The Ethnographer in the Machine

Everyday Experiences with AI-enabled Data Analysis

Bibliographic Data

ID5948262
AuthorsSuzanne Walsh (Remesh), Sean Walsh (0000-0001-7308-5154), Jaroslava Pallas‐brink
Year2023
Volume2023
Issue1
Pages512-528
Publication date2023-11-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueEthnographic Praxis in Industry Conference Proceedings (CONFERENCE)
Journal identifiersISSN: 1559-890X • E-ISSN: 1559-8918
PublisherWiley (PUBLISHER • GB)
DOI10.1111/epic.12185
OpenAlexW4406323253
LanguageEN
Citations received4
References cited57

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

Data science · Ethnography · Human–computer interaction · Sociology · AI in Service Interactions · Anthropology · Computer Science · Ethics and Social Impacts of AI · Personal Information Management and User Behavior · Psychology

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