Rethinking Qualitative Evidence in the Age of AI: Decentralizing Decision-Making in MEL

Seminario web | En línea

Sobre el evento

Organizations collect vast amounts of qualitative data from the field; yet much of it is used only for storytelling rather than decision making, often remaining limited to program officers and managers. As teams experiment with AI tools to analyze transcripts and field notes, unstructured data often produces weak or unreliable insights. Using a MEL case study, this session demonstrates how structuring qualitative evidence enables responsible AI-supported analysis while preserving context and rigor. It also explores when AI strengthens evaluation, when human judgement should take precedence, and how to make evidence visible across teams for decentralized learning and decision-making.

Presentador/a

Nombre Título Biografía
Akshay Roongta Co-Founder, Dots Co-founder of Dots, with 10+ years of experience across WASH, health & education; expert at blending systems thinking with participatory research to help teams make sense of lived experiences for lasting change.
Yashna Jhamb Co-Founder, Dots Co-founder of Dots, a SaaS platform helping organizations collect, organize, and analyze qualitative data at scale. Acumen fellow with a background in ethnographic research and systems thinking; advocate for ethical tech that amplifies overlooked voices and drives equity-centered change

Temas

Evaluadores Responsables de la toma de decisiones VOPEs / Redes de evaluación Académicos Sociedad civil Tema anual: Evaluación, evidencia y confianza en la era de la IA Uso de la evidencia

Detalles del evento

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