The US Department of Justice filed a Statement of Interest in the copyright infringement litigation between The New York Times and OpenAI and Microsoft, et. al., largely siding with the AI companies and strongly favoring the notion of LLM training as fair use. We asked the chefs for their thoughts.
The journal portfolio, platform, or membership is no longer enough, as AI transforms how research is discovered and consumed. How will your organization adapt?
Today, we learn what’s in store for this year’s fall seminar from SSP.
Today’s guest bloggers posit four important trends in scholarly communications that our community should be ready to tackle.
As AI research assistants learn our preferences, they may also become better at mirroring our assumptions. Avoiding that outcome will require more than a better prompt.
The opportunity presented by AI is not to remove the human layer of scholarship. It is to recognize why that layer has always mattered.
Today’s post explains how Ukraine’s academic publishing sector is confronting a global monograph crisis with unexpected urgency and innovation.
Today’s guest post argues that scholarly publishers’ institutional credibility and alignment are in crisis, and suggests the time for a structural rebrand is now.
Machine readers replacing human readers can sound like a threat. Today’s post argues that our community is well prepared to face these challenges and seize the opportunities.
Today’s post provides a brief analysis of self-referencing and scholarly impact through the lens of stigmergy theory
In this AI era, establishing trust and validating article versions with persistent identifiers (PIDs) is more important than ever.
Today’s guest post argues that digital preservation is not just a technical problem, but a function that often ignores issues of social justice, quietly codifying existing imbalances in scholarly communication.
From 19th-century beef tea to paper mills and generative AI, the challenge is no longer detection alone; it is preventing bad claims from becoming embedded knowledge.
Today’s guest post asks: Do trust markers and other systematic fraud-prevention practices exclude unaffiliated authors from contributing to the scholarly record?
The central risk of AI in scholarly publishing is therefore not hallucination but cognitive debt: the gradual erosion of the human capacities that give scholarship its originality, integrity, and meaning.