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Containment, isolation, and control mechanisms for system execution.
Also in Non-Model
Stage: Containment and Mitigation; Stakeholder: AI Developers; Additional information: AI developers should prepare containment measures that are rapid and flexible. In the event of a LOC event, safety should take priority over service continuity. Effective containment may require immediate measures, including model shutdown, that make it harder for a rogue AI to take actions. Plans should be adaptable, as specific response depends on the context where the model is deployed, its level of access and its capabilities. Communication lines to external infrastructure and service providers who could take action to limit proliferation should be established.
Reasoning
Shutdown measures control model execution and runtime behavior through termination mechanisms.
Monitor critical capability levels
2.2.2 Testing & EvaluationIdentify early warning signs and emergent capabilities
2.2.1 Risk AssessmentEstablish standardised benchmarks and reporting
3.2.1 Benchmarks & EvaluationImplement compute monitoring and anomaly detection
1.2.3 Monitoring & DetectionEnhance hardware and supply chain oversight
2.3.3 Monitoring & LoggingLead efforts to establish shared criteria for AI LOC
3.2.2 Technical StandardsStrengthening Emergency Preparedness and Response for AI Loss of Control Incidents
Somani, Elika; Friedman, Anjay; Wu, Henry; Lu, Marianne; Byrd, Christopher; van Soest, Henri; Zakaria, Sana (2025)
As artificial intelligence (AI) systems become increasingly embedded in essential infrastructure and services, the risks associated with unintended failures rise. Developing comprehensive emergency response protocols could help mitigate these significant risks. This report focuses on understanding and addressing AI loss of control (LOC) scenarios where human oversight fails to adequately constrain an autonomous, general-purpose AI.
Other (multiple stages)
Applies across multiple lifecycle stages
Developer
Entity that creates, trains, or modifies the AI system
Manage
Prioritising, responding to, and mitigating AI risks
