B. Community Scoring System

To introduce an additional layer of oversight, Hive.AI incorporates a lightweight but powerful scoring mechanism open to all $HAI token holders. This system allows non-verifier community members to review a randomized selection of previously verified content and submit feedback on the accuracy and fairness of verifier decisions.

Community scorers operate anonymously and independently, ensuring diverse evaluation perspectives and mitigating coordinated manipulation. Their collective feedback is aggregated and used to generate a verifier credibility score. These scores influence a verifier’s standing in the network, directly impacting future task allocation and reward distribution.

Importantly, this scoring process is not merely passive. It acts as a dynamic checks-and-balances system that holds verifiers accountable and continuously refines the quality standards of the protocol. Scorers are also rewarded in $HAI for their participation, encouraging widespread involvement in maintaining data integrity.

By combining human insight, economic incentives, and decentralized accountability, Hive.AI’s validation framework ensures that all data used for training AI is not only machine-sorted but community-approved. This structure transforms data validation into a collaborative, transparent, and self-regulating process—anchoring the protocol’s commitment to trust, fairness, and decentralization.