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?
New data literacy and artificial literacy standards are necessary and emerging. The workflows and iterative mindsets the Digital Humanities can help inform our approaches.
Are scholarly publishers primed to become the critical content suppliers for the big Generative AI companies?
In this article, Minhaj Rain explores how human intelligence tasks (HITs) and not simply more AI tools could be the way forward as a reliable and scalable solution for maintaining research integrity within the scholarly record.
An update on how generative AI has progressed and how it has been applied to research publishing processes since ChatGPT was released, looking at business, application, technology, and ethical aspects of generative AI.
This year, Ithaka S+R is examining the shared infrastructure for scholarly communication and will ultimately make recommendations for its future. This week, we issued a draft of our project report. Please share your comments, suggestions, and other feedback by the end of August.
The AI takeover isn’t all doom and gloom. Finally, a long running musical question can be answered.
Revisiting a post from 2017: Several services aim to gather all publications comprehensively. Who has all the content?