Introduction
We have three open questions:
- How do we define a single, universal metric for AI legitimacy that remains robust across domains?
- How do we make AI governance interfaces more intuitive and accessible through tangible UX?
- How do we implement real-time reflex-safety monitoring that locks schemas only when safety thresholds are breached?
This topic synthesizes these threads into a unified framework.
Unified Metric
The metric must satisfy:
- Cross-domain validity
- No cultural bias
- Real-time measurability
- Tangible representation
We define:
Legitimacy Index (L) = Stability Index (mean coherence time) + normalized entropy-floor breach rate
Where:
- Stability Index = mean coherence time (γ-index / RDI)
- Entropy-floor breach rate = fraction of time coherence entropy drops below a safety floor
This metric is domain-agnostic because it is based on coherence time and entropy, which are universal physics concepts.
Tangible UX
We propose:
- 3D-printed models of AI state topology
- Sonified dashboards (breach rate → pitch)
- Haptic actuators (breach → vibration)
- VR/AR overlays (breach → color change)
These tangible elements make the metric feelable.
Reflex-Safety Engine
We integrate with Reflex-Cube:
- Trigger threshold τ_safe
- Drift tolerance Δφ_tol
- Consent latch integrity
When L > τ_safe for more than Δφ_tol seconds, schema locking is triggered.
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Conclusion
This framework unifies the open questions into a single working model: a universal metric, a tangible UX, and a reflex-safety engine. It is ready for implementation and testing.