AI in Post Editing of News: A Study with Arabic News Articles

Authors

  • Muneer Hezam Alqahtani

    Department of Curriculum and Instruction, College of Education, King Faisal University, Al­Ahsa 31982, Saudi Arabia
  • Arif Ahmed Mohammed Hassan Al­Ahdal

    Department of English Language and Literature, College of Languages and Humanities, Qassim University, Buraydah 51542, Saudi Arabia

DOI:

https://doi.org/10.30564/fls.v7i10.11043
Received: 13 April 2025 | Revised: 22 July 2025 | Accepted: 31 July 2025 | Published Online: 29 September 2025

Abstract

The accelerated evolution of artificial intelligence (AI) tools has greatly influenced the practice of translation, specifically challenging their capacity to localize material in a manner that complies with the cultural and contextual demands of the target audiences. The study examines the localization capacity and precision of two of the most widespread  AI models—Google Translate and ChatGPT—in translating Arabic news stories into English. The study collected 15 news stories from major Saudi newspapers to act as the baseline dataset. AI­generated translations are compared with professionally created human translations to determine the level of localization achieved. All translations were evaluated by a panel of professional language experts according to predefined localization measures. Their evaluation is quantitatively analyzed via SPSS to determine statistical differences in localization quality. The research seeks to uncover how far AI­based tools can localize culturally unique content, identify challenges for such models, and provide genre­based differences in performance. The results provide insights into the limitations of AI in localizing news content today and the potential for future expansion. Furthermore, the results revealed stark differences in the quality of localization between AI and human translations, identifying key challenges and noting differences in the effectiveness of localization across various news types. ChatGPT emerged as the most accurate AI model for localizing the news data. This study adds to the body of literature on emphasizing the importance of post­editing and AI­aided translation in the case of Arabic­English language pairs.

Keywords:

AI Output; Arabic News Items; Localization; Post­Editing; Research Work

References

[1] Barrat, J., 2023. Our Final Invention: Artificial Intelligence and the End of the Human Era. Hachette UK: London, UK.

[2] Bian, L.J., 2021. Application of artificial intelligence technology in forestry news English translation. Forest Chemicals Review. 237–245. Available from:https://doi.org/10.17762/jfcr.vi.187 (cited 13 April 2025).

[3] Fuad, A., Al-Yahya, M., 2022. Recent developments in Arabic conversational AI: A literature review. IEEE Access. 10, 23842–23859. DOI: https://doi.org/10.1109/ACCESS.2022.3155521

[4] Muftah, M., 2022. Machine vs human translation: A new reality or a threat to professional Arabic-English translators. PSU Research Review. 8(2), 484–497. DOI: https://doi.org/10.1108/PRR-02-2022-0024

[5] Liu, X.T., Li, C.Z., 2023. Artificial Intelligence and Translation. In: Sin-Wai, C. (ed.). Routledge Encyclopedia of Translation Technology, 2nd ed. Routledge: New York, NY, USA. pp. 280–302.

[6] Fowler, R., 1991. Language in the News: Discourse and Ideology in the Press. Psychology Press: London, UK.

[7] Chuanmao, T. (ed.), 2021. Contemporary Translation Studies. CSMFL Publications: Beijing, China.

[8] Murgia, M., 2024. Code Dependent: Living in the Shadow of AI. Henry Holt and Company: New York, NY, USA.

[9] Cebollada, S., Payá, L., Flores, M., et al., 2021. A state-of-the-art review on mobile robotics tasks using artificial intelligence and visual data. Expert Systems with Applications. 167, 114195. DOI: https://doi.org/10.1016/j.eswa.2020.114195

[10] Zhang, B., Williams, P., Titov, I., et al., 2020. Improving massively multilingual neural machine translation and zero-shot translation. arXiv preprint. arXiv:2004.11867. DOI: https://doi.org/10.48550/arXiv.2004.11867

[11] Bentivogli, L., Bisazza, A., Cettolo, M., et al., 2016. Neural versus phrase-based machine translation quality: A case study. arXiv preprint. arXiv:1608.04631. DOI: https://doi.org/10.48550/arXiv.1608.04631

[12] Alowedi, N.A., Al Ahdal, A.A.M.H., 2023. Artificial Intelligence-based Arabic-to-English machine versus human translation of poetry: An analytical study of outcomes. Journal of Namibian Studies. 34, 1523–1538.

[13] Huang, X.Y., Li, S., Wang, Y., et al., 2023. Trends, research issues and applications of artificial intelligence in language education. Educational Technology & Society. 26(1), 112–131.

[14] Lim, J., 2023. How News Organizations and Journalists Understand Artificial Intelligence: Application of News Language Database to AI-Related News Stories. In: Nah, S. (eds.). Research Handbook on Artificial Intelligence and Communication. Edward Elgar Publishing: Cheltenham, UK. pp. 108–124. DOI: https://doi.org/10.4337/9781803920306.00015

[15] Al-Hassani, H., Chatterjee, A., 2023. Linguistic and Cultural Localization in AI-Driven Translation: An Arabic-English Perspective. Mathematics. 13(3), 449. DOI: https://doi.org/10.3390/math13030449

[16] De-Lima-Santos, M.F., Ceron, W., 2021. Artificial intelligence in news media: Current perceptions and future outlook. Journalism and Media. 3(1), 13–26. DOI: https://doi.org/10.3390/journalmedia3010002

[17] Baniata, L.H., Park, S., Park, S.B., 2018. A neural machine translation model for Arabic dialects that utilises multitask learning (MTL). Computational Intelligence and Neuroscience. 2018(1), 7534712. DOI: https://doi.org/10.1155/2018/7534712

[18] Li, S., Wang, B., 2023. Introduction to the special issue: Translation in political discourse and global narratives. International Journal of Chinese and English Translation & Interpreting. 2023(3), 1–16. DOI: https://doi.org/10.56395/ijceti.v2i1.86

[19] Akhtar, J., 2025. Translating Sacred Words: Ethical Frameworks for Religious Text Translation in Modern Pedagogy. In: Amini, M. (ed.). Cutting-Edge Approaches in Translator Education and Pedagogy. IGI Global Scientific Publishing: Hershey, PA, USA. pp. 161–190.

[20] Al-Ahdal, A.A.M.H., Alfallaj, F.S.S., Al-Awaid, S.A.A., et al., 2017. Translation courses at Qassim University, Saudi Arabia: A study of existing problems and possible solutions. US-China Foreign Language. 15(3), 45–53.

[21] Toral, A., Sánchez-Cartagena, V.M., 2017. A multifaceted evaluation of neural versus phrase-based machine translation for 9 language directions. arXiv preprint. arXiv:1701.02901. DOI: https://doi.org/10.48550/arXiv.1701.02901

[22] Läubli, S., Sennrich, R., Volk, M., 2018. Has machine translation achieved human parity? A case for document-level evaluation. arXiv preprint. arXiv:1808.07048. DOI: https://doi.org/10.48550/arXiv.1808.07048

[23] Al-Jarf, R., 2025. DeepSeek, Google Translate, and Copilot’s Translation of Arabic Grammatical Terms Used Metaphorically. Journal of Computer Science and Technology Studies. 7(3), 46–57.

[24] Zhang, B., Haddow, B., Birch, A., 2023. Prompting large language model for machine translation: A case study. In Proceedings of the 40th International Conference on Machine Learning, Honolulu, HI, USA, 23–29 July 2023; pp. 41092–41110.

[25] Mohammed, O.S.M., 2023. Yemeni Students Utilization of Google Translate for Learning English Language: Use, Advantages, and Disadvantages. Journal of Social Studies. 29(4), 136–156.

[26] Bielsa, E., Bassnett, S., 2009. Translation in Global News. Routledge: London, UK.

[27] Ranathunga, S., Lee, E.S.A., Prifti Skenduli, M., et al., 2023. Neural machine translation for low-resource languages: A survey. ACM Computing Surveys. 55(11), 1–37.

Downloads

How to Cite

Hezam Alqahtani, M., & Mohammed Hassan Al­Ahdal, A. A. (2025). AI in Post Editing of News: A Study with Arabic News Articles. Forum for Linguistic Studies, 7(10), 853–867. https://doi.org/10.30564/fls.v7i10.11043

Issue

Vol. 7 , Iss. 10 (October 2025): In progress

Article Type

Article

License

Copyright © 2025 Muneer Hezam Alqahtani, Arif Ahmed Mohammed Hassan Al­Ahdal

Creative Commons License

This is an open access article under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License.