Navigating Generative Artificial Intelligence (GenAI) In Qualitative Research: Applications and Recommendations

Qualitative research generates vast amounts of textual, visual and audio data that require labour-intensive abstraction. Using technology like Generative Artificial Intelligence (GenAI) to streamline and accelerate data collection, analysis and reporting procedures is appealing. However, inherently qualitative research relies on a researcher’s social interaction with research participants, attention to the complexities of social contexts and research fields as well as in-depth analytical engagement with the data. It is therefore unsurprising that the use of GenAI in qualitative research is debated among researchers. Some advocate for incorporating Large Language Models (LLMs) in the research process, while others warn of the loss of human understanding when artificial intelligence is used to construct meaning from narrative data or even to conduct qualitative research interviews without a human interviewer. A third approach suggests moving beyond these binary positions to adopt reflexive and responsible use of this technology when conducting qualitative research.

The session invites researchers to critically contribute to this debate, reflecting on potential uses or conversely, rejection of GenAI use in qualitative research. We encourage contributions that cover different stages of the qualitative research process and highlight epistemological, methodological, analytical or other tensions. The session aims to facilitate a discussion on how to navigate the seemingly unstoppable presence of GenAI in qualitative research, addressing its usefulness (or not) and offering suggestions for ensuring quality, upholding the value of transparency, and adhering to ethical issues.