Sharad Goel, M. Perelman, Ravi Shroff, D. Sklansky
{"title":"打击大数据时代的警察歧视","authors":"Sharad Goel, M. Perelman, Ravi Shroff, D. Sklansky","doi":"10.1525/NCLR.2017.20.2.181","DOIUrl":null,"url":null,"abstract":"The exponential growth of available information about routine police activities offers new opportunities to improve the fairness and effectiveness of police practices. We illustrate the point by showing how a particular kind of calculation made possible by modern, large-scale datasets — determining the likelihood that stopping and frisking a particular pedestrian will result in the discovery of contraband or other evidence of criminal activity — could be used to reduce the racially disparate impact of pedestrian searches and to increase their effectiveness. For tools of this kind to achieve their full potential in improving policing, though, the legal system will need to adapt. One important change would be to understand police tactics such as investigatory stops of pedestrians or motorists as programs, not as isolated occurrences. Beyond that, the judiciary will need to grow more comfortable with statistical proof of discriminatory policing, and the police will need to be more receptive to the assistance that algorithms can provide in reducing bias.","PeriodicalId":44796,"journal":{"name":"New Criminal Law Review","volume":null,"pages":null},"PeriodicalIF":0.4000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"41","resultStr":"{\"title\":\"Combatting Police Discrimination in the Age of Big Data\",\"authors\":\"Sharad Goel, M. Perelman, Ravi Shroff, D. Sklansky\",\"doi\":\"10.1525/NCLR.2017.20.2.181\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The exponential growth of available information about routine police activities offers new opportunities to improve the fairness and effectiveness of police practices. We illustrate the point by showing how a particular kind of calculation made possible by modern, large-scale datasets — determining the likelihood that stopping and frisking a particular pedestrian will result in the discovery of contraband or other evidence of criminal activity — could be used to reduce the racially disparate impact of pedestrian searches and to increase their effectiveness. For tools of this kind to achieve their full potential in improving policing, though, the legal system will need to adapt. One important change would be to understand police tactics such as investigatory stops of pedestrians or motorists as programs, not as isolated occurrences. Beyond that, the judiciary will need to grow more comfortable with statistical proof of discriminatory policing, and the police will need to be more receptive to the assistance that algorithms can provide in reducing bias.\",\"PeriodicalId\":44796,\"journal\":{\"name\":\"New Criminal Law Review\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.4000,\"publicationDate\":\"2017-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"41\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"New Criminal Law Review\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1525/NCLR.2017.20.2.181\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"New Criminal Law Review","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1525/NCLR.2017.20.2.181","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Social Sciences","Score":null,"Total":0}
Combatting Police Discrimination in the Age of Big Data
The exponential growth of available information about routine police activities offers new opportunities to improve the fairness and effectiveness of police practices. We illustrate the point by showing how a particular kind of calculation made possible by modern, large-scale datasets — determining the likelihood that stopping and frisking a particular pedestrian will result in the discovery of contraband or other evidence of criminal activity — could be used to reduce the racially disparate impact of pedestrian searches and to increase their effectiveness. For tools of this kind to achieve their full potential in improving policing, though, the legal system will need to adapt. One important change would be to understand police tactics such as investigatory stops of pedestrians or motorists as programs, not as isolated occurrences. Beyond that, the judiciary will need to grow more comfortable with statistical proof of discriminatory policing, and the police will need to be more receptive to the assistance that algorithms can provide in reducing bias.
期刊介绍:
Focused on examinations of crime and punishment in domestic, transnational, and international contexts, New Criminal Law Review provides timely, innovative commentary and in-depth scholarly analyses on a wide range of criminal law topics. The journal encourages a variety of methodological and theoretical approaches and is a crucial resource for criminal law professionals in both academia and the criminal justice system. The journal publishes thematic forum sections and special issues, full-length peer-reviewed articles, book reviews, and occasional correspondence.