{"title":"差别隐私在2020年人口普查中的应用纪事","authors":"V. Hotz, Joseph Salvo","doi":"10.1162/99608f92.ff891fe5","DOIUrl":null,"url":null,"abstract":"In this article, we chronicle the U.S. Census Bureau’s development of the Disclosure Avoidance System (DAS) for the publicly released products of the 2020 Census of Population. We provide a brief history of the Census Bureau’s fulfillment of its dual mission of conducting and disseminating the constitutionally mandated decennial information on the U.S. population and its promise of safeguarding the confidentiality of that information. We discuss the basis for and development of a new DAS for released data products from the 2020 Census and the evidence that emerged from various user communities on the accuracy and usability of data produced under this new DAS. We offer some assessments of this experience, the dilemmas and challenges that the Census Bureau faces for producing usable data while safeguarding the confidentiality of the information it collects, and some recommendations for addressing these challenges in the future.","PeriodicalId":73195,"journal":{"name":"Harvard data science review","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"A Chronicle of the Application of Differential Privacy to the 2020 Census\",\"authors\":\"V. Hotz, Joseph Salvo\",\"doi\":\"10.1162/99608f92.ff891fe5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this article, we chronicle the U.S. Census Bureau’s development of the Disclosure Avoidance System (DAS) for the publicly released products of the 2020 Census of Population. We provide a brief history of the Census Bureau’s fulfillment of its dual mission of conducting and disseminating the constitutionally mandated decennial information on the U.S. population and its promise of safeguarding the confidentiality of that information. We discuss the basis for and development of a new DAS for released data products from the 2020 Census and the evidence that emerged from various user communities on the accuracy and usability of data produced under this new DAS. We offer some assessments of this experience, the dilemmas and challenges that the Census Bureau faces for producing usable data while safeguarding the confidentiality of the information it collects, and some recommendations for addressing these challenges in the future.\",\"PeriodicalId\":73195,\"journal\":{\"name\":\"Harvard data science review\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Harvard data science review\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1162/99608f92.ff891fe5\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Harvard data science review","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1162/99608f92.ff891fe5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Chronicle of the Application of Differential Privacy to the 2020 Census
In this article, we chronicle the U.S. Census Bureau’s development of the Disclosure Avoidance System (DAS) for the publicly released products of the 2020 Census of Population. We provide a brief history of the Census Bureau’s fulfillment of its dual mission of conducting and disseminating the constitutionally mandated decennial information on the U.S. population and its promise of safeguarding the confidentiality of that information. We discuss the basis for and development of a new DAS for released data products from the 2020 Census and the evidence that emerged from various user communities on the accuracy and usability of data produced under this new DAS. We offer some assessments of this experience, the dilemmas and challenges that the Census Bureau faces for producing usable data while safeguarding the confidentiality of the information it collects, and some recommendations for addressing these challenges in the future.