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