OBJECTIVE: To investigate whether manipulating the format of an automated decision aid's cues can improve participants' information integration strategies in a signal detection task. BACKGROUND: Automation-aided decision making is often suboptimal, falling well short of statistically ideal levels. The choice of format in which the cues from the aid are displayed may help users to better understand and integrate the aid's judgments with their own. METHOD: Participants performed a signal detection task that asked them to classify random dot images as either blue or orange dominant. They made their judgments either unaided or with assistance from a 93% reliable automated decision aid. The aid provided a binary judgment, along with an estimate of signal strength in the form of either a raw value, a likelihood ratio, or a confidence rating (Experiments 1 and 2) or a binary judgment along with either a verbal or verbal-visuospatial expression of confidence (Experiment 3). Aided sensitivity was benchmarked to the predictions of various statistical models of collaborative decision making. RESULTS AND CONCLUSION: Aided performance was suboptimal, matching the predictions of some of the least efficient models. Most importantly, performance was similar across cue formats. APPLICATION: Results indicate that changes to the format in which cues from a signal detection aid are rendered are unlikely to dramatically improve the efficiency of automation-aided decision making.
OBJECTIVE: To investigate whether manipulating the format of an automated decision aid's cues can improve participants' information integration strategies in a signal detection task. BACKGROUND: Automation-aided decision making is often suboptimal, falling well short of statistically ideal levels. The choice of format in which the cues from the aid are displayed may help users to better understand and integrate the aid's judgments with their own. METHOD:Participants performed a signal detection task that asked them to classify random dot images as either blue or orange dominant. They made their judgments either unaided or with assistance from a 93% reliable automated decision aid. The aid provided a binary judgment, along with an estimate of signal strength in the form of either a raw value, a likelihood ratio, or a confidence rating (Experiments 1 and 2) or a binary judgment along with either a verbal or verbal-visuospatial expression of confidence (Experiment 3). Aided sensitivity was benchmarked to the predictions of various statistical models of collaborative decision making. RESULTS AND CONCLUSION: Aided performance was suboptimal, matching the predictions of some of the least efficient models. Most importantly, performance was similar across cue formats. APPLICATION: Results indicate that changes to the format in which cues from a signal detection aid are rendered are unlikely to dramatically improve the efficiency of automation-aided decision making.
Entities:
Keywords:
cues; decision-making strategies; human–automation interaction; information integration; signal detection theory