Data Feminism

Welcome back, for another episode of the “22 Lessons on Ethics and Technology” series. In this episode, I speak with Dr. Lauren Klein about the complicated relationship between data, race, and gender, and what she calls “data feminism.” What is the relationship between data visualizations, representation, and construction of categories—and difference? How have visualizations constructed race and gender? And how can a feminist data science approach help in constructing a more just and equal world?

Dr. Lauren Klein is an associate professor in the Departments of English and Quantitative Theory & Methods at Emory University. She received her A.B. from Harvard University and her Ph.D. from the Graduate Center of the City University of New York (CUNY). Her research interests include digital humanities, data science, data studies, and early American literature. Before arriving at Emory, Klein taught in the School of Literature, Media, and Communication at Georgia Tech where she directed the Digital Humanities Lab.

She is currently at work on two major projects: the first, Data by Design, is an interactive book on the history of data visualization. Awarded an NEH-Mellon Fellowship for Digital Publication, Data by Design emphasizes how the modern visualizing impulse emerged from a set of complex intellectually and politically-charged contexts in the United States and across the Atlantic.

Her second project, tentatively titled Vectors of Freedom, employs a range of quantitative methods in order to surface the otherwise invisible forms of labor, agency, and action involved in the abolitionist movement of the nineteenth-century United States.

Dr. Klein is the author of An Archive of Taste: Race and Eating in the Early United States (University of Minnesota Press, 2020). This book shows how thinking about eating can help to tell new stories about the range of people, from the nation’s first presidents to their enslaved chefs, who worked to establish a cultural foundation for the United States. Klein is also the co-author (with Catherine D’Ignazio) of Data Feminism (MIT Press, 2020), a trade book that explores the intersection of feminist thinking and data science. With Matthew K. Gold, she edits Debates in the Digital Humanities (University of Minnesota Press), a hybrid print/digital publication stream that explores debates in the field as they emerge. The most recent book in this series is Debates in the Digital Humanities 2019.