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Scientific writing is a major consideration when writing a research paper, as it encompasses all aspects of the research. With the rise of digitalization, new opportunities have emerged for the development of Artificial intelligence (AI)-driven tools and algorithms designed to analyze the vast amounts of data being uploaded. It has allowed researchers and practitioners to more efficiently access and evaluate a vast array of scientific papers. This capability facilitates the connection of related studies from the past, identifies research gaps, and speeds up the processes of literature review, evidence generation, and knowledge discovery. Despite these advancements, AI tools are subject to ethical considerations, regulatory approval, compliance with data protection regulations, journal guidelines, transparency, and public perception. Some text prompts are used to instruct AI tools to generate effective information. Fostering trust and transparency with AI tools in scientific writing includes operationalizing frameworks, addressing discrepancies, reducing plagiarism, and generating new innovative ideas. Future trends suggest that AI capabilities will keep advancing and developing, underscoring the need for ethical considerations and the need to balance AI automation with human expertise. However, it cannot replace the creativity and critical thinking skills that are crucial for scientific writing and research. The key objective of this review is to discuss and assess various AI-based tools and algorithms, focusing on their key features and how they can support researchers and authors in enhancing their writing skills.
Sharma et al. (Tue,) studied this question.
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