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Towards Algorithmic Fairness in Space-Time: Filling in Black Holes
New technologies and the availability of geospatial data have drawn attention to spatio-temporal biases present in society.
Detecting Bias in the Presence of Spatial Autocorrelation
In spite of considerable practical importance, current algorithmic fairness literature lacks technical methods to account for underlying geographic dependency while evaluating or mitigating bias issues for spatial data.
Bias Detection
Fairness
Applications
Computers and Society
Towards Integrating Fairness Transparently in Industrial Applications
Numerous Machine Learning (ML) bias-related failures in recent years have led to scrutiny of how companies incorporate aspects of transparency and accountability in their ML lifecycles.
