Assessing user performance within the context of synthetic interactions is a multifaceted endeavor. This review analyzes current methodologies for assessing human interaction with AI, emphasizing both advantages and limitations. Furthermore, the review proposes a novel reward system designed to improve human productivity during AI interactions.

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