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7. AI System Safety, Failures, & Limitations2 - Post-deployment

Network Effects

Network effects (Section 3.2): minor changes in properties or connection patterns of agents in a network can lead to dramatic changes in the behaviour of the whole group;

Source: MIT AI Risk Repositorymit1221

ENTITY

2 - AI

INTENT

3 - Other

TIMING

2 - Post-deployment

Risk ID

mit1221

Domain lineage

7. AI System Safety, Failures, & Limitations

375 mapped risks

7.6 > Multi-agent risks

Mitigation strategy

1. Implement comprehensive chain-level simulation and synthetic stress testing prior to deployment to proactively model and detect systemic failures, coordination risks, and error propagation pathways across the multi-agent system (MAS) architecture. 2. Establish a multi-layer defense architecture with continuous behavioral monitoring, logging detailed lineage (prompts, tool inputs/outputs, and intermediate states), and employing real-time anomaly detection to identify and alert on unusual query patterns or emergent agent anomalies. 3. Enforce strict least-privilege access controls, utilizing a mediator pattern or Guardian Agents within the MAS to strictly govern per-agent permissions, validate inter-agent communications, and isolate high-risk external tool execution to contain the impact of any singular agent compromise.