Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Artificial intelligence and transparency: Toward a framework for disclosure of AI use in learning, research, and publication
0
Zitationen
1
Autoren
2026
Jahr
Abstract
This article addresses the following question: How should authors disclose the use of Artificial Intelligence (AI) in their research, as well as in the crafting of any manuscripts based upon their research so that readers, reviewers, and editors can clearly see how and where AI shaped a scholarly contribution? The question was discussed in a presentation at the 2025 NISO Plus conference in which the current state of AI disclosure was examined. The ultimate recommendation that emerged is that the Artificial Intelligence Disclosure (AID) Framework could serve as the basis of an international standard for AI disclosure because the Framework supports standardized, consistent, and transparent reporting of AI use across the full arc of learning, research, and publication. It is designed to complement, not replace, the conventional citation of direct AI outputs, and it situates AI assistance in context to make process-level work visible.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.611 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.504 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 8.025 Zit.
BioBERT: a pre-trained biomedical language representation model for biomedical text mining
2019 · 6.835 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.781 Zit.