Anyone can fake a scientific image with AI, tricking even academic journals – and undermining trust in science
Publish Date: 2026-06-22 08:36:00
Source Domain: theconversation.com
A photograph of Earth glowing in deep space, the Moon’s cratered horizon stretching across its foreground, caught many people’s eyes in April 2026. Astronauts captured the image while aboard NASA’s Artemis II mission, and like the famous Apollo 8 “Earthrise” image, the picture felt instantly real and inspiring for many.
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?
The proliferation of AI-generated science images in public spaces is not simply a misinformation problem. As a researcher who studies visual science communication and public trust, I believe it also contributes to a crisis of trust in science in the age of AI, and the tools scientists have long relied on to establish visual credibility are losing their grip.
AI-generated images infiltrate science
AI tools are already changing how scientific visuals are created, shared and publicized.
Researchers use them to generate illustrations, create synthetic data, edit lab images and produce materials for education and public outreach.
While AI can help scientists communicate complicated ideas more creatively and efficiently, these same tools blur the lines between illustration, enhancement and fabrication.
In 2024, two papers were retracted after publishing AI-generated figures posessing biologically impossible structures. In April 2026, the New England Journal of Medicine retracted a paper after discovering that a clinical image had been manipulated with AI. These are just cases that came to mass public attention and are likely just the tip of the iceberg. Researchers have warned that AI-generated visuals pose growing threats in fields that depend heavily on visual evidence, such as materials science.
Academic publishers are beginning to adopt AI-detection tools. However, systems designed to detect fake images will almost always lag behind systems designed to…