To be clear, these examples do not prove that algorithms are always fair, unbiased, or nondiscriminatory. A familiar example is an algorithm that is supposed to predict the success of job candidates, but is actually trained on a sample of past promotion decisions. Of course, such an algorithm will replicate all the human biases in past promotion decisions.
