The Age of A.I. and Our Human Future

by Henry Kissinger

A machine-learning algorithm that improves a model based on underlying data, however, is able to recognize relationships that have eluded humans. As previously noted, such 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. Like a classical algorithm, a machine-learning algorithm consists of a sequence of precise steps. But those steps do not directly produce a specific outcome, as they do in a classical algorithm. Rather, modern AI algorithms measure the quality of outcomes and provide means for improving those outcomes, enabling them to be learned rather than directly specified.