Evaluation, Evidence, and Trust in the Age of AI: Centering Indigenous Knowledge and Community Voices
Webinaire | En ligne
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Organisé par:
Monitoring and Evaluation Professionals Association of Kenya (MEPAK)
À propos de l'événement
The growing use of Artificial Intelligence (AI) in evaluation is transforming how evidence is generated, analyzed, and used. While AI presents opportunities for efficiency and innovation, it also raises critical concerns around trust, bias, data ownership, and the marginalization of local knowledge systems.
For Indigenous communities, these concerns are particularly significant. Evaluation systems have historically been extractive, often overlooking Indigenous ways of knowing, community-defined indicators of success, and culturally grounded approaches to learning and accountability. The introduction of AI risks deepening these challenges if it relies on datasets that exclude or misrepresent Indigenous realities.
At the same time, Indigenous knowledge systems offer valuable approaches to evaluation—grounded in relational accountability, storytelling, collective reflection, and lived experience—that can enrich and humanize AI-driven processes. There is an urgent need to explore how evaluation can integrate AI responsibly while safeguarding Indigenous knowledge, ensuring data sovereignty, and strengthening trust with communities.
This session brings together perspectives on AI, evaluation, and Indigenous knowledge to examine how evaluators can navigate this evolving landscape in ways that are ethical, inclusive, and context-responsive.
For Indigenous communities, these concerns are particularly significant. Evaluation systems have historically been extractive, often overlooking Indigenous ways of knowing, community-defined indicators of success, and culturally grounded approaches to learning and accountability. The introduction of AI risks deepening these challenges if it relies on datasets that exclude or misrepresent Indigenous realities.
At the same time, Indigenous knowledge systems offer valuable approaches to evaluation—grounded in relational accountability, storytelling, collective reflection, and lived experience—that can enrich and humanize AI-driven processes. There is an urgent need to explore how evaluation can integrate AI responsibly while safeguarding Indigenous knowledge, ensuring data sovereignty, and strengthening trust with communities.
This session brings together perspectives on AI, evaluation, and Indigenous knowledge to examine how evaluators can navigate this evolving landscape in ways that are ethical, inclusive, and context-responsive.
Conférenciers
| Nom | Titre | Biography |
|---|---|---|
| EDDAH KANINI | Monitoring, Evaluation and Gender Specialist | Monitoring, Evaluation, and Learning Specialist with over 15 years’ experience across Africa, with expertise in Indigenous evaluation, gender and equity-focused evaluation, and systems approaches. She has contributed to global discourse on AI and evaluation ethics and actively promotes culturally responsive and community-centered evaluation practices. |
| Jackline Musuya |