Considerations in using AI for Qualitative Analysis

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 capabilities differ from previously available tools designed to facilitate qualitative analysis, such as concept and topic modelling, automated coding, and machine learning. 

We then consider how the core capabilities of generative-AI 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 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 including ATLAS.ti,  DiscoverText, MAXQDA, NVivo and QDA Miner and also Chatbots like ChatGPT.