Meta Workers Say Requesting Leave Cost Them Their Jobs in New Lawsuit

Artificial intelligence is rapidly changing how companies hire, evaluate, and manage employees. Supporters say it can eliminate bias, improve efficiency, and help businesses make better decisions. Critics warn that algorithms can amplify hidden inequities, particularly when they judge workers using data that fails to reflect the realities of modern workplaces.

That debate has landed in federal court, where 26 Meta employees allege the tech giant’s AI-assisted layoff process unfairly targeted workers who had taken protected medical, parental or family leave. Their lawsuit doesn’t argue that artificial intelligence itself made the final decision to terminate employees. Instead, it claims AI-driven productivity metrics became a critical part of a system that systematically disadvantaged people whose work output naturally declined while they were legally away from their jobs.

The case arrives as artificial intelligence becomes increasingly embedded in human resources, from résumé screening and performance reviews to workforce planning. Whatever the outcome, the lawsuit is poised to test how employment laws written decades before the AI era apply when algorithms influence decisions about who stays and who goes.

The Lawsuit’s Central Claim

The employees are among roughly 8,000 workers Meta announced it would lay off earlier this year, representing about 10% of its workforce. According to the complaint filed in federal court in Oakland, California, the company relied on a combination of internal AI systems, keystroke and activity-monitoring data, AI usage dashboards and algorithm-assisted performance rankings as part of its layoff selection process.

The lawsuit argues those systems inherently disadvantaged employees on protected leave because they could not accumulate the same productivity data as colleagues actively working. Lawyers for the employees contend Meta failed to adjust those performance metrics to account for approved medical leave, parental leave, or disability accommodations before using the information during layoff evaluations.

Each of the 26 anonymous plaintiffs had either taken protected leave or requested reasonable accommodations for a disability before being selected for layoff. About half had taken leave related to pregnancy or caregiving, including eight women on maternity or pregnancy-related leave and four men who had taken parental leave. One employee alleges a manager warned that taking approved medical leave for a serious health condition would increase the likelihood of being selected for layoffs, despite the leave being legally protected.

The lawsuit alleges Meta violated multiple federal and state employment laws, including the Family and Medical Leave Act, the Americans with Disabilities Act, the Pregnancy Discrimination Act and the Pregnant Workers Fairness Act. The employees are seeking a court order preventing their layoffs from taking effect while their claims proceed through arbitration.

Meta Rejects the Allegations

Meta has forcefully disputed the claims, saying the lawsuit “lacks merit and is not based on facts.” The company maintains that workforce management and organizational decisions “were and are made by people, not AI,” rejecting the assertion that artificial intelligence determined who lost their jobs.

Even so, the lawsuit raises questions extending well beyond one company’s workforce. Employment experts have increasingly warned that algorithmic tools designed to measure productivity can create unintended consequences if they fail to distinguish between reduced performance and legally protected absences. Systems built to reward continuous activity may inadvertently penalize workers whose careers temporarily pause because of pregnancy, illness, or caregiving responsibilities.

The complaint also relies on the legal concept of “disparate impact,” which argues that a policy can violate anti-discrimination laws even if it appears neutral on its face. According to the plaintiffs, the alleged AI-assisted evaluation process disproportionately affected women because they are statistically more likely to take pregnancy and caregiving leave, placing them at greater risk under productivity-based performance measurements.

That legal theory has taken on renewed significance as artificial intelligence becomes more common in employment decisions. Although the Trump administration has sought to reduce federal enforcement of disparate impact claims, private lawsuits remain available, and several state laws continue to recognize the doctrine as a basis for challenging workplace discrimination.

A Defining Test for AI in the Workplace

The lawsuit reflects a broader transformation taking place across corporate America. Businesses increasingly rely on artificial intelligence to automate administrative work, analyze employee performance, and assist with workforce planning. Supporters argue these systems improve consistency and efficiency, while critics caution that automation can replicate existing biases if the underlying data or evaluation methods fail to account for real-world circumstances.

Researchers have long warned that AI systems are only as reliable as the information they process. If an algorithm treats every reduction in activity as lower performance without recognizing legally protected leave, employees recovering from illness, caring for family members, or welcoming a new child could face unintended disadvantages. That concern has fueled growing calls for greater transparency, human oversight and regular audits of AI-driven employment tools.

The Meta case may ultimately hinge less on whether artificial intelligence was involved than on how it was used. If the plaintiffs can show that AI-assisted metrics influenced decisions without appropriate safeguards for protected workers, the lawsuit could become an important reference point for companies integrating automation into human resources.

As AI continues reshaping the modern workplace, the legal system is beginning to confront a new question: when algorithms help evaluate employees, who bears responsibility if those systems produce discriminatory outcomes? The answer could influence not only the future of workplace AI but also the standards companies must meet as technology takes on a larger role in managing the people behind the business.