The study from the Georgia Institute of Technology found that image-detection systems were 5% less accurate at detecting dark-skinned pedestrians.
from the Georgia Institute of Technology suggests autonomous driving systems may have more difficulty detecting pedestrians with dark skin than those with light skin.
The researchers analyzed how effective image-detection systems were at identifying light-skinned and dark-skinned pedestrians.The researchers suggested that the difference could result from not having enough dark-skinned pedestrians in the images used to train the systems and the systems' insufficient emphasis on learning from the smaller population of dark-skinned pedestrians.
The researchers responsible for the study had eight image-detection systems analyze images of pedestrians. The people in the photos were separated into two groups based on how their skin tones aligned with the Fitzpatrick skin type scale, which divides skin tones into six categories.
The researchers suggested that the differences in pedestrian-detection accuracy could result from not having enough dark-skinned pedestrians in the images used to train the systems, as well as the systems' insufficient emphasis on learning from the smaller population of dark-skinned pedestrians.
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