Carnegie Mellon University

Just Drive

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Cell Phone Study Sparks Action

Cell Phone While Driving

The National Safety Council recently called for a ban on cell phone use while driving. Behind the push? A recent study by Carnegie Mellon Psychology Professor Marcel Just demonstrating the dangers of distraction at the wheel.

Just and his colleagues showed that simply listening to a cell phone while driving can cause drivers to commit errors as if they were under the influence of alcohol. New findings by Carnegie Mellon researchers show making the devices hands-free or voice-activated is not sufficient in eliminating these distractions.

"Drivers need to keep not only their hands on the wheel, they also have to keep their brains on the road," said Just, director of Carnegie Mellon's Center for Cognitive Brain Imaging and author of the report.

"A generation from now, when we have changed the social norm and culture about cell phone use while driving, and people come to accept it as socially unacceptable and dangerous behavior — as our society has similarly adjusted its norms about drunk driving — Dr. Just's science will be viewed as one of the ground-breaking studies that pushed our nation to action," said John Ulczycki, the National Safety Council's communications & public affairs executive director.

For the first time, Just's study used brain imaging to document that listening to a call reduces the amount of brain activity associated with driving by 37 percent. This can cause drivers to weave out of their lane, based on the performance of subjects using a driving simulator.

Other distractions, such as eating, listening to the radio or talking with a passenger, also can divert a driver. Though it is not known how these activities compare to cell-phone use, Just said there are reasons to believe cell phones may be especially distracting.

"Talking on a cell phone has a special social demand, such that not attending to the cell conversation can be interpreted as rude, insulting behavior," he noted. A passenger, by contrast, is likely to recognize increased demands on the driver's attention and stop talking.

The research of Just and colleague Tom Mitchell, chair of Carnegie Mellon's Machine Learning Department, was featured on recent episode of CBS News' 60 Minutes — exploring how machine learning and language technologies may someday make it possible to use brain scans to identify thoughts.

The report focused on the Carnegie Mellon team's recent findings about how the mind encodes the meaning of words.

Related Links: Thought-Reading Demo  |  CCBI