Beyond Quantity Research with Subsymbolic AI
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...
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| Andere auteurs: | , , , , , |
|---|---|
| Formaat: | Elektronisch Hoofdstuk |
| Taal: | Engels |
| Gepubliceerd in: |
Bielefeld
transcript Verlag
2023
|
| Reeks: | KI-Kritik / AI Critique
6 |
| Onderwerpen: | |
| Online toegang: | OAPEN Library: download the publication OAPEN Library: description of the publication |
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| 520 | |a 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? | ||
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