Please use this identifier to cite or link to this item:
https://doi.org/10.48548/pubdata-1404
Resource type | Dissertation |
Title(s) | Automated Patterns of Culture |
Subtitle(s) | Philosophy and Machine Learning |
DOI | 10.48548/pubdata-1404 |
Handle | 20.500.14123/1473 |
Creator | Prado, Maria Belen 0000-0002-7908-3739 (Fakultät Kulturwissenschaften, Leuphana Universität Lüneburg 02w2y2t16) |
Referee | Hörl, Erich 0009-0006-3304-0895 Nigro, Roberto 1137348704 Kauppinen, Tomi 0000-0003-3479-7022 |
Advisor | Hörl, Erich 0009-0006-3304-0895 |
Abstract | The book, entitled Automated Patterns of Culture: Machine learning and Culture [APOC], represents a unique contribution to the interdisciplinary exploration of patterns, offering an insightful engagement of the evolving process of pattern recognition in AI technologies with philosophical and media theories. The work not only expands on contemporary scholarship but also provides a provocative and profound dialogue with them. APOC navigates in a completely novel way the complexities of patterns with precision by underlying their evolution at different scales (as found in nature (ancestrality), mediated by humans and technics (history), and mediated and produced between technologies themselves (hyperhistory). It not only clarifies the historical development of pattern recognition techniques but also provides critical reflections that illuminate the current challenges and ethical as well as psycho-social considerations within the rapidly evolving landscape of artificial intelligence. |
Language | English |
Keywords | Artificial Intelligence; Machine Learning; Behavior Pattern; Homophily |
Date of defense | 2023-12-05 |
Year of publication in PubData | 2024 |
Publishing type | First publication |
Date issued | 2024-11-04 |
Creation context | Research |
Granting Institution | Leuphana Universität Lüneburg |
Published by | Medien- und Informationszentrum, Leuphana Universität Lüneburg |
Files in This Item:
File | Description | Size | Format | |
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Prado_Automated_Patterns_of_Culture_Diss.pdf License: Nutzung nach Urheberrecht open-access | 4.39 MB | Adobe PDF | View/Open |
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