Machine Learning For Criminology And Crime Research
Download Machine Learning For Criminology And Crime Research full books in PDF, epub, and Kindle. Read online free Machine Learning For Criminology And Crime Research ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
| Author | : Richard Berk |
| Publisher | : Springer |
| Total Pages | : 184 |
| Release | : 2018-12-13 |
| Genre | : Computers |
| ISBN | : 3030022722 |
This book puts in one place and in accessible form Richard Berk’s most recent work on forecasts of re-offending by individuals already in criminal justice custody. Using machine learning statistical procedures trained on very large datasets, an explicit introduction of the relative costs of forecasting errors as the forecasts are constructed, and an emphasis on maximizing forecasting accuracy, the author shows how his decades of research on the topic improves forecasts of risk. Criminal justice risk forecasts anticipate the future behavior of specified individuals, rather than “predictive policing” for locations in time and space, which is a very different enterprise that uses different data different data analysis tools. The audience for this book includes graduate students and researchers in the social sciences, and data analysts in criminal justice agencies. Formal mathematics is used only as necessary or in concert with more intuitive explanations.
| Author | : Gian Maria Campedelli |
| Publisher | : Taylor & Francis |
| Total Pages | : 195 |
| Release | : 2022-06-09 |
| Genre | : Computers |
| ISBN | : 1000596559 |
Machine 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 most important trends in computational criminology and quantitatively characterizing publication patterns at the intersection of AI and criminology, through a network science approach. This book also looks to the future, proposing two goals and four pathways to increase the positive societal impact of algorithmic systems in research on crime. The sixth chapter provides a survey of the methods emerging from the integration of machine learning and causal inference, showcasing their promise for answering a range of critical questions. With its transdisciplinary approach, Machine Learning for Criminology and Crime Research is important reading for scholars and students in criminology, criminal justice, sociology, and economics, as well as AI, data sciences and statistics, and computer science.
| Author | : Gian Maria Campedelli |
| Publisher | : Routledge |
| Total Pages | : 208 |
| Release | : 2022 |
| Genre | : Computers |
| ISBN | : 9781003217732 |
"Machine Learning for Criminology and Crime Research reviews the roots of the intersection between machine learning, Artificial Intelligence, 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 Artificial Intelligence (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 non-technical primer on machine learning. The following chapter reviews some of the most important trends in computational criminology and quantitatively characterizing publication patterns at the intersection of AI and criminology, through a network science approach. The book also looks to the future, proposing two goals and four pathways to increase the positive societal impact of algorithmic systems in research on crime. The final chapter provides a survey of the methods emerging from the integration of machine learning and causal inference, showcasing their promise for answering a range of critical questions. With its transdisciplinary approach, Machine Learning for Criminology and Crime Research is important reading for scholars and students in criminology, criminal justice, sociology and economics, as well as Artificial Intelligence, data sciences and statistics, and computer science"--
| Author | : Carl T. Bergstrom |
| Publisher | : Random House Trade Paperbacks |
| Total Pages | : 338 |
| Release | : 2021-04-20 |
| Genre | : Political Science |
| ISBN | : 0525509208 |
Bullshit isn’t what it used to be. Now, two science professors give us the tools to dismantle misinformation and think clearly in a world of fake news and bad data. “A modern classic . . . a straight-talking survival guide to the mean streets of a dying democracy and a global pandemic.”—Wired Misinformation, disinformation, and fake news abound and it’s increasingly difficult to know what’s true. Our media environment has become hyperpartisan. Science is conducted by press release. Startup culture elevates bullshit to high art. We are fairly well equipped to spot the sort of old-school bullshit that is based in fancy rhetoric and weasel words, but most of us don’t feel qualified to challenge the avalanche of new-school bullshit presented in the language of math, science, or statistics. In Calling Bullshit, Professors Carl Bergstrom and Jevin West give us a set of powerful tools to cut through the most intimidating data. You don’t need a lot of technical expertise to call out problems with data. Are the numbers or results too good or too dramatic to be true? Is the claim comparing like with like? Is it confirming your personal bias? Drawing on a deep well of expertise in statistics and computational biology, Bergstrom and West exuberantly unpack examples of selection bias and muddled data visualization, distinguish between correlation and causation, and examine the susceptibility of science to modern bullshit. We have always needed people who call bullshit when necessary, whether within a circle of friends, a community of scholars, or the citizenry of a nation. Now that bullshit has evolved, we need to relearn the art of skepticism.
| Author | : John McDaniel |
| Publisher | : Routledge |
| Total Pages | : 452 |
| Release | : 2021-02-25 |
| Genre | : Computers |
| ISBN | : 0429560389 |
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.
| Author | : Serena Quattrocolo |
| Publisher | : Springer Nature |
| Total Pages | : 230 |
| Release | : 2020-08-27 |
| Genre | : Law |
| ISBN | : 3030524701 |
This book discusses issues relating to the application of AI and computational modelling in criminal proceedings from a European perspective. Part one provides a definition of the topics. Rather than focusing on policing or prevention of crime – largely tackled by recent literature – it explores ways in which AI can affect the investigation and adjudication of crime. There are two main areas of application: the first is evidence gathering, which is addressed in Part two. This section examines how traditional evidentiary law is affected by both new ways of investigation – based on automated processes (often using machine learning) – and new kinds of evidence, automatically generated by AI instruments. Drawing on the comprehensive case law of the European Court of Human Rights, it also presents reflections on the reliability and, ultimately, the admissibility of such evidence. Part three investigates the second application area: judicial decision-making, providing an unbiased review of the meaning, benefits, and possible long-term effects of ‘predictive justice’ in the criminal field. It highlights the prediction of both violent behaviour, or recidivism, and future court decisions, based on precedents. Touching on the foundations of common law and civil law traditions, the book offers insights into the usefulness of ‘prediction’ in criminal proceedings.
| Author | : S. Smys |
| Publisher | : Springer Nature |
| Total Pages | : 983 |
| Release | : 2021-03-27 |
| Genre | : Technology & Engineering |
| ISBN | : 9813343052 |
This book is a collection of best selected papers presented at the International Conference on Inventive Computation and Information Technologies (ICICIT 2020), organized during 24–25 September 2020. The book includes papers in the research area of information sciences and communication engineering. The book presents novel and innovative research results in theory, methodology and applications of communication engineering and information technologies.
| Author | : J. C. Barnes |
| Publisher | : John Wiley & Sons |
| Total Pages | : 967 |
| Release | : 2021-09-08 |
| Genre | : Social Science |
| ISBN | : 1119110726 |
The Encyclopedia of RESEARCH METHODS IN CRIMINOLOGY & CRIMINAL JUSTICE The most comprehensive reference work on research designs and methods in criminology and criminal justice This Encyclopedia of Research Methods in Criminology and Criminal Justice offers a comprehensive survey of research methodologies and statistical techniques that are popular in criminology and criminal justice systems across the globe. With contributions from leading scholars and practitioners in the field, it offers a clear insight into the techniques that are currently in use to answer the pressing questions in criminology and criminal justice. The Encyclopedia contains essential information from a diverse pool of authors about research designs grounded in both qualitative and quantitative approaches. It includes information on popular datasets and leading resources of government statistics. In addition, the contributors cover a wide range of topics such as: the most current research on the link between guns and crime, rational choice theory, and the use of technology like geospatial mapping as a crime reduction tool. This invaluable reference work: Offers a comprehensive survey of international research designs, methods, and statistical techniques Includes contributions from leading figures in the field Contains data on criminology and criminal justice from Cambridge to Chicago Presents information on capital punishment, domestic violence, crime science, and much more Helps us to better understand, explain, and prevent crime Written for undergraduate students, graduate students, and researchers, The Encyclopedia of Research Methods in Criminology and Criminal Justice is the first reference work of its kind to offer a comprehensive review of this important topic.
| Author | : Tom Daems |
| Publisher | : Routledge |
| Total Pages | : 229 |
| Release | : 2020-12-31 |
| Genre | : Political Science |
| ISBN | : 1000288277 |
Criminology and Democratic Politics brings together a range of international leading experts to consider the relationship between criminology and democratic politics. How does criminology relate to democratic politics? What has been the impact of criminology on crime and justice? How can we make sense of the uses, non-uses, and abuses of criminology? Such questions are far from new, but in recent times they have moved to the centre of debate in criminology in different parts of the world. The chapters in Criminology and Democratic Politics aim to contribute to this global debate. Chapters cover a range of themes such as punishment, knowledge, and penal politics; crime, fear, and the media; democratic politics and the uses of criminological knowledge; and the public role of criminology. An accessible and compelling read, this book will appeal to students and scholars of criminology, sociology, and politics and all those interested in how criminology relates to democratic politics in modern times.
| Author | : Michael Adorjan |
| Publisher | : Taylor & Francis |
| Total Pages | : 184 |
| Release | : 2023-03-31 |
| Genre | : Philosophy |
| ISBN | : 1000853527 |
Building on the editors’ previous publication, Engaging with Ethics in International Criminological Research, this new book brings together a fresh collection of leading international scholars tackling ethical dilemmas in criminological research. Contributors address how they have experienced and addressed ethical issues in their research, and how they have balanced the benefits and harms of doing such research for both the researcher and the researched. Ethical Dilemmas in International Criminological Research draws on various issues across a range of jurisdictions and political and social contexts, including cybercrime and transgressive online actions; state and police responses to crime; the war on drugs; working with traumatised participants in criminological research; punishment and prison; and sex, sexualities, and gender. Moreover, this collection aims to offer a truly international perspective, including insights from research projects in the Global South. This book is essential reading for junior scholars just starting out with original research, as well as more seasoned researchers looking to gain insights into the challenges of criminological research in other cultural contexts. It is also instructive reading for students taking courses in criminological and social research methods.
