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Cited by 233Aesthetic Perception and AnalysisArt, Technology, and CultureDigital Media and Visual Art

The DOI matches its Crossref record; 82 of the 83 references it cites were found in a registry or an index.

Humans versus AI: whether and why we prefer human-created compared to AI-created artwork

Open access
Bellaiche, Lucas, Shahi, Rohin, Turpin, Martin Harry, Ragnhildstveit, Anya, Sprockett, Shawn, Barr, Nathaniel, Christensen, Alexander, Seli, Paul·2023·Cognitive Research: Principles and Implications
DOI 10.1186/s41235-023-00499-6PMC PMC10319694
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Abstract

With the recent proliferation of advanced artificial intelligence (AI) models capable of mimicking human artworks, AI creations might soon replace products of human creativity, although skeptics argue that this outcome is unlikely. One possible reason this may be unlikely is that, independent of the physical properties of art, we place great value on the imbuement of the human experience in art. An interesting question, then, is whether and why people might prefer human-compared to AI-created artworks. To explore these questions, we manipulated the purported creator of pieces of art by randomly assigning a “Human-created” or “AI-created” label to paintings actually created by AI, and then assessed participants’ judgements of the artworks across four rating criteria (Liking, Beauty, Profundity, and Worth). Study 1 found increased positive judgements for human- compared to AI-labelled art across all criteria. Study 2 aimed to replicate and extend Study 1 with additional ratings (Emotion, Story, Meaningful, Effort, and Time to create) intended to elucidate why people more-positively appraise Human-labelled artworks. The main findings from Study 1 were replicated, with narrativity (Story) and perceived effort behind artworks (Effort) moderating the label effects (“Human-created” vs. “AI-created”), but only for the sensory-level judgements (Liking, Beauty). Positive personal attitudes toward AI moderated label effects for more-communicative judgements (Profundity, Worth). These studies demonstrate that people tend to be negatively biased against AI-created artworks relative to purportedly human-created artwork, and suggest that knowledge of human engagement in the artistic process contributes positively to appraisals of art.

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Fig. 1 Sample images (representational and abstract, respectively) taken from Artbreeder. See https://osf.io/cgw8v/ for all stimuli
Fig. 1 Sample images (representational and abstract, respectively) taken from Artbreeder. See https://osf.io/cgw8v/ for all stimuliCC BY · PubMed Central
Fig. 2 Distribution of values on artworks associated with AI and Human for each criterion (Liking, Beauty, Profundity, Worth). Error bars represent standard error of the mean. Following multiple-comparison corrections, *p < 0.05, **p < 0.01, ***p < 0.001
Fig. 2 Distribution of values on artworks associated with AI and Human for each criterion (Liking, Beauty, Profundity, Worth). Error bars represent standard error of the mean. Following multiple-comparison corrections, *p < 0.05, **p < 0.01, ***p < 0.001CC BY · PubMed Central
Fig. 3 Interaction plots showing moderations by Effort and Story on Liking and Beauty, two sensory-level criteria. Confidence bands represent the 95% confidence interval
Fig. 3 Interaction plots showing moderations by Effort and Story on Liking and Beauty, two sensory-level criteria. Confidence bands represent the 95% confidence intervalCC BY · PubMed Central
Fig. 4 Interaction plot of Positive AI attitudes on communicative judgements of Profundity and Worth. Confidence bands represent the 95% confidence interval
Fig. 4 Interaction plot of Positive AI attitudes on communicative judgements of Profundity and Worth. Confidence bands represent the 95% confidence intervalCC BY · PubMed Central

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Research works printed but not linked: 1

  1. Moffat, D., & Kelly, M. G. (2006). An investigation into people’s bias against computational creativity in music composition. Assessment, 13(11), 1–8.

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Metadata

Authors
Bellaiche, L., Shahi, R., Turpin, M. H., Ragnhildstveit, A., Sprockett, S., Barr, N., Christensen, A., & Seli, P.
Affiliations
  • Duke University (US)
  • University of Waterloo (CA)
  • University of Cambridge (GB)
  • California College of the Arts (US)
  • Sheridan College (US)
  • Vanderbilt University (US)
Corresponding author
Bellaiche, Lucas
ORCID
Venue
Cognitive Research: Principles and Implications
Publisher
Springer Science and Business Media LLC
Published
2023-07-04
Volume
8
Issue
1
Pages
42-42
ISSN
2365-7464 (ISSN-L)
DOI
10.1186/s41235-023-00499-6
PMC
PMC10319694
OpenAlex
W4383058345
Cited by
233
References
83
Citations by year
2026: 82 · 2025: 98 · 2024: 48 · 2023: 4
FWCI
34.66
Type
journal article
Language
en
Open access
Licence
Locations
  • Cognitive Research Principles and Implications (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Apollo (University of Cambridge) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • SOURCE Sheridan's Institutional Repository (Sheridan College) (submittedVersion, cc-by)
Funders
National Science Foundation
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Aesthetic Perception and Analysis
  • Social Sciences › Arts and Humanities › Visual Arts and Performing Arts › Art, Technology, and Culture
  • Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Digital Media and Visual Art
Keywords
AI-generated art, art evaluation, aesthetic judgment, narrativity, perceived effort, attitudes toward AI
MeSH terms
Artificial Intelligence, Beauty, Emotions, Humans, Judgment, Paintings

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