WATCH ON-DEMAND
This on-demand webinar is part of The Qualitative Insights Summit 2026:
Explore African qual research and AI with Mpho Mpofu, from documenting fieldwork methods to checking the provenance of AI-generated insights.
COMPLETE THE FORM TO WATCH THE VIDEO FOR FREE
African qualitative research and AI intersect in questions about whose fieldwork knowledge is documented, and reflected in AI-generated answers. In this webinar, Mpho Mpofu of Masutane discusses those questions using research for The Qual African.
Mpho shares examples of context-sensitive qualitative practice, practical ways to document methods during projects and questions researchers can use to evaluate AI-generated claims before presenting them to clients.
Key Takeaways:
- Examine the research record. Mpho argues that some fieldwork knowledge held by African researchers is insufficiently documented and may therefore be less visible to AI systems.
- Interpret silence in context. Researchers in the project describe how silence can carry different meanings depending on the setting and relationships involved.
- Translate meaning, not just words. The session highlights the risk of losing context when translation does not capture what a participant intends.
- Adapt stimuli to the setting. Mpho shares an example of changing research materials when an image carried an unintended local association.
- Build community trust. She describes the time and relationships that may be needed to access particular communities respectfully.
- Capture techniques during fieldwork. Debriefs and voice notes can help teams record observations and name methods while a project is underway.
- Check the provenance of AI output. Mpho examines sources, asking follow-up questions and decides whether you can stand behind a claim before sharing it with a client.
- Use AI with awareness of its limits. She describes uses such as transcription and literature reviews alongside concerns about translation and missing context.
What’s Covered:
Why fieldwork knowledge can be missing from the record
To begin, Mpho draws on The Qual African, which is based on interviews with 31 qualitative researchers. She argues that researchers’ practical knowledge isn’t always documented in ways AI systems can see. Because of this, polished AI output shouldn’t be mistaken for grounded evidence.
Silence, translation and cultural context
The session then explores how silence can reflect respect, protocol or other dynamics of the situation. Likewise, it explains why translating words alone can miss what someone means. Mpho also shares examples of adapting stimulus materials and building community relationships in specific contexts.
Documenting qualitative methods during live projects
Next, Mpho describes how to make documentation part of everyday project work, for instance through field-day debriefs and moderator voice notes. She also gives examples of named techniques. One is “threading”, which means carrying a participant’s earlier point through the rest of the conversation. Another is “pegging”, which means noting a topic to come back to later.
Checking where AI-generated insights come from
Mpho then suggests four questions to ask. Who produced the source? Could it actually support the claim? What follow-up questions can the answer stand up to? And, finally, can you as the researcher stand behind it? That said, she notes that a missing citation is a reason to investigate, not proof in itself that a statement was made up.
Where AI helps and where local judgement matters
Lastly, Mpho points to English-language transcription and literature reviews as useful applications. At the same time, she highlights AI’s limits in translation and in reading non-verbal context. With this in mind, she encourages researchers to share their knowledge in conversations about how these tools are designed and used.
Speaker:
Mpho Mpofu – Founder & CEO, Masutane
Mpho is a qualitative researcher at Masutane, and the creator of The Qual African, a body of work exploring qualitative research practice through interviews with researchers working across different African contexts.