Location
Hilton Waikoloa Village, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
7-1-2025 12:00 AM
End Date
10-1-2025 12:00 AM
Description
While much research focuses on the adoption and benefits of generative AI (GenAI) technologies, this study explores the reasons behind the non-use of these tools after initial adoption. A mixed-methods approach was employed, beginning with an exploratory qualitative study to identify scenarios and reasons for non-use among experienced GenAI users. This was followed by a quantitative study analyzing the relationship between these reasons and non-use across various contexts. Findings highlight key concerns, such as output quality, ethical implications, and the loss of human connection, as significant predictors of non-use. Additionally, individual characteristics, like the need for social connectedness, significantly influence non-use behavior. These insights are critical for designers, organizations, and managers to understand and address barriers to GenAI usage, ultimately aiming to enhance the effective integration of these technologies in diverse settings.
Recommended Citation
Wells, Taylor; Steffen, Jacob; Hughes, Amanda; Richardson, Benjamin; Meservy, Tom; and Schuetzler, Ryan, "Resistance to Generative AI: Investigating the Drivers of Non-Use" (2025). Hawaii International Conference on System Sciences 2025 (HICSS-58). 5.
https://aisel.aisnet.org/hicss-58/cl/machines_as_teammates/5
Resistance to Generative AI: Investigating the Drivers of Non-Use
Hilton Waikoloa Village, Hawaii
While much research focuses on the adoption and benefits of generative AI (GenAI) technologies, this study explores the reasons behind the non-use of these tools after initial adoption. A mixed-methods approach was employed, beginning with an exploratory qualitative study to identify scenarios and reasons for non-use among experienced GenAI users. This was followed by a quantitative study analyzing the relationship between these reasons and non-use across various contexts. Findings highlight key concerns, such as output quality, ethical implications, and the loss of human connection, as significant predictors of non-use. Additionally, individual characteristics, like the need for social connectedness, significantly influence non-use behavior. These insights are critical for designers, organizations, and managers to understand and address barriers to GenAI usage, ultimately aiming to enhance the effective integration of these technologies in diverse settings.
https://aisel.aisnet.org/hicss-58/cl/machines_as_teammates/5