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Large Language Models in Qualitative Research: Uses, Tensions, and Intentions

Author(s)
Schroeder, Hope; Randazzo, Casey; Mimno, David; Schoenebeck, Sarita; Le Quéré, Marianne Aubin
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Abstract
Qualitative researchers use tools to collect, sort, and analyze their data. Should qualitative researchers use large language models (LLMs) as part of their practice? LLMs could augment qualitative research, but it is unclear if their use is appropriate, ethical, or aligned with qualitative researchers’ goals and values. We interviewed twenty qualitative researchers to investigate these tensions. Many participants see LLMs as promising interlocutors with attractive use cases across the stages of research, but wrestle with their performance and appropriateness. Participants surface concerns regarding the use of LLMs while protecting participant interests, and call attention to an urgent lack of norms and tooling to guide the ethical use of LLMs in research. We document the rapid and broad adoption of LLMs across surfaces, which can interfere with intentional use vital to qualitative research. We use the tensions surfaced by our participants to outline recommendations for researchers considering using LLMsin qualitative research and design principles for LLM-assisted qualitative research tools.
Description
CHI ’25, Yokohama, Japan
Date issued
2025-04-25
URI
https://hdl.handle.net/1721.1/162590
Department
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
Publisher
ACM|CHI Conference on Human Factors in Computing Systems
Citation
Hope Schroeder, Marianne Aubin Le Quéré, Casey Randazzo, David Mimno, and Sarita Schoenebeck. 2025. Large Language Models in Qualitative Research: Uses, Tensions, and Intentions. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (CHI '25). Association for Computing Machinery, New York, NY, USA, Article 481, 1–17.
Version: Final published version
ISBN
979-8-4007-1394-1

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