Title:
Regulatory Implications of AI-enabled Hazard Detection: Aligning YOLO-Based Safety Systems with OSHA and New York State Frameworks

Authors:
Dr. Robb Shawe, USA

Abstract:

This research examines the regulatory implications of integrating AI-enabled hazard-detection systems, specifically YOLO-based computer-vision technologies, into occupational safety frameworks in New York State. The study evaluates the alignment of real-time detection systems with existing OSHA standards and state-level regulatory requirements. Findings indicate that while AI technologies significantly enhance hazard detection performance and compliance monitoring, current regulatory frameworks remain largely structured around manual inspection models. The paper introduces a governance-based approach, grounded in the AI-Augmented Safety Governance Model (AASGM), to support the integration of AI systems within existing regulatory environments. The findings highlight the need for adaptive regulatory strategies that incorporate real-time monitoring, human oversight, and accountability mechanisms. The study contributes to the advancement of Safety 4.0 by bridging technological innovation with regulatory policy and governance structures.

DOI: http://dx.doi.org/10.51505/ijaemr.2026.11316