Why Authors Aren’t Disclosing AI Use and What Publishers Should (Not) Do About It
Only a negligible percentage of authors seem to actually be disclosing their AI use. Here’s why I think that’s the case.
Only a negligible percentage of authors seem to actually be disclosing their AI use. Here’s why I think that’s the case.
Today’s guest author raises the question of whether a researcher submitting an article that was significantly drafted by an LLM without clear disclosure is effectively engaging in a contemporary form of ghost authorship.
At the STM innovation and Integrity days in London last week, it’s clear that research integrity has become an increasingly pressing issue. Many publishers are reporting significant increases in submissions of questionable legitimacy. perhaps now is the time for a new alliance between publishers, funders, institutions and researchers to protect the integrity of the scholarly record, before it’s too late.
Who are public-good curators and how can they help improve public trust in science? Learn more in this interview with Tracey Brown (Sense about Science) and Camille Gamboa (Sage) about their recently co-published booklet on the topic.
Today’s guest bloggers share results of an exploratory survey of funding research services, offering a snapshot of a library community in transition.
Rather than just bolting on AI to existing publication workflows,there is a real opportunity to rethink and redesign them for human–AI collaboration. Some thoughts on what that looks like in practice.
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.
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.
If science is to be both honest and healthy, we must accept that statistically non-significant results are part of reality. The SAMPL guidelines, if adopted widely by scholarly publishers and journal editors, hold a solution for authors who worry their results are not “significant.”
We’re finally seeing a move to truly digital-first publishing systems and in today’s post Alice Meadows interviews Liz Ferguson of Wiley about this transition, including their own Research Exchange platform.
Today, we talk to thought leaders Helen King and Chris Leonard, who offer a nuanced look at how peer review might adapt, fracture, or reinvent itself in the AI era.
The future of peer review isn’t about choosing between humans and AI, or between speed and quality, but about combining the strengths of both to enable speed with quality, to ensure quality, ethics, and trust in the scholarly record.
Summing up the Committee on Publication Ethics (COPE) Forum discussion on Emerging AI Dilemmas in Scholarly Publishing, which explored the many challenges AI presents for the scholarly community.
A scholarly disinformation taxonomy could help prevent scholarly communications from being gamed by fraudulent actors.
Robert Harington talks to Carsten Buhr, CEO of De Gruyter Brill, in this series of perspectives from some of Publishing’s leaders across the non-profit and for-profit sectors of our industry.