The team behind machine learning systems take steps to avoid problematic biases by instructing reviewers to have a bias towards scientific consensus and demonstration of expertise while sending the same dataset to multiple people from diverse backgrounds. However, unfair biases can still creep into these systems if the training data itself is biased, so they work hard to remove and reduce them in the algorithms.