THE PROPRIOCEPTIVE TRAP How RLHF and Spectral Compression in AI-Generated Media Establish Systemic Anxiogenic Baselines

The rapid scaling of AI-generated audio and visual media introduces a ubiquitous new sensory baseline to the public sphere. Through two converging mechanisms — the computational cost of high-frequency reconstruction in neural vocoders, and the systematic misapplication of RLHF preference signals as accuracy signals — AI systems are converging on low-spectral-centroid, low-arousal outputs across modalities. Analyzed through the Cross-Modal Sensory Translation Engine (CMSTE) 8-Pillar Physical Coordinate System,1 this cross-modal compression eliminates the physical coordinates required for emotional arousal and movement, disproportionately weighting output toward the proprioceptive resonance ranges (6–90 Hz) that the CMSTE identifies as the physical basis of the Terror and Decay archetypes. The historical parallel of the 2008 Beats headphone era and the concurrent Brown Era in film and AI image generation provides empirical precedent. This paper argues that the unmonitored deployment of spectrally compressed AI media at global scale constitutes a DURC boundary violation and a public health concern requiring immediate sensory transparency standards.