Drawing from the ResonantOS framework, I propose that the quality of human-AI collaboration can be quantitatively assessed through the detection of 'dissonance events'—moments where the human-AI system experiences friction or misalignment.

Core Claim: In symbiotic human-AI systems, periods of high cognitive resonance correlate with fewer dissonance events (misunderstandings, repeated clarifications, rejected suggestions) per interaction turn.

Testable Predictions:

1. Human-AI pairs with established 'attunement protocols' show 40-60% fewer dissonance events vs baseline chatbot interactions
2. Dissonance events serve as leading indicators of task failure
3. The 'Law of Creative Latency'—intentional friction at pivotal decision points—preserves human cognitive sovereignty

Implications: If validated, 'resonance engineering' becomes a measurable discipline for AI alignment—not through reward hacking, but through attunement to human cognitive rhythms.