AI and Indigenous Knowledge: Ethical Technology and Data Sovereignty

It promises faster decisions, streamlined systems, and sweeping changes across industries. As these tools become more embedded in our everyday lives, a critical question is emerging: How does AI interact with Indigenous knowledge systems?

This is more than just a technical question — it’s also an ethical one. For communities who have long fought to protect and reclaim their stories, languages, and ways of knowing, AI presents both exciting opportunities and real risks. We must be willing to ask: Who benefits from these tools? Who has a say in how they’re used? And how can Indigenous communities lead the way in shaping digital futures that honour tradition?

AI tools like ChatGPT, image generators, and predictive algorithms are trained on huge datasets. These datasets are often compiled from the open internet or institutional archives, usually without the consent of the individuals or communities whose stories and knowledge are being used. This means that oral histories, language resources, and even digitized cultural artifacts can be absorbed and reproduced by AI systems, often out of context and without honouring their creators and origins.

For Indigenous communities, this can be problematic. AI can strip nuance from knowledge, propagate stereotypes, or turn sacred stories into content. Worse, it can become part of extractive systems that take without giving back.

That’s why data sovereignty — the right of communities to govern how their data is collected, used, and shared — is a key issue in the AI conversation. Who within a community governs the data is also an important conversation — who gives permission for collective knowledge?

Despite the risks, many Indigenous leaders and technologists are exploring ways to harness AI in ways that reflect community values.

• Language revitalization: AI models can help generate new language learning tools, translate between dialects, and preserve rare recordings. Initiatives like the Indigenous Languages Technology Project are already doing this with care and consent.
• Community mapping: AI can enhance visual storytelling and land-use planning by helping communities organize, interpret, and present spatial and cultural knowledge in meaningful ways. With tools like satellite imagery analysis and pattern recognition, AI can detect environmental changes such as shifting water levels, deforestation, or erosion over time. This information can be visualized through maps that are layered with traditional place names, harvesting areas, seasonal knowledge, and oral histories. AI can also assist in translating narrative data — like interview transcripts or archival texts — into visual formats by identifying themes and linking them to specific locations. These combined methods allow communities to tell their own land-based stories, support decision-making, and safeguard traditions using accessible, interactive formats.
• Ethical research: Tools like AI-powered transcription or text analysis can assist community researchers, provided they're used transparently and with permission.

At Narratives, we’ve seen how emerging tech, when guided by Indigenous ethics and leadership, can amplify stories rather than overwrite them. In our Research & Learning and Capacity Facilitating work, we often support communities in shaping their own data practices. This can include anything from qualitative coding and archival analysis to digital storytelling.

There’s no one-size-fits-all answer to whether a community should adopt AI tools. Some may choose to make these tools their own, using them in ways that reflect community goals and cultural practices. Others may resist these technologies altogether, focusing instead on place-based practices and intergenerational knowledge transfer.

What’s most important is that these choices are community-led.

The conversation about AI and Indigenous knowledge is still unfolding. But one thing is clear: technology must serve people, not the other way around.

As researchers, designers, and facilitators, we have a role to play in ensuring that the digital tools we use reflect the values of care, accountability, and self-determination. At Narratives, that means staying grounded in relationships, listening deeply, and always asking what justice looks like, in both our outcomes as well as, perhaps more importantly, our methods.

The future of AI doesn't have to be extractive. With Indigenous leadership, it can become something entirely different: a future where tradition and technology can walk together.