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Regulating Artificial Intelligence In Healthcare: Balancing Innovation, Patient Safety, And Ethical Accountability




Soham Sandeep Joshi, LL.M., Symbiosis Law School, Pune


ABSTRACT


Artificial Intelligence (AI) is rapidly reshaping healthcare by enhancing diagnostic accuracy, enabling predictive treatment, and optimising patient monitoring. While these advancements promise efficiency and accessibility, they simultaneously expose healthcare systems to unprecedented legal and regulatory challenges. In India, the absence of binding legislation— contrasted with structured regimes such as the U.S. FDA's SaMD Action Plan, EHDS Regulation, 2025 and the EU's AI Act—has left governance fragmented and largely dependent on non-binding ethical guidelines, most notably the ICMR 2023 framework. This regulatory shortfall raises pressing concerns regarding liability for algorithmic errors, patient safety, bias mitigation, and data privacy. Through a doctrinal and comparative analysis, this research identifies the central regulatory gap in India: the over-reliance on voluntary codes without enforceable safeguards. The study argues for a risk-based, legally binding framework incorporating mandatory audits, post- market monitoring, and clear accountability rules. Ultimately, the findings underscore the imperative for India to move beyond aspirational ethics toward robust regulation that balances innovation with patient-centric protections, thereby aligning healthcare AI with both constitutional principles and global best practices.


Keywords: Artificial Intelligence in Healthcare; ICMR Guidelines; Data Protection; Algorithmic Accountability; Regulatory Framework; India



Indian Journal of Law and Legal Research

Abbreviation: IJLLR

ISSN: 2582-8878

Website: www.ijllr.com

Accessibility: Open Access

License: Creative Commons 4.0

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All research articles published in The Indian Journal of Law and Legal Research are fully open access. i.e. immediately freely available to read, download and share. Articles are published under the terms of a Creative Commons license which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

 

Disclaimer:

The opinions expressed in this publication are those of the authors. They do not purport to reflect the opinions or views of the IJLLR or its members. The designations employed in this publication and the presentation of material therein do not imply the expression of any opinion whatsoever on the part of the IJLLR.

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