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        Artificial Intelligence - Intelligent Art?

        Human-Machine Interaction and Creative Practice

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        Contributor(s)
        Voigts, Eckart (editor)
        Auer, Robin Markus (editor)
        Elflein, Dietmar (editor)
        Kunas, Sebastian (editor)
        Röhnert, Jan (editor)
        Seelinger, Christoph (editor)
        Language
        English
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        Abstract
        As algorithmic data processing increasingly pervades everyday life, it is also making its way into the worlds of art, literature and music. In doing so, it shifts notions of creativity and evokes non-anthropocentric perspectives on artistic practice. This volume brings together contributions from the fields of cultural studies, literary studies, musicology and sound studies as well as media studies, sociology of technology, and beyond, presenting a truly interdisciplinary, state-of-the-art picture of the transformation of creative practice brought about by various forms of AI.
        URI
        https://library.oapen.org/handle/20.500.12657/90688
        Keywords
        Artificial Intelligence; AI Art; Creativity; Literature; Music; Machine Learning; GPT; GAN; NLP; Media; Art; Digitalization; Digital Media; Media Philosophy; Media Art; Media Aesthetics; Media Studies
        DOI
        10.14361/9783839469224
        ISBN
        9783839469224, 9783839469224, 9783837669220
        Publisher
        transcript Verlag
        Publisher website
        https://www.transcript-verlag.de/
        Publication date and place
        Bielefeld, 2024
        Series
        Digitale Gesellschaft, 64
        Classification
        Media studies: internet, digital media and society
        Philosophy
        Digital, video and new media arts
        Pages
        292
        Rights
        https://creativecommons.org/licenses/by-sa/4.0/
        • Imported or submitted locally

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        License

        • 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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