Ensuring Equity in AI-Based HR Decision-Making: An Algorithmic Fairness Approach to DEI Governance

The rapid integration of artificial intelligence (AI) into human resource (HR) decision-making systems has transformed organizational practices in recruitment, performance evaluation, promotion, and workforce analytics. While these technologies promise efficiency and objectivity, growing evidence indicates that AI systems may reproduce or amplify existing social and organizational biases, thereby undermining diversity, equity, and inclusion (DEI) objectives. This study addresses the critical challenge of ensuring equity in AI-based HR systems through an algorithmic fairness lens. The paper develops a conceptual governance framework that integrates technical fairness metrics, organizational oversight mechanisms, and ethical principles into HR decision-making processes. Drawing on interdisciplinary insights from human resource management, AI ethics, and governance theory, the study identifies key sources of algorithmic bias, evaluates prevailing fairness criteria, and proposes a multi-layered DEI governance model. The findings emphasize the necessity of embedding fairness auditing, transparency, and human oversight into AI systems to prevent discriminatory outcomes. The study contributes to the emerging discourse on AI governance by bridging the gap between technical algorithmic design and organizational DEI strategies. It offers practical implications for policymakers, HR professionals, and organizational leaders seeking to align technological innovation with equitable workforce practices.

کلیدواژه ها:

Artificial intelligence ، Decision-making systems ، DEI ، Biases ، Algorithmic Fairness