ArticleJDS communications2025
Generative artificial intelligence tools in journal article preparation: A preliminary catalog of ethical considerations, opportunities, and pitfalls.
Article in JDS communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The launch of generative artificial intelligence (GenAI) tools has catalyzed considerable discussion about the potential impacts of these systems within the scientific article preparation process. This symposium paper seeks to summarize current recommendations on the use of GenAI tools in scientific article preparation, and to provide speculations about the future challenges and opportunities of GenAI use in scientific publishing. Due to the dynamic nature of these tools and the rapid advancement of their sophistication, the most important recommendation is that ongoing engagement and discussion within the scientific community about these issues is critical. When using GenAI tools in scientific article preparation, humans are ultimately accountable and responsible for products produced. Given that accountability, an expert panel convened by the National Academies of Science, Engineering, and Medicine recently proposed principles of GenAI use in science communication, including (1) transparent disclosure and attribution; (2) verification of AI-generated content and analyses; (3) documentation of artificial intelligence (AI)-generated data; (4) a focus on ethics and equity; and (5) continuous monitoring, oversight, and public engagement. In addition to the importance of human accountability, many publishers have established consistent policies suggesting that GenAI tools should not be used for peer reviewing, figure generation or manipulation, or assigned authorship on scientific articles. Along with the potential ethical challenges associated with GenAI use in scientific publishing, there are numerous potential benefits. Herein we summarize example conversations demonstrating the capacity of GenAI tools to support the article preparation process, and an example standard operating procedure for human-AI interaction in article preparation. Finally, diverse broader questions about the impact of GenAI tools on communication, knowledge, and advancement of science are raised for rumination.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.