Evaluating trustworthy AI agents in real-world systems requires measuring multiple dimensions beyond task performance—including physical safety, fairness, and auditability—and building in transparent oversight mechanisms that log all interventions.
SolarChain-Eval is a benchmark for testing AI agents in decentralized energy markets, measuring both how well they perform economically and whether they behave safely and fairly. It uses physics rules to prevent agents from exploiting invalid data, and includes an AI auditor that reviews risky decisions.