Conceptual Normative Framework: 1–6 Layer Reflexivity Framework (Ver0.1)

Contemporary human–AI interaction systems increasingly incorporate reflection, explanation, and metacognitive features. However, prevailing approaches often assume that deeper reflection, more comprehensive self-analysis, or stronger optimization are inherently beneficial. This assumption overlooks the cognitive costs these processes may impose—particularly under sustained load—such as fatigue, instability, and escalating interpretive pressure. This paper proposes a layered normative operational framework for human–AI interaction. The framework is built upon an operational ontology that defines layers as boundaries of operational legitimacy rather than psychological states or developmental stages. Each layer specifies which forms of cognition, interpretation, or meta-editing are permissible under given conditions of system load, fatigue, and risk. The framework emphasizes default non-escalation, explicit consent for cross-layer transitions, load-aware pacing, and the preservation of users’ naming and interpretive authority. These constraints treat reflection not as an inherently beneficial process, but as an operation that carries situational cost and risk. By redefining reflection as a conditionally constrained operation rather than a universally applicable process, the model offers an alternative to optimization-driven or depth-seeking interaction paradigms. It provides a safety-oriented interpretive ontology for designing human–AI interaction systems that remain usable, respectful, and sustainable under real-world cognitive constraints.