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Lingnan study: AI falls short on context and cultural rhetoric

HK

Lingnan study:  AI falls short on context and cultural rhetoric
HK

HK

Lingnan study: AI falls short on context and cultural rhetoric

2026-07-21 14:28 Last Updated At:14:30

 

 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.

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.

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

Hong Kong’s universities have once again demonstrated academic strength on the international stage. The latest 2026 ShanghaiRanking’s Global Ranking of Academic Subjects shows that at least 90 subjects across Hong Kong’s universities have entered the global top 50, with 21 subjects ranking among the world’s top 10. The Hong Kong Polytechnic University (PolyU) claimed the top spot globally in two subjects: Transportation Science & Technology and Hospitality & Tourism Management. The University of Hong Kong (HKU), The Education University of Hong Kong (EdUHK), and The Chinese University of Hong Kong (CUHK) all made it into the global top 10 for Education, underscoring the city’s overall strength in the field.

The University of Hong Kong, Photo source: reference image

The University of Hong Kong, Photo source: reference image

HKU’s Education subject ranked second globally in this year’s ranking, its highest-ever position, while retaining its place as the top in Asia. Professor Yang Rui, Dean of the Faculty of Education at HKU, expressed his delight at the achievement. He noted that it fully reflects the collective efforts of faculty members in conducting high-level research and publishing in leading international academic journals, as well as the Faculty’s close partnerships with research collaborators worldwide, which continue to expand the reach and impact of its work. “I am deeply grateful to our Faculty members for their commitment to advancing educational knowledge and promoting the exchange and application of these outcomes worldwide,” he said.

The Hong Kong Polytechnic University, Photo source: reference image

The Hong Kong Polytechnic University, Photo source: reference image

PolyU delivered the most outstanding performance in this ranking, with 23 subjects entering the global top 50, the highest number among all Hong Kong institutions. Six of its subjects ranked in the global top 10. In addition to the two subjects that topped the world, these include Management (global 2nd), Civil Engineering (global 3rd), Energy Science & Engineering (global 4th), and Mechanical Engineering (global 10th), spanning multiple traditional strengths in engineering and management.

The City University of Hong Kong, Photo source: reference image

The City University of Hong Kong, Photo source: reference image

City University of Hong Kong (CityU) had 44 subjects ranked this year, two more than last year. Twenty-two subjects entered the global top 50, with four subjects- Library & Information Science, Metallurgical Engineering, Energy Science & Engineering, and Public Administration- making it into the global top 10. Furthermore, CityU ranked first in Hong Kong in 10 subjects, including Library & Information Science, Business Administration, and Veterinary Sciences, leading other local institutions in multiple areas.

The Lingnan University, Photo source: reference image

The Lingnan University, Photo source: reference image

Lingnan University had eight subjects ranked this year, a nearly twofold increase from three last year. Five subjects, including Computer Science & Engineering and Electrical & Electronic Engineering, appeared on the list for the first time. Its Artificial Intelligence subject, newly listed last year, jumped dramatically in the rankings and entered the global top 100 for the first time, placing in the 76–100 band. Professor Qin Si Zhao, President of Lingnan University, said the results reflect growing international recognition of the University’s academic and research work. “Lingnan will review the ranking results and their assessment indicators, using them as a reference to further consolidate our ‘Liberal Arts + Technology’ development direction,” he said.

Photo source: shanghairanking.com

Photo source: shanghairanking.com

The ShanghaiRanking’s Global Ranking of Academic Subjects is released by ShanghaiRanking, a higher education evaluation agency. It covers 57 subjects across five major fields: Natural Sciences, Engineering, Life Sciences, Medical Sciences, and Social Sciences. The ranking uses international academic indicators to assess the performance of higher education institutions worldwide in each subject, evaluating five categories: World-Class Faculty, World-Class Research Output, High-Quality Research, Research Impact, and International Collaboration. This year’s ranking assessed over 3,000 universities globally, with more than 2,000 institutions from about 96 countries and regions appearing on the lists.

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