TRACE Project Launches to Advance AI interoperability
The community comes together to launch TRACE, a project to improve generative AI systems’ interoperability, verifiability and usage tracking.
The Representation Is Not the Scholarship
The problem with AI may not be that machines are growing more intelligent. It may be that we are becoming increasingly skilled at amplifying a highly capable, but limited form of cognition.
Are Libraries Prepared for the Second Digital Transformation of Distinctive Collections?
Academic and research libraries, as well as public libraries, historical societies, and other organizations, hold extensive collections of rare and unique materials, such as archival and manuscript collections. These materials form an essential part of humanity’s cultural and historical record, and they are the vital source material for many humanistic fields. I believe that a second digital transformation is at hand for distinctive collections. How can library leaders establish a strategy for their distinctive collections that is fit for purpose today?
AI and Scholarly Reading: Foxes versus Hedgehogs
Some readers are foxes, and some are hedgehogs. What kind of reader is AI, and how will that impact both the practice of science and the business of journal publishing?
Ask the Chefs: Peer Review Capacity — Uncomfortable Truths and Overlooked Conversations
For Peer Review Week 2026, we asked the Chefs two questions: What is one uncomfortable truth about peer review that the scholarly publishing community doesn’t talk about enough? And, beyond recruiting more reviewers, what conversation about peer review capacity are we overlooking?
Guest Post — A Groupthink We Don’t Talk Much About
Today’s guest post challenges our community to face tendencies toward groupthink and address the incentive structures that resist adaptation and innovation.
Guest Post — The Unbundling of Scholarly Publishing: A Trilemma for the AI Era
The journal portfolio, platform, or membership is no longer enough, as AI transforms how research is discovered and consumed. How will your organization adapt?
Guest Post – A Year of Trends Beyond Scholarly Comms: What You Need to Know
Today’s guest bloggers posit four important trends in scholarly communications that our community should be ready to tackle.
Guest Post — The Human Layer: Why AI Makes Academic Libraries More Essential, Not Less
The opportunity presented by AI is not to remove the human layer of scholarship. It is to recognize why that layer has always mattered.
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.