Meta layoffs raise concerns over AI bias in workforce decisions
Former Meta employees say internal AI scores and keystroke data helped pick layoff targets, including workers on medical leave.
Meta employees who had taken medical or family leave say the company used internal AI scores, token-usage dashboards and productivity metrics to decide who was cut, turning a May layoff of nearly 8,000 people into a test of how automated workforce tools handle protected leave. The 26 anonymous plaintiffs say the system could not account for absences tied to disability or leave, which put the decision-making process itself under scrutiny.
The lawsuit, filed in federal court in Oakland, California, says Meta relied on a cluster of internal systems, including Metamate, a large language model assistant, an employee-trained "second brain" that tracked communications and documents, and a productivity score built from keystrokes, screen content, emails and browser history. The plaintiffs, who came from six states and the District of Columbia, say they were notified in May that their jobs would end starting July 22 and are asking for a preliminary order blocking the layoffs while they pursue private arbitration.
Meta said the claims "lack merit and are not based on facts" and that "workforce management and organizational decisions were and are made by people, not AI." The suit also appears to be the first against a major U.S. company to challenge the alleged use of AI in conducting layoffs, coming less than a month after a California judge let Workday defend allegations that its AI hiring software weeded out applicants in ways that violated state law and the federal ban on disability discrimination.
For monday.com engineers, product managers and sales teams, the practical lesson is that AI used in people operations cannot be treated like a black box. If a company uses machine scores in reviews, ranking or restructuring, it needs auditable inputs, documented human review and a clear owner for accommodation decisions, because enterprise buyers evaluating AI-driven workflow automation will ask whether those controls exist before they trust the product with sensitive data.
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