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            The Democratization of Artificial Intelligence

            Net Politics in the Era of Learning Algorithms (Edition 1)

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            Contributor(s)
            Sudmann, Andreas (editor)
            Collection
            Knowledge Unlatched (KU)
            Language
            English
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            Résumé
            After a long time of neglect, Artificial Intelligence is once again at the center of most of our political, economic, and socio-cultural debates. Recent advances in the field of Artifical Neural Networks have led to a renaissance of dystopian and utopian speculations on an AI-rendered future. Algorithmic technologies are deployed for identifying potential terrorists through vast surveillance networks, for producing sentencing guidelines and recidivism risk profiles in criminal justice systems, for demographic and psychographic targeting of bodies for advertising or propaganda, and more generally for automating the analysis of language, text, and images. Against this background, the aim of this book is to discuss the heterogenous conditions, implications, and effects of modern AI and Internet technologies in terms of their political dimension: What does it mean to critically investigate efforts of net politics in the age of machine learning algorithms?
            URI
            https://doab-dev.siscern.org/handle/20.500.12854/176481
            Keywords
            Social Science; Media Studies; thema EDItEUR::J Society and Social Sciences::JB Society and culture: general::JBC Cultural and media studies::JBCT Media studies
            DOI
            https://doi.org/10.14361/9783839447192
            ISBN
            9783839447192
            Publisher
            transcript Verlag
            Publisher website
            http://www.transcript-verlag.de
            Publication date and place
            Bielefeld, 2019
            Grantor
            • Knowledge Unlatched
            Imprint
            transcript Verlag
            • OAPEN harvesting collection

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            • logo EUEuropean Union
              This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

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