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Exploring ChatGPT’s potential as a qualitative research partner

Researcher and participant perspectives on AI-generated insights

Bibliographic Data

ID12733389
AuthorsLynette Pretorius (0000-0002-8998-7686, Australian Regenerative Medicine Institute, corresponding author), Chris Pretorius (0009-0008-4984-0066, The University of Melbourne)
Year2025
Pages1-33
Publication date2025-11-10
Open AccessNo
TypeARTICLE
VenueQualitative Research in Psychology (JOURNAL)
Journal identifiersISSN: 1478-0887 • E-ISSN: 1478-0895
PublisherTaylor & Francis (PUBLISHER • GB)
DOI10.1080/14780887.2025.2585840
OpenAlexW4416065720
LanguageEN
References cited36

The increasing presence of generative AI in research presents both opportunities and challenges for qualitative data analysis. While generative AI tools such as ChatGPT can assist with pattern recognition, text classification, and summarisation, their role in in-depth, interpretive qualitative analysis remains under-theorised. This article draws on Actor-Network Theory to examine the integration of ChatGPT as a non-human (and arguably more-than-human) actor within a socio-material assemblage of qualitative data analysis. Using a researcher–participant–ChatGPT triadic model, we explore how analytic insight develops through processes of translation, reflexivity, and relational engagement. Our findings suggest that ChatGPT participates in the co-construction of meaning, prompting theoretical reflection, unsettling researcher assumptions, and contributing to distributed agency within the research network. Rather than streamlining analysis, ChatGPT reconfigures it, offering a new mode of participatory research in which power, interpretation, and knowledge are dynamically negotiated across human and non-human actors

Action research · Ethnography · Lived experience · Narrative · Participant observation · Phenomenology (philosophy · Qualitative research · Reflexivity · AI in Service Interactions · Artificial Intelligence in Healthcare and Education · Ethics and Social Impacts of AI

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