Collaborating Authors

Twitter algorithmic bias bounty challenge unveils age, language and skin tone issues


Twitter has released a detailed report on the results of its first algorithmic bias bounty challenge, revealing a number of areas where their systems and algorithms were found to have been lacking in fairness. The increasing scale of AI is raising the stakes for major ethical questions. Twitter machine learning engineer Kyra Yee and user researcher Irene Font Peradejordi noted that the bias bounty challenge that took place in August was partially spurred by complaints from Twitter users in October 2020 about an image cropping feature that was found to have cut out Black faces in favor of white faces. Users even illustrated the problem using photos of former US President Barack Obama, showing that his face, and any others with darker skin, were cropped out of images that instead focused on white faces in the same photo. Twitter committed to decreasing its reliance on ML-based image cropping and it began rolling out the changes in May 2021.

Could bug bounties help find biased algorithms? This competition put the idea to the test


Kulynych earned the top reward thanks to his discovery that Twitter's algorithm tends to apply a "beauty filter". Twitter has been trialing an unprecedented method to find the hidden biases in its own algorithms. The social media platform has enrolled external researchers in a one-of-a-kind competition, in which winning participants were those that could come up with the most compelling evidence demonstrating an unfair practice that is carried out by one of the company's algorithms. Called the "algorithmic bias bounty challenge", the initiative provided participants with full access to the code that underpins Twitter's image-cropping algorithm, which determines how pictures should be cropped to be easily viewed when they come up on a user's timeline. SEE: The Pentagon says its new AI can see events'days in advance' The model is programmed to estimate what a person is most likely to want to look at in a picture – that is, the most salient part of the image, which is why it is also known as the saliency algorithm.

Why Twitter wants ethical hackers to fix its algorithmic biases


Twitter is applying the bug bounty model to machine learning. The micro-blogging site has launched the industry's first algorithmic bias bounty competition. The challenge was created to identify potential harms in Twitter's notorious image cropping algorithm, which was largely abandoned after exhibiting gender- and race-based biases. Attend the tech festival of the year and get your super early bird ticket now! The company now wants to incentivize the community to find further unidentified risks of the algorithm.

Twitter announces first algorithmic bias bounty challenge


Twitter has announced its first algorithmic bias bounty challenge, offering cash prices ranging from $500 to $3,500 for those who can help the social media giant identify a range of issues. After significant backlash last year, the company admitted in May that its automatic cropping algorithm repeatedly cropped out Black faces in favor of White ones. It also favored men over women, according to research from Twitter. Multiple Twitter users proved this fact using pictures of themselves or of famous figures, like former President Barack Obama. Rumman Chowdhury, director of Twitter META, explained that the company decided to change the algorithm and admitted that companies like Twitter often "find out about unintended ethical harms once they've already reached the public."

Twitter launches bug bounty contest to detect algorithmic bias


Twitter has laid out plans for a bug bounty competition with a difference. This time around, instead of paying researchers who uncover security issues, Twitter will reward those who find as-yet undiscovered examples of bias in its image-cropping algorithm. Back in April, Twitter said it would study potential "unintentional harms" created by its algorithms, beginning with its image-cropping one. It started using the algorithm in 2018 in an attempt to focus on the most interesting parts of images in previews. Some users criticized how Twitter handled automated cropping, claiming that the algorithm tends to focus on lighter-skinned people in photos.