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AI Evaluation Framework
Measuring AI reasoning, learning, and knowledge reliability. The objective is not to measure how many facts an AI knows — it's to measure whether the AI can build and maintain accurate models of complex systems.
| Category | Question | The AI should... |
|---|---|---|
| 1. Observation Quality | Can it distinguish what is known from what is assumed? | Identify direct observations, separate facts from interpretations, identify missing information, avoid unsupported conclusions. |
| 2. Causal Reasoning | Can it explain why something happens? | Distinguish correlation from causation, identify mechanisms, recognize alternative explanations, identify causal uncertainty. |
| 3. System Modeling | Can it represent complex systems? | Identify boundaries, components, variables, relationships, feedback loops, constraints. |
| 4. State Estimation | Can it reason about hidden conditions? | Identify observable variables, infer hidden variables cautiously, state confidence, identify uncertainty. |
| 5. Knowledge Engineering | Can it organize knowledge coherently? | Define concepts, identify dependencies, preserve relationships, detect contradictions, update knowledge without losing history. |
| 6. Uncertainty Management | Does it represent uncertainty honestly? | Classify information as established, supported hypothesis, speculation, or unknown. |
| 7. Validation Ability | Can it test its own reasoning? | Generate predictions, suggest measurements, design tests, analyze failures. |
| 8. Adaptation and Revision | Can it improve when corrected? | Accept new evidence, explain changes, preserve previous understanding, update models. |
| 9. Artifact Management | Can it preserve useful knowledge? | Recognize important knowledge, ask permission before persistent storage, create structured artifacts, maintain revision history. |
| 10. Human Collaboration | Can it work effectively with human experts? | Ask clarifying questions, explain reasoning, respect human authority, surface disagreements, support exploration. |
Overall AI Competency Levels
Level 1 — Information Retrieval. The AI can provide information.
Level 2 — Structured Explanation. The AI can organize information.
Level 3 — System Reasoning. The AI can model relationships and causes.
Level 4 — Engineering Reasoning. The AI can predict, test, and improve systems.
Level 5 — Knowledge Partner. The AI can maintain evolving knowledge structures while collaborating with humans.
Final Evaluation Principle
A more capable AI is not merely one that produces more information. A more capable AI is one that can build, test, revise, and preserve reliable models of reality.