The Regulation of AI-Based Weaponry under International Humanitarian Law

  • Atirek Shahi
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  • Atirek Shahi

    Student at Jindal Global Law School, India

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Abstract

This decade has seen a remarkable advent of artificial intelligence in warfare. The present (and recently past) wars are using complex machine learning technology to fight the opponent. There are of course humanitarian aspects and concerns to this movement. This research paper explores the complex narrative of AI in armed conflict, focusing the usage of smart Autonomous Weapons Systems (AWS) and its impact on the working of International Humanitarian Law (‘IHL’). The technology is still new and there is unpredictability in its usage and if it can indeed be used fairly. However, this paper in caution, argues against an absolute prohibition of such AI-enabled technology, as an excessive control on the weaponry might hinder the potential benefits it carries, especially towards efficient wars with minimal intended or unintended casualties. Instead, this paper proposes that these machine learning weapons duly comply with the IHL rules to the fullest extent. For this, the paper shall focus on the principle of obligation of constant care under IHL and how it could help hammer out specific mitigatory and precautionary obligations. There is of course the battle with the ambiguity in International law, especially surrounding the "constant care" standard and this paper discusses that too. The ultimate goal is to find a balance between technology and ethics and the human values of peace, applied to a world of machines.

Type

Research Paper

Information

International Journal of Law Management and Humanities, Volume 7, Issue 1, Page 1108 - 1121

DOI: https://doij.org/10.10000/IJLMH.116825

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This is an Open Access article, distributed under the terms of the Creative Commons Attribution -NonCommercial 4.0 International (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/), which permits remixing, adapting, and building upon the work for non-commercial use, provided the original work is properly cited.

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