{"title":"Algorithmic Fairness and Educational Justice","authors":"Aaron Wolf","doi":"10.1111/edth.70029","DOIUrl":null,"url":null,"abstract":"<p>Much has been written about how to improve the fairness of AI tools for decision-making but less has been said about how to approach this new field from the perspective of philosophy of education. My goal in this paper is to bring together criteria from the general algorithmic fairness literature with prominent values of justice defended by philosophers of education. Some kinds of fairness criteria appear better suited than others for realizing these values. Considering these criteria for cases of automated decision-making in education reveals that when the aim of justice is equal respect and belonging, this is best served by using statistical definitions of fairness to constrain decision-making. By contrast, distributive aims of justice are best promoted by thinking of fairness in terms of the intellectual virtues of human decision-makers who use algorithmic tools.</p>","PeriodicalId":47134,"journal":{"name":"EDUCATIONAL THEORY","volume":"75 4","pages":"661-681"},"PeriodicalIF":0.9000,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"EDUCATIONAL THEORY","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/edth.70029","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
引用次数: 0
Abstract
Much has been written about how to improve the fairness of AI tools for decision-making but less has been said about how to approach this new field from the perspective of philosophy of education. My goal in this paper is to bring together criteria from the general algorithmic fairness literature with prominent values of justice defended by philosophers of education. Some kinds of fairness criteria appear better suited than others for realizing these values. Considering these criteria for cases of automated decision-making in education reveals that when the aim of justice is equal respect and belonging, this is best served by using statistical definitions of fairness to constrain decision-making. By contrast, distributive aims of justice are best promoted by thinking of fairness in terms of the intellectual virtues of human decision-makers who use algorithmic tools.
期刊介绍：
The general purposes of Educational Theory are to foster the continuing development of educational theory and to encourage wide and effective discussion of theoretical problems within the educational profession. In order to achieve these purposes, the journal is devoted to publishing scholarly articles and studies in the foundations of education, and in related disciplines outside the field of education, which contribute to the advancement of educational theory. It is the policy of the sponsoring organizations to maintain the journal as an open channel of communication and as an open forum for discussion.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
