Twitter scraps automated image-cropping algorithm, says it cropped out Blacks and females

Twitter says it found the algorithm delivered “unequal treatment based on demographic differences”, and “objectification” bias that focused on a woman’s chest or legs. The microblogging platform said it found the algorithm delivered “unequal treatment based on demographic differences” with whites and males favoured over Blacks and females, and “objectification” bias that focused on a woman’s chest or legs, described as “male gaze.” As part of our commitment to transparency, we’ve also published our analysis on ArXiv and are sharing our source code so you can reproduce and better our analysis. Our model can be investigated via the code we have shared at: https://t.co/wb9qzAMnIj More details in our paper: https://t.co/2qLh7VyJyk https://t.co/20tZjlByVi pic.twitter.com/ilgYhjfMyZ — Shubhanshu Mishra May 19, 2021 “We considered the tradeoffs between the speed and consistency of automated cropping with the potential risks we saw in this research,” she said in a blog post. “One of our conclusions is that not everything on Twitter is a good candidate for an algorithm, and in this case, how to crop an image is a decision best made by people.” The announcement comes amid heightened concerns over advanced algorithms which can deliver biased results due to a lack of data on minorities or other factors.