A Framework for Integrating AI-Powered Systems to Mitigate Bias Risk in HRM Functions - Naoum, Rawiah (Marketing & Menedzsment, 2025)
THE AIM OF THE PAPER This paper investigates the dual role of artificial intelligence (AI) in human resource management (HRM), assessing its capacity to both perpetuate and mitigate biases, particularly within the framework of diversity, equity, and inclusion (DEI). The goal is to identify the sources of AI-induced biases in HRM and establish a strategic framework to effectively reduce these biases. METHODOLOGY This paper conducts a thorough literature assessment on the application of AI in HRM and its implications on DEI efforts. The review draws on a wide range of academic sources, including major databases like Web of Science and Google Scholar, to isolate the mechanisms through which AI tools introduce biases in HR functions such as recruitment, performance assessment, and compensation. MOST IMPORTANT RESULTS The investigation highlights that AI-induced biases in HRM are mainly attributable to three sources: human influence in the design and operation of AI tools, biases inherent in the datasets employed for training AI, and the algorithms’ intrinsic biases. These elements collectively contribute to reinforcing discriminatory practices within organizations, thereby impeding DEI initiatives. RECOMMENDATIONS To combat these biases, the paper proposes a robust framework encompassing four key strategies: enhancing AI and DEI literacy among HR professionals, adopting inclusive design practices for AI tools, ensuring accountability in dataset management, and promoting transparency in AI implementations. These measures aim to equip organizations with the tools to integrate AI into HRM in a manner that fosters an inclusive, fair, and equitable workplace environment.