Industry 5.0 promotes a human-centric approach to technological innovation, emphasizing collaboration between humans and intelligent systems. Within this paradigm, trust represents a fundamental condition for effective and reliable interaction. This study explores the dynamics of trust by integrating a theoretical analysis and an empirical case study. The first part of the research presents a literature-based examination of human–AI trust, identifying key influencing factors such as reliability, transparency, explainability, accountability, and ethical alignment. These insights informed the second phase of the study, which investigated a virtual reality (VR) training system equipped with a voice-based virtual assistant designed to support procedural skill learning. Participants completed a Trust in Automation (TiA) questionnaire covering six dimensions of trust, providing an overview of how users perceive reliability, clarity, and understanding within immersive training environments. Building on these findings, the paper discusses design considerations for developing trustworthy and human-centered VR training systems. It highlights the importance of calibrated feedback, communicative clarity, and transparency as essential elements for fostering trust and effective collaboration between humans and intelligent systems.
Mirabelli et al. (Thu,) studied this question.