Uber is no stranger to accusations of labor and consumer rights violations, including charges of monopoly behavior, racial bias in poor neighborhoods, wage violations and preventing workers from accessing social welfare during the pandemic. Now, adding to this list, is a new lawsuit filed by former driver Thomas Liu alleging Uber violated non-white drivers’ civil rights protected by Title VII of the 1964 Civil Rights Act.
Title VII should be familiar to just about anyone who has looked for a job or offered one. It specifically prohibits denying employment based on race, color, sex, religion, or national origin, and is enforced by the Equal Employment Opportunity Commission (EEOC). According to the suit, Liu claims that Uber’s arbitrary driver rating system unfairly discriminates against non-white drivers.
Uber’s 5-star rating system is generated by passengers, and as Edward Ongweso, Jr. notes for Vice, Uber fires drivers who fall under a 4.6-star rating. Liu’s argument is that
“Uber's use of its star rating system to terminate drivers constitutes unlawful discrimination based on race, both because it has a disparate impact on non-white drivers and because Uber is aware that passengers are prone to discriminate in their evaluation of drivers, but Uber has continued to use this system, thus making it liable for intentional race discrimination,”
The EEOC had initially handled Liu’s case, but came to no conclusion about whether the system violated Title VII. However, it did issue a right to sue letter. As Ongweso, Jr. points out, this will be a hard case to prove because of “data asymmetry,” which, in this case means all the data that could help prove Liu’s case is held by Uber exclusively, and the company is not forthcoming with it.
With a vote on Proposition 22 in California today, this is another important case which may have ramifications not just for Uber but other so-called “platforms” in the gig economy that also rely on user ratings to assess workers. Liu’s lawsuit highlights the pervasive and larger issue of algorithmic bias in numerous areas including employment, law and technology where putatively impartial methods are used to determine hiring and firing decisions, sentencing and bail, and even the type of search results one is likely to see.
