Artificial Intelligence
Author Use of Large Language Models (LLMs) and AI Chatbots in Medicine
Large Language Models (LLMs) and other AI tools, such as ChatGPT, do not currently satisfy our authorship criteria. Notably, an attribution of authorship carries with it accountability for the work, which cannot be effectively applied to LLMs. The use of an LLM or other AI tool in your medical research should be properly documented in the Methods section (and if a Methods section is not available, in the Acknowledgements section) of the manuscript.
The use of an LLM (or other AI tool) for “AI-assisted copy editing” purposes does not need to be declared in our journal of medicine. In this context, we define the term 'AI-assisted copy editing' as AI-assisted improvements to human-generated texts for readability and style, and to ensure that the texts are free of errors in grammar, spelling, punctuation, and tone.
These AI-assisted improvements may include wording and formatting changes to the texts, but do not include generative editorial work, autonomous content creation, or conferring AI authorship. In all cases, there must be human accountability for the final version of the text and agreement from the submitting authors that the edits reflect their original work.
Generative AI Images
The fast-moving area of generative AI image creation has resulted in novel legal copyright and research integrity issues. As publishers, we strictly follow existing copyright law and best practices regarding publication ethics and AI use in medical research. While legal issues relating to AI-generated images and videos remain broadly unresolved, Springer Nature journals are unable to permit their use for publication.
Exceptions related to AI visuals and authorship include*:
- Images/art obtained from agencies with which we have contractual relationships and that have created images in a legally acceptable manner.
- Images and videos that are directly referenced in a piece that is specifically about AI and such cases will be reviewed on a case-by-case basis.
- The use of generative AI tools developed with specific sets of underlying scientific data that can be attributed, checked, and verified for accuracy, provided that ethics, copyright, and terms of use restrictions are adhered to.
*All exceptions must be clearly labeled as generated by AI within the image field.
As we expect things to develop rapidly in this field in the near future, we will review this policy regularly and adapt it if necessary.
Clarifications on AI Image Types and Authorship
Examples of AI-generated image types covered by this policy in journals of medicine include video and animation, including video stills, photography, illustrations such as scientific diagrams, photo-illustrations, and other collages, and editorial illustrations such as drawings, cartoons, or other 2D or 3D visual representations.
Not included in this policy are text-based and numerical display items, such as tables, flow charts, and other simple graphs that do not contain images. Please note that not all AI tools used in medical research are generative. The use of non-generative machine learning tools to manipulate, combine, or enhance existing images or figures should be disclosed in the relevant caption upon submission to allow a case-by-case review.
Peer Reviewer Use of Large Language Models (LLMs) and AI Chatbots in Medicine
Peer reviewers play a vital role in scientific publishing. Their expert evaluations and recommendations guide editors in their decisions and ensure that published research is valid, rigorous, and credible. Editors select peer reviewers primarily because of their in-depth knowledge of the subject matter or methods of the work they are asked to evaluate. This expertise is invaluable and irreplaceable.
Peer reviewers are accountable for the accuracy and views expressed in their reports, and the peer review process operates on a principle of mutual trust between authors, reviewers, and editors.
Despite rapid progress, generative AI tools have considerable limitations; they can lack up-to-date knowledge and may produce nonsensical, biased, or false information. Manuscripts may also include sensitive or proprietary information that should not be shared outside the peer review process. For these reasons, we ask that, while Cureus explores providing our peer reviewers with access to safe AI tools, peer reviewers do not upload manuscripts into generative AI tools while peer reviewing medical research.
If any part of the evaluation of the claims made in the manuscript was in any way supported by an AI tool, we ask peer reviewers to declare the use of such AI tools transparently in the peer review report for our medical journal.