Ask the Community: Takeaways from SSP 2026
We asked some of the attendees of the recent SSP Annual Meeting in Chula Vista, CA, to answer the question: “What are some takeaways from your experience at SSP 2026?”
We asked some of the attendees of the recent SSP Annual Meeting in Chula Vista, CA, to answer the question: “What are some takeaways from your experience at SSP 2026?”
A conversation on AI retrieval, the provenance problem, and the shared infrastructure scholarly publishing needs.
Today’s guest post asserts that AI infrastructure will let publishers truly leverage machines, while brand and community are what will keep them meaningful to humans.
AI scholarly search tools often miss important literature due to incomplete metadata. Better full-text-derived metadata could significantly improve discovery.
For scholarly publishers, the user has changed faster than the systems designed to serve them, and the gap between the two is where most of the difficult work is happening.
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.
Today, we feature a friendly debate on the question: which parts of the research lifecycle should be more automated, and which require more of a human touch — and why?
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.
The threat of zero-click search makes organizational brand more important than ever and presents a huge opportunity.
ScholarOne saw a submission surge in the first quarter of 2026 — evidence that AI is increasing the strain on peer review’s social contract with researchers.
Today’s guest post asserts that trust won’t be restored by “better messaging” alone, but via better incentives, more disciplined public communication, and really listening to the people who have walked away from us.
Today’s guest post proposes a method for identifying, measuring, and managing robotic usage of scholarly content.
Today’s post asks: If research is increasingly accessed through AI-generated summaries rather than via primary sources, then what does it mean to “engage with research” at all?
Today’s guest post sounds an alarm about the use of AI in research and warns that no amount of computational efficiency can compensate for the loss of our capacity for human thought.
The new STM Trends 2030 was released, symbolizing a world full of opportunities but also with dangers lying just below the surface for scholarly publishing.