Data Feminism

Written by Catherine D'Ignazio and Lauren F. Klein

Narrated by Teri Schnaubelt

Today, data science is a form of power. It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, makes it essential to ask: Data science by whom? Data science for whom? Data science with whose interests in mind? The narratives around big data and data science are overwhelmingly white, male, and techno-heroic. In Data Feminism, Catherine D'Ignazio and Lauren Klein present a new way of thinking about data science and data ethics—one that is informed by intersectional feminist thought.



Illustrating data feminism in action, D'Ignazio and Klein show how challenges to the male/female binary can help challenge other hierarchical (and empirically wrong) classification systems. They explain how, for example, an understanding of emotion can expand our ideas about effective data visualization, and how the concept of invisible labor can expose the significant human efforts required by our automated systems. And they show why the data never, ever "speak for themselves."




Data Feminism offers strategies for data scientists seeking to learn how feminism can help them work toward justice, and for feminists who want to focus their efforts on the growing field of data science.

• Language: English
• Publisher: Tantor Media, Inc
• Release date: Sep 23, 2020
• ISBN: 9781705264003

Reviews for Data Feminism

[freeknowledgenow · Rating: 5 out of 5 stars]

Great book! Very informative and accesible even for people, such as myself, who don't work in this field.

[Atticus Foster · Rating: 5 out of 5 stars]

Absolutely mind blowing to me. This book takes my, presumably commonplace, understanding of data science as an apolitical and objective subject, and destroys it. Even as someone who already leans into feminist theory, I'd never thought to consider that the very data our society is based on may be inherently flawed due to a societal obsession with seeming neutral. I now understand that data is always political and dependant on context, and that we can present it in not only more accurate, but more visceral ways. Even if you're not sure you agree with feminist theory, I highly recommend you give this book a chance, I think you'll come out with a new perspective.

[Albany Lucas · Rating: 5 out of 5 stars]

I really appreciate the efforts the authors took to not only consult with minoritised communities in the preparation of this book but how they brought their voices to the forefront. The honesty and humility shown by the authors is admirable and inspiring. Excellent narration too!

[jbd1 · Rating: 5 out of 5 stars]

A beautifully designed and very clearly and excellently written manifesto on data presentation. Highly recommended for all.