Off the mark: The influence of AI-induced errors on consumers

Mueller, Alexander ; Kuester, Sabine ; Janda, Sergej von

Document Type: Working paper
Year of publication: 2022
The title of a journal, publication series: Marketing Science Institute Working Paper Series
Volume: Report No. 22-119
Page range: 1-47
Place of publication: New York, NY
Publishing house: MSI
Publication language: English
Institution: Business School > Marketing & Innovation (Kuester 2005-)
Subject: 330 Economics
Abstract: Despite advances in technology, artificial intelligence (AI) still commonly makes errors. The popular press demonstrates examples of AI which are not error-free, and recent academic literature calls for scrutinizing AI’s pitfalls. This study explores the consequences of AI-induced errors from a marketing perspective. Specifically, we explore consumer responses to different error types as the literature distinguishes technical errors, resulting from a technical disruption of algorithmic processes, and social errors, representing task outcomes that may be mathematically correct but deemed inappropriate due to a social norm violation. We also investigate the impact of error severity by distinguishing between low and high error severity. This distinction is important because prior research has shown different response patterns depending on error severity. Errors can sometimes even evoke positive reactions as described by the pratfall effect. Based on data gathered in four studies, we find that severe errors, regardless of error type, evoke negative responses from consumers. However, minor social errors lead to significantly fewer negative consumer responses than minor technical errors. Cognitive and affective trust mediate the relationship between error type and consumer responses. Our results also reveal that companies should incorporate explainable AI (XAI) into AI applications to mitigate negative effects on consumer responses to erring AI. This study provides a granular perspective on consumer responses to erroneous AI and highlights the importance of AI’s adherence to social norms. Specifically, minor social errors could foster the stigmatization of minorities and suggest the necessity of implementing additional safeguards against social norm violations by AI.

Dieser Eintrag ist Teil der Universitätsbibliographie.

Metadata export


+ Search Authors in

+ Page Views

Hits per month over past year

Detailed information

You have found an error? Please let us know about your desired correction here: E-Mail

Actions (login required)

Show item Show item