A case study showing that AI admissions models can have persistent specificity and sensitivity bias by race and first-generation status, even when overall accuracy is high and common fairness metrics look satisfied.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.AI 1years
2024 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Bias Analysis of AI Models for Undergraduate Student Admissions
A case study showing that AI admissions models can have persistent specificity and sensitivity bias by race and first-generation status, even when overall accuracy is high and common fairness metrics look satisfied.