Ethics and Bias in AI-Powered HR Systems

Abstract

This chapter examines the transformative role of AI in HR, highlighting its dual ability to boost operational efficiency while inadvertently reinforcing systemic biases. It analyzes the integration of AI in resume screening, employee monitoring, and workforce analytics, demonstrating how algorithmic decisions are influenced by historical data and design flaws. Examples such as biased recruitment tools and culturally insensitive emotion-recognition software underscore the ethical risks of opaque “black box” systems. Explores technical vulnerabilities, oversight deficiencies, and broader societal inequities, offering a multidisciplinary perspective on bias in AI-driven HR systems. It also provides strategic recommendations for enhancing transparency and ethical AI design through rigorous dataset auditing, bias-mitigation techniques, and collaborative governance frameworks. Ultimately, it serves as a roadmap for HR professionals, technologists, and organizational leaders striving to harness AI responsibly while ensuring that HR advancements align with principles of fairness, inclusion

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