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Data Feminism
Authors Catherine D'Ignazio and Lauren Klein of 'Data Feminism' (2020, MIT Press) discuss their work charting a course for more ethical and empowering data science practices.

As data are increasingly mobilized in the service of governments and corporations, their unequal conditions of production, their asymmetrical methods of application, and their 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 of the questions that emerge from what we 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. Illustrating data feminism in action, this talk will show how challenges to the male/female binary can help to challenge other hierarchical (and empirically wrong) classification systems; it will explain how an understanding of emotion can expand our ideas about effective data visualization; how the concept of invisible labor can expose the significant human efforts required by our automated systems; and why the data never, ever “speak for themselves.”

The goal of this talk, as with the project of data feminism, is to model how scholarship can be transformed into action: how feminist thinking can be operationalized in order to imagine more ethical and equitable data practices.

This webinar is hosted by the UC Davis DataLab: Data Science and Informatics to explore the relationships between science, society, and technology. For more information about DataLab and how to get involved, see: https://datalab.ucdavis.edu.

May 12, 2021 10:00 AM in Pacific Time (US and Canada)

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Speakers

Catherine D'Ignazio
Assistant Professor, Urban Science and Planning @MIT
Catherine D’Ignazio is a scholar, artist/designer and hacker mama who focuses on feminist technology, data literacy and civic engagement. Director of the Data + Feminism Lab at MIT, she uses data and computational methods to work towards gender and racial equity, particularly in relation to space and place. She has run reproductive justice hackathons, designed global news recommendation systems, created talking and tweeting water quality sculptures, and led walking data visualizations to envision the future of sea level rise. With Rahul Bhargava, she built the platform Databasic.io, a suite of tools and activities to introduce newcomers to data science. Her research at the intersection of technology, design & social justice has been published in the Journal of Peer Production, the Journal of Community Informatics, and the proceedings of Human Factors in Computing Systems (ACM SIGCHI).
Lauren Klein
Associate Professor, English and Quantitative Theory and Methods @Emory University
Lauren Klein directs the Digital Humanities Lab. Before moving to Emory, she taught in the School of Literature, Media, and Communication at Georgia Tech. Klein works at the intersection of digital humanities, data science, and early American literature, with a research focus on issues of gender and race. She has designed platforms for exploring the contents of historical newspapers, modeled the invisible labor of women abolitionists, and recreated forgotten visualization schemes with fabric and addressable LEDs. In 2017, she was named one of the “rising stars in digital humanities” by Inside Higher Ed. 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, 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.
Emily Merchant and Lindsay Poirier
Assistant Professors, Science and Technology Studies @UC Davis
Q&A will be hosted by Emily Merchant and Lindsay Poirier.