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
This study aims to analyze a mechanism of AI responsibility based on attribution theory. It also identifies a new concept, AI locus of control (AI-LOC), reflecting an individual’s belief about the degree to which AI determines decision performance. To this end, we built a website with embedded AI systems where participants longitudinally made corporate credit rating decisions. We created a dynamic panel dataset that includes participants’ decisions per task and decision performance and attitudes per session. The results revealed that AI-LOC and trust in AI were developed in parallel yet differed over time. AI-LOC positively influenced AI use, but trust in AI did not. We reasoned that individuals would likely exhibit self-serving biases and take an egocentric and disengagement coping strategy regarding their decision-making with AI. This study can contribute to understanding the psychological and behavioral aspects of AI use.
Recommended Citation
Lee, Kyootai; Cho, Wooje; and Woo, Han-Gyun, "A Mythic Belief Regarding Trust in Artificial Intelligence: Uncovering the Role of Responsibility Perception for AI Use in Decision Makings" (2024). Hawaii International Conference on System Sciences 2024 (HICSS-57). 4.
https://aisel.aisnet.org/hicss-57/da/xai/4
A Mythic Belief Regarding Trust in Artificial Intelligence: Uncovering the Role of Responsibility Perception for AI Use in Decision Makings
Hilton Hawaiian Village, Honolulu, Hawaii
This study aims to analyze a mechanism of AI responsibility based on attribution theory. It also identifies a new concept, AI locus of control (AI-LOC), reflecting an individual’s belief about the degree to which AI determines decision performance. To this end, we built a website with embedded AI systems where participants longitudinally made corporate credit rating decisions. We created a dynamic panel dataset that includes participants’ decisions per task and decision performance and attitudes per session. The results revealed that AI-LOC and trust in AI were developed in parallel yet differed over time. AI-LOC positively influenced AI use, but trust in AI did not. We reasoned that individuals would likely exhibit self-serving biases and take an egocentric and disengagement coping strategy regarding their decision-making with AI. This study can contribute to understanding the psychological and behavioral aspects of AI use.
https://aisel.aisnet.org/hicss-57/da/xai/4