Dr. Anshu Ankolekar, JMIR Correspondent
Image credit: Anshu Ankolekar
The article “The Right to Understanding in Healthcare AI” explores important tensions. Although the European Union’s AI law provides a legal basis for transparency, the technical and clinical realities of meaningful explanation remain largely undefined.
The report, written by JMIR correspondent Anshu Ankolekar, highlights that as high-risk AI systems become the standard for medical imaging and diagnosis, patients increasingly have the right to ask, “Why did the computer come to this conclusion?” However, the opacity of advanced algorithms often prevents even the most experienced clinicians from providing answers that are technically accurate and actually useful for patients.
This analysis points out several significant obstacles that prevent current legal frameworks, such as the EU AI law and GDPR, from leading to better patient care.
- Interpretability tradeoff: The most accurate AI models often operate through millions of parameters that are impossible for humans to fully track. Forcing simpler, more easily explained models can come at the expense of diagnostic accuracy, which can be in direct conflict with patient safety.
- Automation bias: Research shows that incorrect suggestions by AI can lead clinicians to incorrect diagnoses, regardless of their experience level. Descriptions made by clinicians who have already followed the algorithm may not reflect an independent clinical evaluation.
- Literacy barriers: 22% to 58% of EU citizens report difficulty understanding health information. Providing technical details about algorithmic logic often results in cognitive overload rather than informed consent.
