Sensitive to a T: The effects of non-spatial computer-aided detection cues on user sensitivity in a visual letter search task

Computer-aided detection (CAD) systems generally use a binary cue to indicate a target in an image to an observer (Cunningham, Drew, & Wolfe, 2017). This means that the CAD system provides a marker around (or an arrow pointing towards) any location in an image where the strength of the signal is above a certain threshold and does not provide a marker for those locations where the signal is below the threshold. CAD systems are not completely accurate. In target-present trials, the CAD system may correctly mark the target only (hit), however it may also commit three errors: It may correctly mark the target and incorrectly mark one or more distractors (hit / false alarm), fail to mark the target and incorrectly mark one or more distractors (miss / false alarm), or fail to mark the target and correctly not mark any distractors (miss). In target-absent trials, the CAD may correctly not mark any distractors (correct rejection), or incorrectly mark one or more distractors (false alarm). CAD systems that use binary cues have been shown to lead to increased detection (by the observer) of targets that are marked by the CAD, but they also lead to decreased detection of targets that are missed by the CAD, especially when a distractor has also been cued (Drew, Guthrie, & Reback, 2020; see also Russell & Kunar, 2012 for the exogenous cueing of low prevalence targets). When the CAD system does not provide any cue in a target-present trial (miss), the increased misses of these targets could be due to an overreliance of the observer on the information that the CAD conveys (the overreliance hypothesis; Kunar Watson, Taylor-Phillips, & Wolska, 2017). When the CAD system fails to cue a target and also cues a distractor (miss / false alarm) the increased misses of these targets could be due to an overreliance on the CAD and/or because the exogenous CAD cue(s) capture the observer’s attention to specific locations in the image, drawing it away from non-cued locations that may contain a target. Here, we will test the overreliance hypothesis by removing the localised attentional capture aspect of the CAD cues. We will use non-spatial CAD cues to convey the CAD information to the observer through a coloured border around the image when a target is detected by the CAD system. These cues will provide CAD information to the observer without capturing attention to specific locations. These cues differ from spatial cues in the errors that the system can make. When a target is present and the system provides a cue, it can no longer make the hit / false alarm or miss / false alarm errors. Participants will complete a letter search task under two conditions: with non-spatial CAD cues and without. We predict that participants will perform better (than without CAD) when the non-spatial CAD correctly cues a target (hit), demonstrating that participants are using the CAD information. We also predict that participants will perform worse (than without CAD) when the non-spatial CAD fails to cue a target (miss), thus providing support for the overreliance hypothesis. If participants perform better on CAD hit trials, but no worse on CAD miss trials, both relative to without CAD, this suggests that attentional capture may be responsible for some of the errors in spatial CAD.