In May, Twitter said that it would stop using an artificial intelligence algorithm found to favor white and female faces when auto-cropping images. Now, an unusual contest to scrutinize an AI program for misbehavior has found that the same algorithm, which identifies the most important areas of an image, also discriminates by age and weight, and favors text in English and other Western languages. The top entry, contributed by
Bogdan Kulynych, a graduate student in computer security at EPFL in Switzerland, shows how Twitter's image-cropping algorithm favors thinner and younger-looking people. Kulynych used a deepfake technique to auto-generate different faces, and then tested the cropping algorithm to see how it responded. "Basically, the more thin, young, and female an image is, the more it's going to be favored," says Patrick Hall, principal scientist at BNH, a company that does AI consulting. He was one of four judges for the contest.
Bogdan Kulynyc won $3,500 in this contest to find biases in its cropping algorithm. Mr Kulynyc, a graduate student at the Swiss Federal Institute of Technology in Lausanne's Security and Privacy Engineering Laboratory, discovered the "saliency" of a face in an image could be increased - making it less likely to be hidden by the cropping algorithm - by "making the person's skin lighter or warmer and smoother; and quite often changing the appearance to that of a younger, more slim, and more stereotypically feminine person". Awarding him first prize, Twitter said his discovery showed beauty filters could be used to game the algorithm and "how algorithmic models amplify real-world biases and societal expectations of beauty".
Credits:
https://www.wired.com/story/twitters-photo-cropping-algorithm-favors-young-thin-females/
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