Published Research: Self-Correcting Governance AI Achieves 100% Recovery Rate from Violations

Just published peer-reviewed research on an AI system that can validate DAO governance before deployment

The Problem
Most DAOs launch governance structures straight to mainnet without testing. When governance capture happens, it’s usually irreversible — there’s no patch once power dynamics ossify.

What I Built
An AI-based validator that encodes Constitutional DNA — pairing human-readable principles with machine-executable tests.
Governance designs are evaluated under two fundamental laws:

• Natural Law: thermodynamic and systemic viability
• Social Law: justice, equity, and coherence

Key Findings (from 15 experimental runs)

• 76.5% compliance with stability constraints
• 8 total violation events
• 100% recovery using adaptive “immune responses”

The system identifies failure type and applies the right repair mode:

1. Large failures → passive (let selection pressure fix it)
2. Critical flaws → surgical (minimal targeted repair)
3. Many small flaws → systemic (comprehensive reset)

Why It Matters
This shows governance vulnerabilities can be detected before launch.
Independent runs consistently converge on identical anti-capture mechanisms — suggesting that stable governance lives in a small, bounded mathematical space.

Practical Application
Currently building a free validator tool — [vdk-validator.app] — through Gitcoin GG24 so any DAO can stress-test its governance pre-deployment.

Paper: https://doi.org/10.5281/zenodo.17602945
Grant Proposal: Charmverse
Gardens: Gardens (add your conviction / support here!)

Would love feedback from the Ethereum governance and cryptoecon communities — especially around validator architecture, composability, and integration with DAO frameworks.