The Architecture of Trust: A Framework for Verifiable Identity in Global Health AI Ecosystems

Abstract

With the digitalization of health care came an unprecedented volume of health data that could revolutionize the field of artificial intelligence (AI) for diagnostics, treatment and population health management. Nevertheless, vulnerabilities in health data have emerged as those very properties that make it valuable, its sensitivity, its identifiability, and its mobility across borders, make it vulnerable to misuse, breaches, and loss of public trust. The idea of verifiable identity is not just a technical or engineering problem, it is an architectural problem about how to design an architectural system that is verifiable, useful and beneficial for privacy, across jurisdictions, and most importantly, built into the system, not an add-on. Inspired by the development of self-sovereign identity (SSI), decentralized identifiers (DIDs), verifiable credentials (VCs), and the latest momentum in world health organizations like the World Health Organization (WHO), OECD and the European Health Data Space (EHDS), this paper presents a multi-layered identity architecture for global health AI ecosystems. The framework addresses three major challenges: privacy-utility paradox, interoperability-sovereignty dilemma, and equity-access gap. I think there's a way to make health AI about trust, and that has to be intentional – with deliberate efforts to include cryptographic verification, participatory governance and human-centred design.