For example, an algorithm such as COMPAS might purport to predict the chance of future criminal activity, but it can only rely on measurable proxies, such as being arrested.

But even the smartest algorithms can sometimes behave in unexpected and unwanted ways—for example, picking up gender bias from the text or images they are fed.

Another example of clustering algorithms in use is recommender systems, which group together users with similar viewing, browsing, or shopping patterns to recommend similar content.