Key Takeaways
- A group of 26 current and former Meta employees filed a lawsuit alleging that the company’s AI‑driven layoff selection process discriminated against workers on protected medical or family leave and those with disabilities.
- The plaintiffs claim Meta’s internal AI systems relied on metrics such as performance ratings, productivity scores, and AI‑token consumption—data points that cannot be accrued while an employee is on leave or whose output is diminished by a disability.
- The suit cites violations of protected‑leave statutes and various anti‑discrimination laws, and seeks a preliminary injunction to halt further layoffs, an independent audit of the algorithmic selection process, and resolution of the claims in arbitration.
- Meta denies the allegations, asserting that workforce decisions are made by people, not AI, and that the claims lack factual basis.
- The case follows a similar ruling against Workday over AI‑based hiring tools, highlighting growing judicial scrutiny of AI’s role in employment decisions and its potential impact on protected classes.
Background of the May 2026 Layoffs
In May 2026, Meta announced a round of workforce reductions that affected roughly 10 % of its global staff. Among those impacted were 26 unnamed employees—both current and former workers—who have since joined together as plaintiffs in a federal lawsuit filed in the United States Northern District Court of California. The complaint states that these individuals were selected for termination through a process that the plaintiffs allege was heavily influenced by Meta’s “constellation of internal artificial‑intelligence systems.” The timing of the suit, filed on a Monday, underscores the employees’ desire to challenge the layoffs swiftly while seeking interim relief.
Allegations About AI‑Driven Selection Criteria
The heart of the plaintiffs’ argument is that Meta’s AI tools used inputs that inherently disadvantage employees who are on protected leave or living with disabilities. As the lawyers wrote in the filing:
“Those tools draw on inputs—performance ratings, calibration scores, productivity and output metrics, ‘AI-native’ ratings, and AI‑token consumption—that, by design, cannot be accumulated by an employee who is on protected medical or family leave, or whose output is reduced by a disability.”
According to the complaint, metrics such as AI‑token consumption—a proxy for overall AI usage—were weighted heavily in the algorithm that ranked employees for potential layoffs. Because employees on maternity, paternity, or medical leave do not generate the same level of token usage or productivity scores, the algorithm allegedly penalized them unfairly, resulting in a disparate impact on protected groups.
Legal Foundations of the Claim
The lawsuit asserts that Meta’s conduct violates several federal and state protections, including the Family and Medical Leave Act (FMLA), the Americans with Disabilities Act (ADA), and California’s Fair Employment and Housing Act (FEHA). By allegedly failing to account for approved absences when calculating performance‑based scores, the company is said to have discriminated against workers exercising their legally protected rights. The plaintiffs contend that the AI‑assisted selection process effectively turned neutral‑looking data into a proxy for discrimination, thereby breaching statutory prohibitions against bias based on pregnancy, disability, and related leave status.
Plaintiffs’ Requested Relief
Seeking to halt what they view as an ongoing harm, the plaintiffs ask the court to issue a “preliminary injunction maintaining the status quo of their employment” at Meta while the case proceeds. They also request an independent audit of the algorithmically assisted selection process to examine whether the AI models incorporated prohibited variables or produced discriminatory outcomes. Finally, the complaint asks that any merits of the claims be resolved through arbitration, as stipulated in the employees’ employment agreements, rather than through a prolonged court battle.
Meta’s Official Response
A Meta spokesperson responded to CNBC via email, rejecting the allegations outright:
“Workforce management and organizational decisions were and are made by people, not AI.”
The spokesperson added that the “claims lack merit and are not based on facts.” Meta’s position is that any layoff decisions rested with human managers who considered a holistic view of employee performance, and that the AI tools referenced in the suit were merely supportive analytics, not determinative factors. The company maintains that its internal review processes already safeguard against discriminatory outcomes.
Parallel Case: Workday’s AI Hiring Tools
The Meta lawsuit arrives shortly after a federal judge in California ruled against Workday in a separate employee‑related lawsuit concerning AI‑powered job screening services. In that case, the judge determined that Workday must face claims that its recruiting software allegedly violated state and federal anti‑discrimination laws. Workday denied the allegations, stating:
“Our technology looks only at job qualifications, not protected traits like race, age, or disability,” and that it rigorously tests its products as part of its Responsible AI program to ensure no harm to protected groups.
The similarity between the two cases underscores a growing judicial willingness to scrutinize whether AI systems, even when designed to be neutral, can produce disparate impacts that run afoul of existing employment protections.
Broader Implications for AI in the Workplace
Both the Meta and Workday disputes highlight a critical tension: employers increasingly rely on algorithmic tools to streamline decisions about hiring, performance evaluation, and layoffs, yet those tools can inadvertently encode or amplify biases present in the data they consume. When metrics such as token consumption or productivity scores are used without adjusting for legitimate absences or accommodations, they may disadvantage employees exercising legally protected rights. Legal experts warn that without explicit safeguards—such as bias audits, transparency reports, and human‑in‑the‑loop oversight—companies risk violating anti‑discrimination statutes and facing costly litigation.
The outcomes of these cases could shape future regulatory guidance and corporate best practices. Employers may need to revisit how they design, test, and deploy AI‑driven HR technologies, ensuring that protected‑class variables are explicitly excluded and that alternative measurements account for leave‑related fluctuations in output. Moreover, employees and advocacy groups are likely to press for greater algorithmic transparency, including disclosure of the specific variables and weighting schemes used in employment decisions.
Conclusion
The lawsuit filed by Meta employees represents a salient example of how AI’s expanding role in workforce management is intersecting with longstanding employment protections. By alleging that the company’s AI‑based layoff selection unfairly penalized workers on protected leave and those with disabilities, the plaintiffs are pushing for judicial intervention that could compel Meta—and potentially other tech firms—to reevaluate the fairness of their algorithmic tools. As the case proceeds, it will serve as a bellwether for how courts balance innovation in AI with the imperative to uphold non‑discriminatory practices in the modern workplace.
https://www.cnbc.com/2026/07/14/meta-lawsuit-layoffs-ai.html