TY  - JOUR
T1  - PREDICTIVE POLICING: CASE OF THE UNITED STATES OF AMERICA
TT  - ÖNGÖRÜCÜ POLİSLİK: AMERİKA BİRLEŞİK DEVLETLERİ ÖRNEĞİ
AU  - Öztürk, Şükrü Can
AU  - Erten, Şerafettin
PY  - 2025
DA  - July
Y2  - 2025
JF  - Uluslararası Toplumsal Bilimler Dergisi
JO  - TOBİDER, tobider
PB  - Sadık Hacı
WT  - DergiPark
SN  - 2587-2591
SP  - 212
EP  - 223
VL  - 9
IS  - 2
LA  - en
AB  - 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.
KW  - Predictive Policing
KW  - Algorithmic Bias
KW  - Data-Driven Policing
KW  - Machine Learning In Law Enforcement
KW  - Public Safety Technology
KW  - Surveillance Ethics.
N2  - Son yıllarda, öngörücü polislik (predictive policing), Amerika Birleşik Devletleri’nde suç önleme alanında etkili fakat oldukça tartışmalı bir yaklaşım olarak öne çıkmıştır. Geçmiş suç verilerinden yararlanarak istatistiksel ve makine öğrenmesi modelleri kullanan bu sistemler, kolluk kuvvetlerinin gelecekteki suçların yerini, zamanını ve hatta faillerini önceden tahmin etmelerini amaçlamaktadır. Ancak bu teknolojilerin temel hedefi, etkinlik ve suç oranlarını azaltma gibi amaçlara hizmet etse de, uygulamada adalet, hukukilik ve kamu denetimi gibi alanlarda ciddi tartışmalara neden olmuştur.Bu makale, öngörücü polisliğe ilişkin kuramsal temelleri, ampirik uygulamaları, hukuki eleştirileri ve etik yansımaları çok boyutlu bir biçimde incelemektedir. İlk olarak, rasyonel seçim kuramı, rutin faaliyet teorisi ve kırık camlar kuramı gibi kriminolojik yaklaşımlarla bu uygulamalar arasındaki ilişki tartışılmakta, ardından öngörücü polislik modellerinin bilimsel arka planı açıklanmaktadır. Makalede, Los Angeles (PredPol ve LASER Operasyonu), Chicago (Stratejik Kişi Listesi) ve New York (CompStat ve Domain Awareness System) gibi büyük şehirlerdeki örnek olay incelemeleri üzerinden bu sistemlerin nasıl uygulandığı, değerlendirildiği ve kamuoyunda nasıl karşılandığı analiz edilmektedir.Kapsamlı literatür taraması ve ampirik bulgular ışığında yapılan değerlendirmeler, bu sistemlerin bazı durumlarda suçun önlenmesinde veya kaynakların daha etkili kullanılmasında sınırlı başarılar sağladığını ortaya koymaktadır. Ancak bu kazanımlar, sıklıkla dezavantajlı toplulukların orantısız biçimde hedef alınması, algoritmaların şeffaf olmaması ve bağımsız denetim mekanizmalarının eksikliği gibi önemli sorunlarla gölgelenmektedir.Makale, şeffaf algoritmalar, adil yapay zeka uygulamaları, güçlü veri yönetimi ve toplum temelli denetim gibi bir dizi politika önerisiyle son bulmaktadır. Sonuç olarak, öngörücü polislik teknolojileri taktik düzeyde fayda sağlama potansiyeline sahip olsa da, uzun vadede meşruiyetini ve toplumsal kabulünü ancak etik, hukuki ve adalet odaklı çerçeveler içinde sürdürebilecektir.
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UR  - https://dergipark.org.tr/en/pub/toplumsalbilimler/issue//1712312
L1  - https://dergipark.org.tr/en/download/article-file/4928221
ER  -