The AI Co-Ethnographer: How Far Can Automation Take Qualitative Research?
This addresses the problem of scaling qualitative research while preserving depth for researchers in social sciences and humanities, representing a novel method rather than an incremental improvement.
The paper tackles the labor-intensive and difficult-to-scale nature of qualitative research by introducing The AI Co-Ethnographer (AICoE), a novel end-to-end pipeline that organizes processes like open coding and pattern discovery, resulting in a more integrated and comprehensive analysis of qualitative data.
Qualitative research often involves labor-intensive processes that are difficult to scale while preserving analytical depth. This paper introduces The AI Co-Ethnographer (AICoE), a novel end-to-end pipeline developed for qualitative research and designed to move beyond the limitations of simply automating code assignments, offering a more integrated approach. AICoE organizes the entire process, encompassing open coding, code consolidation, code application, and even pattern discovery, leading to a comprehensive analysis of qualitative data.