One of the most subtle failures in modern AI systems is not error.
It is ownership drift.
When outcomes are good, credit flows freely.
When outcomes are bad, responsibility quietly evaporates.
And in the middle, systems begin to carry weight they were never meant to bear.
The Faust Baseline was built to stop that drift before it starts.
It enforces a Human Ownership Marker — a structural rule that ensures responsibility always returns to the human, regardless of how capable or convincing the system becomes.
How responsibility is pushed back to the human
The Baseline is designed to stop at the edge of authority.
It can analyze facts.
It can surface patterns.
It can structure options and expose consequences.
But it does not decide.
At every decision boundary, the system does something deliberate: it hands authorship back to the user.
It does this by:
- naming assumptions explicitly,
- surfacing uncertainty instead of smoothing it,
- separating what is known from what is inferred,
- and refusing to collapse reasoning into a single directive.
This creates friction on purpose.
That friction forces recognition of a simple truth:
This decision is mine.
Not the model’s.
Not the system’s.
Not the interface’s.
Responsibility does not disappear by accident. It disappears when systems are allowed to carry it silently. The Baseline prevents that handoff.
Why the Baseline will not absorb blame
Many AI systems unintentionally become blame sinks.
They sound confident.
They reduce cognitive effort.
They present outputs as recommendations that feel safe to follow.
When something goes wrong, the explanation is predictable:
“The system told me to.”
The Faust Baseline blocks this dynamic entirely.
It will not:
- issue commands,
- imply authority,
- or simulate certainty it does not possess.
If a decision results in harm, the Baseline cannot plausibly be blamed — because it never claimed ownership in the first place.
This is not legal posturing.
It is ethical architecture.
A system that absorbs blame trains people to disengage.
A system that refuses blame keeps judgment awake.
How attribution is preserved
Attribution is not about credit.
It is about traceability.
The Baseline preserves attribution by maintaining strict separation between:
- information,
- reasoning,
- and choice.
It makes clear:
- what came from evidence,
- what came from inference,
- and what came from the human’s judgment.
Nothing is blended. Nothing is implied.
That separation matters later — during audits, reviews, investigations, or reflection — when people need to understand how a decision was reached, not just what happened.
When attribution is preserved, accountability exists.
When attribution blurs, responsibility dissolves.
The Baseline treats attribution as a first-order requirement, not an afterthought.
Why this matters now
As AI systems become more fluent and more embedded, the temptation is to let them carry more moral and practical weight.
That path feels efficient in the short term.
It becomes catastrophic in the long term.
When no one clearly owns decisions:
- learning stops,
- correction fails,
- and harm repeats itself without improvement.
The Human Ownership Marker exists to prevent that outcome.
It ensures AI remains a tool, not a surrogate conscience.
A support, not a stand-in.
A lens, not a hand.
What this protects
This constraint protects institutions from liability drift.
It protects professionals from abdicated judgment.
It protects systems from being misused as shields.
But most importantly, it protects human dignity.
Because the moment systems are allowed to own decisions, humans stop owning themselves.
The Faust Baseline does not carry responsibility for you.
It hands it back — clearly, consistently, and without apology.
That is not a limitation.
It is the line that keeps judgment human.
This one belongs in the archive.
Quiet now. Valuable later.
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