AI screening tools are used by most large employers — and increasingly by AI training platforms themselves, as we describe in our review of Mercor's AI video interview. A major ongoing lawsuit is directly testing what legal accountability for these systems looks like.
What Mobley v. Workday Is About
Mobley v. Workday, Inc., Case No. 4:23-cv-00770 (N.D. Cal.), was filed in 2023 by Derek Mobley — a Black applicant over 40 with a disability — who alleges he was rejected from over 100 positions through Workday's AI hiring platform, often within minutes of applying, including at non-business hours. The lawsuit argues Workday's AI discriminated based on age, race, and disability.
The "Disparate Impact" Theory
The lawsuit operates on the principle of disparate impact — a system can produce discriminatory outcomes without anyone intending to discriminate. The complaint argues Workday's AI models were trained on incumbent employee data from historically less diverse workforces, causing the algorithm to systematically favor certain candidate profiles. A 2024 University of Washington study found that text embedding models used in resume screening favored white-associated names in 85.1% of cases.
Current Status in 2026
As of mid-2026, the case is in active litigation. A Third Amended Complaint was filed March 2026 adding new plaintiffs and expanding race claims to include Asian Americans. The court has ruled that Workday acted as an "agent" of the employers using its screening — a significant designation creating direct liability. The nationwide collective action authorization covering potentially millions of applicants over 40 remains active. A separate January 2026 lawsuit, Kistler v. Eightfold AI, targets similar practices at a platform used by Microsoft, PayPal, and Morgan Stanley.
"Human bias is retail; algorithmic bias is wholesale." — Jones Walker LLP, February 2026
What This Doesn't Mean for Our Reviewed Platforms
To be clear on scope: the Workday lawsuit specifically targets AI screening for traditional employment hiring. Platforms we review — Mercor, micro1 — screen for freelance contractor roles under a different legal framework. This is worth understanding accurately rather than assuming direct equivalence. That said, the underlying principle — that AI screening can produce biased outcomes regardless of intent — applies broadly as a concept.
The Practical Takeaway
If you've been rejected from positions through Workday-screened applications while over 40, between September 2020 and 2026, the collective action is worth researching directly (docket: Mobley v. Workday, Inc., 4:23-cv-00770). More broadly, building application strategies around how AI systems actually evaluate candidates — including the resume-specific guidance in our RLHF keywords guide and AI training resume piece — is increasingly important as these systems proliferate.
What the Lawsuit Alleges
The lawsuit against Workday's AI hiring tool alleges that the automated screening system disproportionately rejected candidates based on protected characteristics — with plaintiffs arguing the AI perpetuated discrimination at scale that would have triggered legal scrutiny in individual human hiring decisions. The case centres on whether AI hiring tools are subject to the same disparate impact standards as traditional employment screening, and whether companies using third-party AI screening tools are liable for their discriminatory outputs.
Why This Matters for AI Training Contractors
The Workday lawsuit is directly relevant to the AI training contractor market because it illustrates the stakes of poor AI evaluation. Human evaluators working on AI hiring-adjacent tasks — including resume screening, candidate assessment, and qualification evaluation — are part of the quality chain that either catches or misses discriminatory patterns. This is a structural argument for higher-quality, more diverse AI evaluation workforces. Contractors with knowledge of employment discrimination law or HR practice are increasingly valuable for these evaluation tracks.
Navigate AI Screening More Effectively
See our application guides and start with verified platforms.