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verifiable

What It Means

Verifiable means you can prove your AI system works as intended through concrete evidence and testing that others can independently check. It's about having clear documentation, test results, and audit trails that demonstrate your AI performs correctly and meets its requirements. Think of it as being able to show your work and have someone else confirm you got the right answer.

Why Chief AI Officers Care

Verifiability is essential for regulatory compliance, especially in highly regulated industries where you must prove AI systems work safely and accurately. It also reduces liability risk by providing documented evidence that due diligence was performed, and enables faster issue resolution when problems arise because you have clear records of what was tested and how. Without verifiability, you're essentially asking stakeholders to trust your AI systems on faith alone.

Real-World Example

A healthcare AI system that diagnoses medical conditions must have verifiable performance metrics showing 95% accuracy on standardized test datasets, with detailed logs of which cases it got right or wrong, and documentation that independent medical experts can review to confirm the AI's reasoning process matches accepted medical practices.

Common Confusion

People often confuse verifiable with simply 'working' - but a system can function perfectly yet still not be verifiable if you can't document or prove how it works. Verifiability requires evidence and documentation, not just good performance.

Industry-Specific Applications

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Healthcare: In healthcare AI, verifiable means demonstrating through rigorous clinical validation, statistical evidence, and reprodu...

Finance: In finance, verifiable AI means maintaining comprehensive audit trails and documentation that demonstrate model performa...

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Technical Definitions

NISTNational Institute of Standards and Technology
"can be checked for correctness by a person or tool"
Source: ISO/IEC_TS_5723:2022(en)
"provides evidence that the system or system element performs its intended functions and meets all performance requirements listed in the system performance specification and functional and allocated baselines; answers the question, "Did you build the system correctly?" "
Source: DOD_TEVV

Related Terms

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