Meta employees have sued the company over claims that AI-assisted layoff tools steered job cuts toward workers on protected leave.
Quick Take
- Twenty-six current and former Meta employees filed a federal lawsuit in Oakland, California.
- The suit says Meta used internal AI-assisted systems, activity data, and productivity scores to rank workers for layoffs.
- Plaintiffs say protected leave, disability, pregnancy, and family care were not fairly accounted for in the scoring.
- Meta says the claims lack merit and that people, not AI, made the workforce decisions.
What the lawsuit says happened
The lawsuit claims Meta used internal AI tools to help decide which employees would be laid off. The plaintiffs say those systems relied on signals like keystrokes, screen content, email activity, browser history, and AI token usage.
A lawsuit accusing Meta of discriminatory artificial intelligence use in firing workers demonstrates how companies leaning on the emerging technology for employment decisions can incur liability. https://t.co/jpeh9SPay7
— Bloomberg Law (@BLaw) July 28, 2026
That matters because leave can make a worker look less active on paper. A person on maternity leave, medical leave, or family leave will naturally generate fewer signs of online productivity. The complaint says Meta did not adjust for that reality before ranking employees for termination.
Why the leave issue sits at the center
The core claim is not simply that Meta used software. It is that the software allegedly disadvantaged people who were on protected leave or had disabilities. The plaintiffs say scores and ratings “by design” could not be accumulated by workers away on leave or working with reduced output because of a disability.
Reporting says about half the plaintiffs had taken leave for caregiving or pregnancy-related reasons. ABC News also reported that eight plaintiffs had taken maternity or pregnancy-related leave, four had taken parental leave, and one had taken leave to care for a family member and later bereavement leave.
The layoff backdrop
The lawsuit came out of Meta’s broader reduction in force. Reporting says the company announced roughly 8,000 layoffs, about 10 percent of its workforce, and plaintiffs were told in May that their jobs would end starting July 22.
That timing gives the case its sharpest edge. One reported allegation says a plaintiff received layoff notice while on approved pre-birth leave just two days before giving birth. That detail is still part of the complaint narrative, but it shows why the workers say the process was not neutral.
The legal fight and the proof problem
The plaintiffs say the layoffs violated laws that protect workers from discrimination or retaliation tied to medical leave, disability, pregnancy, and related family protections. They also asked for emergency relief to stop Meta from finishing the layoffs while the case moves forward.
Meta disputes the case. Reuters reported that a company spokesperson said the claims “lack merit” and that workforce decisions were made by people, not AI.
A judge later declined to block the layoffs, which does not decide the merits but does show how hard these cases can be to prove before discovery opens the company’s internal records.
Why this case is getting so much attention
This lawsuit lands at the point where workplace analytics, artificial intelligence, and employment law collide. The public can see the headline, but not the internal scorecards, audit logs, or ranking sheets that would show how the decisions were really made. That gap is the whole case.
If the plaintiffs can get the records, they may prove a pattern. If not, the dispute may stay trapped between accusation and denial.
For now, the strongest fact is simple: 26 Meta employees say an AI-assisted system helped push people on protected leave into the layoff line. The next phase will decide whether that claim is just a serious allegation, or the beginning of a much bigger legal problem for how major companies use automation inside human resources.
Sources:
abc7.com, reuters.com, youtube.com














