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08/19/2025

Another Employer Faces AI Hiring Bias Lawsuit

Source: Fisher Phillips, August 15, 2025

An unsuccessful job applicant is suing Sirius XM Radio in federal court, claiming the company’s AI-powered hiring tool discriminated against him based on his race. Filed on August 4 in the Eastern District of Michigan, the plaintiff in Harper v. Sirius XM Radio, LLC alleges that the company’s AI system relied on historical hiring data that perpetuated past biases – resulting in his application being downgraded despite his qualifications. The lawsuit accuses Sirius XM of violating federal anti-discrimination statutes by the way it leverages AI tools in hiring, an allegation that we’re seeing more and more of lately. Here’s what you need to know about this case and how it fits into the larger puzzle of workplace AI litigation – plus 10 best practices you should follow as a result.  

Case Summary: Harper v. Sirius XM Radio

  • Court: U.S. District Court, Eastern District of Michigan (2:25-cv-12403)
  • Filed: August 4, 2025
  • Judge: Hon. Terrence G. Berg
  • Complaint: Available by clicking here

In Harper, a job applicant proceeding pro se (representing himself without an attorney) just filed suit in a Michigan federal court.

  • Arshon Harper alleges that Sirius XM relied on an AI-powered hiring system (iCIMS Applicant Tracking System) that embedded historical biases into its evaluation process, resulting in his rejection from approximately 150 positions despite his alleged qualifications in the IT field.
  • According to the complaint, the iCIMS Applicant Tracking System analyzed application materials and assigned scores based on data points that proxy for race (such as educational institutions, home zip code, employment history, etc.), which Harper contends disproportionately disadvantaged African-American candidates.
  • He claims this automated scoring caused his candidacy to be downgraded and for his applications to be eliminated before he could advance to later stages of the hiring process.

Harper asserts two legal theories: disparate treatment, alleging intentional discrimination in the design or use of the AI tool; and disparate impact, claiming the tool’s outcomes had an unlawful discriminatory effect even if the bias was unintentional.

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