Human Authority in the Age of Intelligent Systems: A Sociotechnical Framework for Decision Assurance and Psychosocial Safety

Abstract

The rapid integration of intelligent systems into high-risk industries is reshaping how work is performed, decisions are made, and responsibility is distributed. While automation and artificial intelligence promise gains in efficiency, safety, and productivity, they also introduce under-recognised sociotechnical risks, including degraded human decision authority, cognitive overload, loss of practical expertise, and increasing psychosocial strain associated with uncertainty and workforce transition. This paper argues that current approaches to human factors engineering and system design are insufficient to address these conditions. While technical assurance frameworks for AI-enabled systems continue to mature, equivalent structures for ensuring the integrity, clarity, and sustainability of human decision-making remain underdeveloped. This gap presents a critical risk in high-reliability environments where human judgment is essential for managing variability, uncertainty, and system failure. Drawing on applied experience in automation-intensive operations and informed by an emerging global research agenda, this research introduces the Human Authority Index (HAI) as a novel sociotechnical framework developed by the author for assessing and designing decision-making in human–machine systems. The HAI positions human authority as a safety-critical variable across three dimensions: Decision Clarity, Cognitive Sustainability, and Psychosocial Safety. Together, these dimensions extend traditional human factors approaches by integrating organisational psychology, sociotechnical systems theory, and resilience engineering into a unified model. Through conceptual analysis and industry-informed scenarios, the paper demonstrates how poorly integrated automation can create hidden system fragility, while systems designed with clear human authority exhibit greater resilience and workforce engagement. This research contributes a practical framework to support safe, effective, and meaningful human participation in increasingly autonomous environments.