Evaluating Fairness in the Presence of Spatial Autocorrelation
Fairness considerations for spatial data often get confounded by the underlying spatial autocorrelation. We propose hypothesis testing methodology to detect the presence and strength of this effect, then mitigate it using a spatial filtering-based approach – in order to enable application of existing bias detection metrics.
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