Abstract
Social exchange theory (SET) is a theory that is widely implemented to analyze or explain human behaviors and relationships. Nevertheless, as humans tend to behave socially toward technologies and computers, SET is applied in the field of human-automation interaction (HAI). Thus, this study adopts SET to investigate the interactions between humans and generative artificial intelligence (GAI). Because of the increasing popularity of GAI and the rising importance of technology integration in the workplace nowadays, this study values the research context of using GAI at work. Despite GAI could assist individuals while working, there are drawbacks of GAI, leading initial trust to an important role for individuals to assume the drawbacks in GAI adoption. Considering the utilization of GAI as a form of social exchange behavior, this work aims to examine the impact of initial trust on the usage intention of GAI while incorporating three moderating factors related to social exchange dynamics. The research methodology employs stratified random sampling to gather survey data from individuals with working experience. Research subjects are chosen from different industries. Subsequently, analysis will be conducted to evaluate the findings. Finally, this work can make a valuable contribution to the literature on HAI and can provide practical insights for organizations seeking to employ GAI technologies.
Recommended Citation
Chou, Chih-Yuan and Lee, Chih-Hsuan, "The Impact of Initial Trust on Usage Intention of Generative Artificial Intelligence: A Social Exchange Perspective on Human-Automation Interaction" (2023). Digit 2023 Proceedings. 5.
https://aisel.aisnet.org/digit2023/5
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