Miscellany:
Beyond Quantity. Research with Subsymbolic AI

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dc.contributor.editorSudmann, Andreas
dc.contributor.editorEchterhölter, Anna
dc.contributor.editorRamsauer, Markus
dc.contributor.editorRetkowski, Fabian
dc.contributor.editorSchröter, Jens
dc.contributor.editorWaibel, Alexander
dc.date.accessioned2023-11-22T09:46:54Z
dc.date.available2023-11-22T09:46:54Z
dc.date.issued2023
dc.description.abstractHow 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?en
dc.identifier.doi10.14361/9783839467664
dc.identifier.doihttps://doi.org/10.25969/mediarep/20138
dc.identifier.isbnisbn:978-3-8394-6766-4
dc.identifier.urihttps://www.transcript-verlag.de/978-3-8376-6766-0/beyond-quantity/
dc.identifier.urihttps://mediarep.org/handle/doc/21361
dc.languageeng
dc.publishertranscript
dc.publisher.placeBielefeld
dc.rightsCreative Commons Attribution 4.0 Generic
dc.rights.urihttps://creativecommons.org/licenses/by/4.0
dc.subjectArtificial Intelligenceen
dc.subjectMachine Learningen
dc.subjectArtificial Neural Networksen
dc.subjectSubsymbolic Artificial Intelligenceen
dc.subject.ddcddc:300
dc.titleBeyond Quantity. Research with Subsymbolic AIen
dc.typebook
dc.type.statuspublishedVersion
dspace.entity.typeMisc
local.academicbookseriesKI-Kritik | AI Critique
local.coverpage2023-11-24T00:33:52
local.identifier.firstpublishedhttps://www.transcript-verlag.de/978-3-8376-6766-0/beyond-quantity/
local.source.volume6

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