Visual intelligence has nothing to do with being smart or having a high IQ, a new study has found. 

Researchers found intelligence does not guarantee a person’s ability to learn visual skills, such as interpreting medical X-rays, or tracking a flightpath on a radar display. 

Instead visual skills can be measured as a separate ability and are not associated with general intellect, according to the report, “Domain-specific and domain-general individual differences in visual object recognition”, published in the Cognition journal.  

“People may think they can tell how good they are at identifying objects visually,” said the study’s lead author Isabel Gauthier, a psychology professor at American’s prestigious Vanderbilt University. “But it turns out that they are not very good at evaluating their own skills relative to others.”

Previous research has focused on the positive links between visual skills and intelligence, but Prof Gauthier said she wanted to study how these skills vary among individuals.

“This is quite exciting because performance on cognitive skills is almost always associated with general intelligence,” she said. “It suggests that we really can learn something new about people using these tests, over and beyond all the abilities we already know how to measure.”

Using novel computer-generated creatures called greebles, sheinbugs and ziggerins, Prof Gauthier performed a series of tests using more than 2,000 subjects. 

Displaying six target creatures in sets of three, each set contained a creature from the target group along with two unfamiliar creatures. The participant was then asked to pick out the familiar creature. 

Using the creatures meant people had no prior reference points from the real world with which they might already be familiar.  

The study found the difference in individuals’ visual abilities was on a much larger scale than previously believed. 

“A lot of jobs and hobbies depend on visual skills,” Prof Gauthier said. “Because they are independent of general intelligence, the next step is to explore how we can use these tests in real-world applications where performance could not be well predicted before.”

Researchers tested more than 2,000 subjects and the study was funded by the National Science Foundation awards.

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