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.
© 2020 Tantor Audio (Ljudbok): 9781705264003
Utgivningsdatum
Ljudbok: 23 september 2020
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.
© 2020 Tantor Audio (Ljudbok): 9781705264003
Utgivningsdatum
Ljudbok: 23 september 2020
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Dan
10 apr. 2023
Bra genomgång av hur data och statistik behöver kritiseras inte bara faktamässigt utan på ett samhälleligt plan. Vilken ”makt-matris” ligger bakom statistiken, hur kan man nyansera siffrorna och ge flera perspektiv så dom blir mer rättvisande, etc. Vilket betyder att data-arbete inte är en solo-sport. Och att man måste beakta implikationerna för olika delar av samhället när man jobbar fram abstrakta slutsatser eller beslutsunderlag/modeller.En bra bok som gav mig lite mer verktyg att ifrågasätta statistikens ”grunder” bortom rent matematiska och innehållsmässiga kvaliteter.
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