Data Feminism

(MIT Press, 2020)

By Catherine D’Ignazio and Lauren F. Klein

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.

Women in Global Science: Advancing Academic Careers through International Collaboration

(Stanford University Press, 2017)

By Kathrin Zippel

Scientific and engineering research is increasingly global, and international collaboration can be essential to academic success. Yet even as administrators and policymakers extol the benefits of global science, few recognize the diversity of international research collaborations and their participants, or take gendered inequalities into account. Women in Global Science is the first book to consider systematically the challenges and opportunities that the globalization of scientific work brings to U.S. academics, especially for women faculty.

Kathrin Zippel looks to the STEM fields as a case study, where gendered cultures and structures in academia have contributed to an underrepresentation of women. While some have approached underrepresentation as a national concern with a national solution, Zippel highlights how gender relations are reconfigured in global academia. For U.S. women in particular, international collaboration offers opportunities to step outside of exclusionary networks at home. International collaboration is not the panacea to gendered inequalities in academia, but, as Zippel argues, international considerations can be key to ending the steady attrition of women in STEM fields and developing a more inclusive academic world.