In early 2024, a startling illustration in a published paper sparked spirited debate on social media. The image showed a rat endowed with a penis and testicles that were bigger than the rest of the animal’s body. The authors noted that the illustration was generated by an artificial-intelligence model called Midjourney, but it was obviously inaccurate, depicting four testes and including strange, misspelt text such as ‘sserotgomar cells’. Somehow, it passed peer review.Celebrating Nature’s covers — past, present and future“This was the first mainstream example of where an AI-generated image made it into a scientific paper — and it shouldn’t have been published,” says Elisabeth Bik, a science-integrity consultant in San Francisco, California, who wrote about the incident on her blog. AI tools at the time were not good enough to create credible user-prompted illustrations, as the rat figure showed — but that was then. Two years later, “AI is much better and continuously improving, and we’re at a point where we can no longer distinguish fake from real,” says Bik.Still, errors continue to crop up. In April, a study by researchers in China was retracted by the New England Journal of Medicine because of image manipulation. The numbers on a tape measure, displayed at the top of the figure, were incorrect, exposing the use of an AI tool. In a comment on the post-publication discussion forum, PubPeer, one of the authors notes that they had used an AI tool to adjust the placement of the tape measure, which had been improperly positioned during an emergency medical procedure. “The irregular numbering is an unintended artifact from this adjustment,” they wrote.How to use AI to make a graphical abstract in minutesGraphics, which include schematics, data figures and diagrams, are a crucial part of scientific publishing. And they can substantially affect an article’s influence: an analysis of eight million graphics published in scientific papers found “a significant correlation between scientific impact and the use of visual information, where higher impact papers tend to include more diagrams” (P.-S. Lee et al. IEEE Trans. Big Data 4, 117–129; 2018). However, many researchers have neither the resources nor the skills to create aesthetically pleasing and informative images themselves.The potential for modern AI systems to assist researchers in generating graphics is “huge”, says Sebastian Porsdam Mann, an ethicist at the Centre for Advanced Studies in Bioscience Innovation Law at the University of Copenhagen. AI tools can make scientific illustration accessible to everyone, allowing researchers to better communicate their science in a fraction of the time and at a lower cost than ever before, he says. And it is in researchers’ interests to have good papers that explain complex topics, with good data visualizations and graphical abstracts, he adds.‘Good design takes mastery’: scientific illustrators sketch out AI’s futureBut, as with text, AI image generators such as Midjourney and OpenAI’s DALL-E still make mistakes — the effects of which can range from personal embarrassment to professional censure. “It’s still early days and these are still largely untested waters,” says Mann. But if there’s the slightest hint that you’ve done something wrong while using AI tools, “journals will probably take that very seriously right now”.Here are some guidelines to help researchers navigate this rapidly changing landscape.Check the publisher’s rulesThe first step for anyone wanting to use AI tools in their scientific articles is to check the policies of your preferred journals. There is little agreement around the use of AI tools among academic-journal publishers, with some allowing AI-generated images as long as AI use is disclosed and others forbidding them entirely.The publisher PLOS, for example, allows the use of AI tools, but authors must report how they used them (including the names of any tools used, how they were used, how their output was evaluated and what sections of the article they were used in).AI-generated images and video are here: how could they shape research?Other publishers have a more restrictive stance. Cell Reports (published by Cell Press) prohibits any use of AI-created graphical abstracts and places restrictions on AI use in data visualizations. Springer Nature (which publishes Nature) prohibits the use of generative AI for images but makes exceptions for AI-generated images and videos in articles that are “specifically about AI”, adding that “such cases will be reviewed on a case-by-case basis”. The policy also allows researchers to use AI image-generation 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”. (Nature’s editorial team is independent of its publisher.)But guidance from journals on the use of AI is rarely specific, says Mann, who investigates AI policies in academic publishing. When talking about AI-generated images, people usually think of art and illustrations. But scientific graphics can also include schematics, visual abstracts, figures that depict a study’s data and images used as evidence. “The ethical issues are very different, if you’re using images as evidence or using them to explain things,” he says.Don’t manipulate original dataIn April, biologist Mikael Elias at the University of Minnesota in Saint Paul, posted a series of convincing western blots to the social-media site X. Western blotting detects specific proteins in complex mixtures after they have been separated on a gel. But these images had been created by entering a single prompt into ChatGPT: “generate western blots that represent an experiment in a nature journal article”.Scientific figures that pop: resources for the artistically challenged“While making up data always existed, this is making it unprecedently [sic] easy and accessible,” Elias wrote on the blogging platform Substack (see go.nature.com/4wacqm9). “I am fearing an avalanche of fabricated pieces, with very little ways to distinguish them from legit work. Not tomorrow, but soon.”Bik agrees. She says that although there are clues in Elias’s images that the blots are fake, it would be easy to miss them. And she struggled to suggest any instance in which it would be acceptable to generate images that are provided as primary evidence using AI tools.