Francesco Branda, Massimo Ciccozzi
The integration of artificial intelligence (AI) into the life sciences is radically transforming research, clinical diagnosis, and therapeutic development processes, redefining the relationship between knowledge, decision-making, and responsibility. Advanced tools, from generative models to clinical assistants such as ChatGPT Health, offer greater efficiency, predictive power, and access to data, but carry significant risks of automation bias, epistemic delegation, and loss of professional skills. This article analyzes how the extensive use of AI can threaten cognitive sovereignty, i.e., the ability of researchers and professionals to critically evaluate and contextualize information generated by algorithms. It examines the emerging regulatory landscape, with a focus on the EU Artificial Intelligence Act, Food and Drug Administration (FDA) guidelines, European Medicines Agency (EMA) Good Machine Learning Practice (GMLP) principles, and World Health Organization (WHO) recommendations, which aim to ensure human oversight, transparency, and accountability. Technological tools and training approaches are discussed to mitigate risks such as silent errors, algorithmic dependence, and skill deterioration, promoting AI integration that reinforces human judgment without replacing it. The analysis highlights that the future of life sciences will depend not only on the technical capabilities of models, but also on the critical awareness with which they are used, focusing on training, governance, and responsible AI design.