Data Feminism: what does feminist data science look like?

Contributor(s): Professor Catherine D'Ignazio, Professor Lauren F Klein | Catherine D'Ignazio (@kanarinka) is an Assistant Professor of Urban Science and Planning at MIT. She is also Director of the Data + Feminism Lab, which uses data and computational methods to work towards gender and racial equity. Catherine is a scholar, artist/designer and hacker mama who focuses on feminist technology, data literacy and civic engagement. Her 2020 book, Data Feminism, co-authored with Lauren F Klein, charts a course for more ethical and empowering data science practices. Lauren Klein (@laurenfklein) is an Associate Professor in the departments of English and Quantitative Theory and Methods at Emory University. She works at the intersection of digital humanities, data science, and early American literature, with a research focus on issues of gender and race. Lauren is the author of An Archive of Taste: Race and Eating in the Early United States and, with Catherine D’Ignazio, Data Feminism. Fiona Steele is a Professor and Head of Department at LSE's Department of Statistics. Her research interests are in developments of statistical methods that are motivated by social science problems. Fiona was awarded the Royal Statistical Society Guy Medal in Bronze in 2008 and elected a Fellow of the British Academy in 2009.