改善人工智能对健康公平影响的策略:范围审查
Carl Thomas Berdahl1,2,3, Lawrence Baker1, Sean Mann1
1RAND Corporation, Santa Monica, CA, United States.
JMIR AI
|June 14, 2024
概括
医疗保健中的人工智能 (AI) 可以加剧不平等. 本次审查确定了18个健康公平问题和15个战略,强调数据质量,透明度和社区参与,以确保公平的AI应用程序开发和部署.
科学领域:
- 医疗信息学 医疗信息学
- 人工智能的人工智能
- 健康 公平 研究 健康 公平 研究
背景情况:
- 新兴的人工智能 (AI) 应用程序可以改善健康状况,但有可能使现有的不平等状况延续或恶化.
- 了解和减轻这些风险对于公平的医疗保健服务至关重要.
研究的目的:
- 综合审查与医疗保健中人工智能应用相关的健康公平问题.
- 确定和综合拟议的战略,以解决这些股权问题.
主要方法:
- 在多个数据库 (PubMed,科学网,IEEE Xplore等) 进行系统的文献搜索. 和灰色文献 (FDA,临床试验.gov).
- 纳入标准:确定了健康人工智能的公平问题和相应的战略.
- 使用4步人工智能应用框架 (上下文,数据,模型,部署) 组织了公平问题,并将问题映射到战略中.
主要成果:
- 从660份文件中确定了18个不同的健康公平问题和15个策略.
- 最常见的问题源于数据特征和模型设计.
- 关键策略包括提高数据质量/数量,评估差异,提高透明度,社区参与和改善治理.
结论:
- 为参与规划,开发和实施的利益相关者提供了人工智能公平问题和战略的映射.
- 建议开发商制定以股权为重点的检查清单,并考虑FDA等监管机构的强制性要求.
- 承认未发表的知识的潜力超出了本在线文献综述的范围.
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