AI in hiring and layoffs raises new transparency concerns

Employment discrimination has always operated as a black box. Workers denied promotions or selected for layoffs rarely understand the reasoning behind those decisions, making it difficult to identify unlawful bias or hold employers accountable. Now, artificial intelligence threatens to make that opacity even worse.

A lawsuit filed against Meta by 24 former employees illustrates the emerging problem. The complaint alleges that AI substantially influenced layoff selections, disproportionately targeting employees on protected medical and family leave. According to the suit, Meta's algorithmic system relied on performance ratings, calibration scores, and productivity metrics that employees on leave could not accumulate by design.

The case underscores a fundamental challenge: tech companies will likely claim their AI-driven employment practices constitute proprietary information, shielding the decision-making process from scrutiny even when discrimination is alleged.

The testing gap

Many AI hiring and employment tools receive minimal testing before deployment, according to investigative journalist Hilke Schellmann, author of The Algorithm: How AI Decides Who Gets Hired, Monitored, Promoted, and Fired. Speaking at Seattle University School of Law's Summer Initiative for Technology, Innovation, and Ethics, Schellmann explained that tool builders often treat their systems as proprietary.

This creates a dangerous assumption cycle. Employers deploying AI products may not know what data trained the algorithms, how they were developed, or whether anyone evaluated them for bias. Yet organizations frequently assume that commercially available AI tools have already been vetted for fairness—an assumption that is often wrong.

Why it matters

As AI adoption accelerates in HR departments, the gap between algorithmic decision-making and worker transparency widens. Without visibility into how these systems operate, employees face greater difficulty proving discrimination even when it occurs. The problem extends beyond individual cases: systemic bias can become embedded at scale, affecting hiring, promotions, performance reviews, and terminations across entire organizations. Establishing worker-centered principles for AI employment tools is becoming urgent as more companies integrate these technologies without adequate safeguards.

A path forward

Washington state, home to major tech companies advancing AI development, has an opportunity to lead on this issue. An AI task force administered by the state attorney general recently published recommendations for worker-centered principles governing AI in employment, noting that while these technologies can improve efficiency, they also introduce risks of bias, inequity, and oversurveillance.

Although a bill calling for a workplace AI advisory group did not pass during the 2025 legislative session, the need persists. Whether through legislation or a governor-convened work group, bringing together workers, employers, technologists, and civil rights experts could establish transparent standards for algorithmic employment decisions.

The details were first reported by Chelsey Glasson in Fast Company, drawing on her experience fighting pregnancy discrimination in Big Tech and subsequent research into AI's role in employment practices.