Transforming medicine: a critical analysis of the main ethical challenges in the integration of Artificial Intelligence in evidence-based medicine and personalized medicine

Abstract

Since the late last century, evidence-based medicine (EBM) has become the gold standard in clinical practice, medical training, and health policy development. However, limitations have been identified, leading to the exploration and development of emerging models, including precision medicine (or personalized medicine). Artificial intelligence (AI) has the potential to significantly transform both EBM and personalized medicine. This paper analyses the ethical considerations posed by the use of AI within the framework of EBM and personalized medicine. The issues of bias and their relationship to the principle of equity, the possibility of discrimination, and transparency and explainability closely associated with the opacity of the algorithmic black box will be analysed first. Subsequently, the problems related to data privacy and security, as well as the responsibility surrounding AI-driven decisions and professional autonomy, will be discussed. Finally, the issues linked to equity in access, informed consent, and the ethical use of genetic information will be examined.