Health policy transparency on artificial intelligence

In the context of profound digital transformations that mark healthcare systems globally, artificial intelligence (AI) has become an essential tool in supporting clinical research, therapeutic decisions and the optimization of medical processes. Although the technological promise of AI is substantial, its implementation generates a series of essential challenges, among which the lack of transparency, the difficulties of explainability of algorithmic decisions and the risk of bias stand out. Transparency is thus emerging not only as a technical requirement, but as an ethical and normative principle, essential for maintaining public trust, protecting patients' rights and ensuring responsible technology governance. According to the European Commission (2021), the transparency of an AI system implies its ability to provide clear and intelligible explanations of the logic of automated decisions, along with the traceability of decision-making processes and the data used. In this sense, transparency implies not only technological explainability, but also auditability, clearly defined responsibility and the active participation of all actors involved in the life cycle of AI systems: developers, medical professionals and patients. This study brings together the findings of several recent articles to explore the transparency of artificial intelligence (AI) in public health policies. The analysis highlights both convergences and differences in approach, offering an integrated perspective on how transparency is understood and applied in this field. Key themes such as accountability, equity and trust in AI systems are outlined, alongside contrasts between technical and holistic views of implementation. The study proposes a structured synthesis of the current context and suggests future directions for research and policy development in the field of ethical use of artificial intelligence in health.