Title:
Human–AI Interaction in Occupational Safety: Worker Perceptions, Trust, and Safety Culture Implications of YOLO-Based Hazard Detection Systems

Authors:
Dr. Robb Shawe, USA

Abstract:

This research examines workers' and supervisors' perceptions of YOLO-based hazard-detection systems and their impact on safety culture in New York State workplaces. Using a qualitative research design, semi-structured interviews were conducted with employees, supervisors, and safety managers across construction, manufacturing, and healthcare environments. Thematic analysis revealed that AI-enabled hazard-detection systems enhance situational awareness, improve visibility into compliance, and contribute to a more proactive safety culture. Participants reported high levels of trust in AI-assisted monitoring when systems were implemented with transparency and human oversight. However, concerns related to privacy, over-surveillance, and potential over-reliance on automation were also identified. Findings indicate that the successful integration of AI in occupational safety depends on socio-technical alignment, human-centered implementation, and governance structures that reinforce trust and accountability. The study contributes to the understanding of human–AI interaction in safety-critical environments. The findings support the role of AI as an augmentation to human decision-making rather than a replacement.

DOI: http://dx.doi.org/10.51505/ijaemr.2026.11313