9780262044004-0262044005-Data Feminism (Strong Ideas)

Data Feminism (Strong Ideas)

ISBN-13: 9780262044004
ISBN-10: 0262044005
Author: Catherine DIgnazio, Lauren F. Klein
Publication date: 2020
Publisher: The MIT Press
Format: Hardcover 328 pages
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ISBN-13: 9780262044004
ISBN-10: 0262044005
Author: Catherine DIgnazio, Lauren F. Klein
Publication date: 2020
Publisher: The MIT Press
Format: Hardcover 328 pages

Summary

Data Feminism (Strong Ideas) (ISBN-13: 9780262044004 and ISBN-10: 0262044005), written by authors Catherine DIgnazio, Lauren F. Klein, was published by The MIT Press in 2020. With an overall rating of 3.7 stars, it's a notable title among other Data Processing (Databases & Big Data, History & Culture, Engineering, Social Aspects, Technology, Feminist Theory, Women's Studies) books. You can easily purchase or rent Data Feminism (Strong Ideas) (Hardcover) from BooksRun, along with many other new and used Data Processing books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $3.83.

Description

A new way of thinking about data science and data ethics that is informed by the ideas of intersectional feminism.

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. But Data Feminism is about much more than gender. It is about power, about who has it and who doesn't, and about how those differentials of power can be challenged and changed.

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