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Can AI Regulate Your Emotions? An Empirical Investigation of the Influence of AI Explanations and Emotion Regulation on Human Decision-Making Factors

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  • Olesja Lammert

    (Paderborn University)

Abstract

Research indicates that anger is a prevalent emotion in human-technology interactions, often leading to frustration, rejection and reduced trust, significantly impacting user experience and acceptance of technology. Particularly in high-risk or uncertain situations, where AI explanations are intended to help users make more informed decisions, decision-making is influenced by emotional factors, impairing understanding and leading to suboptimal choices. While XAI research continues to evolve, greater consideration of users' emotions and individual characteristics remains necessary. Broadening empirical studies in this area could foster a more comprehensive understanding of decision-making processes following explanations, especially in relation to the interaction between emotions and cognition. In response, this study seeks to contribute to this area by employing an experimental design to examine the effects of AI explanations and emotion regulation on user reliance and trust of emotional users. The results provide a foundation for future human-centered research in XAI, focusing on the impact of emotions and cognition in human-technology interactions.

Suggested Citation

  • Olesja Lammert, 2025. "Can AI Regulate Your Emotions? An Empirical Investigation of the Influence of AI Explanations and Emotion Regulation on Human Decision-Making Factors," Working Papers Dissertations 139, Paderborn University, Faculty of Business Administration and Economics.
    • Handle: RePEc:pdn:dispap:139
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    File URL: http://groups.uni-paderborn.de/wp-wiwi/RePEc/pdf/dispap/DP139.pdf
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    References listed on IDEAS

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    1. Lerner, Jennifer & Han, Seunghee & Keltner, Dacher, 2007. "Feelings and Consumer Decision Making: Extending the Appraisal-Tendency Framework," Scholarly Articles 37143006, Harvard Kennedy School of Government.
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    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software

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