The Ethnographer in the Machine: Everyday Experiences with AI-enabled Data Analysis

The growing use of artificial intelligence (AI)-enabled research tools in qualitative research has generated new and novel ways for researchers to interact with AI in data analysis, such as through the application of natural language processing (NLP) and machine learning (ML) algorithms on qualitative datasets. With the advancement of AI technologies, and its sensationalization within broader culture, sociotechnical entanglements have become increasingly complex, asking ever more of ethnographers, pushing their understandings of what constitutes the analytic process and the insights derived. It is critical for ethnographers to recognize the relationship inherent in interactions with AI-enabled research tools and develop a flexible approach to conceptualizing the researcher's role within these relationships given the fast-paced changes AI will likely bring to how ethnographers approach analyzing data. Scant interrogation has been placed specifically on AI-enabled qualitative data analysis and the relationship created between researcher and algorithm. This researcher-AI relationship is a relatively unknown territory and is deserving of greater explication. This paper proposes a model of researcher-AI interaction and argues that ethnographers can smartly leverage AI in data analysis if they deepen their understanding of AI tools.