How Autonomy and Trust Influence Patient Satisfaction Under Dynamic Dependencies

Autonomy and trust are central concepts in sociology and psychology and are particularly relevant to the study of hybrid societies in which human and artificial agents interact. Trust is essential for effective collaboration across a wide range of contexts, and the benefits of interacting with autonomous agents for facilitating goal achievement are well established. However, the complex interplay between trust and autonomy remains insufficiently understood, especially in sensitive domains such as healthcare, where ethical values, patient safety, and inter-agent dependencies must be carefully managed. In this work, we employ a multi-agent simulation to investigate the roles of autonomy and trust in relation to patient satisfaction. Our results show that higher levels of autonomy—enabling agents to modify delegations and exploit dependencies—effectively support implicit goal discovery and can enhance explicit goal achievement. Nevertheless, such autonomy may be detrimental compared to lower levels of autonomy that only allow dependency exploitation. This effect is particularly evident in contexts with large pools of partners who lack sufficient competence but are willing to accept multiple concurrent delegations. Conversely, in environments characterized by heterogeneous trustworthiness, higher autonomy proves advantageous, as it enables agents to more effectively discover and leverage dependencies.