Meta employees sue after losing jobs while requesting time off

Artificial intelligence is rapidly transforming the way companies approach hiring, evaluating, and managing their employees. Advocates argue that AI can reduce bias, increase efficiency, and support better decision-making for businesses. However, critics caution that algorithms may unintentionally reinforce hidden inequities, especially when they assess workers using data that does not accurately reflect the realities of modern work environments.

This ongoing debate has reached federal courts, where 26 Meta employees claim the tech company's AI-assisted layoff process unfairly targeted workers who had taken protected medical, parental, or family leave. The lawsuit does not assert that artificial intelligence itself made the final decision to terminate employees. Instead, it argues that AI-driven productivity metrics became a crucial part of a system that systematically disadvantaged individuals whose work output naturally decreased during legally mandated time away from their jobs.

The case comes at a time when artificial intelligence is becoming more deeply integrated into human resources, from resume screening and performance reviews to workforce planning. Whatever the outcome, this lawsuit could serve as a test of how employment laws, written long before the AI era, apply when algorithms influence decisions about who stays and who leaves.

The Lawsuit's Central Claim

The employees are among approximately 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 used 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 claims that these systems inherently disadvantaged employees on protected leave because they could not accumulate the same productivity data as colleagues who were actively working. The plaintiffs' lawyers argue that Meta failed to adjust these 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 further claims that 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 strongly denied the allegations, stating 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 idea that artificial intelligence determined who lost their jobs.

Despite this, the lawsuit raises broader questions that extend beyond Meta’s workforce. Employment experts have increasingly warned that algorithmic tools designed to measure productivity can lead to 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 due to 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.

This legal theory has gained renewed importance as artificial intelligence becomes more common in employment decisions. While the Trump administration sought to limit federal enforcement of disparate impact claims, private lawsuits remain an option, 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 occurring across corporate America. Businesses are increasingly relying on artificial intelligence to automate administrative tasks, analyze employee performance, and assist with workforce planning. Supporters argue that these systems improve consistency and efficiency, while critics warn that automation can perpetuate existing biases if the underlying data or evaluation methods do not account for real-world circumstances.

Researchers have long cautioned 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. This concern has led to growing calls for greater transparency, human oversight, and regular audits of AI-driven employment tools.

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

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

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