A new study by York University researchers has found a potential striking flaw in artificial intelligence (AI) models. Artificial neural networks (ANNs), a type of AI model built to solve vision tasks for computers, have surprisingly emerged as the current best understanding of how our own brain’s visual system works, in the last decade. But does current AI really work like a primate brain?

“Artificial intelligence systems are often described as ‘brain-like’ because they can predict activity in parts of the brain that help us recognize objects,” says York University Assistant Professor Kohitij Kar, senior author of a new study. “Until now, scientists mostly tested this in one direction. They asked whether AI models can predict brain activity.”

In this study, the researchers flipped the question—if AI truly mirrors the brain, shouldn’t brain activity also be able to predict what’s happening inside the AI model?—and developed a reverse predictivity test to find the answer. The findings are published in the journal Nature Machine Intelligence.