DRU: Dynamic Modeling of System Safety to Manage Risk and Enable Internal and External Cross-Stakeholder Alignment

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Traditional models of causality are based on decomposition of behavior into events connected by simple and direct relationships. These chain-of-events models are inadequate to understand, model, assess, and make decisions about risk in complex socio-technical systems where the events have indirect and non-linear relationships. More sophisticated models of human, organizational, and technological behavior are needed to understand and analyze the components of risk and to provide the information required to make good decisions in the face of continual system adaptation and change. This research will examine the potential to use systems-theoretic rather than decompositional models to integrate social, organizational, psychological, and engineering approaches to modeling, analysis, and decision-making about risk in the face of continual change and adaptation. We will validate this approach to improved understanding of the complex socio-technical interactions involved in accidents by using two real systems: the NASA Space Shuttle Program and air traffic control. In addition, we will develop and experimentally evaluate prototype tools based on the model for their ability to improve risk analysis and decision making for complex systems. The systems-theoretic approach to system safety sets the groundwork for a new generation of research on human risk management and decision making in complex systems. The integration of social, organizational, and technical factors into a combined accident causality model could open the door to the development of new risk modeling, analysis, and assessment tools for human and social dynamics research.