{"title":"基于人工智能的缓刑主体分类研究——以成人再犯风险评估工具kprai为例","authors":"Hye Hyun Hahm, Jang wook Lee","doi":"10.25277/kcpr.2023.19.3.167","DOIUrl":null,"url":null,"abstract":"TAs a research method, a literature study was conducted focusing on the 'Recidivism Risk Assessment Tool for Adults Subject to Probation' (KPRAI-R), which is used by the Crime Prevention Policy Bureau of the Ministry of Justice. In particular, the classification of probation subjects was divided into 'initial classification' and 'reclassification', and the limitations of each were derived, and the necessity of using artificial intelligence was divided into initial classification and reclassification and considered. Through this, it was proposed to improve the initial classification and reclassification through the establishment of an 'artificial intelligence (AI)-based automatic classification system'.
 As for the specific improvement measures, first, in relation to the initial classification, ① a more sophisticated AI-based classification system was derived by combining the information analyzed during the initial classification with the evaluation method of the recidivism risk assessment tool (KPRAI-R), ② the career and A plan to use artificial intelligence to minimize the deviation according to inclination and expertise was presented. Second, in relation to reclassification, ① prepare an artificial intelligence-based automatic reclassification system based on post-mortem information analysis after the start of probation, ② prepare an alarm system to automatically recognize the risk of recidivism and prevent recidivism by analyzing additional information collected during probation presented.","PeriodicalId":246265,"journal":{"name":"Korean Association of Criminal Psychology","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A study on the classification of probation subjects using artificial intelligence(AI): Focusing on the Adult Recidivism Risk Assessment Tool(KPRAI-R)\",\"authors\":\"Hye Hyun Hahm, Jang wook Lee\",\"doi\":\"10.25277/kcpr.2023.19.3.167\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"TAs a research method, a literature study was conducted focusing on the 'Recidivism Risk Assessment Tool for Adults Subject to Probation' (KPRAI-R), which is used by the Crime Prevention Policy Bureau of the Ministry of Justice. In particular, the classification of probation subjects was divided into 'initial classification' and 'reclassification', and the limitations of each were derived, and the necessity of using artificial intelligence was divided into initial classification and reclassification and considered. Through this, it was proposed to improve the initial classification and reclassification through the establishment of an 'artificial intelligence (AI)-based automatic classification system'.
 As for the specific improvement measures, first, in relation to the initial classification, ① a more sophisticated AI-based classification system was derived by combining the information analyzed during the initial classification with the evaluation method of the recidivism risk assessment tool (KPRAI-R), ② the career and A plan to use artificial intelligence to minimize the deviation according to inclination and expertise was presented. Second, in relation to reclassification, ① prepare an artificial intelligence-based automatic reclassification system based on post-mortem information analysis after the start of probation, ② prepare an alarm system to automatically recognize the risk of recidivism and prevent recidivism by analyzing additional information collected during probation presented.\",\"PeriodicalId\":246265,\"journal\":{\"name\":\"Korean Association of Criminal Psychology\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-09-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Korean Association of Criminal Psychology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.25277/kcpr.2023.19.3.167\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Korean Association of Criminal Psychology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.25277/kcpr.2023.19.3.167","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A study on the classification of probation subjects using artificial intelligence(AI): Focusing on the Adult Recidivism Risk Assessment Tool(KPRAI-R)
TAs a research method, a literature study was conducted focusing on the 'Recidivism Risk Assessment Tool for Adults Subject to Probation' (KPRAI-R), which is used by the Crime Prevention Policy Bureau of the Ministry of Justice. In particular, the classification of probation subjects was divided into 'initial classification' and 'reclassification', and the limitations of each were derived, and the necessity of using artificial intelligence was divided into initial classification and reclassification and considered. Through this, it was proposed to improve the initial classification and reclassification through the establishment of an 'artificial intelligence (AI)-based automatic classification system'.
As for the specific improvement measures, first, in relation to the initial classification, ① a more sophisticated AI-based classification system was derived by combining the information analyzed during the initial classification with the evaluation method of the recidivism risk assessment tool (KPRAI-R), ② the career and A plan to use artificial intelligence to minimize the deviation according to inclination and expertise was presented. Second, in relation to reclassification, ① prepare an artificial intelligence-based automatic reclassification system based on post-mortem information analysis after the start of probation, ② prepare an alarm system to automatically recognize the risk of recidivism and prevent recidivism by analyzing additional information collected during probation presented.