网络出版日期: 2026-01-28
基金资助
*中国外文局2022年国际传播与翻译人才评价国际化研究课题“西部地区地方高校翻译硕士实习实践教学实施效度与提升路径研究”(FYYJ006)
Generative AI Translation: Ethical Dilemmas and Governance Approaches
生成式人工智能正重塑翻译实践的基本范式,其在效率维度的卓越表现与其在伦理维度的失范状态形成鲜明反差。本文立足于切斯特曼的翻译伦理观,从职责伦理、沟通伦理与服务伦理切入,深度剖析AI翻译场域中责任主体悬置、文化信息耗散与译者主体性衰退三大迷思。具体而言,职责的模糊性导致错误归责与版权归属的双重争议;沟通的机械性引发语境坍塌与文化误读的风险;服务的工具化则带来译者专业价值隐没与用户知情同意虚置的困境。为匡正此失衡,研究倡导通过健全权责界定机制、培育AI文化翻译能力以及构建译者中心的人机协作关系,以实现治理层面的破局。本文主张,未来翻译事业发展的核心在于实现工具理性与价值理性的再平衡,以此筑牢可信赖的翻译伦理体系,护航生成式人工智能翻译的良性演进。
陈莉霞 . 生成式人工智能翻译的伦理迷思与治理破局[J]. 当代外语研究, 2025 , 25(6) : 134 -141 . DOI: 10.3969/j.issn.1674-8921.2025.06.015
Generative artificial intelligence (GAI) is reshaping the fundamental paradigm of translation. Its gains in efficiency starkly contrast with unsettled ethical practices. Drawing on Chesterman’s ethics of commitment, communication, and service, this paper identifies three persistent paradoxes in the GAI-mediated translation arena: suspended responsibility attribution, dissipation or distortion of cultural information, and the erosion of translators’ professional agency. Specifically, blurred duties give rise to dual disputes over error liability and intellectual-property attribution; mechanized communication increases the risks of contextual collapse and cultural misreading; and service instrumentalization obscures translators’ value while weakening user transparency and informed consent. To restore balance, the study proposes a governance agenda comprising: (a) robust mechanisms for delineating accountability across developers, platforms, translators, and clients; (b) cultivation of AI-enabled cultural translation competence to mitigate bias and preserve diversity; and (c) translator-centered human-AI collaboration that embeds expert oversight across the workflow. The paper argues that the sustainable evolution of GAI in translation hinges on re-balancing instrumental rationality with value rationality, thereby establishing a trustworthy ethical framework that safeguards quality, fairness, and public confidence.
| [1] | Abbas, A. 2025. Multilingual AI Bias Detection with SHADES:Building Fair and Inclusive AI Systems[EB/OL]. Unite.AI. [2025-06-27]. https//www.unite.ai/multilingual-ai-bias-detection-with-shades-building-fair-and-inclusive-ai-systems/. |
| [2] | Berman, A. 1984. L’èpreuve de l’étranger, Culture et Traduction Dans L’Allemagne Romantique[M]. Paris: Editions de Gallimard. |
| [3] | Bolukbasi, T., Kai-Wei Chang J. Zou. et al. 2016. Man is to computer programmer as woman is to homemaker? Debiasing word embeddings[J/OL]. Advances in Neural Information Processing Systems 29 (NIPS 2016). [2025-06-11]. https://doi.org/10.1016/j.sasc.2024.200072. |
| [4] | Chesterman, A. 1997. Memes of Translation: The Spread of Ideas in Translation[M]. Amsterdam and Philadelphia: John Benjamins Publishing. |
| [5] | Chesterman, A. 2014. Proposal for a Hieronymic Oath[J]. The Translator 7(2):139-154. |
| [6] | Ehrensberger-Dow, M., A. D. Benites & C. Lehr. 2023. A new role for translators and trainers: MT literacy consultants[J]. The Interpreter and Translator Trainer 17(3):393-411. |
| [7] | Kenny, D. 2022. Machine Translation for Everyone: Empowering Users in the Age of Artificial Intelligence[M]. Berlin: Language Science Press. |
| [8] | Mittelstadt, B. 2019. Principles alone cannot guarantee ethical AI[J]. Nature Machine Intelligence 1(11): 501-507. |
| [9] | Naveen, P. & P. Trojovsky. 2024. Overview and challenges of machine translation for contextually appropriate translations[J]. iScience 27(10): 110878. |
| [10] | Nimdzi Insights. 2025. The 2025 NIMDZI 100:Ranking & Market Analysis[EB/OL]. [2025-08-05]. https://www.nimdzi.com/nimdzi-100-2025/ |
| [11] | Stanovsky, G., N. A. Smith & L. Zettlemoyer. 2019. Evaluating gender bias in machine translation[EB/OL]. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019):1679-1684. [2025-06-11]. https://arxiv.org/pdf/1906.00591. |
| [12] | 方秋明. 2007. 汉斯·约纳斯论现代技术与责任伦理学[J]. 国外理论动态(8):90-91,94. |
| [13] | 杰米·萨斯坎德. 2022. 算法的力量:人类如何共同生存?(李大白译)[M]. 北京: 北京日报出版社. |
| [14] | 李俊、 杜思钰、 马望尧, 等. 2022. 人工智能时代的翻译伦理研究[J]. 科技智囊(11):62-69. |
| [15] | 鲁德. 2022. 多语言AI的现状(丁妍译)[EB/OL]. [2025-06-25]. https://www.ruder.io/state-of-multilingual-ai/?utm_source=chatgpt.com. |
| [16] | 陆艳. 2024. 人工智能时代翻译技术伦理构建[J]. 中国翻译 45(1):117-125. |
| [17] | 王华树、 刘世界. 2021. 人工智能时代翻译技术转向研究[J]. 外语教学 42(5):87-92. |
| [18] | 王华树、 刘世界. 2022. 大数据时代翻译数据伦理研究:概念、问题与建议[J]. 上海翻译(2):12-17. |
| [19] | 王少爽、 陈媛媛. 2025. 技术社会学视域下生成式人工智能对翻译行业发展的影响探析[J]. 上海翻译(4): 59-65. |
| [20] | 王贇、 张政. 2024. ChatGPT人工智能翻译的隐忧与纾解[J]. 中国翻译 45(2):95-102. |
| [21] | 吴美萱、 陈宏俊. 2023. 人工智能时代机器翻译的伦理问题[J]. 外语学刊(6):13-18. |
| [22] | 杨枫. 2023. 翻译在知识之间人在知识之上——写在《知识翻译学宣言》发表2周年之际[J]. 当代外语研究(5):1-2. |
| [23] | 叶立国. 2022. 科技事故三重“责任主体”的确立及其规范逻辑——基于约纳斯“责任原理”的考察[J]. 山东社会科学(10):38-145. |
| [24] | 中国翻译协会翻译技术专业委员会. 2025. 翻译行业生成式人工智能应用指南(2025)[R]. 北京: 中国翻译协会翻译技术专业委员会. |
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