Human Performance Consequences of Automated Decision Aids: The Impact of Degree of Automation and System Experience

Two experiments are reported that investigate to what extent performance consequences of automated aids are dependent on the distribution of functions between human and automation and on the experience an operator has with an aid. In the first experiment, performance consequences of three automated aids for the support of a supervisory control task were compared. Aids differed in degree of automation (DOA). Compared with a manual control condition, primary and secondary task performance improved and subjective workload decreased with automation support, with effects dependent on DOA. Performance costs include return-to-manual performance issues that emerged for the most highly automated aid and effects of complacency and automation bias, respectively, which emerged independent of DOA. The second experiment specifically addresses how automation bias develops over time and how this development is affected by prior experience with the system. Results show that automation failures entail stronger effects than positive experience (reliably working aid). Furthermore, results suggest that commission errors in interaction with automated aids can depend on three sorts of automation bias effects: (a) withdrawal of attention in terms of incomplete cross-checking of information, (b) active discounting of contradictory system information, and (c) inattentive processing of contradictory information analog to a looking-but-not-seeing effect.