Preserving scientific integrity in academic publishing: Navigating artificial intelligence, journal policies, and the impact factor as a quality indicator - PubMed
4 hours ago
- #Artificial Intelligence
- #Scientific Integrity
- #Academic Publishing
- Challenges to scientific integrity include AI integration, mega-journals, and impact factor manipulation.
- Threats are categorized into external pressures (AI misuse, metric-driven models) and internal systemic flaws ('publish or perish' culture, methodological fragility).
- Mega-journals improve accessibility and dissemination but may weaken peer review rigor due to high-volume publishing.
- Proposed solutions include AI transparency frameworks (e.g., CONSORT-AI) and redefining impact metrics to emphasize reproducibility and societal impact.
- Global cooperation (e.g., DORA, COPE) is essential to standardize ethics and address resource disparities.
- Encourages career opportunities based on publication quality over quantity to uphold scientific integrity.