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

June 23, 2026.

The reports of synthetic imagery infiltrating the journals do not surprise me, but they necessitate a rigorous definition of terms. What do we mean by “scientific image”? If we mean a record of an observation, it is a measurement. If we mean a decorative representation of a theory, it is an illustration. The crisis today arises because the journals have conflated the two. An illustration requires only aesthetic plausibility; a measurement requires a chain of provenance.

This crisis rests on two assumptions. First, it assumes that the prestige of the journal - the institution - is a proxy for the truth of the claim. Second, it assumes that visual “evidence” is self-authenticating. Both assumptions are fictions. The institution is a stone portico; it can be occupied by anyone. The image is merely a shadow on the wall of the cave.

Let us apply a geometric proof to the problem of trust. Axiom: Science is not the belief in results, but the verification of the process. Step one: An AI generates a result without a process. Step two: A reviewer accepts the result because it looks familiar. Conclusion: The reviewer has abandoned the method for the sake of the institution’s schedule.

When the image is faked, the institution suffers a wound, but the method remains untouched. If every journal burned tomorrow, the Pythagorean theorem would remain true. The solution is not better software to detect fakes; it is a return to the portable method. Demand the raw data. Demand the proof. If a claim cannot be reconstructed from its first principles by a skeptical mind, it is not science; it is merely a story told with light. We must protect the method of inquiry, for it is the only thing that survives the fire.