Effects of information source, pedigree, and reliability on operator interaction with decision support systems

Abstract

Objective: Two experiments are described that examined operators' perceptions of decision aids.

Background: Research has suggested certain biases against automation that influence human interaction with automation. We differentiated preconceived biases from post hoc biases and examined their effects on advice acceptance.

Method: In Study 1 we examined operators' trust in and perceived reliability of humans versus automation of varying pedigree (expert vs. novice), based on written descriptions of these advisers prior to operators' interacting with these advisers. In Study 2 we examined participants' post hoc trust in, perceived reliability of, and dependence on these advisers after their objective experience of advisers' reliability (90% vs. 70%) in a luggage-screening task.

Results: In Study 1 measures of perceived reliability indicated that automation was perceived as more reliable than humans across pedigrees. Measures of trust indicated that automated "novices" were trusted more than human "novices"; human "experts" were trusted more than automated "experts." In Study 2, perceived reliability varied as a function of pedigree, whereas subjective trust was always higher for automation than for humans. Advice acceptance from novice automation was always higher than from novice humans. However, when advisers were 70% reliable, errors generated by expert automation led to a drop in compliance/reliance on expert automation relative to expert humans.

Conclusion: Preconceived expectations of automation influence the use of these aids in actual tasks.

Application: The results provide a reference point for deriving indices of "optimal" user interaction with decision aids and for developing frameworks of trust in decision support systems.