In recent years, artificial intelligence (AI) has significantly impacted the publication of research articles, transforming the landscape of academic writing and dissemination. However, the integration of AI in this process presents significant ethical challenges that require careful consideration. This review study utilized a comprehensive search strategy, employing keywords such as "artificial intelligence," "publication ethics," "ethical challenges," "academic integrity," and "research dissemination" to identify relevant articles in scientific databases including PubMed, Scopus, CINAHL, and Google Scholar. The search included articles published between 2010 and 2024 in both English and Persian. Research articles, systematic reviews, and case reports that included the specified keywords in their titles and abstracts were selected. A total of 150 articles were screened, and 50 relevant studies were included for detailed analysis. The analysis identified several ethical challenges associated with the use of AI in academic publishing. Concerns regarding academic integrity are paramount, as AI-generated content can blur the lines between original research and automated writing, raising concerns about authorship and plagiarism. Furthermore, the reliance on AI tools for data analysis and manuscript preparation can raise questions about the accuracy and validity of research findings. additionally, the potential for bias embedded within AI algorithms is a significant concern, as it can influence the selection of research topics, the framing of research questions, and even the peer review process. The lack of transparency in AI-driven editorial processes can further undermine trust in academic publishing. This review underscores the urgent need for robust ethical frameworks and regulations to guide the responsible use of AI in academic publishing. Increased awareness and training among researchers and editors regarding the ethical implications of AI are crucial. Interdisciplinary collaborations are essential to address these challenges effectively and ensure the integrity and trustworthiness of academic research in the AI era.
