This report draws together the findings and recommendations from a broad range of work. We have focused on the use of algorithms in significant decisions about individuals, looking across four sectors (recruitment, financial services, policing and local government), and making cross-cutting recommendations that aim to help build the right systems so that algorithms improve, rather than worsen, decision-making.
Financial companies are increasingly using complex algorithms to make decisions regarding loans or insurance - algorithms that look for patterns in data which are associated with risks of default or high insurance claims. This raises risks of bias and discrimination …
Recent reports suggest 9 out of 10 people are biased against women in some way. We wanted to mark International Women’s Day this year by talking about bias in a world of data-driven technology and artificial intelligence, and our forthcoming report on bias in algorithmic decision-making.