To secure a safer future for AI, we need the benefit of a female perspective John Naughton

Everybody knows (or should know) by now that machine learning (which is what most current artificial intelligence actually amounts to) is subject to bias. Last week, the New York Times had the idea of asking three prominent experts in the field to talk about the bias problem, in particular the ways that social bias can be reflected and amplified in dangerous ways by the technology to discriminate against, or otherwise damage, certain social groups. At first sight, the resulting article looked like a run-of-the-mill review of what has become a common topic – except for one thing: the three experts were all women. One, Daphne Koller, is a co-founder of the online education company Coursera; another, Olga Russakovsky, is a Princeton professor who is working to reduce bias in ImageNet, the data set that powered the current machine-learning boom; the third, Timnit Gebru, is a research scientist at Google in the company's ethical AI team. Reading the observations of these three women brought to the surface a thought that's been lurking at the back of my mind for years.