EXPLAINABLE ARTIFICIAL INTELLIGENCE (XAI) IN DIGITAL HEALTH: TENSIONS BETWEEN ALGORITHMIC TRANSPARENCY, INTELLECTUAL PROPERTY, AND ETHICS OF CARE

Abstract

The incorporation of artificial intelligence (AI) in digital health has increased the efficiency and analytical capacity of care systems, but has also intensified ethical, legal, and social challenges associated with algorithmic opacity. This article aims to critically analyze the tensions between algorithmic transparency, intellectual property, and the ethics of care in the context of Explainable Artificial Intelligence (XAI) applied to digital health. It is a critical theoretical essay, based on an integrative review of the scientific literature and a documentary analysis of national and international regulatory frameworks published between 2021 and 2026. The approach adopted is interdisciplinary, articulating contributions from public health, bioethics, law, and science and technology studies. The results indicate that XAI is a central condition for clinical trust, patient safety, and professional autonomy, especially in high-risk applications, while also highlighting structural conflicts with intellectual property protection regimes, notably the use of trade secrets. It is concluded that the adoption of intermediate governance mechanisms, such as layered transparency, independent audits, and meaningful human oversight, is essential to reconcile technological innovation, protection of fundamental rights, and ethical integrity in healthcare.