The Right To Be Forgotten In The Age Of Generative AI: Legal Frameworks, Technical Realities, And Reform Imperatives
R. Priyanga, LL.M, SRM University, Chengalpattu, KTR Campus
ABSTRACT
The right to be forgotten (RTBF) enshrined in Article 17 of the General Data Protection Regulation (GDPR) and partially recognised under India's Digital Personal Data Protection Act, 2023 (DPDPA) was conceived in an era of structured databases and searchable indexes. Generative artificial intelligence (AI) systems, including large language models (LLMs), diffusion models, and multimodal foundation models, have fundamentally destabilised the operative assumptions of this right. Unlike conventional databases, generative AI systems do not merely store data they learn from it, compress it into billions of model parameters, and generate outputs that may reproduce, infer, or reconstruct personal information in unpredictable ways. This paper critically examines the legal, technical, and normative dimensions of the RTBF as applied to generative AI systems. It analyses the adequacy of the GDPR's erasure regime, India's nascent DPDPA framework, and global regulatory responses including recent amendments and legislative proposals. Through landmark case law including Google Spain, NT1 & NT2 v. Google, and emerging AI-specific proceedings the paper maps the widening gap between the legal aspiration of erasure and its technical achievability in AI systems. The paper concludes with concrete reform recommendations for regulators, legislators, and AI developers to operationalise a meaningful RTBF in the generative AI era.
Keywords: Right to Be Forgotten, Generative AI, Large Language Models, GDPR Article 17, DPDPA 2023, Machine Unlearning, Data Erasure, Privacy Law, AI Regulation, Right to Erasure
