Tech leaders are becoming accustomed to thinking of diversity as an essential resource for developing long-term competitive advantage. The current debates around machine learning and artificial intelligence being trained on dodgy data were long predated by important discussions regarding algorithmic bias in machine learning models, and the difficulty of noticing UX decisions that might unintentionally exclude large groups of people if there’s no one to represent them on your team.

Anyone involved in tech and design should be familiar by now with the common problems of unconscious bias. Recruitment algorithms that favour men, automated judicial assistants that display racial bias, even car seat belts are designed for the male anatomy and not the female one.