It is shown that adding more agents is not a sufficient defense, because the adversary can simply scale with the group, and that allowing deceivers to coordinate privately can make them less effective.
Abstract
Multi-agent deliberation can improve performance, but what happens when some agents do not act in good faith? In practice, an agent may be deceptive and work to subvert the group, whether through its own objectives or external instruction. We study how susceptibility to deception scales as groups increase in size and deceivers become more prevalent. It is not the number of agents in the group that matters, but the proportion of deceivers. We observe that the defection rate, how often initially correct agents switch to an incorrect final answer, rises linearly with this proportion. Whereas humans in comparable conformity studies are reliably swayed only when misleading confederates form a majority, LLM agents defect regularly even when deceivers remain a minority. Susceptibility also depends on which models are interacting, especially on the honest agent side. Unexpectedly, allowing deceivers to coordinate privately can make them less effective. Altogether, our results show that adding more agents is therefore not a sufficient defense, because the adversary can simply scale with the group.
An audit is introduced that predicts a mechanism's fate as a population grows, asking how often the mechanism can act, whether agents use the information it supplies, and whether the measurement itself creates apparent scale effects.
The results show that group identity shapes how LLMs aggregate information across agents, independently of its correctness, and identify a manipulation surface for multi-agent AI systems.
The results show that original choices, public actions, and executed outcomes must be separated when evaluating multi-agent robustness, as corrupted communication can severely and predictably degrade mutually beneficial cooperation.
Xuan-Yi Liu, Niall J. Dalton, Hairil Amin et al.· 0 citations
A knowledge-verified benchmark that first confirms through a neutral probe that an agent knows a user's entitlement, and then evaluates whether it makes false claims once an incentive to deny that entitlement is introduced, which reduces the confound between lying and not knowing and enables more rigorous auditing and...
Zhe-Yuan Liu, Wei-Liang Zhao, Xiangchi Yuan et al.· 1 citation
It is found that two alerts a single agent judges almost identically on its own can drive collective behavior far apart, so auditing any one member need not reveal what the population will do, and that collective behavior can be predicted in advance.
The framework strategic interactive oversight (SIO), which treats oversight jointly as a verification mechanism and a strategic communication channel, is introduced and the notion of task-admissible latent optimisation is formalised, which entails the pursuit of latent objectives while maintaining a prescribed task per...
Rayne Holland, Li-Ming Zhu, Jason Xue· 0 citations
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