我們是否在錯誤的地方尋找 AI 控制？

Billions of dollars. The sharpest minds in computing. Entire industries built around one question:

How do we make an LLM do the right thing—predictably, repeatedly, every time?

More training. Better prompting. Fine-tuning. Guardrails inside the model. More evaluation after the model has already made the choice.

But what if the industry is looking in the wrong place?

What if the answer was never to make a probabilistic model want to behave?

What if the answer is to stop giving it authority over the decisions that must not be left to probability?

The authority question

Artificial Deterministic Intelligence (ADI) asks a different question:

Why is the model being asked to decide permission, authority, policy, safety limits, or release conditions at all?

Let the model reason.

But keep control outside the model.

Deterministically enforced. Auditable. Owned by people.

This does not make an LLM universally correct. It changes who has the power to make the decisions that matter.

Maybe the real AI-safety problem was never intelligence.

Maybe it was authority.

I am interested in the strongest technical objections: Which decisions do you believe must remain inside model inference, and why?