AI in the Art History Classroom

Artificial Intelligence is reshaping how we research, analyse, and teach art history. As generative models, image synthesis tools, and data-driven analytics become increasingly embedded in educational practice, their use in disciplines traditionally grounded in human creativity, critical interpretation, and visual literacy raises both exciting opportunities and serious concerns. This panel explores the pedagogical and ethical implications of integrating AI technologies into art history instruction.

We invite papers that critically engage with the impact of AI tools—such as DALL·E 2, Midjourney, Stable Diffusion— on teaching and learning. Can AI foster creativity, enhance critical and analytical skills, or support student engagement? How do we responsibly address the risks of bias, plagiarism, misinformation (“hallucinations”), and the unauthorized use of authors’ and artists’ work in training datasets? How should we assess student work when AI-generated content may be indistinguishable from human-authored assignments?

This session aims to facilitate dialogue around best practices for integrating AI into the classroom. We welcome submissions exploring any aspect of AI’s impact on art history education, including but not limited to:

Using virtual and augmented reality to deliver experiential art history instruction.
Equipping students with the skills to critically evaluate and interpret AI-generated content.
Partnering with museums to develop AI-powered digital exhibitions and educational tools.
Designing coursework that incorporates AI tools to support creativity and critical thinking.
Developing assessment strategies that prepare students for careers in AI-influenced professional contexts.
Ensuring that AI-enhanced learning remains inclusive, accessible, and sensitive to diverse student needs.

Submit your Paper via this form. Please download, complete and send it directly to the Session Convenor(s) below by Sunday 2 November 2025:

Lenia Kouneni, University of St Andrews, gk8@st-andrews.ac.uk

Natalia Sassu Suarez Ferri, University of St Andrews, nessf@st-andrews.ac.uk