LEAP-HI: Safety and Learning from Errors and Near Misses in the Human-Automation Interaction of Socio-Technical Infrastructure Systems

Modern socio-technical infrastructure systems operate in dynamic environments where there is a high level of interaction between human operators and increasingly autonomous technologies that carry out safety-critical tasks. This Leading Engineering for America's Prosperity, Health, and Infrastructure (LEAP-HI) project will research the balance between safety, workload, and economic considerations in these semi-automated socio-technical infrastructure systems to provide improved design and policy tools to both infrastructure providers and regulators by integrating the disciplines of systems engineering, human factors engineering, decision and organizational theories, and economic production theory.

This scientific research contribution supports NSF's mission to promote the progress of science and to advance our national welfare. The expected benefits include improvements in the organization of work, health outcomes associated with the work, and the economic viability of socio-technical infrastructure systems. The project will also support outreach activities to stimulate interest in the socio-technical domain area for students going into STEM-related fields.

This project uses a systems-level theoretical approach that provides a computable safe area of operation for modern socio-technical infrastructure systems. It develops a new metric of mental workload that includes distributed situational awareness as determined by multiple physiological measurements and subjective human perceptions. It explores new regions in decision theory by studying how cognitive biases influence trust in automation and decisions to delegate tasks to automated technologies.

It also examines the identification and attribution of causes of errors, near misses, and incidents as part of organizational learning in these modern systems. Additionally, the research builds on economic production theory to integrate workload, safety, and economic perspectives in determining an infrastructure’s safety envelope. Finally, the research assesses the dynamic trade-offs among workload, marginal safety, and economics within the safety envelope to improve infrastructure decision-making.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.