The Personalization-Privacy Paradox in AI-Enabled Health Care: Managing Trust and Governance Under the European Health Data Space
Journal of Medical Internet Research ·
AI enables increasingly personalized health care, but the data required intensifies long-standing concerns about privacy, confidentiality, and trust as the European Health Data Space (EHDS) expands the primary and secondary use of health data. This viewpoint examines how the EHDS reshapes the personalization-privacy paradox in AI-enabled health care and under what conditions it can manage, rather than resolve, this paradox. Drawing on privacy calculus theory, we analyze the patient-practitioner relationship, the flow of data from primary to secondary use, and the governance mechanisms introduced by Regulation (EU) 2025/327, including data access bodies, data permits, differentiated opt-out rights, and privacy-preserving technologies. We identify 5 governance conditions: purpose-specific governance, accessible opt-out design, practitioner-mediated transparency, privacy-preserving infrastructure, and independent oversight of secondary use actors. When these conditions are met, the EHDS can sustain trust while enabling personalization. We conclude that the EHDS does not eliminate the paradox but can provide a governance architecture to manage it, depending more on implementation quality and patient engagement than on the ambition of the framework itself.