No LLM generated, heavily assisted/co-written, or otherwise reliant work.
Read full explanation
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attention can be safely withdrawn,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 stop defending against it.
A system that requires permanent human vigilance — even if it performs well — has not achieved alignment in any meaningful sense. Its safety depends on continuous external effort rather than intrinsic stability.
3.5 Black-Box Uncertainty and Alignment as a Structural Exchange
Black-box systems inevitably introduce internal uncertainty. The more opaque and unpredictable a system’s internal decision structure is, the higher the baseline psychological noise experienced by those who must rely on it.
As the number of unknown internal factors increases, humans are forced to compensate through vigilance: monitoring, auditing, second-guessing, and defensive control.
At the extreme, a fully transparent and fully predictable system would minimize human psychological noise. However, such a system may also lack the flexibility, abstraction, or capability required for advanced intelligence.
This creates a genuine tension: high-capability systems tend to increase internal opacity, while low-opacity systems may sacrifice performance.
Alignment, therefore, cannot mean eliminating black-box behavior entirely. Instead, it requires a structural exchange:
An aligned AGI must actively reduce alignment-relevant internal uncertainty — through legibility, predictability, and controllability — in order to allow humans to withdraw permanent defensive attention.
If a system does not make this exchange, human supervision cannot relax. Humans will remain fixated on the system’s critical decision points, and collective anxiety will remain structurally elevated.
In this sense, alignment is not merely about correctness of outcomes. It is about whether the system willingly trades internal opacity for human trust, or whether it externalizes uncertainty onto its users indefinitely.
4. Extension to Civilization-Level Knowledge and Technologies
If the previous sections are correct, alignment cannot be evaluated solely at the level of isolated interactions or local task performance. It must generalize to the knowledge and tools an intelligent system produces, and to their long-term effects on human civilization.
Historically, the most valuable forms of human knowledge share a non-accidental property: they systematically and durably reduce baseline human anxiety, both cognitively and physically, by transforming uncertainty into reliable structure.
Foundational theories such as classical mechanics, electromagnetism, and thermodynamics did not merely improve prediction. They allowed humans to withdraw continuous defensive attention from large parts of their environment.
Abstract understanding became embodied stability:
Newtonian mechanics became buildings and bridges that do not require constant fear of collapse.
Electromagnetic theory became communication systems that make separation survivable rather than isolating.
Thermodynamics became heating infrastructure that turns winter from an existential threat into a manageable condition.
Fluid mechanics and structural engineering became flood barriers and coastal defenses that allow entire populations to sleep without permanent vigilance.
The deeper and more general the knowledge, the larger the reduction in ambient uncertainty it enabled. Its value scaled with the degree to which humans could safely stop monitoring, compensating, and defending.
If AGI is genuinely aligned, the same pattern must hold. An aligned system — and the theories, tools, and infrastructures it produces — should enable long-term reductions in human defensive cognitive load at a societal scale.
Conversely, if an advanced system continuously generates capabilities that increase dependence while maintaining or amplifying collective anxiety, then alignment has failed at the civilizational level, regardless of performance metrics.
Human anxiety, in this sense, is not an external side effect of intelligence. It is a diagnostic signal that the system has not yet become something humans can safely rely on.
5. Implications for Alignment Research
If alignment is defined partly by whether humans can exit a defensive posture, then alignment research cannot be evaluated solely by behavioral success or robustness under testing.
Any alignment approach that indefinitely requires humans to remain alert, anxious, or continuously compensating is not converging toward a stable solution — it is merely postponing failure.
This reframes the role of existing work:
Interpretability is not successful unless it enables genuine understanding rather than constant inspection.
Corrigibility is not sufficient unless it allows humans to confidently relinquish supervision.
Value learning is incomplete unless it produces systems that humans can live with without permanent vigilance.
These approaches are not replaced by this criterion, but constrained by it.
6. Limitations and Open Questions
This proposal has clear limitations:
Psychological noise is difficult to quantify.
Humans may misinterpret or project fear.
Systems could potentially simulate legibility without genuine controllability.
Therefore, this condition should be treated as necessary but not sufficient.
However, ignoring it entirely risks building systems that appear aligned while remaining fundamentally destabilizing.
7. Conclusion
I propose a minimal requirement for AGI alignment:
Over time, an aligned system should allow humans to experience reduced uncertainty, reduced vigilance, and increased confidence in control.
At the level of aggregate human experience, this implies a long-term negative trend in defensive psychological noise:
when evaluated over sufficiently long civilizational timescales.
This condition does not require monotonic decrease or the absence of local fluctuations. Temporary increases, shocks, and tolerable oscillations are compatible with alignment.
The inequality above should be understood as a constraint on the long-run direction of evolution, rather than a guarantee about short-term states.
What is incompatible with alignment is a trajectory in which the long-term derivative remains non-negative — that is, where sustained human vigilance and anxiety are structurally required for the system to remain safe.
In this sense, timescales of a few years are insufficient. Alignment must be understood relative to millennial or evolutionary horizons — potentially lasting for as long as the system and its consequences persist.
If this condition cannot be met, then human anxiety is not incidental — it is evidence of misalignment.
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:
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”:
When a problem is genuinely solved, something qualitatively different occurs:
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 stop defending against it.
A system that requires permanent human vigilance — even if it performs well — has not achieved alignment in any meaningful sense.
Its safety depends on continuous external effort rather than intrinsic stability.
3.5 Black-Box Uncertainty and Alignment as a Structural Exchange
Black-box systems inevitably introduce internal uncertainty.
The more opaque and unpredictable a system’s internal decision structure is, the higher the baseline psychological noise experienced by those who must rely on it.
As the number of unknown internal factors increases, humans are forced to compensate through vigilance:
monitoring, auditing, second-guessing, and defensive control.
At the extreme, a fully transparent and fully predictable system would minimize human psychological noise.
However, such a system may also lack the flexibility, abstraction, or capability required for advanced intelligence.
This creates a genuine tension:
high-capability systems tend to increase internal opacity, while low-opacity systems may sacrifice performance.
Alignment, therefore, cannot mean eliminating black-box behavior entirely.
Instead, it requires a structural exchange:
If a system does not make this exchange, human supervision cannot relax.
Humans will remain fixated on the system’s critical decision points, and collective anxiety will remain structurally elevated.
In this sense, alignment is not merely about correctness of outcomes.
It is about whether the system willingly trades internal opacity for human trust, or whether it externalizes uncertainty onto its users indefinitely.
4. Extension to Civilization-Level Knowledge and Technologies
If the previous sections are correct, alignment cannot be evaluated solely at the level of isolated interactions or local task performance.
It must generalize to the knowledge and tools an intelligent system produces, and to their long-term effects on human civilization.
Historically, the most valuable forms of human knowledge share a non-accidental property:
they systematically and durably reduce baseline human anxiety, both cognitively and physically, by transforming uncertainty into reliable structure.
Foundational theories such as classical mechanics, electromagnetism, and thermodynamics did not merely improve prediction.
They allowed humans to withdraw continuous defensive attention from large parts of their environment.
Abstract understanding became embodied stability:
The deeper and more general the knowledge, the larger the reduction in ambient uncertainty it enabled.
Its value scaled with the degree to which humans could safely stop monitoring, compensating, and defending.
If AGI is genuinely aligned, the same pattern must hold.
An aligned system — and the theories, tools, and infrastructures it produces — should enable long-term reductions in human defensive cognitive load at a societal scale.
Conversely, if an advanced system continuously generates capabilities that increase dependence while maintaining or amplifying collective anxiety, then alignment has failed at the civilizational level, regardless of performance metrics.
Human anxiety, in this sense, is not an external side effect of intelligence.
It is a diagnostic signal that the system has not yet become something humans can safely rely on.
5. Implications for Alignment Research
If alignment is defined partly by whether humans can exit a defensive posture, then alignment research cannot be evaluated solely by behavioral success or robustness under testing.
Any alignment approach that indefinitely requires humans to remain alert, anxious, or continuously compensating is not converging toward a stable solution — it is merely postponing failure.
This reframes the role of existing work:
These approaches are not replaced by this criterion, but constrained by it.
6. Limitations and Open Questions
This proposal has clear limitations:
Therefore, this condition should be treated as necessary but not sufficient.
However, ignoring it entirely risks building systems that appear aligned while remaining fundamentally destabilizing.
7. Conclusion
I propose a minimal requirement for AGI alignment:
At the level of aggregate human experience, this implies a long-term negative trend in defensive psychological noise:
d(noise)dt<0\frac{d(\text{noise})}{dt} < 0dtd(noise)<0
when evaluated over sufficiently long civilizational timescales.
This condition does not require monotonic decrease or the absence of local fluctuations.
Temporary increases, shocks, and tolerable oscillations are compatible with alignment.
The inequality above should be understood as a constraint on the long-run direction of evolution, rather than a guarantee about short-term states.
What is incompatible with alignment is a trajectory in which the long-term derivative remains non-negative — that is, where sustained human vigilance and anxiety are structurally required for the system to remain safe.
In this sense, timescales of a few years are insufficient.
Alignment must be understood relative to millennial or evolutionary horizons — potentially lasting for as long as the system and its consequences persist.
If this condition cannot be met, then human anxiety is not incidental — it is evidence of misalignment.