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SUMMARY:Shuyi Li: Understandings of explainable AI (XAI) in research c
 ommunities. A mixed-method approach using topic modelling and SNA
UID:f84e-55a3-51af-3561@www.dhss.phil.fau.eu
DESCRIPTION:The Department of Digital Humanities and Social Studies wo
 uld like to invite you to the following talk in our DH Colloquium: Shu
 yi Li: »Understandings of explainable AI (XAI) in research communitie
 s. A mixed-method approach using topic modelling and SNA« Abstract Ma
 chine learning (ML) is now ubiquitous in daily life and has a far-reac
 hing impact on society. Researchers in Explainable Artificial Intellig
 ence (XAI) strive to develop explainable machine learning techniques t
 o mitigate the adverse effects of black-box models. XAI research inher
 ently requires interdisciplinary collaboration. In light of this\, thi
 s thesis conducts both qualitative and quantitative analyses of litera
 ture from the humanities\, psychology\, and STEM fields to (1) explore
  the extent to which diverse research domains remain isolated from one
  another\, and (2) evaluate both historical and recent influential alg
 orithms from a multidisciplinary perspective. Further information and 
 other upcoming talks in the Colloquium can be found here.
DTSTART:20250611T160000Z
DTEND:20250611T180000Z
LOCATION:Room 3.17 (3. OG)\, Werner-von-Siemens-Straße 61\, 91052 Erlangen
DTSTAMP:20260420T231713Z
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