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AI Risk

Miscoordination

"Miscoordination arises when agents, despite a mutual and clear objective, cannot align their behaviours to achieve this objective. Unlike the case of differing objectives, in common-interest settings there is a more easily well-defined notion of ‘optimal’ behaviour and we describe agents as miscoordinating to the extent that they fall short of this optimum. Note that for common-interest settings it is not suffici...

AI Risk7. AI System Safety, Failures, & Limitations7.6 > Multi-agent risks2 - Post-deployment

Record summary

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Techniques0Attack methods connected to this risk.
Mitigations0Defenses that may help with related attacks.
Domain7. AI System Safety, Failures, & LimitationsThe broad risk area this belongs to.

Risk profile

How this risk is described and categorized.

"Miscoordination arises when agents, despite a mutual and clear objective, cannot align their behaviours to achieve this objective. Unlike the case of differing objectives, in common-interest settings there is a more easily well-defined notion of ‘optimal’ behaviour and we describe agents as miscoordinating to the extent that they fall short of this optimum. Note that for common-interest settings it is not sufficient for agents’ objectives to be the same in the sense of being symmetric (e.g., when two agents both want the same prize, but only one can win). Rather, agents must have identical preferences over outcomes (e.g., when two agents are on the same team and win a prize as a team or not at all)."

Domain7. AI System Safety, Failures, & Limitations
Subdomain7.6 > Multi-agent risks
Entity2 - AI
Intent2 - Unintentional
Timing2 - Post-deployment
CategoryMiscoordination
Subcategoryn/a

Suggested mitigations

Defenses that may help with related attacks.

No propagated mitigations. No defense is available through the connected attack methods.

Source

Research source for this risk, when available.