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August 1, 2025International Journal of Qualitative MethodsOpen Access

Artificial Intelligence and Qualitative Data Analysis: Epistemological Incongruences and the Future of the Human Experience

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Authors

RMRudolf MessnerQueensland University of TechnologySSSamuel SmithQueensland University of TechnologyCRCarol Richards

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Implication

Analysis demonstrates fundamental shortfalls in AI's qualitative data analysis capabilities, suggesting new skills are needed for integration.

Key Points

  • AI struggles to generate robust descriptive and theoretical categories from qualitative data, indicating a need for new methods.
  • Inter-coder reliability was examined through a novel qualitative experimental approach to assess human-AI dynamics.
  • AI-generated content often disconnects from original transcript data, suggesting limitations in understanding human context.
  • The proposed Three-Step Framework emphasizes the development of analytical coaxing skills for effective AI-assisted analysis.

Cite This Study

Messner et al. (2025) studied this question.

synapsesocial.com/papers/68af7e047567bf4f94ff576ahttps://doi.org/10.1177/16094069251371481
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