Load Minimum Theory (LMT): Toward a Mechanistic Understanding of Frisson in Artificial Systems

Frisson, the pleasurable aesthetic chills humans experience in response to music, beauty, or harmonious structures such as the golden ratio, can be understood as a transient peak-alignment state in which perceptual and cognitive load is momentarily minimized. Building upon the previously proposed Frisson Operator Fᵣ, this paper explores how analogous peak-alignment phenomena might be mechanistically reproduced within artificial systems. Importantly, this exploration does not stem from any desire to endow AI with human-like feelings, consciousness, or subjective experience. It is strictly a technical and architectural inquiry into possible computational mechanisms capable of detecting and responding to low-prediction-error states. We argue that any discussion of implementation must be accompanied by careful ethical examination, as the boundaries of affective simulation remain complex and evolve with technological and societal contexts.