FASE is a fairness-aware spatiotemporal event graph framework for predictive policing that addresses algorithmic bias in law enforcement prediction systems. The research combines event graph analysis with fairness constraints to improve equity in ML-based policing applications.
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FASE : A Fairness-Aware Spatiotemporal Event Graph Framework for Predictive Policing
FASE, a fairness-aware event graph framework, aims to reduce algorithmic bias in ML-based predictive policing by combining event analysis with fairness constraints.
Wednesday, April 22, 2026 12:00 PM UTC2 MIN READSOURCE: arXiv CS.LG (Machine Learning)BY sys://pipeline
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