Liberating Information: Exploring Computational Methods to Study Histories of Information, from Decolonization to Digital Humanities Modeling Culture Talk

As debates intensify over regulating AI and big tech, scholars are confronting whether we can use these technologies to address rather than reify inequities. This talk presents two projects exploring how computational methods can help us understand past and present struggles to make information more just. The first uses LLMs and metadata analysis to study in-copyright Third World periodicals, tracing decolonization-era efforts to challenge Western information order; the second analyzes global digital humanities communities on GitHub, examining how coding practices, documentation labor, and platform constraints shape scholarly work. Together, these projects show how AI can surface marginalized histories and invisible practices, even as they reveal that when we talk about “foundation models,” we must attend to the foundations being built through our own research practices and infrastructures.

Zoë LeBlanc is an Assistant Professor in the School of Information Sciences at the University of Illinois Urbana–Champaign. Her research sits at the intersection of the histories of information, digital humanities, and critical data studies, combining archival research with computational methods to study large-scale cultural and informational systems in the past and to develop new research methods in the present.

LeBlanc’s current projects include research on Third World information institutions and periodicals during the Cold War, including work on the New World Information and Communication Order. She is also the principal investigator of the Coding DH project, which examines how programming practices circulate globally through platforms such as GitHub. She is co-authoring, with Meredith Martin, the forthcoming book Data Work in the Humanities, which traces how data creation, curation, and maintenance have become core scholarly practices in the humanities. Her collaborative work includes projects with Rebecca Koeser on missingness and recommendation systems in Shakespeare and Company, and with John Ladd on Network Navigator, a lightweight network analysis tool designed for humanists. At Illinois, LeBlanc teaches courses on digital humanities, cultural analytics, and data-driven approaches to studying culture at scale.

Modeling Culture is generously funded by an AI Lab Seed grant, with additional support from the Humanities Council and the Princeton Humanities Initiative. Thank you to the Department of English for co-sponsorship of the public talks.