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Despite an emerging body of scholarship on applying generative AI (GenAI) to qualitative data analysis, this area remains underdeveloped. This article evaluates how GenAI can support thematic analysis using a publicly available interview dataset from Lumivero. It introduces Guided AI Thematic Analysis (GAITA), an adaptation of King et al.’s (2018) Template Analysis. This framework positions researchers as a reflexive instrument and intellectual leader while thoroughly guiding GPT-4 in four...
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The CGIAR 2030 Research and Innovation Strategy commits organizational change with seven ways of working, including “Making the digital revolution central to our way of working”. In that context, Artificial Intelligence (AI), introduces both opportunities and risks to evaluation practice. Guided by the CGIAR-wide Evaluation Framework, integrating AI tools requires a governance approach to balance innovation with ethical responsibility, ensuring transparency, fairness, accountability, and...
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One of the main questions evaluators have when using AI is: "How can I know if it performs well?" To answer this question, we have developed a guidance note aimed at capturing what we have learned so far about integrating AI into evaluation and to offer a framework for further exploration. Since we began our experiments with Large Language Models (LLMs) in the Spring of 2023, we have made significant progress in using Generative Artificial Intelligence (GenAI) for processing and analyzing...
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This article presents an artificial intelligence-assisted causal mapping pipeline for gathering and analysing stakeholder perspectives at scale. Evidence relevant to constructing a programme theory, as well as evidence for the causal influences flowing through it, are both collected at the same time, without the evaluator needing to possess a prior theory. The method uses an artificial intelligence interviewer to conduct interviews, automated coding to identify causal claims in the...
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Generative AI (GenAI) is evolving rapidly, and its use in violence against women research remains new and largely experimental. While researchers are beginning to explore GenAI’s potential, uncertainty around its risks, ethical challenges, and real-world application persists. Recognising the need for clear guidance, the Sexual Violence Research Initiative (SVRI) partnered with The MERL Tech Initiative (MTI) to develop this resource. This guide aims to provide background on GenAI, strengthen...
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