Predictive Policing and Artificial Intelligence

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.

這本編輯過的書籍匯集了許多世界知名學者的見解，評估了預測性警務和人工智慧（AI）作為相互關聯的政策領域的狀況。預測和AI技術正以前所未有的速度崛起。強大的數位犯罪地圖工具被用於即時識別犯罪熱點，而模式匹配和搜索演算法則在處理龐大的警察資料庫中的日益增長的數據量，以尋找可能會經歷（或犯下）犯罪的人、可能發生犯罪的地點，以及與犯罪解決能力相關的變數。面部和車輛識別攝影機正在追蹤罪犯的移動，而警察部門則根據機器學習和其他形式的預測分析制定策略。這些創新技術在英國、美國和澳大利亞等司法管轄區的現代警務中都有所應用。

AI承諾減少不必要的勞動，加快各種形式的警務工作，鼓勵警察部隊更有效地分配資源，並使警察能夠預防犯罪並保護人們免受各種未來危害。然而，預測和AI技術的承諾並不總是符合現實。它們通常存在重大弱點，成本相當高，並需要做出具有挑戰性的權衡。本書以英國、美國和澳大利亞為重點，探討了選擇架構、決策、人權、問責制和法治等主題，以及AI和預測技術在不同警務背景下的未來應用。本書以清晰直接的風格撰寫，適合警務、犯罪學、犯罪科學、社會學、計算機科學、認知心理學等領域的學生和學者，以及對AI作為當代警務特徵的出現感興趣的人。

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.

John L.M. McDaniel 是英國伍爾弗漢普頓大學社會科學、包容性和公共保護系的教師和研究人員，也是該大學法律研究中心的活躍成員。他的研究專注於警察問責、腐敗、人權以及國際合作和安全等議題。

Ken G. Pease 是英國德比大學的警務學教授。他撰寫了許多關於警務、心理學和犯罪科學的書籍。