Algorithmic Tokenism vs. Digital Marema-Tlou: Decolonizing AI in Evaluation

As the global M&E sector accelerates its adoption of Artificial Intelligence, a critical ethical blind spot is emerging: the linguistic and cultural bias of Large Language Models. Because mainstream AI is predominantly trained on Western datasets and Eurocentric epistemologies, deploying these tools in the Global South risks ushering in a new era of "algorithmic tokenism." Without rigorous safeguards, AI will misinterpret local realities, sanitize grassroots trauma, and erase the "Quiet Knowledge" embedded in indigenous communities.

This session challenges evaluators to look beyond Silicon Valley defaults and apply the Sesotho philosophy of Marema-Tlou (collective wisdom) to digital M&E infrastructure. Drawing on decolonial frameworks, the session will explore how evaluators can avoid digital extraction by co-creating localized AI prompts and guardrails directly with communities.