Statistically, about 70% of the process industry accidents in the refinery control room are caused by human error. It is necessary to develop a deeper understanding of the interaction between humans and the automated systems. This experiment investigated the effectiveness of Overview Displays in a refinery control room by using eye-tracking measures. Specifically, control room operators were presented with three Overview Displays that have been adopted by the oil and gas industry under two levels of difficulty for each display. The dependent variables include five eye-movement metrics that previous studies have related to cognitive processing.The results indicated that Overview Display type significantly affected eye-movement behavior. The consistency between eye tracking results and the performance results suggesting the possibility that eye-tracking measures could be used to indicate the performance results. The findings could be used to increase operator assessment effectiveness.
Human trust in automation has been studied extensively within safety critical domains (military, aviation, process control, etc.) because harmful consequences are associated with the improper calibration of trust in automated systems in these domains (Parasuraman & Riley, 1997). As such, researchers have worked to identify important factors which help humans build trust in such systems (Hoff & Bashir, 2015). With the explosion of AI in consumer technologies, it is becoming equally critical to understand how humans interact with everyday devices. This study investigated how factors that have been identified to impact trust in automation in safety critical domains influence the trust and use of popular digital assistants (Siri, Cortana, Bixby or Google Now). We conducted an online survey with 278 regular users of digital assistants across three generations (GenX, GenY, and GenZ). The results demonstrate that, even after controlling for dispositional factors (i.e., individual characteristics such as age, culture, gender), GenZ exhibited higher trust in digital assistants than GenX. More interestingly, linear regression analyses revealed a different set of predictors of trust for each generation. Results from this survey have implications for the design of digital assistants.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.