3.05 Case study: Predicting tides with AI and indigenous knowledge

This case study provides a compelling real-world example of the powerful synergy that can be achieved when Artificial Intelligence is developed in true partnership with indigenous knowledge holders. The PolArctic project, conducted in 2021 in the Inuit community of Sanikiluaq, Nunavut, Canada, sought to address a critical challenge posed by climate change: shifting environmental patterns were making traditional fishing grounds less reliable, threatening local food security and economic stability.

The project’s innovative approach was to develop an AI model that integrated traditional Inuit knowledge with scientific data and remote sensing techniques to locate previously undiscovered, viable locations for commercial inshore fishing of scallops, clams, and kelp. This initiative stands out because it was one of the first AI models of its kind to treat indigenous knowledge and modern science as equal and complementary systems of understanding. The AI was trained with and validated against both knowledge bases, a direct application of co-creation and cultural respect principles.

The modern science inputs included satellite imagery, field data from university researchers, and AI-derived modelling of near-shore bathymetry and sea-surface temperatures. The indigenous knowledge inputs consisted of the deep, place-based wisdom of the Sanikiluaq community regarding sea ice conditions, water currents, and the historical habitats of marine species. By merging these two knowledge systems, the AI model was able to identify promising new areas for mariculture that would have been difficult to locate using either approach alone.

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Crucially, the project embodied the principle of reciprocity and benefit sharing. The AI’s outputs were designed to be easily communicable, providing information in both English and the local language, Inuktitut. This empowered the community with actionable insights to inform research planning, scientific surveys, and economic exploration, helping them build sustainable and adaptable mariculture solutions. The project serves as a powerful testament that AI and indigenous culture are not in conflict; rather, their thoughtful integration can produce solutions that are more robust, culturally relevant, and effective for climate adaptation.