The Friction Between Generative AI Training and Data Minimization Under the DPDP Act, 2023

Author(s)	Mr. Uday Chauhan
Country	India
Abstract	India has become a hub of technological innovation due to the exponential growth of Generative Artificial Intelligence (AI). But the operational architecture of Large Language Models (LLMs) which require ingestion of massive unfiltered datasets is fundamentally at odds with the data protection principles enshrined under the Digital Personal Data Protection (DPDP) Act, 2023. In this paper we examine the systemic tension between the data consumption requirements of generative machine learning models and the statutory requirement of “Data Minimization” under Indian law. This paper analyses the mechanics of AI ingestion vis-a-vis Section 6 of the DPDP Act and, through a comparative jurisprudence under the GDPR, explores the pitfalls of public data exemptions and demonstrates that the static regulatory framework creates an unsustainable compliance deadlock. This paper finally proposes a reconciled regulatory model with dynamic safe harbors, synthetic data standards, and AI-specific guidelines to harmonize technological advancements with fundamental privacy rights.
Field	Sociology > Administration / Law / Management
Published In	Volume 8, Issue 4, July-August 2026
Published On	2026-08-03

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