{"title":"公共部门自动化决策的四个短教学案例","authors":"Steven Strauss, Isaiah Wonnenberg","doi":"10.2139/ssrn.3904984","DOIUrl":null,"url":null,"abstract":"Much of the discussion around big data, artificial intelligence, machine learning, etc. has focused on the private sector. However, a similar evolution is also taking place in the public sector. Over the summer of 2021, we interviewed government officials, management consultants, academics, and others to better understand these trends. This paper has four short cases that can be used for teaching purposes, which document the use of automated decision-making in the public sector.","PeriodicalId":201243,"journal":{"name":"PSN: Public Administration (Development) (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Four Short Teaching Cases on Automated Decision-Making in the Public Sector\",\"authors\":\"Steven Strauss, Isaiah Wonnenberg\",\"doi\":\"10.2139/ssrn.3904984\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Much of the discussion around big data, artificial intelligence, machine learning, etc. has focused on the private sector. However, a similar evolution is also taking place in the public sector. Over the summer of 2021, we interviewed government officials, management consultants, academics, and others to better understand these trends. This paper has four short cases that can be used for teaching purposes, which document the use of automated decision-making in the public sector.\",\"PeriodicalId\":201243,\"journal\":{\"name\":\"PSN: Public Administration (Development) (Topic)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"PSN: Public Administration (Development) (Topic)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3904984\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"PSN: Public Administration (Development) (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3904984","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Four Short Teaching Cases on Automated Decision-Making in the Public Sector
Much of the discussion around big data, artificial intelligence, machine learning, etc. has focused on the private sector. However, a similar evolution is also taking place in the public sector. Over the summer of 2021, we interviewed government officials, management consultants, academics, and others to better understand these trends. This paper has four short cases that can be used for teaching purposes, which document the use of automated decision-making in the public sector.