On Human Defensive States, Black-Box Uncertainty, and Alignment as a Trust Exchange

Abstract

This post does not propose a new training method, safety technique, or alignment algorithm.
Instead, it proposes a necessary condition for AGI alignment that is currently implicit, but rarely examined directly.

I argue that an aligned AGI must systematically reduce — rather than permanently sustain — human defensive cognitive states when humans interact with, understand, and deploy it.
Crucially, this reduction must be sustained over long time horizons.
If a system’s existence forces humans to remain in a state of persistent uncertainty, vigilance, and lack of control, then alignment has not been achieved, regardless of performance or capability.

1. The Problem We Are Quietly Avoiding

Much of current alignment research focuses on external behavior:
reward design, oversight, interpretability, corrigibility, and evaluation benchmarks.

Implicitly, many approaches rely on the assumption that if a system behaves correctly under sufficient testing and monitoring, alignment is progressing.

However, this assumption overlooks a crucial dimension:

Whether humans can ever exit a permanent defensive posture toward the system.

By defensive posture, I mean a state characterized by persistent uncertainty, the need for continuous monitoring, and the inability to confidently delegate control without anxiety.
This is not merely emotional discomfort; it is a sustained cognitive load associated with perceived loss of predictability and control.

2. Psychological Noise as a First-Person Signal

When humans confront an unsolved problem, they typically experience high internal “noise”:

uncertainty about outcomes,
lack of clear boundaries,
concern about hidden failure modes,
continuous attention and monitoring.

When a problem is genuinely solved, something qualitatively different occurs:

internal degrees of freedom collapse,
the system becomes predictable,
attention can be safely withdrawn,
cognitive load decreases.

This transition is often abrupt and unmistakable.
I propose that this noise-reduction trajectory, from unstable uncertainty to stable predictability, is a fundamental signal of genuine resolution.

3. Why This Is Not a UX or Trust Issue

This claim is often misunderstood as a matter of user comfort or interface quality.
It is neither.

The issue is not whether humans like the system, but whether they can safely st...

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