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 paper examines the potential of ChatGPT to enhance the established Delphi method by providing additional AI-infused expertise. We investigated several aspects of the Delphi method independently: the integration of abstract AI-infused expertise perspectives, the generation of an AI “clone” (digital twin) of a human expert, the rating of scenarios through AI, and the capability of AI to iterate future scenarios and to provide qualitative feedback. The findings suggest that AI systems can augment a Delphi panel by providing new perspectives but cannot replace individual human experts and their respective expertise. The insights shall inform other researchers who want to conduct hybrid Delphi studies with AI-infused expertise. In that sense, with this paper, we aim to lay the foundation for a hybrid Delphi study method and suggest actionable recommendations.
Recommended Citation
Mueller, Roland M.; Thoring, Katja; Klöckner, Hermann W.; and Larsen, Kai, "Crafting Future Scenarios with the Help of AI: Potentials of a Hybrid Delphi Expert Panel" (2024). Hawaii International Conference on System Sciences 2024 (HICSS-57). 3.
https://aisel.aisnet.org/hicss-57/os/theory_and_is/3
Crafting Future Scenarios with the Help of AI: Potentials of a Hybrid Delphi Expert Panel
Hilton Hawaiian Village, Honolulu, Hawaii
This paper examines the potential of ChatGPT to enhance the established Delphi method by providing additional AI-infused expertise. We investigated several aspects of the Delphi method independently: the integration of abstract AI-infused expertise perspectives, the generation of an AI “clone” (digital twin) of a human expert, the rating of scenarios through AI, and the capability of AI to iterate future scenarios and to provide qualitative feedback. The findings suggest that AI systems can augment a Delphi panel by providing new perspectives but cannot replace individual human experts and their respective expertise. The insights shall inform other researchers who want to conduct hybrid Delphi studies with AI-infused expertise. In that sense, with this paper, we aim to lay the foundation for a hybrid Delphi study method and suggest actionable recommendations.
https://aisel.aisnet.org/hicss-57/os/theory_and_is/3