Ethical Reconstruction of Linguistic Signs: An Ethical Study of Machine Translation Based on Linguistic Ontology

Zhaowei  Liang; Wenzhou Shu

doi:10.71204/859k3b53

Authors

Zhaowei Liang Guilin University Author
Wenzhou Shu Southwest University of Political Science and Law Author

DOI:

https://doi.org/10.71204/859k3b53

Keywords:

Machine Translation Ethics, Symbolic Violence, Semantic Entropy Increase, Language Game Theory, Symbolic Ethics Sensitivity Assessment Model, Linguistic Ethics Entropy, Cultural DNA Retention, Cross-Linguistic Games

Abstract

This study confronts the ethical crisis in machine translation (MT) caused by the systematic erosion of cultural semantics and symbolic integrity. While current MT systems achieve high technical performance (e.g., 72.3 BLEU scores in WMT2022), they fail to preserve cultural-contextual nuances, with 34.8% mistranslation rates for culturally loaded terms and 73% semantic reduction for low-resource language symbols. Through deconstructive analysis of Saussure’s arbitrariness principle and Wittgenstein’s language game theory, we demonstrate how algorithmic compression of dynamic semantic networks into unidirectional referential chains perpetuates symbolic violence, exemplified by the 89% loss of Confucian ethical dimensions in translating Chinese ren (benevolence) and 82% erasure of spiritual connotations in Arabic jihad. To address these issues, we propose the Symbolic Ethics Sensitivity Assessment Model (SESAM), a tripartite framework evaluating cultural fidelity, symbolic violence reduction, and ethical risk mitigation on a 0-5 scale. Validated in Meta’s No Language Left Behind project, SESAM increases cultural metaphor retention by 23.6% while maintaining translation efficiency. By integrating Peircean semiotics with computational linguistics, we construct a Cultural Semantic Vector Space using GloVe embeddings, resolving 93% of Traditional Chinese Medicine concept mapping failures. The study further develops the Linguistic Ethics Entropy (LEE) index, benchmarked at ≤0.23 for EU AI Act compliance, as the first quantitative metric for ethical MT. Our findings reveal three advancements: 1) semiotic topology exposing 47:1 corpus imbalance-induced cultural hegemony, 2) Ambiguity Markup Language (AML) reducing medical translation risks by 40%, and 3) an ontological framework reconciling Heideggerian linguistic essence with algorithmic probability through Derrida’s différance-encoded architectures. These interdisciplinary innovations bridge translation ethics, philosophy, and AI, offering actionable solutions for cultural DNA preservation and equitable cross-linguistic communication.

References

Gao, Y., & Cui, Q. (2024). Challenges and countermeasures of translation system construction in generative AI era. Shanghai Translation, (3), 36-42.

Hu, K., & Li, X. (2023). The development of translation research in the context of large language modelling: Problems and prospects. Chinese Translation, 44(6), 64-73.

Hu, Z., & Tang, Q. (2022). A critical review of Western translation ethics. China Translation, 43(6), 22-29.

Huang, Y. (2025). Building a translation team to meet the needs of the times. Foreign Language Teaching and Research, 57(2), 281-289.

Li, H., & Chen, H. (2020). Translation ethics research in the age of technologisation: Challenges and expansion. Journal of Northeastern University (Social Science Edition), 22(1), 112-119.

Li, Z. (2022). Meta-translation ethics: The cornerstone of translation ethics research. Shanghai Translation, (3), 14-20.

Li, Z. (2023). Returning to ethics: The future road of translation ethics research. Journal of Zhejiang Gongshang University, (1), 24-32.

Liu, C., & Kong, Y. (2023). The essence of ethics in translation technology and its basic direction. Journal of Foreign Languages, (5), 79–85.

Shen, H., Wang, X., & Luo, H. (2025). Machines have machine understanding: Philosophical reflections on the problem of understanding in machine translation. Natural Dialectics Letters, 47(3), 35-41.

Sun, J. (2024). Study on ethical misconduct of machine translation in the context of "Artificial Intelligence + Education". Overseas English, (14), 34-37.

Wang, H. (2024). Research on ethical challenges and response strategies of machine translation. Journal of Qiqihar Higher Teacher Training College, (5), 57-60.

Wang, H., & Liu, W. (2022). Research on translation data ethics in the era of big data: Concepts, issues and suggestions. Shanghai Translation, (2), 12-17, 64.

Wang, H., Cui, Q., & Liu, W. (2024). Research on the ethical risk of generative AI translation technology in legal translation. China Translation, 45(3), 110-117.

Wu, J. (2021). Rethinking and reconstructing translation ethics research. China Translation, 42(5), 5-14.

Wu, M., & Chen, H. (2023). Ethical issues of machine translation in the era of artificial intelligence. Journal of Foreign Languages, (6), 13-18.

Xiao, Z., & Wang, S. (2023). Ethical research on the application of translation technology in the era of artificial intelligence: Concepts, problems and countermeasures. Foreign Language E-learning, (5), 106-112.

Xiong, X., & Wang, Y. (2025). Ethical reflections on machine translation under the theory of "Eight Preparations". Journal of Yichun College, 47(1), 91-97.

Xu, X., Zhai, F., & Yang, L. (2024). An inquiry into the contingency and initiative of constructing the ethical system of machine translation under the perspective of translation ethics. Foreign Trade, (11), 103-105.

Yang, L. (2025). Research on language translation and management of multilingual archives. Archival Practice, (3), 171-173.

Yang, L., & Yang, Y. (2023). Reconceptualising translators' responsibilities in the age of digital technology from the perspective of translation ethics. New Horizons, (2), 145-147.

Yin, M. (2023). A review and prospect of research on the interactive longitudinal nature of translation and ethics: A review of The Lauterich Handbook of Translation and Ethics. Foreign Languages, 46(1), 117-121.

Zhang, L., Zhu, H., & Huang, D. (2024). Sign language translation based on deep learning: Past, present and future. Journal of Software, 35(8), 2938-2963.

Zhang, R., & Zhao, S. (2023). Exploring the ethical load of translation technology from the perspective of actor network theory. Foreign Languages, 46(6), 104-112.

Zhang, X., & Shao, L. (2021). Fundamental principles of constructing trustworthy machine translation systems: A viewpoint based on engineering ethics. Foreign Language, 37(1), 1-8.

Zhang, Y., & Zhang, F. (2024). Study on the outreach translation of marine power strategy from the perspective of ecological translation ethics: Taking Xi Jinping on the Governance of the Country (English Edition) as an example. Journal of Ocean University of China (Social Science Edition), (3), 121-128.

Zhu, J. (2023). Translation studies from the perspective of Marxist philosophy: Current status and prospects. Journal of Foreign Languages, (5), 86-92.