Before facial recognition tech can be fair, it needs to be diverse
Feb 18, 2019

Before facial recognition tech can be fair, it needs to be diverse

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As facial recognition software spreads, it brings the challenge of diversity along with it. So far, programs identify male, white faces far more accurately than they do black women, for example. A new IBM project aims to change that. Diversity in Faces is a data set of a million faces pulled from public domain pictures on Flickr. It gives computers a lot more to look at and process, and it introduces a way to better measure diversity in faces. John R. Smith is an IBM fellow and lead scientist of Diversity in Faces. He tells Jed Kim that there's nothing else like this.

Today's show is sponsored by Pitney Bowes and Indeed.

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Before facial recognition tech can be fair, it needs to be diverse

Feb 18, 2019
A new data set aims to help researchers measure diversity in faces.
Current facial recognition technology identifies white men far more accurately than it does black women.
Peter Macdiarmid/Getty Images

As facial recognition software spreads, it brings the challenge of diversity along with it. So far, programs identify male, white faces far more accurately than they do black women, for example. A new IBM project aims to change that. Diversity in Faces is a data set of a million faces pulled from public domain pictures on Flickr. It gives computers a lot more to look at and process, and it introduces a way to better measure diversity in faces. John R. Smith is an IBM fellow and lead scientist of Diversity in Faces. He tells Jed Kim that there’s nothing else like this.

Today’s show is sponsored by Pitney Bowes and Indeed.

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