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The Role of Domain Expertise in Trusting and Following Explainable AI Decision Support Systems

Title data

Bayer, Sarah ; Gimpel, Henner ; Markgraf, Moritz:
The Role of Domain Expertise in Trusting and Following Explainable AI Decision Support Systems.
In: Journal of Decision Systems. Vol. 32 (2022) Issue 1 . - pp. 110-138.
ISSN 1246-0125
DOI: https://doi.org/10.1080/12460125.2021.1958505

Abstract in another language

Although the roots of artificial intelligence (AI) stretch back some years, it currently flourishes in research and practice. However, AI deals with trust issues. One possible solution approach is making AI explain itself to its user, but it is still unclear how an AI can accomplish this in decision-making scenarios. This study focuses on how a user’s expertise influences trust in explainable AI (XAI) and how this influences behaviour. To test our theoretical assumptions, we develop an AI-based decision support system (DSS), observe user behaviour in an online experiment, complemented with survey data. The results show that domain-specific expertise negatively affects trust in AI-based DSS. We conclude that the focus on explanations might be overrated for users with low domain-specific expertise, whereas it is vital for users with high expertise. Investigating the influence of expertise on explanations of an AI-based DSS, this study contributes to research on XAI and DSS.

Further data

Item Type: Article in a journal
Refereed: Yes
Keywords: Explainable Artificial Intelligence; Trust; Decision Support Systems; User Expertise; Online Experiment
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 Administration XVII - Information Systems and Value-Based Business Process Management
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: 10 Sep 2021 09:35
Last Modified: 07 Nov 2023 12:48
URI: https://eref.uni-bayreuth.de/id/eprint/67003