But when almost anyone can fabricate a visually similar image in seconds from a text prompt using artificial intelligence, how do people decide which image is real?
AI tools are already changing how scientific visuals are created, shared and publicized.
While AI can help scientists communicate complicated ideas more creatively and efficiently, these same tools blur the lines between illustration, enhancement and fabrication.
NEJM Images in Clincal Medicine from last week retracted due to AI image manipulation. Look at the numbers on the ruler??♂️ t.co/lafNw15Kao pic.twitter.com/c66u5ZX8PkMay 2, 2026
The biggest concern are realistic-looking visuals that subtly distort scientific details while remaining believable enough to pass initial review.
Trust in scientific images
Research in science communication, including my own, suggests that people judge scientific visuals using a few mental shortcuts. Does the image look technically sophisticated? Does it come from a trusted institution? Does it match what I already believe? Generative AI is undermining all three of these heuristics, or mental shortcuts.
This image of the Earth taken from the Artemis II mission in April 2026 is very much real. Does everyone believe it? (Image credit: NASA)
As a result, authentic scientific images that challenge someone's existing beliefs can now be dismissed as AI-generated, whereas fabricated images that confirm them are easily accepted as evidence. AI, in this way, may amplify motivated reasoning — that is, people's tendency to accept what they already agree with and question what they do not.
If audiences stop trusting visual evidence altogether, science loses one of its most powerful tools for public communication.
One practical path forward is for researchers to treat image provenance — where an image came from and how it was created — with the same seriousness they already apply to data provenance.
My colleagues and I found that people's familiarity with AI significantly shapes how they judge the credibility of AI-generated visuals. Those familiar with AI tools were more likely to view AI disclosure as a sign of transparency, and some rated clearly labeled AI-generated content as more credible than unlabeled content.
Why authentic images remain powerful
The original Apollo 8 "Earthrise" photograph of 1968 carries significant emotional impact. So do the Artemis II images of 2026.
In the age of generative AI, scientific institutions can no longer assume audiences will automatically trust their visuals. Trust now depends on transparency, documentation and clear communication about how visual evidence is produced.
This edited article is republished from The Conversation under a Creative Commons license. Read the original article.
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