{"title":"地理犯罪权证、地理空间创新和数据隐私影响","authors":"Catherine McGowan","doi":"10.1002/pra2.835","DOIUrl":null,"url":null,"abstract":"ABSTRACT Geospatial technologies collect, analyze, and produce information about earth, humans, and objects through a convergence of geographic information systems, remote sensors, and global positioning systems. A microanalysis of Google's U .S. Patent 9,420,426 Inferring a current location based on a user location history (Duleba et al., 2016) reveals how geospatial innovation employs artificial intelligence (AI) to train computer‐vision models, infer, and impute geospatial data. The technical disclosures in patents offer a view within black‐boxed digital technologies to examine potential privacy implications of datafied citizens in a networked society. In patented geospatial innovation, user agency is subverted through AI and anonymous knowledge production. Presently, the Fourth Amendment does not adequately protect citizens in a networked society. Data privacy legal cases are interpreted through a lens of inescapability (Tokson, 2020), which assumes perpetual agency to consent to sharing data. In short, agency‐centered privacy models are insufficient where AI can anonymously produce knowledge about an individual. Privacy implications are exemplified in geofence warrants—an investigative technique that searches location history to identify suspects in a geofenced region in the absence of evidence. This analysis demonstrates that digital privacy rights must expand to datafication models (Mai, 2016) centered on knowledge production.","PeriodicalId":37833,"journal":{"name":"Proceedings of the Association for Information Science and Technology","volume":"77 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Geofence Warrants, Geospatial Innovation, and Implications for Data Privacy\",\"authors\":\"Catherine McGowan\",\"doi\":\"10.1002/pra2.835\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT Geospatial technologies collect, analyze, and produce information about earth, humans, and objects through a convergence of geographic information systems, remote sensors, and global positioning systems. A microanalysis of Google's U .S. Patent 9,420,426 Inferring a current location based on a user location history (Duleba et al., 2016) reveals how geospatial innovation employs artificial intelligence (AI) to train computer‐vision models, infer, and impute geospatial data. The technical disclosures in patents offer a view within black‐boxed digital technologies to examine potential privacy implications of datafied citizens in a networked society. In patented geospatial innovation, user agency is subverted through AI and anonymous knowledge production. Presently, the Fourth Amendment does not adequately protect citizens in a networked society. Data privacy legal cases are interpreted through a lens of inescapability (Tokson, 2020), which assumes perpetual agency to consent to sharing data. In short, agency‐centered privacy models are insufficient where AI can anonymously produce knowledge about an individual. Privacy implications are exemplified in geofence warrants—an investigative technique that searches location history to identify suspects in a geofenced region in the absence of evidence. This analysis demonstrates that digital privacy rights must expand to datafication models (Mai, 2016) centered on knowledge production.\",\"PeriodicalId\":37833,\"journal\":{\"name\":\"Proceedings of the Association for Information Science and Technology\",\"volume\":\"77 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Association for Information Science and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1002/pra2.835\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Association for Information Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/pra2.835","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Social Sciences","Score":null,"Total":0}
Geofence Warrants, Geospatial Innovation, and Implications for Data Privacy
ABSTRACT Geospatial technologies collect, analyze, and produce information about earth, humans, and objects through a convergence of geographic information systems, remote sensors, and global positioning systems. A microanalysis of Google's U .S. Patent 9,420,426 Inferring a current location based on a user location history (Duleba et al., 2016) reveals how geospatial innovation employs artificial intelligence (AI) to train computer‐vision models, infer, and impute geospatial data. The technical disclosures in patents offer a view within black‐boxed digital technologies to examine potential privacy implications of datafied citizens in a networked society. In patented geospatial innovation, user agency is subverted through AI and anonymous knowledge production. Presently, the Fourth Amendment does not adequately protect citizens in a networked society. Data privacy legal cases are interpreted through a lens of inescapability (Tokson, 2020), which assumes perpetual agency to consent to sharing data. In short, agency‐centered privacy models are insufficient where AI can anonymously produce knowledge about an individual. Privacy implications are exemplified in geofence warrants—an investigative technique that searches location history to identify suspects in a geofenced region in the absence of evidence. This analysis demonstrates that digital privacy rights must expand to datafication models (Mai, 2016) centered on knowledge production.