Description
Book SynopsisMachine Learning for Criminology and Crime Research: At the Crossroads reviews the roots of the intersection between machine learning, artificial intelligence (AI), and research on crime; examines the current state of the art in this area of scholarly inquiry; and discusses future perspectives that may emerge from this relationship.
As machine learning and AI approaches become increasingly pervasive, it is critical for criminology and crime research to reflect on the ways in which these paradigms could reshape the study of crime. In response, this book seeks to stimulate this discussion. The opening part is framed through a historical lens, with the first chapter dedicated to the origins of the relationship between AI and research on crime, refuting the novelty narrative that often surrounds this debate. The second presents a compact overview of the history of AI, further providing a nontechnical primer on machine learning. The following chapter reviews some of the mo
Table of Contents
Chapter 1: The "Novelty Narrative": An Unorthodox Introduction
Chapter 2: A Collective Journey: A Short Overview on Artificial Intelligence
Chapter 3: Criminology at the Crossroads? Computational Perspectives
Chapter 4: To Reframe and Reform: Increasing the Positive Social Impact of Algorithmic Applications in Research on Crime
Chapter 5: Causal Inference in Criminology and Crime Research and the Promises of Machine Learning
Chapter 6: Concluding Remarks
