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Objective: We examine how human operators adjust their trust in automation asa result of their moment-to-moment interaction with automation. Background:Most existing studies measured trust by administering questionnaires at the endof an experiment. Only a limited number of studies viewed trust as a dynamicvariable that can strengthen or decay over time. Method: Seventy-fiveparticipants took part in an aided memory recognition task. In the task,participants viewed a series of images and later on performed 40 trials of therecognition task to identify a target image when it was presented with adistractor. In each trial, participants performed the initial recognition bythemselves, received a recommendation from an automated decision aid, andperformed the final recognition. After each trial, participants reported theirtrust on a visual analog scale. Results: Outcome bias and contrast effectsignificantly influence human operators' trust adjustments. An automationfailure leads to a larger trust decrement if the final outcome is undesirable,and a marginally larger trust decrement if the human operator succeeds the taskby him-/her-self. An automation success engenders a greater trust increment ifthe human operator fails the task. Additionally, automation failures have alarger effect on trust adjustment than automation successes. Conclusion: Humanoperators adjust their trust in automation as a result of theirmoment-to-moment interaction with automation. Their trust adjustments aresignificantly influenced by decision-making heuristics/biases. Application:Understanding the trust adjustment process enables accurate prediction of theoperators' moment-to-moment trust in automation and informs the design oftrust-aware adaptive automation.

Toward quantifying trust dynamics: How people adjust their trust after moment-to-moment interaction with automation