A. Koene, Elvira Perez, S. Ceppi, Michael Rovatsos, Helena Webb, Menisha Patel, M. Jirotka, Giles Lane
{"title":"Algorithmic Fairness in Online Information Mediating Systems","authors":"A. Koene, Elvira Perez, S. Ceppi, Michael Rovatsos, Helena Webb, Menisha Patel, M. Jirotka, Giles Lane","doi":"10.1145/3091478.3098864","DOIUrl":null,"url":null,"abstract":"This paper explores the challenges around fair information access when the limits of human attention require algorithmic assistance for 'finding the diamond in the coal mountain'. While often demanded by users, the seemingly intuitive concept of fairness has proven to be very difficult to operationalise for implementation in algorithms. Here we present two pilot studies aimed at getting a better understanding of the conceptualisation of algorithmic fairness by users. The first was a multi-stakeholder focus-group discussion, the second a user experiment/questionnaire. Based on our data we arrive at a picture of fairness that is highly dependent on context and informedness of users, and possibly inherently misleading due to the implied projecting of human intentions onto an algorithmic process.","PeriodicalId":165747,"journal":{"name":"Proceedings of the 2017 ACM on Web Science Conference","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2017 ACM on Web Science Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3091478.3098864","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
This paper explores the challenges around fair information access when the limits of human attention require algorithmic assistance for 'finding the diamond in the coal mountain'. While often demanded by users, the seemingly intuitive concept of fairness has proven to be very difficult to operationalise for implementation in algorithms. Here we present two pilot studies aimed at getting a better understanding of the conceptualisation of algorithmic fairness by users. The first was a multi-stakeholder focus-group discussion, the second a user experiment/questionnaire. Based on our data we arrive at a picture of fairness that is highly dependent on context and informedness of users, and possibly inherently misleading due to the implied projecting of human intentions onto an algorithmic process.