AI vs Human Coding in Evaluation: Trade-offs, Trust, and the Limits of Delegation

Conference | Online

About the Event

AI is reshaping how qualitative evidence is produced, raising questions about reliability and trust. Drawing on a pilot from the LIFT MERL research in Rwanda, this session examines the trade-offs and complementarities between AI-assisted qualitative coding (using AILYZE) and manual coding by trained researchers. The online session will present key findings and lessons, followed by guided group discussions on the use of AI in MEL.

Speakers

名称 标题 Biography
Youngjin Kim Consultant Youngjin Kim is a consultant at Tetra Tech in London, specialising in monitoring, evaluation, and learning (MEL) for international development. Her work focuses on mixed-methods research and the integration of AI-assisted approaches into qualitative evaluation. www.linkedin.com/in/youngjinkimm

Topics and Themes

Evaluators Evaluation Comissioners Evaluation users 专家学者 Civil Society Students Youth Civil Servant / Intl. Organization Employee Yearly Theme: Evaluation, Evidence and Trust in the Age of AI

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