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Artificial Intelligence and Qualitative Data Analysis

Epistemological Incongruences and the Future of the Human Experience

Bibliographic Data

ID2965083
AuthorsRudolf Messner (0000-0002-9049-3499), Samuel Smith (0000-0003-2257-6580), Carol Richards (0000-0001-9887-175X)
Year2025
Volume24
Publication date2025-08-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueInternational Journal of Qualitative Methods (JOURNAL)
Journal identifiersISSN: 1609-4069 • E-ISSN: 1609-4069
PublisherSAGE Publications Inc (PUBLISHER)
DOI10.1177/16094069251371481
OpenAlexW4413689701
LanguageEN
Citations received5
References cited45

The rapid rise of artificial intelligence (AI) has inspired scholarship that seeks to make sense of the impacts of AI technology on a wide range of human activity, including social scientific research. The power of AI to synthesise literature, compile information, and generate content is well recognised, yet its performance on some core dimensions of inductive/abductive research, including qualitative data analysis, is less documented and understood. This paper explores capabilities and implications of AI technology by focusing on the central position of the human experience in constructivist-interpretive research and its representability by dis-experienced AI models. We report on a novel qualitative experimental approach developed by the authors to examine inter-coder reliability between 'human only' and 'human-AI' approaches. Key findings highlight fundamental shortfalls, including AI generated output that is disconnected from the transcript data, and the inability of AI to generate robust descriptive and theoretical categories from raw data despite training. We conclude use of AI in qualitative analysis will require the development of entirely new skillsets, such as 'analytical coaxing', to navigate the vagaries of AI models. Our Three-Step Framework proposes a way to establish and communicate rigour in AI assisted analysis, foregrounding epistemological reflexivity and justifications that acknowledge the centrality of the human experience

Epistemology · Artificial Intelligence in Healthcare and Education · Ethics and Social Impacts of AI · Psychology · Philosophy

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Unique citing works5
Citations per year5
Citation span2025 - 2026 (2)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 5

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