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AI-driven methodologies can transform the study of digital images. Focusing on the Lyon16ci project, which catalogs over 10,000 printed illustrations from Lyon (1480–1600), the paper explores the potential of utilizing automatic image recognition softwares, such as the Imagematching (VGG, Oxford), to detect varying degrees of visual similarity across large iconographic corpora.
By integrating these tools with established iconographic indexing systems like the Warburg Institute Iconographic Database and ICONCLASS, the paper will discuss the opportunities and limitations of utilizing softwares based on AI models for art historical research, also presenting the challenges related to long term sustainability of these digital projects. The new digital art historical approach developed during projects such as "The Illustrated Book in Lyon" (CNRS, Equipex Biblissima) testify to the new possibilities for the analysis of visual material, not only facilitating large-scale iconographic analysis but also encouraging a critical reflection on the methodological, ethical, and epistemological implications of employing AI in art history.