Speaker
Description
Artificial intelligence (AI) tools, particularly generative AI, are increasingly used in English language teaching (ELT) for feedback, assessment support and language practice. Language learning, however, produces rich forms of personal data: learners’ written texts, voice recordings and classroom contributions often carry their experiences, opinions and identities. Although privacy is an established principle in international AI ethics guidance, it has received less direct attention than fairness or transparency as a construct in ELT, and frameworks for AI in education tend to address education broadly, with limited attention to language-specific concerns. This conceptual paper examines what privacy and data governance mean at the level of English teachers’ everyday classroom decisions. Drawing on a narrative review of ELT scholarship on assessment ethics, learner identity and computer-assisted language learning, together with research on AI in education, it reads these literatures through the privacy and data governance principle of UNESCO’s (2021) Recommendation on the Ethics of Artificial Intelligence. The review suggests that privacy, although seldom named as such, has long been embedded in ELT practice through the confidentiality of assessment information and respect for what learners disclose in communicative tasks. AI extends these responsibilities into digital environments, where learner data may be collected, stored and reused in ways that teachers and learners cannot easily see. On this basis, the paper proposes three teacher-level dimensions of privacy in AI-mediated ELT (assessment privacy, learner identity privacy and digital data privacy), each operationalised through practice indicators such as anonymising learner work before using AI for feedback, keeping sensitive personal information out of prompts, and selecting tools with adequate data protection. The framework offers a basis for teacher education and for empirical validation, particularly in secondary schools, where young learners may not fully understand what AI tools collect.
Keywords: AI ethics; learner privacy; data governance; English language teaching; generative AI; teacher practice