Label bias and proxy features drive algorithmic unfairness more than underrepresentation of protected groups in training data, and a new Data Bias Profile quantifies these risks.
Information technology — artificial intelligence (ai) — bias in ai systems and ai aided decision making, 2021
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Underrepresentation, Label Bias, and Proxies: Towards Data Bias Profiles for the EU AI Act and Beyond
Label bias and proxy features drive algorithmic unfairness more than underrepresentation of protected groups in training data, and a new Data Bias Profile quantifies these risks.