A group of 26 current and former Meta employees sued the company Monday, alleging it used an artificial intelligence system to select workers for a May 20 layoff that disproportionately targeted those who had taken protected leave. The federal lawsuit, filed in San Francisco, challenges the legality of using AI-driven performance metrics and employee monitoring data to make termination decisions at scale.
How Meta's AI allegedly selected employees for layoffs
According to the 71-page complaint, Meta did not rely on manager judgment to build its reduction-in-force list. The plaintiffs claim the company instead deployed a set of internal AI tools - including a system called "Metamate," employee-trained "second-brain" agents, keystroke and activity monitoring, AI token-usage dashboards, and algorithmically assisted performance ranking - to score, rank, and select employees.
"Meta did not assemble the termination list through the considered judgment of managers who knew the work," the plaintiffs write. "Instead, Meta used a constellation of internal artificial-intelligence systems … to score, rank and select employees for inclusion on the list."
Because the AI relied on productivity metrics, output data, and activity logs, the system penalized workers who had been on leave and therefore had fewer measurable data points. The complaint states that employees who exercised their rights to protected leave were "disproportionately selected for layoff."
The monitoring program that fed the AI
Earlier in 2026, Meta rolled out an employee-tracking program that captured keystrokes, screen content, mouse activity, browser history, messages, emails, and voice, video, and location data on company devices. The plaintiffs say the data collected through this program was used to build AI tools, and that the monitoring was introduced with minimal notice - an internal post from an engineer in a secondary group, with no consent or opt-out mechanism for some teams.
The suit claims that employees were then reassigned on a non-optional basis to a new engineering organization that built AI tools using this surveillance data. All 26 plaintiffs, who work in various roles across the U.S., share one common factor: each took, requested, or was approved for protected leave within the previous 24 months.
Legal claims and Meta's response
The plaintiffs are seeking injunctive relief to stop their terminations and restore their employment status. Their claims include violations of state protected-leave laws, the Family and Medical Leave Act, the Pregnancy Discrimination Act, and the Americans with Disabilities Act. Because Meta requires employees to sign arbitration agreements with class-action waivers, the workers will pursue their claims individually.
In a statement, a Meta spokesperson said, "These claims lack merit and are not based on facts. Workforce management and organizational decisions were and are made by people, not AI."
The case lands as companies increasingly test AI's role in workforce decisions, a shift that raises practical questions for leaders evaluating AI for Management and compliance teams reviewing AI for Human Resources. The lawsuit underscores the tension between data-driven efficiency and the legal obligation to accommodate protected leave.
Why this matters for HR, IT, and management professionals
For HR and legal teams, the case is a concrete example of how AI-driven layoff selection can create disparate impact if models fail to account for legally protected absences. IT and development leaders who build or deploy employee monitoring tools should note that opaque data collection and reassignment of workers to AI-training roles can become central evidence in discrimination claims. Managers relying on algorithmic ranking systems need to verify that the data feeding those models does not inadvertently penalize employees for exercising workplace rights. The outcome of this litigation will likely shape internal policies around AI governance, leave management, and employee surveillance for years to come.
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