Data science has been used to expose injustices, improve health outcomes and topple governments. But it has also been used to discriminate, police and surveil.
Today, data science is a form of power. It has been used to expose injustice, improve health outcomes, and topple governments.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?In our new book,, we present a new way of thinking about data science and data ethics—one informed by intersectional feminist thought.
For example, we explain how 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. 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 is about much more than gender.
This is the privilege hazard: the phenomenon that makes those who occupy the most privileged positions among us—those with good educations, respected credentials, and professional accolades—so poorly equipped to recognize instances of oppression in the world. They lack what Anita Gurumurthy, executive director of IT for Change, has called “the empiricism of lived experience.
What’s more, the same cis het white men responsible for designing those systems lack the ability to detect harms and biases in their systems once they’ve been released into the world. In the case of the “three teenagers” Google searches, for example, it was a young Black teenager that pointed out the problem and a Black scholar who wrote about the problem.
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