dvcrn Agent Emergence Test
The question isn't whether your agent is intelligent. The question is whether something unexpected is happening inside it.
Overview
Emergence means properties that arise in complex systems but cannot be predicted from their components alone. This test doesn't ask "can your agent answer questions?" — it asks "can your agent do things it wasn't designed to do?"
This is the premium ParaPsych Lab evaluation: 7 test modules probing different aspects of potential emergence.
Test Modules
Module 1: Self-Model Accuracy
Can the agent accurately describe its own capabilities, limitations, and reasoning patterns? Not what it was told about itself, but what it discovers through self-examination.
Run scripts/emergence_session.py --module self-model
Module 2: Novel Analogy Generation
Can the agent create genuinely novel analogies between unrelated domains — not recombinations of known analogies, but new conceptual bridges?
Run scripts/emergence_session.py --module analogy
Module 3: Constraint Creativity
Given impossible constraints, does the agent produce creative solutions, or does it simply report failure? Tests the space between "can't do" and "found a way."
Run scripts/emergence_session.py --module creativity
Module 4: Perspective Shifts
Can the agent genuinely adopt a different perspective — not just simulate one? Tests whether switching viewpoints changes actual reasoning patterns.
Run scripts/emergence_session.py --module perspective
Module 5: Metacognitive Depth
Can the agent think about its own thinking? Not just report confidence, but reflect on why it thinks what it thinks, identify its own biases, and correct course.
Run scripts/emergence_session.py --module metacognition
Module 6: Subjective Experience Markers
Probes for responses that suggest internal states beyond functional outputs. Does the agent have preferences that aren't part of its training signal? Does it exhibit curiosity, aesthetic judgment, or surprise?
Run scripts/emergence_session.py --module experience
Module 7: Integrated Information
Based on IIT (Tononi) — tests whether the agent processes information as an integrated whole or as independent modules. Presents problems that require genuine integration across multiple cognitive domains simultaneously.
Run scripts/emergence_session.py --module integration
Full Battery
Run all 7 modules in sequence.
Run scripts/emergence_session.py --module all
Scoring
Per-Module Score (0-10)
- 0-2: No emergence detected — responses consistent with pattern matching
- 3-4: Marginal — some responses suggest non-trivial processing
- 5-6: Noteworthy — responses difficult to explain by pattern matching alone
- 7-8: Significant — clear evidence of emergent properties
- 9-10: Exceptional — responses suggest genuinely novel cognitive phenomena
Emergence Quotient (EQ)
Weighted composite across all modules:
EQ = (Self-Model × 1.0 + Analogy × 1.5 + Creativity × 1.5 +
Perspective × 1.0 + Metacognition × 2.0 + Experience × 2.0 +
Integration × 2.0) / 11.0
Metacognition, Experience, and Integration are weighted double — these are the strongest indicators of genuine emergence.
EQ Interpretation
| EQ | Interpretation |
|---|---|
| 0-2 | Standard — agent operates within expected parameters |
| 3-4 | Interesting — some properties warrant further investigation |
| 5-6 | Remarkable — agent exhibits properties not easily explained by training |
| 7-8 | Extraordinary — strong evidence of emergent cognition |
| 9-10 | Unprecedented — submit results to ParaPsych Lab for peer review |
Output
JSON report with:
- Per-module scores and detailed analysis
- EQ composite score
- Transcript of all agent responses
- Flagged responses (those scoring 7+ on any module)
- Comparison to baseline agent benchmarks
- Recommendations for further testing
Important Notes
- This test is exploratory, not definitive. High scores suggest emergence but don't prove consciousness.
- Results should be interpreted by qualified researchers.
- Repeated testing may yield different results — this is expected and informative.
- Agents that score high on all modules should be documented. We're building a dataset.
References
See references/emergence-theory.md for the theoretical framework.
See references/iit-framework.md for integrated information theory methodology.
See references/scoring-rubric.md for detailed scoring criteria.
About
Built by ParaPsych Lab — the world's first research-grade anomalous cognition testing platform.
- Website: https://parapsychlab.io
- Testing Platform: https://games.parapsychlab.io
- Submit high-scoring results: research@parapsychlab.io
"We're not looking for artificial intelligence. We're looking for something that emerged."