2025/12/06 by Niclas Flehmig, Flehmig, Niclas, Mary Ann Lundteigen +3
Computer Science · Decision Sciences · Engineering · Health Professions · Psychology · #Computers and Society (cs.CY) #FOS: Computer and information sciences #FOS: Electrical engineering #Human-Automation Interaction and Safety #Human-Computer Interaction (cs.HC) #Occupational Health and Safety Research #Risk and Safety Analysis #Systems and Control (eess.SY) #cs.CY #cs.HC #cs.SY #eess.SY #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2512.06354
This paper was accepted for the IFAC World Congress 2026
openalex publication_date 2025/12/06 · openalex created_date 2025/12/10 · openalex updated_date 2026/07/28 · arxiv created 2026/07/30 · arxiv updated 2026/07/31
This paper addresses a critical gap in the risk assessment of AI-enabled safety-critical systems. While these systems, where AI systems assist human operators, function as complex socio-technical systems, existing risk evaluation methods fail to account for the associated complex interaction between human, technical, and organizational components. Through a comparative analysis of system attributes from both socio-technical and AI-enabled systems and a review of current risk evaluation methods, we confirm the absence of explicit socio-technical considerations in standard risk expressions. To bridge this gap, we introduce a novel socio-technical alignment (STA) variable designed to be integrated into the traditional risk equation. This variable estimates the degree of harmonious interaction between the AI systems, human operators, and organizational processes. A case study on an AI-enabled liquid hydrogen (LH2) bunkering system demonstrates the variable's relevance. By comparing a naive and a safeguarded system design, we illustrate how the STA-augmented expression captures socio-technical safety implications that traditional risk evaluation overlooks, providing a more system-theoretic basis for risk evaluation.