Research in the Era of Generative AI: Investigating Editorial Responses of Nigerian Communication Journals

Journal of Education, Communication, and Digital Humanities -Vol.2, No.1, Sept. 2025 pg. 130 Research in the Era of Generative AI: Investigating Editorial Responses of Nigerian Communication Journals Shadrach Idi, PhD. Department of Mass Communication, Taraba State University, Jalingo shadrac[email protected] & Maikomo, John Moses, PhD. Department of Political Science, Taraba State University, Jalingo [email protected] DOI : https://doi.org/10.5281/zenodo.17311155 Abstract The rapid adoption of generative artificial intelligence (AI) tools like ChatGPT in drafting text including manuscript has raised pressing questions about academic integrity and ethical publishing worldwide. This study investigated the preparedness of Nigerian communication journals to regulate the ethical use of AI in research and manuscript submissions. Using a triangulation approach, the study combined document review of editorial and publishing policies from ten Nigerian communication journals with in-depth interviews involving five journal editors. Data were thematically analysed to identify explicit policy references to AI, editors’ personal initiatives, and challenges hindering effective regulation. Findings revealed that while most journals emphasise originality and prohibit plagiarism, explicit references to AI use remain largely absent. Interviews further showed that editors had not taken proactive initiatives to regulate AI, instead leaning heavily on existing guidelines that were not designed with AI in mind. Key challenges included infrastructural deficits, financial constraints, and poor AI literacy particularly among older senior editors limiting the ability to implement or enforce AI-related policies. The study recommends urgent policy revisions, capacity building, and institutional collaboration to strengthen AI governance in Nigerian scholarly publishing and safeguard the integrity of communication research. Keywords: Generative AI, Editorial Policies, Research Ethics, Communication, Journals, Nigeria Journal of Education, Communication, and Digital Humanities -Vol.2, No.1, Sept. 2025 pg. 131 Introduction The emergence and rapid adoption of Artificial Intelligence (AI) in today's world have significantly transformed various fields, including academia and scientific research. A wide array of AI tools, such as ChatGPT, PaperPal, Elicit, Consensus, OpenAI, Research Rabbit, Perplexity, and HyperWrite, are now employed to facilitate almost every aspect of research, ranging from idea generation, manuscript writing, literature sourcing and review, to data analysis and citation management. AI tools can, in essence, support the research or academic writing process from inception to completion. This development is generating debate within the scientific community. A strand of literature (e.g., Çela et al., 2024; Corrêa, 2023; Cotton et al., 2023; Perkins, 2023a; Roe et al., 2023) argues that AI use in research discourages critical thinking a cornerstone of scholarly inquiry and poses numerous ethical concerns, including plagiarism, article fabrication, privacy invasion, and a lack of data transparency, authenticity, and credibility, which are fundamental pillars of scientific research. On the other hand, therefore, the use of AI tools in research risks undermining academic integrity. On the other hand, some scholars (e.g., Chubb et al., 2021b; Askin et al., 2023; Hosseini et al., 2023; Kenchakkanavar, 2023) view the application of AI in the research process as a positive development. According to them, AI tools enhance research efficiency by automating data analysis, literature searches, editing, and collaboration, while providing access to a broader range of materials. Therefore, AI tools in research lead to time-saving and the production of high-quality research papers. Despite the ongoing debate, there is a growing consensus that AI is here to stay, and attention has shifted to ensuring the ethical utilisation of AI tools. As Kocak (2024) aptly observes, scholarly publishing is rapidly evolving due to AI, necessitating that researchers, authors, reviewers, and editors update their knowledge and address associated challenges to ensure AI tools are used ethically and responsibly. In developed nations, the ethical use of AI in research has garnered substantial attention from publishers, universities, research funding bodies, and international organisations such as UNESCO (Nguyen et al., 2022; Wach et al., 2023; Dabis & Csáki, 2024). Prominent journal publishers, including Elsevier, Springer, COPE, MDPI, and Emerald, have proactively revised their editorial and publishing policies to address the implications of AI technologies. For example, MDPI and COPE mandate that authors disclose the extent of AI usage in their research. Elsevier specifies that generative AI and AI-assisted technologies should primarily enhance readability and language clarity, without replacing key authoring responsibilities. Journal of Education, Communication, and Digital Humanities -Vol.2, No.1, Sept. 2025 pg. 132 Similarly, Springer allows the use of AI tools for copy-editing to improve text readability and eliminate errors in grammar and punctuation but strictly prohibits their use for generative editorial work or autonomous content creation. These journal platforms have also expressed their commitment to continuously revisiting and adapting their publishing policies in response to the evolving landscape of AI and related technologies. Clearly stated regulations and editorial policies on AI usage are believed to play a crucial role in promoting the ethical use of AI and safeguarding the integrity of scientific output (Resnik & Hosseini, 2024). However, in Nigeria, although existing studies (e.g. Temitope et al, 2025; Pantuvo et al, 2025; Mohammed & Shehu, 2023; Bali et al, 2024; Shadrach et al., 2024) indicate a degree of AI adoption among researchers and higher educational institutions, there is a noticeable gap in understanding how research institutions and organisations are addressing the ethical challenges associated with these tools. While numerous journals and publishers across various disciplines continue to disseminate research, it remains uncertain whether these entities have revised their policies or established robust standards to ensure the ethical utilisation of AI technologies. Against this backdrop, the current study was conducted with a focus on communication journals in Nigeria. The Problem With the widespread adoption of AI especially Generative AI such as ChatGPT in academic research globally, it is anticipated that publishers may increasingly receive entirely AIgenerated submissions (Anderson et al., 2023; Tate et al., 2023). This development poses significant threats to research integrity and its contribution to societal progress. Detecting AIgenerated text remains highly challenging. Scholars such as Perkins et al. (2023) have revealed that even advanced AI detection software, including Turnitin, achieves a detection rate of only 54.8%, with inaccuracies identified across various detection tools (Weber-Wulff et al., 2023). This challenge is further compounded by the ongoing development of AI tools capable of evading many detection systems. In response, there has been a growing call for updated author guidelines and publishing policies to address the ethical use of AI in scholarly publishing (Liebrenz et al., 2023). It is argued that when authors are made aware of the potential harm of unethical AI use in their work, they are more likely to exercise caution (Lund & Ting, 2023). Journal of Education, Communication, and Digital Humanities -Vol.2, No.1, Sept. 2025 pg. 133 While this issue is receiving considerable attention in the United States and Europe, the same cannot be said for developing nations such as Nigeria. In Nigeria, numerous journals, including a range of communication journals published by universities and professional bodies, consistently receive and disseminate research articles. However, it remains unclear whether these journals have revised their policies or established standards to manage the use of AI, as there is a paucity of studies on this issue within the Nigerian context. This study aims to fill this gap, with a specific focus on Nigerian communication journals, considering their popularity. Research Questions The study was guided by the following research questions: 1. To what extent do Nigerian communication journals incorporate ethical guidelines on the use of generative AI in manuscript submissions? 2. What personal initiatives, if any, do Nigerian journal editors employ to regulate the use of AI in submitted manuscripts? 3. What challenges hinder the effective implementation of strategies for managing the use of generative AI in manuscript submissions? Conceptualizing AI Artificial Intelligence (AI) has a far longer history than is often assumed, with its philosophical and scientific roots traceable as far back as ancient Greece (Şenocak, et al 2023). The modern conception of AI, however, is strongly associated with the pioneering work of Alan Turing (1950) and the landmark Dartmouth Conference in 1956, where John McCarthy officially coined the term, defining it as “the science and engineering of making intelligent machines” (McCorduck, 2004). Since then, AI has continued to attract scholarly attention across disciplines, yet it still lacks a universally agreed definition. Different scholars have nonetheless provided working definitions. For instance, Bellman, as cited in Gil de Zúñiga, et al (2023), describes AI as computational systems capable of executing tasks generally linked with human intelligence, including learning, reasoning, perception, problem-solving, and decision-making. In a similar vein, Rashid and Kausik (2024) define AI as machine-based intelligence that simulates human cognitive functions, particularly decision-making and problem-solving. Within the broader spectrum of AI exists a more specialised category known as Generative AI. Generative AI refers to systems designed to create new content whether text, images, audio, code, or video through the identification and replication of patterns found in existing data ((Mariani & Dwivedi, 2024). A widely known example of such technology is ChatGPT. Unlike other AI models that may focus solely on classification or prediction, generative models Journal of Education, Communication, and Digital Humanities -Vol.2, No.1, Sept. 2025 pg. 134 distinguish themselves through their capacity for creativity, producing entirely new content in response to user prompts. The creative potential of generative AI has made it increasingly popular among diverse groups, particularly researchers and authors. However, this very capacity raises ethical concerns about originality, authorship, and the integrity of research outputs. The ability of such tools to generate entire manuscripts or significant portions of scholarly work has fuelled debates on whether generative AI undermines established academic standards or, conversely, provides innovative opportunities for knowledge production. Previous Related Empirical Studies The integration of AI into education has prompted numerous studies that highlight both the opportunities and challenges it presents for learning and research. These studies consistently emphasise the urgent need for ethical frameworks to regulate AI use in scientific contexts. Some especially in the developed countries have also examined how stakeholders in the scientific community especially journal publishers are adjusting their policies in response to the growing adoption of AI in research. For example, Perkins and Roe (2024) explored publisher policies on AI-assisted authorship and academic work using inductive thematic analysis. Their findings indicated broad agreement among publishers that human authorship remains essential, and although the use of generative AI tools is permissible, it must be transparently disclosed. Similarly, Corrêa et al. (2023) analysed 200 governance policies and ethical guidelines on AI use issued by public bodies, academic institutions, private companies, and civil society organisations worldwide. Their study sought to determine whether a global consensus exists on the ethical principles guiding AI applications and to contribute to the formation of future regulations. They identified 17 recurring principles, with transparency and accountability standing out as the most prominent. In another study, Hegazy et al. (2024) examined the ethical awareness of postgraduate students and their adherence to ethical standards when using AI in scientific writing. The research, conducted with 68 students at the College of Education, King Faisal University, Saudi Arabia, revealed moderate levels of awareness and compliance regarding the ethical use of AI. Likewise, Chen et al. (2024) investigated research integrity in the age of AI, identifying challenges and potential responses. Their findings underscored the need for comprehensive AI integrity guidelines, incorporating explicit protocols for AI use in data analysis and publication, in order to safeguard transparency and accountability in AI-supported research. Along similar lines, Qadhi et al. (2024) critically assessed discourses on ethical AI in higher education, Journal of Education, Communication, and Digital Humanities -Vol.2, No.1, Sept. 2025 pg. 135 arguing that policymakers, educators, and AI developers must collaborate to establish practical ethical guidelines. Dabis and Csáki (2024) further examined the ethical challenges posed by generative AI in higher education, analysing the initial responses of 30 universities ranked among the top 500 in the Shanghai Ranking between May and July 2023. Their study highlighted the ethical imperative that student work must reflect individual knowledge, with human actors bearing ultimate moral and legal responsibility for AI-related misconduct. In the African context, Ajwang and Ikoha (2024) investigated the “publish or perish” dilemma in Kenyan academia in relation to AI. Drawing on institutional guidelines, policies, norms, and previous studies, they identified unethical practices that undermine research integrity, such as falsification, fabrication, plagiarism, p-hacking, authorship conflicts, salami publication, duplicate publication, data manipulation, and inappropriate statistical analysis. The reviewed literature indicates that global research on how journals and publishers are developing policies to uphold ethical standards in the era of AI remains in its infancy, and is almost non-existent in Nigeria. Most existing studies focus broadly on educational and noneducational institutions, with only a few, such as Perkins and Roe (2024), addressing journalspecific contexts. This supports UNESCO’s position that although multiple concerns regarding AI in education have been identified, policy responses remain largely generic and implicit (Miao, et al, 2025). Furthermore, most of the existing studies rely on a single methodology, typically qualitative analysis or systematic literature reviews, without incorporating the perspectives of journal editors and authors. Such omissions limit deeper understanding of the issue. Therefore, while these studies provide valuable insights into the importance of revising or creating policies and guidelines for AI use across various sectors, there is a pressing need for research that directly investigates journal-specific policies, while also incorporating the perspectives of both editors and authors. This focus is particularly crucial because journals play a central role in disseminating cutting-edge research, which in turn shapes practice and policy across other domains. Addressing this gap underscores the significance of the present study. Theoretical underpinning This study is anchored on the Ethics of Technology Theory (ETT). The theory emerged in the mid-twentieth century in response to the rapid development of technologies. It represents a synthesis of the contributions of several scholars, including Hans Jonas, Langdon Winner, and James Moor (Green, 2022). The Ethics of Technology Theory posits that most technological innovations bring both benefits and risks to society, and therefore require careful ethical Journal of Education, Communication, and Digital Humanities -Vol.2, No.1, Sept. 2025 pg. 136 evaluation to strike a balance between these risks and benefits (Bashiir, 2025). In this regard, developers, users, and regulators share a moral responsibility to ensure that technologies are designed and applied ethically, in order to minimise inherent risks while maximising societal good. The issue of technology ethics has generated considerable debate and scholarship. Several frameworks have been proposed to explain the phenomenon. While general ethical theories such as utilitarianism and deontology can be applied to explain adoption of technology, nonetheless, there remains a paucity of studies explicitly identifying the Ethics of Technology Theory as a framework for examining the subject, suggesting that ETT is still developing. The present study adapts the Ethics of Technology Theory to explain the ethical challenges posed by the emergence of AI tools in research and to propose policy and editorial measures to guide journals and publishers. In doing so, this study extends the literature on ETT and its relevance to contemporary debates on technology and ethics. Materials and Methods This study adopts a triangulation research approach comprising document review and in-depth interviews. The document review was conducted using a checklist to analyse the editorial and publishing ethical policies of communication journals, with the aim of identifying any references to the use of AI in research and the nature of such references. In-depth interviews were conducted with journal editors to understand their perspectives on the use of AI in research, to uncover any strategies not explicitly stated in their policy and ethical guidelines, and to explore the challenges they encounter in regulating AI. The population of this study consists of all journals of communication and media studies published by universities and professional bodies in Nigeria, along with their editors. However, a purposive sample of ten journals and five editors was selected based on their online presence. The accessible journals are listed below. Journal of Education, Communication, and Digital Humanities -Vol.2, No.1, Sept. 2025 pg. 137 Table 1: List of selected Journals Investigated S/N Name of Journal Publisher / Address 1 International Journal of Communication Department of Mass Communication, University of Nigeria, Nsukka 2 Covenant Journal of Communication (CJOC) Department of Mass Communication, Covenant University, Ota, Nigeria 3 IMSU Journal of Communication Studies Department of Mass Communication, Imo State University, Owerri, Nigeria 4 Nassarawa State Journal of Communication and Media Studies (NJOMACS) Department of Mass Communication, Nasarawa State University, Keffi 5 Taraba State University Journal of Communication and Media Studies (TSUJCM) Department of Mass Communication, Taraba State University, Jalingo 6 Nigerian Journal of Communication (NJC) African Council for Communication Education (ACCE), Nigeria Chapter 7 Babcock Journal of Mass Communication (BJMC) Department of Mass Communication, Babcock University, Ilishan-Remo, Ogun State 8 NTAtvc Journal of Communication Nigerian Television Authority – Television College (NTAtvc), Jos 9 Nnamdi Azikiwe University Journal of Communication and Media Studies Department of Mass Communication, Nnamdi Azikiwe University, Awka 10 Journal of Communication and Media Studies (JCMR) Association of Media and Communication Researchers of Nigeria (AMCRON) Source: Authours’ Compilation Data collected from the document review (publishing policies) and in-depth interviews were analysed using inductive thematic analysis, a method widely employed in qualitative research for identifying, analysing, and reporting patterns (themes) within data (Braun & Clarke, 2006). This approach was chosen because it provides a flexible and robust research tool that enables a rich and detailed account of the data regarding the phenomenon under investigation. It further allows researchers to identify recurring themes of meaning within the dataset. Data Presentation The data obtained from the interviews and the review of the editorial and publishing policies of selected Nigerian communication journals were analysed and presented thematically. Verbatim quotations from respondents were included to reinforce points and to provide evidence that directly addressed each research question. Journal of Education, Communication, and Digital Humanities -Vol.2, No.1, Sept. 2025 pg. 138 RQ 1: To what extent do Nigerian communication journals incorporate ethical guidelines on the use of Generative AI in manuscript submissions? The first goal of the study is to determine the extent the journals incorporate ethical guidelines regarding the issue of Generative AI in their editorial and publishing policies. Based on the result of the analysis we found most Nigerian communication journals do not have any direct ethical guidelines or policy for managing the use of AI. Out of the ten journals investigated only one TSU Journal of Communication and Media Studies (TSUJCMS) has introduced guidelines regarding the use of AI. According to Item 2 in the updated TSUJCMS Guidelines for contributor’s states, “All submissions will undergo plagiarism and AI detection tests. Articles exceeding 15% plagiarism or 15% AI-generated content will be rejected”. Item 3 provide more detail information regarding AI use. It states thus: Authors must disclose any use of AI tools in their submissions, ensuring such contributions do not exceed 15%. The use of AI to generate entire articles, research ideas, or data without significant human oversight is strictly prohibited. Authors remain fully accountable for the integrity, originality, and validity of their work. Non-compliance with this policy will result in a public ban from the journal (https://www.tsujcms.org). Most of the journals underscored the importance of originality in their policies and publishing guidelines without mentioning anything about the use of AI, rather plagiarism. For instance the Babcock Journal of Mass Communication (BJMC) publishing policy and guidelines says,“BJMC takes academic integrity very seriously, articles that return above 15% similarity index on the Turnitin anti-plagiarism software would be rejected” https://journal.babcock.edu.ng/j/bjmc. In the same light, the publishing Guidelines of IMSU Journal of Communication Studies, states as follows: ...IMSU Journal of Communication Studies is committed to maintaining high standards with strict ethical policies. Any infringements of professional ethical codes, such as plagiarism, fraudulent use of data, or false claims of authorship, are strictly forbidden. All articles for submission must be original to the author(s) and free from plagiarism (https://www.imsujcs.com/policies.html). Similarly, the Nasarawa Journal of Multimedia and Communication Studies (NJOMACS) in its Plagiarism Policy states that: NJOMACS is committed to maintaining high standards through an in-depth peer-review process with sound ethical policies. Any infringements of professional ethical codes, such as plagiarism; including self-plagiarism, fraudulent use of data, are seriously frowned at by the journal with zero tolerance. https://www.njomacs.com/policies In the same vein, item 10 number in the author’s guideline of the Nigeria Journal of Communication (TNJC) states: “Manuscripts submitted to the TNJC shall be subjected to plagiarism check and only those that meet the acceptable threshold shall be published” Journal of Education, Communication, and Digital Humanities -Vol.2, No.1, Sept. 2025 pg. 145 Hagendorff, T. (2020). The ethics of AI ethics: An evaluation of guidelines. Minds & Machines, 30, 99–120. https://doi.org/10.1007/s11023-020-09517-8 Hegazy, H. Z., Gaber, S. A., Alkhateeb, I. A., Alqatam, M. A., Almughyirah, S. M., Mahgoub, Y. M., & Ali, H. A. (2024). Saudi postgraduate students' ethical commitment between awareness and application of artificial intelligence in scientific writing. International Journal of Learning, Teaching and Educational Research, 23(10), 583–598. https://doi.org/10.26803/ijlter.23.10.28 Hosseini, M., Resnik, D. B., & Holmes, K. (2023). The ethics of disclosing the use of artificial intelligence tools in writing scholarly manuscripts. Research Ethics, 19(4), 449–465. https://doi.org/10.1177/17470161231180449 Kenchakkanavar, A. Y. (2023). Exploring the artificial intelligence tools: Realizing the advantages in education and research. Journal of Advances in Library and Information Science, 12(4), 218–224. Kocak, Z. (2024). Publication ethics in the era of artificial intelligence. Journal of Korean Medical Science, 39(33). https://doi.org/10.3346/jkms.2024.39.e249 Liebrenz, M., Schleifer, R., Buadze, A., Bhugra, D., & Smith, A. (2023). Generating scholarly content with ChatGPT: Ethical challenges for medical publishing. The Lancet Digital Health, 5(3), e105–e106. https://doi.org/10.1016/S2589-7500(23)00019-5 Lund, B., & Ting, W. (2023). Chatting about ChatGPT: How may AI and GPT impact academia and libraries? SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4333415 Mariani, M., & Dwivedi, Y. K. (2024). Generative artificial intelligence in innovation management: A preview of future research developments. Journal of Business Research, 175, 114542. https://doi.org/10.1016/j.jbusres.2024.114542 McCorduck, P., & Cfe, C. (2004). Machines who think. A K Peters/CRC Press. https://doi.org/10.1201/9780429258985 Miao, F., Holmes, W., Huang, R., & Zhang, H. (2025, April 14). AI and education: Guidance for policy-makers. UNESCO. https://www.unesco.org/en/articles/ai-and-educationguidance policy-makers Mohammed, K., & Shehu, A. (2023). A review of artificial intelligence (AI) challenges and future prospects of explainable AI in major fields: A case study of Nigeria. Open Journal of Physical Science, 4(1), 1–18. https://doi.org/10.52417/ojps.v4i1.458 Nguyen, A., Ngo, H. N., Hong, Y., Dang, B., & Nguyen, B. T. (2022). Ethical principles for artificial intelligence in education. Education and Information Technologies, 28(4), 4221 4241. https://doi.org/10.1007/s10639-022-11316-w Pantuvo, M. K., Joseph, D., & Minakaro, F. M. (2025). AI and academics: What 500 Nigerian researchers think. Journal of Applied Information Science and Technology, 18(1). https://doi.org/10.70118/jaist.202501801.16 Journal of Education, Communication, and Digital Humanities -Vol.2, No.1, Sept. 2025 pg. 146 Perkins, M., & Roe, J. (2024). Academic publisher guidelines on AI usage: A ChatGPT supported thematic analysis. F1000Research, 12, 1398. https://doi.org/10.12688/f1000research.142411.2 Powell, A. B., Ustek-Spilda, F., Lehuedé, S., & Shklovski, I. (2022). Addressing ethical gaps in ‘technology for good’: Foregrounding care and capabilities. Big Data & Society, 9(2). https://doi.org/10.1177/20539517221113774 Qadhi, S. M., Alduais, A., Chaaban, Y., & Khraisheh, M. (2024). Generative AI, research ethics, and higher education research: Insights from a scientometric analysis. Information, 15(6), 325. https://doi.org/10.3390/info15060325 Rashid, A. B., & Kausik, M. A. K. (2024). AI revolutionizing industries worldwide: A comprehensive overview of its diverse applications. Hybrid Advances, 7, 100277. https://doi.org/10.1016/j.hybadv.2024.100277 Ray, P. P. (2023). ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope. Internet of Things and CyberPhysical Systems, 3, 121–154. https://doi.org/10.1016/j.iotcps.2023.04.003 Reijers, W., & Gordijn, B. (2019). Moving from value sensitive design to virtuous practice design. Journal of Information, Communication and Ethics in Society, 17(2), 196–209. https://doi.org/10.1108/JICES-10-2018-0080 Resnik, D. B., & Hosseini, M. (2024). The ethics of using artificial intelligence in scientific research: New guidance needed for a new tool. AI and Ethics. https://doi.org/10.1007/s43681-024-00493-8 Shadrach, I., Tsokwa, S., & Foseh, N. (2024). Knowledge and utilization of artificial research tools among university academics in Taraba State, Nigeria. TSU Journal of Communication and Media Studies, 4(2), 1–10. https://tsujcms.org Tate, T. P., Doroudi, S., Ritchie, D., Xu, Y., & Uci, M. W. (2023, January 10). Educational research and AI-generated writing: Confronting the coming tsunami. OSF Preprints. https://doi.org/10.35542/osf.io/4mec3 Temitope, A. B., Taoheedat, A., & Oyeranti, O. R. (2025). Artificial intelligence in Nigerian higher education: An analysis of opportunities and threats. International Journal of Multidisciplinary Research and Growth Evaluation, 6(3), 592–597. https://www.allmultidisciplinaryjournal.com Wach, K., Duong, C. D., & Ejdys, J., et al. (2023). The dark side of generative artificial intelligence: A critical analysis of controversies and risks of ChatGPT. Entrepreneurial Business and Economics Review, 11(2), 7–24. https://doi.org/10.15678/eber.2023.110201 Weber-Wulff, D., Anohina-Naumeca, A., Bjelobaba, S., Foltýnek, T., Guerrero-Dib, J., Popoola, O., Šigut, P., & Waddington, L. (2023). Testing of detection tools for AIgenerated text. International Journal for Educational Integrity, 19(1).