Ensuring ADA compliance in AI hiring: review, analysis, and disability discrimination framework

Abstract

Artificial intelligence (AI) is revolutionizing hiring processes with the use of automated tools, including resume screening algorithms, video interviews, and chatbots, which offer increased efficiency and scalability. However, these technologies often fail to accommodate the diverse needs of disabled individuals, who already face disproportionately high unemployment rates. This results in potential noncompliance with the Americans with Disabilities Act (ADA), which mandates equal opportunities and reasonable accommodations in employment. The opacity of AI algorithms, often described as a “black box,” exacerbates challenges in detecting and correcting bias. This study uses a systematic review methodology to analyze existing literature, case studies, and regulatory frameworks, evaluating the alignment of AI hiring systems with ADA standards. Insights from this approach inform recommendations for accessible design principles, explainable AI (XAI) technologies, bias audits, and the importance of human oversight. These findings provide a roadmap for harmonizing innovation with inclusivity, advancing policy discussions to ensure fairness, transparency, and equity in employment for individuals with disabilities.