The relationship of trust and dependence.

The concepts of automation trust and dependence have often been viewed as closely related and on occasion, have been conflated in the research community. Yet, trust is a cognitive attitude and dependence is a behavioural measure, so it is unsurprising that different factors can affect the two. Here, we review the literature on the correlation between trust and dependence. On average, this correlation across people was quite low, suggesting that people who are more trusting of automation do not necessarily depend upon it more. Separately, we examined experiments that explicitly manipulated the reliability of automation, finding that higher automation reliability increased trust ratings twice as fast as dependence behaviours. This review provides novel quantitative evidence that the two constructs are not strongly correlated. Implications of this work, including potential moderating variables, contexts where trust is still relevant, and considerations of trust measurement, are discussed.

Trust in automation is a cognitive attitude, and dependence on automation is a physical behaviour. Therefore, it is important to understand the differences between the two, especially as they have been conflated in the literature. This review highlights the small average correlation in the literature between subjective trust and objective dependence, which suggests that measuring trust as dependence (or vice versa) may not be valid. This suggests, then, that practitioners should carefully consider how trust and dependence are being measured in a given context so as not to incorrectly conflate the two.

Detection of Hostile Intent by Spatial Movements.

OBJECTIVE: The ability of people to infer intentions from movement of other vessels was investigated. Across three levels of variability in movements in the path of computer-controlled ships, participants attempted to determine which entity was hostile. BACKGROUND: Detection of hostile intentions through spatial movements of vessels is important in an array of real-world scenarios. This experiment sought to determine baseline abilities of humans to do so. METHODS: Participants selected a discrete movement direction of their ship. Six other ships' locations then updated. A single entity displayed one of two hostile behaviors: shadowing, which involved mirroring the participant's vessel's movements; and hunting, which involved closing in on the participant's vessel. Trials allowed up to 35 moves before identifying the hostile ship and its behavior. Uncertainty was introduced through adding variability to ships' movements such that their path was 0%, 25%, or 50% random. RESULTS: Even with no variability in the ships' movements, accurate detection was low, identifying the hostile entity about 60% of the time. Variability in the paths decreased detection. Detection of hunting was strongly degraded by distance between ownship and the hostile ship, but shadowing was not. Strategies employing different directions of movement across the trial, but also featuring some runs of consecutive movements, facilitated detection. CONCLUSIONS: Early identification of threats based on movement characteristics alone is likely to be difficult, but particularly so when adversaries employ some level of uncertainty to mask their intentions. These findings highlight the need to develop decision aids to support human performance.

Mitigating the Costs of Spatial Transformations With a Situation Awareness Augmented Reality Display: Assistance for the Joint Terminal Attack Controller 3-17.

OBJECTIVE: Evaluate and model the advantage of a situation awareness (SA) supported by an augmented reality (AR) display for the ground-based joint terminal attack Controller (JTAC), in judging and describing the spatial relations between objects in a hostile zone. BACKGROUND: The accurate world-referenced description of relative locations of surface objects, when viewed from an oblique slant angle (aircraft, observation post) is hindered by (1) the compression of the visual scene, amplified at a lower slang angle, (2) the need for mental rotation, when viewed from a non-northerly orientation. APPROACH: Participants viewed a virtual reality (VR)-simulated four-object scene from either of two slant angles, at each of four compass orientations, either unaided, or aided by an AR head-mounted display (AR-HMD), depicting the scene from a top-down (avoiding compression) and north-up (avoiding mental rotation) perspective. They described the geographical layout of four objects within the display. RESULTS: Compared with the control condition, that condition supported by the north-up SA display shortened the description time, particularly on non-northerly orientations (9 s, 30% benefit), and improved the accuracy of description, particularly for the more compressed scene (lower slant angle), as fit by a simple computational model. CONCLUSION: The SA display provides large, significant benefits to this critical phase of ground-air communications in managing an attack-as predicted by the task analysis of the JTAC. APPLICATION: Results impact the design of the AR-HMD to support combat ground-air communications and illustrate the magnitude by which basic cognitive principles "scale up" to realistically simulated real-world tasks such as search and rescue.

Rendezvous Under Temporal Uncertainty.

OBJECTIVE: Three experiments sought to understand performance limitations in controlling a ship attempting to meet another moving ship that approached from various trajectories. The influence of uncertainty, resulting from occasional unpredictable delays in one's own movement, was examined. BACKGROUND: Cognitive elements of rendezvous have been little studied. Related work such as the planning fallacy and bias toward underestimating time-to-contact imply a tendency toward late arrival at a rendezvous. METHODS: In a simplified simulation, participants controlled the speed and/or heading of their own ship once per scenario to try to rendezvous with another ship. Forty-five scenarios of approximately 30 s were conducted with different starting geometries and, in two of three experiments, with different frequencies and lengths of the unexpected delays. RESULTS: Perfect rendezvous were hard to obtain, with a general tendency to arrive late and pass behind the target vessel, although this was dependent on the angle of approach and relative speed. When occasional delays were introduced, less frequent but longer delays disrupted performance more than shorter but more frequent delays. Where delays were possible, but no delay occurred, there was no longer evidence of a general tendency to more frequently pass behind the target ship. Additionally, people did not wait to see if the unpredictable delays would occur before executing a course of action. Different control strategies were deployed and dual axis control was preferred. CONCLUSIONS: The tendency to arrive late and the influence of the possibility of uncertain delays are discussed in relationship to control strategies.

Information Access Effort: The Role of Head Movements for Information Presented at Increasing Eccentricity on Flat Panel and Head-Mounted Displays.

OBJECTIVE: This experiment examined performance costs when processing two sources of information positioned at increasing distances using a flat panel display and an augmented reality head-mounted display (AR-HMD). BACKGROUND: The AR-HMD enables positioning virtual information at various distances in space. However, the proximity compatibility principle suggests that closer separation when two sources of information require mental integration assists performance, whereas increased separation between two sources hurts integration performance more than when a single source requires focused attention. Previous studies have provided inconsistent findings regarding costs associated with increased separation. Few of these experiments have examined separation for both focused and integration tasks, compared vertical and lateral separation, or measured head movements. METHOD: Three experiments collectively examined these issues using a flat panel display and a virtual display presented with an HMD, where the separation of information varied laterally or vertically during a focused attention (digit reading) task and an information integration (mental subtraction) task. RESULTS: There was no performance cost for either display when information was increasingly separated. However, head movements mitigated performance costs by preserving accuracy at larger separations without increasing response time. CONCLUSION: Head movements appear to mitigate performance costs associated with presenting information increasingly far apart on flat panel displays and HMDs. Both eye scanning and head movements appear to be less effortful than expected. APPLICATION: These findings have important implications for design guidelines regarding the placement of information presented on flat panel displays and, more specifically, HMDs, which can present information 360° around the user.

Modeling Task Scheduling Decisions of Emergency Department Physicians.

OBJECTIVE: This study evaluated task-scheduling decisions in the context of emergency departments by comparing patterns of emergency physicians' task-scheduling models across levels of experience. BACKGROUND: Task attributes (priority, difficulty, salience, and engagement) influence task-scheduling decisions. However, it is unclear how attributes interact to affect decisions, especially in complex contexts. An existing model of task scheduling, strategic task overload management-no priority (STOM-NP), found that an equal weighting of attributes can predict task-scheduling behavior. Alternatively, mathematical modeling estimated that priority alone could make similar predictions as STOM-NP in a parsimonious manner. Experience level may also influence scheduling decisions. METHOD: An experimental design methodology shortened a judgment analysis approach to compare a priori task-scheduling decision strategies. Emergency physicians with two levels of experience rank-ordered 10 sets of 3 tasks varying on 4 task attributes in this complex environment. RESULTS: Bayesian statistics were used to identify best-fit decision strategies. STOM-NP and priority-only provided the best model fits. STOM-NP fit the lower-experienced physicians best, whereas priority-only-using only one cue-fit the higher-experienced physicians best. CONCLUSION: Models of decision strategies for task-scheduling decisions were extended to complex environments. Experts' level of experience influenced task-scheduling decisions, where the scheduling decisions of more-experienced experts was consistent with a more frugal decision process. Findings have implications for training and evaluation. APPLICATION: We assessed models of cues that influence task-scheduling decisions, including a parsimonious model for task priority only. We provided a sample approach for shortening methods for understanding decisions.

Absence of DOA Effect but No Proper Test of the Lumberjack Effect: A Reply to Jamieson and Skraaning (2019).

OBJECTIVE: The aim was to evaluate the relevance of the critique offered by Jamieson and Skraaning (2019) regarding the applicability of the lumberjack effect of human-automation interaction to complex real-world settings. BACKGROUND: The lumberjack effect, based upon a meta-analysis, identifies the consequences of a higher degree of automation-to improve performance and reduce workload-when automation functions as intended, but to degrade performance more, as mediated by a loss of situation awareness (SA) when automation fails. Jamieson and Skraaning provide data from a process control scenario that they assert contradicts the effect. APPROACH: We analyzed key aspects of their simulation, measures, and results which we argue limit the strength of their conclusion that the lumberjack effect is not applicable to complex real-world systems. RESULTS: Our analysis revealed limits in their inappropriate choice of automation, the lack of a routine performance measure, support for the lumberjack effect that was actually provided by subjective measures of the operators, an inappropriate assessment of SA, and a possible limitation of statistical power. CONCLUSION: We regard these limitations as reasons to temper the strong conclusions drawn by the authors, of no applicability of the lumberjack effect to complex environments. Their findings should be used as an impetus for conducting further research on human-automation interaction in these domains. APPLICATIONS: The collective findings of both Jamieson and Skraaning and our study are applicable to system designers and users in deciding upon the appropriate level of automation to deploy.

Nautical Collision Avoidance : The Cognitive Challenges of Balancing Safety, Efficiency, and Procedures.

OBJECTIVE: Experimentally investigate maneuver decision preferences in navigating ships to avoid a collision. How is safety (collision avoidance) balanced against efficiency (deviation from path and delay) and rules of the road under conditions of both trajectory certainty and uncertainty. BACKGROUND: Human decision error is a prominent factor in nautical collisions, but the multiple factors of geometry of collisions and role of uncertainty have been little studied in empirical human factors literature. APPROACH: Eighty-seven Mechanical Turk participants performed in a lower fidelity ship control simulation, depicting ownship and a cargo ship hazard on collision or near-collision trajectories of various conflict geometries, while controlling heading and speed with the sluggish relative dynamics. Experiment 1 involved the hazard on a straight trajectory. In Experiment 2, the hazard could turn on unpredictable trials. Participants were rewarded for efficiency and penalized for collisions or close passes. RESULTS: Participants made few collisions, but did so more often when on a collision path. They sometimes violated the instructed rules of the road by maneuvering in front of the hazard ship's path. They preferred speed control to heading control. Performance degraded in conditions of uncertainty. CONCLUSION: Data reveal an understanding of maneuver decisions and conditions that affect the balance between safety and efficiency. APPLICATION: The simulation and data highlight the degrading role of uncertainty and provide a foundation upon which more complex questions can be asked, asked of more trained navigators, and decision support tools examined.

Anchoring and Adjustment in Uncertain Spatial Trajectory Prediction.

OBJECTIVE: The aim of this study was to explore the impact of prior information on spatial prediction and understanding of variability. BACKGROUND: In uncertain spatial prediction tasks, such as hurricane forecasting or planning search-and-rescue operations, decision makers must consider the most likely case and the distribution of possible outcomes. Base performance on these tasks is varied (and in the case of understanding the distribution, often poor). Humans must update mental models and predictions with new information, sometimes under cognitive workload. METHOD: In a spatial-trajectory prediction task, participants were anchored on accurate or inaccurate information, or not anchored, regarding the future behavior of an object (both average behavior and the variability). Subsequently, they predicted an object's future location and estimated its likelihood at multiple locations. In a second experiment, participants repeated the process under varying levels of external cognitive workload. RESULTS: Anchoring influenced understanding of most likely predicted location, with fairly rapid adjustment following inaccurate anchors. Increasing workload resulted in decreased overall performance and an impact on the adjustment component of the task. Overconfidence was present in all conditions. CONCLUSION: Prior information exerted short-term influence on spatial predictions. Cognitive load impaired users' ability to effectively adjust to new information. Accurate graphical anchors did not improve user understanding of variability. APPLICATION: Prior briefings or forecasts about spatiotemporal trajectories affect decisions even in the face of initial contradictory information. To best support spatial prediction tasks, efforts also need to be made to separate extraneous load-causing tasks from the process of integrating new information. Implications are discussed.

Effect of Visualization Training on Uncertain Spatial Trajectory Predictions.

OBJECTIVE: The goal of this study was to explore the ways in which visualizations influence the prediction of uncertain spatial trajectories (e.g., the unknown path of a downed aircraft or future path of a hurricane) and participant overconfidence in such prediction. BACKGROUND: Previous research indicated that spatial predictions of uncertain trajectories are challenging and are often associated with overconfidence. Introducing a visualization aid during training may improve the understanding of uncertainty and reduce overconfidence. METHOD: Two experiments asked participants to predict the location of various trajectories at a future time. Mean and variance estimates were compared for participants who were provided with a visualization and those who were not. RESULTS: In Experiment 1, participants exhibited less error in mean estimations when a linear visualization was present but performed worse than controls once the visualization was removed. Similar results were shown in Experiment 2, with a nonlinear visualization. However, in both experiments, participants who were provided with a visualization did not retain any advantage in their variance estimations once the visualization was removed. CONCLUSIONS: Visualizations may support spatial predictions under uncertainty, but they are associated with benefits and costs for the underlying knowledge being developed. APPLICATION: Visualizations have the potential to influence how people make spatial predictions in the presence of uncertainty. Properly designed and implemented visualizations may help mitigate the cognitive biases related to such predictions.

NMR of molecular endofullerenes dissolved in a nematic liquid crystal.

We report the NMR of the molecular endofullerenes H2@C60, H2O@C60 and HF@C60 dissolved in the nematic liquid crystal N-(4-methoxybenzylidene)-4-butylaniline (MBBA). The 1H NMR lines of H2 and H2O display a doublet splitting due to residual dipole-dipole coupling. The dipolar splitting depends on temperature in the nematic phase and vanishes above the nematic-isotropic phase transition. The 19F spectrum of HF@C60 dissolved in MBBA displays a doublet splitting in the nematic phase, with contributions from the 1H-19F dipole-dipole coupling and J-coupling. The phenomena are analyzed using a model in which the fullerene cages acquire a geometrical distortion, either through interaction with the liquid crystal environment, or through their interaction with the endohedral molecules. The distorted cages become partially oriented with respect to the liquid crystal director, and the endohedral molecules become partially oriented with respect to the distorted cages.

Implementing Lumberjacks and Black Swans Into Model-Based Tools to Support Human-Automation Interaction.

OBJECTIVE: The objectives were to (a) implement theoretical perspectives regarding human-automation interaction (HAI) into model-based tools to assist designers in developing systems that support effective performance and (b) conduct validations to assess the ability of the models to predict operator performance. BACKGROUND: Two key concepts in HAI, the lumberjack analogy and black swan events, have been studied extensively. The lumberjack analogy describes the effects of imperfect automation on operator performance. In routine operations, an increased degree of automation supports performance, but in failure conditions, increased automation results in more significantly impaired performance. Black swans are the rare and unexpected failures of imperfect automation. METHOD: The lumberjack analogy and black swan concepts have been implemented into three model-based tools that predict operator performance in different systems. These tools include a flight management system, a remotely controlled robotic arm, and an environmental process control system. RESULTS: Each modeling effort included a corresponding validation. In one validation, the software tool was used to compare three flight management system designs, which were ranked in the same order as predicted by subject matter experts. The second validation compared model-predicted operator complacency with empirical performance in the same conditions. The third validation compared model-predicted and empirically determined time to detect and repair faults in four automation conditions. CONCLUSION: The three model-based tools offer useful ways to predict operator performance in complex systems. APPLICATION: The three tools offer ways to predict the effects of different automation designs on operator performance.

Benefits of Imperfect Conflict Resolution Advisory Aids for Future Air Traffic Control.

OBJECTIVE: The aim of this study was to examine the human-automation interaction issues and the interacting factors in the context of conflict detection and resolution advisory (CRA) systems. BACKGROUND: The issues of imperfect automation in air traffic control (ATC) have been well documented in previous studies, particularly in conflict-alerting systems. The extent to which the prior findings can be applied to an integrated conflict detection and resolution system in future ATC remains unknown. METHOD: Twenty-four participants were evenly divided into two groups corresponding to a medium- and a high-traffic density condition, respectively. In each traffic density condition, participants were instructed to perform simulated ATC tasks under four automation conditions, including reliable, unreliable with short time allowance to secondary conflict (TAS), unreliable with long TAS, and manual conditions. Dependent variables accounted for conflict resolution performance, workload, situation awareness, and trust in and dependence on the CRA aid, respectively. RESULTS: Imposing the CRA automation did increase performance and reduce workload as compared with manual performance. The CRA aid did not decrease situation awareness. The benefits of the CRA aid were manifest even when it was imperfectly reliable and were apparent across traffic loads. In the unreliable blocks, trust in the CRA aid was degraded but dependence was not influenced, yet the performance was not adversely affected. CONCLUSION: The use of CRA aid would benefit ATC operations across traffic densities. APPLICATION: CRA aid offers benefits across traffic densities, regardless of its imperfection, as long as its reliability level is set above the threshold of assistance, suggesting its application for future ATC.

Overconfidence in Projecting Uncertain Spatial Trajectories.

OBJECTIVE: The aim of this study was to understand factors that influence the prediction of uncertain spatial trajectories (e.g., the future path of a hurricane or ship) and the role of human overconfidence in such prediction. BACKGROUND: Research has indicated that human prediction of uncertain trajectories is difficult and may well be subject to overconfidence in the accuracy of forecasts as is found in event prediction, a finding that indicates that humans insufficiently appreciate the contributions of variance in nature to their predictions. METHOD: In two experiments, our paradigm required participants to observe a starting point, a position at time T, and then make a prediction of the location of the trajectory at time NT. They experienced several trajectories from the same underlying model but perturbed by random variance in heading and speed. RESULTS: In Experiment 1A, people predicted linear paths well and were better in heading predictions than in speed predictions. However, participants greatly underestimated the variance in predicted location, indicating overconfidence. In Experiment 1B, the effect was replicated with frequencies rather than probabilities used in variance estimates. In Experiment 2, people predicted nonlinear trajectories poorly, and overconfidence was again observed. Overconfidence was reduced on the more difficult predictions. In both main experiments, those better at predicting the mean were not better at predicting the variance. CONCLUSIONS: Predicting the level of uncertainty in spatial trajectories is not well done and may involve qualitatively different abilities than prediction of the mean. APPLICATION: Improving real-world performance at prediction demands developing better understanding of variability, not just the average case. Biases in prediction of uncertainty may be addressed through debiasing training and/or visualization tools that could assist in more calibrated action planning.

Time Sharing Between Robotics and Process Control: Validating a Model of Attention Switching.

OBJECTIVE: The aim of this study was to validate the strategic task overload management (STOM) model that predicts task switching when concurrence is impossible. BACKGROUND: The STOM model predicts that in overload, tasks will be switched to, to the extent that they are attractive on task attributes of high priority, interest, and salience and low difficulty. But more-difficult tasks are less likely to be switched away from once they are being performed. METHOD: In Experiment 1, participants performed four tasks of the Multi-Attribute Task Battery and provided task-switching data to inform the role of difficulty and priority. In Experiment 2, participants concurrently performed an environmental control task and a robotic arm simulation. Workload was varied by automation of arm movement and both the phases of environmental control and existence of decision support for fault management. Attention to the two tasks was measured using a head tracker. RESULTS: Experiment 1 revealed the lack of influence of task priority and confirmed the differing roles of task difficulty. In Experiment 2, the percentage attention allocation across the eight conditions was predicted by the STOM model when participants rated the four attributes. Model predictions were compared against empirical data and accounted for over 95% of variance in task allocation. More-difficult tasks were performed longer than easier tasks. Task priority does not influence allocation. CONCLUSIONS: The multiattribute decision model provided a good fit to the data. APPLICATIONS: The STOM model is useful for predicting cognitive tunneling given that human-in-the-loop simulation is time-consuming and expensive.

Effects of Information Access Cost and Accountability on Medical Residents' Information Retrieval Strategy and Performance During Prehandover Preparation: Evidence From Interview and Simulation Study.

OBJECTIVE: We aimed to examine the effects of information access cost and accountability on medical residents' information retrieval strategy and performance during prehandover preparation. BACKGROUND: Prior studies observing doctors' prehandover practices witnessed the use of memory-intensive strategies when retrieving patient information. These strategies impose potential threats to patient safety as human memory is prone to errors. Of interest in this work are the underlying determinants of information retrieval strategy and the potential impacts on medical residents' information preparation performance. METHOD: A two-step research approach was adopted, consisting of semistructured interviews with 21 medical residents and a simulation-based experiment with 32 medical residents. RESULTS: The semistructured interviews revealed that a substantial portion of medical residents (38%) relied largely on memory for preparing handover information. The simulation-based experiment showed that higher information access cost reduced information access attempts and access duration on patient documents and harmed information preparation performance. Higher accountability led to marginally longer access to patient documents. CONCLUSION: It is important to understand the underlying determinants of medical residents' information retrieval strategy and performance during prehandover preparation. We noted the criticality of easy access to patient documents in prehandover preparation. In addition, accountability marginally influenced medical residents' information retrieval strategy. APPLICATION: Findings from this research suggested that the cost of accessing information sources should be minimized in developing handover preparation tools.

State of science: mental workload in ergonomics.

Mental workload (MWL) is one of the most widely used concepts in ergonomics and human factors and represents a topic of increasing importance. Since modern technology in many working environments imposes ever more cognitive demands upon operators while physical demands diminish, understanding how MWL impinges on performance is increasingly critical. Yet, MWL is also one of the most nebulous concepts, with numerous definitions and dimensions associated with it. Moreover, MWL research has had a tendency to focus on complex, often safety-critical systems (e.g. transport, process control). Here we provide a general overview of the current state of affairs regarding the understanding, measurement and application of MWL in the design of complex systems over the last three decades. We conclude by discussing contemporary challenges for applied research, such as the interaction between cognitive workload and physical workload, and the quantification of workload 'redlines' which specify when operators are approaching or exceeding their performance tolerances.

Quantitative effects of overlay clutter and information access effort: Examining the scan-clutter trade-off in displays with geospatial maps.

Overlaying images from multiple geospatial databases increases clutter and imposes attentional costs by disrupting focusing attention on each database and dividing attention when comparing databases. Costs of overlay clutter may offset the benefits of reduced scanning between two images displayed separately. In two experiments, we examine these attention issues using computational metrics to quantify clutter. We also examine how the scan-clutter trade-off is modified by different levels of clutter, display separation, and task attentional requirements. Participants viewed information from a geographical terrain database and a schematic map database and made judgments that required focusing attention on either database or integrating information across both. In Experiment 1, databases were presented as either overlaid or adjacent displays, and in Experiment 2, as either overlay, adjacent, or more separated displays. Results showed that response time was modulated by the magnitude of clutter, spatial separation, and task type. Results also revealed that clutter costs dominated those of spatial separation, particularly in tasks requiring focused attention. A computational feature congestion metric of clutter effectively predicted performance but could be improved by incorporating an overlay component, which amplified the costs of clutter. The results provide design guidelines for overlay displays (e.g., head-mounted displays) that will minimize the scan-clutter trade-off. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Beyond the Wizard of Oz: Negative Effects of Imperfect Machine Learning to Examine the Impact of Reliability of Augmented Reality Cues on Visual Search Performance.

Despite knowing exactly what an object looks like, searching for it in a person's visual field is a time-consuming and error-prone experience. In Augmented Reality systems, new algorithms are proposed to speed up search time and reduce human errors. However, these algorithms might not always provide 100% accurate visual cues, which might affect users' perceived reliability of the algorithm and, thus, search performance. Here, we examined the detrimental effects of automation bias caused by imperfect cues presented in the Augmented Reality head-mounted display using the YOLOv5 machine learning model. 53 participants in the two groups received either 100% accurate visual cues or 88.9% accurate visual cues. Their performance was compared with the control condition, which did not include any additional cues. The results show how cueing may increase performance and shorten search times. The results also showed that performance with imperfect automation was much worse than perfect automation and that, consistent with automation bias, participants were frequently enticed by incorrect cues.

Supporting detection of hostile intentions: automated assistance in a dynamic decision-making context.

In a dynamic decision-making task simulating basic ship movements, participants attempted, through a series of actions, to elicit and identify which one of six other ships was exhibiting either of two hostile behaviors. A high-performing, although imperfect, automated attention aid was introduced. It visually highlighted the ship categorized by an algorithm as the most likely to be hostile. Half of participants also received automation transparency in the form of a statement about why the hostile ship was highlighted. Results indicated that while the aid's advice was often complied with and hence led to higher accuracy with a shorter response time, detection was still suboptimal. Additionally, transparency had limited impacts on all aspects of performance. Implications for detection of hostile intentions and the challenges of supporting dynamic decision making are discussed.