Guest Post — Why Research Expectations Have Outpaced the Systems That Enabled Them (Part 2)
Today’s post is the second in a series arguing that fractures appearing across research systems are symptoms of a mismatch within today’s research ecosystem.
Today’s post is the second in a series arguing that fractures appearing across research systems are symptoms of a mismatch within today’s research ecosystem.
Today’s guest post asserts that AI infrastructure will let publishers truly leverage machines, while brand and community are what will keep them meaningful to humans.
Today’s post shares the results of an initiative designed to answer the question: what would it actually take to build a publishing model fit for the research ecosystem we have now, rather than the one we inherited?
Faced with technological shifts not seen since the advent of the internet, Todd Toler and Angela Cochran posit that the biggest challenges for organizations building an AI strategy are human, not technology.
As AI-driven search reduces friction in information-seeking, what happens to serendipity, frustration, and “night 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.
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.
Guest blogger Hema Thakur shares results of her experiment using AI to improve the accessibility of peer review feedback — her findings may concern you!
How can organizations facilitate safe and comprehensive engagement with AI? And how can individuals within those organizations engage and advocate for their own AI literacy?
In today’s Mental Health Awareness Monday post, Lisa Colledge shows how your research culture can be an asset that boosts mental health and innovation.
Jon Repetti reflects on the lessons being learned from the American Philosophical Society’s re-entrance into the fray of the scholarly publishing marketplace.
What can we do to encourage and improve methods reporting in scientific articles? A new report summarizes recommendations for editors and publishers alike.
Do publishers really understand what tools researchers are using and how they are using them? Can we do more to create better policies based on real use cases and not hypothetical conjecture about what AI might do in the future?
Even a flawed paper can offer lessons on how (not) to report, and what (not) to claim.
The gaps in capability of AI will narrow over time, but publishers and end users need education on those gaps to make investment decisions and to confidently utilize Generative AI tools effectively.