{"title":"人工智能应用于乳腺疾病的伦理和哲学","authors":"David Casacuberta","doi":"10.1016/j.senol.2024.100656","DOIUrl":null,"url":null,"abstract":"<div><div>This article addresses the ethical challenges of using AI in breast pathology detection, highlighting that algorithmic reliability is not sufficient without fairness. Based on Rawls' ideas of fairness, it discusses biases in data and algorithms that may affect accuracy in different populations. Furthermore, it criticizes dataism and proposes an approach that integrates ethical considerations into the development of medical AI applications from the outset.</div></div>","PeriodicalId":38058,"journal":{"name":"Revista de Senologia y Patologia Mamaria","volume":"38 2","pages":"Article 100656"},"PeriodicalIF":0.2000,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Ética y filosofía de la inteligencia artificial aplicada a la enfermedad mamaria\",\"authors\":\"David Casacuberta\",\"doi\":\"10.1016/j.senol.2024.100656\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This article addresses the ethical challenges of using AI in breast pathology detection, highlighting that algorithmic reliability is not sufficient without fairness. Based on Rawls' ideas of fairness, it discusses biases in data and algorithms that may affect accuracy in different populations. Furthermore, it criticizes dataism and proposes an approach that integrates ethical considerations into the development of medical AI applications from the outset.</div></div>\",\"PeriodicalId\":38058,\"journal\":{\"name\":\"Revista de Senologia y Patologia Mamaria\",\"volume\":\"38 2\",\"pages\":\"Article 100656\"},\"PeriodicalIF\":0.2000,\"publicationDate\":\"2024-12-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Revista de Senologia y Patologia Mamaria\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0214158224000847\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"OBSTETRICS & GYNECOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Revista de Senologia y Patologia Mamaria","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0214158224000847","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"OBSTETRICS & GYNECOLOGY","Score":null,"Total":0}
Ética y filosofía de la inteligencia artificial aplicada a la enfermedad mamaria
This article addresses the ethical challenges of using AI in breast pathology detection, highlighting that algorithmic reliability is not sufficient without fairness. Based on Rawls' ideas of fairness, it discusses biases in data and algorithms that may affect accuracy in different populations. Furthermore, it criticizes dataism and proposes an approach that integrates ethical considerations into the development of medical AI applications from the outset.