AUTHENTICITY AND DEAUTHENTICITY: AI VS. HUMAN WRITTEN DISCOURSE
DOI:
https://doi.org/10.5281/zenodo.19643398Keywords:
AI-Generated Writing Works, AI-Produced Writing Creations, Authorship and Style, Discourse Qualitative ResearchAbstract
The paper presents research into how academia is addressing the growing issue of valid authorship, given that generative artificial intelligence (AI) tools are now producing similar products to those of humans. In response to this question, the authors undertake an analysis of the differences between what is produced by human authors versus machines(AI) through the examination of these products, specifically an academic essay (i.e., dissertations) created by humans and another created solely by a machine using comparative discourse analytical means. Both products are assessed in terms of the language used to convey meanings and the distinctiveness of the language compared with the author's use of language in their personal writings. The data for this project were collected from thirty-one Papers (i.e., one Paper created using machine-generated text and 30 essays by human-created texts) through an investigation of the organization of the writing, the meaning derived from the use of language, stylistic usage and choice, the way people tell their story, as well as the perception of writers as ideologically positioned. The findings support the conclusion that while the written work produced by machines is functionally coherent, there is less emotional content or risk taken in the telling of these stories. Additionally, there is no real variation among the types of stylistic choices or emotional content within these essays, as opposed to those written by humans, which allude to more grounded and personalized authorship, all of which contribute to a reader's perception of authenticity. Suggesting that there are certain dimensions of authorial voice that cannot be mimicked by AI tools and are therefore present in human-created texts that AI-generated texts do not possess in terms of originality.
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References
A. (1996). Borrowing others’ words: Text, ownership, memory, and plagiarism. TESOL Quarterly, 30(2), 201–230. https://doi.org/10.2307/3588141 https://onlinelibrary.wiley.com/doi/10.2307/3588141
Adel, A., & Alani, N. (2025). Can generative AI reliably synthesise literature? Exploring hallucination issues in ChatGPT. AI & Society, 40(11), 6799–6812. https://doi.org/10.1007/s00146-025-02406-7 https://link.springer.com/article/10.1007/s00146-025-02406-7
Alawida, M., Mejri, S., Mehmood, A., Chikhaoui, B., & Isaac Abiodun, O. (2023). A comprehensive study of ChatGPT: Advancements, limitations, and ethical considerations in natural language processing and cybersecurity. Information, 14(8), Article 462. https://doi.org/10.3390/info14080462 https://www.mdpi.com/2078-2489/14/8/462
Dogru-Huzmeli, E., Moore-Vasram, S., Phadke, C., et al. (2025). Evaluating ChatGPT’s ability to simplify scientific abstracts for clinicians and the public. Scientific Reports, 15(1), 33466. https://doi.org/10.1038/s41598-025-11086-8 https://www.nature.com/articles/s41598-025-11086-8
Farooq, M. (2025). Perceived authenticity of AI-generated images: Trust, realism, and revision behavior. Journal of Visual Communication and AI Studies, 4(1), 1–18. https://www.jvcai.org/article/1006
Glikson, E., & Woolley, A. W. (2020). Human trust in artificial intelligence: Review of empirical research. Academy of Management Annals, 14(2), 627–660. https://doi.org/10.5465/annals.2018.0057 https://journals.aom.org/doi/10.5465/annals.2018.0057
Information Technology Industry Council. (2023). Approaches to content authentication in the age of generative AI. https://www.itic.org/publications/ai-content-authentication-2023
Information Technology Industry Council. (2024). Advancing AI authentication: Provenance, watermarking, and standards. https://www.itic.org/publications/ai-authentication-standards-2024
Ippolito, D., Duckworth, D., Callison-Burch, C., & Eck, D. (2020). Automatic detection of generated text is easiest when humans are fooled. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 180–191. https://doi.org/10.18653/v1/2020.acl-main.16 . https://aclanthology.org/2020.acl-main.16
Labadze, L., Grigolia, M., & Machaidze, L. (2023). Role of AI chatbots in education: Systematic literature review. International Journal of Educational Technology in Higher Education, 20(1), Article 56. https://doi.org/10.1186/s41239-023-00426-1 https://link.springer.com/article/10.1186/s41239-023-00426-1
McKee, H. A., & Porter, J. E. (2009). The ethics of digital writing research. Peter Lang. https://www.peterlang.com/document/1050644 https://www.peterlang.com/document/1050644,
Sardinha, T. B. (2024). AI-generated vs human-authored texts: A multidimensional comparison. Applied Corpus Linguistics, 4, Article 100083. https://doi.org/10.1016/j.acorp.2023.100083 https://www.sciencedirect.com/science/article/pii/S2666799123000436
Shuhaiber, A. (2025). Determinants of continued use of ChatGPT among university students. Computers & Education: Artificial Intelligence, 6, 100–118. https://www.journals.elsevier.com/computers-andeducation-artificial-intelligence
Soni, M., & Wade, V. (2023). Comparing abstractive summaries generated by ChatGPT to real summaries through blinded reviewers and classification models. arXiv. http://arxiv.org/abs/2303.17650
Vanneste, S., Padiyath, R., & van den Bosch, A. (2024). Perceived agency and trust in AI-generated content. Human–Computer Interaction, 39(3), 401–429. https://doi.org/10.1080/07370024.2023.2284567 https://www.tandfonline.com/doi/full/10.1080/07370024.2023.2284567
Zhang, M. A., Amjad, A. I., Aslam, S., & Fakhrou, A. (2024). Global insights: ChatGPT’s influence on academic and research writing, creativity, and plagiarism policies. Frontiers in Research Metrics and Analytics, 9, Article 1486832. https://doi.org/10.3389/frma.2024.1486832 https://www.frontiersin.org/articles/10.3389/frma.2024.1486832/full.
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Copyright (c) 2025 Sofia Maqbool , Dr. Sidra Ahmad (Author)

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