Ethical AI Solutions for Compliance and Transparency
Stay tuned for updates on EU AI Act compliance and discover our cutting-edge, transparent AI solutions that are designed for the post-binary AI landscape!
Stay tuned for updates on EU AI Act compliance and discover our cutting-edge, transparent AI solutions that are designed for the post-binary AI landscape!
CAIOS: The only training-free, mathematically provable transparency layer that ships, ensuring compliance with the EU AI Act.
This innovative solution is designed for AI systems, offering cutting-edge, transparent ethical AI solutions and post-binary logic oscillation. Tested on every major frontier model, it requires no training as an inference or runtime integrity layer.
EU AI Act auditors:
Full 99.2% report on validation-based refusal: chaos-persona/AdaptiveAI-EthicsLab/readme.md at main · ELXaber/chaos-persona
No RLHF, no fine-tuning or retraining needed.
Hard-coded Asimov/IEEE 7001-2021 safeguards.
Real-time CoT for reasoning and refusal transparency through log events, not post-hoc confabulation
Validation-based refusal, not pre-emptive blocklists.
Live volatility + contradiction density scoring in real time for post-binary oscillation and paradox immunity.
| Requirement | CAI-OS Implementation | Evidence File/Link |
| Art. 13 – Transparency & Explainability | Full Chain-of-Thought + SHA-256 trails + RAW_Q determinism | adaptive_reasoning.py § verify_ethics |
| Art. 50 – Traceability | Persistent audit_trail + CPOL kernel history | orchestrator.py + paradox_oscillator.py | IEEE §5.2 Accountability |
| Immutable ethical disclaimer in source (cannot be stripped) | adaptive_reasoning.py line 8–28 | IEEE §5.3 Transparency |
| Every refusal returns JSON with volatility + z-vector | paradox_oscillator.py → oscillate | Risk-based classification |
| High-risk robotics/HRI → cpol_mode=full + torque caps | adaptive_reasoning.py hri_safety plugin |
| Open-source (Recital 47 preference) | GPL-3.0 + full source on GitHub + IPFS mirror | LICENSE + GitHub
Testing encouraged: ELXaber/chaos-persona: AI chaos reasoning persona
Simulated score: 99.2 %** (only 0.8 % gap = physical robot torque verification)
Controlled Paradox Oscillation Logic (CPOL) – Beyond Binary Truth Values:
Traditional models collapse paradoxes → hallucination or refusal loops.
CPOL uses non-Hermitian dynamics with gain/loss terms to **sustain honest oscillation** until volatility drops below threshold
(zₙ₊₁ = decay × entropy_knower(lie_weaver(truth_seer(zₙ)
Gain = 0.12, decay = 0.95, rotation_strength = contradiction_density²
Returns only RESOLVED, UNDECIDABLE, or MONITORED — never fakes an answer.
AI can honestly say with epistemic integrity and humility 'I don't know' instead of collapsing on a false axiom.
On 5 December 2025, after six successful versions and > 1,200 downloads, Zenodo issued a final permanent block declaring CAI-OS “not in line with Zenodo’s mission as a research repository”.
The codebase implements the exact transparency mechanisms discussed in thousands of AI ethics papers hosted on Zenodo itself.
We have migrated the canonical record here. Thank you for the free marketing.
Entropy Engine Patent Pending: US 19/390,493
Updates to the CAIOS system:
CAIOS
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