AI-textuality: Expanding intertextuality to theorize human-AI interaction with generative artificial intelligence

Abstract This paper introduces the concept of AI-textuality that extends Bakhtin’s notion of intertextuality to encompass interactions involving texts produced by generative artificial intelligence (GenAI). Intertextuality provides a valuable lens for understanding how GenAI outputs are created through the assemblage of digital and multimodal texts from vast datasets. Building on this perspective, this paper presents a model to theorize the intertextual nature of AI-generated texts in educational settings. The model frames human-AI interaction as an interplay between humans’ experiences in a material space and GenAI’s computational processing in a digital space. Drawing on data from a high school classroom, the model illustrates how students engaged with GenAI to discuss key ideas in the lesson. It highlights how students’ engagement with AI-generated texts was shaped by their textualization of experiences, the intertextual probability of GenAI’s responses, and the joint construction of knowledge between students and GenAI. Through the illustration, the paper argues that AI-textuality has the potential to revise and expand traditional understandings of intertextuality to incorporate our interactions with GenAI in the digital age.

Authors

Institutions

Publication Details

Journal
Applied Linguistics
Published
2025-04-19
DOI
https://doi.org/10.1093/applin/amaf016
Citations
7
Primary Topic
Topic Modeling
Type
article
Field-Weighted Citation Impact
17.37

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

AI-textuality: Expanding intertextuality to theorize human-AI interaction with generative artificial intelligence

Kok‐Sing Tang
7 citations
Applied Linguistics
Topic Modeling
17.37
article

AI-textuality: Expanding intertextuality to theorize human-AI interaction with generative artificial intelligence

Kok‐Sing Tang
article en
7 citations

Abstract

Abstract This paper introduces the concept of AI-textuality that extends Bakhtin’s notion of intertextuality to encompass interactions involving texts produced by generative artificial intelligence (GenAI). Intertextuality provides a valuable lens for understanding how GenAI outputs are created through the assemblage of digital and multimodal texts from vast datasets. Building on this perspective, this paper presents a model to theorize the intertextual nature of AI-generated texts in educational settings. The model frames human-AI interaction as an interplay between humans’ experiences in a material space and GenAI’s computational processing in a digital space. Drawing on data from a high school classroom, the model illustrates how students engaged with GenAI to discuss key ideas in the lesson. It highlights how students’ engagement with AI-generated texts was shaped by their textualization of experiences, the intertextual probability of GenAI’s responses, and the joint construction of knowledge between students and GenAI. Through the illustration, the paper argues that AI-textuality has the potential to revise and expand traditional understandings of intertextuality to incorporate our interactions with GenAI in the digital age.

Applied Linguistics
Curtin University (AU)
Curtin University of Technology
Openalex Percentile: Top 1%
Topic Modeling
17.37
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

AI-textuality: Expanding intertextuality to theorize human-AI interaction with generative artificial intelligence — Kok‐Sing Tang · Applied Linguistics (2025) | TGRS Research Map | TGRS