作者简介

Catherine D'Ignazio is Assistant Professor of Urban Science and Planning in the Department of Urban Studies and Planning at MIT.
Lauren F. Klein is Associate Professor of English and Quantitative Theory & Methods at Emory University.

内容简介

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.


Catherine D'Ignazio is Assistant Professor of Urban Science and Planning in the Department of Urban Studies and Planning at MIT.

Lauren F. Klein is Associate Professor of English and Quantitative Theory & Methods at Emory University.

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豆瓣评论

  • 米洛克莱特
    大数据时代人人转码,除了最直白的经济利益,数据背后带来的权利也很可怕。数据表面象征着客观和事实,但其实只是一种imagined objectivity,无形之中加深了原有不平等权利的结构,如果不是专门停下来question这些根本不会想到吧…读完的感受就是大学真的应该把Data Ethics设为必修课 10-10
  • 豆友96532787
    后几章明显力不足,前几章还是有很多好观点。数据是信息,是知识,也是人为的构造,一定会受文化、政治、社会的影响。数据道德的话题应该成为每个人的必修课。12-23
  • 点苍
    读下来酣畅淋漓 虽然某些论证自我重合度比较高 但某种程度上称得上women in tech 小组的guideline(我瞎讲的10-24
  • 顾予美
    推荐给做数据的友邻,用来重新审视自己工作,思考数据从收集、处理到应用各环节可能存在的性别偏见。我虽然上过几节统计课,但不做数据到底感觉无法实践,不太尽兴,也早就形成批判和质疑数据作为客观事实的敏感度了。如果单作为女权读本,对我来说再浓缩精简一些会更好。01-04
  • 弱碱性金鱼
    女性主义的数据素养。有批判有行动的方法。但data确实只是人工智能的一部分。data也是一种统治技术,为了不被统治也得学会一套方法论。个人觉得不错的一本书。06-23

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