metric
What It Means
A metric is a standardized way to measure and score something specific about your AI systems or processes. It defines both what you're measuring and how you calculate the score, creating a consistent ruler that everyone can use to track performance, quality, or other important characteristics.
Why Chief AI Officers Care
Metrics are essential for proving AI system performance to executives, regulators, and auditors because they provide objective, repeatable measurements. Without standardized metrics, you can't demonstrate compliance, compare vendor solutions, track improvement over time, or make data-driven decisions about AI investments and risk management.
Real-World Example
An AI lending system uses an 'accuracy metric' that measures what percentage of loan default predictions were correct over the past quarter, calculated as (correct predictions ÷ total predictions) à 100, giving a score like 87% that can be tracked monthly and compared against regulatory requirements.
Common Confusion
People often confuse metrics with simple measurements or KPIs, but metrics specifically require both a defined calculation method and a standardized scale, making them reproducible and comparable across different teams, time periods, or systems.
Industry-Specific Applications
See how this term applies to healthcare, finance, manufacturing, government, tech, and insurance.
Healthcare: In healthcare AI, metrics must align with clinical outcomes and patient safety standards while meeting regulatory requir...
Finance: In finance, metrics for AI systems must align with regulatory requirements like model risk management under SR 11-7, fai...
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Includes:
- 6 industry-specific applications
- Relevant regulations by sector
- Real compliance scenarios
- Implementation guidance
Technical Definitions
NISTNational Institute of Standards and Technology
"defined measurement method and measurement scale"Source: ISO/IEC_TS_5723:2022(en)
"(1) quantitative measure of the degree to which a system, component, or process possesses a given attribute; (2) defined measurement method and the measurement scale; c.f., measure in this section above"Source: aime_measurement_2022, citing ISO/IEC 24765
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