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A Survey of AI Reliance

Title data

Eckhardt, Sven ; Kühl, Niklas ; Dolata, Mateusz ; Schwabe, Gerhard:
A Survey of AI Reliance.
In: ACM Computing Surveys. (November 2025) .
ISSN 1557-7341
DOI: https://doi.org/10.1145/3776528

Official URL: Volltext

Abstract in another language

Although artificial intelligence (AI) systems are becoming increasingly indispensable, research into how humans rely on these systems (AI reliance) is lagging behind. To advance this research, this survey presents a novel, comprehensive sociotechnical perspective on AI reliance, essential to fully understand the phenomenon. To address these challenges, the survey introduces a categorization framework resulting in a morphological box, which guides rigorous AI reliance research. Further, the survey identifies the core influences on AI reliance within the components of a sociotechnical system and discusses current limitations alongside emerging future research avenues to form a research agenda.

Further data

Item Type: Article in a journal
Refereed: Yes
Keywords: Artifical intelligence; Reliance; Literature survey
Institutions of the University: Faculties > Faculty of Law, Business and Economics > Department of Business Administration
Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Chair Business Informatics and Human-Centered Artificial Intelligence
Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Chair Business Informatics and Human-Centered Artificial Intelligence > Chair Business Informatics and Human-Centered Artificial Intelligence - Univ.-Prof. Dr.-Ing. Niklas Kühl
Research Institutions
Research Institutions > Affiliated Institutes
Research Institutions > Affiliated Institutes > FIM Research Center for Information Management
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: 02 Dec 2025 14:08
Last Modified: 02 Dec 2025 14:08
URI: https://eref.uni-bayreuth.de/id/eprint/95367