This study examines how human-AI (Artificial Intelligence) collaboration can address the challenges posed by cognitive biases and bounded rationality in Human Resource Management (HRM). In today's complex environment, human judgment is influenced by factors such as cognitive bias (systematic errors in thinking)and bounded rationality, which is the tendency to make satisfactory rather than optimal decisions due to cognitive limitations. These issues can compromise the fairness and efficiency of HRM processes such as recruitment and performance evaluation. AI offers a solution by enabling objective, data-driven decision-making. However, AI systems can also reinforce biases present in their training data. The paper proposes a framework of "dual dynamics" where AI acts as a cognitive partner, not just a tool, to enhance human judgment by identifying bias patterns and simulating alternative scenarios. This approach integrates AI's analytical power with human empathy and ethical reasoning to foster more equitable and rational decision-making. Case studies in human resources analytics illustrate this partnership. In recruitment, companies like SoftBank and Unilever use AI to reduce bias and increase efficiency in tasks such as resume screening and video interviews, while human oversight remains for final decisions. In talent development, Coca-Cola uses AI to recommend career paths and learning opportunities, helping employees navigate complex decisions. The paper concludes that AI's transformative potential in HRM hinges on the co-evolution of humans and AI, with each leveraging the other's strengths and offsetting their respective weaknesses. Future research should explore ways to improve AI's understanding of emotional cues and to strengthen human trust in AI-driven decision-making.
Yukiko Nakagawa (Sun,) studied this question.