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AI evidence extraction

The Ethical Aspects of AI in Scientific Publishing.

Joris R Delanghe · PubMed · 2026

AI-generated evidence extraction, verified across multiple analytical personas. Not a substitute for the peer-reviewed original.

9/10
Relevance
1/4
Quality (LMQS)
I
Evidence
0
Citations
0.00
FWCI

Methodology & findings

Study design

Narrative review and ethical analysis of AI's role in scientific publishing; no empirical experiments, surveys, or measurements conducted.

Main result

The paper identifies that "AI tools are used in generating papers" and raises several critical ethical concerns: "if AI contributes, should they be credited as authors?" and "if AI is involved in writing, this should be disclosed to maintain transparency." Additionally, the authors note that "AI-driven tools might lack the nuanced human understanding" and that "over-reliance on AI could compromise publishing quality."

Research paradigm

Interpretivist/Critical theory

Author conclusions

The authors conclude that "AI offers possibilities to speed up and to improve scientific publishing, but it is essential to judge and to address the ethical implications. This requires guidelines and rules warranting an honest, transparent and integer approach of publishing."

Open questions raised

  • The paper identifies the need for frameworks addressing: (1) authorship and accountability when AI contributes to papers, (2) intellectual property rights frameworks redesigned for AI-generated content, (3) guidelines for AI disclosure in scientific publishing, (4) strategies to mitigate global inequality in science exacerbated by AI, and (5) methods to maintain peer review integrity when AI tools are used.
  • The authors identify the need for ethical frameworks and governance structures: "This requires guidelines and rules warranting an honest, transparent and integer approach of publishing." Implicit gaps include the need for clear authorship attribution policies, intellectual property frameworks adapted for AI-generated content, and mechanisms to prevent exacerbation of global research inequality.
  • The paper identifies the need for "guidelines and rules" to address ethical implications of AI in publishing, suggesting this is an emerging area requiring further development of governance frameworks.
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