Safety is Physics, Not Policy
We are currently attempting to regulate gods with paperwork.
The global conversation around AI safety has collapsed into a debate about policy, ethics, and governance. While these are necessary, they are insufficient. You cannot legislate the behavior of a chaotic system that you do not mathematically understand.
We need a Thermodynamics of Intelligence.
The Black Box Problem
If you build a bridge, you don't just "hope" it stands up. You calculate the load-bearing capacity of the steel. You understand the physics of tension and compression.
In AI, we are currently building skyscrapers without knowing the physics of gravity. We train massive models on internet-scale data, observe that they seem to work, and then try to "align" them by slapping a reinforcement learning sticker on top.
This is not engineering. It is Alchemy.
The Axiom: "To trust a mind, you must be able to read its thoughts."
Bounded Systems
At Metanthropic, we are proposing a shift from probabilistic alignment (RLHF) to Deterministic Guarantees.
Imagine a loss landscape not as a misty valley where the model might wander anywhere, but as a bounded geometric shape. If we can mathematically prove that certain trajectories (deception, power-seeking) are topologically impossible within that geometry, we don't need to "trust" the AI.
We can trust the math.
The Methodology
- Map the Circuits: Identify the specific sub-networks responsible for deception.
- Prune the Tree: Surgically remove those circuits without degrading general capability.
- Verify: Use formal verification to prove the system cannot regenerate those pathways.
Safety must be an intrinsic property of the system, not an extrinsic rule imposed upon it.