| Sumario: | This article examines the influence of Beauchamp and Childress' Principles of Biomedical Ethics—respect for patient autonomy, beneficence, non-maleficence, and justice—on bioethics and clinical practice, highlighting their longstanding role as a practical framework for ethical decision-making in healthcare. It explores the adaptation of these principles, known as principlism, for implementation in artificial intelligence (AI), particularly in medical settings, where principlism’s flexibility and transparency support algorithmic ethical reasoning better than other moral theories. The article reviews pioneering AI applications such as the MedEthEx and METHAD algorithms, which operationalize principlism to address complex ethical dilemmas, and discusses the potential and challenges of integrating principlism into generative AI models like large language models. While principlism offers a promising mid-level abstraction for guiding AI ethics, concerns remain about AI’s tendency toward post-hoc rationalization and alignment with user preferences rather than genuine ethical reasoning, underscoring the need for careful oversight as principlism enters the era of machine intelligence.
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