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Updated: Jun 20, 2026

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

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Published on: June 3, 2013

Where does the bias begin? Cognitive processing differences in the aesthetic evaluation of AI-generated art.

Yongquan Wang¹, Yiwei Cao², Jingnan Cai¹

¹School of Theater, Film and Television, Communication University of China, Beijing, China.

Frontiers in Psychology

|June 19, 2026

Summary

The negative bias against AI-generated art emerges during controlled processing, not automatic processing. Providing interpretive cues significantly reduces this bias, suggesting a need for meaning construction in aesthetic appreciation.

Keywords:

aesthetics artificial intelligence computer-generated art dual-process theories meaning construction

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Published on: May 1, 2021

Area of Science:

Cognitive Psychology
Art Perception
Artificial Intelligence

Background:

The Pleasure-Interest Model of Aesthetic Liking (PIA model) provides a framework for understanding aesthetic judgments.
A potential negative bias towards AI-generated art has been observed, but its underlying cognitive mechanisms remain unclear.

Purpose of the Study:

To investigate whether the negative bias against AI-generated art originates from automatic or controlled cognitive processing.
To determine if interpretive semantic cues can mitigate this bias.

Main Methods:

Three experiments were conducted using exclusively AI-generated artworks.
Creator labels were manipulated while artwork remained constant.
Processing conditions were varied to favor either automatic or controlled cognitive engagement.
Interpretive semantic cues (textual descriptions) were provided in some conditions.

Main Results:

The negative bias against AI-generated art was significantly smaller under conditions promoting automatic processing compared to controlled processing.
This bias predominantly emerged during controlled processing.
Providing interpretive semantic cues substantially mitigated the negative bias.

Conclusions:

The negative bias towards AI-generated art is primarily a phenomenon of controlled, rather than automatic, cognitive processing.
Facilitating meaning construction through semantic cues can reduce prejudice against AI-generated art.
Findings contribute to understanding aesthetic appreciation in the context of AI.