Diversified Cultivation of Native Artificial Intelligence
In a groundbreaking event, the first global gathering on Indigenous AI took place at Quebec's Mila Institute in mid-July. The goal of this gathering was to "support ancestral knowledge" and to "recognize the multiplicity of ways of being intelligent in the world."
Indigenous AI holds great promise for preserving and revitalizing Indigenous languages and cultures. Artificial intelligence (AI) can be used to create interactive tools that facilitate language learning and usage, document endangered languages, transcribe oral traditions, and support Indigenous-led innovation.
One such example is the "Skobot," a wearable AI device designed by Anishinaabe roboticist Danielle Boyer. This device converses fluently in Anishinaabemowin, offering an engaging way for younger generations to access and practice Indigenous languages.
AI can also digitize languages and transcribe oral traditions that are at risk of being lost, storing linguistic and cultural knowledge for future generations. This is crucial for sustaining cultural identity and promoting education that is culturally relevant.
However, Indigenous researchers face several challenges in integrating their languages into AI systems. Data sovereignty and ethical concerns are critical, as Indigenous data is ancestral and sacred. Traditionally, AI training data come from sources reflecting colonial legacies, risking misrepresentation and exploitation of Indigenous knowledge without proper consent or control.
Another challenge is the lack of Indigenous participation in AI development. Without Indigenous leadership and involvement in AI design, systems tend to reinforce existing biases and exclude Indigenous perspectives. This marginalizes communities rather than empowering them.
Indigenous researchers may also face technical and resource limitations, with limited access to AI expertise, infrastructure, and funding necessary to develop tools that authentically represent their languages and cultures.
Despite these challenges, there are promising trends emerging. For instance, an increasing number of AI startups are being led by Indigenous people, and there are initiatives like the "Indigenous AI Explorers" program that encourage the development of AI tools in remote areas.
Michael Running Wolf, a co-founder of Mila's First Languages AI Reality (FLAIR) project, calls for a "reappropriation" of AI tools to collect data and then use it to revitalize indigenous languages, rather than just preserve them.
Elissa Strome, executive director of the pan-Canadian AI strategy at the Canadian Institute for Advanced Research (CIFAR), has stated that there's still a lot of work to be done to achieve a certain equity in the AI field. She hasn't seen any examples of big companies interested in Indigenous perspectives in AI.
Indigenous researchers from various parts of the world are using AI to address the specific needs of their nations. For example, the Buffalo In Motion project aims to reintroduce bison to ancestral Anishinaabe lands using AI and ecological data.
In conclusion, while AI holds immense potential for Indigenous language preservation and revitalization, addressing ethical issues and ensuring Indigenous control and participation are essential to overcome the systemic challenges faced by Indigenous researchers. The ongoing global gathering at Quebec's Mila Institute is a significant step towards achieving this goal.
The incorporation of artificial intelligence (AI) in education and self-development, such as the "Skobot" device designed by Anishinaabe roboticist Danielle Boyer, offers an engaging way for younger generations to learn and practice Indigenous languages. However, Indigenous researchers face challenges in integrating their languages into AI systems, including data sovereignty and ethical concerns, lack of Indigenous participation in AI development, and technical and resource limitations. To achieve a certain equity in the AI field and overcome these challenges, it's crucial to reappropriate AI tools for collecting data and revitalizing indigenous languages, and encourage initiatives like the "Indigenous AI Explorers" program that champion Indigenous-led innovation.
