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Research Paper Volume 8 Issue 4 183 - 194 July 10, 2025

Data Colonialism and Indigenous Art: Why the World Needs a Centralized International Database

Lead author · Corresponding
Geetika Garg
Student at Chanakya National Law University, Patna, India
Download PDF Full text DOIhttps://doij.org/10.10000/IJLMH.1110359
Abstract

AI now is efficient and can do multiple creative works that were earlier only possible by creative humans such poetry, music, story writing and the most popular Painting as we have seen during the infamous Ghibli trend in Instagram, where AI turned ordinary pictures into beautiful hand-drawn art. But what happens when these creative works are not just inspired by modern artists, but are trained on centuries-old indigenous artworks? Indigenous art forms like Aboriginal dot paintings, Native American beadwork, or Warli designs are not just only visual styles. They are cultural identities, shaped by generations of storytelling, rituals, and history. But current intellectual property laws don’t fully protect them. Copyright focuses on individual creators. Geographical Indications protect products, not patterns. While countries like Peru and Panama have tried to safeguard cultural expressions, there is no such strong international system that stops AI models from using these styles without asking or sharing benefits. This paper tries to present a solution by creating a centralized global database of indigenous art and AI companies should be required to consult this database before using cultural works in training their models. More importantly, indigenous communities must have control, consent, and a share of the benefits. Without this, intellectual property law will continue to favour those with power and leave behind those whose creativity built entire cultural traditions.

Type
Research Paper
Information
International Journal of Law Management and Humanities, Volume 8, Issue 4, Page 183 - 194
DOI: https://doij.org/10.10000/IJLMH.1110359
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CC BY-NC 4.0 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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The views and opinions expressed in this manuscript are those of the author(s) alone and do not reflect the views, policies, or position of the Journal.

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