Sustainability & AI
Data colonialism
A critical term for the extraction of data from people and territories, echoing historical resource colonialism.
Definition
A critical concept describing the extraction of data from people and territories — concentrated in the hands of a few powerful actors — as a continuation of historical colonial resource appropriation.
Quick reference
At a glance
- Subject
- Sustainability & AI
- Editorial status
- Editorial draft
- Definition status
- Contested
- Last updated
- 21 August 2026
- Also known as
- data extractivism (related)
References
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This source supports the explanation of how the term is applied, measured or governed in practice.
Overview
What it means
Coined by Couldry and Mejias (2019), the term frames large-scale data collection as appropriation of human life as raw material, disproportionately affecting lower-income countries whose data and labour feed AI systems while value accrues elsewhere. It connects AI supply chains — from labelling workforces to scraped content — to global inequality.
How it is used
The concept informs debates on data governance, benefit-sharing and digital sovereignty, and critiques of AI development models that extract data and labour from the Global South. It appears in UNESCO-era AI ethics discourse and data-justice advocacy.
Why it matters
Data colonialism gives language to the distributional question inside AI: who provides the raw material, who does the invisible work, and who captures the value. Sustainability's equity pillar applies to the digital economy too.
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