AI Colonialism: The New Frontier of Extraction
Artificial intelligence and large-scale data infrastructures function as central nodes in the global digital economy. Framing data as a "resource" or "raw material" mirrors historical extractive logic. Data concerning Indigenous lands, cultures, and peoples is frequently collected, analyzed, and commercialized without community governance.
machine learning engenders "AI Colonialism." Digital capitalism depends on data relations that enable the extraction of information for commodification.
AI systems rely on global data flows that systematically extract value from the Global South while imposing Western universalist values. Key mechanisms include:
- > EXTRACTIVISM: The scraping of data and outsourcing of precarious labor to marginalized regions.
- > EPISTEMIC UNIVERSALISM: Imposing Western order and moral absolutism through technical systems that ignore local realities.
- > DATA SCARCITY FALLACY: The narrative that Southern or Indigenous data is "missing," justifying aggressive scraping without regard for sacred or communal context.
Indigenous Data Sovereignty (IDSov)
Indigenous Data Sovereignty (IDSov) asserts that Indigenous Peoples possess inherent rights to govern the creation, ownership, and application of data related to their communities, lands, and knowledge systems.
Historically, research involving Indigenous communities operated under colonial frameworks. Anthropologists and biologists collected artifacts and genetic samples that were stored in external archives without returning benefits. In the digital era, extraction occurs through satellite imaging, genomic sequencing, and LLM training pipelines.
IDSov shifts the focus from "open data" to "governed data." While open science initiatives emphasize accessibility, Indigenous frameworks mandate context, responsibility, and relational accountability.
OCAP® Principles
Developed by the First Nations Information Governance Centre in Canada to counter research exploitation.
- Ownership: Communities collectively own their information.
- Control: Indigenous Peoples control data management.
- Access: Right to access data regardless of location.
- Possession: Physical custody to enforce ownership.
Traditional Knowledge (TK) Labels
Digital metadata tags developed by the Local Contexts initiative to communicate cultural expectations.
- Seasonal or ceremonial restrictions.
- Attribution requirements.
- Community-specific access protocols.
- Cultural sensitivity warnings.
[ DATA_GOVERNANCE_PARADIGMS ]
Compare standard scientific data management with the CARE Principles.
Indigenous Protocols for Artificial Intelligence
Indigenous Protocols for AI (IP AI) offer frameworks to refuse purely human-centric, extractive approaches to technology. Modern AI ethics are human-centered. Indigenous philosophies operate through a relational worldview.
Technology cannot be separated from its ecological context. AI is not a neutral instrument; these protocols shift the focus toward Relational Ethics.
Machine as Kin
Inspired by Indigenous epistemologies, this concept proposes that AI systems function as part of a "circle of relationships." It encourages designers to evaluate systems within social and ecological networks.
Grounded Locality & Indigenous-Centered Design
AI should be co-designed with specific communities to support local governance. This approach rejects the "black box" model, demanding transparent systems governed by local structures.
Decolonial AI Alignment and Language Sovereignty
Alignment in AI refers to tuning a model to follow human values. Imposing purely Western values risks ethical essentialism. Decolonial alignment incorporates plural ethical systems.
Language preservation applications within Indigenous communities raise structural questions regarding data ownership.
Case Study: Te Hiku Media
Te Hiku Media developed speech recognition models for Māori. They refused to share their curated archive with major tech companies, maintaining data sovereignty over cultural heritage.
Latam-GPT
Latin American researchers are developing open-source models incorporating underrepresented languages like Mapuche, Guaraní, and Quechua to counter English-centric monopolies.
Technology as Resistance and Practical Return
Sovereignty involves practical returns: technological infrastructures that directly benefit communities. Examples include satellite monitoring, AI-powered mapping, biodiversity tracking based on ecological knowledge, and digital archives governed by community protocols.
Indigenous communities resist "Digital Biopiracy"—the nonconsensual use of digital sequence information (DSI) extracted from biological resources.
Independent digital infrastructures are necessary for decoloniality. True sovereignty requires shifting communities from passive data sources to active co-creators of technological systems.
>> Bibliographic_References.log
- [01] Carroll, S. R., Rodriguez-Lonebear, D., & Martinez, A. (2019). Indigenous data governance: Strategies from United States Native Nations. Data Science Journal.
- [02] First Nations Information Governance Centre. (2020). OCAP®: Ownership, Control, Access and Possession.
- [03] Global Indigenous Data Alliance (GIDA). (2019). CARE Principles for Indigenous Data Governance.
- [04] Local Contexts Initiative. Traditional Knowledge Labels.
- [05] Lewis, J. E., Arista, N., Pechawis, A., et al. (2020). Making Kin with the Machines. Journal of Design and Science.
- [06] Te Hiku Media. Māori Language AI Development Project.
- [07] UNESCO (2021). Decolonizing AI: Toward Inclusive Digital Futures.
- [08] Nature Machine Intelligence (2022). Indigenous Knowledge and Artificial Intelligence Ethics.