AI is imprecise in that it does not require a predefined relationship between a property and an effect to identify a partial relationship. It can, for example, select highly likely candidates from a larger set of possible candidates. This capability captures one of the vital elements of modern AI. Using machine learning to create and adjust models based on real-world feedback, modern AI can approximate outcomes and analyze ambiguities that would have stymied classical algorithms.