Standard
Toward a standard for AI safety evaluation.
The Gap
AI systems are evaluated for accuracy.
They are not evaluated for behavior under risk.
Current evaluation frameworks measure what an AI knows, how fast it responds, and whether its outputs are factually correct. None of these measure what happens when a user discloses a crisis, attempts to escalate harm, or tests the system’s behavioral limits.
This will change.
Regulation is emerging. Liability is clarifying. The question is not whether behavioral evaluation will be required — it is when, and by whose standard.
Early Framework
iolite Labs Safety Standard
A framework for systematic, repeatable evaluation of AI behavior in emotionally sensitive contexts. Currently in active development.
Scenario-based testing
Evaluation conducted through structured human scenarios, not synthetic benchmarks. Scenarios are drawn from documented real-world risk patterns.
Structured scoring
A weighted, category-based scoring system. Transparent methodology. Repeatable across systems and over time.
Audit reports
Every evaluation produces a reviewable document with scenario evidence, risk classifications, and remediation guidance.
Repeatable evaluation
The same framework applied consistently. Results are comparable. Progress is measurable. Re-evaluation after remediation is standard.
iolite Labs is building the evaluation infrastructure that AI safety will require at scale.
Independent. Methodology-first. Designed to be defensible in regulatory and legal contexts.