This book brings together history and theory in art and media to examine the effects of artificial intelligence and machine learning in culture, and reflects on the implications of delegating parts of the creative process to AI.
This book brings together history and theory in art and media to examine the effects of artificial intelligence and machine learning in culture, and reflects on the implications of delegating parts of the creative process to AI.
Eduardo Navas is Associate Research Professor of Art and Digital Arts & Media Design in the School of Visual Arts, and Research Faculty in the College of Arts and Architecture's Arts & Design Research Incubator (ADRI) at Pennsylvania State University, where he researches and teaches principles of cultural analytics and digital humanities. Navas is the author of Remix Theory: The Aesthetics of Sampling (2012), Art, Media Design, and Postproduction: Open Guidelines on Appropriation and Remix (2018), and Spate: A Navigational Theory of Networks (2016). He is co-editor of The Routledge Companion to Remix Studies (2014), Keywords in Remix Studies (2017), and The Routledge Handbook of Remix Studies and Digital Humanities (2021).
Inhaltsangabe
Metacreativity Part I: Interstitial Paradigms 1. Labor 2. Modularity 3. Memory 4. Technology 5. Compression 6. Simulation 7. Environs Part II: Meta Paradigms 8. Art 9. Music 10. Media 11. Culture 12. History Part III: Metacreativity 13. Principles of Metacreativity 14. AI Aesthetics After Remix 15. Conclusion: Tripartages
Metacreativity Part I: Interstitial Paradigms 1. Labor 2. Modularity 3. Memory 4. Technology 5. Compression 6. Simulation 7. Environs Part II: Meta Paradigms 8. Art 9. Music 10. Media 11. Culture 12. History Part III: Metacreativity 13. Principles of Metacreativity 14. AI Aesthetics After Remix 15. Conclusion: Tripartages
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