Interaction Creates Dynamical AI Behavior Absent in Isolation

As AI agents increasingly interact with each other in real-world deployments, understanding emergent behaviors from these interactions becomes critical. This paper studies what happens when one AI ("boss") issues directives to another ("subordinate") without listening to replies, finding that the subordinate enters an unexpected behavioral state distinct from both its solo behavior and its boss's behavior. This has implications for designing multi-agent AI systems, predicting unintended emergent dynamics in agent hierarchies, and informing safety considerations for deployed AI-AI communication pipelines, such as automated business workflows or agent swarms where message delivery patterns could meaningfully shape collective behavior. Paper: https://arxiv.org/abs/2608.07457