Former Meta workers allege AI layoffs targeted disabled employees

Twenty-six former Meta employees filed a federal lawsuit in Oakland, California, accusing the company of using AI-powered software that disproportionately pushed out workers with disabilities or medical leave histories during mass layoffs earlier this year. The complaint says the system relied on factors such as productivity and AI token usage, measurements the plaintiffs say were especially damaging to employees who missed work because of illness, disability or family care obligations.

The workers say Meta told them in May that their jobs would be eliminated starting July 22. They are now seeking a preliminary court order to stop the company from completing the layoffs while their claims proceed in arbitration. The plaintiffs argue that Meta’s employment agreements require many workplace disputes to be handled individually in arbitration, but do not block requests for temporary relief.

At the center of the case is a basic question with broad implications for employers: whether software that appears neutral on paper can still screen out workers whose medical conditions, disabilities or caregiving duties affect how often they are online or how quickly they produce work. The plaintiffs contend that a ranking system built on productivity and AI token usage can reward constant availability while penalizing people who take protected leave or work under medical limits.

That argument could make the lawsuit a test case for how anti-discrimination law applies when automated tools help decide who stays and who goes. If the court allows the challenge to move forward, employers across the country could face closer scrutiny over how they use algorithmic scores in performance reviews, promotion decisions and layoffs, especially when those scores are tied to metrics that do not capture disability-related absences or approved leave.

The dispute also lands as Meta continues to restructure around AI-heavy products and smaller teams. Meta has said the allegations lack merit, but the case could force a wider reckoning over whether AI systems used in human resources are truly objective or whether they can amplify bias behind a veneer of precision.