Book

Data Feminism

Catherine D'Ignazio and Lauren F. Klein

MIT Press, 2020

Buy book or audiobook

Read or listen offline

Amazon Kindle

1×

Editorial Rating

Qualities

Analytical
Eye Opening
Concrete Examples

Recommendation

What gets left out of datasets can be interesting and as telling as what gets left in. Catherine D’Ignazio and Lauren F. Klein ask: Who decides? They illustrate their “seven principles of data feminism” through campaigns and creative projects. Though aimed at data scientists, “data visualizers” and anyone relying on data to make their arguments – which means everyone – will find much to ponder. Considering the source has never mattered more.

Summary

Feminism holds that the sexes should be equal politically, socially and economically. Data now informs feminist activism.

Feminists strive for “co-liberation:” Nobody is free until everybody is free. They use data to show how systems of oppression harm everyone.

“Intersectionality” describes the intersection of marginalized identities – for example, the inequalities Black women face are not only racially based, but also gender based. The term explores how oppression and privilege intersect to maintain systemic discrimination. Racism, sexism, homophobia, ableism and classism form systemic oppression.

Oppression so embeds in everyday life – and datasets – that people aren’t aware of it.

Sociologist Patricia Hill Collins explains the “matrix of domination” as four “domains.” The “structural domain”– one of the four domains –“codifies oppression,” for example, in laws and through the institutions that uphold them. Originally, states defined voters as property owners. Only men could own property, so only men could vote. Congress redefined voting as a right of “male citizens.” In 1920, most women gained suffrage, but states imposed barriers...

About the Authors

Catherine D’Ignazio teaches Urban Science and Planning at MIT. Co-author Lauren F. Klein teaches Quantitative Theory and Methods at Emory University.

Comment on this summary

More on this topic

In our Journal

1 year ago

Journal Article

Building a More Equitable Future

Applying the lessons of history to chart the future of technology Digital transformation affects every area of life and work, yet technological progress has not been equitable or inclusive, as a Microsoft map of areas in the US without access to broadband internet service vividly illustrates. Contrary to popular belief, technologies are not inherently neutral. […]

3 years ago

Journal Article

Robots Need Bias Awareness Training, Too

Despite their veneer of objectivity, algorithms are as biased as the humans creating them. It’s piñata time! Imagine you’ve invited a bunch of kids to your daughter’s birthday party. You find yourself at a loss watching them squabble over who gets to take the first swing at the papier-mâché lama filled with candy. To prove […]

3 years ago

Journal Article

Women in Tech Make Their Own Luck

Silicon Valley has a gender problem. These women aren’t waiting. Stereotypical conventional wisdom deems science, technology, engineering and math (STEM) are fields too brainy for women, and sexism in Silicon Valley is well-documented. But that doesn’t keep women from embarking on tech careers and succeeding spectacularly. Despite Challenges, Tech Has Its Share of Women Mavericks […]