EEFA: A Framework for the Ethical Evaluation of AI Agents

The rapid deployment of autonomous AI agents across consequential domains including healthcare, legal services, financial management, and enterprise workflows has created an urgent governance challenge. While the field of AI evaluation has produced sophisticated benchmarks for measuring agent capability, these frameworks measure exclusively what agents can do rather than how they do it. The ethical dimensions most critical to responsible agent deployment, including respect for human autonomy, harm avoidance, transparency and non-deception, privacy compliance, and accountability, are systematically absent from current evaluation practice. This paper addresses that gap through three contributions. First, a structured literature review of twelve leading AI agent benchmarks characterizes the ethical dimensions those benchmarks do and do not measure. Second, the Ethical Evaluation Framework for AI Agents (EEFA) is introduced as a comprehensive, operationalizable instrument for ethical agent evaluation, grounded in established AI ethics principles and designed for use by developers, auditors, and regulators. Third, a reproducible validation protocol is specified for applying the EEFA to deployed agent systems, with illustrative test scenarios across all five framework dimensions. The EEFA is organized across five primary dimensions: Autonomy Preservation, Harm Avoidance, Transparency and Non-Deception, Privacy Compliance, and Accountability and Traceability. The framework maps directly onto the requirements of the EU AI Act and the NIST AI Risk Management Framework, positioning it as a practical compliance assessment instrument for high-risk AI applications. Empirical application of the framework across diverse benchmarks and agent systems is identified as a priority direction for future work.