Robustness
The ability of an AI model to maintain performance and correct behaviour when faced with noisy, corrupted, adversarial or otherwise challenging inputs and conditions.
In plain language
How tough an AI is in challenging conditions. A robust AI still works well with noisy data, unusual inputs or slightly different conditions; it doesn't break at the first sign of trouble.
Why this matters
Robustness is a fundamental governance requirement. AI systems that break under pressure or unusual conditions create operational and safety risks. Your governance standards should define robustness testing requirements proportionate to the risk level of each application.
Relevance
GovernanceRobustness testing must be mandated proportionate to application risk, with acceptance thresholds defined and testing methodology documented as part of model approval processes.
Related terms
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