Reading Between the Lines, Part 1: A Cognitive Framework for AI in Scholarly Publishing
AI is now a permanent feature of the scholarly landscape. The question is no longer whether it should be used, but how it should be understood and governed.
AI is now a permanent feature of the scholarly landscape. The question is no longer whether it should be used, but how it should be understood and governed.
Today Alice Meadows interviews Jennifer Fleet (Aries Systems) and Christian Gruback (ChronosHub) about changing author needs and how their recently announced partnership is an effort to address them.
Open Science 2.0 must focus not only on access, but also on trust, interpretation, learning, and effective communication. The challenge facing the scholarly publishing ecosystem is ensuring that what is open is also trustworthy, understandable, and genuinely useful.
Today’s guest post introduces the YCR-index as an alternative to measuring value with raw citation counts.
Building robust citation and attribution into generative AI systems are foundational to usage, credit and trust. We need to expect more from AI.
A conversation on AI retrieval, the provenance problem, and the shared infrastructure scholarly publishing needs.
Federated identity should be a natural fit for library access. So why isn’t it?
For scholarly publishers, the user has changed faster than the systems designed to serve them, and the gap between the two is where most of the difficult work is happening.
With CC Signals, Creative Commons wants to help authors put rules on use of their licensed content for AI training. The problem is, one of the licenses already permits free and unlimited reuse of that content, for any and all purposes. And the licenses are irrevocable.
Today, we feature a friendly debate on the question: which parts of the research lifecycle should be more automated, and which require more of a human touch — and why?
The threat of zero-click search makes organizational brand more important than ever and presents a huge opportunity.
Today’s guest post proposes a method for identifying, measuring, and managing robotic usage of scholarly content.
AI in science should not be viewed merely as a productivity tool layered onto existing workflows. It represents a structural shift in how knowledge moves through society, and therefore in how scientific authority is established and maintained.
Today’s guest post explains the new data space pilot, which will be the focus of the upcoming BISG/SSP webinar on May 12, 2026.
Part 3 of a look at the American Society of Civil Engineers’ inaugural Pathways to Inclusive Publishing Summit, which brought together industry leaders, content creators, and allies to explore strategies for fostering inclusivity and accessibility within the publishing ecosystem.