Analyzes Saudi Arabia's Personal Data Protection Law for AI in healthcare, suggesting reforms for accountability and innovation.
Artificial intelligence is transforming healthcare, but it creates a fundamental regulatory tension. AI systems derive their clinical value from large-scale, multipurpose, and longitudinal use of health data precisely the processing that robust data protection law is designed to constrain. This article argues that Saudi Arabia's Personal Data Protection Law (PDPL) creates a protective-but-underspecified environment for healthcare AI. Its consent-first architecture, broad definition of sensitive health data, and accountability mechanisms provide a strong privacy foundation that, in several respects, exceeds the European Union's General Data Protection Regulation (GDPR). Yet the PDPL lacks the research derogations, standardised transfer instruments, and AI-specific interpretive guidance needed to enable data-intensive AI development. Using doctrinal and comparative legal methods, the article examines four dimensions—consent, data minimisation and retention, cross-border transfers, and accountability for automated decision-making—against the GDPR, the EU AI Act (Regulation (EU) 2024/1689), and the European Health Data Space Regulation. It finds a normative asymmetry: the PDPL is formally more protective but structurally less enabling of the data uses on which clinical AI depends. The article proposes four reforms: research derogations via amended Implementing Regulations; standardised transfer instruments; sector-specific guidance on automated clinical decisions; and an integrated governance framework grounded in Islamic bioethical principles and Vision 2030.
No takes yet. Share an insight, caveat, or question.
Dhali et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: