Ethics in healthcare AI: how should the industry prepare?

We think of AI as an arbiter of neutrality, but when fed biased data it churns out biased results. At the beginning of 2017, Amazon's machine learning division shuttered an artificial intelligence (AI) project it had been working on for the past three years. A team in its machine learning wing had been building computer programmes designed to review job applicants' resumes, giving them star-ratings from one to five – not unlike the way shoppers can rate products purchased from Amazon online. However, within a year of the project beginning, the company realised its system was biased against female applicants. The software was trained to vet applicants by observing patterns in resumes submitted to the company over a ten-year period, the majority of which – due to the male-dominance of the tech industry – came from men.