Selective Access to Decision Support as a Function of Event Uncertainty.

Objective: We investigate the impact of event uncertainty, decision support (DS) display format, and DS sensitivity on participants' behavior, performance, subjective workload, and perception of DS usefulness and performance in a classification task.

Background: DS systems can positively and negatively affect decision accuracy, performance time, and workload. The ability to access DS selectively, based on informational needs, might improve DS effectiveness.

Benchmarking automation-aided performance in a forensic face matching task.

Carragher and Hancock (2023) investigated how individuals performed in a one-to-one face matching task when assisted by an Automated Facial Recognition System (AFRS). Across five pre-registered experiments they found evidence of suboptimal aided performance, with AFRS-assisted individuals consistently failing to reach the level of performance the AFRS achieved alone. The current study reanalyses these data (Carragher and Hancock, 2023), to benchmark automation-aided performance against a series of statistical models of collaborative decision making, spanning a range of efficiency levels.

Decision support improves information integration and criterion placement in a multi-cue signal-identification task.

Identifying contacts in a military context can require operators to integrate multiple cues and to adjust response criteria to event base rates. The current experiment tested whether support from a decision aid would improve these processes. Participants performed a signal identification task that required them to integrate cues displayed as visual scale readings.

Identifying inefficient strategies in automation-aided signal detection.

Automated diagnostic aids can assist human operators in signal detection tasks, providing alarms, warnings, or diagnoses. Operators often use decision aids poorly, though, falling short of best possible performance levels. Previous research has suggested that operators interact with binary signal detection aids using a sluggish contingent cutoff (CC) strategy (Robinson & Sorkin, 1985), shifting their response criterion in the direction stipulated by the aid's diagnosis each trial but making adjustments that are smaller than optimal.

Psychometric curves reveal changes in bias, lapse rate, and guess rate in an online vigilance task.

When human monitors are required to detect infrequent signals among noise, they typically exhibit a decline in correct detections over time. Researchers have attributed this vigilance decrement to three alternative mechanisms: shifts in response bias, losses of sensitivity, and attentional lapses. The current study examined the extent to which changes in these mechanisms contributed to the vigilance decrement in an online monitoring task.

Simple manipulations of anthropomorphism fail to induce perceptions of humanness or improve trust in an automated agent.

Although automation is employed as an aid to human performance, operators often interact with automated decision aids inefficiently. The current study investigated whether anthropomorphic automation would engender higher trust and use, subsequently improving human-automation team performance. Participants performed a multi-element probabilistic signal detection task in which they diagnosed a hypothetical nuclear reactor as in a state of safety or danger.

Psychometric Curves Reveal Three Mechanisms of Vigilance Decrement.

The vigilance decrement is a decline in signal detection rate that occurs over time on a sustained-attention task. The effect has typically been ascribed to conservative shifts of response bias and losses of perceptual sensitivity. Recent work, though, has suggested that sensitivity losses in vigilance tasks are spurious, and other findings have implied that attentional lapses contribute to vigilance failures.

Measuring the Efficiency of Automation-Aided Performance in a Simulated Baggage Screening Task.

Objective: The present study replicated and extended prior findings of suboptimal automation use in a signal detection task, benchmarking automation-aided performance to the predictions of several statistical models of collaborative decision making.

Background: Though automated decision aids can assist human operators to perform complex tasks, operators often use the aids suboptimally, achieving performance lower than statistically ideal.

Method: Participants performed a simulated security screening task requiring them to judge whether a target (a knife) was present or absent in a series of colored X-ray images of passenger baggage.

Ironic efficiency in automation-aided signal detection.

Decision makers often make poor use of the information provided by an automated signal detection aid; recent studies have found that participants assisted by an automated aid fell well short of best-possible sensitivity levels. The present study tested the generalisability of this finding over varying levels of aid reliability. Participants performed a binary signal detection task either unaided or with assistance from a decision aid that was 60%, 85%, or 96%-reliable.

Collaboration improves unspeeded search in the absence of precise target information.

Two-person teams outperform individuals in search tasks, and even exceed expectations based on statistical limitations. Here, we aimed to replicate and extend this result. We used Bayesian hierarchical modelling of receiver operating characteristics to examine collaborative performance in a visual search task wherein top-down target information was constrained.

Shared Gaze Fails to Improve Team Visual Monitoring.

Objective: The aim was to test the value of shared gaze as a way to improve team performance in a visual monitoring task.

Background: Teams outperform individuals in monitoring tasks, but fall short of achievable levels. Shared-gaze displays offer a potential method of improving team efficiency.

Collaborative search in a mock baggage screening task.

Signal detection theory provides models of information integration that allow researchers to predict and benchmark collaborative performance in a visual search task. Naturalistic stimuli, however, may not conform to the simplifying assumptions-specifically, assumptions of equal-variance signal and noise distributions and stochastically independent observers-that are often made to make collaborative signal detection models tractable. Here, we used Bayesian hierarchical modeling of receiver operating characteristics to circumvent this difficulty.

No Effect of Cue Format on Automation Dependence in an Aided Signal Detection Task.

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.

Does wearable device bring distraction closer to drivers? Comparing smartphones and Google Glass.

Background: Head-up and wearable displays, such as Google Glass™, are sometimes marketed as safe in-vehicle alternatives to phone-based displays, as they allow drivers to receive messages without eye-off-the-road glances. However, head-up displays can still compromise driver performance (e.g.

Redundant-target processing is robust against changes to task load.

Monitoring visual displays while performing other tasks is commonplace in many operational environments. Although dividing attention between tasks can impair monitoring accuracy and response times, it is unclear whether it also reduces processing efficiency for visual targets. Thus, the current three experiments examined the effects of dual-tasking on target processing in the visual periphery.

Effects of Task Difficulty and Display Format on Automation Usage Strategy: A Workload Capacity Analysis.

Objective An experiment used workload capacity analysis to quantify automation usage strategy across different task difficulty and display format types in a speeded task. Background Workload capacity measures the efficiency of concurrent information processing and can serve as a gauge of automation usage strategy in speeded decision tasks. The present study used workload capacity analysis to investigate automation usage strategy while information display format and task difficulty were manipulated.

Benchmarking Aided Decision Making in a Signal Detection Task.

Objective: A series of experiments examined human operators' strategies for interacting with highly (93%) reliable automated decision aids in a binary signal detection task.

Background: Operators often interact with automated decision aids in a suboptimal way, achieving performance levels lower than predicted by a statistically ideal model of information integration. To better understand operators' inefficient use of decision aids, we compared participants' automation-aided performance levels with the predictions of seven statistical models of collaborative decision making.

Workload Capacity: A Response Time-Based Measure of Automation Dependence.

Objective: An experiment used the workload capacity measure C(t) to quantify the processing efficiency of human-automation teams and identify operators' automation usage strategies in a speeded decision task.

Background: Although response accuracy rates and related measures are often used to measure the influence of an automated decision aid on human performance, aids can also influence response speed. Mean response times (RTs), however, conflate the influence of the human operator and the automated aid on team performance and may mask changes in the operator's performance strategy under aided conditions.

Texting while driving using Google Glass™: Promising but not distraction-free.

Texting while driving is risky but common. This study evaluated how texting using a Head-Mounted Display, Google Glass, impacts driving performance. Experienced drivers performed a classic car-following task while using three different interfaces to text: fully manual interaction with a head-down smartphone, vocal interaction with a smartphone, and vocal interaction with Google Glass.

Lane keeping under cognitive load: performance changes and mechanisms.

Objective: A pair of simulated driving experiments studied the effects of cognitive load on drivers' lane-keeping performance.

Background: Cognitive load while driving often reduces the variability of lane position. However, there is no agreement as to whether this effect should be interpreted as a performance loss, consistent with other effects of distraction on driving, or as an anomalous performance gain.

Metacognition of multitasking: How well do we predict the costs of divided attention?

Risky multitasking, such as texting while driving, may occur because people misestimate the costs of divided attention. In two experiments, participants performed a computerized visual-manual tracking task in which they attempted to keep a mouse cursor within a small target that moved erratically around a circular track. They then separately performed an auditory n-back task.

Great expectations: top-down attention modulates the costs of clutter and eccentricity.

An experiment and modeling effort examined interactions between bottom-up and top-down attentional control in visual alert detection. Participants performed a manual tracking task while monitoring peripheral display channels for alerts of varying salience, eccentricity, and spatial expectancy. Spatial expectancy modulated the influence of salience and eccentricity; alerts in low-probability locations engendered higher miss rates, longer detection times, and larger costs of visual clutter and eccentricity, indicating that top-down attentional control offset the costs of poor bottom-up stimulus quality.

Change detection: training and transfer.

Observers often fail to notice even dramatic changes to their environment, a phenomenon known as change blindness. If training could enhance change detection performance in general, then it might help to remedy some real-world consequences of change blindness (e.g.

Auditory, visual, and bimodal data link displays and how they support pilot performance.

Background: The design of data link messaging systems to ensure optimal pilot performance requires empirical guidance. The current study examined the effects of display format (auditory, visual, or bimodal) and visual display position (adjacent to instrument panel or mounted on console) on pilot performance.

Methods: Subjects performed five 20-min simulated single-pilot flights.

Spatial interference between attended items engenders serial visual processing.

A pair of experiments investigated the architecture of visual processing, parallel versus serial, across high and low levels of spatial interference in a divided attention task. Subjects made speeded judgments that required them to attend to a pair of color-cued objects among gray filler items, with the spatial proximity between the attended items varied to manipulate the strength of interference between attended items. Systems factorial analysis (Townsend & Nozawa, Journal of Mathematical Psychology 39:321-359, 1995) was used to identify processing architecture.