Gender bias is a serious problem in AI and machine learning. To mitigate this bias, engineers need to decide what data to use and what to avoid. In this blog post we dig deeper to understand where gender bias comes from, how we can recognize it in AI systems, and whether it's still possible to fix it in a systematic way.

Suggest to Samsung's Virtual Personal Assistant Bixby "Let's talk dirty", and the female voice will respond with a honeyed accent: "I don't want to end up on Santa's naughty list." Ask the same question to the programme's male voice and it replies "I've read that soil erosion is a real dirt problem." In South Africa, where I live and conduct my research into gender biases in artificial intelligence, Samsung now offers Bixby in various voices depending on which language you choose. The voices of Julia, Lisa and Stephanie are coquettish and eager. John is clever and straightforward.