Scholarly publishing is seeing continued changes in how research is evaluated, reviewed, and made accessible. As artificial intelligence becomes more integrated into publishing workflows, questions around transparency, accountability, and human oversight are gaining attention.
At the same time, new initiatives are exploring more open approaches to peer review, while publishing organizations are updating their standards to address emerging challenges. Four recent developments offer a closer look at how the scholarly publishing landscape is evolving.
Scholarly publishing organizations update transparency and best practice guidelines
The fifth edition of the Principles of Transparency and Best Practice in Scholarly Publishing, developed jointly by COPE, DOAJ, OASPA, and WAME, introduces updated guidance for journals and publishers. The revised principles address emerging challenges, particularly the use of AI by authors, editors, and peer reviewers. They call for clearer disclosure policies around AI-assisted content and editorial activities, while reaffirming that AI systems cannot be credited with authorship.
The update also introduces stronger safeguards against hijacked journals, expands protections for editorial independence, and provides clearer guidance on handling publication misconduct, overlapping publications, complaints, and appeals. The revised framework reflects the changing expectations placed on scholarly journals and reinforces the importance of transparency, research integrity, and responsible publishing practices. Read the full article here
Nature reports on growing support for preprint-centric publishing
Holly Else’s article in Nature reports on the expansion of the European Commission’s Open Research Europe (ORE) platform, which follows a ‘publish, review, curate’ model. Supported by research funders and organizations across 11 European countries, the expanded platform will provide free editorial services to more than 2.5 million researchers. Under this approach, researchers can publish preprints, undergo open peer review, and make reviewer identities and reports publicly available on the same platform.
The expansion is backed by a €16 million budget through 2030 and forms part of a broader effort to promote open and transparent scholarly communication. Holly also highlights the formation of the Publish, Review, Curate Alliance, bringing together 40 funders, institutions, publishers, and platforms to support similar initiatives. However, questions remain about the practical demands of managing quality control, editorial decisions, and the implications of this model for traditional journal recognition. Read the full article here
Springer Nature and Google DeepMind develop an AI assistant for peer reviewers
Springer Nature and Google DeepMind have announced a research partnership to develop an AI-powered assistant designed to support the peer review process. The prototype, built using Google’s Gemini models, aims to help reviewers navigate manuscripts, analyze large volumes of text, charts, and figures, and identify areas that may require closer attention. The initiative is intended to help researchers work through complex submissions more effectively while allowing them to focus on questions that require specialist scientific judgment.
The system is being tested within Springer Nature’s private and secure Gemini Enterprise environment to maintain the confidentiality of author and reviewer materials. The partnership brings together Springer Nature’s experience in managing peer review and Google DeepMind’s AI capabilities. The development is part of Springer Nature’s broader approach to responsible AI adoption, with human expertise and editorial responsibility remaining central to the process. Read the full article here
The Scholarly Kitchen examines the limits of AI transparency in research
Roohi Ghosh’s article in The Scholarly Kitchen examines whether disclosing AI use in research papers is enough to establish trust and research integrity. The article points out that AI-assisted papers can contain errors, unsupported claims, and fabricated references, but so can papers written entirely by humans. Disclosure indicates whether and how AI was used, but it does not establish whether the content has been properly verified or whether the research is reliable.
The discussion also distinguishes between different applications of AI, noting that using it for language editing carries different risks from using it to generate interpretations, analyze data, or write substantial sections of a manuscript. The article highlights the need to look beyond disclosure and detection toward author accountability and meaningful human validation. While technical tools can help identify potential errors and inconsistencies, human expertise remains important in assessing evidence, reasoning, and the contribution of research. Read the full article here
As scholarly publishing continues to evolve, the balance between technological support, transparent practices, and human accountability remains central to discussions about research quality and peer review. If you’ve come across a piece lately that sparked reflection or raised important questions, feel free to share it with the ReviewerOne community.
