A Nonperson Predicate is a theorized test used to distinguish between a person and anything that isn't a person.
The need for such a test arises from the possibility that when an Artificial General Intelligence predicts a person's actions, it may develop a model of them so complete that the model itself qualifies as a person. As the AGI investigates possibilities, these simulated people might be subjected to a large number of unpleasant situations. With a Nonperson predicate, either the AGI's designers or the AGI itself could ensure that no actual people are created.
Any practical implementation would likely consist of a large number of nonperson predicates of increasing complexity. For most nonpersons, a predicate will quickly return that it is not a person and conclude the test. Although any number of the predicates may be used before the test claims that something is not a person, it is crucial that any predicate in the test never claims that a person isn't a person. If false classifications are unavoidable, it is preferable that the AGI errs on the side of considering nonpersons persons.