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August 11, 2021 12:02 am

Twitter Algorithm Prefers Slimmer, Younger, Light-Skinned Faces

An anonymous reader quotes a report from the BBC: A Twitter image-cropping algorithm prefers to show faces that are slimmer, younger and with lighter skin, a researcher has found. Bogdan Kulynyc won $3,500 in a Twitter-organized contest to find biases in its cropping algorithm. Earlier this year, Twitter's own research found the algorithm had a bias towards cropping out black faces. The "saliency algorithm" decided how images would be cropped in Twitter previews, before being clicked on to open at full size. But when two faces were in the same image, users discovered, the preview crop appeared to favor white faces, hiding the black faces until users clicked through. As a result the company revised how images were handled, saying cropping was best done by people. The "algorithmic-bias bounty competition" was launched in July -- a reference to the widespread practice of companies offering "bug bounties" for researchers who find flaws in code -- with the aim of uncovering other harmful biases. And 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." Second prize went to Halt AI, a female-founded University of Toronto start-up Twitter said showed the algorithm could perpetuate marginalization in the way images were cropped. For example, "images of the elderly and disabled were further marginalized", the company said. Taraaz Research founder Roya Pakzad won third prize for an entry that showed the algorithm was more likely to crop out Arabic text than English in memes.

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