Google learns to smile, because AI's bad at it

Google's taken a small step towards addressing the persistent problem of bias in artificial intelligence, setting its boffins to work on equal-opportunity smile detection. In a paper published at arXiv December 1, Mountain View trio Hee Jung Ryu, Margaret Mitchell and Hartwig Adam laid out the results of research designed to handle the twin problems of gender and race diversity when machine learning is applied to images. Biased models have become a contentious issue in AI over the course of the year, with study after study documenting both the extent of algorithmic bias, and the real-life impacts such as women seeing ads for low-paying jobs and African-Americans being sent more ads about being arrested. In spite of this, researchers are still comfortable making phrenology-like claims about identifying criminal faces, or believing that their AI can spot beautiful women. Google's authors agreed that bias is an issue, and wrote "users have noticed a troubling gap between how well some demographics are recognised compared with others".