I’m more of a scroller than a poster on social media. Like many people, I wind down at the end of the day with a scroll binge, taking in videos of Italian grandmothers making pasta or baby pygmy hippos frolicking.
For a while, my feed was filled with immaculately designed tiny homes, fueling my desire for minimalist paradise. Then, I started seeing AI-generated images; many contained obvious errors such as staircases to nowhere or sinks within sinks. Yet, commenters rarely pointed them out, instead admiring the aesthetic.
These images were clearly AI-generated and didn’t depict reality. Did people just not notice? Not care?
As a cognitive psychologist, I’d guess “yes” and “yes.” My expertise is in how people process and use visual information. I primarily investigate how people look for objects and information visually, from the mundane searches of daily life, such as trying to find a dropped earring, to more critical searches, like those conducted by radiologists or search-and-rescue teams.
With my understanding of how people process images and notice − or don’t notice − detail, it’s not surprising to me that people aren’t tuning in to the fact that many images are AI-generated.
We’ve been here before
The struggle to detect AI-generated images mirrors past detection challenges such as spotting photoshopped images or computer-generated images in movies.
But there’s a key difference: Photo editing and CGI require intentional design by artists, while AI images are generated by algorithms trained on datasets, often without human oversight. The lack of oversight can lead to imperfections or inconsistencies that can feel unnatural, such as the unrealistic physics or lack of consistency between frames that characterize what’s sometimes called “AI slop.”
Despite these differences, studies show people struggle to distinguish real images from synthetic ones, regardless of origin. Even when explicitly asked to identify images as real, synthetic or AI-generated, accuracy hovers near the level of chance, meaning people did only a little better than if they’d just guessed.
In everyday interactions, where you aren’t actively scrutinizing images, your ability to detect synthetic content might even be weaker.
Attention shapes what you see, what you miss
Spotting errors in AI images requires noticing small details, but the human visual system isn’t wired for that when you’re casually scrolling. Instead, while online, people take in the gist of what they’re viewing and can overlook subtle inconsistencies.
Visual attention operates like a zoom lens: You scan broadly to get an overview of your environment or phone screen, but fine details require focused effort. Human perceptual systems evolved to quickly assess environments for any threats to survival, with sensitivity to sudden changes − such as a quick-moving predator − sacrificing precision for speed of detection.
This speed-accuracy…
