Managing Collaborative Development of Artificial Intelligence: Lessons from the Field
Autor: | Mayer, Anne Sophie, van den Broek, Elmira, Kim, Bomi, Karacic, Tomislav, Sosa-Hidalgo, Mario, Huysman, Marleen, Bui, Tung X. |
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Přispěvatelé: | Knowledge, Information and Innovation, Network Institute, KIN Center for Digital Innovation |
Jazyk: | angličtina |
Rok vydání: | 2023 |
Předmět: | |
Zdroj: | Proceedings of the 56th Annual Hawaii International Conference on System Sciences (HICSS 2023), 6139-6148 STARTPAGE=6139;ENDPAGE=6148;TITLE=Proceedings of the 56th Annual Hawaii International Conference on System Sciences (HICSS 2023) |
Popis: | Artificial intelligence (AI) promises businesses superior decisions that outperform those of domain experts. However, AI systems may fail on the ground when they are not developed in collaboration with the experts they seek to bypass. This raises the question of how to manage the collaborative development of AI. Building on a comparative field study, we reveal three key challenges of collaborative AI development in the area of consulting, hiring, and radiology. Based on these findings, we derive guidelines for managers that help them to facilitate the close engagement between AI developers and experts. |
Databáze: | OpenAIRE |
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