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Algorithmic Due Process: Reimagining Natural Justice For AI-Assisted International Arbitration

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Adv. Mrunal Dhamale, LL.M.


ABSTRACT


Artificial intelligence has moved from the periphery of international arbitration to its working core, assisting counsel in document review and legal research, powering predictive analytics, and increasingly shaping the drafting of submissions and even the reasoning of awards. This article argues that the twin pillars of natural justice the right to be heard (audi alteram partem) and the rule against bias (nemo judex in causa sua) cannot simply be transplanted onto algorithmic processes without conceptual renovation. Drawing on the arbitration-specific soft law that has crystallised since 2024, the enforcement framework of the New York Convention and the UNCITRAL Model Law (and its Indian counterpart, the Arbitration and Conciliation Act 1996), and the wider literature on algorithmic contestability, it develops a model of algorithmic due process: a reframing of procedural fairness around explainability, disclosure, contestability and the non-delegability of the arbitral mandate. The article maps where AI most acutely strains fairness opacity, informational asymmetry, improper delegation, confidentiality and enforcement risk and proposes a principled architecture, anchored in a human-in-command standard, capable of preserving both the legitimacy and the enforceability of AI-assisted awards.


Keywords: international arbitration; artificial intelligence; natural justice; due process; algorithmic contestability; reasoned award; enforceability



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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