Catherine D’Ignazio, “Data Feminism”
February 16, 2020 @ 5:00 pm - 6:30 pm
Building E15 - 318
As data are increasingly mobilized in the service of global corporations, governments, and elite institutions, their unequal conditions of production, their inequitable impacts, and their asymmetrical silences become increasingly more apparent. It is precisely this power that makes it worth asking: “Data science by whom? For whom? In whose interest? Informed by whose values?” And most importantly, “How do we begin to imagine alternatives for data’s collection, analysis, and communication?”
These are some of the questions that emerge from what Lauren Klein and Catherine D’Ignazio call Data Feminism (MIT Press 2020). Data feminism is a way of thinking about data science and its products that is informed by the past several decades of intersectional feminist activism and critical thought, emerging anti-oppression design frameworks, and scholarship from the fields of Critical Data Studies, Science & Technology Studies, Geography/GIS, Digital Humanities and Human Computer Interaction. An intersectional feminist lens prompts questions about how, for instance, challenges to the male/female binary can also help challenge other binary (and empirically wrong) classification systems. It encourages us to ask how the concept of invisible labor can help to expose the gendered, racialized, and colonial forms of labor associated with data work. And it demonstrates why the data never, ever, speak for themselves.