Dear TIRF Board Members and Supporters,
Earlier this month, TIRF held its first symposium in China, in collaboration with Beijing Normal University–Hong Kong Baptist University United International College (BNBU, formerly United International College [UIC]) in Zhuhai, Guangdong Province. The event was titled “AI-Empowered English Language Teaching and Learning” and featured two distinguished speakers from TIRF: Professor David Nunan, a TIRF Trustee, and Professor Tianqing Zhu, a data science professor from City University of Macau. In addition, BNBU invited two esteemed speakers: Professor Li Wenzhong from Zhejiang Gongshang University and Professor Leng Jing from East China Normal University.
One of the highlights of the symposium was the two interactive panel discussions that I had the pleasure of moderating. Following each keynote speech, I posed challenging questions to the speakers and encouraged audience participation. These sessions sparked dynamic debates on the pros and cons of using technology in language education, and how English language educators can be empowered by AI in curriculum design, lesson planning, teaching methodologies, and assessment.
The symposium welcomed more than 200 participants from universities, schools, educational companies, and the tech industry. The day was filled with excitement, curiosity, collaboration, and inspiration. A key takeaway was the shared interest in co-creating a research agenda for AI-driven teaching and learning. We hope to reconvene next year to share research findings and best practices.
In my concluding remarks, I posed a provocative question to the audience: “What difference will differences make between AI for STEM and AI for Non-STEM?” The distinction I intended is not only about subject matter—the differences between STEM (science, technology, engineering, and math) and non-STEM areas shapes how AI is applied, interpreted, and trusted. In STEM fields, AI typically engages with structured, quantitative, and precise data—formulas, measurements, simulations. In contrast, AI in the humanities and social sciences deals with unstructured, qualitative, and context-rich data—texts, images, emotions, and social behaviors.
This distinction matters. STEM-related AI tends to prioritize accuracy and optimization. In non-STEM fields, interpretability and nuance are more important, as the data often allow for multiple meanings. In these contexts, AI becomes less about solving problems and more about augmenting human interpretation and fostering inquiry. In the arts, humanities, and language education, AI is not merely a tool but a collaborator. Language educators often treat AI as a subject of analysis, helping society reflect on AI’s social impacts. Ethical concerns—such as representation, authorship, voice, power, and cultural context—must remain central to how we integrate AI into our communication and interpretation.
I also shared that TIRF is currently developing ethical guidelines for language teachers in the use of AI. We believe it is our responsibility to provide educators with clear, practical examples of how AI can be used properly—not to shortcut learning, but to enhance it. Students should be guided in using AI to improve their learning efficiency and effectiveness, not as a way to outsource their academic efforts.
To remain indispensable in this AI-enhanced educational landscape, educators must:
- Embrace AI as a collaborative tool: Let AI handle routine tasks to free up more time for student engagement.
- Develop AI literacy: Understand both the capabilities and limitations of AI to integrate it effectively into teaching practices.
- Engage in ongoing professional development: Participate in training and programs on AI integration in education.
- Prioritize human-centric skills: Cultivate qualities like emotional intelligence and creativity—areas where AI cannot compete.
- Advocate for ethical AI use: Ensure that AI tools are used responsibly, with attention to data privacy, fairness, and equity.
I am grateful that TIRF’s Board of Trustees has taken the lead in developing a practical ethical framework for language teachers worldwide. I am confident that future TIRF events will continue to make a lasting impact on English language education worldwide in the age of AI.
Warm regards,
Jun Liu, PhD
TIRF President
