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evaluation

What It Means

Evaluation is the systematic process of measuring how well something performs against predetermined standards or goals. In AI contexts, it means testing and assessing whether AI systems, processes, or outcomes meet the specific criteria you've set for success, safety, or compliance.

Why Chief AI Officers Care

CAIOs need robust evaluation frameworks to demonstrate AI system performance to executives, satisfy regulatory requirements, and identify potential risks before they impact the business. Without proper evaluation, organizations cannot prove their AI investments are delivering value or meeting safety standards, which creates liability exposure and undermines stakeholder confidence.

Real-World Example

A bank's CAIO implements evaluation protocols for their loan approval AI system by testing it monthly against criteria like accuracy rates above 95%, bias detection across demographic groups, and compliance with fair lending regulations. When evaluation reveals the system's accuracy dropped to 92% due to changing economic conditions, they can quickly retrain the model before it impacts loan decisions.

Common Confusion

People often confuse evaluation with simple performance monitoring, but evaluation requires predetermined criteria and systematic assessment methodology. It's not just watching dashboards - it's deliberately measuring against specific standards you've established upfront.

Industry-Specific Applications

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Healthcare: In healthcare AI, evaluation involves systematically assessing AI models against clinical effectiveness metrics, patient...

Finance: In finance, evaluation involves systematically assessing AI models against regulatory requirements like SR 11-7 for mode...

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Technical Definitions

NISTNational Institute of Standards and Technology
"(1) systematic determination of the extent to which an entity meets its specified criteria; (2) action that assesses the value of something"
Source: aime_measruement_2022, citing ISO/IEC 24765

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