Governance: The KINETIQ DAO

The governance system of KINETIQ AI operates through a progressively decentralized model steered by the Kinetiq DAO. Token-weighted proposals are evaluated using a hybrid of quadratic voting and contribution scoring, designed to prevent plutocratic control.

Key Governance Responsibilities:

• Agent Category Whitelisting: Control over which types of AI agents can operate across public infrastructure zones

• Reward Curve Optimization: Adjusting yield multipliers and incentives based on supply/demand of robotic labor and compute

• Validator Threshold Tuning: Governance over minimum requirements for robotic and compute node onboarding, ensuring quality-of-service

• Treasury Allocations: Grant funding to developers, academic researchers, and robotic hardware startups contributing to protocol growth

Governance Innovations:

• Dynamic Batching: Multi-vote aggregation across epochs for smoother proposal execution

• Behavioral Attestations: Inclusion of R-PoWH (Robotic Proof-of-Work History) as on-chain evidence of useful labor for proposal submission and voting weight

• Agent Audit Committees: Community-curated intelligence groups that validate agent safety, ethics, and function through ZK behavioral proofs

Over time, the Kinetiq DAO evolves into a true global council of robotic infrastructure stewards—optimizing the efficiency, ethics, and economics of the machine economy.