Artificial Intelligence and Publishing Ethics: A Narrative Review and SWOT Analysis

Area of Science:

• Medical Research
• Artificial Intelligence
• Bioethics

Background:

• Artificial intelligence (AI) is experiencing exponential growth, significantly impacting medical science and research methodologies.
• Large language models (LLMs) generate human-like text, offering diverse applications but also posing challenges to scientific integrity.
• The ethical implications of AI in healthcare research necessitate careful consideration, especially concerning its potential for misuse.

Purpose of the Study:

• To provide a comprehensive narrative review of AI, focusing on LLMs in healthcare scientific research.
• To examine the ethical challenges and impact on scientific integrity posed by AI.
• To discuss evolving international guidelines on AI authorship, transparency, and responsible use.

Main Methods:

• A narrative review of published literature was conducted using databases like PubMed, Cochrane, Scopus, and Google Scholar.
• A SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis of AI in research publications was performed.
• Ethical challenges associated with AI in research were evaluated.

Main Results:

• AI and LLMs present both significant benefits and serious challenges to research integrity in healthcare.
• Chatbots, while valuable in education and practice, require caution against malicious or fabricated use.
• International organizations emphasize that chatbots do not qualify as co-authors, permitting only responsible AI use.

Conclusions:

• Researchers must exercise caution, accountability, and transparency when utilizing AI tools like chatbots.
• Adherence to evolving guidelines from organizations like COPE and ICMJE is essential for ethical AI implementation.
• Understanding and applying new ethical approaches is critical for navigating AI's role in scientific research.