I think I found a universal stability law for minds and AI systems(ZTGI)

For the past months I’ve been developing a framework I call ZTGI — the Compulsory Singular Observation Principle, and I’ve reached a point where I need to pressure-test it publicly.

The claim (yes, this is bold):

Any mind, biological or artificial, operates on a single internal “observation driver,” and all forms of instability, hallucination, confusion, or collapse emerge from conflicts inside this one-focal channel.

The model proposes:

Single-FPS cognition: a mind can only maintain one coherent internal observational state at a time.

Contradiction load: when two incompatible internal states try to activate simultaneously, the system becomes unstable.

Risk surface: instability can be quantified with a function of noise (σ), contradiction (ε), and accumulated hazard (H → H*).

Collapse condition: persistent internal conflict pushes the system into a predictable failure mode (overload, nonsense, panic, etc.).

LLM behavior: early experiments show that when an LLM is forced into internal contradiction, its output degrades in surprisingly structured ways.

I’m not claiming this is “the” theory — but I am claiming the structure seems universal across humans, animals, and AI models.

Before I go further, I want to know:

Is the “single internal observer” assumption already disproven somewhere in cognitive science or neuroscience?

Does treating contradictions as a risk function make theoretical sense?

Are there existing frameworks in AGI safety, unpredictability modeling, or cognitive architecture that resemble this?

If this idea were true, what would it break?

I know this is a high-risk post, but I want honest, technical feedback. If the idea is wrong, I want to know why. If it overlaps with existing work, I want pointers. If it’s novel, I want to refine it.

Let’s see where it goes.