IBM wants to diversify facial recognition systems. To do so they used 1 million images of faces from a Flickr dataset that had 100 million videos and photos.
According to CNBC, the images are annotated with tags related to features including gender, facial symmetry, age, and craniofacial measurements.
Researchers at IBM hope the details will help train artificial intelligence-powered facial recognition systems to be more unbiased and precise when identifying faces.
“Facial recognition technology should be fair and accurate,” John Smith, a fellow and lead scientist at IBM, told CNBC by email. “In order for the technology to advance it needs to be built on diverse training data.”
“Many prominent datasets used in the field are too narrow and fall short in coverage and balance,” Smith added. “The data does not reflect the faces we see in the world.”
In 2016, the Center for Privacy and Technology at Georgetown University’s law school found that Black Americans would be “disproportionately affected by police face recognition systems as they are disproportionately targeted for arrests.”
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