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  • Association for Computing Machinery (ACM)  (3)
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  • Association for Computing Machinery (ACM)  (3)
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  • 1
    Online-Ressource
    Online-Ressource
    Association for Computing Machinery (ACM) ; 2019
    In:  Communication Design Quarterly Vol. 7, No. 3 ( 2019-11-15), p. 30-31
    In: Communication Design Quarterly, Association for Computing Machinery (ACM), Vol. 7, No. 3 ( 2019-11-15), p. 30-31
    Kurzfassung: Read and considered thoughtfully, Safiya Umoja Noble's Algorithms of Oppression: How Search Engines Reinforce Racism is devastating. It reduces to rubble the notion that technology is neutral and ideology-free. Noble's crushing the neutrality myth does several things. First, this act lays foundations for her argument: only if you recognize and understand that technology is built with, and integrates, bias, can you then be open to her primary thesis: search engines advance discriminatory and often racist content. Second, it banishes a convenient response for many self-identified meritocratic Silicon Valley "winners" and their supporters. Post-reading, some individuals may retain their beliefs in a neutral and ideology-free technology in spite of the overwhelming evidence and citations Noble brings to bear. Effective countering of Noble's claims is unlikely to occur. For professionals working in technology, information, argumentation, and/or rhetorical studies, Algorithms of Oppression is refreshing. Agonistic towards structural racism and its defenses, single-minded in its evidentiary presentation, collaborative in its acknowledgement of others' scholarship and research, Noble models many academic, critical, and social moves. Technology scholars and writers will find in Algorithms of Oppression a masterful mentor text on how to be an activist researcher scholar. Noble also makes this enjoyable reading. It is uncommon to find academic books that can simultaneously be read, used, and applied by academics and non-academics alike.
    Materialart: Online-Ressource
    ISSN: 2166-1642
    Sprache: Englisch
    Verlag: Association for Computing Machinery (ACM)
    Publikationsdatum: 2019
    ZDB Id: 2714542-6
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
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  • 2
    Online-Ressource
    Online-Ressource
    Association for Computing Machinery (ACM) ; 2018
    In:  Proceedings of the ACM on Human-Computer Interaction Vol. 2, No. CSCW ( 2018-11), p. 1-21
    In: Proceedings of the ACM on Human-Computer Interaction, Association for Computing Machinery (ACM), Vol. 2, No. CSCW ( 2018-11), p. 1-21
    Kurzfassung: Ridesharing services have been viewed as heralding the next generation of mobility and recognized for their potential to provide an alternate and more flexible model of work. These services have also been critiqued for their treatment of employees, low wages, and other concerns. In this paper, we present a qualitative investigation of the introduction of Uber in Dhaka, Bangladesh. Using interview data from drivers and riders, and content analysis of riders' Facebook posts, we highlight how Uber's introduction into Dhaka's existing transportation infrastructure influenced experiences and practices of mobility in the city. Drawing on Iris Marion Young's theory of justice, we demonstrate how the introduction of Uber in Dhaka reinforces existing modes of oppression and introduces new ones, even as it generates room for creative modes of resistance. Finally, we underline algorithms' opacity and veneer of objectivity as a potential source of oppression, call for deepening the postcolonial computing perspective, and make a case for stronger connections between technology interventions and policy.
    Materialart: Online-Ressource
    ISSN: 2573-0142
    Sprache: Englisch
    Verlag: Association for Computing Machinery (ACM)
    Publikationsdatum: 2018
    ZDB Id: 2930194-4
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
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  • 3
    Online-Ressource
    Online-Ressource
    Association for Computing Machinery (ACM) ; 2022
    In:  ACM Transactions on Interactive Intelligent Systems Vol. 12, No. 1 ( 2022-03-31), p. 1-34
    In: ACM Transactions on Interactive Intelligent Systems, Association for Computing Machinery (ACM), Vol. 12, No. 1 ( 2022-03-31), p. 1-34
    Kurzfassung: With the rise of AI and data mining techniques, group profiling and group-level analysis have been increasingly used in many domains, including policy making and direct marketing. In some cases, the statistics extracted from data may provide insights to a group’s shared characteristics; in others, the group-level analysis can lead to problems, including stereotyping and systematic oppression. How can analytic tools facilitate a more conscientious process in group analysis? In this work, we identify a set of accountable group analytics design guidelines to explicate the needs for group differentiation and preventing overgeneralization of a group. Following the design guidelines, we develop TribalGram , a visual analytic suite that leverages interpretable machine learning algorithms and visualization to offer inference assessment, model explanation, data corroboration, and sense-making. Through the interviews with domain experts, we showcase how our design and tools can bring a richer understanding of “groups” mined from the data.
    Materialart: Online-Ressource
    ISSN: 2160-6455 , 2160-6463
    Sprache: Englisch
    Verlag: Association for Computing Machinery (ACM)
    Publikationsdatum: 2022
    ZDB Id: 2644997-3
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
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