Selected from a pool of 1,600 submissions across 18 categories and placing in the top 20 per cent globally as a finalist for the Conference in London, the IDEAL-Gen.AI platform represents a significant advancement in AI-driven instructional design, demonstrating exceptional innovation, impact and scalability, successfully progressing through four rigorous evaluation rounds conducted by a panel of 1,300 international higher education and edtech experts, competing on the global stage alongside prominent institutions such as Stanford University, Imperial College London and the University of South Australia.
Widely regarded as the “Oscars of Education”, the Conference was held in London (UK) from 1 to 3 December 2025. This premier global event brings together visionary education innovators, leaders, and investors committed to transforming learning worldwide.
The IDEAL-Gen.AI platform, developed by the DREAM (Digital Resources for Enhancing Adaptive Methodologies) Team led by Dr Ronnie H. Shroff, Principal Project Fellow of the Teaching and Learning Centre, is part of the Inter-institutional Collaborative Activities for Teaching Development and Language Enhancement (IICA-TDLE) project. This project is funded by the University Grants Committee of Hong Kong SAR, and is led by Lingnan in collaboration with the Hong Kong University of Science and Technology, the Chinese University of Hong Kong and the Hong Kong Polytechnic University.
Prof Frankie Lam, Director of the Teaching and Learning Centre, said that this achievement underscores Lingnan's steadfast commitment to advancing AI-driven educational innovation through cutting-edge technologies, driving transformative change in higher education at the local, regional and global levels.
Lingnan’s IDEAL-Gen.AI Platform is awarded the Bronze Award in the “Best Use of AI” category.
Dr Ronnie H. Shroff, Principal Project Fellow of the Teaching and Learning Centre, attends the QS Reimagine Education Awards and Conference 2025 and receives the Bronze Award in the “Best Use of AI” category.
As generative artificial intelligence (AI) becomes increasingly widely used in translation, questions have been raised over whether it could eventually replace professional interpreters. A joint study led by Lingnan University found that while AI can improve translation efficiency, it is still less capable than professional interpreters of adapting language to context and preserving rhetorical and communicative effects. The researchers conclude that human judgement and oversight remain essential, particularly in politically, diplomatically, and culturally sensitive settings. These findings have been published in Humanities and Social Sciences Communications, a Nature Portfolio journal.
The research team from Lingnan University and the Chongqing University of Posts and Telecommunications analysed 16 Chinese-language speeches delivered at the United Nations General Assembly (UNGA) between 2008 and 2023, and compared the official English interpretations by professional UN conference interpreters with AI-generated translations produced by ChatGPT-4o, examining how each handled language in different contexts.
Before generating the AI translations, the researchers designed detailed prompts that included the speaker's official position, institutional background, year of delivery, audience, and broader sociopolitical stance in order to approximate the contextual information available to professional interpreters.
However, despite providing the AI model with extensive contextual information, they found major differences between AI-generated translations and human interpretations in both contextual understanding and translation strategies.
One key difference concerns the use of personal pronouns. As Chinese frequently omits subjects, professional interpreters were more likely to introduce pronouns such as “our” and “they” to reflect interpersonal meanings and relationships between speakers and audiences, reinforcing collective identity and shared responsibility. AI-generated translations, by contrast, tended to produce more literal renderings with fewer personal pronouns.
For example, a Chinese sentence referring to vaccines as a powerful weapon against the pandemic was rendered by a professional interpreter as:
“Vaccination is our powerful weapon against COVID-19.”
whereas ChatGPT-4o translated it as:
“Vaccines are a powerful weapon against the pandemic.”
The researchers found that the interpreter’s addition of “our” strengthened the sense of collective identity, while the AI translation adopted a more neutral tone.
The study also identified distinct differences in how obligation and responsibility were expressed. Professional interpreters were more likely to adjust modal verbs according to context, using expressions such as “should” and “need to” to convey persuasive rather than mandatory obligation. AI-generated translations, however, relied more heavily on “must” and passive constructions, making responsibility less explicit.
For example, the professional interpretation reads:
“We need to enhance coordinated global COVID-19 response and minimise the risk of cross-border virus transmission.”
whereas the AI translation states:
“International joint prevention and control must be strengthened, and the cross-border spread of the virus must be minimised.”
The researchers found that the AI version obscures the agent responsible for action by using passive constructions.
The study also examined culturally embedded metaphors. More than half (52.63 per cent) of the AI translations reduced culturally specific metaphors to their literal meanings, weakening their rhetorical force. By contrast, professional interpreters adopted more flexible strategies, preserving, adapting, and explaining metaphorical expressions according to context. In about one-third of the cases (31.6 per cent), interpreters retained the metaphor and also conveyed its intended meaning.
A joint study by Lingnan University analyses 16 Chinese-language speeches delivered at the United Nations General Assembly between 2008 and 2023, comparing AI-generated translations with professional conference interpreting. The researchers find that even when AI is provided with extensive contextual information and prompts, major differences remain in contextual understanding and translation strategies between AI and human interpreters.
One example involved the traditional Chinese metaphor of people travelling “in the same boat”. The professional interpreter translated it as:
“We are called upon by our times to unite as one and work together for mutual benefit and win-win progress like passengers in the same boat.”
While ChatGPT-4o rendered it as “Working together and achieving mutual benefits and win-win outcomes are the objective demands of our time.”
According to the researchers, the AI translation conveyed the general meaning, but omitted the metaphorical imagery and its rhetorical impact.
The team noted that ChatGPT-4o generally produces fluent and grammatically accurate translations capable of completing translation tasks effectively. However, drawing on socio-cognitive theory, the study argues that professional interpreters consider not only the source text itself but also factors such as the speaker's identity, communicative setting, audience, cultural background, stance, and rhetorical purpose when deciding how to translate. This suggests that current large language models have yet to replicate fully the human capacity to interpret context and cultural meaning.
Prof Wang Binhua, Professor of the Department of Translation and Head of the Centre for English and Additional Languages at Lingnan University, member of the SIG on Artificial Intelligence in Translation and Interpreting of the European Language Council (ELC), said “Large language models still face the challenge of the ‘black box’, meaning that the mechanisms through which they produce particular translations remain difficult to explain. Unlike professional interpreters, who work within established professional ethical standards and are accountable, AI systems generate translations by identifying patterns in large volumes of language data and do not possess an intrinsic ethical framework. In translation tasks that require careful attention to cultural meaning and contextual understanding, human interpreters remain indispensable in making informed judgements about interpersonal relationships, rhetorical choices, and cultural expression.”
Prof Wang Binhua, Professor of the Department of Translation and Head of the Centre for English and Additional Languages at Lingnan University.
He added that AI is better positioned to augment rather than replace professional translators and interpreters. When integrated with human expertise, AI has the potential to improve efficiency while leaving context-sensitive and culturally informed decision-making in human hands.
For the full research paper A tale of two ‘contexts’: ideological differences in the translations of UN political speeches by human interpreters and by ChatGPT4o, please visit: https://www.nature.com/articles/s41599-026-07877-7
