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Algorithmic Accountability By The Back Door: The Significant Data Fiduciary Due Diligence Mandate As India's De Facto AI Governance Instrument




Mr. Aryan Verma, University of Allahabad


ABSTRACT


India has currently decided not to establish a specific law for artificial intelligence. The India AI Governance Guidelines, released by the Ministry of Electronics and Information Technology on November 5, 2025, indicate this choice for a lighter, voluntary framework based on existing laws instead of a comprehensive statute like the one adopted by the European Union. Yet just nine days later, the same government announced the Digital Personal Data Protection Rules, 2025, whose Rule 13(3) imposes a binding duty on Significant Data Fiduciaries to ensure the algorithmic software they deploy does not pose a likely risk to the rights of Data Principals. This article argues that Rule 13(3), though framed as an incidental data protection obligation, functions in practice as India's first binding algorithmic accountability provision. It traces the provision's scope and enforcement design, places it alongside the voluntary AI Guidelines and the risk-tiered EU AI Act, and identifies four gaps in the current framework: the absence of risk classification, a narrow trigger confined to notified fiduciaries and personal data, a due diligence standard that speaks to the regulator rather than the individual, and the lack of any right for an affected person to know that a decision was automated. It closes with suggestions that could be implemented through delegated rule-making, without the need for fresh legislation.


Keywords: Digital Personal Data Protection Rules, 2025; Significant Data Fiduciary; algorithmic accountability; artificial intelligence governance; automated decision-making.



Indian Journal of Law and Legal Research

Abbreviation: IJLLR

ISSN: 2582-8878

Website: www.ijllr.com

Accessibility: Open Access

License: Creative Commons 4.0

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All research articles published in The Indian Journal of Law and Legal Research are fully open access. i.e. immediately freely available to read, download and share. Articles are published under the terms of a Creative Commons license which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

 

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The opinions expressed in this publication are those of the authors. They do not purport to reflect the opinions or views of the IJLLR or its members. The designations employed in this publication and the presentation of material therein do not imply the expression of any opinion whatsoever on the part of the IJLLR.

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