Forthcoming

Leveraging ChatGPT for Optimized Email Communication: An Analysis of Benefits, Limitations, and Ethical Considerations for AUM Academic Staff

Authors

DOI:

https://doi.org/10.33806/ijaes760

Keywords:

benefits and limitations, ChatGPT, email communication, ethical considerations

Abstract

This study examined the benefits, limitations and ethical considerations of utilizing ChatGPT in email communication among AUM academic staff. Surveying the perspectives of 53 faculty members of the American University of Madaba (AUM) regarding the advantages, disadvantages, and the possible ethical consideration of using ChatGPT in email communication, the results revealed that AUM’s academic staff are aware of the ethical considerations, such as plagiarism and bias in language, of using ChatGPT in email communication. To add, the results indicated that ChatGPT provides several benefits such as efficient drafting of emails, clarity of emails, coherence of messages, enhanced language skills, and convenience of time. As for the limitations, the results showed that ChatGPT would, at times, give the wrong information because it failed to understand the context. Accordingly, replies were out of context and found incapable of handling complex or specialized topics. The study concluded with some recommendations that aim at improving utilizing Chatgpt in a responsible manner in email communication

Author Biographies

Majid Tarawneh, Qatar Foundation, Qatar

(Assistant Professor) – Corresponding Author

Department of English

Qatar Foundation, Qatar

Email: maltarawneh@qf.org.qa

Afag Khzouz, American University of Madaba, Jordan

(Assistant Professor)

Department of Translation, Faculty of Languages and Communications

American University of Madaba, Jordan

Email: a.khzouz@aum.edu.jo

Hanan Madanat, American University of Madaba, Jordan

(Associate Professor)

Department of Translation, Faculty of Languages and Communications

American University of Madaba, Jordan

Email: h.madanat@aum.edu.jo

Wael J. Hamdan, American University of Madaba, Jordan

(Assistant Professor)

Department of Translation, Faculty of Languages and Communications

American University of Madaba, Jordan

Email: w.hamdan@aum.edu.jo

References

Abdulfattah, Omar, Wafya I. Hamouda and Waheed M. A. Altohami. (2026). ‘Translating or stealing? Probing the limits of cross-lingual plagiarism detection systems in literary texts’. International Journal of Arabic-English Studies (IJAES), 26(1): 393-418.

AlAfnan, Mohmmad and Siti Fatimah Mohdzuki. (2023). ‘Do artificial intelligence chatbots have a writing style? An investigation into the stylistic features of ChatGPT-4’. Journal of Artificial Intelligence and Technology, 3(3): 85-94.

Altmäe, Signe, Ana Sola-Leyva, and Andres Salumets. (2023). ‘Artificial intelligence in scientific writing: A friend or a foe?’. Reproductive Biomedicine Online, 47(1): 3-9.

Aziz, Khalil and Hussein Obeidat. (2026). ‘Investigation into the future of human translation industry in the AI era from the translation practitioners’ perspectives’. International Journal of Arabic-English Studies (IJAES), 26(1): 97-114.

Brown, Tom B. and Kathrine E. Wilson. (2023). ‘Ethical considerations in language model usage: Plagiarism and beyond’. Proceedings of the 7th Conference on Ethics in Natural Language Processing, 112-120.

Brown, Tom B., Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin, Chess Jack, Clark Christopher, Berner Sam McCandlish, Alec Radford, Ilya Sutskever and Dario Amodei. (2020). ‘Language models are few-shot learners’. Arxiv, 1: 1-75.

Chen, Qiqi, Li Zhang and Xiaoxiao Wang. (2022). ‘Leveraging language models for efficient email communication in academic settings’. Journal of Information Science, 48(3): 456-470.

Chen, Xinyi, Yifan Li, Zheng Wei, Zhaohui Wang and Ming Zhou. (2022). ‘Exploring the effectiveness of prompt engineering for improving the quality of science communication with large language models’. Arxiv,1: 1-33. Retrieved from [link to arXiv preprint arXiv:2203.16920 ON arxiv.org]

Dergaa, Ismail, Karim Chamari, Piotr Żmijewski and Helmi Ben Saad. (2023). ‘From human writing to artificial intelligence generated text: Examining the prospects and potential threats of ChatGPT in academic writing’. Biology of Sport, 40(2): 615-622.

Fitria, Tira. (2023). ‘Artificial intelligence (AI) technology in OpenAI ChatGPT application: A review of ChatGPT in writing English essay’. ELT Forum: Journal of English Language Teaching, 12(1): 44-58.

Gao, Catherine A., Frederick M. Howard, Nikolay S. Markov, Emma C. Dyer, Shreya Ramesh, Yao Lu and Alexander Pearson. (2022). ‘Comparing scientific abstracts generated by ChatGPT to original abstracts using an artificial intelligence output detector, plagiarism detector, and blinded human reviewers’. SIGKDD Explorations, 26(2): 21-39.

Garg, Ravi K., Vijay L. Urs, Anshul A. Agarwal, Saurabh K. Chaudhary, Vijay Paliwal and Sujit Kar. (2023). ‘Exploring the role of ChatGPT in patient care (diagnosis and treatment) and medical research: A systematic review’. Health Promotion Perspectives, 13(3): 183-191.

Huang, Jiahui and Ming Tan. (2023). ‘The role of ChatGPT in scientific communication: Writing better scientific review articles’. American Journal of Cancer Research, 13(4): 1148-1154.

Huang, Lei, Weijiang Yu, Weitao Ma, Weihong Zhong, Zhangyin Feng, Haotian Wang, Qianglong Chen, Weihua Peng, Xiaocheng Feng, Bing Qin and Ting Liu. (2023). ‘A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions’. Arxiv, 1: 1-58.

Jarrah, Ahmad M., Yousef Wardat and Pedro Fidalgo. (2023). ‘Using ChatGPT in academic writing is (not) a form of plagiarism: What does the literature say?’ Online Journal of Communication and Media Technologies, 13(4): 1-20.

Jones, Matthew, Alice Smith and Laura Brown. (2022). ‘Domain-specific challenges in utilizing ChatGPT for email communication in academia’. Journal of Artificial Intelligence in Education, 35(2): 245-259.

Liu, An, Yifan Li, Ming Zhou, Zhaohui Wang and Xinyi Chen. (2023). ‘Mitigating bias in large language models for science communication’. Arxiv, 1: 97-111.

Megawati, Ruth, Hanida Listiani, Nuridin W. Pranoto, Maik Akobiarek and Ruth R. P. Megahati. (2023). ‘Role of GPT chat in writing scientific articles: A systematic literature review’. Jurnal Penelitian Pendidikan IPA, 9(11): 1078-1084.

Nazzal, Murad K., Ashlyn J. Morris, Reginald S. Parker, Fletcher A. White, Roman M. Natoli, Jill C. Fehrenbacher and Melissa A. Kacena. (2024). ‘Using AI to write a review article examining the role of the nervous system on skeletal homeostasis and fracture healing’. Current Osteoporosis Reports, 22: 217- 221.

Nguyen, Thi M. H. (2023). ‘EFL teachers’ perspectives toward the use of ChatGPT in writing classes: A case study at Van Lang university’. International Journal of Language Instruction, 2(3): 1-47.

Pallant, Julie. (2005). SPSS Survival Guide. New York: Open University Press.

Radford, Alec, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever. (2019). ‘Language models are unsupervised multitask learners’. Open AI Blog, 1(8): 1-24.

Rahman, Md. M., Harold J. R. Terano, Md Nafizur Rahman, Aidin Salamzadeh and Md. Saidur Rahaman. (2023). ‘ChatGPT and academic research: A review and recommendations based on practical examples’. Journal of Education, Management and Development Studies, 3(1): 1-12.

Raj, Rachna and Diego E. Costa. (2024). ‘The role of library versions in developer-ChatGPT conversations’. Proceedings of the 21st International Conference on Mining Software Repositories, 172 – 176.

Salvagno, Michele, ChatGPT, Fabio S. Taccone and Alberto G. Gerli. (2023). ‘Can artificial intelligence help for scientific writing?’ Critical Care, 27(75): 1-5.

Smith, Alice and Michael Johnson. (2021). ‘The impact of large language models on academic email communication’. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 8873-8882.

Wang, Yanbo, Yongcan Yu, Jian Liang and Ran He. (2025). ‘A comprehensive survey on trustworthiness in reasoning with large language models’. Arxiv, 1: 1-38.

Whelan, Brian and Andrea Patane. (2025). ‘Individual fairness in generative text models’. In Giuseppe Nicosia, Varun Ojha, Sven Giesselbach, Panos Pardalos and Renato Umeton (eds.), Machine Learning, Optimization, and Data Science, 73-91. New York: Springer.

Wilson, Katherine E. and John Smith. (2023). ‘Best practices for integrating ChatGPT into email workflows in academia’. Journal of Academic Communication, 27(3): 345-362.

Downloads