Dear TIRF Supporters & Trustees,

One question that has kept me thinking a lot lately is “What does AI mean for English language education?”

For me, the implications of AI extend beyond the university classroom. AI is fundamentally changing the landscape of English language education itself. The question is no longer simply whether AI can help students learn English more efficiently. The deeper question is: What does it mean to learn, teach, assess, and research English when intelligent technologies become part of the learning environment?

This is where TIRF has an important leadership role to play.

We should encourage research on human–AI collaboration in language learning. Instead of framing the future as a competition between teachers and machines, we should investigate how learners, teachers, and AI can work together most effectively. When should AI provide feedback? When should teachers intervene? How can learners evaluate AI-generated feedback rather than simply accept it? And how do we preserve learner agency, critical thinking, and genuine communication in AI-rich environments?

We also need to rethink language assessment. If AI can generate a sophisticated essay in seconds, perhaps the traditional essay is no longer sufficient evidence of language proficiency. We need research on new forms of assessment that examine not only the final product, but also the learner’s reasoning, revision process, interaction, reflection, and ability to use AI responsibly. The question is not how to make assessment “AI-proof,” but how to make assessment meaningful in an AI-enabled world.

Another critical area is linguistic and global equity. AI systems do not necessarily represent all languages, cultures, and varieties of English equally. TIRF should support research examining how AI affects Global Englishes, multilingualism, linguistic diversity, and access to high-quality language education. Will AI democratize English learning around the world, or will it create a new digital and linguistic divide?

We must also investigate the changing role of the English language teacher. Teachers will need more than technical skills. They will need the professional judgment to evaluate AI-generated content, design meaningful AI-supported learning experiences, recognize the limitations and biases of AI, and teach students when to trust a machine—and when not to. Teacher education must therefore evolve from technology adoption toward AI-informed professional judgment.

Finally, TIRF should support research that looks beyond the immediate excitement surrounding particular AI tools. Technologies will change rapidly; our research agenda should therefore focus on enduring questions about learning, language, cognition, equity, ethics, and human development.

In this sense, TIRF’s role should not simply be to ask, “How can we use AI to teach English better?” We should also ask the more fundamental questions: What should English language education become in the age of AI? What forms of language proficiency will matter most? What should remain uniquely human? And how can research ensure that technological progress translates into meaningful, equitable, and human-centered learning?

These questions represent an important opportunity for TIRF to lead, guide, and support the field. Our goal should not be to predict the future of English language education, but to help shape a future in which AI serves learners, teachers, and society—and in which human curiosity, creativity, judgment, and communication remain at the heart of education.

TIRF has an opportunity to become one of the organizations that helps define the research questions, evidence standards, and ethical principles for English language education in the AI era.

Warm regards,

Jun Liu, PhD

TIRF President