Liu v. Uber Techs.

1

THOMAS LIU, individually and on behalf of all others similarly situated, Plaintiff-Appellant, v. UBER TECHNOLOGIES, INC., Defendant-Appellee.

Nos. 22-16507, 22-16712

United States Court of Appeals, Ninth Circuit

June 24, 2024

NOT FOR PUBLICATION

Argued and Submitted December 7, 2023 San Francisco, California

Appeal from the United States District Court for the Northern District of California Vince Chhabria, District Judge Presiding D.C. No. 3:20-cv-07499-VC

Before: COLLINS, FORREST, and SUNG, Circuit Judges.

MEMORANDUM ^[*]

Plaintiff Thomas Liu appeals the district court's dismissal of this putative class action for failure to state a claim on which relief may be granted. See FED. R. CIV. P. 12(b)(6). We have jurisdiction under 28 U.S.C. § 1291. We affirm.

I

Because this case was dismissed at the pleadings stage, we take the following well-pleaded allegations of the operative complaint as true. See Shields v. Credit One Bank, N.A., 32 F.4th 1218, 1220 (9th Cir. 2022). Uber, a transportation company that connects drivers with riders via a mobile app, uses a "star rating system" whereby passengers are asked to rate their drivers on a scale of one to five after each ride. Uber terminates, or "deactivates," drivers who fall below a "minimum average star rating," which "has frequently been set very high." In 2015, Liu was terminated as an Uber driver in the San Diego area when his average star rating fell below 4.6.

Liu who is "Asian and from Hawaii and speaks with a slight accent," filed this putative class action in 2020, alleging that Uber's use of the star rating system in making driver termination decisions discriminates against non-white drivers. In particular, Liu alleges that Uber's reliance on the star rating system allows passengers' racial discrimination against non-white drivers to influence Uber's termination decisions. Liu asserted race discrimination claims under both Title VII of the Civil Rights Act of 1964, 42 U.S.C. § 2000e-2, and California's Fair Employment and Housing Act ("FEHA"), CAL. GOV'T CODE § 12940, and he invoked theories of both disparate impact and disparate treatment. The district court dismissed all claims with prejudice under Rule 12(b)(6), and Liu timely appealed.

II

Under Federal Rule of Civil Procedure 8, Liu's complaint "must contain sufficient factual matter, accepted as true, to 'state a claim to relief that is plausible on its face.'" Ashcroft v. Iqbal, 556 U.S. 662, 678 (2009) (quoting Bell Atl. Corp. v. Twombly, 550 U.S. 544, 570 (2007) (emphasis added)); see also Mattioda v. Nelson, 98 F.4th 1164, 1174-75 (9th Cir. 2024) (holding that "the Iqbal/ Twombly standard" applies to a disability-based "hostile-work-environment claim" under the Rehabilitation Act). Because there are alternative ways to establish a claim of racial discrimination, no particular method of establishing a discrimination claim- such as the prima-facie-case framework set forth in McDonnell Douglas Corp. v. Green, 411 U.S. 792 (1973)-is mandatory at the pleading stage. Swierkiewicz v. Sorema N.A., 534 U.S. 506, 511 (2002) (noting, for example, that "if a plaintiff is able to produce direct evidence of discrimination, he may prevail without proving all the elements of a prima facie case"). Instead, the standard to survive a motion to dismiss is simply whether, in light of the requirements of the substantive law invoked, the plaintiff has pleaded sufficient "factual content that allows the court to draw the reasonable inference that the defendant is liable for the misconduct alleged." Iqbal, 556 U.S. at 678.

Accordingly, reviewing de novo, see Campanelli v. Bockrath, 100 F.3d 1476, 1479 (9th Cir. 1996), we proceed to consider whether Liu pleaded sufficient facts to support his claims of disparate impact and disparate treatment.^[1]

A

To state a claim for discrimination under Title VII and the FEHA based on a disparate impact theory, a plaintiff must plausibly allege: (1) a "significant disparate impact on a protected class or group"; (2) "specific employment practices or selection criteria at issue" and (3) "a causal relationship between the challenged practices or criteria and the disparate impact." Bolden-Hardge v. Office of Cal. State Controller, 63 F.4th 1215, 1227 (9th Cir. 2023) (citation omitted). Assuming arguendo that Liu has adequately pleaded a specific employment practice-viz., "Uber's use of its star rating system to terminate drivers"-we conclude that he has failed to plead sufficient facts to raise a plausible inference that this practice is causally related to a "significant disparate impact" on non-white drivers. In arguing for a contrary conclusion, Liu relies on three categories of allegations, but we conclude that, even taking them together, they fall short of Iqbal's standards.

First, Liu alleges that he experienced "hostile" discriminatory treatment from Uber passengers, including that riders "cancell[ed] ride requests after he had already accepted the ride and the rider was able to view his picture." However, the complaint itself alleges that riders rate drivers "after each ride," and Liu pleaded no facts that would plausibly explain how riders who did not use his services could contribute to his Uber rating. Liu also alleged that he "noticed passengers appearing hostile to him," including "riders asking where he was from in an unfriendly way." But the bare allegation that Liu sometimes thought passengers used an "unfriendly" tone does not support a plausible inference that any passenger discrimination in rating him was sufficiently pervasive to drive down his overall Uber rating.

Second, Liu's complaint cites what the district court characterized as a "broad body of social science literature cataloguing the pervasive effects of racial bias in situations where customers rate or value the services they are receiving." The complaint notes that Uber itself had relied on the racial-discrimination concerns presented in such literature in previously defending its since-abandoned decision to disallow tipping on its app. This literature raises an important concern about rating systems, and it may support an inference of a discriminatory causal relationship if Uber's rating system is producing a significant racial disparity in terminations. But even assuming that, in an appropriate case, reliance on publicly available reports and studies providing relevant evidence of real-world conditions may provide a basis for plausibly inferring a statistical disparity with respect to a particular defendant, that is not the case here. The cited materials in Liu's complaint lack sufficient data concerning relevant actual conditions to provide a non-speculative basis for plausibly inferring that any such significant disparity is actually occurring with respect to Uber.

Third, the operative complaint describes the results of a survey of Uber drivers conducted by Liu's counsel concerning whether the drivers were terminated due to low "star ratings" on the Uber app.^[2] The complaint states that, "[i]n November 2021, Plaintiff's counsel sent a survey by electronic mail to approximately 20,000 Uber drivers (who are clients of Plaintiff's counsel)." This survey "asked the drivers whether they had been deactivated by Uber based upon their star ratings, and it asked them to identify their race." The complaint alleges that approximately 20% of the drivers who received the survey responded, with the following results:

If you have been deactivated by Uber, was it because your star ratings were too low?

What is your race?

Yes

No

% Yes

Statistical significance in disparity with whites?

White

275

1310

.174

--

Asian

125

384 .

.246

Black

201

633

.241

<.0001>

Latins

117

574

.169

no

Other

118

356

.249

Liu's complaint summarizes the chart as follows:

As shown above, 17.4% of white respondents indicated that they had been deactivated by Uber based on star ratings. In contrast, 24.6% of Asian respondents, 24.1% of Black respondents, and 24.9% of respondents who identified their race as "Other" than the choices provided indicated that they had been deactivated by Uber based on star ratings. Only 16.9% of Latinx respondents indicated that they had been deactivated by Uber based on star ratings.

The complaint asserts that Dr. Mark Killingsworth, a professor in the Rutgers University Department of Economics, "examined the survey responses and found the results to be highly statistically significant that race is associated with Uber drivers in the survey reporting that they had been deactivated based on their star ratings."

The complaint further alleges that "Plaintiff's counsel sent a follow-up email to the survey respondents who had answered 'no'" to the question whether they had been deactivated based on star ratings, in order "to clarify whether or not they had been deactivated for any reason." The complaint describes the results of that further survey as follows:

Of the respondents who answered "no" to the survey (and responded to the follow-up request for clarification), 51.7% indicated that they had not been deactivated and 48.3% indicated that they had been deactivated for reasons other than star ratings. Of the drivers who answered "no" to the survey, 56.5% responded to the follow-up request for clarification.

For several reasons, we agree with the district court that the allegations concerning counsel's survey are insufficient to raise a plausible inference that there is a significant racial disparity in star-ratings-based terminations among Uber drivers.

The crucial element of a "disparate impact" claim requires a showing "that an employer uses 'a particular employment practice that causes a disparate impact on the basis of race, color, religion, sex, or national...