Mapping police officers’ experiences & attitudes towards place-based big data policing

• In Event: Digital Criminology: Surveillance, Power and Accountability

Abstract

Over the past decades, law enforcement agencies have increasingly adopted big data and advanced analytical methods, including machine learning and artificial intelligence (AI), to inform their crime prevention strategies. A notable application, referred to as big data policing, focuses on predicting where and when crime is more likely to occur to enhance both strategic and tactical decision-making. Despite growing interest and advancements in this area, significant gaps remain in the scientific literature concerning police officers’ experiences with and attitudes toward these technologies. To address this, this presentation offers an evaluation on the basis of survey data from 522 police officers across 20 Flemish police departments, providing insights into their knowledge, expectations, perceived efficacy, trust, and ethical considerations regarding place-based big data policing. Differences in attitudes based on police officers' roles and gender are discussed, emphasizing the importance of tailoring big data policing models to diverse needs and contexts. The presentation showcases findings that can further inform the effective design, implementation, and evaluation of big data policing tools, highlighting the relevance of user perspectives for ethical and practical applications.

Authors

• Naomi Theinert, Ghent University

• Thom Snaphaan, Avans University of Applied Sciences & Ghent University

• Robin Khalfa, Ghent University

• Wim Hardyns, Ghent University, Department of Criminology, Criminal Law and Social Law