What is it about?
We assessed a generative artificial intelligence tool (Microsoft Copilot) in terms of its capability for thematic analysis. It did not perform reliably. We discuss the ethical and methodological implications of the findings in terms of little q qualitative and Big Q Qualitative discourse.
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Why is it important?
The marketing of AI is that it will solve all of our problems. Actually, under the right conditions, AI is useful for some tasks, and not useful - even problematic - for other tasks. Although many researchers may want to outsource thematic and other qualitative analyses to AI, we do not recommend this.
Perspectives
Although the generative AI space is rapidly changing and publishing cycles cannot keep up with this rate of change, we see this paper as important for demarking a point in time and raising our awareness about what social scientists are trying to achieve. Does AI undermine the trust that human research participants have in researchers? Does it capture the right stuff when it comes to peoples' stories and experiences? Under what circumstances should researchers embrace AI for qualitative data analysis? The paper explores these issues in relation to evidence.
Tanisha Jowsey
Read the Original
This page is a summary of: Frankenstein, thematic analysis and generative artificial intelligence: Quality appraisal methods and considerations for qualitative research, PLOS One, September 2025, PLOS,
DOI: 10.1371/journal.pone.0330217.
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