The recent ruling in Mobley v. Workday has significant implications for employers who use Workday to screen applicants. The case alleges that Workday’s AI-powered applicant screening tools discriminate based on race, age, and disability. While the case is ongoing, the court’s decision to allow the lawsuit to proceed as a class action has far-reaching consequences for employers and AI vendors.
For context, Mobley is a Black man over the age of 40 who identifies as having anxiety and depression. He holds a finance degree from Morehouse College. Between 2017 and 2024, Mobley applied for over 100 jobs at companies using Workday’s AI-based hiring tools and claims he was rejected every time. Mobley alleges that these AI systems incorporate illegal biases and rely on prejudiced training data, resulting in a disparate impact. Specifically, he contends that the AI could infer his race from his graduation from a historically Black college, determine his age from his graduation year, and identify his mental disabilities through personality tests.
Workday requested the district court dismiss the lawsuit; however, on July 12, 2024, the court declined and noted that “there is no meaningful distinction between software decision-makers and human decision-makers for purposes of determining coverage as an agent under the anti-discrimination laws.” This decision allows the case to proceed as a class action. Additionally, the Equal Employment Opportunity Commission (EEOC) filed an amicus brief supporting a class action against Workday, arguing that AI vendors can bear direct liability under federal anti-discrimination laws, similar to traditional employment agencies.
This case highlights the scrutiny of algorithms and data used in applicant screening. Employers can expect increased audits and potential legal challenges to their hiring processes. If the allegations are proven, employers relying on Workday’s AI screening tools could be liable for discriminatory practices, as the court determined that Workday could be considered an “agent” of the employer, sharing responsibility for hiring decisions.
Artificial intelligence is a rapidly evolving field, but these systems often lack the nuanced understanding and contextual awareness of human decision-making. Relying solely on AI for hiring decisions is risky. Human judgment is critical in reducing biases and disparate impacts, catching errors, and ensuring adherence to various federal, state, and local laws and regulations.
Next Steps
Employers must exercise greater diligence in evaluating and selecting AI-powered tools, including understanding the algorithms, data sources, and potential biases. It is essential to remain vigilant in complying with federal, state, and local anti-discrimination laws, which include conducting regular audits, training employees, and establishing clear policies and procedures for AI use.
To better understand how to reduce risk and ensure compliance with equal employment opportunities laws, employers are encouraged to review the EEOC’s technical assistance document, “Assessing Adverse Impact in Software, Algorithms, and Artificial Intelligence Used in Employment Selection Procedures Under Title VII of the Civil Rights Act of 1964,” which is focused on preventing discrimination against job seekers and workers and explains the application of key aspects of Title VII of the Civil Rights Act (Title VII) and the Americans with Disabilities Act (ADA).
Employers should regularly assess the performance of AI tools to identify and mitigate discriminatory patterns. This includes conducting thorough reviews of hiring processes to detect potential biases and areas for improvement. Keep in mind, that regular audits may even be mandated by other laws, such as New York City’s AI bias audit law.
Additionally, employers should train recruiters, hiring managers, and other professionals on unconscious bias and fair hiring practices.
