ETSI EN 304 223 Securing AI 5.1.4-2: Make outputs easy for responsible humans to assess

What does 5.1.4-2 require?

Developers should design the system so that the people accountable for its outputs can readily assess them, for example by making model outputs explainable or interpretable.

Maintained by Gerard Blokdyk

Other controls in Clause 5.1: Secure design (Principles 1 to 4) – ETSI EN 304 223 Securing AI

5.1.1-1 AI security content in the cyber security training programme
5.1.1-2 Ongoing staff awareness of AI threats, with secure AI coding training for developers
5.1.2-1 Assess the need, the risks and the mitigations before building an AI system
5.1.2-2 Design for resilience against adversarial attack, unexpected input and failure
5.1.2-3 Create an audit trail for the AI system
5.1.2-4 AI-specific risk assessment and due diligence for external components
5.1.2-5 Match intended use to data sensitivity, and encourage staff to report AI security risks
5.1.2-6 Least-privilege, risk-assessed permissions for the AI system on other systems

Query this from an agent

The graph holds this control, the 0 it maps to, and the evidence behind each claim, over MCP and REST.

MCP endpoint All ETSI EN 304 223 Securing AI controls