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Option 3: Post-Processing
If we decide to mitigate bias at the post-processing stage, we will have to take the predictions from the model and perform a separate process to reduce bias. We will need as inputs: existing model predictions, labels and group membership; with this we can create a new set of less biased predictions, for example using model optimization. Notice that in order to do this you will need access to protected attributes at the point of inference, which is not always possible.
- Reject Option Classification, which gives favorable outcomes to unprivileged groups and unfavorable outcomes to privileged groups in a confidence band around the decision boundary with the highest uncertainty (Kamiran 2012).