We Can Now Track AI-generated Content. It Doesn’t Solve the Real Problem.
Identifying AI content is now embedded in Claude models. It doesn’t solve the problem we have. It also creates others.
AI Use in The Scholarly Kitchen
Some thoughts on the reader response the Scholarly Kitchen has seen regarding AI use by authors, a recent Nature News article on the efficacy of AI detection tools, and why it’s important to keep experimenting to figure out what’s ethically acceptable.
Guest Post — Your Next Reader Is a Machine, and We Are Ready
Machine readers replacing human readers can sound like a threat. Today’s post argues that our community is well prepared to face these challenges and seize the opportunities.
Guest Post — AI Can Find the Article. Can It Tell Which Version It Used?
In this AI era, establishing trust and validating article versions with persistent identifiers (PIDs) is more important than ever.
Reading Between the Lines, Part 2: Cognitive Debt and the Adaptive Publisher
The central risk of AI in scholarly publishing is therefore not hallucination but cognitive debt: the gradual erosion of the human capacities that give scholarship its originality, integrity, and meaning.
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.
What Authors Expect Now, and Why Publishing Hasn’t Kept Up: An Interview with Jennifer Fleet of Aries Systems and Christian Grubak of ChronosHub
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.
Guest Post — The Third Time is NOT the Charm: Who Will Own How AI Participates in Scholarship?
Today’s guest post warns the community that, in the AI era, we cannot keep building the pieces that lay the foundation and letting someone else own what gets built on top of it.
The Hidden Cost of Trust
Research integrity demands stronger safeguards in order to protect the scholarly record. But for editors, when new integrity measures are introduced, they do not replace existing tasks; they are added alongside them, compounding workloads and responsibilities.
Slow Food, Slow Publishing: The Beauty of Not Being First
Robert Harington reflects on our addiction to speed and advocates for slow scholarly publishing and the inherent beauty of not always being first.
Open Science 2.0: Building Understanding in an AI-Mediated World
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.
Guest Post — Research Needs a Shared Standard for AI Disclosure
Today’s guest post presents outcomes of the WCRI’s (World Conferences on Research Integrity) Focus Track to address this gap in clarity and standardization of AI disclosure.
Guest Post — Beyond the Prestige: Why Scientific Impact is More Than a Numbers Game
Today’s guest post introduces the YCR-index as an alternative to measuring value with raw citation counts.
Guest Post — Now is the Time for AI in Peer Review, and Publishing Policies Need to Recognize This
Today’s post asks us to acknowledge the role of AI in peer review and ensure practical guidance and policies that help scholars respond with consistency and confidence.
Making AI Use of Scholarly Content Traceable, Measurable, and Trustworthy: A Meeting Report from Cambridge Scholarly AI Workshop
A Cambridge workshop proposes new standard work to support provenance, attribution and metrics in scholarly communications AI tools.