An Investigation of the Individual Differences and Causal Attributions That Make or Break Dynamic Trust in Automation

Arielle Mandell

Advisor: Tyler H. Shaw, PhD, Department of Psychology

Committee Members: Ewart de Visser, Eva Wiese

Research Hall, #161
November 29, 2018, 02:00 PM to 04:00 PM


Trust is a critical factor in shaping the interaction between humans and automation. The current study seeks to understand the dynamics of trust in order to promote appropriate trust calibration. In the first experiment, we explore how individual differences in personality, automation-specific schemas and biases, and causal attributions may affect subjective trust, compliance, and performance on a driving task with an automated navigational aid. More specifically, this experiment explores 1) how dispositional factors affect sensitivity to the first automation failure, and 2) the role of the causal attribution process as a possible mediator between the relevant individual differences and dynamic trust. In the second experiment, we assess the efficacy of a trust-enhancing intervention designed to reduce the negative impact of the first automation failure for those most affected by it.