The more we lean on AI to think, the worse we get at noticing when it's wrong.
A new MIT Media Lab study tracked 67 people over four weeks as they used an AI assistant to evaluate news headlines. With the AI helping, their accuracy jumped by 21%. Without it, by week four, their ability to spot fake content had dropped 15.3% from where they started. The skill they thought they were practicing had quietly eroded underneath them.
Real headlines were fine. Accuracy on those barely budged. It was fake content they got worse at catching, which is the one thing the AI was supposedly helping with.
The mechanism is uncomfortable. To know whether AI is wrong, you need to already know enough to catch it. And that knowledge comes from doing the work yourself.
"We're implicitly assuming that people have the expertise to tell whether the AI is right or wrong," Zana Buçinca, an incoming MIT professor who studies human-AI interaction, told TIME. "But expertise forms through effortful engagement. If we circumvent the need for that, we risk eroding the skill itself."
Research out of the University of the Basque Country adds another layer. When people use AI without strong self-regulation habits, they end up confidently wrong. The output looks polished, the answer comes fast, and the brain reads that as competence even when it shouldn't be.
Evan Risko, a University of Waterloo professor who studies what researchers call cognitive offloading, put it to TIME more bluntly: "It's starting to creep into the things we thought were cognitively ours."
A separate study of programmers using a coding tool called VibeCheck caught the moment in a single quote. One participant, asked to review code they'd just generated with AI, said: "I was going to just click 'Apply' and move on, but the modal made me realize I didn't actually know why the state was updating. It forced me to read the code I just asked the AI to write."
That's the trap in miniature. The work felt done. The understanding wasn't there.
The story we keep telling ourselves about AI is that it handles the boring stuff so we can focus on the important stuff. The research keeps showing the opposite. The skills going first are the ones we use to evaluate whether the AI is even right, which means by the time it gets something seriously wrong, we'll be the least equipped we've ever been to notice. That isn't a future problem. It's already showing up four weeks into a study where people thought they were getting sharper.
