Is ChatGPT a "Fire of Prometheus" for Non-Native English-Speaking Researchers in Academic Writing?

Area of Science:

• Academic Publishing
• Scientific Communication
• Artificial Intelligence in Research

Background:

• Non-native English-speaking researchers face challenges in academic writing.
• Large language models (LLMs) offer potential as writing aids.
• Previous tools lacked personalized, 24/7 support for manuscript preparation.

Purpose of the Study:

• To explore the utility of LLMs in supporting academic writing for non-native English speakers.
• To identify potential risks and mitigation strategies associated with LLM use in research.
• To provide guidance on the responsible application of LLMs in manuscript preparation.

Main Methods:

• Review of LLM capabilities for text generation and editing.
• Analysis of potential risks: hallucination, plagiarism, and data privacy.
• Examination of best practices for LLM integration into the writing process.
• Discussion of emerging journal policies on AI tool usage.

Main Results:

• LLMs can function as effective English tutors, particularly for Introduction and Discussion sections.
• Key risks include inaccurate information (hallucination), plagiarism, and privacy breaches.
• Mitigation involves content verification, plagiarism checks, and avoiding sensitive data input.
• Editing and refining text is often more prudent than extensive text generation.

Conclusions:

• LLMs can lower barriers to academic writing in English for non-native speakers.
• Responsible and cautious use is essential to harness LLM benefits.
• Transparency in disclosing AI tool usage is increasingly important for academic integrity.