A Blockchain-Based Framework for AI Ethics Compliance in Autonomous Systems
DOI:
https://doi.org/10.63345/Keywords:
AI ethics, blockchain, smart contracts, autonomous systems, accountability, auditability, Hyperledger FabricAbstract
Autonomous systems make safety-relevant decisions without continuous human supervision. Ethical principles for such systems are widely published but rarely enforced in a way that outside parties can verify. This paper presents a blockchain-based framework that encodes five ethics requirements (safety, fairness, privacy, transparency, and human oversight) as smart contracts. The contracts check decision records submitted by autonomous agents and store tamper-evident compliance evidence on a permissioned ledger. We implemented the framework on Hyperledger Fabric with four organizations and evaluated it on 120,000 decision events from 60 simulated autonomous agents, including 2,400 deliberately injected violations. The framework detected 2,306 of the 2,400 violations (recall 96.1%, precision 94.4%, F1-score 0.952), compared with an F1-score of 0.890 for a centralized rule-engine baseline and 0.182 for sampled manual auditing. It detected all 1,000 log-tampering attempts, sustained 1,740 transactions per second (TPS), and added a median of 3.1 ms to the agents’ control loop. Incident reconstruction time fell from 38.5 minutes to 4.2 minutes compared with centralized logging. The results indicate that ledger-based enforcement can make ethics compliance auditable at a practical performance cost.
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