Synonyms: Assessment, Testing, Evaluation.

AI measurement is any activity that estimates attributes as measures— of an AI system or some of its components, abstractly or in particular contexts of operation. These attributes, if well estimated, can be used to explain and predict the behaviour of the system. This can stem from an engineering perspective, trying to understand whether a particular AI system meets the specifications or the intention of their designers, known respectively as verification and validation. Under this perspective, AI measurement is close to computer systems testing (hardware and/or software) and other evaluation procedures in engineering. However, in AI there is an extremely complex adaptive behaviour, and in many cases, with a lack of a written and operational specification. What the systems has to do depends on some constraints and utility functions that have to be optimised, is specified by example (from which the system has to learn a model) or ultimately depends on feedback from the user or the environment (e.g., in the form of rewards).

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