Location
Hilton Hawaiian Village, Honolulu, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
3-1-2024 12:00 AM
End Date
6-1-2024 12:00 AM
Description
AI-powered digital characters, AI agents, are expanding their scope of application to various fields. However, research on the key factors influencing consumer attitude is insufficient. This experimental study focuses on machine learning (ML) performance (i.e., the behavioral (intelligence) realism of AI agents), which determines users’ trust. This study further investigates the interaction role of the different forms of digital character (i.e., the form realism of AI agents) in the relationship between ML performance and trust. The findings of this study provide a novel understanding of human-AI interaction, expand academic understanding of AI anthropomorphism, and suggest new research directions for digital humans. The results will also guide business practitioners in developing AI services.
Recommended Citation
Kim, Tae Jin; Lee, One-Ki Daniel; and Kang, Juyoung, "Can We Trust an AI Agent? Interaction Effects of Its Machine Learning Performance and Digital Character" (2024). Hawaii International Conference on System Sciences 2024 (HICSS-57). 2.
https://aisel.aisnet.org/hicss-57/in/avatars/2
Can We Trust an AI Agent? Interaction Effects of Its Machine Learning Performance and Digital Character
Hilton Hawaiian Village, Honolulu, Hawaii
AI-powered digital characters, AI agents, are expanding their scope of application to various fields. However, research on the key factors influencing consumer attitude is insufficient. This experimental study focuses on machine learning (ML) performance (i.e., the behavioral (intelligence) realism of AI agents), which determines users’ trust. This study further investigates the interaction role of the different forms of digital character (i.e., the form realism of AI agents) in the relationship between ML performance and trust. The findings of this study provide a novel understanding of human-AI interaction, expand academic understanding of AI anthropomorphism, and suggest new research directions for digital humans. The results will also guide business practitioners in developing AI services.
https://aisel.aisnet.org/hicss-57/in/avatars/2