{"title":"人工智能与医疗保健差距:膝关节放射学警示故事的教训。","authors":"Gordon Hull","doi":"10.1093/jmp/jhaf020","DOIUrl":null,"url":null,"abstract":"<p><p>Enthusiasm about the use of artificial intelligence (AI) in medicine has been tempered by concern that algorithmic systems can be unfairly biased against racially minoritized populations. This article uses work on racial disparities in knee osteoarthritis diagnoses to underline that achieving justice in the use of AI in medical imaging requires attention to the entire sociotechnical system within which it operates, rather than isolated properties of algorithms. Using AI to make current diagnostic procedures more efficient risks entrenching existing disparities; a recent algorithm points to some of the problems in current procedures while highlighting systemic normative issues that need to be addressed while designing further AI systems. The article thus contributes to a literature arguing that bias and fairness issues in AI be considered as aspects of structural inequality and injustice and to highlighting ways that AI can be helpful in making progress on these.</p>","PeriodicalId":47377,"journal":{"name":"Journal of Medicine and Philosophy","volume":" ","pages":""},"PeriodicalIF":1.9000,"publicationDate":"2025-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"AI and Healthcare Disparities: Lessons from a Cautionary Tale in Knee Radiology.\",\"authors\":\"Gordon Hull\",\"doi\":\"10.1093/jmp/jhaf020\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Enthusiasm about the use of artificial intelligence (AI) in medicine has been tempered by concern that algorithmic systems can be unfairly biased against racially minoritized populations. This article uses work on racial disparities in knee osteoarthritis diagnoses to underline that achieving justice in the use of AI in medical imaging requires attention to the entire sociotechnical system within which it operates, rather than isolated properties of algorithms. Using AI to make current diagnostic procedures more efficient risks entrenching existing disparities; a recent algorithm points to some of the problems in current procedures while highlighting systemic normative issues that need to be addressed while designing further AI systems. The article thus contributes to a literature arguing that bias and fairness issues in AI be considered as aspects of structural inequality and injustice and to highlighting ways that AI can be helpful in making progress on these.</p>\",\"PeriodicalId\":47377,\"journal\":{\"name\":\"Journal of Medicine and Philosophy\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2025-09-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Medicine and Philosophy\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1093/jmp/jhaf020\",\"RegionNum\":3,\"RegionCategory\":\"哲学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ETHICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Medicine and Philosophy","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/jmp/jhaf020","RegionNum":3,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ETHICS","Score":null,"Total":0}
AI and Healthcare Disparities: Lessons from a Cautionary Tale in Knee Radiology.
Enthusiasm about the use of artificial intelligence (AI) in medicine has been tempered by concern that algorithmic systems can be unfairly biased against racially minoritized populations. This article uses work on racial disparities in knee osteoarthritis diagnoses to underline that achieving justice in the use of AI in medical imaging requires attention to the entire sociotechnical system within which it operates, rather than isolated properties of algorithms. Using AI to make current diagnostic procedures more efficient risks entrenching existing disparities; a recent algorithm points to some of the problems in current procedures while highlighting systemic normative issues that need to be addressed while designing further AI systems. The article thus contributes to a literature arguing that bias and fairness issues in AI be considered as aspects of structural inequality and injustice and to highlighting ways that AI can be helpful in making progress on these.
期刊介绍:
This bimonthly publication explores the shared themes and concerns of philosophy and the medical sciences. Central issues in medical research and practice have important philosophical dimensions, for, in treating disease and promoting health, medicine involves presuppositions about human goals and values. Conversely, the concerns of philosophy often significantly relate to those of medicine, as philosophers seek to understand the nature of medical knowledge and the human condition in the modern world. In addition, recent developments in medical technology and treatment create moral problems that raise important philosophical questions. The Journal of Medicine and Philosophy aims to provide an ongoing forum for the discussion of such themes and issues.