Model
Model
D1
An AI model is a core component that uses inputs to make inferences and produce outputs.
Review status: 2027-02-23
Technical explanation
As a core system component, a model is used to make inferences from inputs to produce outputs.
Conceptual boundaries
A model is a component, while an AI system also includes its operational context and other components; it is not automatically a faithful representation of the real world.
Provider-neutral example
A demand-forecasting model can turn recent sales and calendar inputs into a predicted quantity for a planner to inspect.
Limitations
A model’s usefulness depends on its intended use and validation; a model can be inaccurate for a real-world setting.
Related concepts
Atomic claims and evidence
1.1OECD, Explanatory Memorandum on the Updated OECD Definition of an AI System
- Source
- OECD, Explanatory Memorandum on the Updated OECD Definition of an AI System
- Source role
- Authoritative source
- Exact locator
- Building AI systems and models, AI model paragraph, p. 7
- Supported claim
- An AI model is a core component of an AI system used to make inferences from inputs to produce outputs.
- Last verification
- Review due
- Scope limitation
- This usage is specific to the OECD explanatory framing and does not make a model a complete AI system.
2.1NIST SP 1500-18r2, NIST Research Data Framework Version 2.0
- Source
- NIST SP 1500-18r2, NIST Research Data Framework Version 2.0
- Source role
- Authoritative source
- Exact locator
- Process/Analyze: Validation and verification, p. 23
- Supported claim
- Model validation determines the degree to which a model accurately represents the real world from the perspective of intended uses.
- Last verification
- Review due
- Scope limitation
- Validation is use-dependent and does not establish accuracy for every context.