Lately, there has been an increased interest towards leveraging the potential of artificial intelligence (AI) within academic writing. Out of other AI tools currently available, recent studies have observed that ChatGPT is extensively used to produce scientific abstracts [1]. ChatGPT has also been used for writing literature reviews, especially systematic reviews.

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Challenges in Research and Publication: Navigating the Impact of ChatGPT AI in Academia

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dr.olivia

Dr.Olivia | Research Writing and Formatting Consultant

28 Mar, 2025

dr.olivia

Dr.Olivia | Research Writing and Formatting Consultant

28 Mar, 2025

Introduction

With the growing integration of AI-powered tools like ChatGPT in academic exploration and publishing, both openings and challenges arise. While artificial intelligence (AI) can help experimenters in drafting, recapitulating, and refining content, it also presents ethical, legal, and scholarly enterprises that must be addressed [1].

This article indicates key problems linked with the use of AI in research, focusing on reference accuracy, accountability debates, ethical issues, AI and plagiarism, biases, and the broader implications for scholarship. By resolving these issues, researchers can include AI tools correctly while regulating academic research integrity and liability [2].

list of AI tools

Figure 1. List of AI tools available for writing assistance, translation and content generation. (Source: Chen, 2023 )


1. The debate over AI authorship

An important debate in academic research publishing is approval of AI-generated content for authorship. While AI helps in research by assisting with summarization, literature reviews, and content refinement, it lacks:

  • Responsibility–AI cannot be responsible for research results [3].
  • Intellectual contribution–It does not induce original study but processes available data [4].
  • Concurrence and ethical responsibility– AI cannot take responsibility for research and academic integrity [5].

To address these enterprises, academic publishers and research institutions must establish clear programs regarding the use of AI tools in academic writing. Most publishing bodies, including COPE (Committee on Publication Ethics), emphasize that authorship should be reserved for mortal contributors who can take full responsibility for their work [6].

  1. AI-references: The problem of absent citations

One of the major risks of AI-assisted research backing is the fabrication of references. For instance, ChatGPT occasionally provides presumptive looking but entirely lack of citations and references [7].

Illustration of AI-Fake references and citations:

ChatGPT was prompted to generate citations for the relationship between face roughness and cutting speed in machining. The tool resulted in the following:

  • Prabhu, S., & Ramamoorthy, B. (2019). Influence of cutting parameters on face roughness and tool wear during turning of AISI 304 pristine sword. Journal of Accoutrements Research and Technology, 8(5), 4929-4939.
  • Balasubramanian, V., Palanikumar, K., & Karthikeyan, R. (2017). An experimental disquisition of face roughness in milling of AISI 304 pristine sword, dimension, 100, 116-125.
  • Zhang, L., Wang, X., & Qian, X. (2019). Effect of cutting parameters on face roughness and residual stress in high-speed milling of Ti-6Al-4V. Accoutrements, 12 (2), 302.

 

These references appear legit but do not actually exist. Fabricated references undermine research credibility and contribute to misinformation [8].

How can researchers resolve this?

  • Verify every reference manually before adding it in a manuscript.
  • Cross-check sources through databases like Google Scholar, PubMed, Scopus, and Web of Science.
  • Use AI tools only as a supplement, not as a primary source of academic citations [9].
  1. The threat of unintentional plagiarism

AI-generated content can occasionally reproduce exact texts from available sources without proper criteria. Experimenters who intentionally use ChatGPT-generated text may be at risk of unintentional plagiarism, violating academic research integrity [10].

Ways to mitigate AI-induced plagiarism

  • Always fact- check AI-generated content and paraphrase information while citing the original source [11].
  • Use plagiarism discovery tools like Turnitin, iThenticate, or Grammarly’s AI and plagiarism checker [12].
  • Manually fit citations to ensure proper credit is given to original authors.

Proper citation and criterion are pivotal to ensure ethical AI use in research. The responsibility eventually lies with authors, pundits, and journal editors to uphold these norms.


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  1. Biases and misinformation
  • Algorithmic impulses–AI can amplify present impulses, making it difficult to distinguish between factual and deceiving content [12].
  • Source Data Limitations–AI is developed by training from the already existing data sources which may contain misinformation and bias [13].
  • Lack of Critical Thinking–AI does not involve critical thinking; it generates content based on learned framework rather than checking the accuracy of the content

How to mitigate inappropriate information and bias?

  • Verify AI content with reliable sources and expert reviews [4].
  • Use AI responsibly as a tool for guidance rather than a whole data source of information [11].
  • Establish a critical method by evaluating data before applying it into research [14].
  1. Ethical enterprises in AI-supported research

The integration of AI in academic jotting raises several ethical enterprises.

  • Transparency–The researchers should easily expose AI use in their articles.
  • Data sequestration–AI platforms store stoner relations, raising enterprises about confidentiality and intellectual property.
  • Responsibility–Since AI cannot be held responsible, the responsibility remains on authors to ensure research integrity [6].

Guidelines for ethical AI use in research

  • Acknowledge AI backing in research articles wherever applicable. It ensures confidentiality.
  • Follow institutional guidelines for AI operation in academic settings [5].
  1. The Rise of predatory publishing

Predatory journals warrants proper peer review and accept low-quality cessions, may take advantage of AI-assisted research to flood the academic space with deceiving studies.

Implicit consequences of AI-generated junk science

  • Lower credibility of academic publications.
  • Increased misinformation in academic literature.
  • Exploitation by raptorial journals that publish AI-assisted research without confirmation [12].

How to mitigate the spread of junk science?

  • Journals should apply AI-discovery tools to screen AI-generated manuscripts.
  • Experimenters must publish in estimable, peer-reviewed journals that uphold strict tract norms.
  • The academic community should develop AI-discovery algorithms to flag AI-generated, non-peer-reviewed content [5].

  1. Brand and power of AI-generated content

Who owns the content generated by AI? The issue of brand and intellectual property rights girding AI-generated text remains a grey area in academia.

  • Does OpenAI (ChatGPT’s creator) hold rights to the content?
  • Does the pioneer who prompts the AI for content own it?
  • What happens when content is based on AI copyrighted material?

 

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Need for clear AI copyright programs

  • Academic institutions and journals must define ownership and criterion programs.
  • Experimenters should admit AI’s part in content creation while ensuring compliance with brand laws.
  • Brand laws must evolve to address AI-generated content power and ethical operation [2].
  1. Limited AI availability and global inequalities

While AI tools like ChatGPT give precious backing to researchers worldwide, commercialization poses a threat of widening global inequalities in academia.

  • Subscription- grounded access may limit experimenters from low-income countries
  • Language limitations in AI models may hamper non-English-speaking scholars.
  • Unstable AI access could consolidate the being difference in research output between high-income and low-income regions [7].

How can the academic community ensure fair AI access?

  • Advocate for open-access AI tools for all experimenters, regardless of financial standing.
  • Encourage backing associations to support AI availability for experimenters in developing countries.
  • Promote multilingual AI development to ensure inclusivity in global exploration.

 

Conclusion

The application of AI in research presents both challenges and advantages. As AI is used to perform tasks such as citation, formatting, referencing, and structuring, it is crucial to ensure its ethical use while maintaining academic integrity.

Takeaways

  • Artificial intelligence cannot be considered as an author in articles.
  • Experimenters should add references and avoid AI-generated content.
  • AI content must be checked for bias, plagiarism, and inaccuracies.
  • The academic community must develop clear copyright guidelines for ethical AI use.
  • Equal access to AI tools is necessary to help global inequalities in exploration

By using AI responsibly, researchers can improve their work while maintaining the integrity of scholarly publishing.

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