Cognitive and Behavioral Impacts of Two Decision-Support Modes for Judgmental Bootstrapping

Abstract

The Cognitive Shadow is a decision-support system that uses policy capturing to model human operators’ judgment policies and provide online predictions of their decisions. The system can provide support in reaction to a decision mismatch (shadowing mode) or proactively (recommendation mode). The goal of this study was to compare these two modes of operation in their ability to effectively model and support decision-making and to examine impacts on information processing, workload, and trust. Participants took part in an aircraft threat evaluation simulation without decision support or with the Cognitive Shadow (either shadowing or recommendation mode). Dwell time was collected over different areas of the user interface. While the recommendation mode had no advantage over the control group, the shadowing mode resulted in greater human and model accuracy. This mode led to longer dwell time over the parameters zone presenting key information for decision-making. These benefits were maintained even after the tool was removed. Workload was unaffected by the mode, and while trust was initially higher in the recommendation mode, it quickly became equivalent between both modes, overall supporting shadowing as the better configuration for cognitive assistance. Results are discussed in terms of decision processes, operators support, and automation bias.