Data Feminism

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MIT Press, Mar 17, 2020 - Social Science - 328 pages
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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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User Review  - JBD1 - LibraryThing

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

Contents

Why Data Science Needs Feminism
1
The Power Chapter
21
Collect Analyze Imagine Teach
49
On Rational Scientific Objective Viewpoints from Mythical Imaginary Impossible Standpoints
73
What Gets Counted Counts
97
Unicorns Janitors Ninjas Wizards and Rock Stars
125
The Numbers Dont Speak for Themselves
149
Show Your Work
173
Our Values and Our Metrics for Holding Ourselves Accountable
215
Auditing Data Feminism by Isabel Carter
223
Acknowledgment of Community Organizations
225
Figure Credits
227
Notes
235
Name Index
303
Subject Index
307
Copyright

Now Lets Multiply
203

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About the author (2020)

Catherine D'Ignazio is Assistant Professor of Urban Science and Planning in the Department of Urban Studies and Planning at MIT.

Lauren F. Klein is Associate Professor of English and Quantitative Theory and Methods at Emory University.

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