oai:eurokd.com:article/2315 2026-09-11

Reframing Generative AI Bias as a Pedagogical Artifact for Critical AI Literacy in TESOL: A Conceptual Framework and Research Agenda Volume 56 Hassan Mohebbi Jessie S. Barrot Generative Artificial Intelligence Bias Computer-Assisted Language Learning Writing Assistant Critical AI Literacy <p style="text-align: justify;"><span style="font-size: 12pt; font-family: 'Cambria', serif; color: black;">This article reconceptualizes bias in generative artificial intelligence (GenAI) as a sociotechnical and pedagogical phenomenon rather than merely a technical flaw to be mitigated. Drawing on critical language awareness, critical applied linguistics, Global Englishes scholarship, and emerging research on AI-mediated language learning, it examines how bias is shaped by training data, language ideologies, institutional priorities, user practices, and broader social inequalities. In TESOL contexts, GenAI may privilege standardized English norms, marginalize linguistic diversity, reproduce culturally narrow representations, and weaken learner agency when its outputs are accepted uncritically. However, we argue that biased AI outputs can also serve as pedagogical artifacts for examining language, culture, identity, and power. To explain this potential, we propose the Pedagogical Transformation Framework of AI Bias, which conceptualizes learners&rsquo; movement from invisible bias to critical AI literacy through five stages: invisible bias, bias recognition, critical interrogation, transformative engagement, and critical AI literacy. From this perspective, we discuss its applications in writing, communication, intercultural learning, and assessment, while highlighting the central role of teacher agency and ethical safeguards. It concludes that the educational significance of AI bias depends not only on its presence but on how teachers and learners critically engage with and transform the assumptions embedded in AI-generated discourse.</span></p> Language Teaching Research Quarterly 2026-09-11 Text https://api.eurokd.com/Uploads/Article/2315/ltrq.2026.56.04.pdf https://doi.org/10.32038/ltrq.2026.56.04 en Pages 66–83