Abstract
Generative AI (GenAI) use is transforming how people work, communicate, and make decisions, raising unique questions about how its users are judged—both by themselves and others. In this article, we offer a framework, grounded in attribution theory, to synthesize the literature and articulate a coherent account of how GenAI use shapes social evaluations of its users. Our framework unravels distinct patterns across actors’ and observers’ perspectives and competence and warmth dimensions, outlining how attributions shape social judgments of GenAI users in a predictable manner. We discuss implications for human-AI interaction research, attribution theory, and the literature on social judgment.
| Original language | English |
|---|---|
| Journal | Current Directions in Psychological Science |
| DOIs | |
| State | Accepted/In press - 2026 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© The Author(s) 2026. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
Keywords
- attribution theory
- generative AI
- interpersonal judgment
- self-other asymmetry
- social perception
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