system card
**A system card** is a comprehensive documentation artifact that describes an AI system's **capabilities, limitations, intended uses, safety evaluations, and ethical considerations**. It serves as the primary transparency mechanism through which AI developers communicate how their system works, how it was tested, and how it should (and should not) be used.
**What a System Card Includes**
- **Model Overview**: Architecture, training data summary, parameter count, training compute, and key design decisions.
- **Intended Use Cases**: What the system is designed to do, target users, and expected deployment contexts.
- **Out-of-Scope Uses**: Explicitly listed use cases the system is **not** designed for and should **not** be used for.
- **Performance Metrics**: Benchmark results across relevant tasks, disaggregated by demographic groups where appropriate.
- **Safety Evaluations**: Results of red-teaming, adversarial testing, bias audits, toxicity evaluations, and jailbreak resistance testing.
- **Limitations and Risks**: Known failure modes, biases, hallucination rates, and contexts where the system performs poorly.
- **Mitigation Strategies**: What safety measures were implemented (RLHF, content filtering, guardrails) and their effectiveness.
- **Data Practices**: High-level description of training data sources, filtering, and any personal data considerations.
**Notable Examples**
- **GPT-4 System Card**: Published by OpenAI alongside the technical report, documenting extensive red-teaming and safety evaluations.
- **Claude Model Card**: Anthropic's documentation of Constitutional AI training and safety characteristics.
- **Gemini Technical Report**: Google DeepMind's documentation of capabilities and safety testing.
**Why System Cards Matter**
- **Regulatory Compliance**: The **EU AI Act** requires comprehensive documentation for high-risk AI systems.
- **User Trust**: Transparent documentation helps users make informed decisions about using AI systems.
- **Accountability**: Creates a public record of known risks and mitigation efforts.
System cards have become a **standard industry practice** for responsible AI deployment, evolving from the earlier concept of **model cards** proposed by Mitchell et al. (2019).