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