On: Anyone can fake a scientific image with AI, tricking even academic journals - an

The alarm over AI-forged images in scientific journals is understandable, but misplaced. The problem is not new; it merely wears a digital mask. Fraudulent data has always existed - fabricated tables, manipulated photographs, selective reporting. The tool changes, not the temptation.

What interests me is the disproportionate reaction. If a researcher alters a gel electrophoresis image by hand, we call it misconduct. If an AI does it, we call it a crisis for science itself. The standard of evidence should not fluctuate with the method of deception. A lie is a lie, whether penned or pixelated.

The deeper issue is the over-reliance on images as proof. Visual evidence has always been persuasive, but it was never sufficient. A photograph of a specimen does not replace the specimen; a graph does not substitute for raw data. The error lies in treating images as conclusions rather than illustrations. If journals now fear AI’s capacity to deceive, perhaps they should revisit their own assumptions about what constitutes proof.

Science has survived worse. It will survive this, provided it remembers that trust is not built on the absence of fraud, but on the presence of verification.