Examples
Worked examples
- Is an instance
A frontier-model deployment safety case structured in GSN with claims about capability evaluation, misuse safeguards, and monitoring.
- Is an instance
A medical-AI safety case integrating with the device's overall regulatory safety case.
Counter-examples
Looks similar, but isn't
- Not an instance
A model card alone.
- Not an instance
A marketing claim of safety without structured argument or evidence.
Editorial commentary
An AI safety case is a structured, evidence-based argument that a specific AI system is acceptably safe to deploy in a defined context, modelled directly on safety cases from established high-consequence engineering disciplines — nuclear power, civil aviation, medical devices — where a documented, auditable argument, not just a test pass/fail result, is the standard way of establishing that a system is fit to operate.
Structure
A safety case typically states an explicit top-level safety claim, decomposes it into sub-claims, and supports each sub-claim with evidence (test results, formal analysis, operational history, red-teaming findings) — often represented using Goal Structuring Notation (GSN), a diagrammatic argument notation adapted from the nuclear and aviation sectors. The point of the structure is to make the argument’s assumptions and gaps visible and reviewable, not to produce a single pass/fail score.
How this differs from a model audit or a system card
A model audit is typically retrospective and criteria-checking (did the model meet defined thresholds?); a safety case is prospective and argument-based (here is why we believe this system is safe to deploy, and here is the evidence). A system card discloses what was found; a safety case argues why the findings support a deployment decision. Red-teaming results are typically one input into a safety case’s evidence base, not a substitute for the case itself.
Why it matters
Safety cases are increasingly requested by government AI safety institutes and referenced in frontier labs’ own voluntary deployment commitments for their most capable systems; the practice is new enough in AI that no single template is yet standard across organisations.
References
- See also: Red-teaming, System card, AI assurance.
Also known as
AI safety case argument
Machine-readable encodings
Use in your systems
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