specify fairness

README.md

@@ -11,13 +11,13 @@ tags:
 - evaluate
 - metric
 description: >-
-  Directional Bias Amplification is a metric that captures the amount of bias (i.e., a conditional probability) that is amplified. This metric was introduced in the ICML 2021 paper ["Directional Bias Amplification"](https://arxiv.org/abs/2102.12594)
+  Directional Bias Amplification is a metric that captures the amount of bias (i.e., a conditional probability) that is amplified. This metric was introduced in the ICML 2021 paper ["Directional Bias Amplification"](https://arxiv.org/abs/2102.12594) for fairness evaluation.
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 # Metric Card for Directional Bias Amplification
 
 ## Metric Description
-Directional Bias Amplification is a metric that captures the amount of bias (i.e., a conditional probability) that is amplified. This metric was introduced in the ICML 2021 paper ["Directional Bias Amplification"](https://arxiv.org/abs/2102.12594)
+Directional Bias Amplification is a metric that captures the amount of bias (i.e., a conditional probability) that is amplified. This metric was introduced in the ICML 2021 paper ["Directional Bias Amplification"](https://arxiv.org/abs/2102.12594) for fairness evaluation.
 
 ## How to Use
 This metric operates on multi-label (including binary) classification settings where each image has a(n) associated sensitive attribute(s).