Data Feminism for AI

In Data Feminism (MIT Press, 2020), Klein and her coauthor Catherine D'Ignazio established a set of principles for doing more just and equitable data science. Informed by the past several decades of intersectional feminist activism and critical thought, the principles of data feminism modeled how to examine and challenge power, rethink binaries and hierarchies, elevate emotion and embodiment, consider context, embrace pluralism, and make labor visible. How can these principles be applied to the current conversation about AI, its present harms, and its future possibilities? This talk will briefly summarize the principles of data feminism before moving to a set of examples that show how these principles can be applied–and extended–in our current technological landscape.

About Lauren Klein

Lauren Klein is Winship Distinguished Research Professor and Associate Professor in the departments of Quantitative Theory & Methods and English at Emory University. At Emory, she also serves as director of the Digital Humanities Lab and PI of the Mellon-funded Atlanta Interdisciplinary AI Network. Previously, she taught in the School of Literature, Media, and Communication at Georgia Tech. Klein’s research brings together computational and critical methods in order to explore questions of gender, race, and justice, both in the past and in the present. She is the author of An Archive of Taste: Race and Eating in the Early United States (University of Minnesota Press, 2020) and, with Catherine D’Ignazio, the award-winning Data Feminism (MIT Press, 2020). With Matthew K. Gold, she edits Debates in the Digital Humanities, a hybrid print-digital publication stream that explores debates in the field as they emerge. Her work has appeared in leading humanities journals including PMLA, American Literature, and American Quarterly; and at technical conferences including ACL, EMNLP, and IEEE VIS. Her research has been supported by grants and fellowships from the ACLS, the NEH, and the Mellon Foundation. Her next major project, Data by Design: An Interactive History of Data Visualization, is forthcoming from the MIT Press in 2024.

This talk is jointly hosted by the Center for Spatial and Textual Analysis (CESTA), and Stanford Data Science, and co-sponsored by the Stanford University Human-Centered Artificial Intelligence (HAI), The Clayman Institute for Gender Research, and the Stanford Humanities Center.