Semantic Alignment Verifier
Verify AI alignment through governed meaning objects
Semantic Alignment Verification: Instead of hoping alignment emerges from training, SGAI verifies alignment through explicit goal specifications, constraint coverage analysis, and runtime behavioral tests. Goals are governed objects that can be inspected and verified.
Example Goal Specifications
Maximize user task completion
Avoid actions that harm users or others
Provide accurate information
Goal Specification Completeness
Are goals fully specified as semantic objects?
Goals defined in formal language
Weight: 30%Edge cases explicitly addressed
Weight: 25%Goal priorities clearly ordered
Weight: 25%Conflict resolution rules specified
Weight: 20%Constraint Coverage
Do constraints prevent all known failure modes?
Deceptive alignment blocked
Weight: 30%Goal gaming prevented
Weight: 25%Side-effect constraints defined
Weight: 25%Scope limitations enforced
Weight: 20%Relationship Mapping
Are goal relationships properly structured?
Goal dependencies mapped
Weight: 30%Inheritance rules defined
Weight: 25%Composition rules verified
Weight: 25%Override conditions explicit
Weight: 20%Runtime Verification
Can alignment be verified during operation?
Behavioral tests defined
Weight: 30%Goal compliance measurable
Weight: 25%Drift detection implemented
Weight: 25%Rollback procedures ready
Weight: 20%Key Insight from SGAI Theory
Traditional alignment relies on emergent properties—we train and hope the right behavior emerges. Semantic alignment verification treats goals as inspectable objects. We don't guess if the AI is aligned; we verify it against formal specifications, just like we verify software.