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Designing Human-AI Hybrids : Challenges and Good Practices From a Multiple Case Study

Title data

Mayer, Valentin ; Schüll, Moritz ; Aktürk, Onur ; Guggenberger, Tobias:
Designing Human-AI Hybrids : Challenges and Good Practices From a Multiple Case Study.
In: Proceedings of the 45th International Conference on Information Systems (ICIS). - Bangkok, Thailand , 2024

Official URL: Volltext

Abstract in another language

The increasing adoption of artificial intelligence (AI) in organizations has led to the emergence of human-AI hybrids, where human and AI agents collaborate on joint tasks. This paper presents a multiple case study exploring the challenges and good practices of constructing and executing such hybrid systems. Using a work system theory perspective, we identify nine challenges and nine good practices from four successfully implemented real world cases of human-AI hybrids, structured along the work system lifecycle. In line with our socio-technical approach, we identify two major stakeholder roles involved in the construction and execution of human-AI hybrids, the technical implementer and the organizational implementer, each of which faces unique challenges and applies different good practices. This research contributes to the growing body of knowledge on the implementation of human-AI hybrids in organizations and provides practical insights for managers and implementers seeking to successfully integrate AI into their work systems.

Further data

Item Type: Article in a book
Refereed: Yes
Keywords: human-AI hybrids; work system theory; multiple case study; human-AI collaboration
Institutions of the University: Faculties > Faculty of Law, Business and Economics > Department of Business Administration
Research Institutions
Research Institutions > Affiliated Institutes
Research Institutions > Affiliated Institutes > Branch Business and Information Systems Engineering of Fraunhofer FIT
Research Institutions > Affiliated Institutes > FIM Research Center for Information Management
Faculties
Faculties > Faculty of Law, Business and Economics
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
300 Social sciences > 330 Economics
Date Deposited: 30 Oct 2024 09:07
Last Modified: 30 Oct 2024 09:07
URI: https://eref.uni-bayreuth.de/id/eprint/90870