Director Bio-texters Private Limited Bhopal 462001 India

Corresponding atuhor email: profshariqali@gmail.com 

Article Publishing History

INTRODUCTION

A decade ago,  Current Science, India’s premier fortnightly journal of the Indian Academy of Science, Bangalore, India, published a series of communications on the quality of research and education in Indian universities, including the doctoral theses, which are literally manufactured on a large scale [1,2 3 4]. These authors had pointed out the issues of publication ethics in the subcontinent, highlighting the prevailing menace and misuse of the fake impact factor-index concept, predatory journals, and their editorial board criteria. Evaluation of one’s research quality in Indian universities and colleges for academic promotions has always been a complicated issue, often swayed by academic politics, nepotism, and favouritism [2 ]. Recently, Ali  [ 5 ] published another article on the current status of scientific research and development in Indian   Universities and colleges, highlighting the problems and challenges higher education faces. This article examines the serious ethical concerns about the rising incidents of academic fraud, particularly the use of artificial intelligence, ChatGPT, and other technologies in the publication of research papers all over the world.

In the last many years, Indian institutions have started to improve their international rankings, and research papers are rapidly increasing in international indexing databases such as Web of Science and Scopus. It can be observed that India has nearly tripled its count of Scopus-indexed documents in the ten years from 2010-2020, outgrowing every other country in the world. This increase seems unnatural compared to the more organic growth observed across the world in the major countries, which have mature research ecosystems.

Despite this quantitative growth in research papers published, none of the Indian universities rank among the best in the world in terms of research and development. After 2020, the rate of research publications has accelerated even further. For instance, till 2022, India had contributed over 550,000 documents in Scopus compared to a lowly 30,000 documents compared to second-placed USA [6 ].

The excessive publication surge using artificial intelligence tools like ChatGPT (GPT = generative pre-trained transformer) is becoming a matter of concern and needs a comprehensive evaluation before it becomes a more complicated issue violating publication ethics. Artificial intelligence (AI) is a general concept that can be applied to specific types of machine-generated computation or learning that has evolved alongside the development of computers.  There are currently over 100 million users of ChatGPT, which was designed and implemented by OpenAI and launched in December 2022 based on the generative pretrained transformer 3.5 (GPT-3.5).

It is reported that the early release of GPT-4, a multimodal GPT capable of responding to text questions with images, has reduced instances of hallucinations [7]. These recent articles have identified a surge of publications, primarily consisting of rapid opinions and suggestions, during the initial phase of ChatGPT’s introduction. One year later, the highest number of ChatGPT-related articles was recorded in Scopus, with PubMed in the medical field and Web of Science across all subjects showing similar figures [7.8].

Numerous accolades have been given to the initiative of this technological innovation; however, some suggest that AI could be used for nefarious purposes, it may eliminate jobs, provide erroneous information, and it might be used for cheating at work or academics. While its origins can be traced to various “beginnings,” most sources suggest that modern development started with the work of Alan Mathison Turing in the early 1950s. The term “artificial intelligence” was coined at a conference organized by Marvin Minsky, John McCarthy, Claude Shannon, and Nathan Rochester of International Business Machines Corporation (IBM) in 1956. Since then, AI has made significant progress and is still making it beyond imagination in certain areas.

According to  Chetwynd  [9], one important concept in understanding AI is that it differs from automation, which is another type of technology that can assist us with productivity and workflow tasks. While automation uses machines to complete a process, the work of automation is based on a finite and explicit set of rules that do not change. AI goes further than automation: AI is the use of intelligent machines that can mimic human behavior or exceed it. It does this through several processes. Machine learning is the detection and prediction of patterns using algorithms after the software has been trained on large datasets.

Chetwynd has appropriately summarised that the use of AI is seductive. It can improve efficiency and productivity. It has the potential to increase equity in scientific publishing. It has the power to create well-written and elegant articles geared toward scientific journals. Yet, researchers and authors cannot be complacent in using this tool; instead, they must actively engage in the output created to ensure that it is correct and current in every aspect, as all authors will be held fully accountable for the material they submit for publication [9].

AI learns from the datasets and then can generate new information that is not specifically contained within the datasets but is predicted from what was learned. Natural language processing is the method used by AI software that allows the computer to understand, interpret, and generate human language. Large language models (LLMs) or generative AI-based software programs use both technologies to understand wide bodies of data, and generate new text on demand (Committee on Publication Ethics [10].

 Dowling and Lucey [11] reported that  AI can be utilized for accurate translation, grammatical correctness, and idea generation, as well as for summarizing content and crafting conclusions. Journal reviewers have found AI particularly useful for generating research ideas and summarizing data. Similarly, Gupta et al [12] have reported on the use of ChatGPT for plastic surgery research, describing its pros and cons. Likewise, Breeding et al have mentioned the immense utilization of ChatGPT in reshaping the future of medical education and learning perspectives, highlighting that it can be both a curse and a blessing [13].

The risk to scientific inquiry becomes exponential if one considers the use of datasets containing deepfake components becoming the base upon which AI is trained. Paper mills are heavily dependent on AI-generated text, and as quickly as the publication industry is developing algorithms to detect falsified research, the paper mills are becoming more sophisticated at avoiding detection, creating additional work and stress across the publication process [14].

There is a whole industry built around the development and submission of false research papers, with the mushrooming of agents, unemployed scholars, and companies that manufacture fake papers, known as “paper mills. COPE Publication Ethics describes these as “profit-oriented, unofficial and potentially illegal organizations that produce and sell fraudulent manuscripts that seem to resemble genuine research [15].

Recently, it has been observed that highly reputed journals have used competitive technologies to detect this academic fraud and retracted several papers across the world. Many journals have already instituted policies regarding the use of AI in scientific paper writing and publishing. It is important to realize that the issues concerned overlap the same issues regarding the use of human assistance in paper writing. The problem is how many publishing houses have access to the advanced technologies, leaving the paper mill industry not only to survive but also proliferate.

It has been discussed in depth by  Chetwynd 5   that AI may plagiarize the work of others. Consider that the role of AI is to use a dataset of information to answer any questions that are posed to it. While the text it creates in response to a question might be newly written by the AI program, it is looking for common patterns, and, in doing so, might unintentionally use the same words as a previous author.

One of the ways we guard against plagiarism is to provide credit for the concepts that come from others. This includes more than just the repetition of words, but also the ideas of others. Depending on AI to do the work of answering a question without additionally assessing the literature independently leaves researchers open to the possibility of claiming the ideas of others as their own, or using the ideas of others without appropriate attribution [16].

Despite all of these limitations, AI not only has the potential to bolster efficiency, but it also makes it possible to level the playing field in published scientific research. LLMs have the capacity to reduce language barriers for authors and mitigate the cost associated with language editing services. It can help with performing the mind-numbing tasks associated with publishing research, such as formatting citations and proofreading, allowing the researcher to spend more time on the development of quality content.

Advantages of AI and ChatGPT in research and development are many, like copy editing, language polishing, arranging citations and references and improving the quality of the manuscript. There are different levels of human and AI assistance in scientific paper writing. At the basic level would be the automated or human version of spell checking. Manuscripts submitted for publication should be spell-checked. There are grades of editing. The lowest level is copy editing. This includes spelling and grammar correction, ensuring consistency in style and formatting, and checking for factual errors. Readability and clarity can also be improved.

Another academic crime is plagiarism, which deprives the original authors of credit for their work. Likewise, if one copies from the AI program verbatim without attribution, it is a form of plagiarism. Paraphrasing without attribution is also unethical. The paraphrasing can be done by the authors themselves, by another person, or now, by an AI system. Taking a paragraph or more from someone else’s work, whether it is published or unpublished, paraphrasing it, and including the result in one’s own work is unethical; giving due credit to authors can minimise this academic fraud.

According to  an article written by Frye [17]  scholars shouldn’t use an AI text generator to produce academic writing. While AI text generators may be able to generate large amounts of text quickly and efficiently, they do not necessarily produce original, well-researched, and well-supported work. Scholars are expected to produce work that advances knowledge and understanding in their field of study, and using an AI text generator to produce academic writing may not fully meet those expectations.

 Additionally, using an AI text generator to produce academic writing, without credit being given to authors, may be considered plagiarism, as it involves presenting someone else’s work (or the work of an AI system) as one’s own without proper attribution or permission. This can violate the ethical standards of academic writing and undermine the originality and intellectual integrity of the work. Therefore, scholars should use their knowledge, skills, and research to produce original and credible academic writing, rather than wholly depending upon technological innovations that may raise ethical concerns.

Rahimi and Abadi [18], in an opinion paper recently have cautioned that as ultimate impact of the emergence of ChatGPT on scientific publishing is not fully understood, but it has diverse implications on the underpinnings of basic science and medicine. With improved versions of AI language models, their widespread application may become inevitable; thus, many manuscripts with AI input may emerge if scrutiny and peer review fail to catch them. Infallible tools for detecting AI-generated content are needed to help editors and peer reviewers in the immediate future. Although ChatGPT can produce more readable abstracts and respond concisely to critical information, the quality of these abstracts was generally rated as lower than that of the original texts [19]. Another study comparing ChatGPT-generated abstracts with those from an obstetrics journal indicated that the median score—based on Grammarly scores, writing issues, and correctness errors—was lower than that of the original abstracts, although there were no grammatical inaccuracies [11].

CONCLUSION

This paper critically examines the ethical implications of AI-assisted research publication, highlighting key risks such as data privacy breaches, algorithmic bias, intellectual property infringement, and the erosion of scholarly trust. It calls for the development of robust ethical frameworks and regulatory guidelines to ensure responsible and equitable use of AI in academic publishing. Despite all of these limitations, AI not only has the potential to bolster efficiency, but it also makes it possible to level the playing field in published scientific research. Fiercely emerging technological innovations  have the capacity to reduce language barriers for authors and mitigate the cost associated with language editing services. They can help with performing the mind-numbing tasks associated with publishing research, such as formatting citations and proofreading, allowing the researcher to spend more time on the development of quality content. AI holds transformative potential for academic publishing, but its ethical integration requires deliberate and collective action. By acknowledging and addressing these concerns, the research community can harness AI’s benefits while safeguarding the principles of scientific integrity and equity. We must not forget that AI tools are not autonomous agents; they operate under human direction. Therefore, the responsibility still lies with the researcher or author.

Conflict of interest: The Author declares no conflict of interest

Data Availability: All data are available from the corresponding author on a reasonable request.

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