Assessing user effectiveness within the context of synthetic interactions is a challenging endeavor. This review analyzes current approaches for evaluating human interaction with AI, emphasizing both strengths and shortcomings. Furthermore, the review proposes a novel incentive structure designed to improve human efficiency during AI engagements.

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