Trust, self-confidence, and operators' adaptation to automation

Abstract

The increasing use of automation to supplant human intervention in controlling complex systems changes the operators' role from active controllers (directly involved with the system) to supervisory controllers (managing the use of different degrees of automatic and manual control). This paper examines the relationship between trust in automatic controllers, self-confidence in manual control abilities, and the use of automatic controllers in operating a simulated semi-automatic pasteurization plant. Trust, combined with self-confidence, predicted the operators' allocation strategy. A Multitrait-multimethod matrix and logit functions showed how trust and self-confidence relate to the use of automation. An ARMAV time series model of the dynamic interaction of trust and self-confidence, combined with individual biases, accounted for 60.9-86.5% of the variance in the use of the three automatic controllers. In general, automation is used when trust exceeds self-confidence, and manual control when the opposite is true. Since trust and self-confidence are two factors that guide operators' interactions with automation, the design of supervisory control systems should include provisions to ensure that operators' trust reflects the capabilities of the automation and operators' self-confidence reflects their abilities to control the system manually.