A systematic review of human vs machine intelligence and ethical tensions in human resource management
TL;DR
A systematic literature review and comprehensive governance framework for responsible AI use in HRM is developed, indicating that AI adoption is prominent in recruitment, selection, and performance management, where algorithms shape evaluative decisions.
Abstract
Artificial Intelligence (AI) has significantly transformed Human Resource Management (HRM), causing ethical and governance challenges around algorithmic decision making. Despite growing research, the literature is conceptually fragmented and lacking an integrative framework to connect applications of AI models with ethical and governance strategies. This study aims to conduct a systematic literature review and develop a comprehensive governance framework for responsible AI use in HRM. A systematic literature review of 84-peer reviewed articles from 2018 to 2024 was conducted through applying PRISMA protocol. Identifying five core HR-functions and nine major ethical issues. Findings indicate that AI adoption is prominent in recruitment, selection, and performance management, where algorithms shape evaluative decisions. Thus, the applications are associated with bias, transparency, and accountability issues. We develop an integrative governance framework highlighting maturity model, legitimacy, and accountability theory to address these concerns. Shifting the focus from AI adoption to governance, advancing literature on AI-HRM, and creating a clear framework for ethically responsible AI management. Offering actionable practical insights for HR professionals, AI developers, and policy makers on the implementation of responsible AI.