Waring2026a
| Waring2026a | |
|---|---|
| BibType | ARTICLE |
| Key | Waring2026a |
| Author(s) | Hansun Zhang Waring, Yo-An Lee |
| Title | Conversation analysis for artificial intelligence |
| Editor(s) | |
| Tag(s) | EMCA, Conversation analysis (CA), Artificial intelligence (AI), Wizard of oz (WoZ), Large language model (LLM), ChatGPT, Human-AI interaction (HAI) |
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| Year | 2026 |
| Language | English |
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| Journal | Research Methods in Applied Linguistics |
| Volume | 5 |
| Number | 3 |
| Pages | 100324 |
| URL | Link |
| DOI | 10.1016/j.rmal.2026.100324 |
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Abstract
Transforming the analytic and technological landscape, the recent rise of generative AI has sparked a surge of scholarly pursuits across a diversity of methodological terrains, and conversation analysis is no exception. With this exciting new direction also comes the need to examine the extent to which CA has advanced as a methodology for examining human-AI interaction (HAI). Based on a carefully curated corpus of “CA for AI” studies, this paper offers a brief summary of conversation analytic (CA) findings on HAI to date, examines the various methodological aspects of such studies, and provides a methodological illustration of what a CA analysis of human-AI interaction (HAI) looks like. These various attempts culminate in a reflection on a set of challenges that characterize the use of CA for investigating HAI as well as ways of navigating these challenges, thereby forming a benchmark for future research in CA-HAI in applied linguistics.
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