Mapping Police Officers’ Anticipated Experiences and Attitudes Towards Place-Based Big Data Policing

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. Specific applications beyond the broader concept of big data policing, such as place-based big data policing, focus on the use of big data analytics to enhance insight into where and when crime is more likely to occur, thereby improving both strategic and tactical decision-making. Despite advancements, limited research explores police officers’ anticipated experiences, self-reported knowledge and ethical considerations regarding these technologies prior to their implementation, particularly outside the United States. Yet these insights are relevant for the design and implementation of applications. This study addresses that gap in pre-implementation research by evaluating survey data from 522 police officers across 20 Flemish police departments, offering insights into their attitudes, knowledge and ethical considerations regarding place-based big data policing, prior to a large-scale field test. Notably, findings indicate small but significant differences on the basis of police officers’ position, suggesting that expectations are shaped by existing technological and organizational frames. To ensure that practical and ethical needs of novel applications are met, this study highlights how end-user perspectives can inform implementation processes, for instance through socio-technical system’s design frameworks.