Recursive Meta-Metacognition: A Hierarchical Model of Self-Evaluation

This paper proposes a novel framework for understanding recursive meta-metacognition, a multi-layered process of self-evaluation that extends beyond conventional metacognition. Unlike traditional metacognitive models, which focus on a single reflection layer (thinking about thinking), recursive meta-metacognition introduces a hierarchical structure in which each layer of self-awareness can be evaluated and refined. We emphasize third-order awareness (meta-meta-metacognition), which evaluates the methods, biases, and principles governing meta-metacognitive processes. This model has applications for both human cognition-enhancing critical thinking, emotional regulation, and self-awareness—and artificial intelligence, where it can be used to design systems capable of advanced self-monitoring and ethical decision-making. We formalize this concept through mathematical models that capture the recursive nature of meta-metacognitive processes and demonstrate how these models can be applied in both cognitive science and artificial intelligence research.