MIT AI Risk Repository · Risk Sub-Category · 63.05.01

Error propagation

Category: Network Effects

Description

"Error Propagation. One well-known issue with communication networks is that information can be corrupted as it propagates through the network.24 As AI systems become capable of generating and processing more and more kinds of information, AI agents could end up ‘polluting the epistemic commons’ (Huang & Siddarth, 2023; Kay et al., 2024) of both other agents (Ju et al., 2024) and humans (see Case Study 7 and Section 3.1) Another increasingly important framework is the use of individual AI agents as part of teams and scaffolded chains of delegation, which transmit not only information but instr

From Multi-Agent Risks from Advanced AI (Hammond2025), as extracted by the MIT AI Risk Repository (CC BY 4.0).

Classification

Causal entity
AI

Subdomain definition: Risks from multi-agent interactions, due to incentives (which can lead to conflict or collusion) and/or the structure of multi-agent systems, which can create cascading failures, selection pressures, new security vulnerabilities, and a lack of shared information and trust.

How other frameworks describe this risk

Other entries from Hammond2025