每天一个应用程序能让医生远离吗? 人工智能症状检查器应用程序,根深蒂固的偏见和专业责任
1Centre of Genomics and Policy, McGill University, Montreal, QC, Canada.
Journal of medical Internet research
|June 5, 2024
概括
由人工智能驱动的症状检查应用程序提供了潜在的健康访问,但引起了对偏见和问责制的担忧. 解决这些道德和法律差距对于安全的mHealth开发和使用至关重要.
科学领域:
- 数字健康数字健康
- 医疗保健中的人工智能
- 医学伦理 医学伦理
背景情况:
- 人工智能 (AI) 越来越多地用于移动健康 (mHealth),导致AI驱动的症状检查应用程序 (AISympCheck).
- 这些应用程序存在道德和法律方面的挑战,包括偏见根深蒂固和专业问责问题.
- 随着COVID-19的流行,AISympCheck应用程序的广泛使用和潜在影响得到了凸显,比如巴比伦和Ada.
研究的目的:
- 分析与人工智能驱动的症状检查应用程序相关的伦理和法律问题.
- 检查人工智能系统中偏见是如何根深蒂固的,以及它对医疗保健不平等的影响.
- 调查应用程序间接误诊的专业问责制和责任方面的挑战.
主要方法:
- 专注分析了两个著名的mHealth应用程序,巴比伦和Ada,作为案例研究.
- 研究了人工智能训练数据中的"垃圾进来,垃圾出去"现象及其对偏见的影响.
- 评估了AISympCheck应用程序的监管环境和专业指导.
主要成果:
- 在AISympCheck应用程序中的偏见往往源于非代表性的培训数据,延续了健康差异.
- 缺乏监管和明确的指导方针,对专业的问责制和医生推提出了挑战.
- 由于应用程序数据中的人口偏差,用户可能会收到扭曲的健康评估.
结论:
- 在设计和实施AISympCheck应用程序时,需要紧急考虑法律和伦理问题.
- 专业机构必须在制定解决伦理和法律差距的指导方面发挥关键作用.
- 技术保障,中立数据培训和监管监督对于减轻偏见和确保用户在移动健康方面做出明智决策至关重要.
关键词:
应用程序应用程序应用程序申请申请表 申请表 申请表应用程序 应用程序 应用程序应用程序 应用程序 应用程序人工智能的人工智能是人工智能.偏见 偏见 偏见 偏见 偏见偏见 偏见 偏见 偏见诊断 诊断 诊断 诊断 诊断 诊断诊断 诊断 诊断 诊断 诊断 诊断伦理学 伦理学这是道德上的道德.伦理学 伦理 伦理学法律是法律,法律是法律.法律法规 法律法规 法律法规在法律上,它是合法的.移动健康 移动健康 移动健康 移动健康移动健康的移动健康手机电话 手机电话手机电话职业义务 职业义务 职业义务职业义务的职业义务.监管 监管 监管 监管 监管 监管规则 条例 条例 规章 规章 规章在安全方面,安全是安全的.进行自我诊断.自己诊断的自我诊断.症状检查器是一个症状检查器.症状检查器 症状检查器
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