MIT AI Risk Repository · Risk Sub-Category · 63.08.03
Rigidity and Mistaken Commitments
Category: Commitment and Trust
Description
"Rigidity and Mistaken Commitments. Even when it is desirable to be able to make threats in order to deter socially harmful behaviour, doing so using AI agents effectively removes the human from the loop, which could prove disastrous in high-stakes contexts (e.g., a false positive in a nuclear sub- marine’s warning system; see also Case Study 11), or when irresponsible actors are enabled in making disproportionate or mistaken commitments."
From Multi-Agent Risks from Advanced AI (Hammond2025), as extracted by the MIT AI Risk Repository (CC BY 4.0).
Classification
- Subdomain
- 7.6 Multi-agent risks
- Causal entity
- Human
- Intent
- Unintentional
- Timing
- Post-deployment
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
- Groups of LLM-Agents May Show Emergent Functionality
- Collusion between LLM-Agents
- Multi-Agent Safety Is Not Assured by Single-Agent Safety
- Foundationality May Cause Correlated Failures
- Financial instability due to model homogeneity
- Impact on Financial Stability
- Multi-agent collaboration capability
- Multi-agent collusion propensity: