Data Feminism

Hardcover, 328 pages

English language

Published April 16, 2020 by MIT Press.

ISBN:
9780262044004

View on OpenLibrary

4 stars (2 reviews)

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 …

3 editions

Important and interesting book

4 stars

This book was very interesting. The authors formulate seven principles for how to do data science without perpetuating or intensifying oppression. It is full of positive examples and stories. It is fun to read, although the format was not very comfortable; it's very large... But I guess it has to be, because it is filled with so much interesting stuff. A very interesting aspect: The authors are really living what they preach: In the end of the book, there is a chapter about their standards and their aspirations for the book; they even included a table about which -isms they wanted to address and how well they managed.

I would recommend it to everyone interested in data science and its public impact.

Subjects

  • Feminism
  • Big data
  • Power (social sciences)
  • Social science
  • Data science
  • Computers