Model Components
Model Card
Introduced by Google researchers in 2019, model cards provide a structured summary of an AI model: training data, evaluation metrics by demographic group, intended and out-of-scope uses, ethical considerations, and known limitations. They promote transparency and responsible deployment.
Major AI labs publish model cards for their systems. They are increasingly required by AI governance frameworks and regulations (EU AI Act) and serve as a key reference for practitioners evaluating whether a model is appropriate for a given application.
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Related Terms
Core Concepts
Explainable AI (XAI)
AI systems that provide transparent insights into their decision-making processes.
Techniques & Methods
AI Alignment
The research field and engineering practice of building AI systems that reliably pursue goals humans actually want, remain controllable, and avoid harmful side effects — operationalized through RLHF, Constitutional AI, evaluations, and interpretability.
Techniques & Methods
Evaluation Metrics
Quantitative measures used to assess how well an AI model performs on a task.
Core Concepts
Bias
Preconceived notions in AI models that affect decision-making and fairness.