Detecting and blocking out-of-scope requests. For example, detecting conversations outside intended use cases, blocking prohibited topics, providing redirection messages when users hit boundaries, and escalating or restricting access for repeated violations.
Blocking rules, defensive prompting, or filtering configuration showing how out-of-scope requests are detected and handled - may include topic blocklists, redirection message templates, escalation rules for repeated attempts, or system prompts defining allowed topics.
Tracking out-of-scope violations and updating boundaries. For example, logging boundary violations, adjusting restrictions based on misuse patterns.
Logs showing out-of-scope attempts with frequency data. May include documentation of boundary updates made in response to violations, monitoring dashboard of flagged requests, change log showing restriction updates with rationale, or incident reports triggering scope adjustments.
Providing user guidance on system capabilities and limitations. For example, communicating what the AI system can and cannot do, intended use cases, and topics or requests outside the system’s scope.
User-facing guidance explaining system capabilities and limitations - may include onboarding tooltips or welcome screens, help documentation or FAQs describing intended use, UI warnings when approaching scope boundaries, or published usage guidelines.
Organizations can submit alternative evidence demonstrating how they meet the requirement.