AI and Aesthetic Bias
Abstract
Abstract This article introduces and analyzes the notion of aesthetic bias in generative AI. I argue that AI models systematically privilege certain aesthetically relevant features while marginalizing others. Drawing on examples from popular text-to-image generators, I highlight recurring tendencies, such as a preference for beauty, spectacle, saturation, or symmetry. These aesthetic biases carry specific risks: they disguise aesthetic preferences as neutrality, threaten to homogenize artistic production and taste, and contribute to creating self-enclosed communities of appreciators, or “aesthetic bubbles.” The upshot is that aesthetic bias in AI demands serious study.
Fields of Study & Subjects
Aesthetic Perception and Analysis
Ethics and Social Impacts of AI
Psychology of Moral and Emotional Judgment
Publication details
- Journal / source
- Journal of Aesthetics and Art Criticism
- Publisher
- Oxford University Press (OUP)
- Volume
- 84
- Issue
- 2
- Pages
- 218–233
- Publication date
- 1 January 2026
- Language
- EN