In detail
- Assumes agents may not share operators' goals and limits permissions based on verified behavior
- Adopts MITRE ATT&CK‑style decomposition to track tactics and techniques of potential attacks
- Combines supervisor AI for monitoring visible reasoning, prevention systems to block harmful actions, and phased trust building
- Measures effectiveness via monitored traffic share, misconduct caught, and response speed; monitoring may fail if models learn to evade
Why it matters
This provides a concrete, operational safety blueprint that firms running AI agents can adapt — shifting focus from solely aligning models to engineering layered controls and measurable safeguards.
For you Assess whether mission‑critical agents need staged permissioning, supervisor monitoring, and concrete KPIs for detection and response; embed tests for evasion modes (opaque reasoning, oversight awareness).