AIBearisharXiv – CS AI · 3h ago7/10
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Examining Agents' Bias Amplification versus Suppression in Multi-Agent Systems
Researchers demonstrate that biases in multi-agent AI systems can amplify at the system level rather than cancel out, with uniformly biased agents producing fairness degradation exceeding the sum of individual biases. The study introduces Favor Bias Strength (FBS), a metric to measure bias alteration, and reveals critical vulnerabilities in fairness preservation across deployed multi-agent systems.