U.S. court dismisses racial discrimination case against Uber

A U.S. appeals court has dismissed a proposed class action lawsuit that claimed Uber Technologies' policy of terminating drivers with low passenger ratings is racially discriminatory. The San Francisco-based 9th U.S. Circuit Court of Appeals ruled on Monday that the plaintiff, Thomas Liu, failed to provide evidence showing that Uber deactivated non-white drivers at a higher rate than white drivers with low ratings.

Thomas Liu, an Asian-American driver, filed the lawsuit in 2020, alleging that Uber's rating system is biased against non-white drivers. However, the three-judge panel of the 9th Circuit found that Liu did not present any concrete evidence to support his claim of racial disparity. The panel stated that Liu's arguments were speculative and lacked the necessary backing to proceed to discovery, where plaintiffs can request documents and testimony from defendants.

Plaintiff's argument and court's response

Liu's lawyers argued that statistical evidence to support their claims would become available only if the case moved forward to discovery. They asserted that passengers are more likely to give poor ratings to non-white drivers, leading to their deactivation under Uber's policy. However, the court found Liu's evidence insufficient. U.S. District Judge Vince Chhabria in San Francisco had previously dismissed the case in 2022, stating there was no plausible statistical disparity among drivers of different races. He criticised a survey conducted by Liu's lawyers, suggesting it was flawed and did not accurately represent the racial composition of Uber drivers.

Reaction from Liu's legal team

Shannon Liss-Riordan, Liu's lawyer, expressed disappointment with the ruling and indicated that they might request the court to reconsider. "We are deeply disappointed and concerned about the ruling," Liss-Riordan said. She emphasized the need for a fair assessment of the claims and suggested that the decision failed to acknowledge potential biases in customer ratings.

Uber's rating system under scrutiny

Uber's system asks passengers to rate drivers on a scale of one to five. Drivers who fail to maintain high scores risk deactivation. Liu's lawsuit claimed that this system disproportionately affects non-white drivers, violating Title VII of the Civil Rights Act of 1964 and California's anti-discrimination laws. Liu was deactivated after his rating fell below 4.6, which he attributed to racial bias from passengers.

Support from the U.S. Equal Employment Opportunity Commission

The U.S. Equal Employment Opportunity Commission (EEOC) supported Liu's case, filing a friend-of-the-court brief. The EEOC cited research indicating that customer ratings are likely influenced by bias, particularly for gig economy workers like Uber drivers. The commission argued that Liu's claims, combined with his lawyers' survey, established a plausible case of discrimination.

Implications and analysis

The court's dismissal highlights the challenges of proving systemic discrimination within platforms reliant on customer ratings. The decision underscores the difficulty plaintiffs face in presenting concrete statistical evidence without access to internal data from companies like Uber. The ruling also raises questions about the effectiveness and fairness of customer rating systems in the gig economy.

Future steps and considerations

While the court's decision represents a setback for Liu and his legal team, it does not close the door on future challenges to Uber's policies. The case could set a precedent for how similar claims are evaluated, particularly regarding the burden of proof required to demonstrate discrimination. It also highlights the ongoing debate about the role of customer feedback in employment decisions and the potential biases inherent in such systems.

As Uber continues to rely on customer ratings to manage its driver workforce, scrutiny of these practices is likely to persist. The case serves as a reminder of the importance of addressing potential biases to ensure fair treatment for all workers in the gig economy.

(Inputs from Reuters)