Catherine D’Ignazio and Lauren F. Klein present at DDI

What does feminist data science look like?

What is feminist data science? How is feminist thinking being incorporated into data-driven work? And how are scholars in the humanities and social sciences, in particular, bringing together data science and feminist theory in their research? Drawing from our recent book, Data Feminism (MIT Press, 2020), we will present a set of principles for doing data science that are informed by the past several decades of intersectional feminist activism and critical thought. In order to illustrate these principles, as well as some of the ways that scholars and designers have begun to put them into action, we will discuss a range of recent research projects including several of our own: 1) A participatory design project about feminicide that uses machine learning to reduce the labor of feminist data activists 2) a thematic analysis of a large corpus of nineteenth-century newspapers that reveals the invisible labor of women newspaper editors; and 3) the development of a model of lexical semantic change that, when combined with network analysis, tells a new story about Black activism in the nineteenth-century United States. Taken together, these examples demonstrate how feminist thinking can be operationalized into more ethical, more intentional, and more capacious data practices, in the digital humanities, computational social science, human-computer interaction and beyond.

Catherine D’Ignazio is Assistant Professor of Urban Science and Planning in the Department of Urban Studies and Planning at MIT.

Lauren F. Klein is Associate Professor of English and Quantitative Theory and Methods at Emory University.