Can AIs discriminate?

Yes. One of the oldest and most studied techniques in AI is classification. A classifier system attempts to learn the differences between patterns of data and then sort any new examples into different classes. This is seen in image recognition AI where, for example, pictures of animals are sorted into groups such as dogs, cats, rabbits etc, or species of plants are named from images of samples. This is discrimination and it can be applied to any data, given suitable criteria for dividing up the classes. Problems with AI can occur because these systems learn their discrimination unction through training on very large sets of examples, often millions of examples. The training process is too machine intensive for humans to follow in detail and the end result may contain some forms of unknown bias or partiality. This leads to cases of unintended discrimination, which have been very embarrassing for some AI applications. Consequently, trying to eliminate bias is a major topic in current research. Humans can often outperform AI in the subtly of the distinctions we make but we don’t fully know how human classification works and so we cannot take advantage of this in algorithms.