‘No accountability, no checks and balances, no responsibility’: how Indigenous peoples think about AI

2026-04-22 · Source: Artificial intelligence (AI) – The Conversation · Field: Government & Public Sector — Public Policy & Governance, Social Services & Welfare · Depth: Fundamental Awareness, short

Summary

The Relational Futures project, which explores Indigenous sovereignty and AI governance, has released findings based on qualitative baselines of Aboriginal and Torres Strait Islander perspectives on AI. The project positions AI as part of a wider system shaping relationships between people, institutions, data, and Country, rather than a standalone tool. Participants expressed limited trust in AI and a willingness to refuse its use, recognizing its potential to intensify existing inequalities in sectors like welfare and health. Concerns extend beyond privacy to environmental costs, appropriation of Indigenous knowledges, and lack of transparency. The research also explored speculative concepts like an "AI Elder," which participants rejected due to AI's inability to form relationships, accountability, or connection to community and Country. The findings highlight the need for AI governance to engage with authority, responsibility, harm, and care, advocating for Indigenous leadership to prevent the reproduction of harms seen in systems like Robodebt.

Key takeaway

For CTOs and VPs of Engineering developing AI systems, your approach must extend beyond technical standards to embrace relational governance. Ignoring Indigenous data sovereignty and community-centric accountability risks replicating harms seen in systems like Robodebt, making your AI less effective and trustworthy for all. You should actively involve Indigenous leadership in design and deployment to ensure systems are safe, equitable, and culturally informed, rather than merely efficient.

Key insights

Indigenous perspectives reveal AI's potential to exacerbate existing inequalities and erode trust without proper accountability and cultural integration.

Principles

• AI systems are not neutral; they amplify existing power dynamics.
• Indigenous data sovereignty requires community control across the data lifecycle.
• True accountability in AI demands relational engagement, not just technical standards.

Method

The Relational Futures project gathered qualitative baselines of Indigenous perspectives on AI through surveys and yarning circles, centering community experiences and exploring speculative AI concepts like an "AI Elder."

In practice

• Prioritize Indigenous leadership in AI system design and governance.
• Design AI for marginalized communities to ensure broader safety and effectiveness.
• Integrate cultural authority and community benefit into AI development.

Topics

• Indigenous Perspectives on AI
• Relational Futures Project
• Indigenous Data Sovereignty
• AI Governance
• Automated Decision-Making

Best for: CTO, VP of Engineering/Data, Director of AI/ML, AI Ethicist, Policy Maker, Research Scientist

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Editorial summary, takeaway, and curation by AIssential. Original article published by Artificial intelligence (AI) – The Conversation.