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Learned Publishing: Volume 37, issue 1, January 2024.

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"There is no research integrity without innovation. If we do not harness the power of emerging tools, we may fail in our stewardship of the scientific record."

From: “The robot uprising is here: Is scholarly publishing ready?” Sami Benchekroun, Learned Publishing 37(1), 10.1002/leap.1595 (2024).

I’m pleased to announce that the January issue of Learned Publishing (Vol. 37, issue 1) is now available to read. The above quote comes from an Opinion article in this special issue, which is themed around the topic “Digital innovations and research integrity – opportunities and risks for scholarly publishing”. This quote captures the importance of innovation for the scholarly publishing industry, now more than ever.

Of course, the role and ethics of the use of artificial intelligence (AI) in scholarly research and publishing is at the forefront of many people’s minds, with the industry having had to move quickly to introduce policies for the use of AI-assisted tools by authors and reviewers. In their Original Article, Lund and Naheem examine the AI authorship policies of 300 top academic journals during the period of late-spring 2023. In their Opinion piece, Kendall and Teixeira da Silva voice concerns around the potential for the abuse of large language models (LLMs), such as ChatGPT, particularly as a potential new tool for predatory publishing, and while pointing out that there are many legitimate ways authors may use LLM-based tools, it will be important for publishers and academia to have tools to detect undisclosed use of such tools. Two further opinion pieces discuss the topic of AI, with Hetzscholdt sounding a note of caution in their article around the ethical and practical concerns that such tools raise, and Benchekroun offering a counterpoint in his article by pointing out the necessity to embrace digital innovation to support research integrity.

Peer review is a crucial part of the process of ensuring research integrity, and two articles in this special issue examine this. In their Original Article, Kousha and Thelwall provide a literature and software summary discussing the partial or complete automation of several publishing-related tasks, including identifying peer reviewers, and potentially supporting reviewing itself. In their Opinion piece, Calamur and Ghosh highlight the strain on the peer review system, and discuss a global survey carried out to gather insights on research integrity and peer review. They conclude that it is essential for peer review systems to embrace innovation, including the ethical use of AI, in a process that must be guided by the collaborative efforts of all stakeholders.

The digitisation of the scholarly record and emergence of innovative tools has unlocked opportunities not only for how publishing workflows operate, but also for the way research is published. Data sharing is an important factor in establishing a high level of research integrity, enabling data transparency and the ability of the wider academic community to scrutinise findings. In their Original Article, Haak et al. describe the development of a model for measuring data sharing and reuse that uses text mining of article methods sections for mentions of research resources, databases, and repositories as a proxy measurement of data sharing and reuse.

One of the primary concerns relating to the use of AI-based tools in scholarly publishing is the potential for their misuse by bad actors – namely, those involved in predatory publishing. This issue includes two Case Studies looking into this further; in the first, Dodgson et al. describe the outcomes of one journal’s efforts to introduce a process to discourage authors' use of references from predatory publishers. In the second, Stockemer and Reidy highlight and provide evidence from their journal of two types of publishing fraud: fake acceptance letters and financial fraud. In addition, in their Opinion Piece, Solomon reflects on the problem of cloned journals, and provides advice for researchers in recognizing and avoiding these.

Given the very recent impact of tools such as AI and LLMs on our industry, many of the articles in this issue are opinion-based in nature. It is to be expected that over the course of this volume of Learned Publishing and beyond, further research and case studies will be published to help establish best practices for these exciting but ethically complex emerging innovations. I look forward with interest to further submissions in this area and to sharing them with our readers.

"We need speed. We need integrity. Instead of allowing the role of AI to stay murky and ambiguous in the publishing process, let's identify the power of human contributions and the power of machine contributions."

From: “The robot uprising is here: Is scholarly publishing ready?” Sami Benchekroun Learned Publishing 37(1), 10.1002/leap.1595 (2024).

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Best wishes,

Jo

Jo Hutchinson

Marketing Specialist

Association of Learned and Professional Society Publishers

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