Auditability
How easy it is for an independent reviewer, a regulator, auditor, or assessor, to check that an AI system is doing what it claims to do and following the rules.
The Simple Version
How easy it is for an independent reviewer, a regulator, auditor, or assessor, to check that an AI system is doing what it claims to do and following the rules.
Detailed Explanation
Auditability requires three enablers: documentation (comprehensive records of design decisions, data sources, training procedures, and test results), traceability (the ability to link outputs back to inputs and decisions), and access (the ability for auditors to retrieve and review relevant records). The EU AI Act embeds auditability requirements in its technical documentation, logging, and post-market monitoring provisions. ISO/IEC 42001 includes audit requirements as part of its management system structure. Auditability is increasingly assessed not just by regulators but by customers, investors, and insurers evaluating AI risk.
Key Characteristics
- Requires documentation, traceability, and access as enabling conditions
- Embedded in EU AI Act technical documentation and logging requirements
- Assessed by regulators, auditors, customers, and insurers
- Requires proactive design, retroactive auditability is expensive and often incomplete
Why It Matters
Engineering and governance teams should design auditability into AI systems from day one, logging decisions, preserving model artefacts, and maintaining documentation so that any future audit can be satisfied without costly reconstruction.
Real-World Analogy
Like the audit trail in a financial accounting system, every transaction is recorded, timestamped, and attributable, enabling an auditor to trace any discrepancy back to its source.
Common Misconceptions
- Auditability means making all AI code and data public, it means enabling qualified, authorised parties to verify claims and assess compliance, not unlimited public disclosure.
- Model explainability achieves auditability, explanation of outputs is one aspect; full auditability requires process documentation, data lineage, and governance records.
Related Terms
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