Today’s guest blogger argues that if we want scholarly publishing to be worth anything in a generation, we must acknowledge the risks we run by relying on intelligent automation.
STM has released voluntary recommendations to help journals and publishers clarify data sharing guidance for medical and health science researchers, where privacy, regulation, and ethics make generic policy language especially hard to apply.
Today, we feature an interview with Tetiana Yaroshenko, Deputy Director for Research and International Affairs at the State Scientific and Technical Library of Ukraine, and Denys Kurbatov, Deputy Minister of Education and Science of Ukraine.
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?
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?
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.
Today’s guest post argues that digital preservation is not just a technical problem, but a function that often ignores issues of social justice, quietly codifying existing imbalances in scholarly communication.
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.
Today’s guest post asks: Do trust markers and other systematic fraud-prevention practices exclude unaffiliated authors from contributing to the scholarly record?
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.
An interview with Natalie Ridgway about new guidelines from the Committee on Publication Ethics.
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.
Today, we reprise the talk by outgoing SSP President Rebecca McLeod at last month’s SSP Annual Meeting.
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.
In honor of Global Accessibility Awareness Day, today’s post shares results from an experiment with qualitative data analysis — demonstrating that, while AI can detect patterns, humans must decide what those patterns mean.