Comparative Designs Reveal Preferences for Human-Generated Rather Than AI-Generated art

Oliver Jacobs*, Farid Pazhoohi, Grayson Mullen, Alan Kingstone

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

The evaluation of AI-generated art has seen increased interest after widespread access to AI-generated art (e.g., DALL-E or Stable Diffusion). While previous studies have suggested that there are preferences for human-generated art, the research remains far from robust with numerous contradictory findings. One potential reason for this discrepancy is differing experimental designs employing comparative or non-comparative methods. To shed light on this problem, two experiments were conducted: one using a Likert scale (N = 250) and another using a 2-alternative forced choice design (N = 102). Our conflicting results between the two designs suggest that traditional Likert-based art appraisals in non-comparative formats may not be sensitive enough to reliably detect preferences that a forced-choice task can reveal. While AI-generated art continues to become more mainstream, people tend to prefer human art in terms of their liking and valuation appraisals when measured in comparative designs that better approximate real-world interaction with art.

Original languageEnglish
Article number02762374251360129
JournalEmpirical Studies of the Arts
DOIs
Publication statusPublished - 28 Jul 2025

ASJC Scopus subject areas

  • Visual Arts and Performing Arts
  • Music
  • Literature and Literary Theory

Keywords

  • art perception
  • artificial intelligence
  • forced-choice design

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