Lawsuit Alleges Meta’s AI Targeted Leave-Taking Employees in Layoffs

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Meta is under legal scrutiny as dozens of its employees have lodged a lawsuit claiming that the company utilized artificial intelligence to select staff for layoffs, disproportionately impacting those on maternity leave, medical leave, and individuals with disabilities. The legal action, submitted in a federal court in California, asserts that Meta leveraged AI-driven performance evaluations and employee activity metrics for workforce reductions, affecting about 8,000 employees earlier this year.

The lawsuit details how Meta purportedly used internal AI systems to score and rank employees for layoffs, sidelining the traditional approach of manager evaluations. This system, the plaintiffs argue, failed to properly account for periods of approved leave, leading to unfairly low performance scores for those who had taken family or medical leave or who were receiving disability accommodations. Among those involved in the case is a scientist who received notice of her dismissal just two days before she was due to give birth, an engineer whose performance rating reportedly suffered due to absence from an injury, and a manager who was laid off shortly after starting medical leave.

The affected employees are pursuing a court injunction to pause the layoffs during the legal proceedings. They are also seeking reinstatement, financial compensation for lost wages and benefits, and an independent audit of the AI systems used by Meta. Despite these allegations, Meta has refuted the claims, maintaining that decisions regarding workforce and organizational changes are made by humans, not AI systems.

This case highlights increasing concerns over AI’s role in workplace decision-making, with critics suggesting that such automated systems may introduce bias, particularly against employees who utilize legally protected leave. The outcome of this lawsuit could set a significant precedent for how AI is employed in corporate environments, especially in terms of fairness and accountability.

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