Putting Tools in Their Place: The role of time and perspective in human-AI collaboration for qualitative analysis

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‘Big data’ corpora are typically the purview of quantitative scholars, who may work with computational tools to derive numerical and descriptive insights. Recent work asks how technology, such as AI, can support qualitative scholars in developing deep and complex insights from large datasets. Jiang et al. address this question, finding that qualitative scholars are generally opposed to using AI to support their practices of data analysis. However, in this paper, we provide nuance to these earlier findings, showing that the stage of qualitative analysis matters for how scholars feel AI can, and should be, used. Through interviews with 15 CSCW and HCI researchers who engage with qualitative analysis of large corpora, we examine AI use at different stages of qualitative analysis. We find that qualitative scholars are open to using AI in diverse ways, such as for data exploration and coding, as long as it supports rather than automates their analytic work practice. Based on our analysis, we discuss how the incorporation of AI can shift some qualitative analysis practices as well as how designing for human-AI collaboration in qualitative analysis necessitates considering the tradeoffs in designing for scale, abstraction, and task delegation.