
Meta employees sue over layoffs they say were driven by discriminatory AI selection systems
Quick Answer
Meta faces a lawsuit from employees claiming that AI-driven layoff decisions disproportionately targeted those with disabilities and on medical leave.
Quick Take
Meta faces a lawsuit from employees claiming that AI-driven layoff decisions disproportionately targeted those with disabilities and on medical leave. The lawsuit, filed in California, alleges that the AI systems generated layoff lists based on performance metrics, with one plaintiff receiving notice just two days before childbirth. Meta denies these claims, asserting that all personnel decisions are made by humans.
Key Points
- Lawsuit claims Meta's AI systems targeted disabled employees during layoffs.
- 8,000 employees were laid off in May, with alleged discriminatory practices.
- Plaintiffs seek to maintain employment until arbitration resolves the case.
- Meta insists that human decision-makers are responsible for layoffs.
- One plaintiff received layoff notice just two days before giving birth.
📖 Reader Mode
~1 min readFormer and current Meta employees are suing the company over allegedly discriminatory layoffs carried out by AI. According to a lawsuit filed in a federal court in California, Meta allegedly used internal AI systems to generate layoff lists when it cut 8,000 employees in May. The systems supposedly targeted employees with disabilities and those on protected medical, family, or parental leave at disproportionate rates. One plaintiff was notified just two days before giving birth, the complaint states. The selection criteria allegedly included performance ratings, productivity, work output, and measured AI usage.
A Meta spokesperson denied the allegations, saying that humans make all personnel decisions. The plaintiffs are seeking a preliminary injunction to keep their jobs until the arbitration is resolved.
— Originally published at the-decoder.com
Want this in your inbox every morning?
Daily brief at your local 8am — bilingual EN/中文, free.
More from The Decoder
See more →
An AI model programmed nonstop for 19 days on a single MirrorCode task that cost $2,600 to run
Epoch AI's MirrorCode benchmark reveals Claude Opus 4.7 as the leader with a 56% solve rate, reconstructing a 16,000-line toolkit in 14 hours. Despite this, all models tested struggle with the most complex tasks, highlighting limitations in current AI capabilities. The single task consumed $2,600 over 19 days, raising questions about cost-effectiveness in AI development.

