Data

After my presentation [Bias: Statistical and Significant] , last week at the [REWORK Women in AI in Healthcare Dinner] in London, I was asked if I could write something on the topic aimed at a less technical audience. It’s my hope this article will provide enough of a technical intuition about the causes of biases in algorithms, while offering an accessible take on how we are inadvertently amplifying existing social and cognitive biases through machine learning — and what we can do to stop it. …