Integration of Generative Artificial Intelligence in Medicine - First Steps Toward an Ethical Risk Management Methodology

Abstract

The integration of Generative Artificial Intelligence into clinical processes requires addressing ethical aspects and inherent risks, contributing not only to the automation of these processes but also to the ongoing development of personalized medicine. The generation of complex diagnostic and personalized treatment solutions must be carried out in accordance with deontological norms and ethical standards, aimed at ensuring the protection of patient autonomy and safety. The development of an architectural framework for the identification of pathologies and the provision of treatment scenarios must ensure both the efficiency of the solutions offered and their compliance with ethical standards, involving the creation of a set of rules and practices that encourage interdisciplinary collaboration between experts in technology, medicine, and law. The fundamental principles that facilitate the integration of emerging technologies into clinical processes promote patient autonomy, decision-making transparency, and clinical responsibility. (Abstract)

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