Data Feminism


Join the Online Ethics Center for its first Fall event in the Bringing Ethics to the Conversation series, scheduled for September 10, 2021 at 12 p.m. Eastern. This webinar, titled "Data Feminism," will feature Dr. Lauren Klein, Associate Professor in the departments of English and Quantitative Theory & Methods at Emory University. Dr. Klein directs the Digital Humanities Lab and 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, 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.

Dr. Klein will be joined by Dr. Michele Claibourn, a political scientist and statistician at the University of Virginia’s Frank Batten School of Leadership and Public Policy. The webinar will be hosted by Dr. Caitlin Wylie, Assistant Professor of Science, Technology, and Society at the University of Virginia’s School of Engineering and Applied Sciences.

About the webinar

As data are increasingly mobilized in the service of governments and corporations, their unequal conditions of production, asymmetrical methods of application, and unequal effects on both individuals and groups have become increasingly difficult for data scientists––and others who rely on data in their work––to ignore. But it is precisely this power that makes it worth asking: “Data science by whom? Data science for whom? Data science, with whose interests in mind?”

These are some questions that emerge from what D’Ignazio and Klein call data feminism: a way of thinking about data science and its communication that is informed by the past several decades of intersectional feminist activism and critical thought. This talk will draw on insights from their collaboratively crafted book about how challenges to the male/female binary can challenge other hierarchical (and empirically wrong) classification systems; how an understanding of emotion can expand our ideas about effective data visualization; and how the concept of “invisible labor” can expose the significant human efforts required by our automated systems. Together, they show how feminist thinking can be operationalized into more ethical and equitable data practices.

Watch the replay

This webinar is brought to you in partnership with UVA's School of Data Science.

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Lauren Klein photo