Beyond the Human-AI Binaries: Advanced Writers' Self-Directed Use of Generative AI in Academic Writing

2025-05-17

AI Summary

This study challenges two prevailing assumptions—that generative AI (GAI) undermines deep learning and offers limited value to advanced L2 writers—by investigating how high-proficiency L2 English writers strategically and autonomously deploy GAI to navigate academic writing challenges. Employing a qualitative case study design integrated with critical discourse analysis and a poststructuralist theoretical framework, the research deconstructs GAI’s multifaceted agency in second-language writing. It introduces an original “dialogic use” model, identifying three writer-constituted ontological positions toward AI: as a mechanical system, a socially constructed entity, and a distributed agentic partner. This model transcends the reductive tool-versus-substitute binary, reconceptualizing authorial identity, text production, and learning processes. The findings advance a destigmatized AI ethics framework and propose a writer-virtue–centered human–AI collaboration paradigm. (149 words)

Technology Category

• Philosophy and Ethics of AI: Artificial General Intelligence
• Natural Language Processing: Sentiment Analysis, Stylistic Analysis, and Argument Mining
• Humans and AI: AI for Accessibility

Application Category

• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Search and Retrieval-Augmented AI: Agentic search

Abstract

This study explores the self-directed use of Generative AI (GAI) in academic writing among advanced L2 English writers, challenging assumptions that GAI undermines meaningful learning and holds less value for experienced learners. Through case studies, we investigate how three (post)doctoral writers engage with GAI to address specific L2 writing challenges. The findings revealed a spectrum of approaches to GAI, ranging from prescriptive to dialogic uses, with participants positioning AI as a tool versus an interactive participant in their meaning-making process, reflecting different views of AI as a mechanical system, social construct, or distributed agency. We highlight the ways AI disrupts traditional notions of authorship, text, and learning, showing how a poststructuralist lens allows us to transcend human-AI, writing-technology, and learning-bypassing binaries in our existing discourses on AI. This shifting view allows us to deconstruct and reconstruct AI's multifaceted possibilities in L2 writers' literacy practices. We also call for more nuanced ethical considerations to avoid stigmatizing L2 writers' use of GAI and to foster writerly virtues that reposition our relationship with AI technology.

Problem

• Explores self-directed Generative AI use in L2 academic writing
• Investigates AI's role as tool versus interactive participant
• Challenges traditional authorship and learning binaries with AI

Innovation

• Case studies explore GAI in academic writing
• GAI ranges from prescriptive to dialogic uses
• Poststructuralist lens redefines human-AI binaries