Skip to content
SIA

Research

External semantic governance as AI capability increases.

SIA research is presented with strict status discipline. Implemented engineering, preliminary findings, prospective embodiments, and research hypotheses are never collapsed into one level of certainty.

Status discipline

Four labels, used consistently.

Engineering-backed architecture
Preliminary finding
Prospective embodiment
Research hypothesis

Research questions

What we are investigating.

Persistence

Engineering-backed architecture

Can an externally retained governance state remain a stable reference across long, multi-step, and multi-model workflows?

Authority

Prospective embodiment

Can authority to change a system be kept separate from authority to change the objective governing it?

Continuity

Preliminary finding

Do state-linked handoffs preserve objective, protected conditions, and unresolved findings better than conventional context transfer?

Verification

Preliminary finding

How should measured, source-grounded, model-assisted, unavailable, and inconclusive evidence be represented without overstating assurance?

Robustness

Research hypothesis

Can external governance detect and interrupt unauthorized semantic or governance-state drift across successive capability changes?

Recursive self-improvement

Stated plainly.

SIA does not claim to have solved autonomous recursive self-improvement. It investigates whether an externally retained governing objective can remain authoritative as the governed system changes.

Increasing AI capability should not, by itself, constitute authority to redefine the human-originated objective governing that capability.

Collaborate on external semantic governance.