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"Even though there is a growing interest in predictive policing, to date there have been few, if any, formal evaluations of these programs. This report documents an assessment of a predictive policing effort in Shreveport, Louisiana, in 2012, which was conducted to evaluate the crime reduction effects of policing guided by statistical predictions. RAND researchers led multiple interviews and focus groups with the Shreveport Police Department throughout the course of the trial to document the implementation of the statistical predictive and prevention models. In addition to a basic assessment of the process, the report shows the crime impacts and costs directly attributable to the strategy. It is hoped that this will provide a fuller picture for police departments considering if and how a predictive policing strategy should be adopted. There was no statistically significant change in property crime in the experimental districts that applied the predictive models compared with the control districts; therefore, overall, the intervention was deemed to have no effect. There are both statistical and substantive possibilities to explain this null effect. In addition, it is likely that the predictive policing program did not cost any more than the status quo."--"Abstract" on web page.
Predictive policing is the use of analytical techniques to identify targets for police intervention with the goal of preventing crime, solving past crimes, or identifying potential offenders and victims. These tools are not a substitute for integrated approaches to policing, nor are they a crystal ball. This guide assesses some of the most promising technical tools and tactical approaches for acting on predictions in an effective way.
This book addresses and reviews progress in a major innovative development within police work known as evidence-based policing. It involves a significant extension and strengthening of links between research and practice and is directed to the task of increasing police effectiveness in the field of community crime prevention. This volume provides an international perspective that synthesizes recent research results from the United States and other countries – including systematic reviews of large bodies of evidence – to illuminate several of the most challenging issues currently confronting police departments. It examines recent advances in research-based models of policing and the expanding base in outcome evaluation. Key areas of coverage include: Managing the nighttime economy. Supervising sex offenders. Tackling domestic/intimate partner violence. Addressing school violence and the formation of gangs. Reducing victim and witness retraction and disengagement. Responding to mental disorders, safeguarding vulnerable adults, and providing victim support. Leveraging public awareness campaigns. In addition, each chapter presents an overview of key issues within a designated area, synthesizes existing reviews, and examines the most recent research. The book clearly and concisely presents major concepts, theories, and research findings, thereby providing both conceptual and analytic tools alongside an integrated presentation of principal findings and messages. The volume concludes with a discussion of current directions in research, key developments in policing strategies, and identification of effective operational structures for facilitating and sustaining research-practice links. Evidence-Based Policing and Community Crime Prevention is a must-have resource for researchers, clinicians and other professionals, and graduate students in forensic psychology, criminology and criminal justice, public health, developmental psychology, psychotherapy and counseling, psychiatry, social work, educational policy and politics, health psychology, nursing, and behavioral therapy/rehabilitation.
This edited text draws together the insights of numerous worldwide eminent academics to evaluate the condition of predictive policing and artificial intelligence (AI) as interlocked policy areas. Predictive and AI technologies are growing in prominence and at an unprecedented rate. Powerful digital crime mapping tools are being used to identify crime hotspots in real-time, as pattern-matching and search algorithms are sorting through huge police databases populated by growing volumes of data in an eff ort to identify people liable to experience (or commit) crime, places likely to host it, and variables associated with its solvability. Facial and vehicle recognition cameras are locating criminals as they move, while police services develop strategies informed by machine learning and other kinds of predictive analytics. Many of these innovations are features of modern policing in the UK, the US and Australia, among other jurisdictions. AI promises to reduce unnecessary labour, speed up various forms of police work, encourage police forces to more efficiently apportion their resources, and enable police officers to prevent crime and protect people from a variety of future harms. However, the promises of predictive and AI technologies and innovations do not always match reality. They often have significant weaknesses, come at a considerable cost and require challenging trade- off s to be made. Focusing on the UK, the US and Australia, this book explores themes of choice architecture, decision- making, human rights, accountability and the rule of law, as well as future uses of AI and predictive technologies in various policing contexts. The text contributes to ongoing debates on the benefits and biases of predictive algorithms, big data sets, machine learning systems, and broader policing strategies and challenges. Written in a clear and direct style, this book will appeal to students and scholars of policing, criminology, crime science, sociology, computer science, cognitive psychology and all those interested in the emergence of AI as a feature of contemporary policing.
Why technology is not an end in itself, and how cities can be “smart enough,” using technology to promote democracy and equity. Smart cities, where technology is used to solve every problem, are hailed as futuristic urban utopias. We are promised that apps, algorithms, and artificial intelligence will relieve congestion, restore democracy, prevent crime, and improve public services. In The Smart Enough City, Ben Green warns against seeing the city only through the lens of technology; taking an exclusively technical view of urban life will lead to cities that appear smart but under the surface are rife with injustice and inequality. He proposes instead that cities strive to be “smart enough”: to embrace technology as a powerful tool when used in conjunction with other forms of social change—but not to value technology as an end in itself. In a technology-centric smart city, self-driving cars have the run of downtown and force out pedestrians, civic engagement is limited to requesting services through an app, police use algorithms to justify and perpetuate racist practices, and governments and private companies surveil public space to control behavior. Green describes smart city efforts gone wrong but also smart enough alternatives, attainable with the help of technology but not reducible to technology: a livable city, a democratic city, a just city, a responsible city, and an innovative city. By recognizing the complexity of urban life rather than merely seeing the city as something to optimize, these Smart Enough Cities successfully incorporate technology into a holistic vision of justice and equity.
This book gathers selected, peer-reviewed contributions presented at the Fifth International Conference on Numerical Analysis and Optimization (NAO-V), which was held at Sultan Qaboos University, Oman, on January 6-9, 2020. Each chapter reports on developments in key fields, such as numerical analysis, numerical optimization, numerical linear algebra, numerical differential equations, optimal control, approximation theory, applied mathematics, derivative-free optimization methods, programming models, and challenging applications that frequently arise in statistics, econometrics, finance, physics, medicine, biology, engineering and industry. Many real-world, complex problems can be formulated as optimization tasks, and can be characterized further as large scale, unconstrained, constrained, non-convex, nondifferentiable or discontinuous, and therefore require adequate computational methods, algorithms and software tools. These same tools are often employed by researchers working in current IT hot topics, such as big data, optimization and other complex numerical algorithms in the cloud, devising special techniques for supercomputing systems. This interdisciplinary view permeates the work included in this volume. The NAO conference series is held every three years at Sultan Qaboos University, with the aim of bringing together a group of international experts and presenting novel and advanced applications to facilitate interdisciplinary studies among pure scientific and applied knowledge. It is a venue where prominent scientists gather to share innovative ideas and know-how relating to new scientific methodologies, to promote scientific exchange, to discuss possible future cooperations, and to promote the mobility of local and young researchers.
Reviews innovations in policing over the last four decades, bringing together top policing scholars to discuss whether police should adopt these approaches.
Public police forces are a regular phenomenon in most jurisdictions around the world, yet their highly divergent legal context draws surprisingly little attention. Bringing together a wide range of police experts from all around the world, this book provides an overview of traditional and emerging fields of public policing, New material and findings are presented with an international-comparative perspective, it is a must-read for students of policing, security and law and professionals in related fields.
"This book examines, describes, and explains the current state of American policing. It proposes a new paradigm that emphasizes the protection of life as the primary mandate, moving away from mere coercion and social control"--
Crime Analysis With Crime Mapping, Fourth Edition provides students and practitioners with a solid foundation for understanding the conceptual nature and practice of crime analysis to assist police in preventing and reducing crime and disorder. Author Rachel Boba Santos offers an in-depth description of this emerging field, as well as guidelines and techniques for conducting crime analysis supported by evidence-based research, real world application, and recent innovations in the field. As the only introductory core text for crime analysis, this must-have resource presents readers with opportunities to apply theory, research methods, and statistics to careers that support and enhance the effectiveness of modern policing.