{"title":"Reflexive Practices in Software Engineering","authors":"Alicia E. Boyd","doi":"10.1109/FairWare59297.2023.00006","DOIUrl":null,"url":null,"abstract":"Software plays a critical role in our daily lives, providing automated support for various tasks in various domains. Behind many of the decisions that modern software makes is a data-driven infrastructure that attempts to create equitable, unbiased decisions. However, numerous examples exist of data-driven software perpetuating societal inequities and further marginalizing populations. How do we attend to software fairness? What are the best approaches for software engineers to be more conscious of the harmful impacts on the most vulnerable within our communities? Prior work recommends new tools to resolve the unfair and biased outcomes; however, the issue of biased inequitable software technology is an interdisciplinary problem that we can no longer solely depend on technical solutions. Instead, we need to incorporate interdisciplinary methods to help address the inequity of software technology. This position paper introduces reflexivity from the social science literature to motivate and encourage software engineers to integrate reflexive practices throughout the entirety of the software engineering process.","PeriodicalId":169742,"journal":{"name":"2023 IEEE/ACM International Workshop on Equitable Data & Technology (FairWare)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE/ACM International Workshop on Equitable Data & Technology (FairWare)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FairWare59297.2023.00006","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
Software plays a critical role in our daily lives, providing automated support for various tasks in various domains. Behind many of the decisions that modern software makes is a data-driven infrastructure that attempts to create equitable, unbiased decisions. However, numerous examples exist of data-driven software perpetuating societal inequities and further marginalizing populations. How do we attend to software fairness? What are the best approaches for software engineers to be more conscious of the harmful impacts on the most vulnerable within our communities? Prior work recommends new tools to resolve the unfair and biased outcomes; however, the issue of biased inequitable software technology is an interdisciplinary problem that we can no longer solely depend on technical solutions. Instead, we need to incorporate interdisciplinary methods to help address the inequity of software technology. This position paper introduces reflexivity from the social science literature to motivate and encourage software engineers to integrate reflexive practices throughout the entirety of the software engineering process.