AI In Public Health Surveillance: Balancing Innovation, Privacy, And Fundamental Rights
Shanu Singh Chouhan, National Law Institute University, Bhopal
ABSTRACT
Artificial intelligence (AI) has become a central instrument of contemporary public health surveillance, powering disease-outbreak detection, syndromic monitoring, predictive epidemic modelling, contact tracing, and resource allocation. The COVID-19 pandemic accelerated the adoption of AI-enabled surveillance tools worldwide, demonstrating both their capacity to detect and contain threats faster than traditional systems and their potential to intrude upon privacy, entrench discrimination, and erode fundamental rights. This paper examines the dual character of AI in public health surveillance, tracing its major applications, the privacy and human-rights risks these applications generate, and the evolving regulatory architecture-principally the World Health Organization’s ethics guidance, the European Union’s General Data Protection Regulation and Artificial Intelligence Act, and emerging national frameworks-designed to govern them. Drawing on peer-reviewed literature, international guidance documents, and case studies of contact-tracing applications and AI-based early-warning systems such as BlueDot and HealthMap, the paper argues that innovation and rights protection are not inherently opposed but require deliberate institutional design: privacy- enhancing technologies, proportionality-based legal tests, algorithmic bias audits, transparency mechanisms, and participatory governance. The paper concludes that a rights-respecting approach to AI-enabled surveillance is not merely a constraint on innovation but a precondition for its long-term legitimacy and effectiveness.
Keywords: artificial intelligence, public health surveillance, privacy, data protection, fundamental rights, GDPR, AI Act, contact tracing, algorithmic bias
