Twitter's first bounty program for AI bias has wrapped up, and there are already some glaring issues the company wants to address. CNETreports that grad student Bogdan Kulynych has discovered that photo beauty filters skew the Twitter saliency (importance) algorithm's scoring system in favor of slimmer, younger and lighter-skinned (or warmer-toned) people. The findings show that algorithms can "amplify real-world biases" and conventional beauty expectations, Twitter said.
This wasn't the only issue. Halt AI learned that Twitter's saliency algorithm "perpetuated marginalization" by cropping out the elderly and people with disabilities. Researcher Roya Pakzad, meanwhile, found that the saliency algorithm prefers cropping Latin writing over Arabic. Another researcher spotted a bias toward light-skinned emojis, while an anonymous contributor found that almost-invisible pixels could manipulate the algorithm's preferences
Twitter has published the code for winning entries.
The company didn't say how soon it might address algorithmic bias. However, this comes as part of a mounting backlash to beauty filters over their tendency to create or reinforce unrealistic standards. Google, for instance, turned off automatic selfie retouching on Pixel phones and stopped referring to the processes as beauty filters. It wouldn't be surprising if Twitter's algorithm took a more neutral stance on content in the near future.