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This workshop considers the rise of Artificial Intelligence (AI) and its implications for qualitative research, to aid students and researchers in deciding whether and how its use is appropriate for their projects.

We begin mapping the field of Computer Assisted Qualitative Data AnalysiS (CAQDAS), putting recent developments in generative-AI in context. This includes differentiating the CAQDAS field from other related fields (text mining/content analysis and computational linguistics/ NLP), and reflecting on how generative-AI (GenAI) capabilities differ from previously available tools designed to facilitate qualitative analysis, including ‘traditional’ forms of AI (supervised and unsupervised machine learning) such as concept identification, topic modelling, text-mining and auto-coding etc.

We then consider how the core capabilities of GenAI map onto the qualitative research workflow and discuss whether, when and how each may have a place, and when they are not appropriate. This includes differentiating genres of GenAI tools for QDA, developments in speech-to-text technologies and the implications on transcription, the role and functioning of AI summarisation, coding and conversing within qualitative materials in different applications, and using generative-AI for ideation, data collection and contributing to the writing up of qualitative research findings.

In considering the technical capabilities we critically reflect on the methodological implications and ethical consequences at every stage of the qualitative workflow. This includes considering how AI tools are developed and marketed to researchers, implemented within existing tools, and how their use affects the research process and the legitimacy of outputs.

The workshop showcases a selection of CAQDAS-packages, new online Aps which harness GenAI capabilities and general-purpose AI tools.