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        nonhuman witnessing

        War, Data, and Ecology after the End of the World

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        Author(s)
        Richardson, Michael
        Collection
        Knowledge Unlatched (KU)
        Language
        English
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        Abstract
        In Nonhuman Witnessing Michael Richardson argues that a radical rethinking of what counts as witnessing is central to building frameworks for justice in an era of endless war, ecological catastrophe, and  technological capture. Dismantling the primacy and notion of traditional human-based forms of witnessing, Richardson shows how ecological, machinic, and algorithmic forms of witnessing can help us better understand contemporary crises. He examines the media-specificity of nonhuman witnessing across an array of sites, from nuclear testing on First Nations land and autonomous drone warfare to deepfakes, artificial intelligence, and algorithmic investigative tools. Throughout, he illuminates the ethical and political implications of witnessing in an age of profound instability. By challenging readers to rethink their understanding of witnessing, testimony, and trauma in the context of interconnected crises, Richardson reveals the complex entanglements between witnessing and violence and the human and the nonhuman.
        URI
        https://library.oapen.org/handle/20.500.12657/95775
        Keywords
        Political Science; History & Theory; Social Science; Media Studies; Privacy & Surveillance
        ISBN
        9781478027782, 9781478025641, 9781478020905
        Publisher
        Duke University Press
        Publisher website
        https://www.dukeupress.edu/
        Publication date and place
        2024
        Imprint
        Duke University Press
        Classification
        Political science & theory
        Media studies
        Ethical issues & debates
        Rights
        https://creativecommons.org/licenses/by-nc-nd/4.0/
        • Harvested from KU

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        • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

        Credits

        • logo EU
        • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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