How to incorporate Indigenous knowledge into AI evaluation frameworks
Incorporate Indigenous knowledge into AI evaluation frameworks by centering relational ethics, community sovereignty, and co-design principles like the CARE Principles, ensuring AI supports rather than extracts from Indigenous data and worldviews in M&E for SDGs.[prism.sustainability-directory]
Guiding Frameworks
Adopt established Indigenous-led protocols to bridge traditional knowledge with AI assessments.
CARE Principles: Prioritize Collective Benefit, Authority to Control, Responsibility, and Ethics—treat data as relational, not commodity, for M&E datasets involving Indigenous communities.[prism.sustainability-directory]
Indigenous Protocol and AI: Emphasize consent protocols, reciprocity, and cultural protocols in AI design, as outlined by Indigenous AI networks.spectrum.library.concordia+1
Two-Eyed Seeing: Blend Indigenous epistemologies (e.g., relational land-based knowledge) with Western metrics for holistic SDG evaluations.[pmc.ncbi.nlm.nih]
Practical Steps for M&E Teams
Follow this co-creative process, adapted for rapid assessments in SDG contexts.
Engage Communities First: Initiate with Indigenous-led consultations to define evaluation goals, data sovereignty, and knowledge-sharing protocols (e.g., oral histories for SDG 2/13).[arcticwwf]
Co-Design Data Pipelines: Integrate Indigenous validation loops—e.g., elder reviews—alongside AI tools like federated learning to preserve privacy and context.[prism.sustainability-directory]
Hybrid Model Training: Weight Indigenous knowledge equally with quantitative data (e.g., PolArctic’s AI for mariculture, blending satellite + traditional fishing insights).[arcticwwf]
Bias Audits with Cultural Lenses: Use SHAP/LIME outputs filtered through Indigenous fairness metrics, like intergenerational equity.[t3-consultants]
Monitor and Reciprocate: Build feedback mechanisms with benefit-sharing (e.g., capacity building), reassessing quarterly per UNESCO alignment.[unesco]
Integration Table
| Framework Element | M&E Application | Example SDG Use [prism.sustainability-directory] |
|---|---|---|
| CARE Authority | Data governance | SDG 15 (Land rights tracking) |
| Two-Eyed Seeing | Model validation | SDG 3 (Health diagnostics with traditional healing) |
| Protocols | Explainability | SDG 4 (Culturally attuned education AI) |
| Reciprocity | Risk assessment | SDG 17 (Partnership audits) |
This decolonial approach enhances AI credibility, equity, and relevance in global evaluations.[pmc.ncbi.nlm.nih]
