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Conceptualizing Multi-party AI Reliance for Design Research

Eckhardt, Sven; Dolata, Mateusz; Bauer-Hänsel, Ingrid; Schwabe, Gerhard (2024). Conceptualizing Multi-party AI Reliance for Design Research. In: 19th International Conference on Design Science Research in Information Systems and Technology, DESRIST 2024, Trollhättan, Sweden, 3 June 2024 - 5 June 2024. Springer (Bücher), 51-65.

Abstract

Appropriate reliance on artificial intelligence (AI)-based systems is paramount to leverage increasing AI performance. However, multi-party settings, where multiple parties with diverging interests interact with the support of AI systems, are currently neglected. In this study, we use Heider’s balance theory to derive a framework that allows us to conceptualize and analyze reliance on AI in multi-party settings. We then use this framework to analyze two large design science research projects. First, we analyze financial advisory service encounters, where the role inequality of advisor and client can lead to a dominance of the advisor. Second, we analyze used car market negotiations, where the problem of partial reliance on AI systems creates a misalignment between the two parties, ultimately failing the negotiations. Finally, we discuss implications and future research on AI reliance in multi-party settings and highlight that this study should serve as a starting point in investigating AI reliance in multi-party settings.

Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Scopus Subject Areas:Physical Sciences > Theoretical Computer Science
Physical Sciences > General Computer Science
Scope:Discipline-based scholarship (basic research)
Language:English
Event End Date:5 June 2024
Deposited On:01 Nov 2024 11:24
Last Modified:02 Nov 2024 21:00
Publisher:Springer (Bücher)
Series Name:Lecture Notes in Computer Science
Number:14621
ISSN:0302-9743
ISBN:9783031611742
OA Status:Closed
Publisher DOI:https://doi.org/10.1007/978-3-031-61175-9_4
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