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Ethical Standards II01:23

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Ethical standards are the backbone of nursing practice, guiding nurses as they interact with patients, families, and colleagues. These standards are crucial for providing safe, empathetic care centered on the patient's needs.
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The FAIR framework: ethical hybrid peer review.

Amos Grünebaum1, Joachim Dudenhausen2, Frank A Chervenak1

  • 15799 Northwell Health, Zucker School of Medicine , Hempstead, NY, USA.

Journal of Perinatal Medicine
|September 22, 2025
PubMed
Summary

The FAIR Framework combines artificial intelligence and human expertise to create a more efficient and equitable peer review system. This innovative approach addresses bias and delays, improving scientific publishing quality.

Keywords:
artificial intelligencehybrid systemsmedical publishingpeer reviewresearch ethicsscientific publishing

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Area of Science:

  • Scientific Publishing
  • Academic Research
  • Scholarly Communication

Background:

  • Traditional peer review suffers from bias, delays, and lack of transparency.
  • These issues hinder scientific progress and incur significant annual costs.
  • Current systems fail to uphold ethical obligations in academic labor.

Purpose of the Study:

  • To propose an ethically-guided hybrid peer review system.
  • Integrate generative artificial intelligence (AI) with human expertise.
  • Address fundamental shortcomings of current review processes.

Main Methods:

  • Developed the FAIR Framework (Fairness, Accountability, Integrity, and Responsibility).
  • Analyzed peer review failures and integrated AI capabilities.
  • Employed standardized prompt engineering with human oversight.

Main Results:

  • FAIR addresses bias via algorithmic detection and standardized protocols.
  • Ensures accountability through transparent audit trails and documented decisions.
  • Maintains integrity via secure local AI processing and confidentiality safeguards.

Conclusions:

  • The FAIR Framework offers a principled solution to peer review inefficiencies.
  • Combines AI-enabled consistency and speed with essential human expertise.
  • Reduces review delays, eliminates bias, and enhances transparency.