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JID Innovations Issues Guidelines for Authors on use of Generative Artificial Intelligence (AI) or Large Language Models (LLM)

The rise of generative artificial intelligence (AI) and large language models (LLM) has implications for authors, reviewers and editors alike. While we recognize there may be advantages in using AI/LLM to provide assistance in writing manuscripts or research grants, especially for non-native English-speaking scientists, we must be aware of the limitations of generative AI/LLM. The tool is only as good as the information that it is taught, which means that biases or misinformation inherent in its teaching can be perpetuated. For these reasons and more, Russell Hall MD, Editor of JID Innovations, recently published an editorial detailing the pros and cons of current AI/LLM (Hall, 2024). From this editorial JID Innovations has developed a policy for authors. In short, JID Innovations expects that all uses of AI/LLM in any part of the research process and/or manuscript preparation be declared. The journal also requires an explicit statement on what, and how, AI/LLM was used in any part of the research process and/or manuscript preparation. If no AI/LLM was used, a standard statement should be supplied. The policy also applies to our reviewers and editors who are prohibited from uploading any part of a manuscript onto a generative AI platform.

JID Innovations editors will assess manuscripts that declare use of AI/LLM (beyond basic tools for checking grammar, spelling, references etc.) on an individual basis to determine the manuscript’s suitability for publication. We will also utilize software applications which have been developed to assist in estimating the probability that AI/LLM were utilized in any aspect of the manuscript. As the field of AI/LLM progresses we will continue to assess our policies and encourage authors with questions to contact us: innovationsoffice@sidnet.org.

Hall, R. P. (2024). Generative Artificial Intelligence, Large Language Models, and JID Innovations. JID Innovations, 4(2), 100256. https://doi.org/10.1016/j.xjidi.2024.100256

 

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