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Autore principale: Dasgupta, Priyadarshini
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Pubblicazione: Zenodo 2026
Accesso online:https://doi.org/10.5281/zenodo.19409373
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author Dasgupta, Priyadarshini
author_facet Dasgupta, Priyadarshini
contents <p>This paper examines a structural parallel that has received little formal academic attention: the degree to which modern artificial intelligence systems are functionally replicating the power architectures of ancient kingdoms and civilisations — not by metaphor, but by convergence of mechanism.</p> <p>Drawing on Vedic epistemic traditions, the weapons systems described in the Mahabharata and Ramayana (particularly the Brahmastra), Kautilya's Arthashastra, and the knowledge-control traditions of Egyptian and Mesopotamian priest-classes, the paper demonstrates that present-day AI infrastructure follows ancient civilisational logic at the structural level. Training data concentration mirrors the sacred archive. Compute gatekeeping mirrors directed-energy weapon control. Recommendation and surveillance systems mirror Mauryan intelligence architecture. The alignment problem mirrors the guru-shishya problem of capability transfer without misuse.</p> <p>The paper argues that this convergence has direct implications for global equity, non-Western knowledge representation, and AI governance — and calls for the establishment of a new interdisciplinary field, Civilisational AI Studies, to examine these questions formally.</p> <p>Keywords: artificial intelligence, ancient civilisations, Brahmastra, Vedic knowledge systems, Arthashastra, Mauryan empire, epistemic weapons, AI governance, civilisational power, knowledge control, alignment, directed energy, India</p> <p>Resource Type: Publication — Journal Article / Preprint</p> <p>Language: English</p> <p>Access: Open Access</p> <p>Licence: Creative Commons Attribution 4.0 International (CC BY 4.0)</p> <p>Publisher: Zenodo</p> <p>Author: Priyadarshini Dasgupta</p> <p>Affiliation: Independent Researcher, West Bengal, India</p>
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spellingShingle The Kingdom Engine: How Artificial Intelligence Is Reconstructing Ancient Civilisational Knowledge Systems to Engineer Societal Power
Dasgupta, Priyadarshini
<p>This paper examines a structural parallel that has received little formal academic attention: the degree to which modern artificial intelligence systems are functionally replicating the power architectures of ancient kingdoms and civilisations — not by metaphor, but by convergence of mechanism.</p> <p>Drawing on Vedic epistemic traditions, the weapons systems described in the Mahabharata and Ramayana (particularly the Brahmastra), Kautilya's Arthashastra, and the knowledge-control traditions of Egyptian and Mesopotamian priest-classes, the paper demonstrates that present-day AI infrastructure follows ancient civilisational logic at the structural level. Training data concentration mirrors the sacred archive. Compute gatekeeping mirrors directed-energy weapon control. Recommendation and surveillance systems mirror Mauryan intelligence architecture. The alignment problem mirrors the guru-shishya problem of capability transfer without misuse.</p> <p>The paper argues that this convergence has direct implications for global equity, non-Western knowledge representation, and AI governance — and calls for the establishment of a new interdisciplinary field, Civilisational AI Studies, to examine these questions formally.</p> <p>Keywords: artificial intelligence, ancient civilisations, Brahmastra, Vedic knowledge systems, Arthashastra, Mauryan empire, epistemic weapons, AI governance, civilisational power, knowledge control, alignment, directed energy, India</p> <p>Resource Type: Publication — Journal Article / Preprint</p> <p>Language: English</p> <p>Access: Open Access</p> <p>Licence: Creative Commons Attribution 4.0 International (CC BY 4.0)</p> <p>Publisher: Zenodo</p> <p>Author: Priyadarshini Dasgupta</p> <p>Affiliation: Independent Researcher, West Bengal, India</p>
title The Kingdom Engine: How Artificial Intelligence Is Reconstructing Ancient Civilisational Knowledge Systems to Engineer Societal Power
url https://doi.org/10.5281/zenodo.19409373