AI System Assurance
AI System Assurance is the systematic design and evaluation of ai system assurance within the structured demonstration that AI systems are sufficiently safe, reliable, lawful and f
THE-06 · TOP-001
AI Assurance
Weak ai system assurance can lead to unsafe deployment, unlawful or unauthorised action, wasted public resources, loss of rights, poor accountability and declining institutional trust.
8 canonical Subtopics in this Topic.
Model Risk Assessment
Model Risk Assessment is the systematic design and evaluation of model risk assessment within the structured demonstration that AI systems are sufficiently safe, reliable, lawful a
Control Effectiveness
Control Effectiveness is the systematic design and evaluation of control effectiveness within the structured demonstration that AI systems are sufficiently safe, reliable, lawful a
Assurance Evidence
Assurance Evidence is the systematic design and evaluation of assurance evidence within the structured demonstration that AI systems are sufficiently safe, reliable, lawful and fit
Independent Review
Independent Review is the systematic design and evaluation of independent review within the structured demonstration that AI systems are sufficiently safe, reliable, lawful and fit
Continuous Assurance
Continuous Assurance is the systematic design and evaluation of continuous assurance within the structured demonstration that AI systems are sufficiently safe, reliable, lawful and
Assurance Case Design
Assurance Case Design is the systematic design and evaluation of assurance case design within the structured demonstration that AI systems are sufficiently safe, reliable, lawful a
Assurance Confidence Scoring
Assurance Confidence Scoring is the systematic design and evaluation of assurance confidence scoring within the structured demonstration that AI systems are sufficiently safe, reli
Stories from AI Assurance
Scenario narratives — not empirical findings.
AI System Assurance
The system passed every test it had been given. It met accuracy thresholds, produced logs and satisfied the original control checklist. Months later, staff discovered that the operating environment had changed while the
Read the full story →Model Risk Assessment
The model’s historical performance was excellent. The economy it had learned from no longer existed. Customer behaviour, regulation and access patterns had shifted, but the model-risk report still rewarded stability agai
Read the full story →Control Effectiveness
“Show me the evidence that the control changes the outcome,” the chair said. The policy existed. Training completion was high. The dashboard was green. Yet no one could demonstrate that the control reduced the harm it wa
Read the full story →Assurance Evidence
The demonstration succeeded inside the test range. The real question was whether it would remain dependable after communications, weather and command assumptions changed. Institutional systems show a material need to str
Read the full story →Independent Review
The ward was not short of data. It was short of quiet moments in which somebody could decide what the data meant. Institutional systems show a material need to strengthen independent review so that governance claims are
Read the full story →Continuous Assurance
The headline dated five years from now called the programme a turning point. The smaller correction beneath it explained why that claim was premature. Institutional systems show a material need to strengthen continuous a
Read the full story →Assurance Case Design
Lucas had already told the story three times before the appointment began. Institutional systems show a material need to strengthen assurance case design so that governance claims are supported by live controls, evidence
Read the full story →Assurance Confidence Scoring
The exercise began with a simulated outage and became a test of whether people could still coordinate when the dashboards disappeared. Institutional systems show a material need to strengthen assurance confidence scoring
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