Title:
The AI-augmented Safety Governance Model (AASGM): A Socio-technical Framework for Real-time Hazard Detection, Human Oversight, and Regulatory Alignment

Authors:
Dr. Robb Shawe, USA

Abstract:

This manuscript introduces the AI-Augmented Safety Governance Model (AASGM), a socio-technical framework that integrates artificial intelligence–enabled hazard-detection systems with human oversight, organizational safety culture, and regulatory compliance structures. Building on empirical findings from YOLO-based hazard detection across multiple industries, the model conceptualizes how real-time detection technologies interact with human decision-making, governance processes, and safety management systems. The AASGM positions artificial intelligence as an augmentation layer within a broader socio-technical system, emphasizing transparency, accountability, and human-centered implementation. The framework provides a structured approach for organizations seeking to operationalize AI in occupational safety while maintaining alignment with regulatory expectations and ethical considerations. The model advances Safety 4.0 by bridging technical capabilities with governance and organizational integration.

DOI: http://dx.doi.org/10.51505/ijaemr.2026.11315