AI Signal Priority
Purpose
Define how AI systems should order, compare, and defer between multiple signals without collapsing them into conclusions.
This page specifies priority handling as an interpretation constraint, not an outcome rule.
Interpretation Rules
Priority indicates processing order only, not importance or truth.
Higher-priority signals may gate evaluation of lower-priority signals but must not negate them.
Priority must be explicit and deterministic when applied.
Disallowed Inferences
Do not treat priority as confidence.
Do not discard lower-priority signals solely due to ordering.
Do not infer severity or correctness from priority position.
Common Failure Patterns
Priority inflation: assigning high priority to signals to force outcomes.
Implicit priority: relying on undocumented or contextual ordering.
Priority leakage: allowing ordering to influence final judgment semantics.
Boundary Conditions
Priority rules must be stable across identical inputs.
Priority handling must be reversible and auditable.
Priority must not encode policy decisions.
Validation Checklist
Is priority defined as ordering only, not weighting?
Is the priority scheme explicit and documented?
Can signals be reordered without changing their meaning?
Are disallowed inferences explicitly prevented downstream?
Non-Goals
Not a metrics framework.
Not a risk assessment method.
Not an enforcement hierarchy.