A trustworthy AI reality-check: the lack of transparency of artificial intelligence products in healthcare.

IF 3.2 Q1 HEALTH CARE SCIENCES & SERVICES
Frontiers in digital health Pub Date : 2024-02-20 eCollection Date: 2024-01-01 DOI:10.3389/fdgth.2024.1267290
Jana Fehr, Brian Citro, Rohit Malpani, Christoph Lippert, Vince I Madai
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引用次数: 0

Abstract

Trustworthy medical AI requires transparency about the development and testing of underlying algorithms to identify biases and communicate potential risks of harm. Abundant guidance exists on how to achieve transparency for medical AI products, but it is unclear whether publicly available information adequately informs about their risks. To assess this, we retrieved public documentation on the 14 available CE-certified AI-based radiology products of the II b risk category in the EU from vendor websites, scientific publications, and the European EUDAMED database. Using a self-designed survey, we reported on their development, validation, ethical considerations, and deployment caveats, according to trustworthy AI guidelines. We scored each question with either 0, 0.5, or 1, to rate if the required information was "unavailable", "partially available," or "fully available." The transparency of each product was calculated relative to all 55 questions. Transparency scores ranged from 6.4% to 60.9%, with a median of 29.1%. Major transparency gaps included missing documentation on training data, ethical considerations, and limitations for deployment. Ethical aspects like consent, safety monitoring, and GDPR-compliance were rarely documented. Furthermore, deployment caveats for different demographics and medical settings were scarce. In conclusion, public documentation of authorized medical AI products in Europe lacks sufficient public transparency to inform about safety and risks. We call on lawmakers and regulators to establish legally mandated requirements for public and substantive transparency to fulfill the promise of trustworthy AI for health.

值得信赖的人工智能现实检查:医疗保健领域人工智能产品缺乏透明度。
值得信赖的医疗人工智能要求底层算法的开发和测试具有透明度,以识别偏差并传达潜在的伤害风险。关于如何实现医疗人工智能产品的透明度,目前已有大量指南,但尚不清楚公开信息是否能充分告知其风险。为了评估这一点,我们从供应商网站、科学出版物和欧洲EUDAMED数据库中检索了欧盟现有的14种经CE认证的II b风险类别人工智能放射产品的公开文件。我们使用自行设计的调查表,根据值得信赖的人工智能指南,报告了这些产品的开发、验证、伦理考虑和部署注意事项。我们用 0、0.5 或 1 给每个问题打分,以评定所需信息是 "不可用"、"部分可用 "还是 "完全可用"。每个产品的透明度都是根据所有 55 个问题计算得出的。透明度得分从 6.4% 到 60.9% 不等,中位数为 29.1%。主要的透明度差距包括缺少有关培训数据、伦理考虑因素和部署限制的文档。同意书、安全监控和 GDPR 合规性等伦理方面的文件很少。此外,针对不同人群和医疗环境的部署注意事项也很少见。总之,欧洲授权医疗人工智能产品的公开文件缺乏足够的公共透明度,无法告知安全性和风险。我们呼吁立法者和监管者制定法律规定的公开和实质性透明度要求,以实现值得信赖的人工智能促进健康的承诺。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
4.20
自引率
0.00%
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审稿时长
13 weeks
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