[Paper Review] In Consideration of Indigenous Data Sovereignty: Data Mining as a Colonial Practice

Jennafer Shae Roberts, Laura N. Montoya|arXiv (Cornell University)|Sep 19, 2023

Ethics and Social Impacts of AISocial Sciences3 citations

TL;DR

This paper argues that data mining perpetuates colonialism by excluding Indigenous voices and data sovereignty, proposing the application of the CARE Principles—Collective Benefit, Authority to Control, Responsibility, and Ethics—to reorient data-driven technologies toward ethical, Indigenous-led governance. By centering Indigenous knowledge and rights, the framework challenges profit- and speed-driven data practices, offering a model for equitable, Earth-centered technological development.

ABSTRACT

Data mining reproduces colonialism, and Indigenous voices are being left out of the development of technology that relies on data, such as artificial intelligence. This research stresses the need for the inclusion of Indigenous Data Sovereignty and centers on the importance of Indigenous rights over their own data. Inclusion is necessary in order to integrate Indigenous knowledge into the design, development, and implementation of data-reliant technology. To support this hypothesis and address the problem, the CARE Principles for Indigenous Data Governance (Collective Benefit, Authority to Control, Responsibility, and Ethics) are applied. We cover how the colonial practices of data mining do not align with Indigenous convictions. The included case studies highlight connections to Indigenous rights in relation to the protection of data and environmental ecosystems, thus establishing how data governance can serve both the people and the Earth. By applying the CARE Principles to the issues that arise from data mining and neocolonialism, our goal is to provide a framework that can be used in technological development. The theory is that this could reflect outwards to promote data sovereignty generally and create new relationships between people and data that are ethical as opposed to driven by speed and profit.

Motivation & Objective

• To critically examine how data mining reinforces colonial power structures by marginalizing Indigenous communities and knowledge systems.
• To highlight the exclusion of Indigenous voices in the design and governance of data-reliant technologies like AI.
• To advocate for Indigenous Data Sovereignty as a necessary ethical and structural shift in data governance.
• To apply the CARE Principles as a framework to align data practices with Indigenous values and rights.
• To foster ethical technological development that prioritizes collective benefit, environmental stewardship, and community control over data.

Proposed method

• Application of the CARE Principles—Collective Benefit, Authority to Control, Responsibility, and Ethics—to analyze and reframe data mining practices.
• Use of case studies to illustrate connections between data governance, Indigenous rights, and environmental protection.
• Critical analysis of data mining as a neocolonial practice that extracts value without consent or reciprocity.
• Integration of Indigenous epistemologies into technological design to challenge dominant, profit-driven models.
• Theoretical framing of data relationships as ethical, relational, and Earth-centered rather than transactional and exploitative.
• Comparative evaluation of current data practices against the CARE Principles to identify misalignments with Indigenous worldviews.

Experimental results

Research questions

• RQ1 How does data mining reproduce colonial power dynamics in the context of AI and digital technologies?
• RQ2 In what ways do current data governance models fail to recognize or respect Indigenous Data Sovereignty?
• RQ3 How can the CARE Principles be operationalized to transform data mining from a colonial to a decolonial practice?
• RQ4 What are the implications of centering Indigenous knowledge and authority in the development of data-driven technologies?
• RQ5 How can data governance models be restructured to ensure collective benefit and environmental sustainability?

Key findings

• Data mining systematically excludes Indigenous communities from decision-making in data-driven technologies, reinforcing historical power imbalances.
• The current model of data extraction prioritizes speed and profit over ethical considerations, community consent, and environmental integrity.
• Application of the CARE Principles reveals significant misalignments between dominant data practices and Indigenous values of collective benefit and responsibility.
• Case studies demonstrate that Indigenous data governance models can simultaneously protect cultural and environmental ecosystems.
• Ethical data governance rooted in Indigenous sovereignty offers a viable alternative to exploitative data practices in AI and digital systems.
• Reframing data relationships through Indigenous epistemologies enables more sustainable, equitable, and community-led technological development.