Human-AI Collaboration and Trust in Human Resource Management: Opportunities, Challenges and Framework for Fair Implementation
TL;DR
The review concludes that trust in AI is separate from trust in human colleagues, that the process shapes trust and the delegation of trust can improve employees’ performance and overall satisfaction, even when the trust is not complete.
Abstract
AI is being increasingly integrated into HRM, modifying recruitment, performance analysis, learning and development, and managerial decisions. This paper uses eighteen recent organizational psychology studies and focuses on information systems and human-computer interaction. It provides a synthesis on what triggers trust between employees and AI, the human-algorithm workload balance, and fairness concerns regarding AI in people management and assessment. The review concludes that trust in AI is separate from trust in human colleagues, that the process shapes trust and the delegation of trust can improve employees’ performance and overall satisfaction, even when the trust is not complete. This review also notes that trust, explainability, accountability, and the varying perceptions of fairness limit the deployment of AI. Task Division, trust construction, varying perceptions of fairness, and the organizational structure are the main components of the Human-AI and HRM collaboration system, which this review seeks to examine. It also identifies research gaps.