How Transparency Measures Can Attenuate Initial Failures of Intelligent Decision Support Systems

Matt, C.; Schlusche, C. (2022). How Transparency Measures Can Attenuate Initial Failures of Intelligent Decision Support Systems. In: Thirtieth European Conference on Information Systems (ECIS 2022). Timișoara, Romania. 18.-24. Juni 2022.

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Owing to high functional complexity, trust plays a critical role for the adoption of intelligent decision support systems (DSS). Especially failures in initial usage phases might endanger trust since users are yet to assess the system’s capabilities over time. Since such initial failures are unavoidable, it is crucial to understand how providers can inform users about system capabilities to rebuild user trust. Using an online experiment, we evaluate the effects of recurring explanations and initial tutorials as transparency measures on trust. We find that recurring explanations are superior to initial tutorials in establishing trust in intelligent DSS. However, recurring explanations are only as effective as tutorials or the combination of both tutorials and recurring explanations in rebuilding trust after initial failures occurred. Our results provide empirical insights for the design of transparency mechanisms for intelligent DSS, especially those with high underlying algorithmic complexity or potentially high damage.

Item Type:

Conference or Workshop Item (Paper)

Division/Institute:

03 Faculty of Business, Economics and Social Sciences > Department of Business Management > Institute of Information Systems > Information Management
03 Faculty of Business, Economics and Social Sciences > Department of Business Management > Institute of Information Systems

UniBE Contributor:

Matt, Christian

Subjects:

000 Computer science, knowledge & systems
300 Social sciences, sociology & anthropology
300 Social sciences, sociology & anthropology > 330 Economics
600 Technology > 650 Management & public relations

Series:

ECIS 2022 Research Papers

Language:

English

Submitter:

Yves Roulin

Date Deposited:

24 May 2022 16:02

Last Modified:

06 Feb 2024 14:59

Related URLs:

BORIS DOI:

10.48350/169370

URI:

https://boris.unibe.ch/id/eprint/169370

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