Cognitive Sovereignty Self-Audit for Aerospace and Defence
This audit measures whether your organisation retains the engineering judgement needed to catch failure modes that AI systems cannot see. In aerospace and defence, atrophied expertise becomes a safety liability the moment AI training data fails to cover reality.
After every AI-assisted design or analysis is completed, assign an engineer who had no role in the AI work to identify three failure modes the AI might have missed. Use this as your leading indicator of skill atrophy.
Require that any engineer who can approve a safety-critical decision must be able to explain the physics and mathematics of the failure mode being addressed without referencing the AI tool.
Run an annual 'black start' exercise. Take a safety-critical system analysis and rebuild it manually from first principles without AI assistance. Compare to the AI version and document what each method caught.
When you hire or train new engineers, ensure they spend at least twelve months learning how to analyse failure modes manually before they are expected to use AI optimisation tools effectively.
In your certification submissions, identify exactly which claims are based on AI analysis and which are based on independent human assessment. Regulators need this distinction to evaluate accountability.