What is data feminism? And how can feminism inform the power of data in the 21st century?

In recent years, a growing body of initiatives corporate and government bodies accountable for making racist, sexist, or classist data products. These include hiring algorithms that demote applicants that went to all women schools, facial recognition algorithms that make racist judgments, data visualizations that reinforce the gender binary, and many other systems. 

Speaking today at CAT Lab is Catherine D’Ignazio, a hacker mama, scholar, and artist/designer who focuses on feminist technology, data literacy and civic engagement. She has run women’s health hackathons, designed global news recommendation systems, created water quality sculptures that talk and tweet,, and led walking data visualizations to envision the future of sea level rise. Her new book from MIT Press, Data Feminism, co-authored with Lauren F. Klein, charts a course for more ethical and empowering data science practices. D’Ignazio is an assistant professor of Urban Science and Planning in the Department of Urban Studies and Planning at MIT where she is the Director of the Data + Feminism Lab.

“Data is the same old oppression”

Many people say that “Data is the new oil.” Many people think of this in a positive way as something to extract, mine, and convert into profit. But profit for whom? Catherine argues that “Data is the same old oppression,” an idea advanced by many advocates including women of color, white women, indigenous communities, and LGBT groups. 

What kind of feminism are Catherine and Lauren mobilizing in this book? Feminism is the belief that all genders should have equal rights. When you look around, you will see that these rights are being ignored. Feminism is also organized activity toward these interests. It’s also a brilliant intellectual heritage from all areas of knowledge on topics related to inequality. 

Catherine tells us that feminism in 2020 is intersectional, not just about women and gender—it’s about power, who has it and who doesn’t. We can’t study gender independently from race, class, able-ism, and other intersecting injustices.

In today’s world, data is power, Catherine tells us. Intersectional feminism, when applied to data science, can challenge that power and help create change. In fact, it needs feminism in order to create that change. To define data feminism, they drew from quantitative social sciences, design, arts, the humanities, and other fields to develop seven principles of data feminism. Their goal was to identify people who are already doing this work even if they don’t consider themselves to be data feminists. They were also inspired to write the book for people who are newcomers to feminism, data science, or both.

Catherine was inspired by Mimi Onuoha’s art project collecting “missing datasets.” These are datasets that don’t exist, and illustrate dynamics of power underlying the reasons for their absence. 

Feminism is ultimately about power. Catherine dells us the story of NiUnaMenos, a Mexican movement that campaigns against gender based violence. In Mexico, there is no comprehensive dataset on this topic. So this movement has collected counter-data in the face of this missing data. While more data doesn’t always lead to change, it’s a valuable strategy for countering power.

Another key contribution of feminist theory is to dismantle false binaries. According to theorists of gender, behind any binary there is always a hierarchy. There are other false binaries, such as between reason and emotion—which can also be gendered. Emotion, says Catherine, has often been exiled from data visualization (which values minimalism). Catherine works toward bringing embodiment, lived experience, and emotion back into data visualization.

Header photo credit: Diana Levine