PubTech Radar 第 39 期：开放情报、AI 智能体与科研出版动态

🆕Recentish news/opinion

• Open Intelligence - by Adam Hyde on Why it is time to see open movements as one shared project

• The Great Turning Point: a Return to Publishing’s Roots - by Ravi Venkataramani, CEO of Kriyadocs

• Doug Way summarises Clarivate’s Q3 earnings call from a librarian’s perspective. “The second was an emphasis on agentic AI tools and the development of native AI tools, like Alma Specto. Specto seems (to this librarian) to be a competitor to JSTOR’s Digital Stewardship Services. When asked specifically about it, leadership sidestepped details and instead discussed their general approach to new products and a couple of other initiatives in more depth. This could mean absolutely nothing—as many companies don’t always answer questions directly, sometimes for business reasons and sometimes because extemporaneous speaking is hard. Just something to file under “interesting.””

• Innovation in scientific publishing and its implications for Crossref DOI registration practices - Request for input

• Is Digital-first Publishing Finally a Reality? An Interview with Liz Ferguson of Wiley

🤖 AI

• Ian Mulvany, Some thoughts on AI Agents.

• AI tools combat paper mill fraud in scientific publishing as peer review system struggles by Nina Notman.

• Ethan Mollick “If the the predictions that AI will create minor scientific discoveries next year and major ones a couple years later come true, it is worth noting that we have no real mechanism in academia for accommodating, reviewing, processing, and disseminating a sudden increase in science. Who is going to read thousands of new papers that marginally advance science? Who is going to read thousands of papers that represent genuine breakthroughs in narrow fields? Who will integrate the knowledge? Who is going to build on them to transfer them into practical products?”.

• When AI Feeds on Poisoned Knowledge — Lessons from Library Genesis to Llama 3.

• Matt Rogerson commenting on Alex Reisner’s article in The Atlantic about Common Crawl.

• We’re not taking the fact-checking powers of AI seriously enough. It’s past time to start. By Mike Caulfield.

• AI Scientist by Andrew White on the history of the term, and gives some ideas on what might define an AI Scientist.

• Beyond the Artifact: The Brutal Economics of Liquid Content by Shuwei Fang. “The cold reality is that when content becomes infinitely replicable and reformattable at near-zero marginal cost, the economic value of any individual piece approaches zero. I believe this will be the major forcing function that drives structural change in the existing news media industry. In an AI-mediated information ecosystem, few existing publications will be able survive on current business models. New upstarts are already emerging, building businesses around capabilities and infrastructure, changing the competitive environment. News media organizations face a stark choice: radically innovate or risk extinction.“

• BadScientist: Can a Research Agent Write Convincing but Unsound Papers that Fool LLM Reviewers? [See also Chris Leonard’s/Claude’s review of this paper ]

• Fauzia Burke on Here’s what authors and publishers need to know about AI-powered book suggestions.

• Large Language Model Relevance Assessors Agree With One Another More Than With Human Assessors.

• 🎧 A conversation with John Frechette, Ben Kaube, and Aaron Tay. (ATG Podcast) “This conversation explores how AI is reshaping the research process - from how papers are discovered to how findings are analyzed, shared, and rewarded. John talks with Ben and Aaron about the new realities of AI-driven search, publishing, and research workflows. Together, they discuss where automation helps or harms, how publishers and librarians are adapting, and what the rise of AI means for research quality and integrity.”

• 12 lessons from news outlets on the cutting edge of AI - key points, ideas and tips from the first day of the JournalismAI Festival in London.

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