{"title":"Themes in data mining, big data, and crime analytics","authors":"G. Oatley","doi":"10.1002/widm.1432","DOIUrl":null,"url":null,"abstract":"This article examines the impact of new AI‐related technologies in data mining and big data on important research questions in crime analytics. Because the field is so broad, the review focuses on a selection of the most important topics. Challenges for information management, and in turn law and society, include: AI‐powered predictive policing; big data for legal and adversarial decisions; bias using big data and analytics in profiling and predicting criminality; forecasting crime risk and crime rates; and, regulating AI systems.","PeriodicalId":48970,"journal":{"name":"Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery","volume":"431 1","pages":""},"PeriodicalIF":6.4000,"publicationDate":"2021-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1002/widm.1432","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 17
Abstract
This article examines the impact of new AI‐related technologies in data mining and big data on important research questions in crime analytics. Because the field is so broad, the review focuses on a selection of the most important topics. Challenges for information management, and in turn law and society, include: AI‐powered predictive policing; big data for legal and adversarial decisions; bias using big data and analytics in profiling and predicting criminality; forecasting crime risk and crime rates; and, regulating AI systems.
期刊介绍：
The goals of Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery (WIREs DMKD） are multifaceted. Firstly, the journal aims to provide a comprehensive overview of the current state of data mining and knowledge discovery by featuring ongoing reviews authored by leading researchers. Secondly, it seeks to highlight the interdisciplinary nature of the field by presenting articles from diverse perspectives, covering various application areas such as technology, business, healthcare, education, government, society, and culture. Thirdly, WIREs DMKD endeavors to keep pace with the rapid advancements in data mining and knowledge discovery through regular content updates. Lastly, the journal strives to promote active engagement in the field by presenting its accomplishments and challenges in an accessible manner to a broad audience. The content of WIREs DMKD is intended to benefit upper-level undergraduate and postgraduate students, teaching and research professors in academic programs, as well as scientists and research managers in industry.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
