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.

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.

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.

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.

How history trails and set size influence detection of hostile intentions.

Previous research suggests people struggle to detect a series of movements that might imply hostile intentions of a vessel, yet this ability is crucial in many real world Naval scenarios. To investigate possible mechanisms for improving performance, participants engaged in a simple, simulated ship movement task. One of two hostile behaviors were present in one of the vessels: Shadowing-mirroring the participant's vessel's movements; and Hunting-closing in on the participant's vessel. In the first experiment, history trails, showing the previous nine positions of each ship connected by a line, were introduced as a potential diagnostic aid. In a second experiment, the number of computer-controlled ships on the screen also varied. Smaller set size improved detection performance. History trails also consistently improved detection performance for both behaviors, although still falling well short of optimal, even with the smaller set size. These findings suggest that working memory plays a critical role in performance on this dynamic decision making task, and the constraints of working memory capacity can be decreased through a simple visual aid and an overall reduction in the number of objects being tracked. The implications for the detection of hostile intentions are discussed.