New Delhi: A student has now proved that Twitter’s image cropping algorithm prefers younger, slimmer faces with lighter skin. Bogdan Kulynyc won $3,500 (£2,530) in a Twitter-organized contest to find biases in its cropping algorithm.
The finding, about the company, which had previously apologized to users after reports of bias, marks the successful conclusion of Twitter’s first ever “algorithmic bug bounty”.
Earlier this year, Twitter’s own research found the algorithm had a bias towards to cropping out black faces. The company has paid $3,500 to Bogdan Kulynych, a graduate student at Switzerland’s EFPL university, who demonstrated the bias in the algorithm, which is used to focus image previews on the most interesting parts of pictures, as part of a competition at the DEF CON security conference in Las Vegas.
Kulynych proved the bias by first artificially generating faces with varying features, and then running them through Twitter’s cropping algorithm to see which the software focused on.
Since the faces were themselves artificial, it was possible to generate faces that were almost identical, but at different points on spectrums of skin tone, width, gender presentation or age – and so demonstrate that the algorithm focused on younger, slimmer and lighter faces over those that were older, wider or darker.
Twitter had come under fire in 2020 for its image cropping algorithm, after users noticed that it seemed to regularly focus on white faces over those of black people and even on white dogs over black ones.
The company initially apologized, saying: “Our team did test for bias before shipping the model and did not find evidence of racial or gender bias in our testing. But it’s clear from these examples that we’ve got more analysis to do. We’ll continue to share what we learn, what actions we take, and will open source our analysis so others can review and replicate.”
Twitter’s own subsequent analysis showed a “4% difference from demographic parity, in favour of white individuals”.