Discipline: Technology and Engineering
Subcategory: Civil/Mechanical/Manufacturing Engineering
Seeung Oh - North Carolina A&T State University
In contemporary society, autonomous systems have become more complex because of the strong need to perform sophisticated tasks and the need to design complex control systems. In complex autonomous systems, the role of the human operator of controlling and monitoring is crucial to avoid failure and risk, and to prevent unpredictable situations that cannot be programmed in the system. Trust can affect the operator’s degree of acceptance and reliance on the automated system, so measuring human operators’ level of trust is vital in predicting their strategies when interacting with the system. Previous studies investigated the relationship between social constructs and neural or physiological evidence and focused on brain regions using fMRI and efMRI, which engage with stimuli related to trust and distrust. This research measures and analyzes human brainwaves in situations involving trust and mistrust using an electroencephalogram (EEG). This research measured and analyzed human brainwaves and brain regions using situations involving trust and mistrust. Investigating human brainwaves using an electroencephalogram (EEG) makes this research valuable because this neuroimaging technique can be a direct and objective method of detecting and measuring human trust. The research is comprised of a two-phase experiment, namely, a word elicitation study used to investigate general trust and a simulation consisting of automatic and manual controls to investigate human trust in automation. Power spectrum and coherence analysis were used to analyze the EEG data collected. The results showed that trust situations affected the alpha and beta waves whereas mistrust situations affected the gamma waves. The frontal and parietal lobes showed active communication for the trust situations whereas the temporal and occipital lobes showed active engagement for the mistrust situations. The results revealed similar brainwaves and brain regions for both general trust and human trust on automation. Further, human trust on automation affects the use of an automatic control. Therefore, trust can assist in effective decision-making by increasing concentration and performance, which are related to the alpha and beta waves and the frontal and parietal lobe. On the other hand, mistrust can disrupt effective decision-making by increasing stress and anxiety, which are related to the gamma waves and the temporal and occipital lobes. My future research goal is to use BCI to determine how human trust in various simulated models of automation affects human operators’ decision-making and their overall performance. Key References: Jian, Jiun-Yin, Bisantz, Ann M., & Drury, Colin, G. (2000). Foundations for an Empirically Determined Scale of Trust in Automated Systems. International journal of cognitive ergonomics, 4(1), 53-71. Lee, J. D. & Moray, N. (1994). Trust, self-confidence, and operators’ adaptation to automation. International Journal of Human-Computer Studies, 40, 153- 184.Not Submitted
Funder Acknowledgement(s): Army Research Laboratory Department of Energy
Faculty Advisor: Dr. Younho Seong, email@example.com
Role: I am the primary author.