Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
The FAIR framework: ethical hybrid peer review
0
Zitationen
3
Autoren
2025
Jahr
Abstract
The FAIR Framework offers a principled solution to peer review inefficiencies by combining AI-enabled consistency and speed with essential human expertise. This hybrid approach reduces review delays, eliminates systematic bias, and enhances transparency while maintaining confidentiality and editorial control. Implementation could significantly reduce the estimated 100 million hours of global reviewer time annually while improving review quality and equity across diverse research communities.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.324 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.189 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.588 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.470 Zit.