Guest Post — AI as Reader, Author, and Reviewer: What Stays Human?
Today’s guest blogger shares highlights from a recent panel at the New Directions Seminar that concluded AI is simultaneously the largest challenge and the largest opportunity.
Manuscript Submissions Are Up! That’s Good, Right?
Publishers have led themselves into a mess by focusing on rising submissions as a positive indicator of journal performance. The time has come to close the floodgates and require that authors demonstrate their commitment to quality science before we let them in the door.
Can a CC License Constrain Fair Use or Other Copyright Limitations or Exemptions?
Creative Commons (CC) licenses expand, not restrict, the permissible uses of copyrighted works.
Guest Post — From Language Barrier to AI Bias: The Non-Native Speaker’s Dilemma in Scientific Publishing
For decades, EAL researchers have faced systemic disadvantages in publishing. AI writing tools promise relief, yet, they also bring new risks into science.
Three Years After the Launch of ChatGPT, Do We Know Where This Is Heading?
Nearly three years after ChatGPT’s debut, generative AI continues to reshape scholarly publishing. The sector has moved from experimentation toward integration, with advances in ethical writing tools, AI-driven discovery, summarization, and automated peer review. While workflows are becoming more efficient, the long-term impact on research creation and evaluation remains uncertain.
Guest Post – Taxonomy of Delegation: How GAIDeT Reframes AI Transparency in Science, an Interview with Yana Suchikova
Today, we speak with Prof. Yana Suchikova about GAIDeT, the Generative AI Delegation Taxonomy, which enables researchers to disclose the use of generative AI in an honest and transparent way.
Guest Post — May the AI Be With Science
AI has opened a new chapter in the saga of science and peer review. Today, guest author Prof. Nihar B. Shah explains how, if guided with integrity, AI can open galaxies of possibilities.
Ask the Chefs: What’s a Bold Experiment with AI in Peer Review You’d Like to See Tested?
To kick off Peer Review Week, we asked the Chefs, What’s a bold experiment with AI in peer review you’d like to see tested?
Rise of the Machine Readers: What They Really Want to Read
As AI becomes a major consumer of research, scholarly publishing must evolve: from PDFs for people to structured, high-quality data for machines.
Guest Post — Who Controls Knowledge in the Age of AI? Part 2, Recommendations for Stakeholders
The MIT Press surveyed book authors on attitudes towards LLM training practices. In Part 2 of this 2 part post, we discuss recommendations for stakeholders to avoid unintended harms and preserve core scientific and academic values.
Guest Post — Who Controls Knowledge in the Age of AI? Part 1
The MIT Press surveyed book authors on attitudes towards LLM training practices. In Part 1 of this 2 part post, we discuss the results: authors are not opposed to generative AI per se, but they are strongly opposed to unregulated, extractive practices and worry about the long-term impacts of unbridled generative AI development on the scholarly and scientific enterprise.
Guest Post — A Smarter Way to License Research Articles for AI
If LLMs are the future of information discovery, valuable scholarly content risks being left behind — unless we build a bridge with better licensing.
Guest Post — The Accessibility Illusion: When AI Simplification Fails the Users With Cognitive Disabilities
Guest blogger Hema Thakur shares results of her experiment using AI to improve the accessibility of peer review feedback — her findings may concern you!
Chefs de Cuisine: Perspectives from Publishing’s Top Table — Matthew Kissner
Robert Harington talks to Matt Kissner, CEO of Wiley, in this series of perspectives from some of Publishing’s leaders across the non-profit and for-profit sectors of our industry.
Ask The Chefs — New Court Decisions Issued in Cases Addressing AI Training and Copyright
We asked the Chefs for their thoughts on two important court decisions on the legality of using copyrighted materials for AI training.