LEADER 01704nam  2200361zu 450 
001 9910764194503321
005 20251116152224.0
010   $a9783732867660
010   $a3732867668
035   $a(CKB)28809871900041
035   $a(BIP)093235347
035   $a(Perlego)4086167
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 
311 08$a3837667669 
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 Alex$4edt
906   $aBOOK
912   $a9910764194503321
996   $aBeyond Quantity: Research with Subsymbolic AI$93651365
997   $aUNINA