Self-driving cars risk ‘future errors’ due to difficulty detecting darker skin tones: Researchers

Systems used by self-driving cars to avoid pedestrians may be less accurate at detecting people with darker skin, a report out of the Georgia Institute of Technology warned recently.

Researchers published their findings in a report, “Predictive Inequity in Object Detection,” after testing several similar systems to determine how accurately they spot people of varying skin tones.

Using a collection of digital photographs showing street scenes with pedestrians, the researchers grouped each person pictured in the dataset by their placement on the Fitzpatrick scale — a classification schema that measures skin tone on a scale of one to six from lightest to darkest — and then gauged how well the object-detection systems spotted people lumped on either side of the spectrum.

Summarizing the results, the researchers wrote that their findings “show uniformly poorer performance of these systems when detecting pedestrians with Fitzpatrick skin types between 4 and 6.”

“This behavior suggests that future errors made by autonomous vehicles may not be evenly distributed across different demographic groups,” the researchers wrote.

On average, detection was five percentage point less accurate among individuals on the darker side of the scale, Vox reported Wednesday.

Read more via WashingtonTimes