Beyond Quantity
Research with Subsymbolic AI
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Beschreibung
An exploration of the implications and effects of AI on scientific and academic practice.
How do artificial neural networks and other forms of artificial intelligence interfere with methods and practices in the sciences? Which interdisciplinary epistemological challenges arise when we think about the use of AI beyond its dependency on big data? Not only the natural sciences, but also the social sciences and the humanities seem to be increasingly affected by current approaches of subsymbolic AI, which master problems of quality (fuzziness, uncertainty) in a hitherto unknown way. But what are the conditions, implications, and effects of these (potential) epistemic transformations and how must research on AI be configured to address them adequately?
Autor*in
Andreas Sudmann
Andreas Sudmann (PD Dr.) ist Medienwissenschaftler an den Universitäten in Bochum und Bonn. Seine Forschungsschwerpunkte liegen u.a. in Künstlicher Intelligenz, digitalen Kulturen, Medientheorie, Mediengeschichte und Medienkritik.
Themen in »Beyond Quantity«
AI AI Machine Learning Machine Learning Artificial Neural Networks Artificial Neural Networks Subsymbolic AI Subsymbolic AI Research on Research Research on Research Digitalization Digitalization Technology Technology Digital Media
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Besprochen in:
Zeitschrift für Medienwissenschaft, 05.02.2025, Raphael Besenbäck
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