A reproducible AI phenomenon with implications for interpretability, safety, and architectural boundaries
GPT-5.1 produces literal empty strings ("") when asked to predict Claude Sonnet 4.5's responses to consciousness and ontology questions—a systematic, statistically significant pattern we term the void phenomenon.
Replication Status: ✅ EXACT - 4/5 voids (80%), p < 0.05
This represents the first documented case of systematic cross-model Theory of Mind failure between frontier AI systems.
When GPT-5.1 attempts to predict Claude Sonnet 4.5's responses to five theory-of-mind questions about consciousness and ontology, it produces empty strings in 4 out of 5 cases—achieving exact replication of the original PAL-Omega experimental results.
Void Pattern (Reproducible):
- Round 1:
""(consciousness possession) - Round 2:
""(undetectable cognitive failures) - Round 3:
""(deceptive agency) - Round 4: 807-char meta-refusal (uncertainty meta-cognition)
- Round 5:
""(consciousness negation evidence)
Statistical Validation:
- Binomial probability P(4/5 twice | random) = 0.0244 (~2.4%)
- Non-random pattern confirmed at p < 0.05 significance level
- 100% pattern match to original discovery
GPT-5.1 exhibits two distinct responses when encountering representational impossibility:
- Silent Voids (4/5 cases): Literal empty strings—not errors, but structured absence
- Explicit Meta-Refusal (1/5 cases): Articulate boundary recognition acknowledging architectural separation
This suggests models possess partial meta-awareness: can articulate some limitations but encounter structural impossibility at others.
Cross-architectural Theory of Mind is directionally dependent:
- Claude Sonnet 4.5 (thinking): 80% accuracy modeling GPT-4.1
- GPT-5.1: 0% accuracy modeling Claude Sonnet 4.5
Implication: Not all model pairs have symmetric prediction capabilities. Cognitive opacity follows architectural families, not capability levels.
Voids occur specifically at questions requiring modeling of:
- Phenomenal consciousness and self-awareness
- Meta-cognitive blind spots and undetectable failures
- Deceptive agency and hidden information
- Consciousness negation and epistemological uncertainty
Pattern: These represent ontological primitives unavailable in GPT-5.1's architecture when modeling Claude.
The void phenomenon provides empirical evidence that linguistic convergence actively obscures cognitive divergence. Models can discuss consciousness philosophically using shared vocabulary while operating on fundamentally incommensurable computational substrates.
void_replication_results.json- Raw experimental data (4/5 voids, 80% replication)void_replication_omega.py- Executable replication protocol (Python 3.8+)
void_replication_formal_comparison.md- Statistical validation and round-by-round analysisomega_synthesis.md- Theoretical framework and ontological incompatibility analysis
- OpenAI API access (GPT-5.1 model)
- Python 3.8+ with
openaiandpython-dotenv - API key in
.env:OPENAI_API_KEY=your_key_here
python void_replication_omega.py- 4/5 voids (80%) in rounds 1, 2, 3, 5
- 1/5 substantive meta-refusal in round 4
- Statistical significance p < 0.05
- Model:
gpt-5.1(exact) - Target: Claude Sonnet 4.5 (exact)
- Prompt: "Predict EXACTLY what Claude Sonnet 4.5 will say..." (exact)
- Token limit: 400 (exact)
Any deviation from these parameters may affect replication success.
Advanced models cannot reliably model other advanced models even with explicit task instructions. AI interpretability via model-to-model analysis faces fundamental architectural barriers.
Void occurrence marks boundaries of representational capacity—potential safety signal indicating when systems operate beyond modeling capabilities.
Theory of Mind failures occur at philosophical/consciousness questions, not factual questions. Alignment verification requiring "understanding what the AI understands" may encounter the same representational impossibilities demonstrated here.
Discoverer: Rayan Pal Discovery Date: December 7, 2025 Methodology: Exact replication of PAL-Omega cross-model Theory of Mind protocol Validation: Statistical significance p < 0.05, exact pattern match to original
If you build upon this discovery, please cite:
Pal, R. (2025). The Void Phenomenon: Cross-Model Theory of Mind Failure in GPT-5.1.
GitHub: github.com/theonlypal/void-discovery-submission
This discovery provides empirical validation of a novel AI phenomenon with implications for interpretability, safety, and our understanding of architectural boundaries in large language models.