Behind Twitter’s Biased AI Cropping and How to Fix It.

Behind Twitter’s Biased AI Cropping and How to Fix It.

Behind Twitter’s Biased AI Cropping and How to Fix It. A dive into the tech and practice that caused the bias in Twitter’s AI Crop and some suggested paths to recovery.

Twitter’s AI crop has a bias. When given a large photo that contained the press photos of Mitch McConnell and Barack Obama, the AI picks Mitch. Swap the position of the two pictures, and the AI picks the white guy again. This behavior has led to a lot of random experimentation online. Still, it’s important to cover what we know, what Twitter’s response was, what caused the problem, and how to fix it.

The History

It’s a well-known fact that people like to click on stories with images. It’s also known that images that are uniform, consistent, and canonical get more clicks. For example, take this photo of the bent pyramid at Dahshur. First, I’ll give you a square center crop.

A tight crop of a pyramid that looks like a pile of bricks.

Are you likely to click on that? Not a chance. Let’s do another square crop, but this time around the salient object.

Wide crop of the whole pyramid.

Boom, it’s click city. This effect gets amplified when it comes to faces. Years ago, Saeideh Bakhshi, Eric Gilbert, and I published findings that showed photos with people’s faces get more engagement on Instagram and Flickr. The Internet is full of tools trying to get better crops and has been for decades because better crops lead to better engagement and more dollars. In this case, it will come down to the Image and the AI.

ai twitter bias computer-science image-cropping

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