A structured method for quantifying the degree of agreement and disagreement across multiple AI agents after they independently analyze the same decision. Rather than forcing agents to a single answer, consensus scoring maps clusters of agreement, points of genuine conflict, and the confidence levels behind each stance.
A structured method for quantifying the degree of agreement and disagreement across multiple AI agents after they independently analyze the same decision. Rather than forcing agents to a single answer, consensus scoring maps clusters of agreement, points of genuine conflict, and the confidence levels behind each stance.
High consensus with high confidence is a strong signal. Low consensus with high confidence indicates a genuine strategic fork that needs empirical validation.
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