Trust and AI weight: human-AI collaboration in organizational management decision-making

Jiale WangXiaoxi Chen^*

• Jinan University, Guangzhou, China

The emergence of Artificial Intelligence (AI) has revolutionized decision-making in human resource management. Since human and AI each possesses distinct strengths in the realm of decision-making, the synergy between human and AI agent has the potential to significantly enhance both the efficiency and the quality of managerial decision-making processes. Although assigning decision weights to AI agents presents innovative avenues for human-AI collaboration, the underlying mechanisms driving the allocation of decision weights to AI agents remain inadequately understood. To elucidate these mechanisms, this paper examines the influence of trust in AI on AI weight allocation within the framework of human-AI cooperation, leveraging the Socio-Cognitive Model of Trust (SCMT). We conducted a series of survey studies involving scenario-based decision-making tasks. Study 1 examined the relationship between trust in AI and AI weight among 111 managers about employee recruitment tasks. The results indicated that trust in AI enhances the decisional weight attributed to AI agents, and willingness to collaborate with AI mediates trust in AI and the weight of AI in personnel selection. Study 2 surveyed 210 managers using employee performance evaluation tasks. The findings revealed that the perceived free will of AI agents negatively moderates the relationship between trust in AI and willing to collaborate with AI, such that the relationship is weaker when individuals perceive a higher degree of free will in AI agents than a lower degree. Theoretically, this paper advances the understanding of the function of trust in human-AI interaction by exploring the trust development from attitude to act in human-AI cooperative decision-making. Practically, it offers valuable insights into the design of AI agent and organizational management within the context of human-AI collaboration.