Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP
Auteurs:
T. Schick, S. Udupa, H Schütze
Publié dans:
arxiv, accepted at TACL, 2021
Éditeur:
Cornell University
Listening to affected communities to define extreme speech: Dataset and experiments.
Auteurs:
A. Maronikolakis, A. Wisiorek, L. Nann, H. Jabbar, S. Udupa and H. Schuetze
Publié dans:
ACL 2022 Findings, 2022
Éditeur:
Arxiv
Ethical Scaling for Content Moderation: Extreme Speech and the (In)Significance of Artificial Intelligence
Auteurs:
S. Udupa, A. Maronikolakis, H. Schuetze, A. Wisiorek
Publié dans:
Shorenstein Center Discussion Papers, Harvard University, 2022
Éditeur:
Shorenstein Center, Harvard Kennedy School
Artificial Intelligence, Extreme Speech and the Challenges of Online Content Moderation
Auteurs:
S. Udupa, E. Hickok, A. Maronikolakis, H. Schuetze, L. Csuka, A. Wisiorek, L. Nann
Publié dans:
AI4Dignity Policy Brief, 2021
Éditeur:
LMU Munich and co-listed by the European Disinformation Observatory
Artificial Intelligence and the Cultural Problem of Online Extreme Speech
Auteurs:
S. Udupa
Publié dans:
Social Science Research Council Items, 2020
Éditeur:
Social Science Research Council
