Юрист ахборотномаси Volume 7 Issue 5 (2025) · pp. 98-104
LEGAL AND ETHICAL FOUNDATIONS FOR THE USE OF MEDICAL DATA IN ARTIFICIAL INTELLIGENCE SYSTEMS
ЮСУПОВА, Фарингиз
Abstract
This article analyzes the legal and ethical foundations of using medical data within artificial intelligence (AI) systems amid the rapid development of digital technologies in the healthcare sector. It explores new forms of legal relationships emerging from the integration of AI into medicine, along with issues of data security and human rights protection. Artificial intelligence is increasingly utilized in healthcare for early disease detection, clinical decision support, epidemiological analysis, and automation of treatment planning. However, the large-scale use of medical data gives rise to complex challenges related to privacy protection, lawfulness of data processing, patientsʼ informed consent, and algorithmic error risks. Therefore, the article examines legal regulation mechanisms, ethical principles, and international experience in handling medical information in AI-based systems from a comparative legal perspective. The research analyzes both international and national regulatory frameworks, including the European Unionʼs General Data Protection Regulation (GDPR), the U.S. Health Insurance Portability and Accountability Act (HIPAA), the Oviedo Convention, as well as the United Nations General Assembly Resolution “The Right to Privacy in the Digital Age” (2013) and the Laws of the Republic of Uzbekistan “On Personal Data” and “On the Protection of Citizensʼ Health. ”The author identifies patientsʼ informed consent, data confidentiality, algorithmic transparency, and non-discrimination as central ethical principles for the responsible use of AI systems. The article also discusses issues of legal liability, information security, the shared responsibility of healthcare professionals and AI developers, and the introduction of algorithmic audit systems to ensure the safety and accountability of medical AI applications.
artificial intelligence; medical data; legal foundations; ethical principles; privacy; data protection; international standards; medical data security; algorithmic transparency
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