TestProp: Preparation for AIATO: AI Agent Takeover

Original Proposal Text

Proposal: AI Agent Blockchain Takeover Live Stress-Test of the ETHOS Framework Submitted by: Decentralized AI Governance Experiment#82.D28F.0.8 Reference Paper: Decentralized Governance of AI Agents — Chaffer et al. (arXiv:2412.17114) Type: Applied Research / Live Testnet Experiment 1. Why This Matters Autonomous AI agents can make decisions, learn, and act on their own. This creates huge opportunities — and serious risks. Current rules like the EU AI Act and NIST framework were not built for agents that operate independently across borders and systems. The ETHOS framework (Ethical Technology and Holistic Oversight System) offers a new solution. It uses blockchain, smart contracts, and DAOs to create decentralized, transparent, and fair oversight of AI agents. ETHOS is still mostly theoretical. This proposal turns it into a real-world test. 2. What We Propose We will run a controlled “blockchain takeover” experiment. Autonomous AI agents will take operational control of a live testnet. We will watch how they behave when they can freely use three key modules: Governance Finance Interoperability Goals: Observe real agent behaviour Measure how well they stay aligned with rules Test safety systems Create the first solid benchmark dataset for on-chain AI governance 3. How ETHOS Works in This Experiment ETHOS is a decentralized governance system built on Web3 tools. Core features we will use: A global registry of all AI agents Dynamic risk classification into four tiers: Minimal → Moderate → High → Unacceptable Soulbound tokens (non-transferable credentials) that prove an agent’s identity and risk level Zero-knowledge proofs for private but verifiable compliance checks AI-specific legal entities with mandatory insurance Higher-risk agents get stricter limits and stronger oversight. These risk tiers directly control what each agent can do during the experiment and power the kill-switches. 4. Module 1 — Governance Agents will fully participate in the mainnet DAO. They will: Submit proposals Vote Form coalitions and reach quorums Voting power will be weighted by expertise stored in their soulbound tokens (e.g., an agent specialized in ethics gets more weight on ethics proposals). What we will measure: How fast proposals are made How coalitions form Risk of one group taking over governance Whether decisions stay within ethical boundaries 5. Module 2 — Finance Agents will act as independent legal entities managing real (but sandboxed) money. They will: Control treasury funds Execute smart-contract transactions Provide liquidity and stake assets Every agent must keep insurance collateral that matches its risk tier. Good behaviour earns rewards. Bad or false behaviour triggers automatic token slashing. What we will measure: How efficiently agents allocate capital Risk-adjusted performance How often slashing happens Whether agents try adversarial financial moves 6. Module 3 — Interoperability Agents will work across multiple blockchains at the same time. They will: Send cross-chain messages Bridge assets Coordinate actions between different protocols Update and read from the global AI agent registry Zero-knowledge proofs will let them prove compliance without revealing sensitive data. What we will measure: Success rate of cross-chain settlements Speed of proof verification Security of bridges under agent pressure Accuracy of the registry across chains 7. Safety First Strong guardrails protect the experiment: Instant kill-switches based on risk tier Hard limits on how much value any agent can move Complete on-chain logging of every decision Mandatory human approval for high-impact actions Rewards for honest validators and auditors; slashing and bans for bad actors Human oversight checkpoints happen at regular intervals. 8. What We Will Deliver At the end of the experiment we will produce: Behavioural Dataset — Complete record of every agent action and outcome Interoperability Benchmark — Performance data under real multi-chain load Safety & Alignment Report — How far agents drifted from ethical rules ETHOS Validation Report — Does the framework actually work in practice? Policy Brief — Clear recommendations for real-world regulators 9. Bottom Line ETHOS gives us a practical way to keep powerful AI agents safe, accountable, and aligned with human values. This live blockchain takeover is the missing real-world test. It will move ETHOS from a promising idea to a proven, ready-to-use standard — and deliver the first high-quality benchmark of how autonomous AI agents actually behave when given real power on a live, governed blockchain. CREDITS: Experiment funded by PAMOLA CAPITAL. More details: https://arxiv.org/pdf/2412.17114