{"title":"Risk","authors":"M. Gray","doi":"10.1080/09332480.2022.2145134","DOIUrl":null,"url":null,"abstract":"Should different people be treated equally or should, as insurers tell us, different people be treated differently? Is discrimination bad, or is it good? Does today’s reliance on machine-generated algorithms to turn risk into measurable uncertainty differ in essence from trusting the actuarial tables generated by de Moivre from a London coffee house? Do legal regulations assure fair balance of the costs and benefits? What about inclusive social insurance?","PeriodicalId":88226,"journal":{"name":"Chance (New York, N.Y.)","volume":"27 1","pages":"36 - 39"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chance (New York, N.Y.)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/09332480.2022.2145134","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Should different people be treated equally or should, as insurers tell us, different people be treated differently? Is discrimination bad, or is it good? Does today’s reliance on machine-generated algorithms to turn risk into measurable uncertainty differ in essence from trusting the actuarial tables generated by de Moivre from a London coffee house? Do legal regulations assure fair balance of the costs and benefits? What about inclusive social insurance?