“To Make Visible the Structures”: Challenging the Canon, Digital and Beyond, with Niall Atkinson and Min Kyung Lee

In the Foreground: Conversations on Art & Writing

In this episode, guest interviewer Anne Helmreich (Getty Foundation) speaks with Niall Atkinson, associate professor of art history at the University of Chicago, and Min Kyung Lee, assistant professor of Growth and Structure of Cities at Bryn Mawr College, to reflect on the canon of art history. They discuss how the canon as a narrative offers a shared framework for discussion, analysis, and exchange, but problems arise when the canon becomes fixed or an imposition. Niall and Min describe how they approach using archives in more varied ways, to capture “different voices,” and they revel in the collaborative nature of computational practices, the scale of which – both zooming out and zooming in – demands that scholars work across disciplines and as a team. Finally, both emphasize the importance of being aware of how we define the data we use, and how we in fact produce the data we use – a reflexive approach that may allow us to confront and correct implicit biases, building a more inclusive and heterogeneous approach to data and "the canon.”
This fourth season of In the Foreground is a special series of five roundtable conversations dedicated to “the Grand Challenges” – a phrase frequently adopted in the sciences to refer to the great unanswered questions that represent promising frontiers – of bringing together digital and computational methods and the social history of art. This series grows out of a colloquium on this topic convened by Anne Helmreich (Associate Director of the Getty Foundation) and Paul B. Jaskot (Professor of Art History at Duke University) at the Clark’s Research and Academic Program in April 2019. Anne and Paul serve as the guest interviewers for this podcast series, for which they have invited back colloquium participants to reflect further on how digital art history might help us explore social history of art’s future, and which digital methods might be effective at analyzing large scale structural issues and modes of visual expression.