In a federal court in Oakland, California, twenty‑six former employees of Meta Platforms have lodged a collective lawsuit accusing the company of deploying AI‑driven tools that disproportionately selected workers with disabilities or who had taken medical leave for a large‑scale layoff. The complaint alleges that Meta relied on metrics such as productivity scores and AI‑token usage, effectively penalising those who missed work for health reasons.

Background

Earlier this year, Meta announced plans to cut roughly 10 % of its global workforce—about 8,000 jobs—beginning in May, with further reductions slated for later in the year. The move came amid a broader industry trend of cost‑cutting and restructuring. However, questions emerged about the role of artificial intelligence in the decision‑making process, especially after internal documents suggested that health‑related data was fed into the algorithmic model, raising concerns of discriminatory outcomes.

Legal Allegations

The lawsuit claims that Meta violated both federal and state statutes that prohibit discrimination and retaliation against employees with disabilities, those on medical leave, or who are pregnant. The plaintiffs, representing six states including California and New York as well as the District of Columbia, argue that the AI system flagged their medical absences as negative performance indicators, thereby unfairly influencing layoff decisions.

Meta’s Response

A Meta spokesperson responded on Tuesday, asserting that the claims lack merit and emphasizing that “workforce management and organisational decisions were and are made by people, not AI.” The company contends that AI tools serve only as decision‑support aids, with final actions taken by human managers—a stance that seeks to distance the firm from direct liability for algorithmic bias.

Implications for the Tech Sector

If the plaintiffs prevail, the case could set a precedent compelling tech firms to overhaul AI‑driven HR systems, ensuring greater transparency, data protection, and compliance with anti‑discrimination laws. Regulators may push for stricter oversight of algorithmic decision‑making, prompting companies to adopt more rigorous bias‑mitigation strategies and to document how AI inputs intersect with protected employee characteristics.