User Stress in Artificial Intelligence: Modeling in Case of System Failure

IEEE Access

Hyun K. Kim¹  Jungyoon Kim²  Jangwoon Park³  Olga Vl. Bitkina⁴  Jaehyun Park⁵ 

[1] Corpus Christi, Corpus Christi, TX, USA;Department of Computer Science, Kent State University, Kent, OH, USA;Department of Engineering, Texas A&x0026;Department of Industrial and Management Engineering, Incheon National University (INU), Incheon, South Korea;M University&x2014;

关键词: Artificial intelligence;    electrodermal activity;    physiological stress;    stepwise regression;    system failure;   

DOI  :  10.1109/ACCESS.2021.3117120

来源: DOAJ

【 摘 要 】

The uninterrupted operation of systems with artificial intelligence (AI) ensures high productivity and accuracy of the tasks performed. The physiological state of AI operators indicates a relationship with an AI system failure event and can be measured through electrodermal activity. This study aims to model the stress levels of system operators based on system trustworthiness and physiological responses during a correct AI operation and its failure. Two groups of 18 and 19 people participated in the experiments using two different types of software with elements of AI. The first group of participants used English proofreading software, and the second group used drawing software as the AI tool. During the tasks, the electrodermal activities of the participants as a stress level indicator were measured. Based on the results obtained, the users’ stress was determined and classified using logistic regression models with an accuracy of approximately 70%. The insights obtained can serve AI product developers in increasing the level of user trust and managing the anxiety and stress levels of AI operators.

【 授权许可】

Unknown