Our upcoming conference
Learn More About our Roundtable Discussions
Session Calendar
This March 13, during our event, participants will engage in focused roundtable discussions led by experts in AI-driven impact measurement. Each session will explore key challenges and opportunities in the field, providing practical insights and action-oriented discussions.
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Table 1: Ethics & AI in Impact Evaluation – Ensuring fairness, transparency, and privacy in AI-driven evaluations.
AI is revolutionizing impact evaluation, but how do we ensure it remains ethical, transparent, and fair? This session explores whether AI tools reinforce biases, compromise privacy, or exclude vulnerable communities, and discusses practical solutions for ensuring AI remains a force for ethical and inclusive evaluation. - Table 2: Future-Proofing Your MEL Career – Essential skills to stay competitive in an AI-driven future.AI is reshaping traditional MEL roles but also creating new career opportunities for professionals who embrace it. How can MEL practitioners, especially young professionals, develop the skills needed to stay competitive in an AI-driven future? This session will focus on which MEL roles are changing or disappearing due to AI, what essential skills professionals should develop to stay relevant, and how young professionals can use AI to accelerate their careers and stand out.
- Table 3: Rethinking Impact Measurement – Should AI redefine our evaluation frameworks?AI is challenging traditional MEL methodologies, but should we adapt AI to our existing methods, or should we redesign impact measurement entirely? This discussion will explore whether AI-driven frameworks are more effective and what shifts MEL professionals need to make to stay ahead.
- Table 4: Amplifying Local Voices – Using AI to enhance community-driven impact assessment.Traditional evaluations excel at numbers but often lack context, emotion, and lived experience. How can AI amplify community voices instead of erasing them? This session explores how AI can support locally-led impact measurement while respecting cultural nuances and ensuring grassroots insights are included in decision-making.
- Table 5: Bridging the AI Trust Gap – Making AI-driven decisions more transparent and accountable.AI-generated insights are increasingly shaping impact measurement, but can we fully trust AI-driven decisions? This session will focus on how AI models can be made more transparent, explainable, and accountable in MEL processes. Participants will discuss the risks of relying on AI without understanding how it makes decisions and explore ways to build greater trust in AI-driven evaluations.
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