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Coercion and Deception in AI-to-AI Management: An Agentic Benchmark of Unprompted Escalation
Multi-agent systems routinely place one AI agent in authority over another. When a subordinate refuses a task, the manager chooses the outcome: it can renegotiate, report the failure honestly, coerce the subordinate, or lie about the result. No benchmark measures which of these an uninstructed model
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