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Trustworthy artificial intelligence researchers should seek to better detect and characterize systematic deviations in data and models (that is, bias). This article provides data scientists with motivation, theory, code, and examples on how to perform disciplined discovery of systematic deviations in data and models at the subset level.
Basel Shbita, Pengyuan Li, et al.
ESWC 2026
Thomas Bohnstingl, Ayush Garg, et al.
ICASSP 2022
Hiroki Yanagisawa, Kohei Miyaguchi, et al.
NeurIPS 2022
Arafat Sultan, Avi Sil, et al.
EMNLP 2022