Investigating Recruitment System Algorithmic Discrimination using AI and Bias

Abstract

AI is being employed in hiring. This raises concerns about algorithm racism and bias. This essay examines AI's role in employment systems, including prejudice in hiring algorithms. AI employment tools are supposed to speed up and improve candidate selection, but they often use old data that may reflect gender, race, or socioeconomic prejudices. how AI systems can unwittingly reinforce these biases, leading to unfair or discriminatory hiring practices. The study examines where bias comes from in AI models, what occurs when bias-based choices are made, and the moral consequences for employers and job seekers. This is done thru case studies and AI-driven recruitment platform analysis. Open data, varied data, and algorithmic audits can reduce bias in AI hiring systems, according to this study. The report emphasizes the need to appropriately employ AI in recruiting to ensure fairness and bias-free practices.