Promoting Fairness and Ethical Practices in AI-Based Performance Management Systems: A Comprehensive Literature Review of Bias Mitigation and Transparency

Abstract

AI-based performance management in HR offers significant benefits by providing continuous, data-driven evaluations and reducing human bias. However, this shift raises concerns about privacy, fairness, and transparency, highlighting the need for a robust ethical framework. This study conducts a thorough literature review to analyze the ethical challenges of AI-based performance management systems and identify bias mitigation strategies in HR. The results emphasize the importance of a proactive approach and continuous evaluation to reduce bias and ensure fairness and transparency. By addressing these ethical challenges, organizations can create a more objective and effective performance management process that drives success.