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Fairness
8 concepts, 8 reviewed and merged.
Criteria
Disparate Impact
A rule can treat everyone identically and still fall much more heavily on one group.
verified
Fairness Criteria
"Fair" is not one thing you can ask a model for.
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Data
Proxy Variable
Delete race from the features and the model finds postcode.
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Representation Bias
If a group is a small fraction of the training data, the model has had less opportunity to learn them and will…
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Foundations
Group vs Individual Fairness
Group fairness asks whether the outcomes come out even across groups.
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Impossibility Result
You cannot have all of them.
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Measurement
Evaluation Disaggregation
Report the metric per group instead of once.
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Methods
Bias Mitigation
Once a disparity has been measured, something has to change.
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