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?
Damned if You Do, Damned if You Don’t: Multilingual Researchers’ Use of AI in Academic Writing
Generative AI has made language tools ubiquitous, but it introduces risks of homogenized texts and semantic slippage.
Guest Post — Peer Review Triage: Deciding What’s Worth Saving
Today’s guest post asks what about our current peer review system is worth saving and if we’re able to establish one that protects editorial judgment and preserves research integrity.
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.
Ask the Chefs: AI and Copyright Licensing
The US Department of Justice filed a Statement of Interest in the copyright infringement litigation between The New York Times and OpenAI and Microsoft, et. al., largely siding with the AI companies and strongly favoring the notion of LLM training as fair use. We asked the chefs for their thoughts.
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.
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.
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.
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.