Trevor Owens

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.

Charting the evolution of practicing digital history Historians have seen their field transformed by the digital age. Research agendas, teaching and learning, scholarly communication, the nature of the archive—all have undergone a sea change that in and of itself constitutes a fascinating digital history. Yet technology's role in the field's development remains a glaring blind spot among digital scholars. Adam Crymble mines private and web archives, social media, and oral histories to show how technology and historians have come together. Using case studies, Crymble merges histories and philosophies of the field, separating issues relevant to historians from activities in the broader digital humanities movement. Key themes include the origin myths of digital historical research; a history of mass digitization of sources; how technology influenced changes in the curriculum; a portrait of the self-learning system that trains historians and the problems with that system; how blogs became a part of outreach and academic writing; and a roadmap for the continuing study of history in the digital era.