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Databases & Big Data - Data Feminism (Strong Ideas)

Description

Book Synopsis: 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.

Details

Introducing Data Feminism (Strong Ideas), a groundbreaking book that revolutionizes the way we think about data science and data ethics. Informed by the ideas of intersectional feminism, this book provides a fresh perspective on the power dynamics surrounding data science.

Data science has the potential to create positive change, such as exposing injustice and improving health outcomes. However, it can also be used for discrimination, surveillance, and control. That's why it's crucial to ask: who is doing data science? Who is it benefiting? Whose interests are being prioritized?

Traditional narratives about big data and data science are dominated by white, male perspectives that uphold a techno-heroic image. In Data Feminism, Catherine D'Ignazio and Lauren Klein challenge this status quo and propose a more inclusive and ethical approach. By integrating intersectional feminist thought, they uncover the flaws in existing classification systems and dismantle the male/female binary.

Discover how an understanding of emotion can revolutionize data visualization, and how the concept of invisible labor reveals the human effort behind automated systems. Data Feminism exposes the fallacy that data "speaks for itself" and empowers data scientists to work towards justice.

Whether you're a data scientist seeking to embrace feminism as a tool for social change or a feminist looking to make an impact in the field of data science, Data Feminism provides practical strategies to challenge and transform power differentials. This book goes beyond gender, exploring the broader issues of power and how they can be challenged and reshaped.

Don't miss out on this transformative read! Get your copy of Data Feminism (Strong Ideas) now and join the movement towards a more just and inclusive data science landscape.

Disclosure: I get commissions for purchases made through links in this website