Judge Signals Workday Faces 1,000s of California AI Bias Claims
Updated
Updated · Reuters · Jun 16
Judge Signals Workday Faces 1,000s of California AI Bias Claims
3 articles · Updated · Reuters · Jun 16
Summary
Monday’s hearing in San Francisco indicated U.S. District Judge Rita Lin is likely to let California discrimination claims proceed against Workday over AI-driven applicant screening used by major employers.
Lin questioned Workday’s argument that California law cannot reach screenings of out-of-state applicants for jobs elsewhere, pointing instead to a 30-year-old state appeals ruling focused on where the allegedly wrongful conduct occurred.
The proposed class action, filed in 2023, now includes four named plaintiffs and claims Workday screened out applicants for discriminatory reasons; original plaintiff Derek Mobley says he was rejected from more than 100 jobs.
The case is the first broad class action targeting AI hiring software and could shape future litigation as more than 80% of U.S. employers, including virtually all Fortune 500 companies, use AI in hiring.
Lin already ruled in 2024 that Workday could be treated as an employer under federal anti-discrimination law, though she did not say when she will decide the California-law issue.
Can a California law dictate how companies worldwide use AI to screen and hire job applicants?
Will a landmark lawsuit finally expose the secret biases hidden inside AI hiring tools?
If an AI hiring tool is biased, who is liable: the developer or the employer who bought it?
Workday AI Bias Lawsuit: Collective Action Over 1.1 Billion Rejected Applications Signals New Era of AI Accountability in Hiring
Overview
The Workday AI bias lawsuit has reached a crucial discovery phase as of June 2026, where obtaining and analyzing comprehensive applicant data is essential. This data is needed to determine if Workday’s AI systems disadvantaged certain groups of candidates. Legal experts stress that without this applicant data, it is impossible to perform the necessary statistical analysis, known as disparate impact analysis, which is central to proving discrimination. The lack of data directly blocks the ability to demonstrate whether bias occurred, making the availability of this information a pivotal factor in the lawsuit’s progress.