Technology Trust: The Impact of Trust Metrics on the Adoption of Autonomous Systems Used in High-Risk Applications

Abstract

As autonomous systems become more capable, end users must make decisions about how and when to deploy such technology. The use and adoption of a technology to replace a human actor depends on its ability to perform a desired task and on the user's experience-based trust that it will do so. The development of experience-based trust in autonomous systems is expensive and high-risk. This work focuses on identifying a methodology for technology discovery that reduces the need for experience-based trust and contributes to increased adoption of autonomous systems. Initial research reveals two problems associated with the adoption of high-risk technologies: (1) end user refusal to accept new systems without high levels of initial trust and (2) lost or uncollected experience-based trust data. The main research hypothesis is that a trust score, or trust metric, can influence the initial formation of trust by functioning as a surrogate for experience-based trust, and that trust in technology can be measured through an odds-based prediction of risk.