Rejected by a Robot: AI Hiring and Its Consequences for Discrimination Law

By Erin Alvis '27

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In 2023, a plaintiff filed a discrimination suit against Workday Inc., a major and widely used recruiting platform in the United States. The plaintiff, Derek Mobley, alleged that Workday’s AI screening tools violated federal discrimination laws. Derek Mobley, a disabled black man over the age of 40, alleges that he was rejected almost immediately from over 100 jobs on Workday’s platform due to these demographic factors. The case was allowed to move forward in 2024 as a class action lawsuit in California and remains in the pleadings and motion-to-dismiss phase. The core dispute in this case has highlighted the difficulties of prosecuting and assigning responsibility for AI-related potential hiring discrimination. This is largely due to the limited amount of AI hiring law in the United States. Mobley v. Workday is one of the first lawsuits of its kind in AI law. The case is the first AI case to apply employment law to a hiring “agent” like Workday, rather than to employers themselves. (1) The Mobley v. Workday case has demonstrated the need for legislation to protect employees from AI hiring practices. 

Pros and Cons of AI Law

This court case could impact millions of job applicants. According to Workday, its platform is used by 65% of Fortune 500 companies and processes 30% of all job openings. (2)  Broader AI hiring is also used by an estimated 88% of American companies for first-round screening. Some companies advocate for AI hiring platforms, arguing that they increase efficiency and benefit businesses and applicants. AI hiring platforms, like Workday, these businesses argue, can reduce HR costs, allow for the review of more applicants, and help companies remain unbiased in the search for the alleged best candidate. Some AI companies argue that AI platforms reduce affinity bias and the halo effect in human hiring. These companies explain that human HR agents favor applicants with backgrounds similar to their own or let one part of the applicant’s resume overshadow the rest, such as coming from an Ivy League school. (3) On the other hand, opponents of AI hiring practices argue that these technologies are harmful to applicants because AI-guided blind hiring standards can be discriminatory due to training biases or algorithmic removal of applicants. 

The concerns surrounding AI hiring are not new; the U.S. Equal Employment Opportunity Commission issued statements in 2022 warning against disability discrimination from software and AI. The federal agency is responsible for advancing opportunity in the workplace by enforcing federal laws prohibiting discrimination. The organization’s statement emphasizes employers' responsibility to comply with federal anti-discrimination laws. The agency mandates that employers must have safeguards in place to prevent discriminatory hiring practices and provide reasonable accommodations to disabled applicants. (4)

These protections are at the core of the lawsuit in Mobley v. Workday. Mobley cites Title VII against allegations of racial discrimination, the Americans with Disabilities Act for hiring protections, and the Age Discrimination in Employment Act (ADEA) against allegations of ageism. (5) Mobley alleges that AI is susceptible to the algorithmic removal of applicants for these traits. When algorithms look for adherence to past applicants, discriminatory patterns can emerge, he argues. 

This problem with algorithmic tools is exemplified in Amazon’s hiring tool, created in 2014. A hiring tool was developed to rate applicants’ resumes on a point scale. The tool was trained on successful employee resumes. This training data leaned heavily toward males, leading the tool to learn that male applicants were favored and creating an unintentional bias against hiring women. This training data resulted in the tool deducting points from resumes when female terms, such as “women’s” or women’s-only colleges, were mentioned. Eventually, Amazon removed the algorithmic tool because the company could not guarantee gender neutrality. (6)

In Workday v. Mobley, Mobley alleges similar flaws in algorithms in Workday’s tools. He claims that the tool discriminates against applicants over 40, based on historical data and training methods. He argues that Workday does not purposefully discriminate, but due to its algorithm, the tool has an unintentional discriminatory effect. The disparate impact of these algorithms, he adds, results in the systematic and automatic removal of applicants. (7) Workday disputes these claims, stating that its hiring tools only evaluate standard, objective job qualifications and do not autonomously reject applicants. Despite Workday’s attempts to dismiss the case, the case was allowed to move forward as a class action suit. 

Hundreds of new plaintiffs who claim discrimination from Workday, aged 40 or older, are expected to join the lawsuit. This suit has strong implications for hopeful employees and employers, who could be the next responsible party in these AI hiring suits. 

Diffusion of Responsibility for AI Outcomes 

There are gray areas in AI hiring legislation that could be exploited. The core issue in Workday v. Mobley is the agent theory. For example, large companies outsource hiring to agents, creating a legal diffusion of responsibility for discriminatory practices. Mobley alleges that Workday, as an AI or software vendor, should be held liable for discrimination, rather than the companies using Workday’s software. They compare Workday to a hiring “agent” that autonomously rejects applicants. This line of thought assigns responsibility for disparate-impact discrimination to the agent, Workday.

Workday argues against this responsibility, objecting that all hiring restrictions are controlled by their managing companies. Workday compares itself to a hiring tool, while the hiring company makes the true, executive decision. This line of logic shifts responsibility for preventing discrimination to managing companies. Should Workday’s attempt to shift liability succeed, the case would break into thousands of lawsuits against the individual companies that use the software. 

Lack of Legislation in AI Hiring Practices

The novel approach to this rule stems from the lack of precedent or legislation in AI law. There is currently no federal legislation on AI hiring; no laws address these specific hiring practices. States like Illinois, California, and New York have mandated consent and disclosure laws for hiring managers who use AI, but many states have no such legislation. (8)

The European Union (EU) has the strongest laws surrounding AI hiring in the world. These laws mandate that companies conduct formal, ongoing bias audits. These European laws explicitly prohibit certain AI hiring practices, including the use of AI for emotion recognition or vocal tone analysis in video interviews. They also mandate meaningful human review and technical documentation before AI recommendations are finalized. If these requirements are not followed, employers are held strictly liable for any discrimination or AI-driven biases. (9)

In the United States, there are no such laws. There are currently no legislative protections against autonomous AI hiring. The lack of legislation governing AI hiring creates low barriers to applicant privacy violations and can expose employers to unintentional violations of discrimination laws. A more standardized AI hiring process is needed with ethical guidelines to prevent injustice to applicants. 

Solution

From these budding lawsuits in the United States, federal legislation is needed to hold employers and AI agents accountable. New legislation should explicitly state that employers or agents cannot delegate their Title VII and ADA obligations by shifting blame. As in the Workday v. Mobley case, where employers and Workday deflect blame onto each other. The burden of preventing discrimination should concretely rest on employers who act on AI-guided recommendations. Employers should be required to conduct ongoing monitoring of their hiring tools for discriminatory outcomes and to document that monitoring. Similar to practices used in the EU would be beneficial, where employers would need to provide risk assessments when using particular AI systems. These systems place the burden on employers using AI systems to provide a report of “identification and analysis of the known and the reasonably foreseeable risks” and “adoption of appropriate and targeted risk management measures.” (10) An unregulated hiring market will harm employees, and it is vital to enact proactive legislation to prevent such harm today and in the future.

AI hiring can have a dangerous effect if employers do not take proactive steps to prevent discrimination. These tools promise objectivity, but at the cost of civil rights. Class action lawsuits, such as Mobley v. Workday, seem to be the initial catalyst for similar AI discrimination lawsuits. These hiring practices have the potential to affect millions of Americans, and legislation is needed to prevent future victims of AI hiring. 

Endnotes

1. Annette Tyman, “Mobley v. Workday: Court Holds AI Service Providers Could Be Directly Liable for Employment Discrimination Under ‘Agent’ Theory,” Seyfarth Shaw, July 19, 2024, https://www.seyfarth.com/news-insights/mobley-v-workday-court-holds-ai-service-providers-could-be-directly-liable-for-employment-discrimination-under-agent-theory.html.

2. Workday, “Workday Announces Fiscal 2026 Fourth Quarter and Full Year Financial Results,” Investor.Workday.com, February 24, 2026, https://investor.workday.com/news-and-events/press-releases/news-details/2026/Workday-Announces-Fiscal-2026-Fourth-Quarter-and-Full-Year-Financial-Results/default.aspx.

3. TheHireHub.AI, “AI Bias-Free Hiring: Reduce Discrimination in 2026,” TheHireHub.AI, April 8, 2026, https://www.thehirehub.ai/blog/ai-bias-free-hiring.

4. “U.S. EEOC and U.S. Department of Justice Warn Against Disability Discrimination,” U.S. Equal Employment Opportunity Commission, https://www.eeoc.gov/newsroom/us-eeoc-and-us-department-justice-warn-against-disability-discrimination?utm_.

5. Ibid.

6. Jeffrey Dastin, “Insight - Amazon Scraps Secret AI Recruiting Tool That Showed Bias Against Women,” Reuters, October 10, 2018, https://www.reuters.com/article/world/insight-amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK0AG/.

7. “Brief of the Equal Employment Opportunity Commission as Amicus Curiae in Support of Plaintiff and in Opposition to Defendant’s Motion to Dismiss,” No. 3:23-cv-00770-RFL, 2024, https://www.eeoc.gov/sites/default/files/2024-04/Mobley%20v%20Workday%20NDCal%20am-brf%2004-24%20sjw.pdf.

8. “AI Law Center: Track Evolving AI Laws in the US, Europe & UK | Orrick,” https://ai-law-center.orrick.com/.

9. “Chapter I: General Provisions | EU Artificial Intelligence Act,” https://artificialintelligenceact.eu/chapter/1/.

10. “Article 9: Risk Management System | EU Artificial Intelligence Act,” https://artificialintelligenceact.eu/article/9/.