AI colonialism
In plain wordsThe criticism that the AI industry repeats patterns of colonial empires, taking data, labor, land and resources from poorer places and peoples while profits and control stay with a few rich companies and countries.
A critical framework describing the AI industry as reproducing colonial relations of extraction and dependency. Its claims include that data, including cultural works, languages and personal information, are taken from communities without meaningful consent or compensation; that low-paid workers, often in the Global South, perform labeling and moderation (ghost workghost work, n.: The hidden human labor behind AI: people, often poorly paid and far away, who label data, check outputs and handle cases the software cannot, while the product appears fully automatic.); that minerals, land, water and energy for chips and data centers come from places that see little of the benefit; and that systems designed in a few countries impose their languages, values and categories elsewhere while capturing markets and infrastructure. Proposed responses include data sovereignty and community data governance, fair labor standards, locally built and controlled models, and decolonial approaches to design. Critics of the framing argue that it stretches the historical concept of colonialism and understates local agency and benefits.
The council refused the dataset deal as AI colonialism: their language recordings for a model they would have to rent back.
Origin
Builds on 'data colonialism', theorized by Nick Couldry and Ulises Mejias (2019), and on 'Decolonial AI' by Shakir Mohamed, Marie-Therese Png and William Isaac (2020). Karen Hao's 'AI Colonialism' series in MIT Technology Review (April 2022) popularized the phrase, and her book Empire of AI (2025) extended the argument to frontier AI companies.
Related
- ghost workghost work, n.: The hidden human labor behind AI: people, often poorly paid and far away, who label data, check outputs and handle cases the software cannot, while the product appears fully automatic.
- digital dividedigital divide, n.: The gap between people, places or countries that have good access to digital technology, and the skills to use it, and those that do not; AI may widen it.
- concentration of powerconcentration of power, n.: The worry that AI will put enormous economic, political or military power in the hands of a few companies, governments or individuals, beyond the reach of ordinary checks and balances.
- sovereign AIsovereign AI, n.: A country's ability to build and run AI on its own terms, so that the computers, models and know-how it relies on cannot be withheld or dictated by foreign companies or governments.
- AI for goodAI for good, n.: Using AI to tackle social and environmental problems, such as disease, poverty, disasters or climate change, rather than only to make a profit.
- surveillance capitalismsurveillance capitalism, n.: A business model in which companies collect huge amounts of data about people's behavior and use it to predict and influence what they will do, mainly to sell advertising.
Sources
- Couldry, N. & Mejias, U. A. (2019). The Costs of Connection: How Data Is Colonizing Human Life and Appropriating It for Capitalism. Stanford University Press.
- Mohamed, S., Png, M.-T. & Isaac, W. (2020). Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence. Philosophy & Technology 33, 659–684.
- Hao, K. (2025). Empire of AI: Dreams and Nightmares in Sam Altman's OpenAI. Penguin Press.
Mentioned in
AI for goodAI for good, n.: Using AI to tackle social and environmental problems, such as disease, poverty, disasters or climate change, rather than only to make a profit., concentration of powerconcentration of power, n.: The worry that AI will put enormous economic, political or military power in the hands of a few companies, governments or individuals, beyond the reach of ordinary checks and balances., digital dividedigital divide, n.: The gap between people, places or countries that have good access to digital technology, and the skills to use it, and those that do not; AI may widen it., ghost workghost work, n.: The hidden human labor behind AI: people, often poorly paid and far away, who label data, check outputs and handle cases the software cannot, while the product appears fully automatic., low-resource languagelow-resource language, n.: A language with little digital text, recorded speech or language tools available — often one spoken by millions — which makes AI systems much weaker in it than in English., surveillance capitalismsurveillance capitalism, n.: A business model in which companies collect huge amounts of data about people's behavior and use it to predict and influence what they will do, mainly to sell advertising.