Automation Usage Decisions: Controlling Intent and Appraisal Errors in a Target Detection Task
نویسندگان
چکیده
BACKGROUND It was proposed that misuse and disuse often occur because operators (a) cannot determine if automation or a nonautomated alternative maximizes the likelihood of task success (appraisal errors) or (b) know the utilities of the options but disregard this information when deciding to use automation (intent errors). OBJECTIVE This investigation assessed the effectiveness of performance feedback, a procedure developed to attenuate appraisal errors, and scenario training, an intervention designed to decrease intent errors. METHODS Operators given feedback were told how many errors they and an automated device made on a target detection task. Scenario training took operators through the thought processes of optimal decision makers after the utilities of the automated and nonautomated alternatives had been determined. Following 200 training trials, participants chose between relying on their observations or an automated device. RESULTS There was little misuse, but disuse rates were high (84%) among operators receiving neither feedback nor scenario training. Operators paired with a more accurate machine and given feedback made approximately twice as many errors as the automated device. Nevertheless, intent errors were commonplace; 55% of the operators who received feedback without scenario training did not rely on automation. Feedback effectiveness was enhanced when used in conjunction with scenario training; the disuse rate decreased to 29%. CONCLUSION A combination of feedback and scenario training was more effective in mitigating disuse than either intervention used in isolation. APPLICATION An important application of these findings is that operator training programs should incorporate techniques to control intent and appraisal errors.
منابع مشابه
Effects of Human-Machine Competition on Intent Errors in a Target Detection Task
OBJECTIVE This investigation examined the impact of human-machine competition (John Henry effects) on intent errors. John Henry effects, expressed as an unwillingness to use automation, were hypothesized to increase as a function of operators' personal investment in unaided performance. BACKGROUND Misuse and disuse often occur because operators (a) cannot determine if automation or a nonautom...
متن کاملAge differences in trust and reliance of a medication management system
The present study examined age differences in trust and reliance of an automated decision aid. In Experiment 1, older and younger participants performed a simple mathematical task concurrent with a simulated medication management task. The decision aid was designed to facilitate medication management, but with varying reliability. Trust, self-confidence and usage of the aid were measured. The r...
متن کاملPerformance Effects of Imperfect Cross-Modal Sensory Cueing in a Target Detection Simulation
Past research has shown that multi-modal sensory cues can reduce the workload of the user while simultaneously increasing performance capacity. This study looks to examine how performance is impacted in a multi-modal sensory cueing target detection task in which the cueing automation is imperfect. Twenty-seven undergraduate participants volunteered to take part in the present multi-modal sensor...
متن کاملEffects of Automation on Situation Awareness in Controlling Robot Teams
Declines in situation awareness (SA) often accompany automation. Some of these effects have been characterized as out-of-the-loop, complacency, and automation bias. Increasing autonomy in multi-robot control might be expected to produce similar declines in operators’ SA. In this paper we review a series of experiments in which automation is introduced in controlling robot teams. Automating path...
متن کاملDesign and Evaluation of Path Planning Decision Support for Planetary Surface Exploration
Human intent is an integral part of real-time path planning and re-planning, thus any decision aiding system must support human-automation interaction. The appropriate balance between humans and automation for this task has previously not been adequately studied. In order to better understand task allocation and collaboration between humans and automation for geospatial path problem solving, a ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Human factors
دوره 49 3 شماره
صفحات -
تاریخ انتشار 2007