PREDICTIVE POLICING: CASE OF THE UNITED STATES OF AMERICA

Authors : Şükrü Can Öztürk, Şerafettin Erten

Pages : 212-223

View : 53 | Download : 88

Publication Date : 2025-07-20

Article Type : Research Paper

Abstract :In recent years, predictive policing has emerged as a highly influential yet deeply controversial approach to crime prevention in the United States. By harnessing historical crime data and applying statistical and machine learning models, law enforcement agencies aim to forecast the location, time, and even individuals most likely to be involved in future criminal activity. While the underlying goal of these systems is to improve efficiency and reduce crime through proactive intervention, their implementation has raised complex questions about fairness, legality, and public accountability. This article provides an in-depth examination of predictive policing from multiple dimensions: theoretical foundations, empirical applications, legal critiques, and ethical implications. It begins by situating predictive policing within broader criminological theories such as rational choice, routine activity theory, and broken windows policing, explaining how these frameworks inform algorithmic crime forecasting. The article then presents detailed case studies from three major U.S. cities–Los Angeles (PredPol and Operation LASER), Chicago (Strategic Subject List), and New York City (CompStat and Domain Awareness System)–to analyze how different models have been operationalized, evaluated, and contested. Through a synthesis of academic research, governmental reports, and empirical evaluations, the article critically assesses whether predictive policing delivers on its promises. Findings suggest that while there may be limited improvements in crime detection or resource deployment in some contexts, these gains are often offset by disproportionate targeting of marginalized communities, lack of transparency in algorithmic design, and absence of independent oversight mechanisms. The article concludes with a set of policy recommendations aimed at mitigating harm and enhancing accountability. These include mandating algorithmic transparency, implementing fairness-aware design principles, strengthening data governance, and embedding community oversight into all stages of system development and deployment. Ultimately, while predictive policing technologies may offer tactical benefits, their long-term value depends on the establishment of ethical, legal, and socially just frameworks that prioritize civil liberties and public trust.
Keywords : Öngörücü Polislik, Algoritmik Önyargı, Veri Temelli Kolluk Faaliyeti, Makine Öğrenmesi, Kamu Güvenliği Teknolojileri, Gözetim Etiği

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