Human Agency in GenAI-ssisted Translation: Lessons from Translating Chinese Policy Reports

Ran Han

doi:10.47297/taposatWSP2633-456929.20250610

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Human Agency in GenAI-ssisted Translation: Lessons from Translating Chinese Policy Reports

6卷第10期

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Human Agency in GenAI-ssisted Translation: Lessons from Translating Chinese Policy Reports
Human Agency in GenAI-ssisted Translation: Lessons from Translating Chinese Policy Reports
Tianjin Foreign Studies University, Tianjin, 300204, China
2025年6卷第10期页码：143-148
纸质出版：2025-10-30
DOI：10.47297/taposatWSP2633-456929.20250610
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Ran Han. (2025). Human Agency in GenAI-ssisted Translation: Lessons from Translating Chinese Policy Reports. 科技理论与实践（英文版）, 6(10), 143-148.

Ran Han.Human Agency in GenAI-ssisted Translation: Lessons from Translating Chinese Policy Reports[J].Theory and Practice of Science and Technology,2025,06(10):143-148.
Ran Han. (2025). Human Agency in GenAI-ssisted Translation: Lessons from Translating Chinese Policy Reports. 科技理论与实践（英文版）, 6(10), 143-148. DOI： 10.47297/taposatWSP2633-456929.20250610.

Ran Han.Human Agency in GenAI-ssisted Translation: Lessons from Translating Chinese Policy Reports[J].Theory and Practice of Science and Technology,2025,06(10):143-148. DOI： 10.47297/taposatWSP2633-456929.20250610.

摘要

Abstract

The rapid development of Generative AI and large language models (LLMs) has significantly transformed the landscape of professional translation

especially for large-volume

high-stakes texts such as policy reports and research papers. While LLMs such as ChatGPT can produce fluent and contextually plausible drafts

their output often requires careful post-editing to ensure accuracy

appropriateness

and alignment with genre conventions. This paper explores the translator's agency in AI-assisted translation through a detailed examination of case studies drawn from a corpus of Chinese policy reports on sustainable agricultural supply chains. Each case demonstrates how the human translator identifies issues

evaluates alternatives

and makes contextually informed revisions

resulting in translations that are not only accurate but also rhetorically effective and suitable for policy discourse. The paper argues that human agency is not diminished but rather reconfigured in AI post-editing. Translators act as diagnosticians and evaluators

working with AI as co-creators to shape the text while ultimately serving as the final gatekeepers of meaning and quality. The study concludes by stressing the qualities translators must cultivate—critical reading

domain knowledge

genre awareness

stylistic sensibility

and editorial judgment—to fully harness AI as a productive partner while maintaining ultimate accountability for the final product.

关键词

Keywords

references

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