THE COMPLEXITY OF ERASURE IN GENOMICAI: ASSESSING THE IMPLICATIONS OF UTILISATION OF GENOMIC DATA FOR AI SYSTEMS & THE RIGHT TO ERASURE UNDER INDIAN LAW

Abstract

The growing use of genomic data in artificial intelligence (AI) systems poses complex data protection challenges, particularly regarding the right to erasure. Genomic data is inherently sensitive and may reveal details about individuals and their biological families. Removing the original dataset alone may not prevent information derived from it or inferred through the trained model when such data is used to train AI models. This raises issues regarding the practical enforceability of the right to erasure, the effectiveness of machine unlearning, and the accountability of stakeholders handling genomic data. This study assess the effectiveness of India’s data protection and health-AI governance frameworks in enforcing the right to erasure after genomic data has been used for AI training. The paper examines the alignment between statutory data-protection requirements and specialized health-AI governance guidance through a doctrinal and analytical review of the Digital Personal Data Protection Act, 2023, the Indian Council of Medical Research's Ethical Guidelines for Application of Artificial Intelligence in Biomedical Research and Healthcare (2023), and the Strategy for Artificial Intelligence in Healthcare for India. It also examines the difference between source-data deletion and model-level erasure, as well as the difficulties in determining whether technical interventions sufficiently address lingering privacy hazards. Conclusively, the paper recommends a framework that aligns the Right to erasure with the technical As a result, the research recommends a six-stage evaluation framework that is rooted in Individual Autonomy and can aid in balancing innovation and Privacy.