Protecting Personal Medical and Health Information in the Era of Generative Artificial Intelligence_Vol. 3 No. 5 (JEL 2026)_Journal of Economics and Law (ISSN: 3005-5768)

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Protecting Personal Medical and Health Information in the Era of Generative Artificial Intelligence

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DOI: https://doi.org/10.62517/jel.202614505

Author(s)

Shan Chen

Affiliation(s)

Xinjiang University of Finance and Economics, Urumqi, Xinjiang, China

Abstract

Generative artificial intelligence is increasingly used in assisted consultation, record generation, image interpretation, and health advice, shifting personal medical and health information from closed processing inside medical institutions to large-scale circulation across multiple actors and scenarios. Such information is sensitive personal information under the Personal Information Protection Law, carrying personality interests that can rarely be restored once infringed. This Article asks how the existing normative system can accommodate the logic of large models in medical settings. The study adopts a doctrinal and typological method, tracing the full processing cycle of corpus aggregation, training, interactive use, and data feedback. It then reviews the applicable norms layer by layer, drawing on comparative experience under the European Union's General Data Protection Regulation and Artificial Intelligence Act. The findings show that rules resting on informed consent as the legal basis, anonymisation as the risk-blocking mechanism, and tort damages as the ex post remedy face structural difficulty: separate consent cannot be obtained from every subject, purpose limitation and minimum necessity fail to constrain cross-scenario reuse, and de-identified data remain exposed to re-identification. Protection must therefore shift from prior consent to risk-based governance of the entire process.

Keywords

Generative Artificial Intelligence; Medical and Health Information; Sensitive Personal Information; Informed Consent; Risk-Based Governance

References

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