LEADER 01621nam 2200325zu 450 001 9910764194503321 005 20231218202028.0 010 $a3-7328-6766-8 035 $a(CKB)28809871900041 035 $a(BIP)093235347 035 $a(EXLCZ)9928809871900041 100 $a20231113|2023uuuu || | 101 0 $aeng 135 $aur||||||||||| 200 10$aBeyond Quantity: Research with Subsymbolic AI 210 $cTranscript Verlag$d2023 215 $a1 online resource (360 p.) 311 08$a9783837667660 330 8 $aHow 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? 700 $aJahn-Sudmann$b Andreas$f1974-$01451273 702 $aSudmann$b Andreas$4edt 702 $aEchterho?lter$b Anna$4edt 702 $aRamsauer$b Markus$4edt 702 $aRetkowski$b Fabian$4edt 702 $aSchro?ter$b Jens$4edt 702 $aWaibel$b Alexander$4edt 906 $aBOOK 912 $a9910764194503321 996 $aBeyond Quantity: Research with Subsymbolic AI$93651365 997 $aUNINA