Today, we speak with Prof. Yana Suchikova about GAIDeT, the Generative AI Delegation Taxonomy, which enables researchers to disclose the use of generative AI in an honest and transparent way.
Tony Alves reflects on the 2025 Peer Review Congress and the rapid evolution of discussions about AI and peer review since 2022.
The STM Association offers a classification scheme for the various possible uses of AI, including GenAI, in the preparation of manuscripts.
Today, we talk to thought leaders Helen King and Chris Leonard, who offer a nuanced look at how peer review might adapt, fracture, or reinvent itself in the AI era.
The future of peer review isn’t about choosing between humans and AI, or between speed and quality, but about combining the strengths of both to enable speed with quality, to ensure quality, ethics, and trust in the scholarly record.
Today’s post discusses research metrics and their relationship to research integrity, inclusivity, and long-term impact.
NISO’s Open Discovery Initiative (ODI) survey reflects the positive and negative expectations of generative AI in web-scale discovery tools.
This post explores author, reviewer, and publisher ethics and responsibilities related to the use of AI in coding and publishing research software.
Today’s guest authors offer practical tips for publishing high-quality image descriptions, a key step toward ensuring genuine accessibility in scholarly communications.
In an era of information abundance and epistemic chaos, libraries serve as crucial sites for democratic knowledge practices — protecting them is critical to preserving the infrastructure of informed citizenship itself.
Summing up the Committee on Publication Ethics (COPE) Forum discussion on Emerging AI Dilemmas in Scholarly Publishing, which explored the many challenges AI presents for the scholarly community.
As AI becomes a major consumer of research, scholarly publishing must evolve: from PDFs for people to structured, high-quality data for machines.
Open access has revolutionized how research reaches readers — yet, true accessibility is an ethical imperative for institutions, publishers, and service providers to create genuinely inclusive scholarly communication.
A scholarly disinformation taxonomy could help prevent scholarly communications from being gamed by fraudulent actors.
Data sonification is the process of translating data into sound. Here, Lutz Bornmann and Christian Leibel present the sonified results of a recent analysis of the impact of scientific team size on innovation.