The Type to Listen to the Machine? The Effect of Personality on the Use of AI Advice
Asbach S, Graf-Vlachy L, Fügener A (2025)
Publication Type: Conference contribution
Publication year: 2025
Publisher: Springer Science and Business Media Deutschland GmbH
Book Volume: 74
Pages Range: 153-168
Conference Proceedings Title: Lecture Notes in Information Systems and Organisation
Event location: Paderborn, DEU
ISBN: 9783031801181
DOI: 10.1007/978-3-031-80119-8_10
Abstract
Personality is a key antecedent of individual differences in advice-taking from humans. We analyze whether and how personality also influences advice-taking from Artificial Intelligence (AI) systems, which are a promising source of advice to aid human decision-making. It is particularly important to understand advice-taking from AI systems because recent research shows that such systems are often used imperfectly. We consider the Big Five personality traits (extraversion, agreeableness, conscientiousness, neuroticism, and openness) as antecedents of the use of AI advice in a cross-sectional study with 595 participants. The results support our theoretical predictions that agreeableness and neuroticism are associated with an increased use of AI advice. Contrary to our predictions, openness seems associated with a decreased use of AI advice, whereas extraversion and conscientiousness do not seem to be related with the use of AI advice.
Involved external institutions
Germany (DE)How to cite
APA:
Asbach, S., Graf-Vlachy, L., & Fügener, A. (2025). The Type to Listen to the Machine? The Effect of Personality on the Use of AI Advice. In Daniel Beverungen, Matthias Trier, Christiane Lehrer (Eds.), Lecture Notes in Information Systems and Organisation (pp. 153-168). Paderborn, DEU: Springer Science and Business Media Deutschland GmbH.
MLA:
Asbach, Simon, Lorenz Graf-Vlachy, and Andreas Fügener. "The Type to Listen to the Machine? The Effect of Personality on the Use of AI Advice." Proceedings of the 18th International Conference on Wirtschaftsinformatik, WI 2023, Paderborn, DEU Ed. Daniel Beverungen, Matthias Trier, Christiane Lehrer, Springer Science and Business Media Deutschland GmbH, 2025. 153-168.
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