APPROXIMATING ALGORITHMS: FROM DISCRIMINATING DATA TO TALKING WITH AN AI.

Wendy Hui Kyong Chun's Discriminating Data: Correlation, Neighborhoods, and the New Politics of Recognition offers important tools to understand and, more importantly, transform the algorithms perpetuating and intensifying discrimination in North American societies. Unpacking her work's implications...

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Publicado en:History & Theory Vol. 61; no. 4; pp. 152 - 166
Autor principal: Hayles, N. Katherine
Formato: Book Review
Publicado: Wiley-Blackwell Dec2022
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Acceso en línea:Ver este registro en EBSCOhost
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        Discriminating Data: Correlation, Neighborhoods & the New Politics of Recognition (Book)
        Chun, Wendy Hui Kyong, 1969-
        Algorithms
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        Barnett, Alex
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          Discriminating Data: Correlation, Neighborhoods & the New Politics of Recognition (Book)
          Chun, Wendy Hui Kyong, 1969-
          Algorithms
          Nonfiction
          Barnett, Alex
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        algorithm
        approximation
        bias
        discrimination
        ethicopolitics
        Wendy Hui Kyong Chun
      ab: Wendy Hui Kyong Chun's Discriminating Data: Correlation, Neighborhoods, and the New Politics of Recognition offers important tools to understand and, more importantly, transform the algorithms perpetuating and intensifying discrimination in North American societies. Unpacking her work's implications, this essay offers seven approximations—ranging from eliminating bias to rethinking the symbiotic relations between humans and computational media—as solutions to the problems she identifies. While some approximations reveal limitations in others, the clashes between them are due to the scope of the frameworks they employ. All are useful in the struggle to comprehend, in both small and large terms, the nature of the profound changes in the contemporary condition as computational media penetrate ever more deeply into the fabrics of our lives.
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