Managing Collaborative Development of Artificial Intelligence: Lessons from the Field

Anne Sophie Mayer, Elmira van den Broek, Bomi Kim, Tomislav Karacic, Mario Sosa-Hidalgo, Marleen Huysman

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

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.

Original languageEnglish
Title of host publicationProceedings of the 56th Annual Hawaii International Conference on System Sciences, HICSS 2023
EditorsTung X. Bui
PublisherHICSS Conference Office Department of IT Management, Shidler College of Business, University of Hawaii
Pages6139-6148
Number of pages10
ISBN (Electronic)9780998133164
Publication statusPublished - 2023
Event56th Annual Hawaii International Conference on System Sciences, HICSS 2023 - Virtual, Online, United States
Duration: 3 Jan 20236 Jan 2023

Publication series

NameProceedings of the Annual Hawaii International Conference on System Sciences
Volume2023-January
ISSN (Print)1530-1605

Conference

Conference56th Annual Hawaii International Conference on System Sciences, HICSS 2023
Country/TerritoryUnited States
CityVirtual, Online
Period3/01/236/01/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE Computer Society. All rights reserved.

Keywords

  • AI development
  • collaboration
  • comparative field study
  • developers
  • domain experts

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