Vance v. Microsoft Corporation

District Court, W.D. Washington·Decided October 17, 2022·No. 2:20-cv-01082·Unknown

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. C20-1082JLR 11 Plaintiffs, ORDER ON MICROSOFT’S v. MOTION FOR SUMMARY 12 JUDGMENT

MICROSOFT CORPORATION, 13 Defendant. 14

15 I. INTRODUCTION 16 Before the court is Defendant Microsoft Corporation’s (“Microsoft”) renewed 17 motion for summary judgment. (Mot. (Dkt. # 127); Reply (Dkt. # 138).) Plaintiffs 18 Steven Vance and Tim Janecyk (collectively, “Plaintiffs”) oppose Microsoft’s motion. 19 (Resp. (Dkt. # 1351).) The court has considered the motion, all materials submitted in 20

1 Plaintiffs originally filed their response under seal because it relied on and cited 21 documents that Microsoft had marked confidential; they also filed a redacted version of their response. (Mot. to Seal (Dkt. # 134); Redacted Resp. (Dkt. # 132).) Because Microsoft did not 22 oppose unsealing the response and the documents, the court denied Plaintiffs’ motion to seal and 1 support of and in opposition to the motion, and the governing law. Being fully advised,2 2 the court GRANTS Microsoft’s motion for summary judgment.

3 II. BACKGROUND 4 The court sets forth the factual and procedural background of this case below. 5 A. Factual Background 6 1. The Diversity in Faces (“DIF”) Dataset 7 Plaintiffs are longtime Illinois residents who, beginning in 2008, uploaded digital 8 photographs, including photos of themselves, to Flickr, a photo-sharing website. (See

9 Compl. (Dkt. # 1) ¶¶ 6-7, 28, 66-67, 75; Vance Dep.3 at 9:15-10:9; Janecyk Dep.4 at 10 39:7-40:1.) In 2014, Yahoo!, Flickr’s then-parent company, publicly released a dataset of 11 about 100 million photographs that had been uploaded to Flickr’s website between 2004 12

13 directed the clerk to remove the seal on Plaintiffs’ responsive brief and the confidential documents. (Mot. to Seal Resp. (Dkt. # 136); 7/11/22 Order (Dkt. # 137).) Accordingly, the 14 court cites the unredacted version of Plaintiffs’ response in this order.

2 Both parties request oral argument on the motion (see Mot. at 1; Resp. at 1). The court, 15 however, concludes that oral argument would not be helpful to its disposition of the motion. See Local Rules W.D. Wash. LCR 7(b)(4). 16

3 Both parties have submitted excerpts from Mr. Vance’s deposition. (See Berger Decl. 17 (Dkt. # 86) ¶ 2, Ex. 1; 7/1/22 Lange Decl. (Dkt. # 132-1) ¶ 2, Ex. 1.) For ease of reference, the court cites directly to the page and line number of the deposition. 18 The court notes that Plaintiffs did not highlight the portions of the deposition transcripts that they referred to in their pleadings as required by Local Civil Rule 10(e)(10). See Local 19 Rules W.D. Wash. LCR 10(e)(10) (“All exhibits [submitted in support of or in opposition to a motion] must be marked to designate testimony or evidence referred to in the parties’ filings.”). 20 The court directs Plaintiffs’ counsel to review the local rules regarding marking exhibits before making any further filings.

21 4 Both parties have submitted excerpts from Mr. Janecyk’s deposition. (See Berger Decl. ¶ 3, Ex. 2; 7/1/22 Lange Decl. ¶ 3, Ex. 2.) For ease of reference, the court cites directly to the 22 page and line number of the deposition. 1 and 2014 (the “YFCC-100M Dataset”). (See Merler Decl. (Dkt. # 85) ¶ 3, Ex. A 2 (“Diversity in Faces”) at 2.) The YFCC-100M Dataset included photos uploaded by both

3 Plaintiffs. (See Vance Dep. at 179:22-23; Janecyk Dep. at 95:22-24.) 4 Before 2018, “there was an industry-wide problem with many facial recognition 5 systems’ ability to accurately characterize individuals who were not male and did not 6 have light colored skin tones.” (Merler Decl. ¶ 4.) As a result, “the facial recognition 7 systems and algorithms associated with those facial recognition systems were trained in 8 such a way that the systems were able to accurately characterize a white, light skinned

9 male subject, but the technology suffered from inaccuracies when it had to characterize a 10 non-male or a person with darker skin tones.” (Id.) Seeking to “advance the study of 11 fairness and accuracy in face recognition technology,” researchers working for 12 International Business Machines Corporation (“IBM”)5 used one million of the photos in 13 the YFCC-100M Dataset to develop the Diversity in Faces (“DiF”) Dataset at issue in

14 this case. (Id. ¶ 5; Diversity in Faces at 2, 7.) The researchers implemented ten “facial 15 coding schemes” to measure aspects of the facial features of the individuals pictured in 16 the photos, such as “craniofacial distances, areas and ratios, facial symmetry and contrast, 17 skin color, age and gender predictions, subjective annotations, and pose and resolution.” 18 (Diversity in Faces at 9.) A statistical analysis of these coding schemes “provided insight

19 into how various dimensions . . . provide indications of dataset diversity.” (Merler 20

5 All of the researchers involved in creating the DiF Dataset were based in and worked 21 out of IBM’s office in Yorktown Heights, New York; and the work was performed on and stored on IBM Research computer servers in Poughkeepsie, New York. (Id. ¶ 8.) None of the work 22 involved computers or systems located in Illinois. (Id.) 1 Decl. ¶ 6.) The coding schemes implemented by the IBM researchers were intended to 2 enable other researchers to develop techniques to estimate diversity in their own datasets,

3 with the goal of mitigating dataset bias, and were “never intended to identify any 4 particular individual.” (Id. ¶ 7.) Rather, the coding schemes were “purely descriptive 5 and designed to provide a mechanism to evaluate diversity in the dataset.” (Id.) 6 IBM provided the DiF Dataset free of charge to researchers who filled out a 7 questionnaire and submitted it to IBM via email. (Id. ¶¶ 4, 9.) The questionnaire 8 required the researcher to verify

9 (i) that he/she would only use the DiF Dataset for research purposes, and (ii) that he/she had read and agreed to the DiF Dataset terms of use, which 10 made clear that the DiF Dataset could only be used for non-commercial, research purposes and prohibited using the DiF Dataset to identify any 11 individuals in images associated with URLs in the DiF Dataset.

12 (Id. ¶ 9; see also id. ¶ 11, Ex. H (DiF Dataset terms of use).) After verifying that a 13 request was for a “legitimate research purpose,” IBM researcher Dr. Michele Merler sent 14 the DiF Dataset to the requesting researcher “via an email that included a link to a 15 temporary Box folder that contained the DiF Dataset.” (Merler Decl. ¶ 10.) 16 2. Plaintiffs’ Photos in the DiF Dataset 17 The DiF Dataset includes at least 61 of the nearly 19,000 public photos that Mr. 18 Vance uploaded to Flickr. (Vance Dep. at 179:22-23, 210:19-24.) Mr. Vance appears in 19 some of the photos in the DiF Dataset; other photos depict people whose state of 20 residence was unknown to Mr. Vance and at least one depicts individuals who themselves 21 were unknown to Mr. Vance. (Id. at 132:4-14; 154:5-16.) 22 1 The DiF Dataset includes 24 of the 1,669 public photos that Mr. Janecyk uploaded 2 to Flickr. (Janecyk Dep. at 74:21-24, 95:22-96:1.) Mr. Janecyk appears in at least one of

3 the photos. (Id. at 99:21-100:6.) Because Mr. Janecyk photographed people on the 4 streets of Chicago, however, he does not know the names or places of residence of the 5 individuals depicted in most of his photos. (Id. at 45:16-46:19, 98:8-100:13, 6 167:11-168:15, 228:19-21.) 7 3. Microsoft’s Downloads of the DiF Dataset 8 Two individuals affiliated with Microsoft downloaded the DiF Dataset in February

9 2019: contractor Benjamin Skrainka and Microsoft Research intern Samira Samadi. 10 (Skrainka Decl. (Dkt. # 87) ¶ 5; Samadi Decl. (Dkt. # 88) ¶¶ 5-6.) The court describes 11 their interactions with the DiF Dataset below.

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