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

They are asking the wrong question. The headline says AI-generated images are “undermining trust in science.” As if trust were a vase on a shelf that a clumsy machine might knock over. The trust was already shattered. The image is only the latest symptom. For decades, the structure of scientific publishing has been a plantation system of its own: the labor of researchers, often publicly funded, harvested for profit by a handful of corporate journals, their work locked behind paywalls, their careers held hostage to the whims of a peer-review process that is as opaque as it is arbitrary. The trust was not in the image; it was in the process. And that process has long been compromised.

Now the forger’s tools are democratized. Anyone, they say, can fake an image. But who has been faking the narrative? Who has been presenting corporate-funded research as disinterested truth? Who has been airbrushing out negative results to maintain the facade of seamless progress? The AI did not create this crisis of credibility. It has merely exposed the fault lines that were always there, the gap between the professed ideals of open inquiry and the closed, proprietary reality. The periphery - the early-career researcher, the scholar from the global south without institutional access - has always seen this logic most clearly. Now the machine makes it visible to everyone.

The solution is not better detection software. It is a different political economy of knowledge. When the enslaved took Saint-Domingue, they did not ask for better whips. They seized the means of production. Science must do the same. Open archives, communal peer review, a dismantling of the prestige economy that rewards splashy, easily-faked images over slow, reproducible work. The fake image is not the problem. It is the alarm. And the alarm is ringing because the house was built on sand.