Vance v. Amazon.com Inc

CourtDistrict Court, W.D. Washington
DecidedMarch 15, 2021
Docket2:20-cv-01084
StatusUnknown

This text of Vance v. Amazon.com Inc (Vance v. Amazon.com Inc) is published on Counsel Stack Legal Research, covering District Court, W.D. Washington primary law. Counsel Stack provides free access to over 12 million legal documents including statutes, case law, regulations, and constitutions.

Bluebook
Vance v. Amazon.com Inc, (W.D. Wash. 2021).

Opinion

1 2 3

4 5 6 7 UNITED STATES DISTRICT COURT WESTERN DISTRICT OF WASHINGTON 8 AT SEATTLE

9 10 STEVEN VANCE, et al., CASE NO. C20-1084JLR 11 Plaintiffs, ORDER GRANTING IN PART v. AND DENYING IN PART 12 AMAZON’S MOTION TO DISMISS AMAZON.COM INC, 13 Defendant. 14

15 I. INTRODUCTION 16 Before the court is Defendant Amazon.com, Inc.’s (“Amazon”) motion to dismiss 17 Plaintiffs Steven Vance and Tim Janecyk’s (collectively, “Plaintiffs”) complaint. (MTD 18 (Dkt. # 18); Reply (Dkt. # 25).) Plaintiffs oppose the motion. (Resp. (Dkt. # 24).) 19 Having considered the motion, the parties’ submissions regarding the motion, the 20 //

21 //

22 // 1 relevant portions of the record, and the applicable law,1 the court GRANTS in part and 2 DENIES in part the motion to dismiss. 3 II. BACKGROUND

4 Facial recognition technology uses computer artificial intelligence and machine 5 learning algorithms to “detect, recognize, verify and understand characteristics of humans 6 faces.”2 (Compl. (Dkt. # 1) ¶ 23 (quoting Michele Merler, et al., Diversity in Faces, IBM 7 Research AI at 1 (Apr. 10, 2019)) (“Diversity in Faces”).) However, “significant 8 technical hurdles” hinder the technology’s accuracy, and improving that accuracy relies

9 upon “the use of data-driven deep learning to train increasingly accurate models by using 10 growing amounts of data.” (Diversity in Faces at 1.) In other words, practice makes 11 perfect: for artificial intelligence to more accurately recognize different faces, “vast 12 quantities of images of a diverse array of faces” must be fed to the underlying 13 machine-learning algorithms. (Compl. ¶ 24.)

14 Amazon is one of many companies that have developed and produced facial 15 recognition products. (Id. ¶¶ 3, 54-56.) Amazon’s product, Amazon Rekognition, allows 16 users to “match new images of faces with existing, known facial images ‘based on their 17 visual geometry.’” (Id. ¶ 55.) Amazon Rekognition is a “fundamental cornerstone” of 18 other Amazon products, including Amazon Photos, Amazon’s smart home systems and

20 1 Both parties request oral argument (MTD at 1; Resp. at 1), but the court finds oral argument unnecessary to its disposition of the motion, see Local Rules W.D. Wash. LCR 7(b)(4).

21 2 For the purposes of a motion to dismiss, the court accepts all well-pleaded allegations in Plaintiffs’ complaint as true and draws all reasonable inferences in favor of Plaintiffs. See Wyler 22 Summit P’ship v. Turner Broad. Sys., Inc., 135 F.3d 658, 661 (9th Cir. 1998). 1 cameras, and Amazon’s virtual assistant technology Alexa. (Id. ¶ 56.) Moreover, 2 Amazon is “the largest provider of facial recognition technology to law enforcement 3 agencies,” including Immigration Customs Enforcement (“ICE”), the Federal Bureau of

4 Investigations (“FBI”), and more than 1,300 other law enforcement agencies. (Id. ¶ 57.) 5 Plaintiffs are Illinois residents who, starting in 2008, uploaded photos of 6 themselves to the photo-sharing website Flickr. (Id. ¶¶ 6-7, 28, 66-67, 75.) Both were in 7 Illinois when uploading the photos. (Id. ¶¶ 66, 75.) Unbeknownst to Plaintiffs, Flickr, 8 through its parent company Yahoo!, compiled hundreds of millions of photographs

9 posted on its platform, including those of Plaintiffs and other Illinois residents, into a 10 dataset (“Flickr dataset”) that it then made publicly available to “help improve the 11 accuracy and reliability of facial recognition technology.” (Id. ¶¶ 29-32.) 12 Utilizing the Flickr dataset, International Business Machines Corporation (“IBM”) 13 selected one million images to create a new dataset called Diversity in Faces in an effort

14 to reduce bias in facial recognition. (Id. ¶ 42.) IBM scanned the “facial geometry” of the 15 images and created a “comprehensive set of annotations of intrinsic facial features,” 16 including craniofacial distances, areas and ratios, facial symmetry and contrast, skin 17 color, age and gender predictions, subjective annotations, and pose and resolution. (Id. 18 ¶ 43 (citing Diversity in Faces at 2).) Ultimately, IBM utilized “19 facial landmark

19 points” to determine “68 key points for each face” and to extract “craniofacial features” 20 for each image in the dataset. (Id. ¶¶ 44-45 (citing Diversity in Faces at 9).) Again, the 21 Diversity in Faces dataset included the facial scans of Plaintiffs and other Illinois 22 // 1 residents, but like Flickr and Yahoo!, IBM did not seek or receive permission from 2 individuals whose faces were analyzed. (Id. ¶¶ 46-47.) 3 IBM made the Diversity in Faces dataset available to other companies seeking to

4 improve their facial recognition technology. (Id. ¶ 49.) To obtain the dataset, companies 5 applied for permission via an online questionnaire, and if IBM granted access, IBM 6 would send a link for companies to download the dataset. (Id. ¶ 50.) Those with the 7 dataset, and the corresponding information, could “identify the Flickr user who uploaded 8 the photograph,” “view the Flickr user’s homepage,” and “view each photograph’s

9 metadata, including any available [information] relating to where the photograph was 10 taken or uploaded.” (Id. ¶ 53.) Amazon applied for and downloaded the dataset from 11 IBM. (Id. ¶ 61.) Amazon used the dataset to improve “the fairness and accuracy of its 12 facial recognition products,” which “improve[d] the effectiveness” of those products and 13 made them “more valuable in the commercial marketplace.” (Id. ¶¶ 64-65.) Once again,

14 the dataset downloaded by Amazon contained Plaintiffs’ information, but Amazon did 15 not inform or obtain permission from Plaintiffs. (Id. ¶¶ 63, 71-72, 79-80.) 16 Plaintiffs bring a class action suit against Amazon for violating Illinois’s 17 Biometric Information Privacy Act, 740 ILCS 14/1, et seq. (“BIPA”), which regulates the 18 collection, storage and use of biometric identifiers and biometric information

19 (collectively, “biometric data”). (Id. ¶¶ 4, 17.) Specifically, they allege violations of two 20 BIPA provisions: (1) Amazon violated § 15(b) by collecting and obtaining biometric 21 data without providing the requisite information or obtaining written releases; and (2) 22 Amazon violated § 15(c) by unlawfully profiting from individuals’ biometric data. (Id. 1 ¶¶ 99-112.) Plaintiffs additionally bring an unjust enrichment claim (id. ¶¶ 113-22) and a 2 separate count for injunctive relief (id. ¶¶ 123-28). 3 III. ANALYSIS

4 When considering a motion to dismiss under Rule 12(b)(6), the court construes the 5 complaint in the light most favorable to the nonmoving party. Livid Holdings Ltd. v. 6 Salomon Smith Barney, Inc., 416 F.3d 940, 946 (9th Cir. 2005). The court must accept 7 all well-pleaded facts as true and draw all reasonable inferences in favor of the plaintiff. 8 Wyler Summit P’ship, 135 F.3d at 661. The court, however, is not required “to accept as

9 true allegations that are merely conclusory, unwarranted deductions of fact, or 10 unreasonable inferences.” Sprewell v. Golden State Warriors, 266 F.3d 979, 988 (9th 11 Cir. 2001). “To survive a motion to dismiss, a complaint must contain sufficient factual 12 matter, accepted as true, to ‘state a claim to relief that is plausible on its face.’” Ashcroft 13 v. Iqbal, 556 U.S. 662, 678 (2009) (quoting Bell Atl. Corp. v. Twombly, 550 U.S. 544,

14 570 (2007)); see also Telesaurus VPC, LLC v. Power,

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