Racism and other biases in artificial intelligence algorithms

According to some prominent voices in the tech world, artificial intelligence presents a looming existential threat to humanity: Warnings by luminaries like Mr Elon Musk and Professor Nick Bostrom about "the singularity" - when machines become smarter than humans - have attracted millions of dollars and spawned a multitude of conferences. But this hand-wringing is a distraction from the very real problems with artificial intelligence today, which may already be exacerbating inequality in the workplace, at home and in our legal and judicial systems. Sexism, racism and other forms of discrimination are being built into the machine-learning algorithms that underlie the technology behind many "intelligent" systems that shape how we are categorised and advertised to. Take a small example from last year: Users discovered that Google's photo app, which applies automatic labels to pictures in digital photo albums, was classifying images of black people as gorillas. Google apologised; it was unintentional. But similar errors have emerged in Nikon's camera software, which misread images of Asian people as blinking, and in Hewlett-Packard's Web camera software, which had difficulty recognising people with dark skin tones.