Meta Platforms is currently embroiled in a legal dispute involving dozens of its former employees, who allege that the company utilized artificial intelligence systems to unfairly target them for layoffs. The lawsuit, brought in a California federal court, asserts that Meta’s use of AI-driven performance evaluations and employee data disproportionately impacted those on maternity leave, medical leave, and employees with disabilities.
The complaint claims that as part of a workforce reduction earlier this year, affecting approximately 8,000 employees, Meta employed internal AI systems to determine which staff members would be laid off. It is alleged that these AI systems, which generated performance scores and rankings, were used in place of traditional manager assessments. The plaintiffs argue that the AI failed to adequately account for approved leave periods, leading to unfairly low performance scores for employees who were on family or medical leave or had disability accommodations.
Among those bringing the lawsuit is a scientist who learned of her termination just two days before her due date. Another plaintiff, an engineer recovering from an injury, contends that his performance rating suffered because of his absence from work. Furthermore, a manager who had recently commenced medical leave alleges he was dismissed shortly after his leave began.
The employees involved in the lawsuit are seeking a court injunction to stop the layoffs while the case is ongoing, along with demands for reinstatement, compensation for lost wages and benefits, and an independent review of Meta’s AI systems. Despite these claims, Meta has refuted the allegations, maintaining that its workforce and organizational decisions are determined by human judgment rather than artificial intelligence.
This legal action arises amidst increasing concerns over the role of AI in workplace decision-making processes. Critics caution that reliance on automated systems could inadvertently introduce bias against employees who are on legally protected leave, thereby raising questions about the fairness and transparency of such technology in employment practices.