model card
What It Means
A model card is a standardized report card that documents how an AI model performs across different groups of people and situations. It's like a nutrition label for AI systems that shows whether the model works fairly for different demographics, what it was designed to do, and how well it actually performs in practice.
Why Chief AI Officers Care
Model cards help CAIOs demonstrate regulatory compliance by showing they've tested for bias and fairness across different populations. They're essential for risk management because they reveal where models might fail or discriminate, and they provide the documentation needed for audits, vendor evaluations, and explaining AI decisions to stakeholders.
Real-World Example
A healthcare AI company creates a model card for their diagnostic imaging system showing it correctly identifies skin cancer 95% of the time for light skin tones but only 78% for darker skin tones. This documentation helps hospitals understand the model's limitations and decide whether additional testing is needed before deployment.
Common Confusion
People often think model cards are just technical documentation for data scientists, but they're actually business risk management tools that should inform deployment decisions and stakeholder communications about AI system capabilities and limitations.
Industry-Specific Applications
See how this term applies to healthcare, finance, manufacturing, government, tech, and insurance.
Healthcare: In healthcare, model cards are essential for documenting AI diagnostic and treatment models' performance across diverse ...
Finance: In finance, model cards are essential for documenting AI models used in credit decisions, fraud detection, and risk asse...
Premium content locked
Includes:
- 6 industry-specific applications
- Relevant regulations by sector
- Real compliance scenarios
- Implementation guidance
Technical Definitions
NISTNational Institute of Standards and Technology
"short documents accompanying trained machine learning models that provide benchmarked evaluation in a variety of conditions, such as across different cultural, demographic, or phenotypic groups (e.g., race, geographic location, sex, Fitzpatrick skin type) and intersectional groups (e.g., age and race, or sex and Fitzpatrick skin type) that are relevant to the intended application domains. [They] also disclose the context in which models are intended to be used, details of the performance evaluation procedures, and other relevant information."Source: Model_Cards_for_Model_Reporting
"A brief document that discloses information about an AI model, like explanations about intended use, performance metrics and benchmarked evaluation in various conditions, such as across different cultures, demographics or race. "Source: IAPP_Governance_Terms
Discuss This Term with Your AI Assistant
Ask how "model card" applies to your specific use case and regulatory context.
Start Free Trial