A group of 26 former Meta employees has filed a lawsuit alleging the company used artificial intelligence tools to unfairly target workers on protected leave for layoffs, a case that brings new scrutiny to how large technology firms deploy internal AI systems in workforce management decisions. The lawsuit, filed in a California court, claims Meta’s reliance on a suite of proprietary AI tools to score and rank employees effectively penalized those who took parental or medical leave, disproportionately selecting them for termination during a company-wide reduction in force.
How Meta’s AI tools allegedly scored employees for layoffs
The former employees allege that Meta used a “constellation” of internal AI systems to evaluate worker performance and determine who should be dismissed. These tools reportedly included an internal AI assistant called Metamate, employee-trained AI agents, and internal dashboards that tracked AI token usage. Together, these systems generated scores and rankings that were then used to compile a termination list. The core of the complaint is that this scoring mechanism failed to account for periods when employees were on legally protected leaves, such as parental or medical leave. The result, according to the lawsuit, was that the AI-based evaluation penalized workers precisely for exercising their legal rights to take time off.
The context of the layoffs and the company’s response
The layoffs in question occurred in May as part of Meta’s broader plan to cut approximately 10 percent of its workforce, or around 8,000 employees. This reduction was part of ongoing cost-cutting measures at the social media giant. In response to the lawsuit, Meta spokesperson Tracy Clayton stated, “These claims lack merit and are not based on facts. Workforce management and organizational decisions were and are made by people, not AI.” This defense directly counters the plaintiffs’ central argument that AI systems, not human discretion, were the decisive factor in selecting which employees to let go.
What the lawsuit alleges about AI bias in workforce decisions
The lawsuit accuses Meta of violating both federal and state laws that prohibit employers from terminating workers for taking protected leave. The core legal question is whether the use of AI-based performance scoring systems constitutes a form of discrimination when they disproportionately affect employees who exercised their right to medical or parental leave. The plaintiffs argue that by deploying AI tools that did not account for leave periods, Meta created a system that was inherently biased against those workers. This case is distinct from other AI bias litigation because it focuses not on hiring or promotion bias, but on the use of AI in termination decisions, an area that has received less regulatory and legal attention.
Why this case matters for the broader AI industry
This lawsuit has significant implications for how companies across the technology sector and beyond design and deploy internal AI tools for human resources and workforce management. The case tests the legal boundaries of employer liability when AI systems are used to make or inform consequential employment decisions. If the court finds that Meta can be held responsible for the discriminatory impact of its AI scoring systems, it could set a precedent forcing companies to more rigorously audit their internal AI tools for bias, especially regarding protected characteristics like leave status. For organizations currently using or considering AI for employee evaluations and layoff decisions, this case underscores the importance of ensuring that training data includes all relevant contextual factors and that models are not designed in a way that inadvertently penalizes protected behaviors.
What organizations should do now
For any company using or evaluating AI tools for performance management, workforce planning, or termination decisions, this lawsuit serves as a clear warning. It is critical to audit internal AI systems to ensure that any scoring or ranking mechanism does not inadvertently incorporate or amplify biases related to legally protected activities like taking medical or family leave. Organizations should document the specific inputs their AI models use and verify that those inputs do not create a disparate impact on protected groups. This is not just a legal or compliance issue—it is a matter of AI governance and responsible deployment. As this case progresses, it will likely provide important guidance on how courts interpret the intersection of employment law and artificial intelligence, making it a development that every AI and software professional should monitor closely.
