arXiv AI By Zihan Chen, Di Zhu, Lei Nico Zheng

Beauty Is Human: When People Love AI-Generated Art, They Think a Human Made It

Read the original on arXiv AI →

The study shows that when people enjoy an artwork, they are more likely to believe it was created by a human, regardless of whether it was actually AI-generated or not. In a large online Turing Test, 22.1 percentage points more of respondents who favored a picture thought it was human-made, and this pattern held across all images and detection methods. Even those who were skeptical of AI art often preferred AI-generated pieces but still attributed them to humans, indicating a strong link between aesthetic preference and perceived authorship.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

arXiv Computer Vision
Oct 19

Generative AI Produces and Transmits Beauty Bias

The paper audits 27 text‑to‑image generators released between 2022 and 2026, examining 51,300 AI‑generated faces and 160,196 real photographs. Using automated metrics and 550 human raters, it finds that AI‑generated faces consistently score higher on attractiveness than real faces, with female‑prompted images often surpassing professional models and darker‑skinned groups receiving lower scores. A preregistered hiring simulation shows that exposure to AI‑generated attractive faces reduces hireability and trustworthiness ratings for real candidates, whereas retouched photographs have no such effect.

By AJ Alvero, Deepak Varuvel Dennison, Alexandra Crespin, Heeyon Kim, Alejandra Regla-Vargas, Avani Akerkar, Jasmine McNealy, Ren\'e Kizilcec
arXiv Computation and Language
Oct 12

How AI Writing Assistance Distorts Perceptions of AI Users and Their Opinions

Hundreds of millions use AI for writing assistance, and a study with 2,939 writers and 11,091 readers examined how AI affects perceptions of writers. Writers who used AI were seen as more opinionated, competent, positive, and demographically privileged, though many writers objected to these distortions yet still preferred AI‑assisted text. Reward models reduced objectionable distortions but lowered user acceptance, and readers trusted and were more persuaded by AI‑assisted writers when distortions were higher.

By Paul R\"ottger, Kobi Hackenburg, Hannah Rose Kirk, Christopher Summerfield