Data feminism

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 surv...

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Hlavní autoři: D'Ignazio, Catherine, 1975-, Klein, Lauren F., 19..-...., auteure en sciences sociales (Autor)
Médium: Livre numérique
Jazyk:Anglais
Vydáno: Cambridge (Mass.) : MIT Press C 2020.
Edice:Ideas series
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On-line přístup:Accès Université d'Orléans et IFPM
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Poznámka: Couverture. https://static.cyberlibris.com/books_upload/136pix/9780262358521.jpg
Titre provenant de la page de titre du document numérique
La pagination de l'édition imprimée correspondante est de 328 p.
Cyberlibris (ScholarVox) corpus Sciences de l'ingénieur
Cyberlibris (ScholarVox) corpus Sciences de l'ingénieur
Autres localisations: Voir dans le Sudoc
Edition sous un autre format:• Data feminism, Catherine d'Ignazio and Lauren F. Klein, 2020, Cambridge (Massachusetts), The MIT Press, 1 vol. (XII-314 p.), Strong ideas, 978-0-262-04400-4
Popis
Shrnutí: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. [D'après source : diffuseur]
Popis jednotky:Couverture. https://static.cyberlibris.com/books_upload/136pix/9780262358521.jpg
Titre provenant de la page de titre du document numérique
La pagination de l'édition imprimée correspondante est de 328 p.
Cyberlibris (ScholarVox) corpus Sciences de l'ingénieur
Cyberlibris (ScholarVox) corpus Sciences de l'ingénieur
Médium:Configuration requise : navigateur internet
ISBN:9780262358521 (édition électronique)
Přístup:L'accès complet à la ressource est réservé aux usagers des établissements qui en ont fait l'acquisition