{"product_id":"machine-learning-for-criminology-and-crime-research-at-the-crossroads-9781032109282","title":"Machine Learning for Criminology and Crime Research: At the Crossroads","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003e\n\u003cbr\u003eMachine Learning for Criminology and Crime Research explores the intersection of machine learning, artificial intelligence, and research on crime, examining the current state of the art and discussing future perspectives. It aims to stimulate discussion on how these paradigms can reshape the study of crime and proposes two goals and four pathways to increase the positive societal impact of algorithmic systems in this area. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Paperback \/ softback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 176 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 29 January 2024\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Taylor \u0026amp; Francis Ltd\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003cbr\u003eMachine Learning for Criminology and Crime Research: At the Crossroads delves into the intricate interplay between machine learning, artificial intelligence (AI), and research on crime, offering a comprehensive examination of the current state-of-the-art in this field of scholarly inquiry. This book explores the historical roots of the intersection between these disciplines, challenges the notion of their novelty, and provides a foundational understanding of AI and machine learning.\u003cbr\u003e\u003cbr\u003eThe second chapter offers a concise yet comprehensive overview of the history of AI, serving as a valuable primer for those unfamiliar with these technologies. The subsequent chapter delves into the emerging trends in computational criminology, employing network science approaches to quantitatively characterize publication patterns at the intersection of AI and criminology.\u003cbr\u003e\u003cbr\u003eFurthermore, this book proposes two overarching goals and four potential pathways to enhance the positive societal impact of algorithmic systems in research on crime. The sixth chapter showcases the emerging methods derived from the integration of machine learning and causal inference, highlighting their immense potential for addressing critical questions in the field.\u003cbr\u003e\u003cbr\u003eWith its transdisciplinary approach, Machine Learning for Criminology and Crime Research appeals to scholars and students across a wide range of disciplines, including criminology, criminal justice, sociology, economics, AI, data sciences, statistics, and computer science. This book serves as a valuable resource for those seeking to understand the transformative potential of these technologies in the study of crime and justice.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 360g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 234 x 156 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9781032109282\u003c\/p\u003e","brand":"Gian Maria Campedelli","offers":[{"title":"Paperback \/ softback","offer_id":45290061431034,"sku":"9781032109282","price":42.83,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/noImage_1_4630f321-29cf-41ac-9953-ef79688cdf58.jpg?v=1707124904","url":"https:\/\/shulphink.com\/products\/machine-learning-for-criminology-and-crime-research-at-the-crossroads-9781032109282","provider":"Shulph Ink","version":"1.0","type":"link"}