Trust of a Military Automated System in an Operational Context

Within this descriptive article, we examine the drivers of human trust of automation using a fielded military technology as the focus area. In contrast to the laboratory, real-life interactions between humans and automation often take place in settings characterized by high complexity that potentially obscure the antecedents of trust. We approach this complexity through a case study, which captures the richness and variety of the operational context in which humans interact with automation. In particular, we utilize and substantiate a theoretical and conceptual trust model synthesized by Lee and See (2004) and examine how well it captures the dynamic nature of trust by using a sample of U.S. Air Force F-16 pilots, engineers, and managers of the Automatic Ground Collision Avoidance System (Auto-GCAS). Our results show the Lee and See model succeeds in capturing most trust factors in the case of these Auto-GCAS stakeholders, and we present areas for enhancement of the model. We conclude by elaborating on lessons learned and hypotheses generated regarding factors affecting trust in Auto-GCAS, providing recommendations for future trust research in field work, and discussing the value of working with an operational community while examining trust evolution over several years.