The Art That Poses Back: Assessing AI Pastiches after Contemporary Artworks

TL;DR

This paper evaluates AI-generated pastiches of contemporary artworks through human and computational assessments, revealing significant stylistic gaps and limitations in AI's ability to replicate artistic depth and intent.

Contribution

It introduces a multi-metric style transfer dashboard for better evaluation of AI art pastiches and highlights the perceptual and conceptual gaps in AI-generated artworks.

Findings

Significant stylistic differences between original and AI-generated works.

Limitations of AI in capturing depth, context, and emotion in art.

Proposed multi-metric evaluation approach improves assessment accuracy.

Abstract

This study explores artificial visual creativity, focusing on ChatGPT's ability to generate new images intentionally pastiching original artworks such as paintings, drawings, sculptures and installations. The process involved twelve artists from Romania, Bulgaria, France, Austria, and the United Kingdom, each invited to contribute with three of their artworks and to grade and comment on the AI-generated versions. The analysis combines human evaluation with computational methods aimed at detecting visual and stylistic similarities or divergences between the original works and their AI-produced renditions. The results point to a significant gap between color and texture-based similarity and compositional, conceptual, and perceptual one. Consequently, we advocate for the use of a "style transfer dashboard" of complementary metrics to evaluate the similarity between pastiches and originals, rather than using a single style metric. The artists' comments revealed limitations of ChatGPT's pastiches after contemporary artworks, which were perceived by the authors of the originals as lacking dimensionality, context, and intentional sense, and seeming more of a paraphrase or an approximate quotation rather than as a valuable, emotion-evoking artwork.