Dr Kathryn Brown, Reader in Art Histories, Markets, and Digital Heritage at Loughborough University joins us at the CDH Open.

Speaker

Dr Kathryn Brown, Reader in Art Histories, Markets, and Digital Heritage at Loughborough University (https://www.lboro.ac.uk/subjects/communication-media/staff/kathryn-brown/)

Kathryn Brown is Reader in Art Histories, Markets, and Digital Heritage at Loughborough University. Her books include Women Readers in French Painting 1870–1890 (2012), Matisse’s Poets (2017), ed. Digital Humanities and Art History (2020), Henri Matisse (2021), Dialogues with Degas (2023), and Art Auctions: Spectacle and Value in the 21st Century (2024). Her most recent work focuses on intersections between AI, art history and museum culture. She is the PI on the AHRC project Designing a Museum of AI Cultures and recently edited Artificial Intelligence and Art History: Looking at Images in an Algorithmic Culture (2026) for The Proceedings of the British Academy. Brown has held fellowships at the Center for Advanced Studies in the Visual Arts (Washington DC), the Beinecke Rare Book and Manuscript Library (Yale University), the Humanities Research Centre of the Australian National University, and the Getty Research Institute. She is the founder and series editor of Contextualizing Art Markets for Bloomsbury Academic.

Abstract

Advances in computer vision, machine learning, and deep learning have informed new methodologies in the humanities for over a decade, but the uptake of AI models for visual analysis in art history has been piecemeal, and recent discourses have been dominated by computer scientists. This presentation explores some of the tensions, challenges, and possibilities that are emerging at this disciplinary nexus. Specifically, the presentation considers how to create and implement computational tools that preserve the insights of historically and theoretically informed art history. How might researchers mediate between computational data and humanistic reasoning? What kinds of conceptual framing are required to ensure the interpretative value of quantitative outputs? Various examples of AI-assisted interpretation are explored and considered in relation to human, curiosity-led observation. Can art history can preserve the methodological plurality of the discipline while also facilitating innovations in AI?

Access

Events are free and open to all unless otherwise stated. The seminar will take place from 5-6pm and is followed by a drinks reception in the English Social Space from 6-7pm.

If you have specific accessibility needs for this event please get in touch. We will do our best to accommodate any requests: https://www.cdh.cam.ac.uk/events/41856/

Description supplied by the event organiser.