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; it explores themes of decision making, human rights and rule of law, as well as considering the future of the use of AI in policing.
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; it explores themes of decision making, human rights and rule of law, as well as considering the future of the use of AI in policing.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
John L.M. McDaniel teaches and researches within the University of Wolverhampton Department of Social Science, Inclusion and Public Protection and is an active member of the University's Law Research Centre. He focuses on issues of police accountability, corruption, human rights, and international cooperation and security. Ken G. Pease is a Professor in Policing at the University of Derby. He has written numerous books on policing, psychology and crime science.
Inhaltsangabe
Introduction 1.The Future of AI in Policing: Exploring the sociotechnical imaginaries Part One: Bias and Big Data 2.Predictive Policing through Risk Assessment 3.Policing, AI and Choice Architecture 4.What Big Data in Health Care Can Teach Us About Predictive Policing 5.Artificial Intelligence and Online Extremism: Challenges and Opportunities 6.Predictive Policing and Criminal Law Part Two: Police Accountability and Human Rights 7. Accountability and indeterminacy in predictive policing 8.Machine learning predictive algorithms and the policing of future crimes: governance and oversight 9.'Algorithmic impropriety' in UK policing contexts: A developing narrative? 10.Big Data Policing: Governing the Machines? 11.Decision-Making: Using technology to enhance learning in police officers Conclusion
Introduction 1.The Future of AI in Policing: Exploring the sociotechnical imaginaries Part One: Bias and Big Data 2.Predictive Policing through Risk Assessment 3.Policing, AI and Choice Architecture 4.What Big Data in Health Care Can Teach Us About Predictive Policing 5.Artificial Intelligence and Online Extremism: Challenges and Opportunities 6.Predictive Policing and Criminal Law Part Two: Police Accountability and Human Rights 7. Accountability and indeterminacy in predictive policing 8.Machine learning predictive algorithms and the policing of future crimes: governance and oversight 9.'Algorithmic impropriety' in UK policing contexts: A developing narrative? 10.Big Data Policing: Governing the Machines? 11.Decision-Making: Using technology to enhance learning in police officers Conclusion
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