Data Feminism by Catherine D’Ignazio and Lauren F. Klein
From the Publisher:
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.
From Lin and Anita:
This group built off of the excitement at D’Ignazio’s LACOL summer keynote about her timely 2020 book, which uses an intersectional feminism lens to explore how and why data is collected, used, and visualized (or is missing). Many faculty, especially in the natural and social sciences, use data in their own research and increasingly in their teaching, and were interested in both the theoretical discussions this book sparks and the many concrete examples they can use in their own classes. With its emphasis on data visualization, this book is a part of the QRC’s effort to focus on viz as a method of teaching quantitative reasoning, which can be especially appealing to those in the humanities and arts.
Book group meetings were held Thursday, January 20, 2022 and Thursday, February 10, 2022.
Facilitators:
Lin Winton, Director of the Quantitative Resource Center and Lecturer in Biology
Anita Chikkatur, Associate Professor of Educational Studies
This book group was co-sponsored by the LTC, the Humanities Center, DGAH and The Andrew W. Mellon Foundation.