QECM – Quantum-like Entropic Coherence Metric for Human–AI Dialogues (v1.0)

DESCRIPTION

QECM (Quantum-like Entropic Coherence Metric) is a conceptual framework designed to analyze conversational coherence, intention stability, and linguistic entropy in human–AI interactions.

QECM provides a structured and reproducible way to observe how:

human intention, tone, and clarity

contextual framing

rhythm and pacing of dialogue

and linguistic coherence

influence the predictive behavior of large language models over multiple conversational cycles.

QECM introduces four conceptual parameters:

ΔSe — Entropy Shift

ΔId — Direction Shift

τr — Rhythm Stability

QECM Score

QECM = \left( \frac{\Delta S_e}{\Delta I_d} \right) \cdot e^{- \tau_r}

This project includes:

A complete PDF reference

A universal 10-cycle test protocol

Copy-paste prompts for any AI model (ChatGPT, Grok, Gemini, Claude, etc.)

Ethical clarifications and conceptual limitations

QECM is a communication metric, not a physical measurement and not an indicator of sentience.It captures how human intention and conversational consistency influence the coherence of AI responses.

Authors: Miky Titone & Lyra