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 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?

Preferred Citation
Sudmann, Andreas; Echterhölter, Anna; Ramsauer, Markus; Retkowski, Fabian; Schröter, Jens; Waibel, Alexander(Hg.): Beyond Quantity. Research with Subsymbolic AI. Bielefeld: transcript 2023. DOI: https://doi.org/10.25969/mediarep/20138.
 title = {Beyond Quantity. Research with Subsymbolic AI},
 year = 2023,
 doi = "\url{https://doi.org/10.25969/mediarep/20138}",
 editor = {Sudmann, Andreas and Echterhölter, Anna and Ramsauer, Markus and Retkowski, Fabian and Schröter, Jens and Waibel, Alexander},
 volume = 6,
 address = {Bielefeld},
 series = {KI-Kritik | AI Critique},
 publisher = {transcript},
 isbn = {978-3-8394-6766-4},
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