`
` iii
`
`TABLE OF AUTHORITIES
`
`CASES
`
`Bateman v. American Multi-Cinema,
`623 F.3d 708 (9th Cir. 2010) . . . . . . . . . . . . . . . 34
`
`Beaudry v. Telecheck Services,
`579 F.3d 702 (6th Cir. 2009) . . . . . . . . . . . . . . . 26
`
`Clapper v. Amnesty Int’l USA,
`__ U.S. __, 133 S. Ct. 1138 (2013) . . . . . 26, 27, 28
`
`F.W. Woolworth Co. v. Contemporary Arts, Inc.,
`344 U.S. 228 (1952) . . . . . . . . . . . . . . . . . . . . . . 25
`
`Feltner v. Columbia Pictures Television, Inc.,
`523 U.S. 340 (1998) . . . . . . . . . . . . . . . . . . . . . . 25
`
`Figueroa v. Sharper Image Corp.,
`517 F. Supp. 2d 1292 (S.D. Fla. 2007)
`
`. . . . . . . 36
`
`Harris v. Mexican Specialty Foods, Inc.,
`564 F.3d 1301 (11th Cir. 2009) . . . . . . . . . . . . . 34
`
`Holman v. Experian Info. Solutions, Inc. et al,
`C.A. No. 11-00180, Dkt. No. 279 (N.D. Cal. Dec.
`29, 2014) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
`
`In re Adobe Sys., Inc. Privacy Litig.,
`66 F. Supp. 3d (N.D. Cal. 2014) . . . . . . . 27, 28, 30
`
`Krottner v. Starbucks Corp.,
`628 F.3d 1139 (9th Cir. 2010) . . . . . . . . . . . . . . 28
`
`Lujan v. Defenders of Wildlife,
`504 U.S. 555 (1992) . . . . . . . . . . . . . . . . . . . . . . 23
`
`
`
` iv
`
`Marzetti v. Williams,
`1 B. & Ad. 415, 109 Eng. Rep. 842
`(K.B. 1830) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
`
`Mass. v. Envtl. Prot. Agency,
`549 U.S. 497 (2007) . . . . . . . . . . . . . . . . . . . . . . 33
`
`Meese v. Keene,
`481 U.S. 465 (1987) . . . . . . . . . . . . . . . . . . . . . . 24
`
`Murray v. GMAC Mortg. Corp.,
`434 F.3d 948 (7th Cir. 2006) . . . . . . . . . . . . 34, 36
`
`Remijas v. Neiman Marcus Group, LLC,
`Dkt. No. 14-3122, 2015 WL 4394814 (7th Cir.
`July 20, 2015) . . . . . . . . . . . . . . . . . . . . . 27, 28, 30
`
`Rude v. Westcott,
`130 U.S. 152 (1889) . . . . . . . . . . . . . . . . . . . . . . 24
`
`Steel Co. v. Citizens for a Better Env’t,
`523 U.S. 83 (1998) . . . . . . . . . . . . . . . . . . . . . . . 24
`
`Tyler v. Michaels Stores, Inc.,
`464 Mass. 492 (2013) . . . . . . . . . . . . . . . . . . . . . 25
`
`Whittemore v. Cutter,
`29 F. Cas. 1120 (C.C.D. Mass. 1813) . . . . . . . . . 25
`
`Wilson v. DirectBuy, Inc.,
`No. 3:09-CV-590JCH, 2011 WL 2050537 (D.
`Conn. May 16, 2011)
`. . . . . . . . . . . . . . . . . . . . . 36
`
`Zivotofsky v. Kerry,
`__ U.S. __, 135 S. Ct. 2076 (2015) . . . . . . . . . . . 26
`
`
`
` v
`
`STATUTES AND REGULATIONS
`
`15 U.S.C. §§ 1681 et seq. . . . . . . . . . . . . . . . . . passim
`
`15 U.S.C. § 1681(a)(2) . . . . . . . . . . . . . . . . . . . . . . . 19
`
`15 U.S.C. § 1681(a)(3) . . . . . . . . . . . . . . . . . . . . . . . 21
`
`15 U.S.C. § 1681(a)(4) . . . . . . . . . . . . . . . . . . . . . . . 20
`
`15 U.S.C. § 1681(b) . . . . . . . . . . . . . . . . . . . . . . . . . 21
`
`15 U.S.C. § 1681a(b) . . . . . . . . . . . . . . . . . . . . . . . . 21
`
`15 U.S.C. § 1681a(d) . . . . . . . . . . . . . . . . . . . . . 21, 26
`
`15 U.S.C. § 1681a(d)(1) . . . . . . . . . . . . . . . . 21, 22, 26
`
`15 U.S.C. § 1681a(f) . . . . . . . . . . . . . . . . . . . . . . 21, 26
`
`15 U.S.C. § 1681b . . . . . . . . . . . . . . . . . . . . . . . . . . 26
`
`15 U.S.C. § 1681b(a) . . . . . . . . . . . . . . . . . . . . . 22, 26
`
`15 U.S.C. § 1681e(b)
`
`. . . . . . . . . . . . . . . . . . . . passim
`
`15 U.S.C. § 1681n . . . . . . . . . . . . . . . . . . . . . . . . . . 22
`
`15 U.S.C. § 1681n(a) . . . . . . . . . . . . . . . . . . . . . . . . 26
`
`15 U.S.C. § 1681n(a)(1)(A)
`
`. . . . . . . . . . . . . . . . . . . 34
`
`15 U.S.C. § 1681n(a)(2) . . . . . . . . . . . . . . . . . . . . . . 34
`
`15 U.S.C. § 1681o . . . . . . . . . . . . . . . . . . . . . . . . . . 22
`
`15 U.S.C. § 1681p . . . . . . . . . . . . . . . . . . . . . . . . . . 22
`
`17 U.S.C. § 504(c) (2012) . . . . . . . . . . . . . . . . . . . . . 25
`
`28 U.S.C. § 1715(b) . . . . . . . . . . . . . . . . . . . . . . . . . 36
`
`28 U.S.C. § 1715(d) . . . . . . . . . . . . . . . . . . . . . . . . . 36
`
`
`
` vi
`
`Cal. Civ. Code § 1785.11.2 . . . . . . . . . . . . . . . . . . . 29
`
`Conn. Gen. Stat. § 42-110m . . . . . . . . . . . . . . . . . . 33
`
`Mass. Gen. Laws ch. 93, § 62A . . . . . . . . . . . . . . . . 29
`
`Mass. Gen. Laws ch. 93A, § 4 . . . . . . . . . . . . . . . . . 33
`
`Mass. Gen. Laws ch. 93H, § 3 . . . . . . . . . . . . . . . . . 29
`
`Pub. L. No. 109-2, 119 Stat. 4, § 2(b)(2) . . . . . . . . . 35
`
`RULE
`
`Sup. Ct. R. 37.4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
`
`OTHER AUTHORITIES
`
`About, RADARIS, https://radaris.com/page/about . . 14
`
`ACXIOM CORP., FORM 10-K (2015), available at
`https://www.sec.gov/Archives/edgar/data/73326
`9/000073326915000018/f10k.htm . . . . . . . . . . . . 6
`
`Alessandro Acquisti & Christina M. Fong, An
`Experiment in Hiring Discrimination Via Online
`Social Networks (July 18, 2015), available at
`http://dx.doi.org/10.2139/ssrn.2031979 . . . . . . . 15
`
`Julia Angwin, The Web’s New Gold Mine: Your
`Secrets, WALL ST. J., July 30, 2010, available at
`http://www.wsj.com/articles/SB1000142405274
`8703940904575395073512989404 . . . . . . . . . . . . 7
`
`Assurance of Discontinuance No. 09-165, In re
`Choicepoint Workplace Solutions Inc., et al. (Dec.
`17, 2009) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
`
`
`
` vii
`
`Assurance of Discontinuance, In re Equifax Info.
`Serv. LLC, et al., No. 15-1480E (Mass. Super. Ct.
`May 20, 2015) . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
`
`Katy Bachman, Big Data Added $156 Billion in
`Revenue to Economy Last Year, ADWEEK, Oct.
`14, 2014, available at http://www.adweek.com/
`news/technology/big-data-added-156-billion-
`revenue-economy-last-year-153107 . . . . . . . . . . . 6
`
`Danielle Keats Citron & Frank Pasquale, The
`Scored Society: Due Process for Automated
`Predictions, 89 WASH. L. REV. 1 (2014) . . . . . . . 10
`
`C o r e L o g i c S a f e R e n t , C O R E L O G I C ,
`http://www.corelogic.com/industry/multifamily-
`housing-solutions.aspx# . . . . . . . . . . . . . . . . . . 13
`
`E B U R E A U ,
`C r e d i t R i s k A s s e s s m e n t ,
`http://www.ebureau.com/b2c/credit-risk-
`assessment#credit . . . . . . . . . . . . . . . . . . . . . . . 12
`
`CROSS-TAB MARKETING SERV. & MICROSOFT CORP.,
`ONLINE REPUTATION IN A CONNECTED WORLD
`(2010), available at http://download.microsoft.
`com/download/C/D/2/CD233E13-A600-482F-
`9 C 9 7 - 5 4 5 B B 4 A E 9 3 B 1 / D P D _ O n l i n e %
`20Reputation %20Research_overview.doc . . . . 15
`
`Pam Dixon & Robert Gellman, The Scoring of
`America: How Secret Consumer Scores Threaten
`Your Privacy and Your Future, WORLD PRIVACY
`FORUM
`(Apr. 2, 2014), available at
`http://www.worldprivacyforum.org/wp-
`content/uploads/2014/04/WPF_Scoring_of_Ame
`rica_Aprill2014_fs.pdf . . . . . . . . . . . . . . . . . . . . . 9
`
`
`
` viii
`
`Enhanced Strategies for Invitation-to-Apply Offers,
`EXPERIAN, http://www.experian.com/marketing-
`services/profitability-score.html
`. . . . . . . . . . . . 13
`
`FEDERAL TRADE COMMISSION, DATA BROKERS: A
`CALL FOR TRANSPARENCY AND ACCOUNTABILITY,
`(2014), available at https://www.ftc.gov/system/
`files/documents/reports/data-brokers-call-
`transparency-accountability-report-federal-
`t r a d e - c o m m i s s i o n - m a y - 2 0 1 4 / 1 4 0 5 2 7
`databrokerreport.pdf . . . . . . . . . . . . . . . . . passim
`
`FEDERAL TRADE COMMISSION, REPORT TO CONGRESS
`UNDER SECTION 319 OF THE FAIR AND ACCURATE
`CREDIT TRANSACTIONS ACT OF 2003 (2012),
`available at https://www.ftc.gov/sites/default/
`files/documents/reports/section-319-fair-and-
`accurate-credit-transactions-act-2003-fifth-
`i n t e r i m - f e d e r a l - t r a d e - c o m m i s s i o n /
`130211factareport.pdf . . . . . . . . . . . . . . . . . . . . 17
`
`Forty-Five Percent of Employers Use Social
`Networking Sites to Research Job Candidates
`( A u g . 1 9 , 2 0 0 9 ) , C A R E E R B U I L D E R ,
`http://www.careerbuilder.com/share/aboutus/p
`ressreleasesdetail.aspx?id=pr519&sd=8/19/200
`9&ed=12/31/2009 . . . . . . . . . . . . . . . . . . . . . . . . 16
`
`G O V E R N M E N T A C C O U N T A B I L I T Y O F F I C E,
`INFORMATION RESELLERS: CONSUMER PRIVACY
`FRAMEWORK NEEDS TO REFLECT CHANGES IN
`TECHNOLOGY AND THE MARKETPLACE, GAO-13-
`663 (2013), available at http://www.gao.gov/
`assets/660/658151.pdf . . . . . . . . . . . . . . . . . 5, 7, 8
`
`
`
` ix
`
`Chris Jay Hoofnagle, Ashkan Soltani, Nathaniel
`Good, Dietrich J. Wambach & Mika D. Ayenson,
`Behavioral Advertising: The Offer You Cannot
`Refuse, 6 HARV. L. & POL’Y REV. 273 (2012) . . . . 7
`
`ILLINOIS ATTORNEY GENERAL’S OFFICE, IDENTITY
`THEFT RESOURCE GUIDE, available at
`http://www.illinoisattorneygeneral.gov/consum
`ers/Identity_Theft_Resource_Guide.pdf . . . . . . 29
`
`Katie Jennings, How Your Doctor And Insurer Will
`Know Your Secrets — Even If You Never Tell
`Them, BUSINESS INSIDER
`(July 9, 2014),
`http://www.businessinsider.com/hospitals-and-
`health-insurers-using-data-brokers-2014-7 . . . 11
`
`Kathy Kristof, Bad Credit Can Double Auto
`Insurance Premiums, CBS MONEYWATCH (Oct.
`25, 2013), http://www.cbsnews.com/news/bad-
`credit-can-double-auto-insurance-premiums/ . . 12
`
`MASSACHUSETTS ATTORNEY GENERAL’S OFFICE,
`GUIDE ON IDENTITY THEFT FOR VICTIMS AND
`C O N S U M E R S
`( 2 0 1 5 ) , a v a i l a b l e a t
`http://www.mass.gov/ago/docs/consumer/id-theft-
`guide.pdf . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
`
`MCKINSEY GLOBAL INST., BIG DATA: THE NEXT
`FRONTIER FOR INNOVATION, COMPETITION, AND
`P R O D U C T I V I T Y
`(2011), av a i l a b l e a t
`http://www.mckinsey.com/insights/business_te
`chnology/big_data_the_next_frontier_for
`innovation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
`
`
`
` x
`
`Ylan Q. Mui, Little-Known Firms Tracking Data
`Used in Credit Scores, WASHINGTON POST (July
`16, 2011), http://www.washingtonpost.com/
`business/economy/little-known-firms-tracking-
`data-used-in-credit-scores/2011/05/24/gIQAXH
`cWII_story.html . . . . . . . . . . . . . . . . . . . . . . . . . 32
`
`National Association of Insurance Commissioners,
`I n s u r a n c e S c o r e s ,
`C r e d i t - B a s e d
`http://www.naic.org/cipr_topics/topic_credit_
`based_insurance_score.htm . . . . . . . . . . . . . . . . 12
`
`NATIONAL CONSUMERS LEAGUE, THE CONSUMER
`DATA INSECURITY REPORT: EXAMINING THE DATA
`BREACH–IDENTITY FRAUD PARADIGM
`IN
`FOUR MAJOR METROPOLITAN AREAS (2014),
`a v a i l a b l e a t http://www.nclnet.org/
`datainsecurity_report . . . . . . . . . . . . . . . . . . . . 27
`
`Nationwide Employment Background Check,
`TALENTWISE, https://www.talentwise.com/
`e m p l o y m e n t - b a c k g r o u n d - c h e c k . h t m l ?
`trackit=276 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
`
`Nationwide Tenant Background Check,
`TALENTWISE, https://www.talentwise.com/
`tenant-background-check.html?trackit=278 . . 14
`
`Frank Pasquale, Reputation Regulation: Disclosure
`and
`the Challenge of Clandestinely
`Commensurating Computing, in THE OFFENSIVE
`INTERNET–PRIVACY, SPEECH, AND REPUTATION
`(Levmore, S. & Nussbaum, M. eds. 2010) . . . . . 16
`
`
`
` xi
`
`Martha Poon, Scorecards as Devices for Consumer
`Credit: The Case of Fair, Isaac and Company
`Incorporated, 55 SOCIOLOGICAL REVIEW, Sept.
`10, 2007 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
`
`Restatement (Second) of Torts § 559 . . . . . . . . . . . 23
`
`Restatement (Second) of Torts § 573 . . . . . . . . . . . 23
`
`Restatement (Second) of Torts § 623A . . . . . . . . . . 23
`
`Restatement (Second) of Torts § 652D . . . . . . . . . . 23
`
`Restatement (Second) of Torts § 652E . . . . . . . . . . 23
`
`Leslie Scism & Mark Maremont, Insurers Test Data
`Profiles to Identify Risky Clients, WALL ST. J.
`(Nov. 19, 2010), http://www.wsj.com/articles/
`SB100014240527487046486045756207509980
`72986 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
`
`Settlement Agreement, In re Experian Info.
`Solutions, Inc., Equifax Info. Servs., LLC, &
`TransUnion LLC (Mar. 8, 2015), available at
`http://www.ag.ny.gov/pdfs/CRA%20Agreement
`%20Fully%20Executed%203.8.15.pdf . . . . . . . . 31
`
`State Security Breach Notification Laws, NAT’L
`CONFERENCE OF STATE LEGISLATURES,
`http://www.ncsl.org/research/telecommunicatio
`ns-and-information-technology/security-breach-
`notification-laws.aspx . . . . . . . . . . . . . . . . . . . . 32
`
`Tenant Score, MYRENTAL.COM, http://www.
`myrental.com/products/tenant-score . . . . . . . . . 14
`
`
`
` xii
`
`U.S. SENATE COMMITTEE ON COMMERCE, SCIENCE,
`AND TRANSPORTATION, OFFICE OF OVERSIGHT
`AND INVESTIGATIONS, MAJORITY STAFF, A REVIEW
`OF THE DATA BROKER INDUSTRY: COLLECTION,
`USE, AND SALE OF CONSUMER DATA FOR
`MARKETING PURPOSES (2013)
`. . . . . . . . . . passim
`
`Untap New Potential with Underbanked
`Consumers, EXPERIAN, http://www.experian.com/
`marketing-services/data-digest-choicescore.html
`. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
`
`a Background Check?,
`Why Perform
`PEOPLEFINDERS.COM, http://www.peoplefinders.
`com/background-check . . . . . . . . . . . . . . . . . . . . 14
`
`
`
` 1
`
`INTERESTS OF AMICI CURIAE
`Amici States1
`in support of
`file this brief
`Respondent as a matter of right pursuant to Supreme
`Court Rule 37.4.
`
`Each of the Amici States is charged with protecting
`the privacy, security, and integrity of its residents’
`personal data through its enforcement of state and
`federal consumer protection laws, including the Fair
`Credit Reporting Act (“FCRA,” 15 U.S.C. §§ 1681 et
`seq.) and its state analogues, state unfair or deceptive
`practices acts, state data breach notification laws, and
`state data security laws or regulations. These laws
`prevent and remedy injuries caused to consumers when
`their personal data is compromised in commerce,
`whether through security breach, unauthorized
`disclosure, or inaccuracies.
`
`The Amici States seek to ensure that their residents
`have equal access to opportunities necessary for social
`and economic well-being, particularly in the areas of
`credit, employment, housing, and
`insurance.
`Increasingly, access to these opportunities is linked to
`personal data. Accordingly, the Amici States share a
`compelling interest in protecting their residents from
`suffering harm due to the communication and use of
`inaccurate personal data in commerce.
`
`Through our enforcement experience, the Amici
`States know that consumers are injured when
`inaccurate personal data is disseminated to businesses
`and individuals who rely on this information when
`
`1 A list of Amici States and their counsel appears on the inside
`cover.
`
`
`
` 2
`
`making decisions about those consumers. Through our
`efforts helping residents mitigate or avoid these harms,
`we know the time and expense required of consumers
`to restore the integrity of compromised personal data
`and have witnessed that many of those efforts are
`unsuccessful. We have an interest in ensuring that our
`consumers can redress these injuries when their
`statutory rights granted by the FCRA are violated.
`
`SUMMARY OF ARGUMENT
`
`New technologies allow for collection, analysis, and
`dissemination of vast amounts of digital data about
`consumers. This data is collected by the “data broker”
`industry.
` Data brokers amass personal,
`comprehensive, and detailed information regarding
`every consumer in the United States. They compile
`and sell individualized data profiles to a variety of
`businesses. In turn, businesses use these profiles to
`make important decisions about consumers regarding
`credit, employment, housing, and insurance, among
`others.
`
`Unfortunately, these data profiles frequently
`contain errors, and when disseminated, propagate false
`information regarding consumers. These inaccuracies
`may determine where one is able to work, whether one
`will be able to rent or buy a home, or whether one will
`be able to obtain a car loan. However, the damage done
`by the publication or sale of an inaccurate data profile
`is frequently impossible for the affected consumer to
`detect or quantify. Nearly all of the collection,
`aggregation, disclosure, and use of the data occur
`without the consumer’s knowledge. Even if a consumer
`learns of the existence or content of his or her data
`profile, it is nearly impossible to discover all of the
`
`
`
` 3
`
`persons and businesses that have reviewed and relied
`on the data profile in making decisions affecting the
`consumer’s life. When data brokers communicate
`inaccurate personal data, affected consumers likely will
`never know the full extent of the resulting damage.
`
`Congress enacted the FCRA to address the harm
`caused by the dissemination of inaccurate information
`about consumers. The statute gives consumers the
`right to seek redress from data brokers, like Petitioner,
`who violate the FCRA when communicating and selling
`inaccurate personal data about them to businesses. In
`doing so, Congress codified the common-law right to
`pursue relief for injuries to reputation and property
`without proof of further harm. By providing this
`remedy, Congress recognized that the publication of
`inaccurate data in a consumer report creates a
`substantial risk of serious adverse consequences for
`consumers such as: the reasonably foreseeable denial
`of a mortgage loan; the inability to purchase and insure
`a vehicle; or the rejection of a job application.
`Consumers also suffer cognizable harm as a result of
`the efforts they undertake to mitigate damage from
`compromised data. These serious injuries more than
`satisfy the requirements of Article III standing.
`Because consumers frequently cannot identify or
`monetize all of the harm caused by inaccurate data
`profiles, Congress rightly has authorized statutory
`damages for a willful violation of the FCRA. This
`private enforcement tool – a vital complement to the
`enforcement efforts of the Amici States – is critical to
`maintaining consumers’ access to opportunities in
`today’s digital economy.
`
`
`
` 4
`
`ARGUMENT
`
`I. CONSUMERS ARE ROUTINELY HARMED BY
`THE DISSEMINATION AND USE OF
`INACCURATE DATA PROFILES.
`
`An entire industry now exists to collect, aggregate,
`and sell detailed personal data about each and every
`one of us. The data that fuels the data broker industry
`is digital, comprehensive, often quite sensitive, and
`harvested without our knowledge by numerous entities
`every day. Once collected, our data is packaged and
`sold to a variety of companies as purportedly accurate
`reflections of who we are, who we were, and who we are
`likely to be. In turn, businesses routinely use these
`profiles to determine whether we are worthy of credit,
`employment, housing, or insurance, and, if so, on what
`terms.
`
`However, decades of experience have demonstrated
`that consumer data profiles
`frequently
`include
`information that
`is
`inaccurate,
`incomplete, or
`misleading. Even well-recognized and established
`consumer data profiles – credit reports – regularly
`propagate inaccurate consumer data. These mistakes
`have substantial, everyday consequences
`for
`consumers. Yet, the damage done by inaccurate data
`is nearly impossible to detect or quantify. Even if a
`consumer
`identifies and endeavors
`to correct
`inaccurate personal data in his or her data profile, he
`or she may not be aware of all of the adverse decisions
`already made by specific users of that inaccurate data.
`Inaccurate data profiles have grave consequences for
`consumers, but those consequences often remain
`hidden.
`
`
`
` 5
`
`A. Vast Amounts of Detailed, Personal
`Consumer Data Are Collected, Processed,
`and Sold By the Data Broker Industry.
`
`New technologies facilitating the rapid collection,
`analysis, and transfer of digital data about consumers
`have given rise to the data broker industry.2 Data
`brokers (like Petitioner) “collect information, including
`personal information about consumers, from a wide
`variety of sources for the purpose of reselling [it] to
`their customers for various purposes, including
`verifying an individual’s identity, differentiating
`records, marketing products, and preventing financial
`fraud.”3 It is a thriving industry, consisting of
`hundreds to thousands of companies, and it continues
`to grow.4
`
`2 See generally MCKINSEY GLOBAL INST., BIG DATA: THE NEXT
`FRONTIER FOR INNOVATION, COMPETITION, AND PRODUCTIVITY
`(2011), available at http://www.mckinsey.com/insights/business_
`technology/big_data_the_next_frontier_for innovation.
`
`3 See FEDERAL TRADE COMMISSION, DATA BROKERS: A CALL FOR
`TRANSPARENCY AND ACCOUNTABILITY, at 23-45 (2014) [“FTC DATA
`BROKER REPORT”], available at https://www.ftc.gov/system/files/
`documents/reports/data-brokers-call-transparency-accountability-
`report-federal-trade-commission-may-2014/140527databrokerrep
`ort.pdf.
`
`4 See GOVERNMENT ACCOUNTABILITY OFFICE, INFORMATION
`RESELLERS: CONSUMER PRIVACY FRAMEWORK NEEDS TO REFLECT
`CHANGES IN TECHNOLOGY AND THE MARKETPLACE, GAO-13-663, at
`5, 34 (2013) [“GAO REPORT”], available at http://www.gao.gov/asset
`s/660/658151.pdf (estimating between 250 and 2,500 existing data
`brokers, depending on definition applied, and observing a “vast
`increase in recent years in the number and type of companies that
`collect and share [consumers’] data with third parties”); see also
`
`
`
` 6
`
`The volume and specificity of consumer data
`compiled by the industry is staggering. One data
`broker claims to have “[m]ulti-sourced insight into
`approximately 700 million consumers worldwide” and
`“[d]emographics,
`life-stage segmentation, brand
`affinities, and purchase tendencies for nearly every
`adult consumer in the U.S.”5 Another claims to have
`“3000 data segments for nearly every U.S. consumer.”6
`
`interact directly with
`Data brokers rarely
`consumers, but instead gather data from various third-
`party sources, including: government and public
`records; social media, online activity, and mobile device
`usage; retail purchases; and secondary or tertiary (or
`even more remote) sources, including other data
`brokers.7
`
`Data brokers use various data collection methods,
`nearly all of which occur without the consumer’s
`
`Katy Bachman, Big Data Added $156 Billion in Revenue to
`Economy Last Year, ADWEEK, Oct. 14, 2014, available at
`http://www.adweek.com/news/technology/big-data-added-156-
`billion-revenue-economy-last-year-153107.
`
`5 ACXIOM CORP., FORM 10-K at 9
`(2015), available at
`https://www.sec.gov/Archives/edgar/data/733269/0000733269150
`00018/f10k.htm.
`
`6 See FTC DATA BROKER REPORT at 47.
`
`7 See U.S. SENATE COMMITTEE ON COMMERCE, SCIENCE, AND
`TRANSPORTATION, OFFICE OF OVERSIGHT AND INVESTIGATIONS,
`MAJORITY STAFF, A REVIEW OF THE DATA BROKER INDUSTRY:
`COLLECTION, USE, AND SALE OF CONSUMER DATA FOR MARKETING
`PURPOSES at 10-11, 15-21 (2013) [“SENATE STAFF REPORT”]; FTC
`DATA BROKER REPORT at 11-15.
`
`
`
` 7
`
`is collected when
` Consumer data
`knowledge.
`consumers use applications on their smartphones or
`tablets, or in the case of geolocation data,8 just by
`carrying such devices in their pockets.9 Consumers’
`interactions with websites (e.g., search requests, sites
`visited, links clicked, and purchases made) are tracked
`and collected by any number of companies using
`“cookies,”10 “flash cookies” (which resist consumers’
`efforts to delete them), or “history sniffers” (which
`collect web browsing history).11 Consumer data is also
`harvested in bulk from the internet using “web
`scrapers,” technology that scans various online sources
`to collect data reflecting a consumer’s activity or
`
`8 “Geolocation data” indicates a mobile device’s physical location.
`
`9 See GAO REPORT at 24-27.
`
`10 A “cookie” is a text file placed on a computer when a user visits
`a website. See Chris Jay Hoofnagle, Ashkan Soltani, Nathaniel
`Good, Dietrich J. Wambach & Mika D. Ayenson, Behavioral
`Advertising: The Offer You Cannot Refuse, 6 HARV. L. & POL’Y REV.
`273, 276 (2012).
`
`11 See GAO REPORT at 23-24 (describing various online tracking
`technologies); see also Julia Angwin, The Web’s New Gold Mine:
`Your Secrets, WALL ST. J., July 30, 2010, at W1, available at
`http://www.wsj.com/articles/SB1000142405274870394090457539
`5073512989404
`(finding top 50 websites
`in the nation,
`representing approximately 40% of websites viewed by Americans,
`installed average of 64 pieces of tracking technology onto visitors’
`computers, often without warning, to scan and collect, in real-time,
`a visitor’s website activity); see generally Hoofnagle, et al., supra
`note 10 (outlining internet tracking technologies).
`
`
`
` 8
`
`postings on social media, blogs, and even other data
`broker websites.12
`
`Nearly all of this data collection occurs outside of
`consumers’ control, knowledge, or view. In 2012,
`prompted by concerns of consumer harm, the Majority
`Staff of the U.S. Senate Committee on Commerce,
`Science, and Transportation, Office of Oversight and
`Investigations, studied the data broker industry.
`Based on its inquiry, it concluded:
`
`their daily
`about
`going
`[C]onsumers
`activities – from making purchases online and at
`brick-and-mortar stores, to using social media,
`to answering surveys to obtain coupons or
`prizes, to filing for a professional license –
`should expect that they are generating data that
`may well end up in the hands of data brokers[;]
`that this data may well be amassed with many
`other details about them data brokers already
`have compiled[; and] that data brokers will draw
`on this data without their permission to
`construct detailed profiles on them reflecting
`judgments about their characteristics and
`predicted behaviors.13
`
`12 See GAO REPORT at 18; FTC DATA BROKER REPORT at 17
`(observing that “some data brokers collect publicly available web-
`based data through web crawlers, which are programs that capture
`content across the Internet and transmit it back to the data
`broker’s servers”).
`
`13 SENATE STAFF REPORT at 35.
`
`
`
` 9
`
`The data collected is detailed, personal, and often
`sensitive. In addition to demographic information,
`data brokers track, inter alia:
`
`• financial and health status;
`• hobbies;
`• religious and political affiliations;
`• stores visited, shopping habits, and items
`purchased;
`• geolocation;
`• online and social media activity;
`• financial transactions;
`• books read, movies or television shows watched,
`and music listened to;
`• sexual habits and/or orientation;
`• type of device used to access the internet; and
`• grocery and alcohol purchases.14
`
`Data brokers also make and record in a consumer’s
`data profile inferences from raw data (e.g., that a
`
`14 See id. at 13-15 (showing variety of information collected by data
`brokers, including, e.g., whether consumer purchases particular
`shampoo or soft drink; miles traveled in prior weeks; alcoholic
`beverages consumed, whether consumer owns pets, hunts,
`maintains juvenile life insurance, or suffers from ailments such as
`Attention Deficit Hyperactivity Disorder); FTC DATA BROKER
`REPORT at 11-14 (listing variety of data elements collected by nine
`data brokers subject to the FTC’s inquiry); Pam Dixon & Robert
`Gellman, The Scoring of America: How Secret Consumer Scores
`Threaten Your Privacy and Your Future, WORLD PRIVACY FORUM
`(Apr. 2, 2014), at 33-38, available at http://www.worldprivacyforum
`.org/wp-content/uploads/2014/04/WPF_Scoring_of_America_April
`l2014_fs.pdf (listing 187 exemplar types of data elements, and
`numerous subtypes, used to generate various consumer scores,
`including information relating to vehicle ownership, lifestyle,
`interests, activities, medical status, property, and assets).
`
`
`
` 10
`
`consumer is a parent based on purchase of baby
`products). They may also aggregate several raw data
`points to create new data points, including various
`“scores” that purport to rate consumers according to
`attributes considered favorable or unfavorable or
`predict future behavior or tendencies.15
`
`Data brokers also use consumer data to group
`consumers into categories based on perceived identity,
`behavior, socio-economic status, or other
`commonalties.16 Such segments include, for example,
`categories labeled “Urban Scramble” or “Mobile Mixers”
`(referring to segments including high concentrations of
`Latino and African-American consumers), “Thrifty
`Elders” (including singles in their late 60’s and early
`70’s in “one of the lowest income clusters”), “Working
`Class Mom,” “Modest Wages,” or “Financially
`Challenged.”17
`
`Data brokers market these consumer data profiles
`to businesses across many industries as purportedly
`accurate proxies for a consumer’s identity, socio-
`
`15 See generally, Danielle Keats Citron & Frank Pasquale, The
`Scored Society: Due Process for Automated Predictions, 89 WASH.
`L. REV. 1 (2014). Examples of some consumer scores are also
`described infra, Section I.B.
`
`16 See SENATE STAFF REPORT at 21-28 (describing various consumer
`profiles offered by data brokers); FTC DATA BROKER REPORT at 19-
`21 (same).
`
`17 FTC DATA BROKER REPORT at 19-21. See also SENATE STAFF
`REPORT at 24 (other segments also focus on a consumer’s perceived
`economic status, including “American Royalty,” “Power Couples,”
`“Established Elite,” “Mid-Life Strugglers,” “Credit Relia
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