Randomness as a Control for Alignment

2 perryspector 0 8/12/2025, 2:59:28 AM
Main Concept:

Randomness is one way one might wield a superintelligent AI with control.

There may be no container humans can design that it can’t understand its way past, with this being what might be a promising exception—applicable in guiding a superintelligent AI that is not yet omniscient/operating at orders of magnitude far surpassing current models.

Utilizing the ignorance of an advanced system via randomness worked into its guiding code in order to cement an impulse while utilizing a system’s own superintelligence in furthering the aims of that impulse, as it guides itself towards alignment, can be a potentially helpful ideological construct within safety efforts.

[Continued]:

Only a system that understands, or can engage with, all the universe’s data can predict true randomness. If prediction of randomness can only be had through vast capabilities not yet accessed by a lower-level superintelligent system that can guide itself toward alignment, then including it as a guardrail to allow for initial correct trajectory can be crucial. It can be that we cannot control superintelligent AI, but we can control how it controls itself.

Method Considerations in Utilizing Randomness:

Randomness sources can include hardware RNGs and environmental entropy.

Integration vectors can include randomness incorporated within the aspects of the system’s code that offer a definition and maintenance of its alignment impulse and an architecture that can allow for the AI to include (as part of how it aligns itself) intentional movement from knowledge or areas of understanding that could threaten this impulse.

The design objective can be to prevent a system’s movement away from alignment objectives without impairing clarity, if possible.

Randomness Within the Self Alignment of an Early-Stage Superintelligent AI:

It can be that current methods planned for aligning superintelligent AI within its deployment are relying on the coaxing of a superintelligent AI towards an ability to align itself, whether researchers know it or not—this particular method of utilizing randomness when correctly done, however, can be extremely unlikely to be surpassed by an initial advanced system and, even while in sync with many other methods that should include a screening for knowledge that would threaten its own impulse towards benevolence/movement towards alignment, can better contribute to the initial trajectory that can determine the entirety of its future expansion.

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