This study examined the relationship of operator personality (Five Factor Model) and characteristics of the task and of adaptive automation (reliability and adaptiveness-whether the automation was well-matched to changes in task demand) to operator performance, workload, stress, and coping. This represents the first investigation of how the Five Factors relate to human response to automation. One-hundred-sixty-one college students experienced either 75% or 95% reliable automation provided with task loads of either two or four displays to be monitored. The task required threat detection in a simulated uninhabited ground vehicle (UGV) task. Task demand exerted the strongest influence on outcome variables. Automation characteristics did not directly impact workload or stress, but effects did emerge in the context of trait-task interactions that varied as a function of the dimension of workload and stress. The pattern of relationships of traits to dependent variables was generally moderated by at least one task factor. Neuroticism was related to poorer performance in some conditions, and all five traits were associated with at least one measure of workload and stress. Neuroticism generally predicted increased workload and stress and the other traits predicted decreased levels of these states. However, in the case of the relation of Extraversion and Agreeableness to Worry, Frustration, and avoidant coping, the direction of effects varied across task conditions. The results support incorporation of individual differences into automation design by identifying the relevant person characteristics and using the information to determine what functions to automate and the form and level of automation.

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This study evaluated the detection accuracy of one of the first brain-computer interfaces intended for personal use by normal, healthy users: the Emotiv EPOC. This system allows the user to directly interact with computer software through thoughts alone. The system was evaluated on its ability to accurately detect and classify six sets of paired mental actions over three evaluation phases. Results found the system to perform significantly better than chance for all mental actions, and improve over time with additional training data. The system detected all actions with equivalent accuracy. Additional investigation of individual differences revealed that a user’s gender, age, handedness, attentional control, vividness of visual imagery, and mental rotation ability all had no bearing on the detection accuracy of the system. These results indicate the Emotiv EPOC system performs its function as a brain-computer interface with an acceptable level of accuracy, yielding many new possibilities for human-computer interaction.

Advances in modern day technology are rapidly increasing the ability of engineers to automate ever more complicated tasks. Often these automated aids are paired with human operators who can supervise their work to ensure that it is free of errors and to even take control of the system if it malfunctions (e.g., pilots supervising an autopilot feature). The goal of this collaboration, between humans and machines, is that it can enhance performance beyond what would be possible by either alone. Arguably the success of this partnership depends in part upon attributions an operator develops that help guide their interaction with the automation. One particular factor that has been shown to guide operator reliance on an automated 'teammate' is trust. The following study examined 140 participants performing a simulated search-and-rescue task. The goal of this experiment was to examine the relationship between automated agent's reliability, operator trust, operator reliance, and performance scores. Results indicated that greater automation reliability is positively correlated with greater user reliance (r=.66), perceived trust (r=.21), and performance scores (r=.34). These results indicate that more reliable aids are rated as significantly higher in terms of perceived trust and relied upon more than less reliable aids. Additionally, the size of the effect is much larger for operator behaviors (i.e., reliance) compared to more subjective measures (i.e., self-reported trust).

The availability of increasingly advanced simulation interfaces has led researchers to question whether these newer interfaces provide a more effective means of providing simulation-based training. An empirical evaluation was conducted comparing the knowledge gained from training with three different systems: narrated computer animations (Flash videos) that are currently in use in the U.S. Army, an interactive virtual environment presented on a standard desktop PC, and the same virtual environment presented on a wearable simulator with head-mounted display. Results indicated no difference in the knowledge gained from any of the training methods, although the Flash videos were deemed less engaging, enjoyable, and elicited less presence than both of the virtual environment training methods. The wearable simulation interface was also found to cause greater levels of simulator sickness than either the desktop PC or Flash video training methods. The results of the current study show no evidence of a benefit of using the wearable system over more traditional desktop systems.