From AI Adoption to AI Practice: Building Governed AI in Scholarly Publishing
How can a publisher make AI useful across the organization while keeping control of confidential information, editorial decisions, and accountability?
The AI Transparency Trap
The absence of AI doesn’t guarantee trustworthy research. And neither does disclosing AI use.
Guest Post — When Research Integrity Fails, the Entire System Follows
Leadership in academia, publishing, funding, and across the supply chain must coordinate efforts to address research integrity. It is this collective responsibility that will restore and protect the credibility of research.
From Content to Trusted Knowledge: Reflections on Frankfurt Book Fair 2026
Thoughts on the Frankfurt Book Fair 2026: how do we turn trusted content into useful knowledge — and help people act on it?
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.
Research Integrity in Scholarly Communications — SSP Pulse Check Report
Today, we take a dive into the results of SSP’s latest Pulse Check Survey, revealing how our community is grappling with research integrity and its interconnected challenges.
Guest Post — Does Peer Review Favor Familiarity Over Innovation?
Closing out Peer Review Week 2026, today’s post suggests that research novelty and capacity for innovation should be given greater priority than clarity and comprehensiveness in peer review.
Rethinking Scholarly Evaluation: Matching Rigor to Purpose
What if the systems designed to protect scientific rigor are also making it harder for new ideas to emerge? Do different scholarly contributions deserve unique forms of evaluation?
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?
When Your AI Knows You Too Well: Personalization, Sycophancy, and the Risk of an Intellectual Echo Chamber in AI-assisted Research
As AI research assistants learn our preferences, they may also become better at mirroring our assumptions. Avoiding that outcome will require more than a better prompt.
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.
Guest Post — Self-Citation Is How Fields Grow
Today’s post provides a brief analysis of self-referencing and scholarly impact through the lens of stigmergy theory
Guest Post — When Errors Become Consensus: Science’s Self-Correction Can No Longer Keep Up
From 19th-century beef tea to paper mills and generative AI, the challenge is no longer detection alone; it is preventing bad claims from becoming embedded knowledge.
Guest Post — The Guild and the Gap: What One Rejection Revealed About the Cost of Credentialism
Today’s guest post asks: Do trust markers and other systematic fraud-prevention practices exclude unaffiliated authors from contributing to the scholarly record?