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
Integrating artificial intelligence (AI) in organizations is often viewed as a way to enhance decision-making by extending human rationality. However, there is an interesting puzzle. While the theoretical accounts of AI conceptualize how contemporary AI technologies, like machine learning, may aid domain experts in making rational decisions, the empirical accounts highlight that despite the enthusiasm and willingness to explore, domain experts often fail to accept AI-based recommendations in making decisions. In this study, we address this puzzle by demonstrating the role of data scientists in shaping domain experts’ decision-making processes. We do so by integrating insights from a qualitative study of three large banks with a computational model based on the tenets of the Garbage Can Model of organizational choice. Our findings highlight the complexities of organizational decision-making when the two groups, with their unique visions of rationality, are tasked to work together.
Recommended Citation
Joshi, Mayur and Chakraborty, Saurav, "AI in the Garbage Cans: How Data Scientists Contribute to Organizational Decision-Making" (2025). Hawaii International Conference on System Sciences 2025 (HICSS-58). 4.
https://aisel.aisnet.org/hicss-58/os/innovation/4
AI in the Garbage Cans: How Data Scientists Contribute to Organizational Decision-Making
Hilton Waikoloa Village, Hawaii
Integrating artificial intelligence (AI) in organizations is often viewed as a way to enhance decision-making by extending human rationality. However, there is an interesting puzzle. While the theoretical accounts of AI conceptualize how contemporary AI technologies, like machine learning, may aid domain experts in making rational decisions, the empirical accounts highlight that despite the enthusiasm and willingness to explore, domain experts often fail to accept AI-based recommendations in making decisions. In this study, we address this puzzle by demonstrating the role of data scientists in shaping domain experts’ decision-making processes. We do so by integrating insights from a qualitative study of three large banks with a computational model based on the tenets of the Garbage Can Model of organizational choice. Our findings highlight the complexities of organizational decision-making when the two groups, with their unique visions of rationality, are tasked to work together.
https://aisel.aisnet.org/hicss-58/os/innovation/4