Emotional Responses to Artificial Intelligence Systems: A Scoping Review of Studied Applications, Key Concepts, and Central Associations.
Saved in:
| Title: | Emotional Responses to Artificial Intelligence Systems: A Scoping Review of Studied Applications, Key Concepts, and Central Associations. |
|---|---|
| Authors: | Koenig, Pascal D.1 (AUTHOR) p.d.koenig@vu.nl, Mehrotra, Siddharth2 (AUTHOR) |
| Source: | International Journal of Human-Computer Interaction. Aug2026, Vol. 42 Issue 15, p11673-11693. 21p. |
| Subjects: | Artificial intelligence, Human-artificial intelligence interaction, Satisfaction, Emotions, Artificial intelligence & ethics, Technology Acceptance Model, Ethical problems |
| Abstract: | This article presents a scoping review of research on how people respond to AI systems on an emotional level. Using 154 contributions from the complete decade 2015 to 2024, it charts which domains and AI systems and which emotional constructs research has focused on and points to central findings regarding the antecedents and the consequences of emotional responses to AI systems. The review identifies a predominant interest in how emotional responses affect AI use and user satisfaction. The most commonly studied antecedents are features that make AI systems more human-like. The ethical implications of fostering emotional responses in this way are, however, rarely discussed. Further, emotional responses emerge as important mediating variables and as influential causes besides non-emotional constructs – thus complementing common technology acceptance models in important ways. The findings are important for achieving a balanced regulation of AI that enables beneficial human-AI engagement while safeguarding human autonomy. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Human-Computer Interaction is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
Be the first to leave a comment!
