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.
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.
If libraries are civic institutions that structure society’s relationship to knowledge, and generative AI is poised to reshape discovery whether libraries act or not, will library leaders will develop strategies that preserve trust, equity, and sustainability?
Each new change in scholarly communication promises to make research fairer, faster, more transparent. Yet, in many cases, researchers, especially from under resourced countries or from countries where English is not the first language, face added pressure to catch up, rather than to move forward.
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.
Between a political policy environment focused on defunding and deleting data collections – an environment in which little can be trusted – and an onslaught of new AI tools that feed indiscriminately on data, bits of information at the intersection of rows and columns are appearing in headlines more than ever before. To avoid cultural memory loss, we must build systems that save what humanity needs across disciplinary silos rather than saving some archives and losing others through an accident of history.
Today’s guest bloggers share analysis on the relationship between impact and policy during Global Goals Week 2025.
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.
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?
What can you expect from this fall’s New Directions in Scholarly Publishing Seminar in Washington, DC?
This post explores author, reviewer, and publisher ethics and responsibilities related to the use of AI in coding and publishing research software.
As AI becomes a major consumer of research, scholarly publishing must evolve: from PDFs for people to structured, high-quality data for machines.
What happens when AI-infused information systems increasingly provide answers rather than directing people to sources?
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.
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.
Level 3 of STM’s SDG roadmap has launched, reminding us that academic publishers have both the responsibility & opportunity to be catalysts for positive, global change.