Abigale Stangl, Kristina Shiroma, Bo Xie, K. Fleischmann, D. Gurari
{"title":"Visual Content Considered Private by People Who are Blind","authors":"Abigale Stangl, Kristina Shiroma, Bo Xie, K. Fleischmann, D. Gurari","doi":"10.1145/3373625.3417014","DOIUrl":null,"url":null,"abstract":"We present an empirical study into the visual content people who are blind consider to be private. We conduct a two-stage interview with 18 participants that identifies what they deem private in general and with respect to their use of services that describe their visual surroundings based on camera feeds from their personal devices. We then describe a taxonomy of private visual content that is reflective of our participants’ privacy-related concerns and values. We discuss how this taxonomy can benefit services that collect and sell visual data containing private information so such services are better aligned with their users.","PeriodicalId":433618,"journal":{"name":"Proceedings of the 22nd International ACM SIGACCESS Conference on Computers and Accessibility","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 22nd International ACM SIGACCESS Conference on Computers and Accessibility","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3373625.3417014","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
We present an empirical study into the visual content people who are blind consider to be private. We conduct a two-stage interview with 18 participants that identifies what they deem private in general and with respect to their use of services that describe their visual surroundings based on camera feeds from their personal devices. We then describe a taxonomy of private visual content that is reflective of our participants’ privacy-related concerns and values. We discuss how this taxonomy can benefit services that collect and sell visual data containing private information so such services are better aligned with their users.