Quantifying fairness in spatial predictive policing

Predictive policing leverages data-driven models to anticipate future criminal events and guide law enforcement strategies. However, concerns about algorithmic fairness have emerged, as these models risk perpetuating discrimination and inequities, particularly among vulnerable populations. While prior research has acknowledged the influence of disparities in crime reporting levels on these models, the extent of their impact on vulnerable populations remains insufficiently understood, posing a cr