Can technology augment order writing capacity at regulators?

Natasha Aggarwal, Satyavrat Bondre (), Amrutha Srinivasa Desikan, Bhavin Patel and Dipyaman Sanyal ()
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Satyavrat Bondre: Dono Consulting

No 16, Working Papers from Trustbridge Rule of Law Foundation

Abstract: This paper critically examines the opportunities and challenges of using technology, in particular Large Language Models (LLMs), to assist regulatory order writing in quasi-judicial settings, with a focus on the Indian context. The paper proposes augmenting rather than replacing human decision-makers, aiming to improve regulatory order writing practice through responsible use of LLMs. It identifies the core principles of administrative law that must be upheld in these settings — such as application of mind, reasoned orders, non arbitrariness, rules against bias, and transparency — and analyses how inherent limitations of LLMs, including their probabilistic reasoning, opacity, potential for bias, confabulation, and lack of metacognition, may undermine these principles. The paper reviews international frameworks and case studies from various jurisdictions, highlighting common design principles like human oversight, transparency, nondiscrimination, and security. It proposes a comprehensive Problem-Solution-Evaluation (PSE) framework for responsibly integrating LLMs into order writing processes. This framework maps specific technical, design, and systemic solutions to each identified risk, and outlines evaluation strategies — end-to-end, component-wise, human-in-theloop, and automated — to ensure ongoing alignment with legal standards. The article concludes with practical recommendations for the development and deployment of LLM-based systems in regulatory environments.

Pages: 58 pages
Date: 2025-12
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https://trustbridge.in/RePEc/papers/2025_Aggarwaletal_techOrderWriting.pdf First version, 2025 (application/pdf)

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