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            KI-Realitäten

            Modelle, Praktiken und Topologien maschinellen Lernens

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            Contributor(s)
            Groß, Richard (editor)
            Jordan, Rita (editor)
            Language
            German
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            Abstract
            Maschinelles Lernen stellt zunehmend einen wichtigen Faktor soziotechnischen Wandels dar. Zugleich ist es selbst Produkt der Realitäten, an deren Reproduktion es in Form praktischer Anwendungen wie auch als Spekulationsobjekt beteiligt ist. Die Beiträge des Bandes verhandeln gegenwärtige Manifestationen maschinellen Lernens als Phänomene, die für epistemische Verunsicherungen sorgen und die Bedingungen von Sozialität rekonfigurieren. Sie begegnen dieser Herausforderung, indem sie konkrete Verfahren in ihrer gesellschaftlichen Einbettung analysieren sowie bestehende theoretische Charakterisierungen sogenannter Künstlicher Intelligenz kritisch reflektieren.
            URI
            https://doab-dev.siscern.org/handle/20.500.12854/164263
            Keywords
            STS; Systemtheorie; Maschinelles Lernen; Künstliche Intelligenz; Sozialtheorie; Epistemologie; Digitalisierung; Medien; Digitale Medien; Mediensoziologie; Medienphilosophie; Wissenschaftssoziologie; Medienwissenschaft; Systems Theory; Machine Learning; Artificial Intelligence; Social Theory; Epistemology; Digitalization; Media; Digital Media; Sociology of Media; Media Philosophy; Sociology of Science; Media Studies; thema EDItEUR::J Society and Social Sciences::JB Society and culture: general::JBC Cultural and media studies::JBCT Media studies; thema EDItEUR::Q Philosophy and Religion::QD Philosophy
            DOI
            10.1515/9783839466605
            ISBN
            9783839466605, 9783837666601
            Publisher
            transcript Verlag
            Publisher website
            http://www.transcript-verlag.de
            Publication date and place
            Bielefeld, 2023
            Imprint
            transcript Verlag
            Series
            KI-Kritik / AI Critique,
            Pages
            374
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              This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

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