: 10.56472/25835238/IRJEMS-V4I9P105
Abdullah Mazharuddin Khaja, Aftab Tariq, Michidmaa Arikhad, Tamoor Ali Sadiq. "The HIPAA Singularity: Reconciling Artificial Intelligence, Cybersecurity, and Patient Rights in the U.S. Healthcare Legal Framework" International Research Journal of Economics and Management Studies, Vol. 4, No. 9, pp. 46-54, 2025. Crossref. http://doi.org/10.56472/25835238/IRJEMS-V4I9P105
The integration of artificial intelligence (AI) into the U.S. healthcare system promises transformative benefits, including enhanced diagnostics, improved operational efficiency, and more personalized treatments. However, these advances amplify persistent concerns surrounding patient privacy, cybersecurity vulnerabilities, and autonomy. The Health Insurance Portability and Accountability Act of 1996 (HIPAA) remains the primary statutory safeguard for medical information; however, its definitions and implementation frameworks were designed for a pre-AI, pre-cloud computing environment. This paper investigates how HIPAA can adapt to address the intersecting challenges of AI-driven medical innovation and escalating cybersecurity threats while upholding patient rights. Drawing on interdisciplinary legal, technical, and ethical literature, as well as empirical breach data, we highlight systemic gaps. Analysis of federal reporting reveals that hacking incidents accounted for nearly 80% of healthcare data breaches in 2023, with exposed records escalating from 41 million in 2019 to more than 276 million in 2024. Additionally, a 2025 survey of U.S. health systems demonstrated universal adoption of generative AI for clinical documentation, contrasted with lower performance in imaging and sepsis detection. These findings underscore an urgent need for regulatory modernization. We argue that HIPAA must evolve to include AI-specific provisions, mandate robust cybersecurity controls, and strengthen patient consent mechanisms. Proposed reforms include statutory amendments introducing algorithmic accountability, mandatory encryption standards, transparent de-identification practices, and oversight mechanisms designed to balance innovation with equity. Without proactive legal reform, the convergence of AI deployment and cyber vulnerabilities risks eroding public trust and hindering the ethical and sustainable integration of AI in healthcare.
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