Guest Post — Reflecting on a Decade with the Open Discovery Initiative: Insights from IEEE
Julie Zhu reflects on the IEEE’s journey with the Open Discovery Initiative (ODI) and the benefits of ODI conformance statements.
Julie Zhu reflects on the IEEE’s journey with the Open Discovery Initiative (ODI) and the benefits of ODI conformance statements.
Are there enough reviewers though to meet demand and is the peer review process efficient enough to handle the sheer volume of papers being published? How can a combination of human expertise and AI make the peer review process more efficient?
Robert Harington provides a template for scholarly societies wondering how to grapple with the overwhelming and omnipresent prospect of an AI future.
The role of libraries and archives as streaming grows, choice declines, and the death of the red envelopes arrives.
In 2023, AI has been back in the news in a big way. Large Language Models and ChatGPT threatened our’s and many other industries with huge disruption. As with so many threatened techno-shocks, a large degree of this one was hype, but what will happen after the hype fades. What, if anything, will be the lasting legacy of ChatGPT?
A panel attending the 2023 AUPresses Meeting hosted a conversation about optimizing books metadata and measuring its impact on search experiences in the mainstream web.
Human-dependent peer review is inequitable, suffers from injustice, and is potentially unsustainable. Here’s why we should replace it (eventually) with AI-based peer review.
In today’s Peer Review Week guest post, Joe Pold of PLOS interviews the senior editorial team of PLOS Computational Biology about their experience of mandating code sharing for the journal, and its impact on peer review
How machines learn, as demonstrated by a pile of matchboxes playing tic-tac-toe.
The challenges offered by artificial intelligence require a different approach than that seen for plagiarism detection.
When the University of Michigan was forced to disconnect from the internet last week, it resulted in disruptions to several key services it provides to the broader research community, such as the University of Michigan Press, HathiTrust, and ICPSR. What can we learn from this experience?
Was a recent Scholarly Kitchen piece analyzing the capabilities of ChatGPT a fair test? What happens if you run a similar test with an improved prompt on LLMs that are internet connected and up to date?
What uses for artificial intelligence (AI) might we expect outside of the publication workflow? Some answers to this question can be found through the lenses of sustainability, justice, and resilience.
To identify both benefits and risks of generative AI for our industry, we tested ChatGPT and Google Bard for authoring, for submission and reviews, for publishing, and for discovery and dissemination.
Twelve years after the Open Discovery Initiative (ODI) launched, I wonder: How are scholarly content providers leveraging ODI conformance statements to drive transparency and usage via web-scale library discovery services?